ProEthica Case 7 Ontology
type: Ontology
created: 2026-06-05T09:35:07.200537
title: Use of Artificial Intelligence in Engineering Practice
imports: cases
imports: intermediate

BER Case 90-6
type: NamedIndividual
comment: The Board cited this case to establish historical precedent for the ethical use of computer-assisted drafting and design tools, and to show that the BER has long grappled with questions about new technology in engineering practice, including early references to AI.
was generated by: ProEthica Case 7 Extraction

BER Case 98-3
type: NamedIndividual
comment: The Board cited this case to draw a parallel to Engineer A's use of AI-assisted drafting tools without sufficient competency verification, and to reinforce the principle that technology must not replace or substitute for engineering judgment, while also distinguishing Engineer A as not wholly incompetent unlike the engineer in that case.
was generated by: ProEthica Case 7 Extraction

Case 7 Timeline
type: NamedIndividual
type: TemporalEntity
action count: 10
event count: 8
total elements: 18
synthesis literal: hasTimepoints
synthesis literal: temporalConsistency
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_AI Disclosure Omission for Des
type: NamedIndividual
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_AI Disclosure Omission for Rep
type: NamedIndividual
comment: Because the AI tool adoption directly caused the report generation and its stylistic inconsistencies, concealing the AI's role deceives the client about the true authorship and quality basis of the deliverable, which undermines the trust that professional attribution obligations are designed to protect.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_AI Tool Adoption for Design
type: NamedIndividual
analyzes action: AI Tool Adoption for Design
comment: Using AI for design generation under dual deliverable pressure carries normative weight because the causal chain produces AI-generated design outputs that feed into a review process already shown to be cursory, meaning the absence of a clear fulfillment or violation here reflects a gap in oversight that amplifies the risk of undetected design defects reaching the client.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_AI Tool Adoption for Report
type: NamedIndividual
analyzes action: AI Tool Adoption for Report
comment: Adopting the AI tool for the report fulfils competence obligations by leveraging available technology, but the causal chain shows it directly produces an AI Disclosure Omission, meaning the fulfillment of competence is undermined by a transparency failure that leaves the client and public unaware of how the deliverable was generated.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Client Data Upload to AI
type: NamedIndividual
analyzes action: Client Data Upload to AI
comment: Uploading client data to the AI tool violates confidentiality because it causally produces client data exposure to a third-party system, and this breach is not offset by the downstream report generation benefit, since the client never consented to their proprietary information leaving the engineer's control.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Cursory Design Document Review
type: NamedIndividual
analyzes action: Cursory Design Document Review
comment: The cursory review caused a design defect to be discovered only after submission, which triggered a client revision instruction, meaning the failure to exercise adequate direction and control over the work product directly produced a safety-relevant gap that the responsible charge obligation exists precisely to prevent.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Design Document Submission
type: NamedIndividual
analyzes action: Design Document Submission
comment: Submitting the design document without adequate review or qualification fulfils no protective obligation and instead places a potentially defective design into the project record, meaning the public safety and responsible charge violations are not merely procedural but carry real downstream consequences given that a defect was in fact present.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Draft Report Sealing and Submi
type: NamedIndividual
comment: Sealing and submitting the report gives it the force of a professional certification, so violating credit and attribution obligations at this step matters because it formally commits Engineer A to standing behind a product whose actual origins were misrepresented, compounding the downstream stylistic inconsistency into a documented professional record.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Project Acceptance
type: NamedIndividual
analyzes action: Project Acceptance
comment: Accepting the project within the bounds of competence matters because it establishes the foundational professional commitment to public safety, and any downstream failures in design review or AI tool use trace back to whether the engineer had the genuine capability to oversee the full scope of work from the outset.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

CausalLink_Thorough Report Review
type: NamedIndividual
analyzes action: Thorough Report Review
comment: Conducting a thorough review fulfils both direction and control over the work product and competence obligations, and this matters causally because the report stylistic inconsistency produced by AI generation and draft sealing could have been caught and corrected before submission, making the review the critical intervention point for maintaining professional accountability.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Conclusion_1
type: EthicalConclusion
type: NamedIndividual
answers question1: 1
conclusion number: 1
conclusion text: Engineer A's use of AI in report writing was partly ethical, and partly unethical.
conclusion type: board_explicit
extraction reasoning: Parsed from imported case text (no LLM)
was generated by: ProEthica Case 7 Extraction

Conclusion_101
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
answers question1: 101
answers question2: 1
cited provision1: II.1.c.
conclusion number: 101
conclusion text: Beyond the Board's finding that Engineer A's use of AI in report writing was partly ethical and partly unethical, the most independently significant ethical breach was not the use of AI itself but rather Engineer A's upload of Client W's confidential site data and groundwater monitoring information into an open-source AI platform without obtaining Client W's prior consent. This act violated Code Section II.1.c regardless of the quality of the resulting report or the thoroughness of Engineer A's subsequent review. The confidentiality breach is analytically separable from the competence and disclosure questions: even if Engineer A had produced a flawless, fully attributed report, the unauthorized exposure of proprietary client data to an open-source system with unknown data retention and third-party access policies would remain an independent ethical violation. The Board's conclusion that the report submission was partly ethical should therefore be understood as resting on a foundation that was itself compromised before Engineer A wrote a single word of review commentary.
conclusion type: analytical_extension
was generated by: ProEthica Case 7 Extraction

Conclusion_102
type: EthicalConclusion
type: NamedIndividual
cites provision: II 2 a
cites provision: I 2
answers question1: 102
answers question2: 2
cited provision1: I.2.
cited provision2: II.2.a.
conclusion number: 102
conclusion text: The Board's finding that AI-assisted drafting tools are not unethical per se must be qualified by a competence threshold that Engineer A failed to meet before deploying those tools on a live client engagement. Code Sections I.2 and II.2.a require engineers to undertake assignments only when qualified by education or experience in the specific technical field involved. This obligation extends to the tools an engineer selects to perform that work: adopting AI drafting software that was entirely new to the market, with which Engineer A had no prior experience, for the purpose of generating sealed engineering design documents, is not ethically equivalent to using a mature, well-understood software application. The analogy the Board drew between AI tools and conventional engineering software—such as CAD or finite element analysis programs—understates the difference in verification burden. Established engineering software produces deterministic outputs that engineers can validate against known benchmarks; large-language-model and AI-drafting outputs are probabilistic, context-sensitive, and capable of producing plausible-looking but technically incorrect results, as the design deficiencies in this case demonstrated. Engineer A's lack of tool-specific proficiency therefore created a foreseeable competence gap that the cursory design review did not close, and the Board's permissive conclusion about AI tool use should not be read to excuse adoption of unfamiliar AI tools without a minimum threshold of tool-specific qualification.
conclusion type: analytical_extension
was generated by: ProEthica Case 7 Extraction

Conclusion_103
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 103
answers question2: 3
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 103
conclusion text: The Board's conclusion that Engineer A had no professional or ethical obligation to disclose AI use in the report—by analogy to conventional engineering software—does not adequately account for the distinct authorship and attribution dimensions raised by large-language-model text generation. Code Section III.9 requires engineers to give credit for engineering work to those to whom credit is due. When an AI system generates the substantive prose of a professional report, the question of authorship credit is not merely a stylistic preference but a professional representation about the origin of the intellectual work product. Client W's observation that the report read as if written by two different authors is not a trivial aesthetic complaint: it is evidence that the AI-generated sections were perceptibly distinct in character from Engineer A's own writing, which means the report implicitly represented a unified human authorship that did not exist. This implicit misrepresentation, even absent an affirmative false statement, is in tension with Code Sections I.5 and III.3, which prohibit deceptive acts and conduct that deceives the public. The Board's non-disclosure conclusion should therefore be treated as contingent on circumstances where AI involvement is not perceptible and does not create a false impression of authorship—conditions that were not met in this case.
conclusion type: analytical_extension
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_104
type: EthicalConclusion
type: NamedIndividual
cites provision: III 8 a
cites provision: II 2 b
cites provision: I 1
answers question1: 104
answers question2: 2
cited provision1: I.1.
cited provision2: II.2.b.
cited provision3: III.8.a.
conclusion number: 104
conclusion text: The Board's partial ethical approval of Engineer A's report work—grounded in Engineer A's thorough cross-checking—should not be extended to the engineering design documents, where the standard of review was categorically different and the consequences of error were categorically more serious. For the report, Engineer A verified factual claims against journal articles and checked phrasing for originality; this is a form of substantive intellectual engagement with the AI output. For the design documents, Engineer A conducted only a cursory review and adjusted certain elements for site-specific conditions, yet affixed a professional seal. Code Section II.2.b prohibits engineers from signing plans dealing with subject matter in which they lack competence, and the act of sealing is a public representation that the engineer has exercised responsible charge over the work. A cursory review of AI-generated plans that contained misaligned dimensions and omitted safety features required by local regulations does not constitute responsible charge; it constitutes a delegation of engineering judgment to an unqualified automated system. The seal therefore misrepresented the degree of professional oversight actually applied, creating a risk to public safety that the Board correctly identified as an ethical violation but that deserves emphasis as the most serious failure in this case.
conclusion type: analytical_extension
was generated by: ProEthica Case 7 Extraction

Conclusion_105
type: EthicalConclusion
type: NamedIndividual
cites provision: II 2 a
cites provision: I 2
answers question1: 104
answers question2: 402
cited provision1: I.2.
cited provision2: II.2.a.
conclusion number: 105
conclusion text: A dimension the Board did not address is the structural role that Engineer B's retirement played in creating the conditions for Engineer A's ethical failures. Engineer A's loss of mentorship and quality assurance review was not merely a personal inconvenience but a foreseeable competence gap that Engineer A was obligated to address through affirmative professional measures before accepting or continuing sealed deliverable work. The NSPE Code's competence obligations are not satisfied by the historical fact of prior mentored experience; they require that an engineer be currently qualified to perform the work independently or with appropriate oversight at the time of performance. Engineer A's response to the mentorship gap—unilaterally adopting an unfamiliar open-source AI tool as a functional substitute for peer review—was not a professionally adequate adaptation. Ethically sound alternatives would have included engaging a qualified substitute reviewer, limiting the scope of accepted work to tasks within Engineer A's independent competence, or declining the engagement pending identification of appropriate oversight. The Board's analysis would benefit from explicitly recognizing that the mentor loss was not a mitigating circumstance but a triggering condition that elevated Engineer A's professional obligations rather than relaxing them.
conclusion type: analytical_extension
was generated by: ProEthica Case 7 Extraction

Conclusion_106
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: I 1
cites provision: I 5
answers question1: 3
answers question2: 306
answers question3: 202
cited provision1: I.1.
cited provision2: I.5.
cited provision3: III.3.
conclusion number: 106
conclusion text: The Board's discretionary approach to AI disclosure—treating it as ethically favored but not categorically required absent contractual obligation—produces an unstable standard that is likely to erode client trust and professional accountability as AI tools become more capable and more widely used. From a consequentialist perspective, a universal norm requiring disclosure whenever AI plays a substantial role in generating a sealed work product would produce better outcomes across three dimensions: it would enable clients to make informed decisions about the work product they are receiving; it would create professional incentives for engineers to maintain genuine responsible charge rather than delegating judgment to AI systems; and it would allow the profession to develop empirical knowledge about where AI-assisted engineering succeeds and fails. The Board's analogy to conventional engineering software is likely to become increasingly untenable as AI systems move from computation tools to generative authorship tools, and the profession would benefit from proactively establishing disclosure norms before the absence of such norms produces more serious public safety failures than the design deficiencies observed in this case.
conclusion type: analytical_extension
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_2
type: EthicalConclusion
type: NamedIndividual
answers question1: 2
conclusion number: 2
conclusion text: The use of AI-assisted drafting tools by Engineer A was not unethical per se.
conclusion type: board_explicit
extraction reasoning: Parsed from imported case text (no LLM)
was generated by: ProEthica Case 7 Extraction

Conclusion_201
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
answers question1: 101
answers question2: 301
answers question3: 302
cited provision1: II.1.c.
conclusion number: 201
conclusion text: In response to Q101: Engineer A's upload of Client W's confidential site data and groundwater monitoring information into an open-source AI platform without obtaining Client W's prior consent constitutes an independent and serious breach of the client confidentiality obligation under Code Section II.1.c. Open-source AI platforms, by their nature, may retain, process, or expose input data in ways that fall outside the engineer's control, and Engineer A's unfamiliarity with the tool's full functionality compounds this risk. This breach is analytically separable from the quality of Engineer A's subsequent review of the report: even if the report were technically flawless, the act of exposing confidential client data to an uncontrolled third-party platform without consent is independently unethical. The breach does not become retroactively permissible because no confirmed data leak occurred; the obligation under II.1.c is triggered by unauthorized disclosure, not by demonstrated harm. Accordingly, the submission of the report is rendered ethically deficient on confidentiality grounds alone, independent of any assessment of report quality or AI disclosure obligations.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_202
type: EthicalConclusion
type: NamedIndividual
cites provision: II 2 a
cites provision: I 2
answers question1: 102
answers question2: 2
cited provision1: I.2.
cited provision2: II.2.a.
conclusion number: 202
conclusion text: In response to Q102: Engineer A did not satisfy the competence requirement under Code Sections I.2 and II.2.a before adopting the AI-assisted drafting tool for a live client engagement. The tool was new to the market, Engineer A had no prior experience with it, and Engineer A's own unfamiliarity with its full functionality is explicitly acknowledged in the case facts. Competence under the Code is not limited to domain expertise in environmental engineering; it extends to the tools and methods an engineer employs to produce sealed deliverables. Using an untested, unfamiliar tool on a live engagement — particularly one generating design documents that would bear a professional seal — without any prior validation, pilot testing, or independent verification protocol falls below the standard of care the Code demands. At minimum, before relying on AI-assisted drafting software for sealed deliverables, an engineer should: (1) conduct independent validation of the tool's outputs against known correct solutions; (2) understand the tool's known failure modes and limitations; and (3) establish a verification protocol sufficient to catch errors the tool is known to produce. Engineer A did none of these things for the design documents, and the resulting deficiencies — misaligned dimensions and omitted safety features — are a foreseeable consequence of that failure.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_203
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 103
answers question2: 3
answers question3: 301
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 203
conclusion text: In response to Q103: Engineer A's omission of any disclosure about AI authorship, in the context of a report that Client W independently observed 'read as if written by two different authors,' constitutes a deceptive act or misrepresentation of authorship under Code Sections I.5 and III.3, independent of whether the factual content of the report was accurate. Deception under the Code does not require an affirmative false statement; it encompasses conduct that creates a false impression in the mind of the recipient. By submitting the report under their professional seal without any attribution of AI involvement, Engineer A implicitly represented the work as their own original professional writing. The stylistic inconsistency noticed by Client W is direct evidence that the AI's contribution was perceptible and material — not merely a background tool analogous to spell-check or grammar software. When a client can detect that a work product appears to have multiple authors, and the engineer withholds the explanation that one of those apparent 'authors' is an AI system, the omission crosses from permissible non-disclosure into functional misrepresentation. This conclusion is independent of the Board's finding that AI-assisted drafting is not unethical per se; the ethical problem here is not the use of AI but the concealment of its perceptible and substantial role.
conclusion type: question_response
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_204
type: EthicalConclusion
type: NamedIndividual
cites provision: II 2 a
cites provision: II 2 b
cites provision: I 2
answers question1: 104
answers question2: 402
cited provision1: I.2.
cited provision2: II.2.a.
cited provision3: II.2.b.
conclusion number: 204
conclusion text: In response to Q104: Engineer A's loss of Engineer B as mentor and quality assurance reviewer created a foreseeable and material competence gap that Engineer A was ethically obligated to address through means other than the unilateral adoption of an unfamiliar AI tool. The Code's competence obligations under Sections I.2 and II.2.a do not permit an engineer to substitute an untested technology for the human oversight and peer review that previously ensured the adequacy of their work product. Engineer A had several ethically permissible alternatives: engaging a substitute peer reviewer with relevant expertise, limiting the scope of accepted work to deliverables within Engineer A's independent capacity, or declining the engagement pending identification of adequate quality assurance support. Instead, Engineer A accepted both a complex technical report and engineering design documents — deliverables that would bear a professional seal — while simultaneously losing their primary quality assurance resource and adopting an unfamiliar AI tool as a replacement. This compounded the risk rather than mitigating it. The design deficiencies that resulted — misaligned dimensions and omitted safety features — are a direct and foreseeable consequence of this failure to address the competence gap through appropriate professional means.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_205
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 201
answers question2: 301
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 205
conclusion text: In response to Q201: A genuine and irresolvable tension exists between the principle of technical accuracy achieved through thorough review and the principle of honest representation of authorship and process. The Board's finding that Engineer A's thorough cross-checking of the report satisfied the competence obligation addresses only the output quality dimension of the ethical analysis. It does not resolve — and in fact obscures — the separate question of whether Engineer A misrepresented the nature and origin of the work product. An engineer may produce a technically accurate report while simultaneously creating a false impression about who or what authored it. When these two obligations cannot be simultaneously fulfilled — that is, when using AI produces a technically adequate product but concealing AI use constitutes deception — the obligation of candor and non-deception should take precedence, because the Code's prohibitions on deceptive acts under Sections I.5 and III.3 are categorical in character and do not yield to consequentialist justifications based on output quality. Technical accuracy is a necessary but not sufficient condition for ethical compliance.
conclusion type: question_response
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_206
type: EthicalConclusion
type: NamedIndividual
cites provision: III 8 a
cites provision: II 2 b
cites provision: I 1
answers question1: 203
answers question2: 2
answers question3: 305
cited provision1: I.1.
cited provision2: II.2.b.
cited provision3: III.8.a.
conclusion number: 206
conclusion text: In response to Q203: A fundamental conflict exists between the act of affixing a professional seal and the adequacy of the oversight that seal is intended to certify. The professional seal is not merely a formality; under Code Section II.2.b and state engineering seal law, it represents the engineer's certification that they exercised responsible charge over the work. Engineer A's cursory review of AI-generated design documents — which failed to detect misaligned dimensions and omitted safety features required by local regulations — means that the seal was affixed to documents that Engineer A had not adequately reviewed. The seal therefore functioned not as a certification of responsible charge but as a misrepresentation of it. This is among the most serious ethical failures in the case, because the seal is the primary mechanism by which the public and clients rely on the engineer's professional judgment. To prevent this failure mode, procedural safeguards for sealing AI-generated design documents should include: (1) a systematic, element-by-element verification of all dimensions and specifications against source data; (2) explicit cross-checking of all design features against applicable local, state, and federal regulatory requirements; and (3) documented evidence of the review process sufficient to demonstrate responsible charge. A cursory review is categorically insufficient when AI has generated the primary content of sealed design documents.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_207
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: II 1 c
cites provision: I 5
answers question1: 301
answers question2: 302
cited provision1: I.5.
cited provision2: II.1.c.
cited provision3: III.3.
conclusion number: 207
conclusion text: In response to Q301 and Q302: From a deontological perspective, Engineer A failed two categorical duties simultaneously. First, the duty of candor to Client W was breached by omitting disclosure of AI involvement in both the report and the design documents. A Kantian analysis requires asking whether the maxim 'engineers may omit disclosure of AI authorship when the output is technically adequate' could be universalized without contradiction. It cannot: if all engineers concealed AI involvement whenever they judged the output satisfactory, clients would be systematically deprived of information material to their ability to evaluate the work product and the professional relationship, undermining the very trust on which professional licensure depends. Second, the duty to protect client confidentiality was breached by uploading Client W's proprietary data to an open-source platform without consent. This duty is categorical under Code Section II.1.c and does not admit of exceptions based on the engineer's assessment of likely harm. The absence of a confirmed data breach is irrelevant to the deontological analysis: the wrong consists in the unauthorized act of disclosure itself, not in its consequences. Both violations are independently sufficient to render Engineer A's conduct unethical under a deontological framework, and they compound each other in a way that reflects a broader pattern of prioritizing personal convenience over professional obligation.
conclusion type: question_response
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_208
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
cites provision: II 2 a
cites provision: I 1
cites provision: I 2
answers question1: 303
cited provision1: I.1.
cited provision2: I.2.
cited provision3: II.1.c.
cited provision4: II.2.a.
conclusion number: 208
conclusion text: In response to Q303: From a consequentialist perspective, the aggregate outcomes of Engineer A's AI-assisted workflow produce a net harm that substantially outweighs the efficiency gains sought. The benefits were limited to time savings in drafting and the ability to meet deliverable deadlines without a quality assurance reviewer. The harms include: (1) exposure of Client W's confidential site and groundwater data to an uncontrolled open-source platform, creating ongoing and unquantifiable data security risk; (2) submission of design documents containing misaligned dimensions and omitted safety features required by local regulations, creating direct public safety risk and requiring costly revision; (3) erosion of Client W's trust, evidenced by the client's observation that the report appeared to have two authors and by the client's instruction to revise the design documents; and (4) the broader systemic harm of normalizing inadequate AI oversight in professional engineering practice. The efficiency gain from AI adoption is only ethically defensible when the engineer has sufficient familiarity with the tool to ensure that the output meets professional standards. Here, Engineer A's unfamiliarity with the tool, combined with a cursory review of the design documents, meant that the efficiency gain was achieved by transferring risk to the client and the public rather than by genuinely improving productivity.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_209
type: EthicalConclusion
type: NamedIndividual
cites provision: III 8 a
cites provision: II 2 a
cites provision: II 2 b
cites provision: I 2
answers question1: 304
answers question2: 305
cited provision1: I.2.
cited provision2: II.2.a.
cited provision3: II.2.b.
cited provision4: III.8.a.
conclusion number: 209
conclusion text: In response to Q304 and Q305: From a virtue ethics perspective, Engineer A's conduct in both the report and design document contexts falls short of the professional integrity and responsible stewardship that the public and clients are entitled to expect from a licensed engineer. A virtuous engineer, confronted with the loss of a trusted mentor and quality assurance reviewer, would respond by seeking alternative qualified oversight — not by substituting an unfamiliar, unvalidated AI tool for human professional judgment. The choice to adopt an open-source AI drafting tool with no prior experience, on a live client engagement involving sealed deliverables, reflects a disposition toward self-reliance that is admirable in principle but reckless in execution when the engineer lacks the competence to validate the tool's outputs. More seriously, Engineer A's decision to affix a professional seal to AI-generated design documents after only a cursory review reflects a self-serving shortcut that undermines the moral foundation of professional licensure. The seal exists to assure the public that a qualified professional has exercised genuine judgment over the work. Affixing it to documents that Engineer A had not adequately reviewed — and that contained detectable errors — is not merely a procedural lapse; it is a betrayal of the public trust that the seal is designed to embody. A virtuous engineer would have either declined to seal the documents until a thorough review was complete or sought qualified assistance before submission.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_210
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 306
answers question2: 202
answers question3: 3
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 210
conclusion text: In response to Q306: A universal norm requiring engineers to disclose AI involvement whenever AI plays a substantial role in generating a work product would produce better outcomes for public safety, client trust, and the engineering profession than the current discretionary approach endorsed by the Board. The Board's analogy between AI tools and conventional engineering software — such as CAD or structural analysis programs — is imperfect in a critical respect: conventional engineering software executes deterministic calculations based on engineer-defined inputs, while large language model AI generates probabilistic text and design content that may contain errors, hallucinations, or stylistic artifacts that are not traceable to any specific engineer input. This fundamental difference in the nature of the tool's contribution justifies a different disclosure standard. Mandatory disclosure of substantial AI involvement would: (1) enable clients to make informed decisions about the work product and the professional relationship; (2) create accountability incentives that encourage engineers to conduct more rigorous reviews of AI-generated content; (3) allow the profession to develop empirical data about AI tool reliability across different application domains; and (4) prevent the kind of functional deception illustrated by this case, where a client independently detected AI involvement through stylistic inconsistency. The current discretionary approach, by contrast, permits concealment of AI involvement as long as the engineer judges the output to be adequate — a standard that is self-assessed, unverifiable, and inconsistent with the Code's broader commitment to transparency and public trust.
conclusion type: question_response
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_211
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
cites provision: II 2 a
cites provision: I 2
answers question1: 401
answers question2: 101
answers question3: 3
cited provision1: II.1.c.
cited provision2: I.2.
cited provision3: II.2.a.
conclusion number: 211
conclusion text: In response to Q401: Prior disclosure to Client W and explicit written consent for uploading confidential site data to an open-source AI platform would have resolved the confidentiality breach under Code Section II.1.c and would have substantially altered the ethical assessment of the engagement. Had Engineer A disclosed the intended use of open-source AI software before beginning work — including the fact that confidential client data would be input into the platform — Client W would have had the opportunity to evaluate the data security implications, negotiate alternative arrangements, or withhold consent. This would have either eliminated the confidentiality violation (if consent were granted) or prevented the data exposure entirely (if consent were withheld). However, prior consent for data upload would not have resolved all ethical violations: the design document deficiencies arising from inadequate review and the responsible charge failures would have persisted regardless of disclosure. The counterfactual therefore supports the conclusion that disclosure and consent are necessary but not sufficient conditions for ethical compliance — they address the confidentiality and transparency dimensions of the analysis but do not substitute for the competence and responsible charge obligations that Engineer A independently failed to satisfy.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_212
type: EthicalConclusion
type: NamedIndividual
cites provision: II 2 a
cites provision: II 2 b
cites provision: I 2
answers question1: 402
answers question2: 104
answers question3: 2
cited provision1: I.2.
cited provision2: II.2.a.
cited provision3: II.2.b.
conclusion number: 212
conclusion text: In response to Q402: Had Engineer A engaged a qualified substitute reviewer to replace Engineer B's mentorship and quality assurance role before submitting either the report or the design documents, the design deficiencies, regulatory omissions, and responsible charge failures identified in this case would very likely have been prevented. A competent peer reviewer would have been expected to detect misaligned dimensions and omitted safety features — errors that Client W, a non-engineer client, was able to identify upon review. The presence of qualified peer review would also have satisfied the spirit of the responsible charge obligation under Code Section II.2.b, because the engineer's judgment would have been supplemented — rather than replaced — by another qualified professional. Under those circumstances, AI use would have remained ethically permissible: the tool would have served its appropriate function as a drafting aid subject to meaningful professional oversight, rather than as a substitute for the professional judgment that Engineer A lacked the independent capacity to fully exercise. This counterfactual reinforces the conclusion that the ethical failures in this case are not primarily attributable to AI use per se, but to the absence of adequate professional oversight — a gap that Engineer A was obligated to fill through qualified human review rather than through technological substitution.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_213
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
cites provision: II 2 b
cites provision: I 1
answers question1: 403
answers question2: 1
answers question3: 2
cited provision1: II.2.b.
cited provision2: I.1.
cited provision3: II.1.c.
conclusion number: 213
conclusion text: In response to Q403: If Engineer A had applied the same level of thorough, cross-referenced review to the AI-generated design documents as they applied to the AI-generated report — verifying all dimensions against source data, checking safety feature requirements against local regulations, and reconciling site-specific conditions — the Board's finding of an ethical violation for failure to maintain responsible charge over the design documents would not have been warranted on review-adequacy grounds. The Board's distinction between the report (ethical) and the design documents (unethical) rests substantially on the difference in review quality: thorough review for the report, cursory review for the design documents. A thorough review of the design documents that successfully identified and corrected all misaligned dimensions and omitted safety features before submission would have satisfied the responsible charge obligation under Code Section II.2.b. However, this counterfactual does not eliminate all ethical concerns: the confidentiality breach from uploading client data to an open-source platform and the non-disclosure of AI involvement would have persisted regardless of review quality. The counterfactual therefore isolates the responsible charge violation as a curable deficiency — one that adequate review could have remedied — while confirming that the confidentiality and transparency violations are structural features of Engineer A's approach that no amount of post-generation review can retroactively cure.
conclusion type: question_response
was generated by: ProEthica Case 7 Extraction

Conclusion_214
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 404
answers question2: 3
answers question3: 103
answers question4: 301
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 214
conclusion text: In response to Q404: Voluntary disclosure of AI tool use in both the report and the design documents at the time of submission would have materially altered the client's trust, the professional relationship, and the Board's ethical assessment regarding the disclosure obligation. Client W's observation that the report 'read as if written by two different authors' demonstrates that the absence of disclosure was already functionally deceptive: the client perceived an anomaly that had a specific explanation — AI authorship of the introduction — that Engineer A withheld. Had Engineer A proactively disclosed the AI tools used and the extent of AI involvement, Client W would have had a factual explanation for the stylistic inconsistency, would have been positioned to make an informed judgment about the adequacy of Engineer A's review, and would have retained the ability to request additional assurances or alternative approaches. Such disclosure would have aligned Engineer A's conduct with the Code's requirements of candor under Sections I.5 and III.3 and would have transformed the AI use from a concealed practice into a transparent professional choice subject to client evaluation. The Board's conclusion that disclosure is not ethically required as a general matter does not address the specific circumstance where non-disclosure is already functionally deceptive — a circumstance this case presents directly. In that specific circumstance, the ethical obligation to avoid deception independently requires disclosure, regardless of whether a general disclosure norm exists.
conclusion type: question_response
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_3
type: EthicalConclusion
type: NamedIndividual
answers question1: 3
conclusion number: 3
conclusion text: Similar to other software used in the design or detailing process, Engineer A has no professional or ethical obligation to disclose AI use to Client W (unless such disclosure is required under Engineer A’s contract with Client W).
conclusion type: board_explicit
extraction reasoning: Parsed from imported case text (no LLM)
was generated by: ProEthica Case 7 Extraction

Conclusion_301
type: EthicalConclusion
type: NamedIndividual
cites provision: III 3
cites provision: III 9
cites provision: I 5
answers question1: 201
answers question2: 202
answers question3: 1
answers question4: 3
cited provision1: I.5.
cited provision2: III.3.
cited provision3: III.9.
conclusion number: 301
conclusion text: The most consequential unresolved tension in this case is between Engineer A AI Report Competence and Engineer A AI Authorship Concealment. The Board found that Engineer A's thorough cross-checking of the report satisfied the competence standard, effectively decoupling technical accuracy from the question of authorship transparency. However, this resolution is incomplete: an engineer can produce a factually correct work product while simultaneously misrepresenting—by omission—the nature and origin of that product. Client W's observation that the report read as if written by two different authors demonstrates that the concealment was not merely theoretical; it was perceptible and materially affected the client's understanding of what they received. The Board's implicit prioritization of output quality over process transparency teaches that, under the current framework, competence obligations can be satisfied independently of candor obligations. This case suggests that framework is insufficient: where AI plays a substantial authorship role and that role is perceptible to the client, the principle of Engineer A AI Disclosure Transparency should be treated as a corollary of competence rather than a separate, discretionary consideration. Competence and candor should be jointly necessary conditions for ethical submission of a sealed work product.
conclusion type: principle_synthesis
synthesis literal: citationProvenance
was generated by: ProEthica Case 7 Extraction

Conclusion_302
type: EthicalConclusion
type: NamedIndividual
cites provision: III 8 a
cites provision: II 2 b
cites provision: I 1
answers question1: 203
answers question2: 2
answers question3: 305
cited provision1: I.1.
cited provision2: II.2.b.
cited provision3: III.8.a.
conclusion number: 302
conclusion text: The tension between Engineer A Responsible Charge Design Failure and Engineer A Seal on AI Design Documents exposes a structural vulnerability in how professional sealing norms interact with AI-generated outputs. The professional seal is the legal and ethical mechanism by which an engineer certifies responsible charge—meaning the engineer has exercised sufficient judgment, direction, and verification over the work product to stand behind it publicly. In this case, Engineer A's cursory review of AI-generated design documents that contained misaligned dimensions and omitted safety features required by local regulations means the seal was affixed to a product over which responsible charge had not, in fact, been exercised. The seal did not confirm oversight; it obscured its absence. This tension was not resolved by the Board so much as it was exposed: the Board's finding of an ethical violation for the design documents implicitly acknowledges that sealing AI-generated work after only a high-level review fails the responsible charge standard. The case teaches that the principle of Engineer A Seal on AI Design Documents cannot be treated as equivalent to sealing conventionally produced documents unless the engineer's review is substantively equivalent in depth and rigor to what would have been required had the engineer produced the documents without AI assistance. The seal's moral and legal weight demands that AI-assisted design receive verification proportionate to the risk of the output, not merely a review proportionate to the engineer's familiarity with the tool.
conclusion type: principle_synthesis
was generated by: ProEthica Case 7 Extraction

Conclusion_303
type: EthicalConclusion
type: NamedIndividual
cites provision: II 1 c
cites provision: II 2 a
cites provision: I 2
answers question1: 204
answers question2: 101
answers question3: 102
answers question4: 104
answers question5: 202
cited provision1: I.2.
cited provision2: II.1.c.
cited provision3: II.2.a.
conclusion number: 303
conclusion text: The interaction among Engineer A Client Data AI Upload, Engineer A Professional Competence AI Use, and Engineer A Mentor Loss Response reveals that what appears on the surface to be a single decision—adopting an AI tool—was in fact a compounded ethical failure involving three independently assessable breaches that reinforced one another. First, uploading Client W's confidential site data and groundwater monitoring information into an open-source AI platform without prior consent violated the client confidentiality principle regardless of whether any data breach materialized, because the obligation under Code Section II.1.c is triggered by unauthorized disclosure, not by demonstrated harm. Second, adopting an AI drafting tool that was entirely new to the market with no prior experience, and applying it to sealed deliverables for a live client engagement, violated the competence principle because Engineer A could not evaluate the tool's accuracy, limitations, or failure modes before relying on it. Third, Engineer A's response to the loss of Engineer B as mentor and quality assurance reviewer—substituting an unfamiliar AI tool rather than seeking a qualified peer reviewer, limiting scope, or declining work beyond independent capacity—violated the principle of Engineer A Mentor Loss Response, which required Engineer A to address the competence gap through means that preserved rather than compounded professional risk. The case teaches that when multiple principles are simultaneously in tension, the ethical analysis must treat each breach as independently actionable rather than allowing a finding of compliance on one dimension—such as the quality of the report review—to offset or absorb violations on others. Engineer A AI Tool Non-Disclosure Report and Engineer A AI Disclosure Transparency cannot be resolved by analogy to conventional software tools when the tool in question is unfamiliar, open-source, and processing confidential client data, because that analogy assumes …
conclusion type: principle_synthesis
was generated by: ProEthica Case 7 Extraction

DP1
type: DecisionPoint
type: NamedIndividual
decision point id: DP1
decision question: Should Engineer A (and Engineer B as mentor) proactively disclose to Client W that AI tools were used to generate portions of the report and design, or treat AI as an internal drafting tool requiring no separate client notification?
focus: Engineer B Mentor Engineer and Engineer A failed to disclose to Client W that AI tools were used in preparing the environmental report and design documents. The board must determine whether engineers are obligated to proactively disclose AI tool usage and AI-generated content to the client before submission, or whether existing professional review and sealing practices are sufficient.
option1: Proactively inform Client W that AI tools were used to generate portions of the report and design, identify which sections were AI-assisted, and describe the verification steps taken before sealing.
option2: Treat AI as an internal production tool equivalent to CAD or spreadsheet software, relying on the engineer's professional seal to represent full responsibility for the work product without separate disclosure of the tools used to produce it.
option3: Document AI tool usage in the internal project file and quality assurance records without providing a separate client-facing disclosure, on the basis that tool-level documentation satisfies professional record-keeping obligations without requiring client notification.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP10
type: DecisionPoint
type: NamedIndividual
decision point id: DP10
decision question: Should Engineer B limit involvement to a cursory review of Engineer A's AI-generated design documents, or must Engineer B provide substantive mentorship and technical oversight sufficient to close the competence gap and ensure regulatory safety compliance?
focus: Engineer B, acting as mentor, faces a decision about the adequacy of oversight provided to Engineer A on a project where AI tools are being used extensively and Engineer A has limited competence in AI-assisted design. The question is whether Engineer B's cursory review of design documents satisfies the mentorship and regulatory safety compliance obligations.
option1: Conduct a substantive, targeted review of the AI-generated design documents focused specifically on the areas where Engineer A has demonstrated basic proficiency, including AI output verification and safety feature compliance, providing direct corrective guidance before Engineer A seals the documents.
option2: Perform a high-level review of the design documents for obvious errors and general conformance, treating the mentorship role as advisory and leaving detailed technical verification to Engineer A as the responsible sealing engineer.
option3: Formally notify project leadership that Engineer A's proficiency in AI-assisted design is insufficient for the scope of work without additional support, recommend reassignment of design responsibility or engagement of a specialist, and decline to provide a review that would imply adequate oversight has been achieved.
role label: Engineer B Mentor Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP11
type: DecisionPoint
type: NamedIndividual
decision point id: DP11
decision question: Should Engineer A conduct a full independent technical review of AI-generated design documents before sealing them, or apply standard QA protocols treating AI output as equivalent to conventional drafting tools?
focus: Engineer A sealed design documents produced largely by AI without exercising responsible charge, omitting required safety features. The core question is whether Engineer A should have conducted a thorough independent technical review before sealing, or whether applying standard QA protocols to AI-generated design outputs was sufficient.
option1: Perform a complete, line-by-line independent technical review of all AI-generated design documents, verifying safety features, code compliance, and design integrity before sealing, regardless of time or resource constraints.
option2: Apply the same QA review process used for conventionally drafted documents, treating AI output as equivalent to CAD-generated drawings and relying on standard checklist-based review before sealing.
option3: Conduct a targeted independent review of safety-critical design elements with a qualified peer reviewer while applying standard QA protocols to non-safety-critical portions, acknowledging the limits of solo AI output verification.
role label: Engineer A
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP12
type: DecisionPoint
type: NamedIndividual
decision point id: DP12
decision question: Should Engineer A fully disclose AI tool usage to the client and apply heightened verification to AI-generated report and design outputs, or treat AI as an internal drafting tool requiring only standard review and no separate disclosure?
focus: Engineer A used AI tools to generate both a technical report and design documents without disclosing AI involvement to the client or mentor, and without adequately verifying AI-generated outputs. The question is whether Engineer A had an obligation to disclose AI tool usage and verify outputs to a higher standard given the circumstances.
option1: Proactively inform the client that AI tools were used in producing the report and design documents, identify AI-generated sections, and apply a more rigorous verification standard to AI outputs than would be applied to conventionally produced work.
option2: Use AI tools as internal productivity aids equivalent to CAD or spreadsheet software, applying standard QA review without separate client disclosure, on the basis that the engineer remains professionally responsible for the final sealed product.
option3: Note AI tool usage in project documentation and methodology sections of the report without a separate client notification, following existing firm software disclosure policy and relying on the client to inquire further if desired.
role label: Engineer A
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP13
type: DecisionPoint
type: NamedIndividual
decision point id: DP13
decision question: Should Engineer A seek alternative mentorship or supervisory support after losing access to a mentor, or continue the project independently given existing competence in the domain?
focus: Engineer A lost access to a mentor mid-project and continued work without seeking alternative supervision or guidance, despite having only basic proficiency in several critical areas including responsible charge verification and AI direction control for design. The question is whether Engineer A should have sought alternative mentorship or paused work rather than proceeding independently.
option1: Pause work on tasks requiring responsible charge and AI oversight, and actively seek a qualified supervising engineer or peer reviewer before proceeding, acknowledging the gap created by the mentor's departure.
option2: Continue project work limited strictly to tasks within Engineer A's demonstrated competence, deferring or flagging tasks requiring higher-level oversight until a replacement mentor or supervisor is identified.
option3: Continue the full scope of project work independently, relying on AI tools to supplement the guidance previously provided by the mentor, on the basis that advanced domain competence and AI assistance together constitute adequate professional judgment.
role label: Engineer A
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP14
type: DecisionPoint
type: NamedIndividual
decision point id: DP14
decision question: Should Engineer A proactively disclose AI tool usage to the client and conduct independent verification of all AI-generated design and report content before sealing and submitting deliverables, or is it sufficient to apply standard QA protocols without separate disclosure?
focus: Engineer A used an AI tool to generate substantial portions of both the design documents and the project report without disclosing this to the client, without maintaining adequate direction and control over AI outputs in the design phase, and without verifying AI-generated design content before sealing. Multiple obligations related to disclosure, responsible charge, and design verification remain unmet. The core tension is whether Engineer A must proactively disclose AI involvement and conduct independent verification before sealing and submitting deliverables, or whether existing QA practices and professional judgment are sufficient.
option1: Proactively inform the client of AI tool involvement in both the design and report deliverables, conduct independent technical verification of all AI-generated content before sealing, and correct any safety or technical deficiencies identified during review.
option2: Treat the AI tool as equivalent to conventional engineering software such as CAD or finite element analysis programs, applying the firm's standard quality assurance protocols without issuing a separate disclosure to the client, on the basis that method selection is an internal professional judgment.
option3: Acknowledge AI tool usage within the project report's methodology section and design document notes without a separate client notification, and apply enhanced verification only to safety-critical design elements while relying on domain expertise for remaining outputs.
role label: Engineer A
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP2
type: DecisionPoint
type: NamedIndividual
decision point id: DP2
decision question: Should Engineer A refrain from uploading Client W's confidential site and groundwater data into open-source AI platforms, or is use of such platforms permissible when the engineer exercises professional judgment over the outputs?
focus: Engineer A uploaded Client W's confidential site data and groundwater monitoring information into open-source AI software, exposing that data to a third-party platform outside the protected professional relationship. The board must determine whether this action violated the engineer's confidentiality obligation to the client and what standard of care applies when using AI tools that process client data.
option1: Decline to input Client W's confidential site and groundwater data into any open-source AI platform, instead using AI tools only with anonymized or non-confidential data, or using enterprise AI platforms with contractual data protection agreements.
option2: Seek explicit written authorization from Client W before uploading any confidential project data to AI platforms, disclosing the platform's data handling practices and allowing the client to make an informed decision about acceptable risk.
option3: Treat AI platforms as equivalent to other cloud-based engineering software routinely used without specific client authorization, relying on the engineer's professional judgment that the efficiency and quality benefits justify use of available tools within normal practice.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP3
type: DecisionPoint
type: NamedIndividual
decision point id: DP3
decision question: Must Engineer A verify, independently direct, and properly attribute all AI-generated technical content in sealed reports and design documents, or is applying standard QA review to AI outputs sufficient to satisfy responsible charge obligations?
focus: Engineer A submitted a report and design documents that omitted citations to AI-generated technical content and misrepresented the authorship of the work product. Multiple obligations related to technical citation, authorship representation, responsible charge, and design verification are marked unmet. The board must determine what standard of verification and attribution applies when AI tools generate substantive technical content that an engineer then seals.
option1: Independently verify all AI-generated technical content against engineering first principles or established references, document the verification process, include proper citations to AI tools and source data, and seal only content that the engineer can personally defend as technically sound.
option2: Apply the same quality assurance review procedures used for work produced by junior engineers or conventional software to AI-generated content, treating the engineer's professional judgment in reviewing outputs as sufficient to establish responsible charge without requiring independent re-derivation of every result.
option3: Apply heightened independent review to AI-generated content in safety-critical design elements while applying standard QA protocols to non-safety-critical sections, and defer sealing until a senior engineer with AI competency reviews the safety-critical outputs.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP4
type: DecisionPoint
type: NamedIndividual
decision point id: DP4
decision question: Should Engineer A proactively disclose to the client that AI tools generated substantial portions of the design and report, or present the deliverables as conventionally authored engineering work?
focus: Engineer A must decide whether to disclose to the client that AI tools generated substantial portions of both the design documents and the written report, or to present the work product as conventionally authored engineering output.
option1: Inform the client before or upon delivery that AI tools generated substantial portions of the design documents and report, identifying which sections were AI-produced and describing the verification steps taken.
option2: Treat AI tools as equivalent to other computational or drafting software such as CAD or FEA packages, disclosing AI usage only if the client specifically inquires, consistent with how other software tools are handled.
option3: Document AI tool usage in internal project records and deliverable metadata without a separate client notification, on the basis that the engineer reviewed and sealed the work and therefore bears full professional responsibility regardless of the generative method.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP5
type: DecisionPoint
type: NamedIndividual
decision point id: DP5
decision question: Should Engineer B require Engineer A to disclose AI authorship of the deliverables to the client, or accept the work as submitted on the basis that Engineer B's review satisfies the professional responsibility?
focus: Engineer B, acting as mentor to Engineer A, must decide whether to require Engineer A to disclose the AI-generated authorship of the report and design to the client, or to allow the work to proceed without that disclosure given that Engineer B reviewed the output.
option1: Direct Engineer A to notify the client of AI tool usage in the design and report before final delivery, and confirm that disclosure has been made before Engineer B provides any further mentorship endorsement of the work.
option2: Conduct an independent technical review of the AI-generated content and, if satisfied with quality and accuracy, allow the deliverables to proceed without requiring separate AI disclosure, on the basis that Engineer B's review establishes professional accountability for the output.
option3: Counsel Engineer A on the professional risks of omitting AI disclosure and recommend disclosure as best practice, but ultimately defer to Engineer A's judgment as the engineer of record rather than mandating a specific course of action.
role label: Engineer B Mentor Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP6
type: DecisionPoint
type: NamedIndividual
decision point id: DP6
decision question: Should Engineer A seal the AI-generated design documents based on the review conducted, or withhold the seal until a more rigorous independent verification of safety compliance and responsible charge is completed?
focus: Engineer A must decide whether to seal design documents that were substantially generated by AI tools without adequate verification of safety compliance and responsible charge, or to withhold the seal until independent verification is complete.
option1: Decline to seal the design documents until a complete independent technical review confirms safety compliance and all required design features are present, accepting schedule delay as necessary to meet responsible charge obligations.
option2: Apply the firm's standard quality assurance review process to the AI-generated design, treating AI output as equivalent to conventionally drafted documents and sealing upon completion of that review, consistent with how other computer-assisted design tools are handled.
option3: Retain an independent reviewer with relevant safety expertise to evaluate the safety-critical portions of the AI-generated design before sealing, while applying standard review to non-safety-critical elements, balancing schedule pressure against the heightened risk of AI-generated safety features.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP7
type: DecisionPoint
type: NamedIndividual
decision point id: DP7
decision question: Should Engineer B conduct a full independent technical review of the AI-assisted design documents before sealing, or apply a standard supervisory review comparable to reviewing conventional CAD-produced work?
focus: Engineer B must decide what level of review to apply to design documents that Engineer A produced with substantial AI assistance, before affixing a seal as the responsible charge engineer.
option1: Review every substantive element of the AI-assisted design documents independently, verifying calculations, safety features, and code compliance before sealing, treating AI-generated content as requiring the same scrutiny as work from an unfamiliar subconsultant.
option2: Apply the firm's existing quality assurance protocols to the AI-assisted documents at the same level used for conventional CAD-produced work, relying on Engineer A's advanced environmental domain competence and intermediate verification proficiency as a reasonable internal check.
option3: Commission a focused third-party technical review of safety-critical and AI-generated design elements while applying standard supervisory review to the remaining portions, balancing thoroughness with practical resource constraints.
role label: Engineer B Mentor Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP8
type: DecisionPoint
type: NamedIndividual
decision point id: DP8
decision question: Should Engineer A proactively disclose to the client and to Engineer B the nature and extent of AI tool usage in the design and report before those documents are finalized, or treat the AI tools as internal drafting aids that do not require separate disclosure?
focus: Engineer A must decide how to disclose the AI tools used and the extent of AI involvement in both the design documents and the report, given that multiple AI disclosure and authorship obligations are unmet.
option1: Proactively inform the client and Engineer B of the specific AI tools used, the portions of the design and report they generated, and the verification steps taken, before any documents are sealed or submitted.
option2: Treat AI tools as internal drafting aids equivalent to spreadsheet or CAD software, disclosing their use only if the client or Engineer B specifically asks, on the basis that professional responsibility attaches to the engineer's judgment rather than to the tools employed.
option3: Record the AI tools and their outputs in the internal project file to preserve a verifiable audit trail, while omitting proactive client notification on the grounds that the engineer's professional seal represents adequate assumption of responsibility for all methods used.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

DP9
type: DecisionPoint
type: NamedIndividual
decision point id: DP9
decision question: Should Engineer A seal and submit the AI-generated design documents after only a cursory review, or must Engineer A conduct a thorough independent technical verification before sealing?
focus: Engineer A faces a decision about whether to seal and submit design documents that were substantially generated by AI tools without adequate independent technical verification, responsible charge oversight, or confirmation that required safety features are present.
option1: Perform a comprehensive, line-by-line technical review of all AI-generated design documents, independently verify that all required safety features are present and code-compliant, and only affix the professional seal after establishing genuine responsible charge over the entire design.
option2: Apply the firm's standard quality assurance review protocols to the AI-generated documents at the same level used for conventionally drafted designs, treating AI as an advanced drafting tool, and seal upon completion of that standard review without a separate AI-specific verification layer.
option3: Pause the sealing process, engage a qualified senior engineer or external reviewer to provide the mentorship and technical oversight lost when Engineer B departed, and seal only after that substitute oversight confirms the design documents are complete, safe, and accurate.
role label: Engineer
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A's site observation and data gathering before project deliverables due date
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: groundwater monitoring data from a site Engineer A had been observing for over a year
from entity text: Engineer A's site observation and data gathering
owl time property: time:intervalBefore
to entity text: project deliverables due date
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: project deliverables due date
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

I.1.
type: NamedIndividual
comment: Hold paramount the safety, health, and welfare of the public.
was generated by: ProEthica Case 7 Extraction

I.2.
type: NamedIndividual
comment: Perform services only in areas of their competence.
was generated by: ProEthica Case 7 Extraction

I.5.
type: NamedIndividual
comment: Avoid deceptive acts.
was generated by: ProEthica Case 7 Extraction

II.1.c.
type: NamedIndividual
comment: Engineers shall not reveal facts, data, or information without the prior consent of the client or employer except as authorized or required by law or this Code.
was generated by: ProEthica Case 7 Extraction

II.2.a.
type: NamedIndividual
comment: Engineers shall undertake assignments only when qualified by education or experience in the specific technical fields involved.
was generated by: ProEthica Case 7 Extraction

II.2.b.
type: NamedIndividual
comment: Engineers shall not affix their signatures to any plans or documents dealing with subject matter in which they lack competence, nor to any plan or document not prepared under their direction and control.
was generated by: ProEthica Case 7 Extraction

III.3.
type: NamedIndividual
comment: Engineers shall avoid all conduct or practice that deceives the public.
was generated by: ProEthica Case 7 Extraction

III.8.a.
type: NamedIndividual
comment: Engineers shall conform with state registration laws in the practice of engineering.
was generated by: ProEthica Case 7 Extraction

III.9.
type: NamedIndividual
comment: Engineers shall give credit for engineering work to those to whom credit is due, and will recognize the proprietary interests of others.
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_1
type: NamedIndividual
comment: This question arose because the act of uploading client data to an open-source AI platform is a factual trigger that sits at the intersection of two legitimate professional obligations, one demanding confidentiality and one demanding competent direction of tools. The deontological framing sharpens the question by asking whether the confidentiality duty is categorical and outcome-independent, which forces a determination of whether the absence of an actual breach is legally or ethically irrelevant to the duty itself.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_10
type: NamedIndividual
comment: This question arose because Engineer B's retirement created a foreseeable structural change in Engineer A's quality assurance capacity at the same moment Engineer A adopted an unfamiliar AI tool and accepted sealed deliverables, producing a compound competence deficit that the responsible charge obligation alone may not have been designed to address. The question forces analysis of whether the obligation to practice within competence required Engineer A to act before the engagement rather than only during it, and what specific remediation steps that obligation demanded.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_11
type: NamedIndividual
comment: This question emerged because the Board's competence finding and the concealment finding were reached independently, leaving open whether satisfying one obligation can offset a violation of the other. The two principles address different dimensions of professional conduct, technical quality and representational honesty, and the case provides no hierarchy for resolving their conflict when a single submission implicates both.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_12
type: NamedIndividual
comment: The question emerged because Engineer A's conduct simultaneously satisfied the factual conditions that activate both warrants: the AI contribution was substantial enough that stylistic inconsistency became detectable, yet the Board's own reasoning acknowledged the software analogy as a legitimate basis for non-disclosure. The absence of a governing regulatory standard left both warrants in play without a rule to subordinate one to the other, making the tension a genuine unresolved conflict rather than a clear violation.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_13
type: NamedIndividual
comment: This question emerged because the professional seal is designed to function as a guarantee of responsible charge, but Engineer A's cursory review of AI-generated plans containing misaligned dimensions and omitted safety features meant the seal communicated a level of oversight that had not actually occurred. The gap between what the seal formally represents and what Engineer A actually performed created a direct conflict between the obligation to seal work under responsible charge and the obligation to ensure that responsible charge was genuinely exercised before sealing.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_14
type: NamedIndividual
comment: This question emerged because Engineer A's single act of uploading confidential client data to an unfamiliar AI tool simultaneously activated two distinct ethical warrants, one protecting client privacy and one requiring professional competence, and the factual record does not resolve whether those warrants operate on the same normative ground or on independent grounds. The question of whether to treat the violations as compounded or independent is not merely taxonomic but determines how responsibility is assigned, what remedies are appropriate, and whether the ethical analysis focuses on harm to the client, harm to professional standards, or both.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_15
type: NamedIndividual
comment: This question emerged because Engineer B's retirement created a genuine competence gap at the same moment Engineer A faced dual deliverable pressure, and Engineer A responded by deploying an unfamiliar AI drafting tool rather than seeking alternative qualified oversight or declining work beyond independent capacity. The virtue ethics framing sharpens the question by asking not just whether the outcome was harmful but whether Engineer A demonstrated the self-knowledge and professional honesty that integrity requires before accepting and executing work under those conditions.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_16
type: NamedIndividual
comment: This question arose because the professional seal is the institutional symbol of responsible stewardship, and Engineer A's cursory review created a direct contest between the virtue of diligence that the seal represents and the self-serving convenience of accepting AI output without the verification that would make the seal honest. The discovery of design deficiencies after submission made the gap between the character trait the seal implies and the character trait Engineer A actually demonstrated impossible to ignore.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_17
type: NamedIndividual
comment: This question emerged because the actual harms produced by Engineer A's undisclosed AI use, including design defects, public safety risks, and client data exposure, created observable evidence that discretionary disclosure failed to protect the interests it was meant to protect. The gap between the outcomes the current approach produced and the outcomes a universal norm might have produced forced a consequentialist evaluation of whether the warrant authorizing discretion is strong enough to survive the rebuttal that mandatory disclosure would have prevented those harms.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_18
type: NamedIndividual
comment: This question arose because the Board identified multiple distinct violations, and it is genuinely unclear whether a single procedural act, prior written consent, would have collapsed those violations into a compliant engagement or whether the responsible charge, verification, and public safety failures would have remained as independent grounds for ethical censure. The question forces a structural analysis of whether the violations are causally linked to the absence of consent or whether they reflect deeper competence and oversight failures that consent alone could not have cured.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_19
type: NamedIndividual
comment: This question arose because the Board's findings identified failures across multiple dimensions simultaneously, including design deficiencies, regulatory omissions, and responsible charge deficits, and it became unclear whether those failures were caused by the absence of a substitute reviewer specifically or by a broader pattern of inadequate verification that a substitute reviewer might not have corrected. The question forces a structural analysis of whether the ethical permissibility of AI use depends on the presence of a qualified human reviewer in the oversight chain, or whether it depends on the competence and rigor of whoever holds responsible charge.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_2
type: NamedIndividual
comment: This question arose because Engineer A's AI-assisted workflow produced multiple distinct categories of harm across a single project, and consequentialism demands a unified net assessment rather than isolated evaluation of each failure. The question became necessary because the data shows real efficiency motivation alongside real harm production, and no single warrant resolves whether the aggregate outcome is net negative without contested empirical judgments about harm probability, severity, and the counterfactual value of the efficiency gains.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_20
type: NamedIndividual
comment: This question emerged because the Board's finding rested on the inadequacy of Engineer A's review of the design documents, but Engineer A had demonstrated the capacity for thorough AI output review in the context of the report. The question asks whether the ethical violation was a function of the review process Engineer A chose to apply, rather than an inherent consequence of using AI-assisted drafting tools, which creates genuine uncertainty about whether the violation was avoidable through conduct rather than unavoidable through context.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_21
type: NamedIndividual
comment: This question arose because the stylistic inconsistency noticed by Client W created observable evidence that the work product had a non-uniform origin, which transformed what might have been a private tool-use decision into a situation where the client was already drawing inferences about authorship without accurate information. The question then asks whether voluntary disclosure would have reframed the entire ethical situation, because if transparency at submission would have resolved the client's concern and altered the Board's analysis, then the omission itself becomes the operative ethical failure rather than the AI use.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_3
type: NamedIndividual
comment: This question emerged because Engineer A sealed and submitted AI-generated work products to Client W without any acknowledgment of AI involvement in either deliverable, creating a factual record of non-disclosure that directly contests the deontological principle that candor to a client is an obligation owed regardless of consequences. The question is not resolved by pointing to outcome because deontological analysis asks whether the duty was honored at the moment of action, and the competing warrants disagree on whether non-disclosure of AI authorship constitutes a breach of that duty or merely a lapse in attribution practice.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_4
type: NamedIndividual
comment: This question arose because the data simultaneously supports two defensible positions: that AI tools are legitimate engineering aids when an engineer seals and takes responsibility for the work, and that a high-level review of AI-generated design documents falls short of the direction and control required by responsible charge. The Engineer A Design Deficiencies state, combined with the Engineer A Unfamiliar Drafting Tool state and the loss of mentorship oversight captured in Engineer A Mentor Unavailable, created a factual record that makes it genuinely contestable whether Engineer A's review process met the standard that would make the AI tool use ethical.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_5
type: NamedIndividual
comment: The question emerged because Engineer A produced client deliverables substantially through AI tools and then omitted any mention of that fact, placing the client in a position of receiving work without knowing its origin. The absence of an explicit disclosure rule created genuine uncertainty about whether the obligation to be transparent about authorship and method extends beyond the engineer's internal professional responsibility and reaches the client relationship directly.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_6
type: NamedIndividual
comment: The question arose because Engineer A's thorough review satisfies the professional competence and responsible charge obligations that normally govern work product quality, but the act of submitting AI-generated text without disclosure leaves the attribution and intellectual honesty obligations unresolved. The two sets of obligations point to different conclusions about the same conduct, and neither fully overrides the other given the facts, which is precisely what generates the ethical question.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_7
type: NamedIndividual
comment: This question arose because Engineer A's decision to input Client W's confidential data into an open-source AI platform created a potential confidentiality violation that is analytically separate from any question about the report's technical adequacy. The question forces a determination of whether a procedural breach in how work was generated can independently condemn a submission that might otherwise be technically sound, which the Code's structure does not explicitly resolve.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_8
type: NamedIndividual
comment: The question emerged because Engineer A's state of unfamiliarity with the AI drafting tool, combined with the loss of mentor oversight after Supervisor Retirement and the pressure of Dual Deliverable Pressure, produced sealed design documents with safety-relevant deficiencies. The absence of any profession-wide threshold for AI tool proficiency before sealed use left the competence standard contested, forcing the question of what minimum readiness is required before an engineer may rely on such tools for deliverables that carry a professional seal.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

QuestionEmergence_9
type: NamedIndividual
comment: This question arose because Client W's direct observation of stylistic inconsistency transformed what might otherwise be a silent omission into a situation where the client was actively forming an incorrect inference about authorship, making Engineer A's silence function more like a tacit false assertion. The question is whether the combination of a detectable anomaly and continued non-disclosure crosses the line from mere omission into misrepresentation under the cited code sections, independent of factual accuracy.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Question_1
type: EthicalQuestion
type: NamedIndividual
question number: 1
question text: Was Engineer A’s use of AI to create the report text ethical, given that Engineer A thoroughly checked the report?
question type: board_explicit
was generated by: ProEthica Case 7 Extraction

Question_101
type: EthicalQuestion
type: NamedIndividual
question number: 101
question text: By uploading Client W's confidential site data and groundwater monitoring information into an open-source AI platform without obtaining Client W's prior consent, did Engineer A breach the client confidentiality obligation under Code Section II.1.c, and does that breach independently render the report submission unethical regardless of the quality of Engineer A's subsequent review?
question type: implicit
was generated by: ProEthica Case 7 Extraction

Question_102
type: EthicalQuestion
type: NamedIndividual
question number: 102
question text: Given that Engineer A used an AI drafting tool that was entirely new to the market and with which Engineer A had no prior experience, did Engineer A satisfy the competence requirement under Code Sections I.2 and II.2.a before adopting that tool for a live client engagement, and what minimum level of tool-specific proficiency should be required before an engineer may rely on AI-assisted drafting software for sealed deliverables?
question type: implicit
was generated by: ProEthica Case 7 Extraction

Question_103
type: EthicalQuestion
type: NamedIndividual
question number: 103
question text: Because the AI-generated report produced stylistically inconsistent text that Client W noticed and attributed to what appeared to be two different authors, did Engineer A's omission of any disclosure about AI authorship constitute a deceptive act or misrepresentation of authorship under Code Sections I.5 and III.3, independent of whether the factual content of the report was accurate?
question type: implicit
was generated by: ProEthica Case 7 Extraction

Question_104
type: EthicalQuestion
type: NamedIndividual
question number: 104
question text: To what extent did Engineer A's loss of Engineer B as a mentor and quality assurance reviewer create a foreseeable competence gap that Engineer A was obligated to address through means other than unilateral adoption of an unfamiliar AI tool—such as engaging a substitute peer reviewer, limiting the scope of accepted work, or declining the engagement—before undertaking sealed deliverables for Client W?
question type: implicit
was generated by: ProEthica Case 7 Extraction

Question_2
type: EthicalQuestion
type: NamedIndividual
question number: 2
question text: Was Engineer A’s use of AI-assisted drafting tools to create the engineering design documents ethical, given that Engineer A reviewed the design at a high level?
question type: board_explicit
was generated by: ProEthica Case 7 Extraction

Question_201
type: EthicalQuestion
type: NamedIndividual
question number: 201
question text: Does the principle of Engineer A AI Report Competence—which the Board found satisfied by Engineer A's thorough cross-checking of the report—conflict with the principle of Engineer A AI Authorship Concealment, in that an engineer may produce a technically accurate work product while simultaneously misrepresenting the nature and origin of that work product, and if so, which obligation should take precedence when the two cannot be simultaneously fulfilled?
question type: principle_tension
was generated by: ProEthica Case 7 Extraction

Question_202
type: EthicalQuestion
type: NamedIndividual
question number: 202
question text: Does the principle of Engineer A AI Disclosure Transparency—which the Board acknowledged is ethically favored when AI plays a substantial role—conflict with the principle of Engineer A AI Tool Non-Disclosure Report, which the Board grounded in an analogy to conventional engineering software that carries no mandatory disclosure obligation, and how should engineers resolve this tension in the absence of a universal regulatory standard?
question type: principle_tension
was generated by: ProEthica Case 7 Extraction

Question_203
type: EthicalQuestion
type: NamedIndividual
question number: 203
question text: Does the principle of Engineer A Responsible Charge Design Failure—arising from Engineer A's cursory review of AI-generated plans that contained misaligned dimensions and omitted safety features—conflict with the principle of Engineer A Seal on AI Design Documents, in that affixing a professional seal is intended to certify responsible charge but the act of sealing here obscured rather than confirmed the adequacy of engineering oversight, and what procedural safeguards should govern the sealing of AI-generated design documents?
question type: principle_tension
was generated by: ProEthica Case 7 Extraction

Question_204
type: EthicalQuestion
type: NamedIndividual
question number: 204
question text: Does the principle of Engineer A Client Data AI Upload—which reflects the engineer's interest in leveraging available tools to meet client deliverable demands—conflict with the principle of Engineer A Professional Competence AI Use, in that using an unfamiliar open-source AI tool to process confidential client data may simultaneously undermine both the client's data security interests and the engineer's own competence obligations, and should the ethical analysis treat these as a single compounded violation or as two independently assessable breaches?
question type: principle_tension
was generated by: ProEthica Case 7 Extraction

Question_3
type: EthicalQuestion
type: NamedIndividual
question number: 3
question text: If the use of AI was acceptable, did Engineer A have an ethical obligation to disclose the use of AI in any form to the Client?
question type: board_explicit
was generated by: ProEthica Case 7 Extraction

Question_301
type: EthicalQuestion
type: NamedIndividual
question number: 301
question text: From a deontological perspective, did Engineer A fulfill their duty of candor to Client W by omitting any disclosure of AI involvement in both the report and the engineering design documents, regardless of whether that omission ultimately harmed the client?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_302
type: EthicalQuestion
type: NamedIndividual
question number: 302
question text: From a deontological perspective, did Engineer A violate a categorical duty to protect client confidentiality by uploading Client W's proprietary site data and groundwater monitoring information into an open-source AI platform without obtaining prior consent, irrespective of whether any actual data breach occurred?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_303
type: EthicalQuestion
type: NamedIndividual
question number: 303
question text: From a consequentialist perspective, did the aggregate outcomes of Engineer A's AI-assisted workflow — including the polished but stylistically inconsistent report, the deficient design documents with misaligned dimensions and omitted safety features, and the potential exposure of confidential client data — produce a net harm that outweighs the efficiency gains Engineer A sought by adopting AI tools?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_304
type: EthicalQuestion
type: NamedIndividual
question number: 304
question text: From a virtue ethics perspective, did Engineer A demonstrate the professional integrity and intellectual honesty expected of a licensed engineer by choosing to use an unfamiliar, open-source AI drafting tool — with no prior experience — as a substitute for the mentorship and quality assurance oversight previously provided by Engineer B, rather than seeking alternative qualified review or declining work beyond their current independent capacity?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_305
type: EthicalQuestion
type: NamedIndividual
question number: 305
question text: From a virtue ethics perspective, does Engineer A's decision to apply their professional seal to AI-generated design documents after only a cursory review reflect the character trait of responsible stewardship that the public and clients are entitled to expect from a licensed professional engineer, or does it represent a self-serving shortcut that undermines the moral foundation of professional licensure?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_306
type: EthicalQuestion
type: NamedIndividual
question number: 306
question text: From a consequentialist perspective, would a universal norm requiring engineers to disclose AI involvement whenever AI plays a substantial role in generating a work product produce better outcomes for public safety, client trust, and the engineering profession than the current discretionary approach endorsed by the Board?
question type: theoretical
was generated by: ProEthica Case 7 Extraction

Question_401
type: EthicalQuestion
type: NamedIndividual
question number: 401
question text: If Engineer A had disclosed to Client W, prior to beginning work, that they intended to use open-source AI software and had obtained explicit written consent for uploading confidential site data to that platform, would the ethical violations identified by the Board regarding client data exposure and lack of attribution have been avoided, and would the overall ethical assessment of the engagement have changed?
question type: counterfactual
was generated by: ProEthica Case 7 Extraction

Question_402
type: EthicalQuestion
type: NamedIndividual
question number: 402
question text: What if Engineer A had sought a qualified substitute reviewer — such as a peer engineer or a licensed colleague — to replace Engineer B's mentorship and quality assurance role before submitting either the report or the design documents? Would the design deficiencies, regulatory omissions, and responsible charge failures identified by the Board have been prevented, and would AI use have remained ethically permissible under those circumstances?
question type: counterfactual
was generated by: ProEthica Case 7 Extraction

Question_403
type: EthicalQuestion
type: NamedIndividual
question number: 403
question text: If Engineer A had conducted the same level of thorough, cross-referenced review on the AI-generated design documents as they applied to the AI-generated report — verifying dimensions, checking safety feature requirements against local regulations, and reconciling site-specific conditions — would the Board's finding of an ethical violation for failure to maintain Responsible Charge over the design documents still have been warranted?
question type: counterfactual
was generated by: ProEthica Case 7 Extraction

Question_404
type: EthicalQuestion
type: NamedIndividual
question number: 404
question text: What if Engineer A had voluntarily disclosed the use of AI tools in both the report and the design documents — including the specific AI software used and the extent of AI involvement — at the time of submission to Client W? Would such proactive transparency have altered the client's trust, the professional relationship, or the Board's ethical assessment regarding the disclosure obligation, and does the client's observation that the report 'read as if written by two different authors' suggest that non-disclosure was already functionally deceptive?
question type: counterfactual
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_1
type: NamedIndividual
comment: Because Engineer A exposed Client W's confidential data to a system with unknown retention and access policies before obtaining any consent, the board found an independent breach of II.1.c that the quality of the resulting report could not retroactively cure, since the violation was complete at the moment of upload.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_10
type: NamedIndividual
comment: Because the Board found the report technically competent but simultaneously found the concealment of AI authorship perceptible and materially misleading, the Board concluded that the existing framework is insufficient and that competence and candor should be treated as jointly necessary conditions for ethical submission of a sealed work product where AI plays a substantial authorship role.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_11
type: NamedIndividual
comment: Because Engineer A reviewed the AI-generated design documents only at a high level and the documents contained misaligned dimensions and omitted required safety features, the board found that the act of sealing did not confirm responsible charge but instead obscured its absence, making the sealing and submission of those documents an ethical violation under the responsible charge standard.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_12
type: NamedIndividual
comment: Because Engineer A's single decision to adopt an AI tool compounded three distinct ethical failures that each independently violated a code obligation, the board concluded that the ethical analysis could not treat these as a unified or offsetting set of considerations, and that each breach remained actionable on its own terms regardless of Engineer A's performance on other dimensions of the engagement.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_13
type: NamedIndividual
comment: Because Engineer A thoroughly checked the AI-generated report and verified its technical content before submission, the board found that the use of AI for report drafting was not unethical in that respect, though the conclusion is partial because other aspects of the same engagement, including the data upload and the design documents, were found to be unethical.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_14
type: NamedIndividual
comment: Because the board found that AI-assisted drafting is not categorically different from other engineering software tools when the engineer exercises adequate oversight, it concluded that Engineer A's use of AI for drafting was not unethical per se, with the ethical assessment turning on the quality of the review performed rather than on the fact of AI use itself.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_15
type: NamedIndividual
comment: Because no contractual or regulatory requirement compelled disclosure and the board analogized AI drafting tools to conventional software, it concluded that Engineer A had no independent ethical obligation to disclose AI use to Client W, though this resolution is conditional on the absence of a disclosure requirement and does not address whether the client-observable stylistic inconsistency independently triggered a duty to correct a potentially deceptive impression.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_16
type: NamedIndividual
comment: Because Client W could detect a stylistic discontinuity consistent with multiple authors, and because Engineer A offered no explanation, the board found that the omission created a false impression of sole human authorship. The conclusion rests on the perceptibility of the AI contribution in this case, not on a universal rule that all AI use must be disclosed.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_17
type: NamedIndividual
comment: Because Engineer A simultaneously lost their mentor, accepted complex sealed deliverables, and adopted an unfamiliar AI tool without any substitute peer review, the board found that the competence gap was foreseeable and the resulting design deficiencies were a direct consequence of failing to address it through appropriate professional means.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_18
type: NamedIndividual
comment: Because Engineer A's thorough review addressed only output quality and left the authorship misrepresentation intact, the board found that satisfying the competence obligation does not discharge the separate and categorical obligation of candor, and that the latter must prevail when the two cannot be simultaneously fulfilled.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_19
type: NamedIndividual
comment: Because Engineer A's review did not detect errors that a systematic check would have caught, the board found that the seal functioned as a misrepresentation of responsible charge rather than a certification of it, and prescribed specific procedural safeguards to prevent this failure mode when AI generates sealed design content.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_2
type: NamedIndividual
comment: Because Engineer A had no experience with the AI tool and because the tool's probabilistic output characteristics created a verification burden that conventional software does not, the board concluded that adopting it for live sealed work without any tool-specific qualification failed the competence threshold under I.2 and II.2.a, regardless of whether AI tools are permissible in principle.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_20
type: NamedIndividual
comment: Because Engineer A acted without client consent on the data upload and without disclosure on the authorship question, the board found two independent categorical violations that compound each other as a pattern of prioritizing personal convenience over professional obligation, with the absence of a confirmed breach being irrelevant to the deontological analysis.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_21
type: NamedIndividual
comment: Because Engineer A was unfamiliar with the tool and reviewed the design documents only at a high level, the efficiency gains were achieved by offloading risk onto the client and the public rather than by genuinely improving productivity, and the board found that the aggregate harms across data security, public safety, client trust, and professional norms substantially outweighed those gains.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_22
type: NamedIndividual
comment: Because Engineer A chose technological substitution over qualified human oversight after losing Engineer B, and then sealed documents containing detectable errors following only a cursory review, the board found that both decisions reflected a disposition that fell short of the professional integrity and responsible stewardship that licensure demands.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_23
type: NamedIndividual
comment: Because AI language models produce content through probabilistic processes that differ fundamentally from deterministic engineering software, and because non-disclosure in this case was already functionally deceptive as evidenced by the client's independent detection of AI involvement, the board concluded that a universal disclosure norm for substantial AI involvement would produce better outcomes than the current discretionary standard.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_24
type: NamedIndividual
comment: Because Engineer A's violations included both the unauthorized data upload and the independent failures of competence and responsible charge over the design documents, the board found that prior consent would have eliminated the confidentiality breach but would have left the design deficiency and sealing violations intact.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_25
type: NamedIndividual
comment: Because the design deficiencies were detectable by a non-engineer client and arose from the absence of qualified oversight rather than from AI use per se, the board concluded that engaging a qualified substitute reviewer before submission would have prevented the responsible charge failures and preserved the ethical permissibility of AI-assisted drafting.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_26
type: NamedIndividual
comment: Given that the Board's distinction between the report and the design documents rested substantially on the difference in review depth rather than on the mere fact of AI use, the Board concluded that a counterfactually thorough review of the design documents would have satisfied the responsible charge obligation under II.2.b, because the deficiencies in the submitted documents were curable through the same verification process Engineer A successfully applied to the report. However, because the confidentiality breach and the non-disclosure of AI involvement were structural features of Engineer A's workflow that preceded and were independent of any review step, those violations would have persisted even under the counterfactual, confirming that responsible charge is a curable deficiency while confidentiality and transparency violations are not.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_3
type: NamedIndividual
comment: Because Client W could detect the stylistic discontinuity between AI-generated and human-written sections, Engineer A's silence about AI involvement functioned as an implicit claim of sole human authorship, placing the omission in tension with the deception prohibitions in I.5 and III.3 and the attribution obligation in III.9.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_4
type: NamedIndividual
comment: Because the design review was cursory rather than substantive, and because the sealed documents contained errors that a competent review would have caught, the board found that the seal misrepresented the degree of professional oversight applied and that this failure, given the public safety consequences of deficient design documents, was the most serious ethical violation in the case.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_5
type: NamedIndividual
comment: Because Engineer B's retirement removed a structural component of Engineer A's quality assurance process and because Engineer A's substitution of an unfamiliar AI tool for that human oversight was not a professionally adequate adaptation, the board concluded that the mentor loss elevated rather than relaxed Engineer A's obligations and that the ethical failures in this case were foreseeable consequences of failing to address that gap through appropriate professional measures.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_6
type: NamedIndividual
comment: Given that no mandatory disclosure rule currently exists and the Board analogized AI tools to conventional engineering software, the Board concluded that disclosure is ethically favored but not required, while simultaneously warning that this standard is unstable and will likely produce worse outcomes as AI capabilities grow.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_7
type: NamedIndividual
comment: Because Engineer A exposed Client W's confidential data to an uncontrolled platform without consent, the Board found an independent ethical breach under II.1.c, treating the absence of demonstrated harm as irrelevant to whether the obligation was violated.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_8
type: NamedIndividual
comment: Because Engineer A used an untested, unfamiliar tool on a live engagement without any prior validation or verification protocol, and because the resulting deficiencies were foreseeable, the Board concluded that the competence requirement under I.2 and II.2.a was not satisfied before the tool was adopted.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

ResolutionPattern_9
type: NamedIndividual
comment: Because Client W could perceive the stylistic inconsistency caused by AI authorship and Engineer A withheld the explanation, the Board concluded that the omission crossed from mere non-disclosure into functional deception, independently triggering the candor obligations under I.5 and III.3 in this specific circumstance.
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Design

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Report

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Design Defect Discovery

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: Revision Instruction Issued

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Client W

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Client Data Upload to AI

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Report Generation

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Tool Adoption for Design

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Design Generation

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Draft Report Sealing and Submission

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: Report Stylistic Inconsistency

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Report Generation

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: Report Stylistic Inconsistency

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Tool Adoption for Report

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Disclosure Omission for Report

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Dual Deliverable Pressure

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Tool Adoption for Design

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Supervisor Retirement

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: AI Tool Adoption for Report

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Client Data Upload to AI

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: Client Data Exposure

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (cause)
type: Derivation
comment: property=cause; causal chain's cause text resolved to the case individual(s) by embedding shortlist + LLM select
value: Cursory Design Document Review

Causal edge (effect)
type: Derivation
comment: property=effect; causal chain's effect text resolved to the case individual(s) by embedding shortlist + LLM select
value: Design Defect Discovery

Causal edge (responsibleAgent)
type: Derivation
comment: property=responsibleAgent; causal chain's responsibleAgent text resolved to the case individual(s) by embedding shortlist + LLM select
value: Engineer A

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_Client_Data_Upload_to_AI

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_Cursory_Design_Document_Review

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_Project_Acceptance

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_Thorough_Report_Review

Causal edge (causedByAction)
type: Derivation
comment: property=causedByAction; causal chain's causedByAction text resolved to the case individual(s) by embedding shortlist + LLM select
value: http://proethica.org/cases/7#Action_Design_Document_Submission

Defeasibility edge from interpretation
type: Derivation
comment: source_field=interpretation; confidence=0.7
generated at time: 2026-06-05T09:35:20.843301+00:00
value: Using a novel AI tool without understanding its accuracy limitations, and reviewing its output only cursorily, falls below the competence standard required before sealing and submitting engineering design documents.

Defeasibility edge from interpretation
type: Derivation
comment: source_field=interpretation; confidence=0.65
generated at time: 2026-06-05T09:35:20.843408+00:00
value: Responsible charge requires active engagement from conception to completion, not merely reviewing outputs after preparation. Engineer A's high-level review of AI-generated plans did not satisfy this standard, constituting a violation of licensure law and NSPE Code section III.8.a.

Defeasibility edge from interpretation
type: Derivation
comment: source_field=interpretation; confidence=0.5
generated at time: 2026-06-05T09:35:20.843512+00:00
value: The BER treated this as the most serious ethical concern arising from Engineer A's use of AI-assisted drafting, grounding the responsible charge and competence violations in the fundamental canon.

Defeasibility edge from interpretation
type: Derivation
comment: source_field=interpretation; confidence=0.6
generated at time: 2026-06-05T09:35:20.843192+00:00
value: The report review was more substantive than the design document review, but the inconsistency in writing style noted by the client suggests the verification did not fully address the limitations of AI-generated synthesis.

Defeasibility edge from interpretation
type: Derivation
comment: source_field=interpretation; confidence=0.7
generated at time: 2026-06-05T09:35:20.843058+00:00
value: Because Engineer A had domain expertise in environmental engineering and conducted substantive verification of the AI output, the use of AI for report drafting was within the bounds of professional competence for this component of the work.

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Drafted Design Exists; Unverified Design Content State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Undisclosed AI Contribution to Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Undisclosed AI Contribution to Report State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Undisclosed AI Contribution to Report State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Drafted Report Exists; Unverified Content State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Drafted Report Exists; Unverified Content State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Assisted Design Document Drafting State; Client Confidential Data in Public Domain State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Assisted Report Drafting State; Client Confidential Data in Public Domain State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Assisted Report Drafting State; Client Confidential Data in Public Domain State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: AI-Assisted Report Drafting State; Client Confidential Data in Public Domain State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Confidentiality Risk State; Third-Party Data Exposure State

Fluent edge (terminates)
type: Derivation
comment: property=terminates; happening's terminates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Client Data Confidentiality State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Client Confidential Data in Public Domain State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State

Fluent edge (initiates)
type: Derivation
comment: property=initiates; happening's initiates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State

Fluent edge (terminates)
type: Derivation
comment: property=terminates; happening's terminates state text resolved to the case State(s) by embedding shortlist + LLM multi-select (Event Calculus fluent transition)
value: Unverified AI Report Draft State

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work; Avoid Deceptive Acts

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work; Avoid Deceptive Acts

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Transparency and Attribution; Professional Integrity

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work; Avoid Deceptive Acts

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work; Avoid Deceptive Acts

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work; Avoid Deceptive Acts

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Technological Innovation in Engineering Practice; Professional Competency

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Technological Innovation in Engineering Practice; Professional Competency

Normative edge (raisesObligation)
type: Derivation
comment: property=raisesObligation; action's raisesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Technological Innovation in Engineering Practice; Professional Competency

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Technological Innovation in Engineering Practice; Professional Competency

Normative edge (raisesObligation)
type: Derivation
comment: property=raisesObligation; action's raisesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Client Confidentiality; Direction and Control Over Work Product

Normative edge (raisesObligation)
type: Derivation
comment: property=raisesObligation; action's raisesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Client Confidentiality; Direction and Control Over Work Product

Normative edge (raisesObligation)
type: Derivation
comment: property=raisesObligation; action's raisesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Client Confidentiality; Direction and Control Over Work Product

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Respect for Client Privacy; Avoid Deceptive Acts

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Respect for Client Privacy; Avoid Deceptive Acts

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Client Confidentiality

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety; Responsible Charge

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety; Responsible Charge

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety; Responsible Charge

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety; Responsible Charge

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public; Undertake Assignments Only When Qualified

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public; Undertake Assignments Only When Qualified

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public; Undertake Assignments Only When Qualified

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public; Undertake Assignments Only When Qualified

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Public Safety; Responsible Charge; Professional Competency

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Public Safety; Responsible Charge; Professional Competency

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Public Safety; Responsible Charge; Professional Competency

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Public Safety; Responsible Charge; Professional Competency

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Hold Paramount the Safety, Health, and Welfare of the Public; Direction and Control Over Work Product; Responsible Charge; Undertake Assignments Only When Qualified

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Hold Paramount the Safety, Health, and Welfare of the Public; Direction and Control Over Work Product; Responsible Charge; Undertake Assignments Only When Qualified

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Hold Paramount the Safety, Health, and Welfare of the Public; Direction and Control Over Work Product; Responsible Charge; Undertake Assignments Only When Qualified

Normative edge (fulfillsObligation)
type: Derivation
comment: property=fulfillsObligation; action's fulfillsObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Perform Services Within Competence

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Responsible Charge

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Responsible Charge

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Responsible Charge

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work

Normative edge (violatesObligation)
type: Derivation
comment: property=violatesObligation; action's violatesObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Credit and Attribution for Engineering Work

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Normative edge (fulfillsObligation)
type: Derivation
comment: property=fulfillsObligation; action's fulfillsObligation text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Direction and Control Over Work Product; Perform Services Within Competence

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Normative edge (guidedByPrinciple)
type: Derivation
comment: property=guidedByPrinciple; action's guidedByPrinciple text resolved to the case Obligation/Principle individual(s) by embedding shortlist + LLM multi-select (obligation-engagement grounding)
value: Professional Competency; Public Safety

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Environmental Engineer

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Environmental Engineer

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Environmental Engineer

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Environmental Engineer

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (obligatedParty)
type: Derivation
comment: property=obligatedParty; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A Responsible Charge

Participant edge (possessedBy)
type: Derivation
comment: property=possessedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Participant edge (invokedBy)
type: Derivation
comment: property=invokedBy; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A AI-Assisted Design

Participant edge (constrainedEntity)
type: Derivation
comment: property=constrainedEntity; component party text resolved to the case Agent(s) by embedding shortlist + LLM select
value: Engineer A

Actor relationship edge (has_client)
type: Derivation
comment: relation_type=has_client; property=hasClient
generated at time: 2026-06-05T09:35:08.607595+00:00
value: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W

Actor relationship edge (peer)
type: Derivation
comment: relation_type=peer; property=professionalPeerOf
generated at time: 2026-06-05T09:35:08.607776+00:00
value: Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts

Actor relationship edge (reviewed_by)
type: Derivation
comment: relation_type=reviewed_by; property=workReviewedBy
generated at time: 2026-06-05T09:35:08.615195+00:00
value: Engineer A appears to be operating in a compromised manner -- namely, without the help of Engineer B

Actor relationship edge (peer)
type: Derivation
comment: relation_type=peer; property=professionalPeerOf
generated at time: 2026-06-05T09:35:08.610216+00:00
value: Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts

Resource edge (availableTo)
type: Derivation
comment: property=availableTo; resource used_by text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A

Resource edge (availableTo)
type: Derivation
comment: property=availableTo; resource used_by text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A

Resource edge (availableTo)
type: Derivation
comment: property=availableTo; resource used_by text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A used AI-assisted drafting tools to generate preliminary engineering design documents but did not disclose this to Client W when submitting the plans.

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A used a new AI-assisted drafting tool without prior experience and conducted only a high-level review of the generated design documents

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A did not proactively disclose to Client W that AI tools substantially contributed to the contaminant report and design documents

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A's AI-generated contaminant report did not include citations of pertinent documents of technical authority

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A used AI software to generate the initial draft of the contaminant report but did not disclose this to Client W

R->P->O edge: adheresToPrinciple
type: Derivation
value: AI-generated design documents submitted by Engineer A omitted key safety features required by local regulations

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A applied their professional seal to engineering design documents generated primarily by AI tools after only a cursory review

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A did not disclose the use of AI tools to Client W in either the report or the design documents

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A sealed and submitted AI-generated design documents after only a high-level review, without the substantive involvement in design and development required by responsible charge

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A's insufficient review of AI-generated design documents resulted in omitted safety features and misaligned dimensions that could cause regulatory noncompliance and safety hazards

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A used an AI drafting tool without prior experience or understanding of its accuracy limitations, producing design documents with technical errors that the engineer did not detect during review.

R->P->O edge: adheresToPrinciple
type: Derivation
value: When Engineer B retired and became unavailable, Engineer A substituted AI software for the quality assurance review function that Engineer B had previously provided, without seeking alternative peer review or supervisory oversight.

R->P->O edge: adheresToPrinciple
type: Derivation
value: When Engineer B became unavailable due to retirement, Engineer A proceeded with AI-assisted design work without seeking alternative review mechanisms

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A conducted only a cursory review of AI-generated design documents despite having no prior experience with the AI drafting tool

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A conducted a more thorough review of the AI-generated report, cross-checking key facts against professional journal articles and verifying phrasing

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A accepted AI-generated design documents after only a high-level review without outlining solution guidelines, critically challenging outputs, or verifying that the AI-generated design met independent professional standards

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A uploaded Client W's proprietary project information into a public-domain open-source AI interface without obtaining prior consent from Client W

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A used open-source AI language processing software to generate the initial contaminant report draft and performed a thorough review, cross-checking key facts against professional sources and making textual adjustments

R->P->O edge: adheresToPrinciple
type: Derivation
value: Engineer A made minor wording adjustments to AI-generated report text to personalize it and did not disclose AI authorship

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A accepted AI-generated design documents after only a high-level review without outlining solution guidelines, critically challenging outputs, or verifying that the AI-generated design met independent professional standards

R->P->O edge: derivedFromPrinciple
type: Derivation
value: When Engineer B retired and became unavailable, Engineer A substituted AI software for the quality assurance review function that Engineer B had previously provided

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A's AI-generated contaminant report did not include citations of pertinent documents of technical authority

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A uploaded Client W's proprietary project information into a public-domain open-source AI interface without obtaining prior consent from Client W

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A conducted only a cursory review of AI-generated design documents despite having no prior experience with the AI drafting tool, resulting in submission of plans with misaligned dimensions and omitted safety features.

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A used a new AI-assisted drafting tool without prior experience and conducted only a high-level review of the generated design documents, failing to detect misaligned dimensions and omitted safety features

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A made minor wording adjustments to AI-generated report text to personalize it and did not disclose AI authorship, effectively presenting AI-generated content as independently authored professional writing.

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A sealed and submitted AI-generated design documents after only a high-level review, without the substantive involvement in design and development required by responsible charge

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A conducted a more thorough review of the AI-generated report, cross-checking key facts against professional journal articles and verifying phrasing

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A used AI software to generate the initial draft of the contaminant report but did not disclose this to Client W, submitting the report without citing the AI software or its large language models.

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A conducted a more thorough review of the AI-generated report, cross-checking key facts against professional journal articles and verifying phrasing, demonstrating partial but not complete satisfaction of the verification obligatio

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A applied their professional seal to engineering design documents generated primarily by AI tools after only a cursory review

R->P->O edge: derivedFromPrinciple
type: Derivation
value: AI-generated design documents submitted by Engineer A omitted key safety features required by local regulations, creating a potential public safety risk

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A did not proactively disclose to Client W that AI tools substantially contributed to the contaminant report and design documents

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A's insufficient review of AI-generated design documents resulted in omitted safety features and misaligned dimensions that could cause regulatory noncompliance and safety hazards, violating the paramount obligation to protect publ

R->P->O edge: derivedFromPrinciple
type: Derivation
value: Engineer A used AI-assisted drafting tools to generate preliminary engineering design documents but did not disclose this to Client W when submitting the plans.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to exercise genuine direction and control over the AI-assisted drafting tool by outlining solution guidelines and constraints, critically challenging outputs, and verifying results before accepting the AI-generated

R->P->O edge: hasObligation
type: Derivation
value: When Engineer B retired and became unavailable, Engineer A was obligated to identify and implement an adequate alternative quality assurance process for their professional work products rather than substituting an unfamiliar AI tool

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to include citations to pertinent documents of technical authority in the AI-assisted contaminant report submitted to Client W.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to obtain prior consent from Client W before uploading Client W's proprietary project information into a public-domain open-source AI interface.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to conduct a thorough and competent review of the AI-generated engineering design documents, sufficient to identify regulatory non-compliance and technical errors, before submitting those documents to Client W.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to accurately represent the AI-generated origin of the contaminant report content and to refrain from presenting AI-generated text as their own original intellectual work

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to conduct a comprehensive, experience-based verification of the AI-generated design documents with active involvement in the design and development process before sealing and submitting them.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to exercise direction and control over the AI language processing tool used to generate the contaminant report draft

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to disclose to Client W that AI software was used to generate the initial draft of the contaminant report, including the use of large language models, before or at the time of submission.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to conduct a thorough and competent review of the AI-generated contaminant report before submission

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to apply their professional seal to the engineering design documents only after conducting a review sufficient to take genuine professional responsibility for the content

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to verify that the AI-generated design documents included all safety features required by local regulations before submitting them to Client W.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to proactively disclose to Client W that AI language processing software substantially contributed to the contaminant report.

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to ensure that the engineering design documents submitted to Client W included all safety features required by local regulations before submission

R->P->O edge: hasObligation
type: Derivation
value: Engineer A was obligated to disclose to Client W that AI-assisted drafting tools were used to generate the preliminary engineering design documents before or at the time of submission.

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public safety; regulatory compliance

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public safety; regulatory compliance

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public affected by the design

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public affected by the design

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public users of the groundwater infrastructure

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public users of the groundwater infrastructure

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public safety

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W; public safety

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (affects)
type: Derivation
comment: property=affects; state affectedParties text resolved to the case Agent(s) by embedding shortlist + LLM multi-select
value: Engineer A; Client W

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI software is used to generate a draft report, design document, or other professional work product

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not omit disclosure of AI use where professional standards or client expectations require transparency

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not seal or submit AI-generated work without thorough independent review

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI tool use to clients and relevant parties

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to verify accuracy, originality, and completeness of AI-generated content

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI software is used to generate a draft report, design document, or other professional work product

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Engineer A using AI software to generate the initial draft report and submitting it to Client W with a professional seal

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not omit disclosure of AI use where professional standards or client expectations require transparency

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not seal or submit AI-generated work without thorough independent review

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI tool use to clients and relevant parties

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to verify accuracy, originality, and completeness of AI-generated content

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tools are used to generate or substantially draft a professional work product

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent AI-generated content as entirely self-authored without disclosure

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not seal or certify work without disclosing the role of AI in its production where standards require

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to correct any false impression created by non-disclosure

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI use to clients and relevant parties

State edge (terminatedByEvent)
type: Derivation
comment: property=terminatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Disclosure of AI use is made to the client or relevant parties

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI software is used to generate a draft report, design document, or other professional work product

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Engineer A using AI language processing software to draft the groundwater monitoring report and submitting it to Client W

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not omit disclosure of AI use where professional standards or client expectations require transparency

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not seal or submit AI-generated work without thorough independent review

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI tool use to clients and relevant parties

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to verify accuracy, originality, and completeness of AI-generated content

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Confidential client data uploaded to an open or third-party platform

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not represent the work product as fully confidential if data was exposed

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not continue using the platform with client data absent consent

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to assess and mitigate downstream confidentiality risks

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent outputs as professionally validated without adequate review

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not rely on tool outputs without independent verification when tool behavior is not fully understood

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose use of unfamiliar tools to clients or supervisors where output reliability is uncertain

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to conduct thorough verification of tool outputs before relying on them

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tools substantially contributed to the work product

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Engineer A entering information gathered from Client W into open-source AI software

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not represent AI-generated content as solely the product of the professional's own analysis without disclosure

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must include citations and attribution consistent with professional standards

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to disclose substantial AI contributions to clients

State edge (terminatedByEvent)
type: Derivation
comment: property=terminatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Disclosure of AI use made to client

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Client W identifying misaligned dimensions and omission of required safety features in the AI-generated design documents

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to assess whether deficiencies create safety or regulatory compliance risks

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to assess whether deficiencies create safety or regulatory compliance risks

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tool used to generate technical plans or documents

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not affix signature or seal to AI-generated documents reviewed only at a high level

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to conduct experience-based quality assurance review

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to refrain from sealing or signing documents not under proper direction and control

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Mentor or supervisor retires, resigns, or otherwise becomes unavailable

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not proceed with work requiring mentorship support without establishing an alternative

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to identify alternative quality assurance mechanisms

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to seek additional support before undertaking work that previously required mentorship

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Client W identifying that required safety features were omitted from the AI-generated design documents

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to assess whether deficiencies create safety or regulatory compliance risks

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tool used to generate technical plans or documents

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Client W's discovery of omitted safety features and misaligned dimensions in the design documents

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not affix signature or seal to AI-generated documents reviewed only at a high level

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to conduct experience-based quality assurance review

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to refrain from sealing or signing documents not under proper direction and control

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to assess whether deficiencies create safety or regulatory compliance risks

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Reliance on AI or other tools substitutes for engineering judgment

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not delegate engineering judgment entirely to AI tools

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to make engineering decisions personally or through supervised subordinates

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to refrain from sealing documents not under genuine direction and control

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Reliance on AI or other tools substitutes for engineering judgment

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Must not delegate engineering judgment entirely to AI tools

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to make engineering decisions personally or through supervised subordinates

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Duty to refrain from sealing documents not under genuine direction and control

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tools are used to generate or substantially draft a professional work product

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent AI-generated content as entirely self-authored without disclosure

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not seal or certify work without disclosing the role of AI in its production where standards require

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to correct any false impression created by non-disclosure

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI use to clients and relevant parties

State edge (terminatedByEvent)
type: Derivation
comment: property=terminatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Disclosure of AI use is made to the client or relevant parties

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: AI tools are used to generate or substantially draft a professional work product

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent AI-generated content as entirely self-authored without disclosure

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose AI use to clients and relevant parties

State edge (terminatedByEvent)
type: Derivation
comment: property=terminatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Disclosure of AI use is made to the client or relevant parties

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Engineer A's decision to use new open-source AI drafting software without prior experience

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent outputs as professionally validated without adequate review

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not rely on tool outputs without independent verification when tool behavior is not fully understood

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose use of unfamiliar tools to clients or supervisors where output reliability is uncertain

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to conduct thorough verification of tool outputs before relying on them

State edge (activatedByEvent)
type: Derivation
comment: property=activatedByEvent; description resolved to the endpoint by embedding shortlist + LLM select
value: Engineer A electing to use a newly released AI-assisted drafting tool without prior experience or established verification protocols for its outputs

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not represent outputs as professionally validated without adequate review

State edge (activatesConstraint)
type: Derivation
comment: property=activatesConstraint; description resolved to the endpoint by embedding shortlist + LLM select
value: Should not rely on tool outputs without independent verification when tool behavior is not fully understood

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to disclose use of unfamiliar tools to clients or supervisors where output reliability is uncertain

State edge (activatesObligation)
type: Derivation
comment: property=activatesObligation; description resolved to the endpoint by embedding shortlist + LLM select
value: Obligation to conduct thorough verification of tool outputs before relying on them

submission of both deliverables to Client W before Client W's review and identification of issues
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: When Client W reviewed the draft report ... Client W, however, noticed several issues with the AI-generated design documents ... Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans
from entity text: submission of both deliverables to Client W
owl time property: time:intervalBefore
to entity text: Client W's review and identification of issues
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Client W s review and identification of issues
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions. Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions. Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A ... submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Engineer A ... submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.

Temporal relation edge (fromEntity)
type: Derivation
comment: property=fromEntity; temporal relation's fromEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software

Temporal relation edge (toEntity)
type: Derivation
comment: property=toEntity; temporal relation's toEntity text resolved to the case Action/Event individual by embedding shortlist + LLM select
value: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software

Client W Project Client
type: ClientRole
type: NamedIndividual
actor: Client W
case involvement: Commissioned Engineer A to prepare a contaminant report and engineering design documents for a groundwater infrastructure site. Reviewed deliverables, identified quality inconsistencies in the report, and raised concerns about errors and regulatory omissions in the design documents.
concept category: Role
confidence: 0.95
other attribute: project_type: Groundwater infrastructure modification
other attribute: review_action: Identified misaligned dimensions and omitted safety features in design documents
role category: provider_client
role class: Client Role
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations
text references: Client W reviewed the draft report
text references: was retained by Client W to prepare a comprehensive report addressing the manufacture, use, and characteristics of an organic compound
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:26.869728+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Client Role'
matched ontology class: ClientRole
matched ontology label: Client Role
matches existing: true
source text: was retained by Client W to prepare a comprehensive report addressing the manufacture, use, and characteristics of an organic compound
synthesis literal: caseInvolvement
synthesis literal: confidence
synthesis literal: roleCategory
synthesis literal: roleClass
synthesis literal: textReferences
comment: Commissioned Engineer A to prepare a contaminant report and engineering design documents for a groundwater infrastructure site. Reviewed deliverables, identified quality inconsistencies in the report, and raised concerns about errors and regulatory omissions in the design documents.
generated at time: 2026-06-03T13:59:26.869728+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Authorship Representation
type: AIAuthorshipRepresentationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Authorship Representation Capability
capability statement: Engineer A possessed the capability to accurately represent the AI-generated origin of the contaminant report and design documents but did not proactively disclose AI authorship to Client W, raising transparency concerns.
case context: Engineer A used AI tools to generate both the contaminant report and design documents but did not disclose the AI contribution to Client W, who later identified inconsistencies and design errors.
concept category: Capability
confidence: 0.85
demonstrated through: Failure to proactively disclose to Client W that AI software substantially generated the contaminant report and design documents, which contributed to client confusion when inconsistencies were identified.
proficiency level: intermediate
text references: Given that Client W identified issues in the engineering design and questioned inconsistencies in the report, proactive disclosure could have prevented misunderstandings and strengthened trust.
text references: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A possessed the capability to accurately represent the AI-generated origin of the contaminant report and design documents but did not proactively disclose AI authorship to Client W, raising transparency concerns.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Direction Control Design
type: AIDirectionandControlCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Direction and Control Capability
capability statement: Engineer A failed to exercise adequate AI direction and control capability over the AI-assisted drafting tool used for engineering design documents, conducting only a high-level review and not outlining solution guidelines or constraints before relying on AI-generated outputs.
case context: Engineer A used a new AI-assisted drafting tool to generate preliminary engineering design documents and elected to conduct only a high-level review, without the comprehensive verification process required for responsible charge.
concept category: Capability
confidence: 0.87
demonstrated through: Failure to outline solution guidelines and constraints for the AI-assisted drafting tool, and failure to critically challenge AI-generated design outputs, resulting in undetected dimension errors and omitted safety features.
proficiency level: basic
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
text references: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to exercise adequate AI direction and control capability over the AI-assisted drafting tool used for engineering design documents, conducting only a high-level review and not outlining solution guidelines or constraints before relying on AI-generated outputs.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Direction Control Report
type: AIDirectionandControlCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Direction and Control Capability
capability statement: Engineer A demonstrated partial exercise of AI direction and control capability for the contaminant report by performing a thorough review, cross-checking key facts, and making adjustments, but did not fully apply this capability to the AI-assisted design documents.
case context: Engineer A used AI language processing software to draft a contaminant report and conducted a review sufficient to maintain direction and control over that document, but applied only a high-level review to the AI-generated design documents.
concept category: Capability
confidence: 0.85
demonstrated through: Thorough review and cross-checking of the AI-generated contaminant report against professional sources, with adjustments to text, satisfying direction and control requirements for that work product.
proficiency level: intermediate
text references: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control, as required by Code section II.2.b
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control, as required by Code section II.2.b
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A demonstrated partial exercise of AI direction and control capability for the contaminant report by performing a thorough review, cross-checking key facts, and making adjustments, but did not fully apply this capability to the AI-assisted design documents.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Disclosure
type: AIToolDisclosureCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Tool Disclosure Capability
capability statement: Engineer A lacked or failed to exercise the capability to recognize that use of AI software to generate the report draft and design documents triggered a professional disclosure obligation to Client W.
case context: Engineer A used open-source AI software to generate an initial report draft and preliminary design documents for Client W but did not disclose this use in either submission.
concept category: Capability
confidence: 0.9
demonstrated through: Failure to cite AI software or large language model use in either the submitted report or the engineering design documents, despite using AI tools for both deliverables.
proficiency level: basic
text references: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A lacked or failed to exercise the capability to recognize that use of AI software to generate the report draft and design documents triggered a professional disclosure obligation to Client W.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Output Verification Design
type: AIOutputVerificationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Output Verification Capability
capability statement: Engineer A failed to adequately apply AI output verification capability to the AI-generated engineering design documents, conducting only a high-level review that did not detect misaligned dimensions or omitted safety features.
case context: Engineer A reviewed AI-generated design documents at a high level only, without the comprehensive verification required to take responsible charge, resulting in submission of documents with significant errors.
concept category: Capability
confidence: 0.88
demonstrated through: High-level review of AI-generated design documents that failed to identify misaligned dimensions and omitted regulatory safety features subsequently discovered by Client W.
proficiency level: basic
text references: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement.
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions. When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions. When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to adequately apply AI output verification capability to the AI-generated engineering design documents, conducting only a high-level review that did not detect misaligned dimensions or omitted safety features.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Output Verification Report
type: AIOutputVerificationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Output Verification Capability
capability statement: Engineer A applied AI output verification capability to the contaminant report by conducting a thorough review and cross-checking key facts against professional sources, meeting the standard for responsible charge over that work product.
case context: Engineer A reviewed the AI-generated contaminant report sufficiently to maintain responsible charge, though the report still lacked required citations.
concept category: Capability
confidence: 0.85
demonstrated through: Thorough review of the AI-generated contaminant report, cross-checking against professional sources, and making textual adjustments before submission.
proficiency level: advanced
text references: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A applied AI output verification capability to the contaminant report by conducting a thorough review and cross-checking key facts against professional sources, meeting the standard for responsible charge over that work product.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Tool Disclosure
type: AIToolDisclosureCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Tool Disclosure Capability
capability statement: Engineer A possessed the capability to recognize that AI tools substantially contributed to the contaminant report and design documents and that this contribution warranted disclosure to Client W, but did not exercise this capability.
case context: Engineer A used AI tools to generate both the contaminant report and engineering design documents for Client W without disclosing the AI contribution, contrary to emerging best practices and transparency obligations.
concept category: Capability
confidence: 0.87
demonstrated through: Failure to inform Client W that AI language processing software and AI-assisted drafting tools substantially contributed to the work products delivered, despite best practices indicating such disclosure is warranted.
proficiency level: intermediate
text references: BER Case 98-3 emphasized that engineers must acknowledge significant contributions by others. AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9
text references: There are currently no universal guidelines mandating AI disclosure in engineering work, but best practices suggest informing clients when AI substantially contributes to a work product.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: There are currently no universal guidelines mandating AI disclosure in engineering work, but best practices suggest informing clients when AI substantially contributes to a work product.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A possessed the capability to recognize that AI tools substantially contributed to the contaminant report and design documents and that this contribution warranted disclosure to Client W, but did not exercise this capability.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Authorship Representation
type: AIAuthorshipRepresentationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Authorship Representation Capability
capability statement: Engineer A failed to accurately represent the AI-generated origin of the report content, presenting AI-synthesized text as professional work product without attribution, and made only minor wording adjustments to personalize AI-generated content.
case context: Engineer A used AI software to generate the initial report draft, made minor adjustments to personalize the content, and submitted the report without disclosing the AI-generated origin of the polished introductory sections.
concept category: Capability
confidence: 0.87
demonstrated through: Submission of AI-generated report draft without authorship disclosure, combined with minor wording edits intended to personalize content, resulting in a report Client W observed read as if written by two different authors.
proficiency level: basic
text references: Client W noted that the introduction discussing the contaminant's manufacture, use, and characteristics to be exceptionally polished. The Client commented that the report read as if written by two different authors
text references: Engineer A also made minor adjustments to some of the wording to personalize the content. Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A also made minor adjustments to some of the wording to personalize the content. Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to accurately represent the AI-generated origin of the report content, presenting AI-synthesized text as professional work product without attribution, and made only minor wording adjustments to personalize AI-generated content.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data AI Upload
type: ConfidentialDataPlatformConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A input Client W's proprietary site data and groundwater monitoring information into open-source AI software to generate both the contaminant report draft and the preliminary design documents, without apparent consideration of the confidentiality implications of using an open-source platform.
concept category: Constraint
confidence: 0.86
constraint class: Confidential Data Platform Constraint
constraint statement: Engineer A was constrained from uploading Client W's confidential site data and groundwater monitoring information into open-source AI software, as doing so exposed confidential client information to a third-party platform outside the protected professional relationship.
severity: high
source: NSPE Code of Ethics confidentiality provisions, professional duty to protect client information
temporal scope: At the time of AI software use for both the report and design documents
text references: Engineer A gathered the relevant information provided by Client W and relied on the AI software to synthesize the information
text references: Engineer A input the information gathered from Client W into the AI software
text references: The AI drafting software was also open-sourced.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.78
match reasoning: Via class 'Confidential Data Platform Constraint': The Confidentiality Constraint class covers boundaries on information disclosure and privacy, which encompasses this scenario. However, the specific application to open-source AI platform data upload is a variant not explicitly addressed by the existing class. Matching as a variant of Confidentiality Constraint at medium confidence, while defining a more specific reusable subtype for AI platform contexts.
matched ontology class: ConfidentialityConstraint
matched ontology label: Confidentiality Constraint
matches existing: true
source text: Engineer A gathered the relevant information provided by Client W and relied on the AI software to synthesize the information
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained from uploading Client W's confidential site data and groundwater monitoring information into open-source AI software, as doing so exposed confidential client information to a third-party platform outside the protected professional relationship.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data Confidentiality
type: ClientDataConfidentialityCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Client Data Confidentiality Capability
capability statement: Engineer A had the professional background to recognize that uploading client proprietary information to a public-domain AI interface required prior client consent, but failed to exercise this capability before uploading Client W's data.
case context: Engineer A used an open-source AI language processing tool to draft a contaminant report and uploaded Client W's confidential project information without obtaining prior consent.
concept category: Capability
confidence: 0.85
demonstrated through: Failure to obtain consent before uploading Client W's proprietary project information into an open-source AI interface, resulting in a confidentiality breach.
proficiency level: intermediate
text references: The facts here do not indicate Engineer A obtained permission from Client W to use the private information in the public domain.
text references: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.72
match reasoning: Via class 'Client Data Confidentiality Capability': The existing Confidentiality Scope Reasoning Capability addresses reasoning about limits of confidentiality obligations, but that class focuses on distinguishing between protecting review contents and procedurally improper conduct. This capability is more specifically about recognizing when tool use exposes client data to public domains and obtaining consent, which is a distinct application of confidentiality reasoning in the AI tool context. A medium-confidence match to the parent concept is appropriate, but the AI-tool-specific data upload dimension is sufficiently distinct to warrant a new class.
matched ontology class: ConfidentialityScopeReasoningCapability
matched ontology label: Confidentiality Scope Reasoning Capability
matches existing: true
source text: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A had the professional background to recognize that uploading client proprietary information to a public-domain AI interface required prior client consent, but failed to exercise this capability before uploading Client W's data.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Direction Control
type: ResponsibleChargeDirectionConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A used an AI-assisted drafting tool new to the market and conducted only a high-level review of the output, resulting in misaligned dimensions and omitted safety features. Engineer B's retirement had removed the quality assurance oversight Engineer A had previously relied upon.
concept category: Constraint
confidence: 0.9
constraint class: Responsible Charge Direction Constraint
constraint statement: Engineer A was required to actively direct and control the AI-assisted drafting process from conception through completion, including outlining solution guidelines and constraints before delegating to the AI tool, and critically evaluating all outputs rather than conducting only a high-level review after preparation.
severity: critical
source: NSPE Code of Ethics, Code section II.2.b; NSPE Position Statement No. 10-1778
temporal scope: Throughout the preparation and review of the AI-generated engineering design documents
text references: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement.
text references: NSPE defines 'Responsible Charge' in NSPE Position Statement No. 10-1778 as 'being actively engaged in the engineering process, from conception to completion.'
text references: Reviewing drawings or documents after preparation without involvement in the design and development process does not satisfy the definition of Responsible Charge.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was required to actively direct and control the AI-assisted drafting process from conception through completion, including outlining solution guidelines and constraints before delegating to the AI tool, and critically evaluating all outputs rather than conducting only a high-level review after preparation.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Safety Compliance
type: EngineeringDesignErrorRecognitionCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Engineering Design Error Recognition Capability
capability statement: Engineer A failed to exercise adequate engineering design error recognition capability during review of the AI-generated design documents, missing misaligned dimensions and omitted safety features that were subsequently identified by Client W.
case context: Engineer A reviewed AI-generated engineering design documents for a groundwater infrastructure modification project but conducted only a cursory review, missing regulatory deficiencies that Client W identified upon review.
concept category: Capability
confidence: 0.86
demonstrated through: Cursory review of AI-generated plans that failed to detect misaligned dimensions and the omission of key safety features required by local regulations.
proficiency level: intermediate
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations. Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Engineering Design Error Recognition Capability'
matched ontology class: EngineeringDesignErrorRecognitionCapability
matched ontology label: Engineering Design Error Recognition Capability
matches existing: true
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to exercise adequate engineering design error recognition capability during review of the AI-generated design documents, missing misaligned dimensions and omitted safety features that were subsequently identified by Client W.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Safety Regulatory Compliance
type: SafetyConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Client W identified that the AI-generated engineering design documents omitted key safety features required by local regulations, creating a public safety risk and requiring revision of the plans.
concept category: Constraint
confidence: 0.92
constraint class: Safety Constraint
constraint statement: Engineer A was constrained to ensure that engineering design documents submitted to Client W included all safety features required by local regulations, and submission of documents omitting those features violated this inviolable safety boundary.
severity: critical
source: Local site safety regulations, NSPE Code of Ethics public safety provisions
temporal scope: At the time of preparing and submitting engineering design documents
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Safety Constraint'
matched ontology class: SafetyConstraint
matched ontology label: Safety Constraint
matches existing: true
source text: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained to ensure that engineering design documents submitted to Client W included all safety features required by local regulations, and submission of documents omitting those features violated this inviolable safety boundary.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Seal Responsible Charge
type: ResponsibleChargeSealConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A relied on AI-assisted drafting tools to generate the preliminary design documents and performed only a cursory review before submission, raising the question of whether responsible charge was exercised as required for valid seal application.
concept category: Constraint
confidence: 0.85
constraint class: Responsible Charge Seal Constraint
constraint statement: Engineer A was constrained to apply their professional seal to the engineering design documents only if they had exercised genuine responsible charge over the preparation of those documents, which a cursory post-preparation review of AI-generated output did not satisfy.
severity: critical
source: State engineering seal law, NSPE responsible charge definition, NSPE Code of Ethics
temporal scope: At the time of sealing and submitting engineering design documents
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft, but applied their seal consistent with state law
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained to apply their professional seal to the engineering design documents only if they had exercised genuine responsible charge over the preparation of those documents, which a cursory post-preparation review of AI-generated output did not satisfy.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Seal Verification
type: ResponsibleChargeVerificationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Responsible Charge Verification Capability
capability statement: Engineer A failed to exercise adequate responsible charge verification capability before sealing the AI-generated design documents, conducting only a cursory review insufficient to identify regulatory deficiencies.
case context: Engineer A bore formal responsible charge over the AI-generated design documents and applied their seal, but the review conducted was insufficient to detect significant regulatory and dimensional errors.
concept category: Capability
confidence: 0.87
demonstrated through: Application of professional seal to design documents following only a cursory review, after which Client W identified misaligned dimensions and omitted safety features.
proficiency level: basic
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: Engineer A was obligated to apply their professional seal to the engineering design documents only after conducting a review sufficient to take general responsibility for the work
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to exercise adequate responsible charge verification capability before sealing the AI-generated design documents, conducting only a cursory review insufficient to identify regulatory deficiencies.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Domain Expertise Environmental
type: DomainExpertise
type: NamedIndividual
possessed by: Engineer A
capability class: Domain Expertise
capability statement: Engineer A possessed domain expertise as an experienced environmental engineer with strong technical expertise in groundwater monitoring data analysis and contaminant risk assessment, which was sufficient to maintain direction and control over the AI-generated contaminant report.
case context: Engineer A was retained as an experienced environmental engineer with several years of experience and strong technical expertise, which distinguished the situation from BER Case 98-3 where the engineer lacked relevant competence entirely.
concept category: Capability
confidence: 0.87
demonstrated through: Application of environmental engineering expertise to review, cross-check, and adjust the AI-generated contaminant report, and recognition of site-specific conditions requiring adjustment in the design documents.
proficiency level: advanced
text references: Engineer A, as an experienced environmental engineer, was competent to analyze groundwater monitoring data and assess contaminant risks.
text references: The facts specifically note Engineer A has 'several years of experience' and 'strong technical expertise.' But the facts also note Engineer A appears to be operating in a compromised manner
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Domain Expertise'
matched ontology class: DomainExpertise
matched ontology label: Domain Expertise
matches existing: true
source text: Engineer A, as an experienced environmental engineer, was competent to analyze groundwater monitoring data and assess contaminant risks.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A possessed domain expertise as an experienced environmental engineer with strong technical expertise in groundwater monitoring data analysis and contaminant risk assessment, which was sufficient to maintain direction and control over the AI-generated contaminant report.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Environmental Domain Competence
type: DomainExpertise
type: NamedIndividual
possessed by: Engineer A
capability class: Domain Expertise
capability statement: Engineer A possessed domain expertise in environmental engineering, including groundwater monitoring and contaminant analysis, developed over several years of licensed professional practice and site observation.
case context: Engineer A was retained as a licensed environmental engineer to prepare a contaminant report and engineering design documents for groundwater infrastructure modifications, drawing on over a year of site observation.
concept category: Capability
confidence: 0.85
demonstrated through: Performance of groundwater monitoring data analysis over more than a year at the site, and preparation of a comprehensive contaminant report addressing manufacture, use, and characteristics of an emerging organic contaminant.
proficiency level: advanced
text references: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report addressing the manufacture, use, and characteristics of an organic compound identified as an emerging contaminant of concern.
text references: This work required Engineer A to perform an analysis of groundwater monitoring data from a site Engineer A had been observing for over a year.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Domain Expertise'
matched ontology class: DomainExpertise
matched ontology label: Domain Expertise
matches existing: true
source text: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report addressing the manufacture, use, and characteristics of an organic compound identified as an emerging contaminant of concern.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A possessed domain expertise in environmental engineering, including groundwater monitoring and contaminant analysis, developed over several years of licensed professional practice and site observation.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentor Loss Response
type: MentorshipGapAdaptationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Mentorship Gap Adaptation Capability
capability statement: Engineer A recognized the quality assurance gap created by Engineer B's retirement but selected an inadequate substitute mechanism, relying on unfamiliar AI tools without implementing alternative professional review.
case context: When Engineer B retired and became unavailable, Engineer A faced delivery obligations for both a technical report and design documents without the quality assurance support that had previously compensated for Engineer A's lower confidence in technical writing.
concept category: Capability
confidence: 0.88
demonstrated through: Decision to use open-source AI software as a substitute for Engineer B's mentorship and quality assurance review, without prior experience with the tool and without arranging alternative professional oversight.
proficiency level: basic
text references: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing. Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
text references: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents. The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing. Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A recognized the quality assurance gap created by Engineer B's retirement but selected an inadequate substitute mechanism, relying on unfamiliar AI tools without implementing alternative professional review.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentorship Gap Adaptation
type: MentorshipGapAdaptationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Mentorship Gap Adaptation Capability
capability statement: Engineer A failed to exercise mentorship gap adaptation capability after Engineer B retired, continuing to rely on AI-generated outputs without implementing an adequate alternative quality assurance mechanism to replace Engineer B's oversight role.
case context: Engineer B, who had served as mentor and quality assurance reviewer for Engineer A, retired and became unavailable. Engineer A did not replace this oversight function before proceeding with AI-assisted work products.
concept category: Capability
confidence: 0.88
demonstrated through: Failure to identify and implement an alternative quality assurance process after Engineer B became unavailable, resulting in reliance on AI-generated design documents without adequate independent review.
proficiency level: basic
text references: Engineer A, as the engineer in Responsible Charge of the project, is required to provide an experienced-based quality assurance review, engaging in critical discussions, mentorship, and professional development -- elements that AI cannot replicate.
text references: the facts also note Engineer A appears to be operating in a compromised manner -- namely, without the help of Engineer B -- such that Engineer A relied on the AI-generated plans and specifications without proper oversight.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: the facts also note Engineer A appears to be operating in a compromised manner -- namely, without the help of Engineer B -- such that Engineer A relied on the AI-generated plans and specifications without proper oversight.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to exercise mentorship gap adaptation capability after Engineer B retired, continuing to rely on AI-generated outputs without implementing an adequate alternative quality assurance mechanism to replace Engineer B's oversight role.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report AI Verification
type: AIOutputVerificationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: AI Output Verification Capability
capability statement: Engineer A exercised partial AI output verification capability for the report by cross-checking key facts and verifying phrasing, but did not extend equivalent verification to the engineering design documents.
case context: Engineer A applied different levels of review to the two AI-generated deliverables, conducting a more thorough review of the report but only a cursory review of the design documents, which contained regulatory deficiencies identified by Client W.
concept category: Capability
confidence: 0.88
demonstrated through: Thorough fact-checking and search engine verification of report content versus cursory review of AI-generated design documents that missed misaligned dimensions and omitted safety features.
proficiency level: intermediate
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: Not being familiar with the full functionality of the AI software, including the accuracy and originality of AI-generated text, Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:21.353968+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Not being familiar with the full functionality of the AI software, including the accuracy and originality of AI-generated text, Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A exercised partial AI output verification capability for the report by cross-checking key facts and verifying phrasing, but did not extend equivalent verification to the engineering design documents.
generated at time: 2026-06-03T14:06:21.353968+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report Authorship Representation
type: Non-Deception
type: NamedIndividual
constrained entity: Engineer A
case context: Client W observed that the report read as if written by two different authors, with the AI-generated introduction appearing exceptionally polished compared to the sections Engineer A personally revised, suggesting the undisclosed AI authorship was perceptible and potentially misleading.
concept category: Constraint
confidence: 0.9
constraint class: Non-Deception
constraint statement: Engineer A was constrained by the non-deception principle from presenting AI-generated report content as their own original professional work product without disclosure, because doing so created a false impression about the authorship and intellectual origin of the submitted report.
severity: high
source: NSPE Code of Ethics non-deception and honesty provisions
temporal scope: At the time of report submission and throughout the client relationship
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
text references: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Non-Deception'
matched ontology class: Non Deception
matched ontology label: Non-Deception
matches existing: true
source text: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained by the non-deception principle from presenting AI-generated report content as their own original professional work product without disclosure, because doing so created a false impression about the authorship and intellectual origin of the submitted report.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report Citation Omission
type: TechnicalCitationConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: The AI-generated contaminant report submitted to Client W did not include citations to pertinent documents of technical authority, which Engineer A failed to add during review.
concept category: Constraint
confidence: 0.88
constraint class: Technical Citation Constraint
constraint statement: Engineer A was required to include citations to pertinent documents of technical authority in the AI-assisted contaminant report, and the omission of such citations from the AI-generated content constituted a failure to meet the professional standard of care required by NSPE Code section III.9.
severity: medium
source: NSPE Code of Ethics, Code section III.9
temporal scope: At the time of preparing and submitting the contaminant report to Client W
text references: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority. Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority. Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was required to include citations to pertinent documents of technical authority in the AI-assisted contaminant report, and the omission of such citations from the AI-generated content constituted a failure to meet the professional standard of care required by NSPE Code section III.9.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Responsible Charge Verification Design
type: ResponsibleChargeVerificationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Responsible Charge Verification Capability
capability statement: Engineer A failed to apply responsible charge verification capability to the AI-generated design documents, substituting a high-level review for the comprehensive, experience-based verification required to support sealing and submission.
case context: Engineer A bore formal responsible charge over the AI-assisted design documents but did not conduct a review sufficient to satisfy the NSPE definition of responsible charge, resulting in submission of documents with regulatory and safety deficiencies.
concept category: Capability
confidence: 0.9
demonstrated through: Sealing and submitting AI-generated design documents after only a high-level review, without the active involvement in design and development required by the definition of responsible charge.
proficiency level: basic
text references: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
text references: NSPE defines 'Responsible Charge' in NSPE Position Statement No. 10-1778 as 'being actively engaged in the engineering process, from conception to completion. Engineering decisions must be personally made by the professional engineer or by others over which the professional engineer provides supervisory direction and control authority. Reviewing drawings or documents after preparation without involvement in the design and development process does not satisfy the definition of Responsible Charge.'
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A failed to apply responsible charge verification capability to the AI-generated design documents, substituting a high-level review for the comprehensive, experience-based verification required to support sealing and submission.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Safety Feature Recognition
type: SafetyFeatureRecognitionCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Safety Feature Recognition Capability
capability statement: Engineer A, as an experienced environmental engineer, possessed the technical capability to identify required safety features in engineering design documents but failed to apply this capability during review of the AI-generated design documents.
case context: Engineer A reviewed AI-generated engineering design documents at a high level only, failing to identify omitted safety features required for regulatory compliance before submitting the documents to Client W.
concept category: Capability
confidence: 0.85
demonstrated through: Failure to detect omitted safety features required by local regulations in the AI-generated design documents, which were subsequently identified by Client W.
proficiency level: advanced
text references: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
text references: failure to detect misaligned dimensions and omitted safety features further indicates that Engineer A did not exercise sufficient diligence. The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.74
match reasoning: Via class 'Safety Feature Recognition Capability': The existing Engineering Design Error Recognition Capability covers identifying errors, omissions, and deficiencies in engineering plans including safety implications. The present capability is a more specific instantiation focused on safety feature recognition and regulatory compliance checking. A medium-confidence match to the existing class is appropriate, but the regulatory compliance and safety feature identification dimension is sufficiently distinct to warrant a separate class for precision.
matched ontology class: EngineeringDesignErrorRecognitionCapability
matched ontology label: Engineering Design Error Recognition Capability
matches existing: true
source text: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A, as an experienced environmental engineer, possessed the technical capability to identify required safety features in engineering design documents but failed to apply this capability during review of the AI-generated design documents.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Technical Citation
type: TechnicalCitationCapability
type: NamedIndividual
possessed by: Engineer A
capability class: Technical Citation Capability
capability statement: Engineer A, as an experienced environmental engineer, possessed the capability to identify and include citations to pertinent documents of technical authority in professional reports, but did not apply this capability when reviewing the AI-generated contaminant report.
case context: The AI-generated contaminant report submitted to Client W lacked citations to pertinent technical authority documents, which Engineer A failed to supply during review.
concept category: Capability
confidence: 0.82
demonstrated through: Failure to ensure the AI-generated contaminant report included citations to pertinent documents of technical authority before submission to Client W.
proficiency level: intermediate
text references: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority. Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:06.673267+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority. Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
synthesis literal: capabilityClass
synthesis literal: capabilityStatement
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: demonstratedThrough
synthesis literal: proficiencyLevel
synthesis literal: textReferences
comment: Engineer A, as an experienced environmental engineer, possessed the capability to identify and include citations to pertinent documents of technical authority in professional reports, but did not apply this capability when reviewing the AI-generated contaminant report.
generated at time: 2026-06-03T14:11:06.673267+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer B Mentor Engineer
type: MentorEngineer
type: NamedIndividual
actor: Engineer B
case involvement: Served as mentor and supervisor to Engineer A, providing guidance and quality assurance reviews of report drafts. Recently retired and became unavailable, removing the professional check that Engineer A had depended upon.
concept category: Role
confidence: 0.9
other attribute: relationship_to_engineer_a: Mentor and supervisor
other attribute: status: Retired
role category: professional_peer
role class: Mentor Engineer
text references: Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts
text references: Engineer B recently retired and was no longer available to Engineer A in a work capacity
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:26.869728+00:00
first discovered in case: 7
match confidence: 0.78
match reasoning: Via class 'Mentor Engineer': Mentor Engineer is a specialization of Professional Peer Role. The ontology lists Professional Peer Role as covering collegial relationships with mentoring and review obligations, which directly describes Engineer B's function. A distinct leaf class is warranted because the mentoring and supervisory quality-assurance dimension is more specific than generic peer review.
matched ontology class: ProfessionalPeerRole
matched ontology label: Professional Peer Role
matches existing: true
source text: Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts
synthesis literal: caseInvolvement
synthesis literal: confidence
synthesis literal: roleCategory
synthesis literal: roleClass
synthesis literal: textReferences
comment: Served as mentor and supervisor to Engineer A, providing guidance and quality assurance reviews of report drafts. Recently retired and became unavailable, removing the professional check that Engineer A had depended upon.
generated at time: 2026-06-03T13:59:26.869728+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer B's mentorship and QA reviews before Engineer B's retirement
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
from entity text: Engineer B's mentorship and QA reviews
owl time property: time:intervalBefore
to entity: Supervisor Retirement
to entity text: Engineer B's retirement
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Engineer B s retirement
interval before: Supervisor Retirement
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Local Site Safety Regulations
type: LegalResource
type: NamedIndividual
available to: Engineer A
concept category: Resource
confidence: 0.83
created by: Local regulatory authority
document title: Local regulatory requirements for groundwater infrastructure design safety features
resource class: Legal Resource
text references: an omission of key safety features required by local regulations
text references: ensuring that all elements satisfied the necessary professional and regulatory standards
used by: Engineer A
used in context: Client W identified that the AI-generated design documents omitted key safety features required by local regulations, establishing the regulatory standard against which Engineer A's design documents were found deficient.
version: Applicable local regulations at time of case
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:19.637051+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Legal Resource'
matched ontology class: LegalResource
matched ontology label: Legal Resource
matches existing: true
source text: an omission of key safety features required by local regulations
synthesis literal: confidence
synthesis literal: createdBy
synthesis literal: documentTitle
synthesis literal: resourceClass
synthesis literal: textReferences
synthesis literal: usedInContext
synthesis literal: version
comment: Client W identified that the AI-generated design documents omitted key safety features required by local regulations, establishing the regulatory standard against which Engineer A's design documents were found deficient.
generated at time: 2026-06-03T13:59:19.637051+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

NSPE Code of Ethics
type: ProfessionalCode
type: NamedIndividual
available to: Engineer A
concept category: Resource
confidence: 0.95
created by: National Society of Professional Engineers
document title: NSPE Code of Ethics for Engineers
resource class: Professional Code
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A did not cite their use of AI-software or its large language models
text references: Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report
used by: Engineer A
used in context: Governs Engineer A's professional obligations regarding competence, responsible use of AI tools, disclosure to clients, accuracy of sealed documents, and public safety in engineering deliverables.
version: Current
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:19.637051+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Professional Code'
matched ontology class: ProfessionalCode
matched ontology label: Professional Code
matches existing: true
source text: Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report
synthesis literal: confidence
synthesis literal: createdBy
synthesis literal: documentTitle
synthesis literal: resourceClass
synthesis literal: textReferences
synthesis literal: usedInContext
synthesis literal: version
comment: Governs Engineer A's professional obligations regarding competence, responsible use of AI tools, disclosure to clients, accuracy of sealed documents, and public safety in engineering deliverables.
generated at time: 2026-06-03T13:59:19.637051+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

State Engineering Seal Law
type: LegalResource
type: NamedIndividual
available to: Engineer A
concept category: Resource
confidence: 0.85
created by: State legislature or professional licensing board
document title: State Professional Engineering Licensing Statute governing seal application
resource class: Legal Resource
text references: applied their seal consistent with state law
used by: Engineer A
used in context: Engineer A applied their professional seal to the draft report consistent with state law, making the conditions and requirements of that law directly relevant to the propriety of sealing AI-assisted work.
version: Applicable state law at time of case
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:19.637051+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Legal Resource'
matched ontology class: LegalResource
matched ontology label: Legal Resource
matches existing: true
source text: applied their seal consistent with state law
synthesis literal: confidence
synthesis literal: createdBy
synthesis literal: documentTitle
synthesis literal: resourceClass
synthesis literal: textReferences
synthesis literal: usedInContext
synthesis literal: version
comment: Engineer A applied their professional seal to the draft report consistent with state law, making the conditions and requirements of that law directly relevant to the propriety of sealing AI-assisted work.
generated at time: 2026-06-03T13:59:19.637051+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

During drafting phase, before cursory review
type: Instant

At design document submission
type: Instant

At report submission
type: Instant

During drafting phase, before thorough review
type: Instant

During design document preparation phase
type: ProperInterval

During report preparation phase
type: ProperInterval

During AI-assisted drafting phase, before submission
type: Instant

During both report and design document preparation phases
type: Instant

After receiving AI-generated design documents, before submission
type: ProperInterval

Upon Client W's review of submitted design documents
type: Instant

At design document submission
type: Instant

At report submission
type: Instant

Concurrent with project execution phase
type: ProperInterval

At project initiation, after Engineer B's retirement
type: Instant

Upon Client W's review of submitted report
type: Instant

After Client W's review of design documents
type: Instant

Before project deliverables were due, over a year into site observation
type: Instant

After receiving the AI-generated report draft, before submission
type: ProperInterval

AI generation of initial report draft before Engineer A's thorough review and cross-checking of the report
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries
from entity: AI Report Generation
from entity text: AI generation of initial report draft
owl time property: time:intervalBefore
to entity: Thorough Report Review
to entity text: Engineer A's thorough review and cross-checking of the report
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Engineer A s thorough review and cross-checking of
interval before: Thorough Report Review
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI generation of preliminary design documents before Engineer A's cursory review of design documents
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
from entity: AI Design Generation
from entity text: AI generation of preliminary design documents
owl time property: time:intervalBefore
to entity: Cursory Design Document Review
to entity text: Engineer A's cursory review of design documents
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Cursory Design Document Review
interval before: Engineer A s cursory review of design documents
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client W's identification of issues in design documents before Client W's instruction to Engineer A to revise the plans
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
from entity: Design Defect Discovery
from entity text: Client W's identification of issues in design documents
owl time property: time:intervalBefore
to entity: Revision Instruction Issued
to entity text: Client W's instruction to Engineer A to revise the plans
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Client W s instruction to Engineer A to revise the
interval before: Revision Instruction Issued
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A's cursory review of design documents before submission of design documents to Client W
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions. Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
from entity: Cursory Design Document Review
from entity text: Engineer A's cursory review of design documents
owl time property: time:intervalBefore
to entity: Design Document Submission
to entity text: submission of design documents to Client W
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Design Document Submission
interval before: submission of design documents to Client W
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A's thorough review of the report before submission of draft report to Client W
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Engineer A ... submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft
from entity: Thorough Report Review
from entity text: Engineer A's thorough review of the report
owl time property: time:intervalBefore
to entity: Draft Report Sealing and Submission
to entity text: submission of draft report to Client W
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Draft Report Sealing and Submission
interval before: submission of draft report to Client W
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer B's retirement before Engineer A's use of AI software for dual deliverables
type: TemporalRelation
type: NamedIndividual
allen relation: before
evidence: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software
from entity: Supervisor Retirement
from entity text: Engineer B's retirement
owl time property: time:intervalBefore
to entity: Dual Deliverable Pressure
to entity text: Engineer A's use of AI software for dual deliverables
synthesis literal: allenRelation
synthesis literal: description
synthesis literal: evidence
synthesis literal: fromEntity
synthesis literal: fromEntityURI
synthesis literal: owlTimeURI
synthesis literal: toEntity
synthesis literal: toEntityURI
comment: Entity1 is before Entity2
interval before: Dual Deliverable Pressure
interval before: Engineer A s use of AI software for dual deliverab
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Design Defect Discovery → Revision Instruction Issued
type: CausalChain
type: NamedIndividual
causal language: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
causal step1: Design Defect Discovery -- Client W finds defects in the submitted design
causal step2: Revision Instruction Issued -- Client W formally instructs Engineer A to revise the plans
cause: Design Defect Discovery
cause text: Design Defect Discovery
counterfactual: Had no defects been discovered, Client W would not have instructed Engineer A to revise the plans
effect: Revision Instruction Issued
effect text: Revision Instruction Issued
necessary factors: Client W's discovery of misaligned dimensions and omitted safety features
necessary factors: Client W's review of the design documents
responsibility type: direct
responsible agent: Client W
responsible agent text: Client W
sufficient factors: Discovery of defects in the design documents was enough to prompt a formal revision instruction
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client Data Upload to AI → AI Report Generation
type: CausalChain
type: NamedIndividual
causal language: Engineer A input the information gathered from Client W into the AI software, and, after a few refining prompts, received a first draft of the report generated by the AI software.
causal step1: Client Data Upload to AI -- Engineer A inputs Client W information into the AI
causal step2: AI Report Generation -- AI produces a first draft of the report
cause: Client Data Upload to AI
cause text: Client Data Upload to AI
counterfactual: Without the data input and prompts, the AI would not have produced the draft report
effect: AI Report Generation
effect text: AI Report Generation
necessary factors: Functioning AI language processing software
necessary factors: Input of Client W's gathered information
necessary factors: Refining prompts provided to the AI
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Inputting client data plus refining prompts was enough for the AI to generate a first draft report
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Tool Adoption for Design → AI Design Generation
type: CausalChain
type: NamedIndividual
causal language: Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans, including basic layouts and technical specifications.
causal step1: AI Tool Adoption for Design -- Engineer A decides to use the AI-assisted drafting tool
causal step2: AI Design Generation -- AI produces preliminary design documents with layouts and specifications
cause: AI Tool Adoption for Design
cause text: AI Tool Adoption for Design
counterfactual: Without adopting and feeding the AI drafting tool, the preliminary AI-generated design would not exist
effect: AI Design Generation
effect text: AI Design Generation
necessary factors: Input of Client W's gathered information into the AI
necessary factors: Reliance on the tools to generate plans
necessary factors: Use of AI-assisted drafting tools
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Inputting data and relying on AI-assisted drafting tools was enough to generate preliminary design plans
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Draft Report Sealing and Submission → Report Stylistic Inconsistency
type: CausalChain
type: NamedIndividual
causal language: When Client W reviewed the draft report, Client W noted that the section analyzing the groundwater monitoring data would benefit from minor edits for grammar and clarity, but found the introduction discussing the contaminant's manufacture, use, and characteristics to be exceptionally polished.
causal step1: Draft Report Sealing and Submission -- Engineer A seals and submits the draft report to Client W
causal step2: Report Stylistic Inconsistency -- Client W notes the report reads as if written by two different authors
cause: Draft Report Sealing and Submission
cause text: Draft Report Sealing and Submission
counterfactual: Without submission to Client W, the inconsistency would not have been noted by the client
effect: Report Stylistic Inconsistency
effect text: Report Stylistic Inconsistency
necessary factors: Presence of stylistically divergent sections in the report
necessary factors: Submission of the draft report to Client W
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Submitting the stylistically mixed report to the client was enough to enable the client's observation of inconsistency
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Report Generation → Report Stylistic Inconsistency
type: CausalChain
type: NamedIndividual
causal language: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
causal step1: AI Report Generation -- AI produces a highly polished introduction section
causal step2: Thorough Report Review -- Engineer A reviews and makes only minor wording adjustments
causal step3: Draft Report Sealing and Submission -- Report submitted with mixed authorial voices
causal step4: Report Stylistic Inconsistency -- Client W observes the report reads as if written by two authors
cause: AI Report Generation
cause text: AI Report Generation
counterfactual: Had the entire report been written in a uniform voice (or fully harmonized by Engineer A), the inconsistency would not have been observed
effect: Report Stylistic Inconsistency
effect text: Report Stylistic Inconsistency
necessary factors: AI-generated polished introduction section
necessary factors: Engineer A's own writing style in the data analysis section
necessary factors: Juxtaposition of the two within one report
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Combination of AI-generated polished prose alongside human-drafted content produced a noticeable stylistic mismatch
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Tool Adoption for Report → AI Disclosure Omission for Report
type: CausalChain
type: NamedIndividual
causal language: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
causal step1: AI Tool Adoption for Report -- Engineer A uses AI to draft the report
causal step2: AI Disclosure Omission for Report -- Engineer A chooses not to cite the AI's contribution
cause: AI Tool Adoption for Report
cause text: AI Tool Adoption for Report
counterfactual: Had Engineer A chosen to disclose, the omission and resulting transparency concern would not have arisen
effect: AI Disclosure Omission for Report
effect text: AI Disclosure Omission for Report
necessary factors: Absence of disclosure to the client
necessary factors: Engineer A's decision not to cite the AI use
necessary factors: Substantial AI contribution to the report
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Use of AI plus a deliberate choice not to cite it produced the disclosure omission
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Dual Deliverable Pressure → AI Tool Adoption for Design
type: CausalChain
type: NamedIndividual
causal language: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents
causal step1: Dual Deliverable Pressure -- Engineer A faces concurrent report and design deadlines
causal step2: AI Tool Adoption for Design -- Engineer A decides to use AI-assisted drafting tools for design documents
cause: Dual Deliverable Pressure
cause text: Dual Deliverable Pressure
counterfactual: Without the concurrent pressure and loss of support, Engineer A may not have turned to an unfamiliar AI drafting tool for design work
effect: AI Tool Adoption for Design
effect text: AI Tool Adoption for Design
necessary factors: Absence of Engineer B's support
necessary factors: Availability of AI-assisted drafting tools
necessary factors: Concurrent deadlines for report and design
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Combination of time pressure + lack of mentorship + availability of AI tools led to adoption for design
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Supervisor Retirement → AI Tool Adoption for Report
type: CausalChain
type: NamedIndividual
causal language: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report
causal step1: Supervisor Retirement -- Engineer B retires, removing prior QA review and mentorship
causal step2: Dual Deliverable Pressure -- Engineer A faces concurrent report and design deadlines without support
causal step3: AI Tool Adoption for Report -- Engineer A decides to use open-source AI software to draft the report
cause: Supervisor Retirement
cause text: Supervisor Retirement
counterfactual: Had Engineer B remained available for review, Engineer A would likely have relied on mentorship rather than adopting unfamiliar AI software
effect: AI Tool Adoption for Report
effect text: AI Tool Adoption for Report
necessary factors: Engineer A's lack of confidence in technical writing
necessary factors: Loss of Engineer B's quality assurance and mentorship
necessary factors: Need to deliver the report
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Combination of mentor unavailability + writing insecurity + delivery deadline drove adoption of AI software
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client Data Upload to AI → Client Data Exposure
type: CausalChain
type: NamedIndividual
causal language: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
causal step1: AI Tool Adoption for Report -- Engineer A selects open-source AI software
causal step2: Client Data Upload to AI -- Engineer A enters Client W's private information into the interface
causal step3: Client Data Exposure -- Confidential information effectively placed in the public domain
cause: Client Data Upload to AI
cause text: Client Data Upload to AI
counterfactual: Had Engineer A not uploaded the data, or used a secure/private tool with consent, exposure would not have occurred
effect: Client Data Exposure
effect text: Client Data Exposure
necessary factors: Absence of client consent to public disclosure
necessary factors: Possession of Client W's confidential information
necessary factors: Use of an open-source (public) AI interface
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Uploading confidential client data into an open-source AI interface was enough to expose it to the public domain
within agent control: true
discovered in section: discussion
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Cursory Design Document Review → Design Defect Discovery
type: CausalChain
type: NamedIndividual
causal language: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
causal step1: AI Design Generation -- AI produces plans with misaligned dimensions and missing safety features
causal step2: Cursory Design Document Review -- Engineer A reviews only superficially, missing the defects
causal step3: Design Document Submission -- Defective documents submitted to Client W
causal step4: Design Defect Discovery -- Client W identifies misaligned dimensions and omitted safety features
cause: Cursory Design Document Review
cause text: Cursory Design Document Review
counterfactual: Had Engineer A conducted a comprehensive verification process, the misaligned dimensions and omitted safety features would likely have been caught and corrected before Client review
effect: Design Defect Discovery
effect text: Design Defect Discovery
necessary factors: AI-generated plans containing misaligned dimensions and omitted safety features
necessary factors: Failure to detect the errors before submission
necessary factors: Only a cursory (insufficient) review by Engineer A
responsibility type: direct
responsible agent: Engineer A
responsible agent text: Engineer A
sufficient factors: Combination of AI-generated defects + insufficient review allowed defects to remain in submitted documents
within agent control: true
discovered in section: facts
synthesis literal: causalLanguage
synthesis literal: causalSequence
synthesis literal: counterfactual
synthesis literal: necessaryFactors
synthesis literal: responsibilityType
synthesis literal: sufficientFactors
synthesis literal: withinAgentControl
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Attribution
type: AIDisclosureConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: AI language processing software fundamentally shaped the contaminant report submitted to Client W, but Engineer A did not disclose this contribution or attribute it in the work product.
concept category: Constraint
confidence: 0.85
constraint class: AI Disclosure Constraint
constraint statement: Engineer A was required to disclose and attribute the substantial contribution of AI language processing software to the contaminant report, consistent with the obligation to give credit for engineering work to those to whom credit is due under NSPE Code section III.9.
severity: medium
source: NSPE Code of Ethics, Code section III.9; BER Case 98-3
temporal scope: At the time of submitting the AI-assisted contaminant report to Client W
text references: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9, '[e]ngineers shall give credit for engineering work to those to whom credit is due, and will recognize the proprietary interests of others.'
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9, '[e]ngineers shall give credit for engineering work to those to whom credit is due, and will recognize the proprietary interests of others.'
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was required to disclose and attribute the substantial contribution of AI language processing software to the contaminant report, consistent with the obligation to give credit for engineering work to those to whom credit is due under NSPE Code section III.9.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data Upload Consent
type: ConfidentialDataPlatformConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A uploaded Client W's confidential project information into a publicly accessible AI interface to generate a draft groundwater monitoring report, without obtaining Client W's consent to share that information externally.
concept category: Constraint
confidence: 0.92
constraint class: Confidential Data Platform Constraint
constraint statement: Engineer A was prohibited from uploading Client W's confidential proprietary site data and groundwater monitoring information into an open-source AI interface without first obtaining Client W's prior consent, as doing so placed the client's private information in the public domain.
severity: high
source: NSPE Code of Ethics, Code section II.1.c
temporal scope: At the time Engineer A used the open-source AI language processing tool to draft the contaminant report
text references: Per Code section II.1.c, confidential information can only be shared with prior consent of the Client.
text references: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Per Code section II.1.c, confidential information can only be shared with prior consent of the Client.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was prohibited from uploading Client W's confidential proprietary site data and groundwater monitoring information into an open-source AI interface without first obtaining Client W's prior consent, as doing so placed the client's private information in the public domain.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentor Loss Competence Gap
type: CompetenceConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A had relied on Engineer B for quality assurance review of report drafts to compensate for self-assessed limitations in technical writing. After Engineer B retired, Engineer A turned to AI tools without implementing equivalent quality assurance, resulting in deficient work products.
concept category: Constraint
confidence: 0.87
constraint class: Competence Constraint
constraint statement: Engineer A was constrained by the loss of Engineer B's mentorship and quality assurance review from delivering professional work products in areas of personal weakness, specifically technical writing, without implementing an adequate alternative quality assurance mechanism.
severity: high
source: NSPE Code of Ethics competence provisions
temporal scope: Following Engineer B's retirement and throughout the Client W engagement
text references: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing.
text references: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Competence Constraint'
matched ontology class: CompetenceConstraint
matched ontology label: Competence Constraint
matches existing: true
source text: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained by the loss of Engineer B's mentorship and quality assurance review from delivering professional work products in areas of personal weakness, specifically technical writing, without implementing an adequate alternative quality assurance mechanism.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentorship Loss Design Oversight
type: MentorshipContinuityPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents
balancing with: Responsible Charge Integrity Principle
balancing with: Technology Substitution Prohibition Principle
concept category: Principle
concrete expression: When Engineer B became unavailable due to retirement, Engineer A proceeded with AI-assisted design work without seeking alternative review mechanisms, resulting in inadequate oversight of work that contained safety-critical errors.
confidence: 0.84
interpretation: The loss of Engineer B's mentorship and quality assurance review created a gap in oversight that Engineer A was required to address by finding alternative review mechanisms rather than proceeding with a high-level self-review of novel AI-generated outputs.
invoked by: Engineer A Responsible Charge
principle class: Mentorship Continuity Principle
tension resolution: The BER identified Engineer A as operating in a compromised manner without Engineer B's guidance, treating the failure to seek alternative oversight as a contributing factor in the ethical violations rather than a complete excuse.
text references: Engineer A, as the engineer in Responsible Charge of the project, is required to provide an experienced-based quality assurance review, engaging in critical discussions, mentorship, and professional development -- elements that AI cannot replicate.
text references: The facts also note Engineer A appears to be operating in a compromised manner -- namely, without the help of Engineer B -- such that Engineer A relied on the AI-generated plans and specifications without proper oversight.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: The facts also note Engineer A appears to be operating in a compromised manner -- namely, without the help of Engineer B -- such that Engineer A relied on the AI-generated plans and specifications without proper oversight.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: When Engineer B became unavailable due to retirement, Engineer A proceeded with AI-assisted design work without seeking alternative review mechanisms, resulting in inadequate oversight of work that contained safety-critical errors.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Direction Control
type: AIDirectionandControlObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used a new AI-assisted drafting tool without prior experience, conducted only a high-level review of the generated design documents, and did not outline solution guidelines or critically challenge the AI outputs, resulting in omitted safety features and misaligned dimensions.
compliance status: unmet
concept category: Obligation
confidence: 0.91
derived from principle: Engineer A AI Design Substitution
obligation class: AI Direction and Control Obligation
obligation statement: Engineer A was obligated to exercise genuine direction and control over the AI-assisted drafting tool by outlining solution guidelines and constraints, critically challenging outputs, and verifying results before accepting the AI-generated design documents.
temporal scope: Throughout the AI-assisted design document preparation process
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
text references: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to exercise genuine direction and control over the AI-assisted drafting tool by outlining solution guidelines and constraints, critically challenging outputs, and verifying results before accepting the AI-generated design documents.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer B
type: Agent
type: NamedIndividual
has role: Engineer B Mentor Engineer
professional peer of: Engineer A

Engineer A AI Judgment Substitution
type: TechnologySubstitutionConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A relied on AI-generated plans and specifications without proper oversight following Engineer B's retirement, resulting in design documents with misaligned dimensions and omitted safety features required by local regulations.
concept category: Constraint
confidence: 0.88
constraint class: Technology Substitution Constraint
constraint statement: Engineer A was prohibited from using the AI-assisted drafting tool as a substitute for independent engineering judgment, and was required to critically challenge and verify all AI-generated design outputs against professional standards before acceptance rather than relying on them without proper oversight.
severity: critical
source: NSPE Code of Ethics, Fundamental Canon I.1; BER Case 98-3
temporal scope: Throughout the preparation and review of the AI-generated engineering design documents
text references: Engineer A relied on the AI-generated plans and specifications without proper oversight.
text references: Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
text references: technology must not replace or be used as a substitute for engineering judgement.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: technology must not replace or be used as a substitute for engineering judgement.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was prohibited from using the AI-assisted drafting tool as a substitute for independent engineering judgment, and was required to critically challenge and verify all AI-generated design outputs against professional standards before acceptance rather than relying on them without proper oversight.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Tool Non-Disclosure Design
type: AIToolDisclosurePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Engineering design documents submitted to Client W
balancing with: Time pressure to deliver design documents
concept category: Principle
concrete expression: Engineer A used AI-assisted drafting tools to generate preliminary engineering design documents but did not disclose this to Client W when submitting the plans.
confidence: 0.9
interpretation: Disclosure of AI tool use in design documents is required so clients and regulators can evaluate the basis for the design and the degree of independent engineering judgment applied.
invoked by: Engineer A AI-Assisted Design
principle class: AI Tool Disclosure Principle
tension resolution: The principle was violated: Engineer A again chose not to disclose AI tool use in the design documents.
text references: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A used AI-assisted drafting tools to generate preliminary engineering design documents but did not disclose this to Client W when submitting the plans.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Documents Competence Failure
type: AIVerificationCompetencePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents
balancing with: Responsible Charge Integrity Principle
balancing with: Technology Substitution Prohibition Principle
concept category: Principle
concrete expression: Engineer A used a new AI-assisted drafting tool without prior experience and conducted only a high-level review of the generated design documents, failing to detect misaligned dimensions and omitted safety features, falling below the competence standard for AI-assisted design work.
confidence: 0.92
interpretation: Unlike the report, where Engineer A had domain expertise and conducted substantive verification, the design documents received insufficient scrutiny. The lack of experience with the tool combined with a high-level review rather than comprehensive verification constituted a failure of the AI verification competence obligation.
invoked by: Engineer A AI-Assisted Design
principle class: AI Verification Competence Principle
tension resolution: The BER found that Engineer A was not incompetent in the general sense but operated in a compromised manner without adequate oversight, resulting in an ethical violation through insufficient verification of AI-generated design outputs.
text references: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement.
text references: Engineer A also prepared draft design documents with a AI-assisted drafting tool that was new to the market. Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
text references: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A also prepared draft design documents with a AI-assisted drafting tool that was new to the market. Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A used a new AI-assisted drafting tool without prior experience and conducted only a high-level review of the generated design documents, failing to detect misaligned dimensions and omitted safety features, falling below the competence standard for AI-assisted design work.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Documents Verification
type: AIOutputVerificationConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A performed only a cursory review of AI-generated design documents, which left misaligned dimensions and omitted safety features required by local regulations undetected until Client W identified them.
concept category: Constraint
confidence: 0.87
constraint class: AI Output Verification Constraint
constraint statement: Engineer A was constrained to conduct a sufficiently thorough technical review of the AI-generated engineering design documents to identify regulatory omissions and dimensional errors before submission, and a cursory review did not satisfy this constraint.
severity: critical
source: NSPE Code of Ethics, state engineering seal law, local site safety regulations
temporal scope: Prior to submission of engineering design documents to Client W
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained to conduct a sufficiently thorough technical review of the AI-generated engineering design documents to identify regulatory omissions and dimensional errors before submission, and a cursory review did not satisfy this constraint.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentor Loss Response
type: MentorshipContinuityPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Report and design document preparation without mentor oversight
balancing with: Client delivery expectations
balancing with: Professional Competence
concept category: Principle
concrete expression: When Engineer B retired and became unavailable, Engineer A substituted AI software for the quality assurance review function that Engineer B had previously provided, without seeking alternative peer review or supervisory oversight.
confidence: 0.85
interpretation: The loss of Engineer B created a quality assurance gap that Engineer A was obligated to address through alternative review mechanisms. Substituting an unfamiliar AI tool without equivalent verification did not satisfy this obligation.
invoked by: Engineer A Responsible Charge
principle class: Mentorship Continuity Principle
tension resolution: The principle was not satisfied: Engineer A chose AI substitution over alternative peer review, and the resulting work product contained errors that Engineer B's review might have caught.
text references: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software
text references: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: When Engineer B retired and became unavailable, Engineer A substituted AI software for the quality assurance review function that Engineer B had previously provided, without seeking alternative peer review or supervisory oversight.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Report Stylistic Inconsistency
type: Event
type: NamedIndividual
caused by action: Thorough Report Review
causes state change: Client W identified a quality concern in the report, signaling that the document's authorship was inconsistent even if factually adequate.
concept category: Event
event type: outcome
initiates text: Authorship Attribution Question State
initiates text: Client Concern State
severity: low
temporal extent: instant
temporal marker: Upon Client W's review of submitted report
temporal sequence: 11
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: The submitted report exhibited a stylistic inconsistency noted by Client W, who observed that the document read as if written by two different authors, likely reflecting the blending of AI-generated and human-reviewed content.
has time: Upon Client W's review of submitted report
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Dual Deliverable Pressure
type: Event
type: NamedIndividual
caused by action: Project Acceptance
causes state change: Engineer A operated under elevated workload conditions with two simultaneous major deliverables and no supervisory backup.
concept category: Event
event type: automatic_trigger
initiates text: Elevated Workload State
initiates text: Resource Deficit State
severity: medium
temporal extent: interval
temporal marker: Concurrent with project execution phase
temporal sequence: 3
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: Engineer A faced concurrent deadlines for both the comprehensive contaminant report and the groundwater infrastructure design documents, creating compounded workload pressure.
has time: Concurrent with project execution phase
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Verification Failure
type: AIVerificationCompetencePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents for groundwater infrastructure
balancing with: Loss of mentor oversight
balancing with: Time pressure
concept category: Principle
concrete expression: Engineer A conducted only a cursory review of AI-generated design documents despite having no prior experience with the AI drafting tool, resulting in submission of plans with misaligned dimensions and omitted safety features.
confidence: 0.92
interpretation: Using a novel AI tool without understanding its accuracy limitations, and reviewing its output only cursorily, falls below the competence standard required before sealing and submitting engineering design documents.
invoked by: Engineer A AI-Assisted Design
principle class: AI Verification Competence Principle
tension resolution: The principle was not satisfied: the cursory review was insufficient given Engineer A's unfamiliarity with the tool and the regulatory stakes of the design documents.
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A conducted only a cursory review of AI-generated design documents despite having no prior experience with the AI drafting tool, resulting in submission of plans with misaligned dimensions and omitted safety features.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Competence
type: AIVerificationCompetencePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated contaminant report draft
balancing with: AI Tool Disclosure Principle
balancing with: Client Data Confidentiality Principle
concept category: Principle
concrete expression: Engineer A used open-source AI language processing software to generate the initial contaminant report draft and performed a thorough review, cross-checking key facts against professional sources and making textual adjustments, satisfying the competence requirement for AI-assisted report writing.
confidence: 0.87
interpretation: Because Engineer A had domain expertise in environmental engineering and conducted substantive verification of the AI output, the use of AI for report drafting was within the bounds of professional competence for this component of the work.
invoked by: Engineer A Environmental Engineer
principle class: AI Verification Competence Principle
tension resolution: Competence in verification was satisfied for the report, but separate obligations regarding client data confidentiality and attribution were not fulfilled, meaning overall ethical compliance was incomplete.
text references: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control.
text references: Engineer A, as an experienced environmental engineer, was competent to analyze groundwater monitoring data and assess contaminant risks.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A, as an experienced environmental engineer, was competent to analyze groundwater monitoring data and assess contaminant risks. Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A used open-source AI language processing software to generate the initial contaminant report draft and performed a thorough review, cross-checking key facts against professional sources and making textual adjustments, satisfying the competence requirement for AI-assisted report writing.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Relationship
type: ClientRelationshipEstablished
type: NamedIndividual
activates constraint: Engineer A Design AI Output Verification
activates constraint: Engineer A Unfamiliar Drafting Tool Use
activates obligation: Engineer A Report AI Disclosure
activates obligation: Engineer A Report AI Verification
affects: Client W
affects: Engineer A
active period: From retention by Client W through completion of report and design documents
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.97
principle transformation: Transforms general competence and due care principles into specific verification and disclosure duties when deploying tools whose accuracy and limitations are not yet understood by the professional.
state class: Client Relationship Established
subject: Engineer A's professional engagement with Client W
terminated by: Completion and acceptance of all deliverables
text references: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report
triggering event: Client W retaining Engineer A to prepare the comprehensive report and engineering design documents
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Client Relationship Established'
matched ontology class: ClientRelationship
matched ontology label: Client Relationship Established
matches existing: true
source text: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's professional engagement with Client W
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentor Loss Response
type: MentorshipGapCompetenceObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A lost access to mentor Engineer B's quality assurance reviews upon Engineer B's retirement and responded by using open-source AI software with which Engineer A had no prior experience, resulting in deficient design documents being submitted to Client W.
compliance status: unmet
concept category: Obligation
confidence: 0.86
derived from principle: Engineer A Mentor Loss Response
obligation class: Mentorship Gap Competence Obligation
obligation statement: When Engineer B retired and became unavailable, Engineer A was obligated to identify and implement an adequate alternative quality assurance process for their professional work products rather than substituting an unfamiliar AI tool for the oversight function Engineer B had previously provided.
temporal scope: Upon Engineer B's retirement and throughout the project delivery period
text references: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents. The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
text references: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.75
match reasoning: Via class 'Mentorship Gap Competence Obligation': This obligation is a contextual specialization of the existing Competence Obligation, addressing the specific situation where a quality assurance mentor becomes unavailable. The existing class covers the general duty to practice within competence but does not address the specific duty to maintain quality assurance processes when supervisory support is lost. A new class is warranted to capture this distinct scenario type.
matched ontology class: CompetenceObligation
matched ontology label: Competence Obligation
matches existing: true
source text: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts. But Engineer B recently retired and was no longer available to Engineer A in a work capacity.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: When Engineer B retired and became unavailable, Engineer A was obligated to identify and implement an adequate alternative quality assurance process for their professional work products rather than substituting an unfamiliar AI tool for the oversight function Engineer B had previously provided.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Mentor Unavailable
type: MentorUnavailableState
type: NamedIndividual
activated by event: Supervisor Retirement
activates constraint: Engineer A Mentor Loss Competence Gap
activates obligation: Engineer A Design Safety Compliance
activates obligation: Engineer A Mentor Loss Response
affects: Client W
affects: Engineer A
active period: From Engineer B's retirement through the completion of the engagement
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.95
principle transformation: Transforms general competence obligations into specific duties to secure alternative quality assurance before undertaking work previously dependent on mentorship.
state class: Mentor Unavailable State
subject: Engineer A's loss of access to Engineer B as mentor and quality assurance reviewer
terminated by: Not resolved within the case
text references: Engineer B recently retired and was no longer available to Engineer A in a work capacity
text references: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B
triggering event: Engineer B's retirement from active work capacity
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer B recently retired and was no longer available to Engineer A in a work capacity
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's loss of access to Engineer B as mentor and quality assurance reviewer
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report Technical Citations
type: TechnicalCitationObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used AI language processing software to generate the initial draft of a contaminant report but did not include citations to pertinent technical authority documents in the final report.
compliance status: unmet
concept category: Obligation
confidence: 0.88
derived from principle: Engineer A AI Report Attribution
obligation class: Technical Citation Obligation
obligation statement: Engineer A was obligated to include citations to pertinent documents of technical authority in the AI-assisted contaminant report submitted to Client W.
temporal scope: At the time of preparing and submitting the contaminant report
text references: Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
text references: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: the facts do not indicate the AI-generated report included citations of pertinent documents of technical authority
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to include citations to pertinent documents of technical authority in the AI-assisted contaminant report submitted to Client W.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Technical Writing Competence
type: CompetenceState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Judgment Substitution
activates obligation: Engineer A Design Safety Compliance
activates obligation: Engineer A Design Seal
affects: Client W
affects: Engineer A
active period: Throughout the engagement, from initial assignment through submission of deliverables
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.92
principle transformation: Transforms the responsible charge and public safety principles into a concrete prohibition on passive post-hoc review as a substitute for active supervisory engagement throughout the engineering process.
state class: Competence State
subject: Engineer A's self-assessed limitation in technical writing
terminated by: Not resolved within the case; persists through the described events
text references: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing
text references: Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supervisor, Engineer B, to refine report drafts
triggering event: Engineer A's recognition of personal weakness in technical writing and loss of mentorship support
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Competence State'
matched ontology class: CompetenceState
matched ontology label: Competence State
matches existing: true
source text: Engineer A is known for their strong technical expertise but is, personally, less confident in their technical writing
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's self-assessed limitation in technical writing
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Project Acceptance
type: Action
type: NamedIndividual
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Reduced quality assurance coverage due to absence of Engineer B
fulfills obligation text: Perform Services Within Competence
guided by principle: Engineer A Professional Competence AI Use
guided by principle: Engineer A Public Safety Design Errors
guided by principle: Engineer A Safety Feature Omission
guided by principle text: Professional Competency
guided by principle text: Public Safety
has agent: Engineer A
has mental state: deliberate
initiates text: Dual Deliverable Obligation
initiates text: Reduced Quality Assurance Support State
intended outcome: Fulfill professional engagement and deliver required work products to Client W
raises obligation text: Undertake Assignments Only When Qualified
requires capability text: Engineering design and review
requires capability text: Environmental engineering expertise
requires capability text: Quality assurance oversight
requires capability text: Technical report writing
temporal extent: instant
temporal marker: At project initiation, after Engineer B's retirement
temporal sequence: 2
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A accepted the dual engagement from Client W to produce a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications, without securing alternative quality assurance support after Engineer B's retirement.
has time: At project initiation, after Engineer B's retirement
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Revision Instruction Issued
type: Event
type: NamedIndividual
caused by action: Design Document Submission
causes state change: Engineer A became obligated to revise the design documents, and the project moved into a remediation phase rather than proceeding to implementation.
concept category: Event
event type: outcome
initiates text: Design Revision Required State
initiates text: Project Remediation Phase State
severity: high
temporal extent: instant
temporal marker: After Client W's review of design documents
temporal sequence: 18
terminates text: Design Submission Complete State
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: Client W raised concerns about the defective design documents and formally instructed Engineer A to revise the plans to correct the identified deficiencies.
has time: After Client W's review of design documents
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Attribution
type: AIDisclosureConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: AI-assisted drafting tools generated the preliminary engineering design documents submitted to Client W, but Engineer A did not disclose this contribution.
concept category: Constraint
confidence: 0.85
constraint class: AI Disclosure Constraint
constraint statement: Engineer A was required to disclose and attribute the substantial contribution of AI-assisted drafting tools to the engineering design documents submitted to Client W, consistent with the obligation to give credit for engineering work to those to whom credit is due.
severity: medium
source: NSPE Code of Ethics, Code section III.9; BER Case 98-3
temporal scope: At the time of submitting the AI-assisted engineering design documents to Client W
text references: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9.
text references: There are currently no universal guidelines mandating AI disclosure in engineering work, but best practices suggest informing clients when AI substantially contributes to a work product.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was required to disclose and attribute the substantial contribution of AI-assisted drafting tools to the engineering design documents submitted to Client W, consistent with the obligation to give credit for engineering work to those to whom credit is due.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Substitution
type: TechnologySubstitutionProhibitionPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents
balancing with: AI Verification Competence Principle
balancing with: Responsible Charge Integrity Principle
concept category: Principle
concrete expression: Engineer A accepted AI-generated design documents after only a high-level review without outlining solution guidelines, critically challenging outputs, or verifying that the AI-generated design met independent professional standards, effectively substituting AI output for engineering judgment.
confidence: 0.91
interpretation: The BER analogized responsible AI use to supervising an engineering intern: outputs must be outlined, challenged, and verified against independent professional standards before acceptance. Engineer A's high-level review fell short of this standard, constituting impermissible substitution.
invoked by: Engineer A AI-Assisted Design
principle class: Technology Substitution Prohibition Principle
tension resolution: The prohibition on substitution was treated as absolute in this context: no efficiency or novelty justification could excuse accepting AI-generated design outputs without substantive independent evaluation.
text references: It is the [BER]'s position that technology has an important place in the practice of engineering, but it must never be a replacement of a substitute for engineering judgement.
text references: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
text references: Only after the engineer in Responsible Charge has satisfied themselves that the proposed solution is in accordance with their own and professional standards should the design/report be accepted. These are steps that, in this case, Engineer A chose not to follow.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Much like directing an engineering intern to solve a problem, responsible use of AI requires an engineer to outline solution guidelines and constraints. Recommendations from the program or intern should not be blindly accepted, they should be considered and challenged and the resulting outputs should be understood.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A accepted AI-generated design documents after only a high-level review without outlining solution guidelines, critically challenging outputs, or verifying that the AI-generated design met independent professional standards, effectively substituting AI output for engineering judgment.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Disclosure
type: AIDisclosureConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A used open-source AI software to draft a groundwater contaminant report for Client W but did not disclose this use when submitting the draft, despite the AI having generated the substantive content of the introduction section.
concept category: Constraint
confidence: 0.88
constraint class: AI Disclosure Constraint
constraint statement: Engineer A was constrained by professional ethics to disclose to Client W that AI language processing software was used to generate the initial draft of the contaminant report, and failure to do so constituted a violation of this constraint.
severity: high
source: NSPE Code of Ethics, professional norms on honesty and transparency with clients
temporal scope: At the time of report submission to Client W
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained by professional ethics to disclose to Client W that AI language processing software was used to generate the initial draft of the contaminant report, and failure to do so constituted a violation of this constraint.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data AI Upload
type: ClientDataConfidentialityPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Client W proprietary site and contaminant data
balancing with: AI Verification Competence Principle
balancing with: Professional Competence
concept category: Principle
concrete expression: Engineer A uploaded Client W's proprietary project information into a public-domain open-source AI interface without obtaining prior consent from Client W, constructively placing confidential client data in the public domain.
confidence: 0.91
interpretation: The confidentiality obligation under NSPE Code section II.1.c extends to incidental or constructive disclosure arising from tool selection. Uploading client data to a public AI interface is functionally equivalent to disclosure, regardless of intent.
invoked by: Engineer A Environmental Engineer
principle class: Client Data Confidentiality Principle
tension resolution: The BER found no justification for the disclosure: Engineer A should have either obtained client consent or used a tool that did not expose client data to public access.
text references: Per Code section II.1.c, confidential information can only be shared with prior consent of the Client.
text references: The facts here do not indicate Engineer A obtained permission from Client W to use the private information in the public domain.
text references: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.78
match reasoning: Via class 'Client Data Confidentiality Principle': The existing Confidentiality Principle covers the general obligation to protect client information. This instance adds a domain-specific qualifier about constructive disclosure through AI tool use, which is a meaningful variant warranting a more specific class rather than a direct match. The existing Confidentiality Principle does not address the incidental-disclosure-via-tool-selection scenario, so a variant class is appropriate.
matched ontology class: ConfidentialityPrinciple
matched ontology label: Confidentiality Principle
matches existing: true
source text: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A uploaded Client W's proprietary project information into a public-domain open-source AI interface without obtaining prior consent from Client W, constructively placing confidential client data in the public domain.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Deficient Submission
type: DeficientWorkProductSubmittedState
type: NamedIndividual
activates obligation: Engineer A Safety Feature Omission
affects: Client W
affects: Engineer A
active period: From submission of the design documents to Client W through Client W's identification of the errors; correction not described in the facts
affected parties: Client W
affected parties: Engineer A
affected parties: public safety
affected parties: regulatory compliance
concept category: State
confidence: 0.92
principle transformation: Transforms general professional responsibility and public safety principles into specific corrective action and notification duties once deficiencies in a submitted work product are confirmed.
state class: Deficient Work Product Submitted State
subject: Engineer A's submission of AI-generated design documents containing misaligned dimensions and omitted safety features required for regulatory compliance
terminated by: Would require correction of all deficiencies and resubmission; not resolved within the case facts
text references: The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards.
text references: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
triggering event: Client W's review revealing misaligned dimensions and omitted safety features in the AI-generated design documents
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's submission of AI-generated design documents containing misaligned dimensions and omitted safety features required for regulatory compliance
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Unfamiliar AI Tool
type: UnfamiliarToolDeploymentState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A Design AI Output Verification
activates constraint: Engineer A Unfamiliar Drafting Tool Use
activates obligation: Engineer A AI Design Disclosure
activates obligation: Engineer A Design Documents Verification
affects: Client W
affects: Engineer A
active period: From the decision to use AI software through submission of both deliverables
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.94
principle transformation: Transforms general competence and due care principles into specific verification and disclosure duties when deploying tools whose accuracy and limitations are not yet understood by the professional.
state class: Unfamiliar Tool Deployment State
subject: Engineer A's use of AI drafting software with no prior experience
terminated by: Not resolved within the case
text references: Not being familiar with the full functionality of the AI software, including the accuracy and originality of AI-generated text
text references: The AI drafting software was new to the market and Engineer A had no previous experience with the tool
triggering event: Engineer A's decision to use new open-source AI drafting software without prior experience
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: The AI drafting software was new to the market and Engineer A had no previous experience with the tool
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's use of AI drafting software with no prior experience
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Unfamiliar Drafting Tool Use
type: UnfamiliarToolCompetenceConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A used an AI-assisted drafting tool that was new to the market and with which Engineer A had no established experience, resulting in a cursory review that failed to catch misaligned dimensions and omitted safety features in the submitted design documents.
concept category: Constraint
confidence: 0.84
constraint class: Unfamiliar Tool Competence Constraint
constraint statement: Engineer A was constrained by competence boundaries from relying on an AI-assisted drafting tool with which they had no prior experience to generate engineering design documents for client submission without additional safeguards, because lack of familiarity with the tool's capabilities and limitations prevented adequate evaluation of its outputs.
severity: high
source: NSPE Code of Ethics competence provisions, professional engineering standards
temporal scope: At the time of selecting and using the AI drafting tool for Client W's design documents
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.78
match reasoning: Via class 'Unfamiliar Tool Competence Constraint': The existing Competence Constraint class covers boundaries defined by agent capabilities and technical limitations, which encompasses this scenario. The unfamiliar tool variant is a specific application of that general class. Matching as a variant at medium confidence while defining a more specific reusable subtype for unfamiliar tool deployment contexts.
matched ontology class: CompetenceConstraint
matched ontology label: Competence Constraint
matches existing: true
source text: The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained by competence boundaries from relying on an AI-assisted drafting tool with which they had no prior experience to generate engineering design documents for client submission without additional safeguards, because lack of familiarity with the tool's capabilities and limitations prevented adequate evaluation of its outputs.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Disclosure Omission for Design
type: Action
type: NamedIndividual
initiates: Engineer A Undisclosed AI Design
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Client W unaware of AI involvement and therefore unable to apply appropriate scrutiny or make informed decisions about the reliability of the designs
guided by principle: Engineer A AI Authorship Concealment
guided by principle: Engineer A AI Disclosure Transparency
guided by principle: Engineer A AI Report Attribution
guided by principle: Engineer A AI Tool Non-Disclosure Report
guided by principle: Engineer A Transparency to Client
guided by principle text: Professional Integrity
guided by principle text: Transparency and Attribution
has agent: Engineer A
has mental state: deliberate
initiates text: Undisclosed AI Contribution to Design Documents State
intended outcome: Submit the design documents as a professional work product without separately identifying AI as a contributing tool
requires capability text: Awareness of professional attribution norms for AI-assisted design work
requires capability text: Judgment about transparency obligations to clients
temporal extent: instant
temporal marker: At design document submission
temporal sequence: 15
violates obligation: Engineer A AI Authorship Representation
violates obligation: Engineer A AI Design Disclosure
violates obligation text: Avoid Deceptive Acts
violates obligation text: Credit and Attribution for Engineering Work
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A chose not to disclose the use of AI-assisted drafting tools when submitting the engineering design documents to Client W, providing no indication that the plans and specifications were substantially generated by AI software.
has time: At design document submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data AI Upload
type: ClientDataConfidentialityObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used an open-source AI language processing tool to generate a contaminant report draft, uploading Client W's confidential project data into the public-domain interface without documented client consent.
compliance status: unmet
concept category: Obligation
confidence: 0.93
derived from principle: Engineer A Client Data AI Upload
obligation class: Client Data Confidentiality Obligation
obligation statement: Engineer A was obligated to obtain prior consent from Client W before uploading Client W's proprietary project information into a public-domain open-source AI interface.
temporal scope: Prior to uploading any client data into the AI tool
text references: The facts here do not indicate Engineer A obtained permission from Client W to use the private information in the public domain.
text references: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.8
match reasoning: Via class 'Client Data Confidentiality Obligation': This is a specific variant of the existing Confidentiality Obligation, narrowed to the context of uploading client data into public-domain AI tools without consent. The existing class covers duty to protect confidential information generally; this specialization addresses the AI-tool transmission vector.
matched ontology class: ConfidentialityObligation
matched ontology label: Confidentiality Obligation
matches existing: true
source text: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to obtain prior consent from Client W before uploading Client W's proprietary project information into a public-domain open-source AI interface.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Deficiencies
type: DeficientWorkProductSubmittedState
type: NamedIndividual
activated by event: Design Defect Discovery
activates obligation: Engineer A Safety Feature Omission
affects: Client W
affects: Engineer A
active period: From Client W's identification of deficiencies through correction and resubmission
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.94
principle transformation: Transforms general professional responsibility and public safety principles into specific corrective action and notification duties once deficiencies in a submitted work product are confirmed.
state class: Deficient Work Product Submitted State
subject: The engineering design documents found to contain errors and regulatory omissions
terminated by: Engineer A revising the plans to meet professional and regulatory standards
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations
text references: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards
triggering event: Client W identifying misaligned dimensions and omission of required safety features in the AI-generated design documents
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The engineering design documents found to contain errors and regulatory omissions
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Inadequate AI Review
type: InadequateAIReviewState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A Design Documents Verification
activates obligation: Engineer A Design Safety Compliance
activates obligation: Engineer A Design Seal
affects: Client W
affects: Engineer A
active period: From Engineer A's use of the AI drafting tool through Client W's discovery of errors in the design documents
affected parties: Client W
affected parties: Engineer A
affected parties: public affected by the design
concept category: State
confidence: 0.91
principle transformation: Transforms the responsible charge and public safety principles into a concrete obligation to apply at least the same level of scrutiny to AI-generated work as to human-generated work, including critical engagement with outputs rather than passive acceptance.
state class: Inadequate AI Review State
subject: Engineer A's high-level review of AI-assisted drafting tool output for the design documents, which left misaligned dimensions and omitted safety features undetected
terminated by: Client W's identification of errors in the design documents; full remediation not described in the facts
text references: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement.
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
text references: When Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
triggering event: Engineer A electing to conduct only a high-level review of AI-generated design documents rather than a comprehensive verification
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's high-level review of AI-assisted drafting tool output for the design documents, which left misaligned dimensions and omitted safety features undetected
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report AI Verification
type: AIVerificationCompetencePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated contaminant report
balancing with: Unfamiliarity with AI tool capabilities
concept category: Principle
concrete expression: Engineer A conducted a more thorough review of the AI-generated report, cross-checking key facts against professional journal articles and verifying phrasing, demonstrating partial but not complete satisfaction of the verification obligation.
confidence: 0.83
interpretation: The report review was more substantive than the design document review, but the inconsistency in writing style noted by the client suggests the verification did not fully address the limitations of AI-generated synthesis.
invoked by: Engineer A AI-Assisted Design
principle class: AI Verification Competence Principle
tension resolution: The principle was partially satisfied for the report but the stylistic inconsistency identified by the client indicates residual gaps in verification.
text references: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.
text references: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A conducted a more thorough review of the AI-generated report, cross-checking key facts against professional journal articles and verifying phrasing, demonstrating partial but not complete satisfaction of the verification obligation.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Undisclosed AI Report
type: UndisclosedAIUseState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Design Attribution
activates obligation: Engineer A AI Design Disclosure
affects: Client W
affects: Engineer A
terminated by event: AI Report Generation
active period: From submission of the report through the case's described events
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.92
principle transformation: Transforms honesty and transparency principles into specific disclosure obligations when AI tools have played a material role in producing a professional work product.
state class: Undisclosed AI Use State
subject: Engineer A's omission of disclosure of AI use in the report
terminated by: Not resolved within the case
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
triggering event: Engineer A submitting the AI-assisted report to Client W without disclosing AI use
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's omission of disclosure of AI use in the report
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client Data Exposure
type: Event
type: NamedIndividual
initiates: Engineer A Client Data Exposure
terminates: Engineer A Confidential Client Data AI Input
caused by action: Client Data Upload to AI
causes state change: Client W's confidential site data entered a third-party AI system, creating a potential confidentiality breach outside Engineer A's control.
concept category: Event
event type: outcome
initiates text: Confidentiality Risk State
initiates text: Third-Party Data Exposure State
severity: high
temporal extent: instant
temporal marker: During AI-assisted drafting phase, before submission
temporal sequence: 6
terminates text: Client Data Confidentiality State
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: When Engineer A uploaded client monitoring data and site information to the open-source AI software, that proprietary client data was transmitted to and processed by a third-party system outside Engineer A's control.
has time: During AI-assisted drafting phase, before submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Authorship Concealment
type: IntellectualHonestyinAuthorshipPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Contaminant report submitted to Client W
balancing with: AI Tool Disclosure Principle
balancing with: Client perception of professional capability
concept category: Principle
concrete expression: Engineer A made minor wording adjustments to AI-generated report text to personalize it and did not disclose AI authorship, effectively presenting AI-generated content as independently authored professional writing.
confidence: 0.87
interpretation: Personalizing AI-generated text without disclosing its origin misrepresents the intellectual authorship of the work product. The client's observation that the report read as if written by two authors indicates the concealment was imperfect and material.
invoked by: Engineer A AI-Assisted Design
principle class: Intellectual Honesty in Authorship Principle
tension resolution: The principle was violated: Engineer A's minor edits did not transform AI-generated content into independently authored work, and the absence of disclosure misrepresented the work's intellectual origin.
text references: Engineer A also made minor adjustments to some of the wording to personalize the content.
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
text references: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.75
match reasoning: Via class 'Intellectual Honesty in Authorship Principle': Intellectual Honesty exists in the ontology as a general principle. The AI authorship context is a specific and emergent variant that the existing class does not fully address, particularly the novel question of whether presenting AI-generated text without disclosure constitutes a failure of intellectual honesty. The match is a variant rather than a direct match, warranting a new class that specializes the existing principle for AI authorship contexts.
matched ontology class: Intellectual Honesty
matched ontology label: Intellectual Honesty
matches existing: true
source text: Engineer A also made minor adjustments to some of the wording to personalize the content. Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A made minor wording adjustments to AI-generated report text to personalize it and did not disclose AI authorship, effectively presenting AI-generated content as independently authored professional writing.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Disclosure
type: AIDisclosureConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A used an AI-assisted drafting tool new to the market to generate preliminary engineering design documents for Client W but did not disclose this use, and the documents were later found to contain misaligned dimensions and omitted safety features.
concept category: Constraint
confidence: 0.88
constraint class: AI Disclosure Constraint
constraint statement: Engineer A was constrained by professional ethics to disclose to Client W that AI-assisted drafting tools were used to generate the preliminary engineering design documents, and failure to do so constituted a violation of this constraint.
severity: high
source: NSPE Code of Ethics, professional norms on honesty and transparency with clients
temporal scope: At the time of design document submission to Client W
text references: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:06:33.588436+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was constrained by professional ethics to disclose to Client W that AI-assisted drafting tools were used to generate the preliminary engineering design documents, and failure to do so constituted a violation of this constraint.
generated at time: 2026-06-03T14:06:33.588436+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Disclosure Transparency
type: AIToolDisclosurePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated contaminant report and design documents
applied to: Client W
balancing with: Attribution and Credit Principle
balancing with: Client Data Confidentiality Principle
concept category: Principle
concrete expression: Engineer A did not proactively disclose to Client W that AI tools substantially contributed to the contaminant report and design documents, and Client W subsequently identified inconsistencies and errors that proactive disclosure could have helped prevent or address.
confidence: 0.87
interpretation: While no universal guidelines mandate AI disclosure, best practices and the transparency obligations underlying NSPE Code section III.9 support informing clients when AI substantially shapes a work product, particularly when the client may need to assess reliability or provenance.
invoked by: Engineer A Environmental Engineer
principle class: AI Tool Disclosure Principle
tension resolution: The BER found that proactive disclosure would have strengthened trust and prevented misunderstandings, treating it as a best-practice obligation even in the absence of a universal mandate.
text references: Given that Client W identified issues in the engineering design and questioned inconsistencies in the report, proactive disclosure could have prevented misunderstandings and strengthened trust.
text references: There are currently no universal guidelines mandating AI disclosure in engineering work, but best practices suggest informing clients when AI substantially contributes to a work product.
text references: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency. BER Case 98-3 emphasized that engineers must acknowledge significant contributions by others.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A did not proactively disclose to Client W that AI tools substantially contributed to the contaminant report and design documents, and Client W subsequently identified inconsistencies and errors that proactive disclosure could have helped prevent or address.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Attribution
type: AttributionandCreditPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated contaminant report
balancing with: AI Tool Disclosure Principle
balancing with: Intellectual Honesty in Authorship Principle
concept category: Principle
concrete expression: Engineer A's AI-generated contaminant report did not include citations of pertinent documents of technical authority, and Engineer A did not disclose to Client W that AI substantially contributed to the report, failing the attribution and credit obligation under NSPE Code section III.9.
confidence: 0.88
interpretation: Attribution obligations require both citation of technical sources synthesized by AI and disclosure of AI's substantial role in shaping the work product. Absence of citations undermines the professional record; absence of disclosure prevents the client from assessing provenance.
invoked by: Engineer A Environmental Engineer
principle class: Attribution and Credit Principle
tension resolution: The BER found that proactive disclosure of AI contributions and proper citation of technical authority were required for ethical use of AI in report preparation, and their absence rendered Engineer A's use of AI less than ethical.
text references: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9.
text references: Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
text references: The facts do not indicate the AI-generated report included citations of pertinent documents of technical authority.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Per Code section III.9, engineers are required to 'give credit for engineering work to those to whom credit is due,' so Engineer A's ethical use of the AI software would need to include appropriate citations.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A's AI-generated contaminant report did not include citations of pertinent documents of technical authority, and Engineer A did not disclose to Client W that AI substantially contributed to the report, failing the attribution and credit obligation under NSPE Code section III.9.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Tool Non-Disclosure Report
type: AIToolDisclosurePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Contaminant report submitted to Client W
balancing with: Client expectations for polished deliverables
concept category: Principle
concrete expression: Engineer A used AI software to generate the initial draft of the contaminant report but did not disclose this to Client W, submitting the report without citing the AI software or its large language models.
confidence: 0.9
interpretation: Professional norms of transparency require disclosure of AI tool use so clients can assess the provenance and reliability of the work product. Non-disclosure here concealed a material fact about how the report was produced.
invoked by: Engineer A AI-Assisted Design
principle class: AI Tool Disclosure Principle
tension resolution: The principle was violated: Engineer A chose not to disclose AI use, prioritizing seamless delivery over transparent representation of authorship.
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A used AI software to generate the initial draft of the contaminant report but did not disclose this to Client W, submitting the report without citing the AI software or its large language models.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Environmental Engineer
type: EnvironmentalEngineer
type: NamedIndividual
adheres to principle: Engineer A AI Disclosure Transparency
adheres to principle: Engineer A AI Report Attribution
adheres to principle: Engineer A AI Report Competence
adheres to principle: Engineer A Client Data AI Upload
has obligation: Engineer A AI Report Disclosure
has obligation: Engineer A Client Data AI Upload
has obligation: Engineer A Report AI Disclosure
has obligation: Engineer A Report Technical Citations
actor: Engineer A
case involvement: Licensed environmental engineer retained by Client W to prepare a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications at a monitored site.
concept category: Role
confidence: 0.92
experience level: Several years
has license: Professional Engineer
has specialty: Environmental engineering, groundwater monitoring
role category: provider_client
role class: Environmental Engineer
text references: Engineer A was tasked to develop engineering design documents (plans and specifications) for modifications to groundwater infrastructure at the same site
text references: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:26.869728+00:00
first discovered in case: 7
match confidence: 0.75
match reasoning: Via class 'Environmental Engineer': Environmental Engineer is a specialization of Engineer Role in the ontology. The ontology has Engineer Role as the occupational archetype head for all engineer specializations, so this is a medium-confidence match to the parent. A distinct leaf class is warranted because environmental engineering carries domain-specific obligations around contaminant reporting and groundwater infrastructure not captured by the generic Engineer Role.
matched ontology class: EngineerRole
matched ontology label: Engineer Role
matches existing: true
source text: Engineer A, an environmental engineer with several years of experience and holding a professional engineering license, was retained by Client W to prepare a comprehensive report
synthesis literal: caseInvolvement
synthesis literal: confidence
synthesis literal: roleCategory
synthesis literal: roleClass
synthesis literal: textReferences
comment: Licensed environmental engineer retained by Client W to prepare a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications at a monitored site.
generated at time: 2026-06-03T13:59:26.869728+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Regulatory Non-Compliance Design
type: Non-CompliantState
type: NamedIndividual
activates obligation: Engineer A Safety Feature Omission
affects: Client W
affects: Engineer A
active period: From submission of the deficient design documents through correction and resubmission
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.93
principle transformation: Transforms general professional responsibility and public safety principles into specific corrective action and notification duties once deficiencies in a submitted work product are confirmed.
state class: Non-Compliant State
subject: The engineering design documents that omit safety features required by local regulations
terminated by: Engineer A revising the plans to satisfy regulatory requirements
text references: an omission of key safety features required by local regulations
text references: instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards
triggering event: Client W identifying that the AI-generated design documents omit key safety features required by local regulations
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Non-Compliant State'
matched ontology class: NonCompliant
matched ontology label: Non-Compliant State
matches existing: true
source text: an omission of key safety features required by local regulations
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The engineering design documents that omit safety features required by local regulations
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Transparency to Client
type: Transparency
type: NamedIndividual
invoked by: Engineer A
applied to: Report and design documents submitted to Client W
balancing with: Client perception of professional capability
balancing with: Competitive norms
concept category: Principle
concrete expression: Engineer A did not disclose the use of AI tools to Client W in either the report or the design documents, depriving the client of information material to evaluating the work product's reliability and the basis for the engineer's professional judgments.
confidence: 0.86
interpretation: Transparency in professional relationships requires engineers to be open about the methods and tools used to produce work products, particularly when those tools are novel and their reliability is uncertain.
invoked by: Engineer A AI-Assisted Design
principle class: Transparency
tension resolution: The principle was not satisfied: non-disclosure of AI tool use prevented the client from making an informed assessment of the work product's provenance.
text references: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Transparency'
matched ontology class: Transparency
matched ontology label: Transparency
matches existing: true
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft, but applied their seal consistent with state law.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A did not disclose the use of AI tools to Client W in either the report or the design documents, depriving the client of information material to evaluating the work product's reliability and the basis for the engineer's professional judgments.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Unfamiliar Drafting Tool
type: UnfamiliarToolDeploymentState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A Design AI Output Verification
activates constraint: Engineer A Unfamiliar Drafting Tool Use
activates obligation: Engineer A AI Design Disclosure
activates obligation: Engineer A Design Documents Verification
affects: Client W
affects: Engineer A
active period: From Engineer A's adoption of the new AI drafting tool through the production and submission of the design documents
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.88
principle transformation: Transforms general competence and due care principles into specific verification and disclosure duties when deploying tools whose accuracy and limitations are not yet understood by the professional.
state class: Unfamiliar Tool Deployment State
subject: Engineer A's use of an AI-assisted drafting tool that was new to the market and with which Engineer A had no established experience
terminated by: Would require Engineer A to develop sufficient familiarity and verification protocols for the tool before relying on its outputs for professional work products
text references: Engineer A also prepared draft design documents with an AI-assisted drafting tool that was new to the market.
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
triggering event: Engineer A electing to use a newly released AI-assisted drafting tool without prior experience or established verification protocols for its outputs
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A also prepared draft design documents with an AI-assisted drafting tool that was new to the market.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's use of an AI-assisted drafting tool that was new to the market and with which Engineer A had no established experience
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Supervisor Retirement
type: Event
type: NamedIndividual
causes state change: Engineer A lost access to supervisory oversight and quality assurance support, leaving the project without a senior review resource.
concept category: Event
event type: exogenous
initiates text: Reduced QA Support
initiates text: Unsupervised Practice State
severity: high
temporal extent: instant
temporal marker: Before project deliverables were due, over a year into site observation
temporal sequence: 1
terminates text: Active Supervision State
terminates text: QA Resource Available State
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: Engineer B, Engineer A's mentor and supervisor, retired before project deliverables were due, removing the primary quality assurance resource from the project.
has time: Before project deliverables were due, over a year into site observation
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Authorship Representation
type: AIAuthorshipHonestyObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A made minor wording adjustments to AI-generated report text to personalize it and submitted the report without disclosing AI authorship, effectively presenting the AI-generated content as their own original professional writing.
compliance status: unmet
concept category: Obligation
confidence: 0.88
derived from principle: Engineer A AI Authorship Concealment
obligation class: AI Authorship Honesty Obligation
obligation statement: Engineer A was obligated to accurately represent the AI-generated origin of the contaminant report content and to refrain from presenting AI-generated text as their own original intellectual work by making only minor wording adjustments without attribution.
temporal scope: At the time of preparing and submitting the draft contaminant report
text references: Engineer A also made minor adjustments to some of the wording to personalize the content.
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
text references: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A also made minor adjustments to some of the wording to personalize the content.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to accurately represent the AI-generated origin of the contaminant report content and to refrain from presenting AI-generated text as their own original intellectual work by making only minor wording adjustments without attribution.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Undisclosed Use
type: UndisclosedAIUseState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Design Disclosure
activates constraint: Engineer A AI Report Disclosure
activates obligation: Engineer A AI Report Disclosure
activates obligation: Engineer A Report AI Disclosure
affects: Client W
affects: Engineer A
terminated by event: AI Report Generation
active period: From report submission through case analysis; no disclosure is noted in the facts
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.88
principle transformation: Transforms honesty and transparency principles into specific disclosure obligations when AI tools have played a material role in producing a professional work product.
state class: Undisclosed AI Use State
subject: Engineer A's use of AI language processing software to draft the groundwater monitoring report without disclosing that use to Client W or including AI attribution
terminated by: Would require proactive disclosure to Client W and inclusion of appropriate citations
text references: AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9.
text references: The facts also do not indicate the AI-generated report included citations of pertinent documents of technical authority.
text references: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
triggering event: Engineer A submitting the AI-assisted report to Client W without disclosure or attribution
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's use of AI language processing software to draft the groundwater monitoring report without disclosing that use to Client W or including AI attribution
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Confidential Client Data AI Input
type: ConfidentialInformationHeld
type: NamedIndividual
activated by event: AI Report Generation
activated by event: Client Data Exposure
activates constraint: Engineer A AI Design Attribution
activates constraint: Engineer A AI Report Attribution
activates obligation: Engineer A AI Design Disclosure
affects: Client W
affects: Engineer A
terminated by event: AI Report Generation
active period: From Engineer A inputting Client W's information into the AI software through the engagement
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.88
principle transformation: Transforms the general honesty and attribution principles into a concrete obligation to proactively disclose when AI has substantially shaped a work product, even absent a universal regulatory mandate to do so.
state class: Confidential Information Held
subject: Client W's proprietary site data and groundwater monitoring information input into open-source AI software
terminated by: Not resolved within the case
text references: Engineer A gathered the relevant information provided by Client W and relied on the AI software to synthesize the information
text references: Engineer A input the information gathered from Client W into the AI software
text references: The AI drafting software was also open-sourced
triggering event: Engineer A entering information gathered from Client W into open-source AI software
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Confidential Information Held'
matched ontology class: ConfidentialInformation
matched ontology label: Confidential Information Held
matches existing: true
source text: Engineer A gathered the relevant information provided by Client W and relied on the AI software to synthesize the information
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Client W's proprietary site data and groundwater monitoring information input into open-source AI software
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Documents Verification
type: AIOutputVerificationObligation
type: NamedIndividual
defeasible under: Engineer A Unfamiliar Drafting Tool
obligated party: Engineer A
case context: Engineer A conducted only a cursory review of AI-generated design documents produced by a tool with which Engineer A had no prior experience, resulting in submission of documents with misaligned dimensions and omitted safety features required by local regulations.
compliance status: unmet
concept category: Obligation
confidence: 0.92
derived from principle: Engineer A AI Design Verification Failure
derived from principle: Engineer A Design Documents Competence Failure
obligation class: AI Output Verification Obligation
obligation statement: Engineer A was obligated to conduct a thorough and competent review of the AI-generated engineering design documents, sufficient to identify regulatory non-compliance and technical errors, before submitting those documents to Client W.
temporal scope: Prior to submission of engineering design documents to Client W
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.75
match reasoning: Via class 'AI Output Verification Obligation': This obligation is a specialization of the existing Competence Obligation, applied specifically to the context of AI-generated outputs. The existing class covers the general duty to practice within competence, but does not address the specific verification duty that arises when AI tools are used to generate professional work products. A new class is warranted to capture this distinct obligation type.
matched ontology class: CompetenceObligation
matched ontology label: Competence Obligation
matches existing: true
source text: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to conduct a thorough and competent review of the AI-generated engineering design documents, sufficient to identify regulatory non-compliance and technical errors, before submitting those documents to Client W.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Public Safety Design Omission
type: PublicSafetyatRisk
type: NamedIndividual
activated by event: Design Defect Discovery
activates obligation: Engineer A Safety Feature Omission
affects: Client W
affects: Engineer A
active period: From identification of the safety feature omissions through correction of the design documents
affected parties: Client W
affected parties: Engineer A
affected parties: public users of the groundwater infrastructure
concept category: State
confidence: 0.9
principle transformation: Transforms general professional responsibility and public safety principles into specific corrective action and notification duties once deficiencies in a submitted work product are confirmed.
state class: Public Safety at Risk
subject: The risk to public safety created by the omission of required safety features in the engineering design documents
terminated by: Engineer A revising the plans to include all required safety features
text references: Client W raised concerns about the accuracy and reliability of the engineering design
text references: an omission of key safety features required by local regulations
triggering event: Client W identifying that required safety features were omitted from the AI-generated design documents
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Public Safety at Risk'
matched ontology class: PublicSafetyAtRisk
matched ontology label: Public Safety at Risk
matches existing: true
source text: an omission of key safety features required by local regulations
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The risk to public safety created by the omission of required safety features in the engineering design documents
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Responsible Charge Deficit
type: ResponsibleChargeDeficitState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Judgment Substitution
activates obligation: Engineer A Design Safety Compliance
activates obligation: Engineer A Design Seal
affects: Client W
affects: Engineer A
active period: From Engineer A's use of the AI drafting tool through the submission of deficient design documents; persists until responsible charge obligations are properly satisfied
affected parties: Client W
affected parties: Engineer A
affected parties: public safety
concept category: State
confidence: 0.9
principle transformation: Transforms the responsible charge and public safety principles into a concrete prohibition on passive post-hoc review as a substitute for active supervisory engagement throughout the engineering process.
state class: Responsible Charge Deficit State
subject: Engineer A's failure to maintain active supervisory direction and control over AI-generated design documents, relying on post-preparation review rather than engagement throughout the design process
terminated by: Would require Engineer A to re-engage with comprehensive verification and active supervisory direction; not resolved within the case facts
text references: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
text references: Engineer A, as the engineer in Responsible Charge of the project, is required to provide an experienced-based quality assurance review, engaging in critical discussions, mentorship, and professional development.
text references: Reviewing drawings or documents after preparation without involvement in the design and development process does not satisfy the definition of Responsible Charge.
triggering event: Engineer A sealing and submitting AI-generated design documents reviewed only at a high level without active involvement in the design and development process
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's failure to maintain active supervisory direction and control over AI-generated design documents, relying on post-preparation review rather than engagement throughout the design process
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Undisclosed AI Design
type: UndisclosedAIUseState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Design Attribution
activates constraint: Engineer A AI Report Disclosure
activates obligation: Engineer A AI Report Disclosure
activates obligation: Engineer A Report AI Disclosure
affects: Client W
affects: Engineer A
terminated by event: AI Report Generation
active period: From submission of the design documents through the case's described events
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.92
principle transformation: Transforms honesty and transparency principles into specific disclosure obligations when AI tools have played a material role in producing a professional work product.
state class: Undisclosed AI Use State
subject: Engineer A's omission of disclosure of AI use in the engineering design documents
terminated by: Not resolved within the case
text references: Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents
triggering event: Engineer A submitting the AI-assisted design documents to Client W without disclosing AI use
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's omission of disclosure of AI use in the engineering design documents
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Tool Adoption for Design
type: Action
type: NamedIndividual
initiates: Engineer A AI Design Documents
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Risk of errors in AI-generated designs given Engineer A's unfamiliarity with the tool and absence of comprehensive review process
guided by principle: Engineer A AI Design Substitution
guided by principle: Engineer A Professional Competence AI Use
guided by principle text: Professional Competency
guided by principle text: Technological Innovation in Engineering Practice
has agent: Engineer A
has mental state: deliberate
initiates text: AI-Assisted Design Document Drafting State
initiates text: Client Confidential Data in Public Domain State
intended outcome: Efficiently generate preliminary design documents to meet project deliverable requirements without the benefit of Engineer B's oversight
raises obligation: Engineer A Design Responsible Charge
raises obligation text: Direction and Control Over Work Product
raises obligation text: Hold Paramount the Safety, Health, and Welfare of the Public
raises obligation text: Responsible Charge
requires capability text: Engineering design expertise for groundwater infrastructure
requires capability text: Proficiency with AI drafting tool capabilities and limitations
requires capability text: Regulatory knowledge for local safety requirements
temporal extent: interval
temporal marker: During design document preparation phase
temporal sequence: 12
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A decided to use AI-assisted drafting tools, which were new to the market and with which Engineer A had no prior experience, to generate preliminary engineering design documents including basic layouts and technical specifications for the groundwater infrastructure modifications.
has time: During design document preparation phase
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client Data Upload to AI
type: Action
type: NamedIndividual
initiates: Engineer A Client Data Exposure
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Potential exposure of confidential client information to the public domain
guided by principle: Engineer A Client Data AI Upload
guided by principle: Engineer A Transparency to Client
guided by principle text: Avoid Deceptive Acts
guided by principle text: Respect for Client Privacy
has agent: Engineer A
has mental state: deliberate
initiates text: Client Confidential Data in Public Domain State
intended outcome: Provide the AI software with sufficient project context to generate relevant and accurate draft content
requires capability text: Client confidentiality management
requires capability text: Understanding of data privacy implications of open-source AI platforms
temporal extent: instant
temporal marker: During both report and design document preparation phases
temporal sequence: 5
violates obligation: Engineer A Client Data AI Upload
violates obligation text: Client Confidentiality
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A entered Client W's private project information into the open-source AI software interface to generate report content and design documents, effectively placing confidential client data into a public-domain platform without obtaining Client W's prior consent.
has time: During both report and design document preparation phases
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Draft Report Sealing and Submission
type: Action
type: NamedIndividual
fulfills obligation: Engineer A Report AI Direction Control
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Sealing a document with undisclosed AI contributions and without full citation of technical authority sources
fulfills obligation text: Direction and Control Over Work Product
fulfills obligation text: Perform Services Within Competence
guided by principle: Engineer A Professional Competence AI Use
guided by principle: Engineer A Responsible Charge Design Failure
guided by principle: Engineer A Seal on AI Design Documents
guided by principle text: Professional Competency
guided by principle text: Responsible Charge
has agent: Engineer A
has mental state: deliberate
initiates text: Sealed Draft Report Submitted State
intended outcome: Fulfill the contractual deliverable and assert professional responsibility over the report content in accordance with state licensure requirements
requires capability text: Environmental engineering expertise sufficient to take responsible charge of the report
requires capability text: Understanding of sealing obligations under state law
temporal extent: instant
temporal marker: At report submission
temporal sequence: 10
terminates text: Dual Deliverable Obligation for Report
violates obligation: Engineer A AI Authorship Representation
violates obligation: Engineer A Report Technical Citations
violates obligation text: Credit and Attribution for Engineering Work
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A applied their professional seal to the draft report consistent with state law and submitted it to Client W with language clearly identifying it as a draft.
has time: At report submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Documents
type: AI-GeneratedWorkProductState
type: NamedIndividual
activated by event: AI Design Generation
activates constraint: Engineer A AI Design Disclosure
activates constraint: Engineer A Design AI Output Verification
activates obligation: Engineer A AI Design Disclosure
activates obligation: Engineer A Report AI Verification
affects: Client W
affects: Engineer A
active period: From AI generation of the design documents through Client W's identification of deficiencies
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.93
principle transformation: Transforms general honesty, competence, and professional accountability principles into specific duties of disclosure, verification, and independent review when AI tools contribute substantially to a professional work product.
state class: AI-Generated Work Product State
subject: The engineering design documents generated using AI-assisted drafting tools and submitted to Client W
terminated by: Client W's identification of deficiencies and instruction to revise
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions
text references: Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans
triggering event: Engineer A using AI-assisted drafting tools to generate preliminary design plans and specifications and submitting them to Client W
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The engineering design documents generated using AI-assisted drafting tools and submitted to Client W
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Responsible Charge
type: ResponsibleChargeVerificationObligation
type: NamedIndividual
defeasible under: Engineer A Responsible Charge Deficit
obligated party: Engineer A
case context: Engineer A sealed and submitted AI-generated design documents after only a high-level review, without substantive involvement in the design and development process, resulting in omitted safety features and misaligned dimensions.
compliance status: unmet
concept category: Obligation
confidence: 0.92
derived from principle: Engineer A Responsible Charge Design Failure
obligation class: Responsible Charge Verification Obligation
obligation statement: Engineer A was obligated to conduct a comprehensive, experience-based verification of the AI-generated design documents with active involvement in the design and development process before sealing and submitting them.
temporal scope: During preparation and prior to sealing and submission of the design documents
text references: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
text references: Engineer A's oversight of engineering plans was inadequate, raising ethical concerns. AI-generated technical work requires at least the same level of scrutiny as human-created work.
text references: Reviewing drawings or documents after preparation without involvement in the design and development process does not satisfy the definition of Responsible Charge.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.82
match reasoning: Via class 'Responsible Charge Verification Obligation': This obligation is closely related to the already-extracted Responsible Charge Seal Obligation but emphasizes the verification and active-involvement dimension rather than the sealing act itself. It is a variant of that class focusing on the process of responsible charge rather than the sealing act.
matched ontology class: ResponsibleChargeSealObligation
matched ontology label: Responsible Charge Seal Obligation
matches existing: true
source text: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to conduct a comprehensive, experience-based verification of the AI-generated design documents with active involvement in the design and development process before sealing and submitting them.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report AI Direction Control
type: AIDirectionandControlObligation
type: NamedIndividual
defeasible under: Engineer A AI Report Work Product
obligated party: Engineer A
case context: Engineer A used open-source AI software to generate the initial contaminant report draft, then performed a thorough review, cross-checked key facts against professional journal articles, and made adjustments to the text.
compliance status: met
concept category: Obligation
confidence: 0.88
derived from principle: Engineer A Report AI Verification
obligation class: AI Direction and Control Obligation
obligation statement: Engineer A was obligated to exercise direction and control over the AI language processing tool used to generate the contaminant report draft, which was satisfied by thorough review and cross-checking against professional sources.
temporal scope: During preparation and review of the contaminant report
text references: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control, as required by Code section II.2.b.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Because Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text, the final document remained under Engineer A's direction and control, as required by Code section II.2.b.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to exercise direction and control over the AI language processing tool used to generate the contaminant report draft, which was satisfied by thorough review and cross-checking against professional sources.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Safety Feature Omission
type: PublicSafetyParamount
type: NamedIndividual
invoked by: Engineer A
applied to: Groundwater infrastructure design documents
balancing with: Client delivery expectations
balancing with: Time pressure
concept category: Principle
concrete expression: AI-generated design documents submitted by Engineer A omitted key safety features required by local regulations, creating a potential public safety risk that the client identified during review.
confidence: 0.88
interpretation: The omission of required safety features from engineering design documents implicates the fundamental obligation to hold public safety paramount. The engineer's cursory review of AI-generated plans failed to protect against this risk.
invoked by: Engineer A Responsible Charge
principle class: Public Safety Paramount
tension resolution: The principle was not adequately served: the failure to verify AI-generated safety-critical design elements allowed a public safety risk to reach the client review stage rather than being caught by the engineer.
text references: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Public Safety Paramount'
matched ontology class: PublicSafetyParamount
matched ontology label: Public Safety Paramount
matches existing: true
source text: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: AI-generated design documents submitted by Engineer A omitted key safety features required by local regulations, creating a potential public safety risk that the client identified during review.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Seal on AI Design Documents
type: ResponsibleChargeIntegrityPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: Sealed engineering design documents for groundwater infrastructure
balancing with: Loss of mentor review
balancing with: Time pressure
concept category: Principle
concrete expression: Engineer A applied their professional seal to engineering design documents generated primarily by AI tools after only a cursory review, submitting plans that contained misaligned dimensions and omitted required safety features.
confidence: 0.89
interpretation: Applying a professional seal represents a public declaration of responsible charge and independent professional judgment. A cursory review of AI-generated documents that fails to catch regulatory omissions does not satisfy the substantive oversight the seal implies.
invoked by: Engineer A Responsible Charge
principle class: Responsible Charge Integrity Principle
tension resolution: The principle was violated: the seal was applied without the substantive independent review it represents, as evidenced by the errors identified by the client.
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
text references: submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft, but applied their seal consistent with state law.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A applied their professional seal to engineering design documents generated primarily by AI tools after only a cursory review, submitting plans that contained misaligned dimensions and omitted required safety features.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Disclosure Omission for Report
type: Action
type: NamedIndividual
initiates: Engineer A AI Report Undisclosed Use
initiates: Engineer A Undisclosed AI Report
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Failure to give credit to AI contributions as required by attribution norms
foreseen unintended effects: Potential client misunderstanding about authorship
guided by principle: Engineer A AI Authorship Concealment
guided by principle: Engineer A AI Disclosure Transparency
guided by principle: Engineer A AI Report Attribution
guided by principle: Engineer A AI Tool Non-Disclosure Report
guided by principle: Engineer A Transparency to Client
guided by principle text: Professional Integrity
guided by principle text: Transparency and Attribution
has agent: Engineer A
has mental state: deliberate
initiates text: Undisclosed AI Contribution to Report State
intended outcome: Submit the report as a professional work product without drawing attention to AI involvement, consistent with then-current absence of universal mandatory disclosure guidelines
requires capability text: Awareness of professional attribution norms
requires capability text: Judgment about disclosure obligations for AI-assisted work
temporal extent: instant
temporal marker: At report submission
temporal sequence: 9
violates obligation: Engineer A AI Authorship Representation
violates obligation: Engineer A AI Report Disclosure
violates obligation: Engineer A Report AI Disclosure
violates obligation text: Avoid Deceptive Acts
violates obligation text: Credit and Attribution for Engineering Work
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A chose not to disclose the use of AI language processing software or cite its contributions when submitting the draft report to Client W, and did not include citations to the AI-generated content or the large language models used.
has time: At report submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Disclosure
type: AIToolDisclosureObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used open-source AI software to generate the initial draft of a contaminant report for Client W and submitted the report without disclosing AI involvement, making only minor wording adjustments to personalize the content.
compliance status: unmet
concept category: Obligation
confidence: 0.93
derived from principle: Engineer A AI Tool Non-Disclosure Report
obligation class: AI Tool Disclosure Obligation
obligation statement: Engineer A was obligated to disclose to Client W that AI software was used to generate the initial draft of the contaminant report, including the use of large language models, before or at the time of submission.
temporal scope: At the time of submitting the draft report to Client W
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to disclose to Client W that AI software was used to generate the initial draft of the contaminant report, including the use of large language models, before or at the time of submission.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Client Data Exposure
type: ClientDataExposedState
type: NamedIndividual
activated by event: Client Data Exposure
activates constraint: Engineer A AI Report Disclosure
activates constraint: Engineer A Client Data Upload Consent
activates obligation: Engineer A Report AI Disclosure
affects: Client W
affects: Engineer A
active period: From the moment Engineer A uploaded Client W's data to the AI platform through the point of case analysis; no remediation or consent is noted in the facts
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.9
principle transformation: Transforms the general confidentiality principle into a concrete obligation to notify the client and obtain consent before using open-domain AI tools with private client data.
state class: Client Data Exposed State
subject: Engineer A's upload of Client W's confidential information to an open-source AI interface
terminated by: Not terminated within the case facts; would require client notification, consent, or confirmed data removal
text references: The facts here do not indicate Engineer A obtained permission from Client W to use the private information in the public domain.
text references: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
triggering event: Engineer A uploading Client W's private information into an open-source AI interface without prior consent
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: When Engineer A uploaded Client W's information into the AI open-source interface, this was tantamount to placing the Client's private information in the public domain.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's upload of Client W's confidential information to an open-source AI interface
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Responsible Charge
type: ResponsibleChargeEngineer
type: NamedIndividual
adheres to principle: Engineer A Mentor Loss Response
adheres to principle: Engineer A Mentorship Loss Design Oversight
adheres to principle: Engineer A Public Safety Design Errors
adheres to principle: Engineer A Responsible Charge Design Failure
adheres to principle: Engineer A Safety Feature Omission
adheres to principle: Engineer A Seal on AI Design Documents
has obligation: Engineer A Design Responsible Charge
has obligation: Engineer A Design Safety Compliance
has obligation: Engineer A Design Seal
has obligation: Engineer A Mentor Loss Response
has obligation: Engineer A Safety Feature Omission
actor: Engineer A
case involvement: Bore formal responsible charge over the AI-assisted design documents and contaminant report, but conducted only a high-level review of AI-generated engineering plans, failing to satisfy the active engagement and supervisory control requirements of responsible charge, resulting in undetected dimensional errors and omitted safety features.
concept category: Role
confidence: 0.88
has license: Professional Engineer
has specialty: Environmental engineering
other attribute: responsible_charge_status: Deficient under NSPE Position Statement No. 10-1778
role category: provider_client
role class: Responsible Charge Engineer
text references: By relying on AI-assisted tools without a comprehensive verification process of its output, Engineer A risked violating this requirement
text references: Engineer A did not maintain responsible charge in violation of licensure law
text references: Engineer A, as the engineer in Responsible Charge of the project, is required to provide an experienced-based quality assurance review, engaging in critical discussions, mentorship, and professional development
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:00:40.742585+00:00
first discovered in case: 7
match confidence: 0.72
match reasoning: Via class 'Responsible Charge Engineer': Responsible Charge Engineer is a specialization of Engineer Role, distinguished by the formal licensure-law concept of responsible charge, which imposes active engagement and supervisory control obligations beyond general engineering practice. No existing extracted class captures this specific licensure-based accountability framing.
matched ontology class: EngineerRole
matched ontology label: Engineer Role
matches existing: true
source text: Engineer A did not maintain responsible charge in violation of licensure law
synthesis literal: caseInvolvement
synthesis literal: confidence
synthesis literal: roleCategory
synthesis literal: roleClass
synthesis literal: textReferences
comment: Bore formal responsible charge over the AI-assisted design documents and contaminant report, but conducted only a high-level review of AI-generated engineering plans, failing to satisfy the active engagement and supervisory control requirements of responsible charge, resulting in undetected dimensional errors and omitted safety features.
generated at time: 2026-06-03T14:00:40.742585+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Responsible Charge Design Failure
type: ResponsibleChargeIntegrityPrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents
balancing with: Technology Substitution Prohibition Principle
concept category: Principle
concrete expression: Engineer A sealed and submitted AI-generated design documents after only a high-level review, without the substantive involvement in design and development required by responsible charge, resulting in documents with safety-critical errors reaching the client.
confidence: 0.93
interpretation: Responsible charge requires active engagement from conception to completion, not merely reviewing outputs after preparation. Engineer A's high-level review of AI-generated plans did not satisfy this standard, constituting a violation of licensure law and NSPE Code section III.8.a.
invoked by: Engineer A Responsible Charge
principle class: Responsible Charge Integrity Principle
tension resolution: The BER found no acceptable balance: responsible charge cannot be satisfied by reviewing AI outputs without substantive involvement in the design process, regardless of the efficiency benefits of AI-assisted drafting.
text references: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
text references: Engineer A, as the engineer in Responsible Charge of the project, is required to provide an experienced-based quality assurance review, engaging in critical discussions, mentorship, and professional development -- elements that AI cannot replicate.
text references: Reviewing drawings or documents after preparation without involvement in the design and development process does not satisfy the definition of Responsible Charge.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A did not maintain responsible charge in violation of licensure law which violates Code section III.8.a.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A sealed and submitted AI-generated design documents after only a high-level review, without the substantive involvement in design and development required by responsible charge, resulting in documents with safety-critical errors reaching the client.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design AI Output Verification
type: AIOutputVerificationConstraint
type: NamedIndividual
constrained entity: Engineer A
case context: Engineer A conducted only a high-level review of AI-generated design documents, failing to identify misaligned dimensions and omitted safety features required by local regulations, resulting in a deficient and noncompliant submission.
concept category: Constraint
confidence: 0.92
constraint class: AI Output Verification Constraint
constraint statement: Engineer A was required to conduct a sufficiently thorough independent technical review of the AI-generated engineering design documents before submission and sealing, sufficient to identify misaligned dimensions, omitted safety features, and regulatory noncompliance, and to take genuine responsible charge of the final work product.
severity: critical
source: NSPE Code of Ethics, Fundamental Canon I.1; Code section II.2.b; NSPE Position Statement No. 10-1778
temporal scope: Before submission and sealing of the AI-generated engineering design documents
text references: AI-generated technical work requires at least the same level of scrutiny as human-created work.
text references: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
text references: failure to detect misaligned dimensions and omitted safety features further indicates that Engineer A did not exercise sufficient diligence.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:11:08.316438+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A elected to only conduct a high-level review and adjusted certain elements to align with site-specific conditions.
synthesis literal: caseContext
synthesis literal: confidence
synthesis literal: constraintClass
synthesis literal: constraintStatement
synthesis literal: severity
synthesis literal: source
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was required to conduct a sufficiently thorough independent technical review of the AI-generated engineering design documents before submission and sealing, sufficient to identify misaligned dimensions, omitted safety features, and regulatory noncompliance, and to take genuine responsible charge of the final work product.
generated at time: 2026-06-03T14:11:08.316438+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Public Safety Design Risk
type: PublicSafetyatRisk
type: NamedIndividual
activated by event: AI Design Generation
activated by event: Design Defect Discovery
activates constraint: Engineer A Design Documents Verification
activates obligation: Engineer A Design Safety Compliance
activates obligation: Engineer A Design Seal
affects: Client W
affects: Engineer A
active period: From submission of the deficient design documents through Client W's identification of errors; full remediation not described
affected parties: Client W
affected parties: Engineer A
affected parties: public
concept category: State
confidence: 0.92
principle transformation: Transforms the responsible charge and public safety principles into a concrete obligation to apply at least the same level of scrutiny to AI-generated work as to human-generated work, including critical engagement with outputs rather than passive acceptance.
state class: Public Safety at Risk
subject: The risk to public safety arising from omitted safety features and misaligned dimensions in the AI-generated design documents submitted by Engineer A
terminated by: Would require correction of all safety-critical omissions and regulatory compliance verification
text references: The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards, conflicting with the Fundamental Canon I.1, 'hold paramount the safety, health, and welfare of the public'.
text references: key safety features (including those necessary for compliance with local regulations) were omitted.
triggering event: Client W's discovery of omitted safety features and misaligned dimensions in the design documents
urgency level: high
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Public Safety at Risk'
matched ontology class: PublicSafetyAtRisk
matched ontology label: Public Safety at Risk
matches existing: true
source text: key safety features (including those necessary for compliance with local regulations) were omitted.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The risk to public safety arising from omitted safety features and misaligned dimensions in the AI-generated design documents submitted by Engineer A
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report AI Verification
type: AIOutputVerificationObligation
type: NamedIndividual
defeasible under: Engineer A AI Report Work Product
obligated party: Engineer A
case context: Engineer A conducted a thorough review of the AI-generated report, cross-checking key facts against professional journal articles and running search engine queries to verify originality of phrasing, before submitting the draft report to Client W.
compliance status: met
concept category: Obligation
confidence: 0.87
derived from principle: Engineer A Report AI Verification
obligation class: AI Output Verification Obligation
obligation statement: Engineer A was obligated to conduct a thorough and competent review of the AI-generated contaminant report before submission, which Engineer A substantially met by cross-checking key facts against professional journal articles and verifying phrasing against existing published language.
temporal scope: Prior to submission of the draft contaminant report to Client W
text references: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.75
match reasoning: Via class 'AI Output Verification Obligation': This obligation is a specialization of the existing Competence Obligation, applied specifically to the context of AI-generated outputs. The existing class covers the general duty to practice within competence, but does not address the specific verification duty that arises when AI tools are used to generate professional work products. A new class is warranted to capture this distinct obligation type.
matched ontology class: CompetenceObligation
matched ontology label: Competence Obligation
matches existing: true
source text: Engineer A conducted a thorough review of the report, cross-checking key facts against professional journal articles and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to conduct a thorough and competent review of the AI-generated contaminant report before submission, which Engineer A substantially met by cross-checking key facts against professional journal articles and verifying phrasing against existing published language.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Thorough Report Review
type: Action
type: NamedIndividual
fulfills obligation: Engineer A Report AI Direction Control
terminates: Engineer A AI Report Draft
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Review may not catch all deficiencies given unfamiliarity with AI output characteristics
fulfills obligation text: Direction and Control Over Work Product
fulfills obligation text: Perform Services Within Competence
guided by principle: Engineer A Professional Competence AI Use
guided by principle: Engineer A Public Safety Design Errors
guided by principle: Engineer A Safety Feature Omission
guided by principle text: Professional Competency
guided by principle text: Public Safety
has agent: Engineer A
has mental state: deliberate
initiates text: Report Under Engineer Direction and Control State
intended outcome: Ensure factual accuracy, originality, and professional quality of the report before submission to Client W
requires capability text: Critical evaluation of AI-generated text
requires capability text: Environmental engineering domain expertise
requires capability text: Technical knowledge to fact-check environmental contaminant content
temporal extent: interval
temporal marker: After receiving the AI-generated report draft, before submission
temporal sequence: 8
terminates text: Unverified AI Report Draft State
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A conducted a thorough review of the AI-generated report draft, cross-checking key facts against professional journal articles, verifying phrasing through search engine queries to check for copied language, and making minor wording adjustments to personalize the content.
has time: After receiving the AI-generated report draft, before submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Draft
type: AI-GeneratedWorkProductState
type: NamedIndividual
activated by event: AI Design Generation
activated by event: AI Report Generation
activates constraint: Engineer A AI Design Disclosure
activates constraint: Engineer A Design AI Output Verification
activates obligation: Engineer A AI Design Disclosure
activates obligation: Engineer A Report AI Verification
affects: Client W
affects: Engineer A
active period: From AI generation of the report draft through submission to Client W
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.93
principle transformation: Transforms general honesty, competence, and professional accountability principles into specific duties of disclosure, verification, and independent review when AI tools contribute substantially to a professional work product.
state class: AI-Generated Work Product State
subject: The draft report generated using AI software and submitted to Client W
terminated by: Client W's review and identification of inconsistencies; pending revision
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
text references: Engineer A relied on the AI software to synthesize the information and generate an initial draft of the necessary report
text references: applied their seal consistent with state law
triggering event: Engineer A using AI software to generate the initial draft report and submitting it to Client W with a professional seal
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T14:00:13.061399+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A relied on the AI software to synthesize the information and generate an initial draft of the necessary report
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: The draft report generated using AI software and submitted to Client W
generated at time: 2026-06-03T14:00:13.061399+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Seal
type: ResponsibleChargeSealObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A applied their professional seal to AI-generated engineering design documents after only a cursory review, and the sealed documents contained misaligned dimensions and omitted safety features required by local regulations.
compliance status: unmet
concept category: Obligation
confidence: 0.9
derived from principle: Engineer A Seal on AI Design Documents
obligation class: Responsible Charge Seal Obligation
obligation statement: Engineer A was obligated to apply their professional seal to the engineering design documents only after conducting a review sufficient to take genuine professional responsibility for the content, including verification that all regulatory safety requirements were satisfied.
temporal scope: At the time of sealing and submitting the engineering design documents
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: Engineer A applied their seal consistent with state law.
text references: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A applied their seal consistent with state law.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to apply their professional seal to the engineering design documents only after conducting a review sufficient to take genuine professional responsibility for the content, including verification that all regulatory safety requirements were satisfied.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Public Safety Design Errors
type: PublicSafetyParamount
type: NamedIndividual
invoked by: Engineer A
applied to: AI-generated engineering design documents with omitted safety features
balancing with: Professional Competence
balancing with: Responsible Charge Integrity Principle
concept category: Principle
concrete expression: Engineer A's insufficient review of AI-generated design documents resulted in omitted safety features and misaligned dimensions that could cause regulatory noncompliance and safety hazards, violating the paramount obligation to protect public safety.
confidence: 0.94
interpretation: The omission of safety features required for regulatory compliance directly implicated public welfare. The BER treated this as the most serious ethical concern arising from Engineer A's use of AI-assisted drafting, grounding the responsible charge and competence violations in the fundamental canon.
invoked by: Engineer A Responsible Charge
principle class: Public Safety Paramount
tension resolution: Public safety paramountcy was not balanced against competing considerations; it served as the foundational reason why insufficient AI review is ethically impermissible regardless of efficiency or tool novelty.
text references: The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards, conflicting with the Fundamental Canon I.1, 'hold paramount the safety, health, and welfare of the public'.
text references: While AI-assisted drafting can be beneficial, the identified errors suggest insufficient review, which could compromise public welfare and impinge on Engineer A's ethical and professional obligations.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:08:23.434917+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Public Safety Paramount'
matched ontology class: PublicSafetyParamount
matched ontology label: Public Safety Paramount
matches existing: true
source text: The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards, conflicting with the Fundamental Canon I.1, 'hold paramount the safety, health, and welfare of the public'.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A's insufficient review of AI-generated design documents resulted in omitted safety features and misaligned dimensions that could cause regulatory noncompliance and safety hazards, violating the paramount obligation to protect public safety.
generated at time: 2026-06-03T14:08:23.434917+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Safety Feature Omission
type: SafetyFeatureComplianceObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A submitted AI-generated design documents that omitted key safety features required by local regulations, creating potential public safety hazards and regulatory noncompliance.
compliance status: unmet
concept category: Obligation
confidence: 0.92
derived from principle: Engineer A Safety Feature Omission
obligation class: Safety Feature Compliance Obligation
obligation statement: Engineer A was obligated to verify that the AI-generated design documents included all safety features required by local regulations before submitting them to Client W.
temporal scope: Prior to submission of the design documents to Client W
text references: Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
text references: The errors in the AI-generated design documents could have led to regulatory noncompliance and safety hazards, conflicting with the Fundamental Canon I.1, 'hold paramount the safety, health, and welfare of the public'.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.84
match reasoning: Via class 'Safety Feature Compliance Obligation': This obligation is a variant of the already-extracted Regulatory Safety Compliance Obligation, with specific emphasis on verifying that safety features required by local regulations are not omitted from AI-generated design documents.
matched ontology class: RegulatoryComplianceObligation
matched ontology label: Regulatory Safety Compliance Obligation
matches existing: true
source text: Client W reviewed the design documents, they found misaligned dimensions and key safety features (including those necessary for compliance with local regulations) were omitted.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to verify that the AI-generated design documents included all safety features required by local regulations before submitting them to Client W.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Tool Adoption for Report
type: Action
type: NamedIndividual
initiates: Engineer A AI Report Draft
initiates: Engineer A AI Report Work Product
initiates: Engineer A Client Data Exposure
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Potential confidentiality exposure from uploading client data to open-source platform
foreseen unintended effects: Uncertainty about AI output accuracy and originality
fulfills obligation text: Perform Services Within Competence
guided by principle: Engineer A AI Report Competence
guided by principle: Engineer A Professional Competence AI Use
guided by principle text: Professional Competency
guided by principle text: Technological Innovation in Engineering Practice
has agent: Engineer A
has mental state: deliberate
initiates text: AI-Assisted Report Drafting State
initiates text: Client Confidential Data in Public Domain State
intended outcome: Compensate for reduced writing confidence and lack of mentorship by using AI to produce a workable first draft efficiently
raises obligation: Engineer A AI Report Disclosure
raises obligation: Engineer A Client Data AI Upload
raises obligation: Engineer A Report AI Disclosure
raises obligation text: Client Confidentiality
raises obligation text: Direction and Control Over Work Product
requires capability text: Environmental engineering domain expertise
requires capability text: Familiarity with AI tool capabilities and limitations
requires capability text: Judgment to evaluate AI-generated technical content
temporal extent: interval
temporal marker: During report preparation phase
temporal sequence: 4
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A decided to use new, open-source AI language processing software to generate an initial draft of the contaminant report rather than drafting it independently or seeking an alternative expert reviewer.
has time: During report preparation phase
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Professional Competence AI Use
type: ProfessionalCompetencePrinciple
type: NamedIndividual
invoked by: Engineer A
applied to: AI-assisted engineering design documents
balancing with: Loss of mentor oversight
balancing with: Time pressure
concept category: Principle
concrete expression: Engineer A used an AI drafting tool without prior experience or understanding of its accuracy limitations, producing design documents with technical errors that the engineer did not detect during review.
confidence: 0.88
interpretation: Professional competence requires engineers to understand the tools they use in professional practice. Deploying an unfamiliar AI tool on safety-critical design work without adequate understanding of its limitations falls below the competence standard.
invoked by: Engineer A AI-Assisted Design
principle class: Professional Competence
tension resolution: The principle was not satisfied: Engineer A's lack of familiarity with the AI tool contributed to a failure to detect errors in the design documents.
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
text references: The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:03:55.305980+00:00
first discovered in case: 7
match confidence: 0.95
match reasoning: Individual typed as existing ontology class 'Professional Competence'
matched ontology class: ProfessionalCompetencePrinciple
matched ontology label: Professional Competence
matches existing: true
source text: The AI drafting software was new to the market and Engineer A had no previous experience with the tool.
synthesis literal: appliedTo
synthesis literal: balancingWith
synthesis literal: concreteExpression
synthesis literal: confidence
synthesis literal: interpretation
synthesis literal: principleClass
synthesis literal: tensionResolution
synthesis literal: textReferences
comment: Engineer A used an AI drafting tool without prior experience or understanding of its accuracy limitations, producing design documents with technical errors that the engineer did not detect during review.
generated at time: 2026-06-03T14:03:55.305980+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI-Assisted Design
type: AI-AssistedDesignEngineer
type: NamedIndividual
adheres to principle: Engineer A AI Authorship Concealment
adheres to principle: Engineer A AI Design Substitution
adheres to principle: Engineer A AI Design Verification Failure
adheres to principle: Engineer A AI Tool Non-Disclosure Design
adheres to principle: Engineer A AI Tool Non-Disclosure Report
adheres to principle: Engineer A Design Documents Competence Failure
adheres to principle: Engineer A Professional Competence AI Use
adheres to principle: Engineer A Report AI Verification
adheres to principle: Engineer A Transparency to Client
has obligation: Engineer A AI Authorship Representation
has obligation: Engineer A AI Design Direction Control
has obligation: Engineer A AI Design Disclosure
has obligation: Engineer A Design Documents Verification
has obligation: Engineer A Report AI Direction Control
has obligation: Engineer A Report AI Verification
actor: Engineer A
case involvement: Used open-source AI software to generate an initial report draft and preliminary engineering design documents without prior experience with the tool, applied a professional seal to the output, and did not disclose AI use to the client. The AI-generated design documents contained misaligned dimensions and omitted key safety features required by local regulations.
concept category: Role
confidence: 0.88
has license: Professional Engineer
other attribute: ai_tool_experience: None prior to this engagement
other attribute: disclosure: No AI use disclosed
role category: provider_client
role class: AI-Assisted Design Engineer
text references: Client W noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations
text references: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review, including language to clearly identify that the supplied report was a draft, but applied their seal consistent with state law
text references: Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents
discovered in case: 7
discovered in pass: 1
discovered in section: facts
first discovered at: 2026-06-03T13:59:26.869728+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents
synthesis literal: caseInvolvement
synthesis literal: confidence
synthesis literal: roleCategory
synthesis literal: roleClass
synthesis literal: textReferences
comment: Used open-source AI software to generate an initial report draft and preliminary engineering design documents without prior experience with the tool, applied a professional seal to the output, and did not disclose AI use to the client. The AI-generated design documents contained misaligned dimensions and omitted key safety features required by local regulations.
generated at time: 2026-06-03T13:59:26.869728+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Report Work Product
type: AI-GeneratedWorkProductState
type: NamedIndividual
activated by event: AI Design Generation
activated by event: AI Report Generation
activates constraint: Engineer A AI Design Disclosure
activates constraint: Engineer A Design AI Output Verification
activates obligation: Engineer A AI Design Disclosure
activates obligation: Engineer A Report AI Verification
affects: Client W
affects: Engineer A
active period: From the report's submission to Client W through the case analysis period
affected parties: Client W
affected parties: Engineer A
concept category: State
confidence: 0.91
principle transformation: Transforms general honesty, competence, and professional accountability principles into specific duties of disclosure, verification, and independent review when AI tools contribute substantially to a professional work product.
state class: AI-Generated Work Product State
subject: Engineer A's groundwater monitoring report substantially drafted by AI language processing software
terminated by: Would require disclosure, attribution, and confirmation that the work product meets professional standards; partially addressed by Engineer A's cross-checking but attribution and consent issues remain
text references: AI, while not a human contributor, fundamentally shaped the report and design documents.
text references: Engineer A performed a thorough review, cross-checked key facts against professional sources, and made adjustments to the text.
text references: Engineer A used AI language processing software to draft a groundwater monitoring report.
triggering event: Engineer A using AI language processing software to draft the groundwater monitoring report and submitting it to Client W
urgency level: medium
discovered in case: 7
discovered in pass: 1
discovered in section: discussion
first discovered at: 2026-06-03T14:01:36.958645+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Engineer A used AI language processing software to draft a groundwater monitoring report.
synthesis literal: activePeriod
synthesis literal: confidence
synthesis literal: stateClass
synthesis literal: subject
synthesis literal: terminatedBy
synthesis literal: textReferences
synthesis literal: triggeringEvent
synthesis literal: urgencyLevel
comment: Engineer A's groundwater monitoring report substantially drafted by AI language processing software
generated at time: 2026-06-03T14:01:36.958645+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Report AI Disclosure
type: AIContributionDisclosureObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used open-source AI software to generate the initial draft of the contaminant report but did not disclose this to Client W when submitting the final report.
compliance status: unmet
concept category: Obligation
confidence: 0.89
derived from principle: Engineer A AI Disclosure Transparency
obligation class: AI Contribution Disclosure Obligation
obligation statement: Engineer A was obligated to proactively disclose to Client W that AI language processing software substantially contributed to the contaminant report.
temporal scope: At the time of delivering the contaminant report to Client W
text references: BER Case 98-3 emphasized that engineers must acknowledge significant contributions by others. AI, while not a human contributor, fundamentally shaped the report and design documents, warranting disclosure under Code section III.9.
text references: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
discovered in case: 7
discovered in pass: 2
discovered in section: discussion
first discovered at: 2026-06-03T14:09:34.826300+00:00
first discovered in case: 7
match confidence: 0.88
match reasoning: Via class 'AI Contribution Disclosure Obligation': This obligation is substantively the same concept as the already-extracted AI Tool Disclosure Obligation. The present class emphasizes the proactive and best-practice dimension but covers the same duty to disclose AI contribution to clients and stakeholders.
matched ontology class: AIToolDisclosureObligation
matched ontology label: AI Tool Disclosure Obligation
matches existing: true
source text: While Engineer A reviewed the content, the lack of disclosure raises concerns about transparency.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to proactively disclose to Client W that AI language processing software substantially contributed to the contaminant report.
generated at time: 2026-06-03T14:09:34.826300+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Design Defect Discovery
type: Event
type: NamedIndividual
initiates: Engineer A Design Deficiencies
initiates: Engineer A Design Deficient Submission
initiates: Engineer A Public Safety Design Omission
initiates: Engineer A Public Safety Design Risk
initiates: Engineer A Regulatory Non-Compliance Design
caused by action: Cursory Design Document Review
causes state change: The design documents were identified as non-compliant and technically deficient, creating a public safety risk and triggering a revision requirement.
concept category: Event
event type: outcome
initiates text: Client Confidence Impaired State
initiates text: Design Revision Required State
initiates text: Public Safety Risk
initiates text: Regulatory Non-Compliance State
severity: critical
temporal extent: instant
temporal marker: Upon Client W's review of submitted design documents
temporal sequence: 17
terminates text: Design Adequacy State
terminates text: Regulatory Compliance State
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: Client W's review of the submitted design documents revealed misaligned dimensions and omitted safety features required by local regulations, constituting a failure of the design deliverable to meet regulatory and professional standards.
has time: Upon Client W's review of submitted design documents
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Design Document Submission
type: Action
type: NamedIndividual
initiates: Engineer A Design Deficiencies
initiates: Engineer A Design Deficient Submission
initiates: Engineer A Public Safety Design Omission
initiates: Engineer A Public Safety Design Risk
initiates: Engineer A Regulatory Non-Compliance Design
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Risk that undetected errors could cause regulatory noncompliance or safety hazards if the documents were acted upon
guided by principle: Engineer A Public Safety Design Errors
guided by principle: Engineer A Responsible Charge Design Failure
guided by principle: Engineer A Safety Feature Omission
guided by principle: Engineer A Seal on AI Design Documents
guided by principle text: Professional Competency
guided by principle text: Public Safety
guided by principle text: Responsible Charge
has agent: Engineer A
has mental state: deliberate
initiates text: Deficient Design Documents Submitted State
initiates text: Public Safety Risk State
initiates text: Regulatory Noncompliance Risk State
intended outcome: Fulfill the contractual deliverable for engineering design documents and advance the project for Client W's review
requires capability text: Comprehensive design review and verification
requires capability text: Regulatory compliance assurance
requires capability text: Responsible charge over engineering plans and specifications
temporal extent: instant
temporal marker: At design document submission
temporal sequence: 16
terminates text: Dual Deliverable Obligation for Design Documents
violates obligation: Engineer A Design Responsible Charge
violates obligation: Engineer A Design Safety Compliance
violates obligation: Engineer A Design Seal
violates obligation text: Direction and Control Over Work Product
violates obligation text: Hold Paramount the Safety, Health, and Welfare of the Public
violates obligation text: Responsible Charge
violates obligation text: Undertake Assignments Only When Qualified
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A submitted the AI-generated engineering design documents to Client W without comprehensive review, without disclosure of AI use, and without verifying that all elements satisfied applicable professional and regulatory standards, including local safety feature requirements.
has time: At design document submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A Design Safety Compliance
type: RegulatorySafetyComplianceObligation
type: NamedIndividual
obligated party: Engineer A
prevails over: Engineer A AI Design Disclosure
case context: AI-generated design documents submitted by Engineer A omitted key safety features required by local regulations, which Client W identified upon review and required Engineer A to correct.
compliance status: unmet
concept category: Obligation
confidence: 0.91
derived from principle: Engineer A Public Safety Design Errors
obligation class: Regulatory Safety Compliance Obligation
obligation statement: Engineer A was obligated to ensure that the engineering design documents submitted to Client W included all safety features required by local regulations before submission, regardless of whether those documents were generated by AI tools.
temporal scope: Prior to submission of engineering design documents to Client W
text references: Client W raised concerns about the accuracy and reliability of the engineering design and instructed Engineer A to revise the plans, ensuring that all elements satisfied the necessary professional and regulatory standards.
text references: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.8
match reasoning: Via class 'Regulatory Safety Compliance Obligation': This obligation is a specialization of the existing Safety Obligation, focused specifically on regulatory compliance in design documents. The existing Safety Obligation covers the general duty to hold paramount public safety, and the external reference standard 'Comply with Applicable Safety Standards' is closely related. A distinct class is warranted because this obligation specifically addresses regulatory compliance verification in submitted design documents rather than the broader public welfare principle.
matched ontology class: SafetyObligation
matched ontology label: Safety Obligation
matches existing: true
source text: Client W, however, noticed several issues with the AI-generated design documents, including misaligned dimensions and an omission of key safety features required by local regulations.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to ensure that the engineering design documents submitted to Client W included all safety features required by local regulations before submission, regardless of whether those documents were generated by AI tools.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Engineer A AI Design Disclosure
type: AIToolDisclosureObligation
type: NamedIndividual
obligated party: Engineer A
case context: Engineer A used AI-assisted drafting tools to generate preliminary design documents for groundwater infrastructure modifications and submitted those documents to Client W without disclosing the AI tool involvement.
compliance status: unmet
concept category: Obligation
confidence: 0.93
derived from principle: Engineer A AI Tool Non-Disclosure Design
obligation class: AI Tool Disclosure Obligation
obligation statement: Engineer A was obligated to disclose to Client W that AI-assisted drafting tools were used to generate the preliminary engineering design documents before or at the time of submission.
temporal scope: At the time of submitting the engineering design documents to Client W
text references: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
discovered in case: 7
discovered in pass: 2
discovered in section: facts
first discovered at: 2026-06-03T14:05:12.288818+00:00
first discovered in case: 7
match confidence: 0.0
matches existing: false
source text: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.
synthesis literal: caseContext
synthesis literal: complianceStatus
synthesis literal: confidence
synthesis literal: obligationClass
synthesis literal: obligationStatement
synthesis literal: temporalScope
synthesis literal: textReferences
comment: Engineer A was obligated to disclose to Client W that AI-assisted drafting tools were used to generate the preliminary engineering design documents before or at the time of submission.
generated at time: 2026-06-03T14:05:12.288818+00:00
was attributed to: Case 7 Extraction
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Report Generation
type: Event
type: NamedIndividual
initiates: Engineer A AI Report Draft
initiates: Engineer A AI Report Work Product
caused by action: AI Tool Adoption for Report
causes state change: A machine-generated draft report existed and was available for Engineer A's review.
concept category: Event
event type: automatic_trigger
initiates text: AI-Drafted Report Exists
initiates text: Unverified Content State
severity: low
temporal extent: instant
temporal marker: During drafting phase, before thorough review
temporal sequence: 7
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: The open-source AI software produced a draft of the comprehensive contaminant report based on the data and inputs provided by Engineer A.
has time: During drafting phase, before thorough review
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Cursory Design Document Review
type: Action
type: NamedIndividual
initiates: Engineer A Design Inadequate AI Review
initiates: Engineer A Public Safety Design Omission
initiates: Engineer A Public Safety Design Risk
initiates: Engineer A Regulatory Non-Compliance Design
initiates: Engineer A Responsible Charge Deficit
concept category: Action
event role context: Licensed Environmental Engineer
foreseen unintended effects: Undetected errors in dimensions and omission of safety features required by local regulations
guided by principle: Engineer A Professional Competence AI Use
guided by principle: Engineer A Public Safety Design Errors
guided by principle: Engineer A Responsible Charge Design Failure
guided by principle: Engineer A Seal on AI Design Documents
guided by principle text: Professional Competency
guided by principle text: Public Safety
guided by principle text: Responsible Charge
has agent: Engineer A
has mental state: deliberate
initiates text: Insufficient Oversight of Design Documents State
initiates text: Public Safety Risk State
initiates text: Regulatory Noncompliance Risk State
intended outcome: Adapt the AI-generated plans to the site context and prepare them for submission without expending the full review effort applied to the report
requires capability text: Comprehensive engineering design review
requires capability text: Dimensional accuracy checking
requires capability text: Regulatory compliance verification
requires capability text: Safety feature validation for groundwater infrastructure
temporal extent: interval
temporal marker: After receiving AI-generated design documents, before submission
temporal sequence: 14
violates obligation: Engineer A Design Responsible Charge
violates obligation: Engineer A Design Safety Compliance
violates obligation: Engineer A Report AI Direction Control
violates obligation: Engineer A Safety Feature Omission
violates obligation text: Direction and Control Over Work Product
violates obligation text: Hold Paramount the Safety, Health, and Welfare of the Public
violates obligation text: Responsible Charge
violates obligation text: Undertake Assignments Only When Qualified
within competence: true
synthesis literal: description
synthesis literal: eventRoleContext
synthesis literal: foreseenUnintendedEffects
synthesis literal: hasAgent
synthesis literal: hasMentalState
synthesis literal: intendedOutcome
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
synthesis literal: withinCompetence
comment: Engineer A performed only a cursory review of the AI-generated engineering design documents, adjusting certain elements to align with site-specific conditions but not conducting a comprehensive verification of dimensions, safety features, or regulatory compliance.
has time: After receiving AI-generated design documents, before submission
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

AI Design Generation
type: Event
type: NamedIndividual
initiates: Engineer A AI Design Documents
caused by action: AI Tool Adoption for Design
causes state change: A machine-generated draft of the design documents existed and was available for Engineer A's review, containing unverified technical specifications.
concept category: Event
event type: automatic_trigger
initiates text: AI-Drafted Design Exists
initiates text: Unverified Design Content State
severity: high
temporal extent: instant
temporal marker: During drafting phase, before cursory review
temporal sequence: 13
synthesis literal: causesStateChange
synthesis literal: description
synthesis literal: eventType
synthesis literal: severity
synthesis literal: temporalExtent
synthesis literal: temporalMarker
synthesis literal: temporalSequence
comment: The open-source AI software produced draft groundwater infrastructure design documents, including dimensions and safety feature specifications, based on inputs provided by Engineer A.
has time: During drafting phase, before cursory review
was attributed to: claude-sonnet-4-6
was generated by: ProEthica Case 7 Extraction

Client W
type: Agent
type: NamedIndividual
has role: Client W Project Client

Engineer A
type: Agent
type: NamedIndividual
has client: Client W
has role: Engineer A AI-Assisted Design
has role: Engineer A Environmental Engineer
has role: Engineer A Responsible Charge
professional peer of: Engineer B
work reviewed by: Engineer B