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Use of Artificial Intelligence in Engineering Practice
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248

Entities

9

Provisions

2

Precedents

19

Questions

24

Conclusions

Stalemate

Transformation
Stalemate Competing obligations remain in tension without clear resolution
Engineer A is caught within a single, unchanging set of rules where several codified duties pull in different directions at once: the duty to serve the client efficiently conflicts with the non-negotiable confidentiality duty (C11, C23); the duty to exercise professional judgment conflicts with the duty to calibrate review to public-safety risk (C12, C22); and the emerging expectation of transparency conflicts with the fact that 'no universal guideline mandating AI disclosure' currently exists (C3, C24). Rather than resolving which obligation prevails, the Board's conclusions largely restate that both obligations remain valid and unresolved, consistent with the stalemate pattern of stakeholders unable to exit the rule-set.
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Synthesis Reasoning Flow
Shows how NSPE provisions inform questions and conclusions - the board's reasoning chain

The board's deliberative chain: which code provisions informed which ethical questions, and how those questions were resolved. Toggle "Show Entities" to see which entities each provision applies to.

Nodes:
■ Provision (e.g., I.1.) ◆ Question: Board = board-explicit, Impl = implicit, Tens = principle tension, Theo = theoretical, CF = counterfactual ▬ Conclusion: Board = board-explicit, Resp = question response, Ext = analytical extension, Synth = principle synthesis ▬ Entity (hidden by default)
Edges:
→ informs → answered by → applies to
Provisions (9)
View Extraction

All provisions in play for this case: the union of board-stated references and analysis-found citations (see each provision's provenance badge). The OntServe case page's Cited NSPE Provisions panel shows the subset actually cited by the committed conclusions, so its count can be lower.

I.1 board + analysis Hold paramount the safety, health, and welfare of the public.
How this applies in the case (showing 3 of 24)
Obligation
Engineer A Public Safety Paramount Duty
This provision directly requires holding public safety paramount as stated in the obligation
Action
Cursory Design Review
Failing to thoroughly review AI generated designs risks public safety
State
AI Design Error Safety Hazard
Public safety is directly threatened by AI design errors
Obligation (3)
  • Engineer A Public Safety Paramount Duty
    This provision directly requires holding public safety paramount as stated in the obligation
  • Engineer A Design Review Duty
    Verifying AI-generated design accuracy protects public safety and welfare
  • Engineer A Responsible Charge QA Duty
    Quality assurance review by the responsible engineer safeguards public safety
Action (3)
  • Cursory Design Review
    Failing to thoroughly review AI generated designs risks public safety
  • Thorough Report Review
    Careful review upholds public safety and welfare
  • Report Sealing and Submission
    Sealing unverified AI work endangers public safety
State (4)
  • AI Design Error Safety Hazard
    Public safety is directly threatened by AI design errors
  • Omitted Safety Features Violation
    Missing safety features endanger public welfare
  • Deficient AI Design Documents
    Deficient documents delivered to client can compromise public safety
  • Cursory Review of AI Plans
    Inadequate review risks public safety from undetected errors
Constraint (3)
  • Engineer A Safety Feature Omission Bar
    Holding safety paramount requires not omitting required safety features from engineering documents.
  • Engineer A Tool Substitution Limit
    Public safety depends on the engineer not letting AI tools replace professional judgment.
  • Engineer A Judgment Substitution Boundary
    Safety welfare mandates independent verification rather than blind reliance on AI output.
Principle (3)
  • Public Welfare in Design Documents
    Missing safety features directly threaten public welfare.
  • Public Welfare in AI Design Errors
    Errors from AI-generated designs could endanger public safety and cause regulatory noncompliance.
  • Responsible Charge over AI-Assisted Design
    Lack of responsible charge risks public safety if errors go undetected.
Role (3)
  • Engineer A Responsible Charge Engineer
    Must hold public safety paramount when relying on AI tools without adequate verification
  • Engineer A Public Responsibility
    Errors in AI-generated documents could compromise public safety and welfare
  • Engineer A Design Engineer
    Design documents affecting groundwater infrastructure must prioritize public safety
Event (2)
  • Design Error Discovery
    Undetected design errors threaten public safety and welfare
  • Report Inconsistency Observation
    Unresolved inconsistencies could compromise safety if not addressed
Resource (1)
  • NSPE Position Statement No. 10-1778
    This position statement addresses public safety concerns related to AI use in engineering practice
Capability (2)
  • Engineer A AI Report Verification
    Verifying AI generated content protects public safety and welfare
  • Engineer A Groundwater Data Analysis
    Accurate groundwater analysis is essential to protect public health and safety
I.2 board + analysis Perform services only in areas of their competence.
How this applies in the case (showing 3 of 19)
Obligation
Engineer A Competence Duty
This provision requires performing services only within areas of competence matching the obligation
Action
AI Tool Adoption
Engineers must ensure competence when adopting new AI tools
State
AI Tool Unfamiliarity
Using an unfamiliar tool falls outside area of competence
Obligation (2)
  • Engineer A Competence Duty
    This provision requires performing services only within areas of competence matching the obligation
  • Engineer A Responsible Charge QA Duty
    Competence underlies the ability to provide a valid quality assurance review
Action (2)
  • AI Tool Adoption
    Engineers must ensure competence when adopting new AI tools
  • Cursory Design Review
    Insufficient review may reflect lack of competence in verifying AI output
State (2)
  • AI Tool Unfamiliarity
    Using an unfamiliar tool falls outside area of competence
  • Untested AI Tool Reliance
    Relying on an untested tool exceeds demonstrated competence
Constraint (3)
  • Engineer A Tool Substitution Limit
    Competence must remain with the engineer, not be substituted by AI software.
  • Engineer A Judgment Substitution Boundary
    Performing only within competence requires independent engineering judgment over AI-generated results.
  • Engineer A Signature Direction Control Boundary
    Competence areas define what an engineer may sign or seal.
Principle (2)
  • Competence in AI-Assisted Environmental Work
    Provision requires performing only within one's area of competence, matching this principle.
  • Responsible Charge over AI-Assisted Design
    Failure to maintain responsible charge suggests inadequate competence oversight of AI work.
Role (2)
  • Engineer A Environmental Engineer
    Must ensure competence in areas where AI-generated content is used for contaminant analysis
  • Engineer A Design Engineer
    Must perform design services only within areas of demonstrated competence
Event (2)
  • AI Design Generation
    Using AI outside ones competence to generate designs violates area of competence rule
  • AI Report Generation
    Relying on AI generated reports without proper competence review is a concern
Resource (2)
  • BER Case 90-6
    This prior case addresses competence requirements relevant to using new tools or techniques
  • NSPE Position Statement No. 10-1778
    This position statement discusses competence requirements when engineers use AI tools
Capability (2)
  • Engineer A Self-Assessment
    Engineer must judge whether the work falls within their competence
  • Engineer A Groundwater Data Analysis
    Competence is required to properly analyze groundwater data
I.5 board + analysis Avoid deceptive acts.
How this applies in the case (showing 3 of 16)
Obligation
Engineer A AI Citation Duty
Failing to disclose AI use could be a deceptive act toward the client
Action
Design AI Disclosure Omission
Omitting AI use disclosure is a deceptive act
State
Uncited AI Tool Use
Failing to disclose AI use is a deceptive omission
Obligation (2)
  • Engineer A AI Citation Duty
    Failing to disclose AI use could be a deceptive act toward the client
  • Engineer A Draft Disclosure Duty
    Not disclosing draft status could deceive the client about the report's completeness
Action (1)
  • Design AI Disclosure Omission
    Omitting AI use disclosure is a deceptive act
State (3)
  • Uncited AI Tool Use
    Failing to disclose AI use is a deceptive omission
  • Technical Authority Citation Omission
    Omitting source citation misrepresents authorship
  • Absent AI Disclosure Guidelines
    Lack of disclosure practice enables deceptive presentation of work
Constraint (2)
  • Engineer A Safety Feature Omission Bar
    Omitting required safety features would be a deceptive act toward the public.
  • Engineer A Judgment Substitution Boundary
    Blind acceptance of AI output without verification risks deceptive representations.
Principle (3)
  • Honesty in AI-Assisted Report Writing
    Provision against deceptive acts aligns with assessing honesty in AI-assisted writing.
  • Transparency of AI Contribution
    Failure to disclose AI contribution relates to avoiding deceptive acts.
  • Transparency About Draft and AI Use
    Disclosing draft status supports avoiding deception.
Role (1)
  • Engineer A Responsible Charge Engineer
    Presenting AI-generated work without proper disclosure could be deceptive
Event (2)
  • AI Design Generation
    Presenting AI generated designs as ones own work without disclosure is deceptive
  • AI Report Generation
    Passing off AI generated reports without disclosure misleads others
Capability (2)
  • Engineer A Draft Status Disclosure
    Disclosing draft status avoids deceiving others about the report status
  • Engineer A Accurate Representation
    Accurate representation directly relates to avoiding deceptive acts
II.1.c board + analysis 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.
How this applies in the case (showing 3 of 8)
Obligation
Engineer A Client Consent Confidentiality Duty
This provision requires prior client consent before revealing confidential information matching the obligation
Action
Confidential Data Input
Inputting confidential client data into AI tools without consent breaches confidentiality
State
Client W Data Public Domain Exposure
Uploading private client data without consent violates confidentiality
Obligation (1)
  • Engineer A Client Consent Confidentiality Duty
    This provision requires prior client consent before revealing confidential information matching the obligation
Action (1)
  • Confidential Data Input
    Inputting confidential client data into AI tools without consent breaches confidentiality
State (1)
  • Client W Data Public Domain Exposure
    Uploading private client data without consent violates confidentiality
Constraint (1)
  • Engineer A Client Data Confidentiality
    This provision directly prohibits revealing client information without consent, matching the confidentiality constraint.
Principle (1)
  • Confidentiality of Client W Information
    Provision restricts revealing client information without consent, matching confidentiality concerns of uploading data to AI.
Role (1)
  • Engineer A Environmental Engineer
    Using open-sourced AI software may risk revealing client data without consent
Event (1)
  • Confidential Information Exposure
    Inputting confidential client data into AI tools reveals information without consent
Capability (1)
  • Engineer A Groundwater Data Analysis
    Client data used in analysis must not be disclosed without consent
II.2.a board + analysis Engineers shall undertake assignments only when qualified by education or experience in the specific technical fields involved.
How this applies in the case (showing 3 of 17)
Obligation
Engineer A Competence Duty
This provision requires undertaking assignments only within qualified technical fields as stated in the obligation
Action
AI Tool Adoption
Engineers must be qualified in the technical fields when using AI tools
State
AI Tool Unfamiliarity
Undertaking work with an unfamiliar tool violates qualification requirement
Obligation (1)
  • Engineer A Competence Duty
    This provision requires undertaking assignments only within qualified technical fields as stated in the obligation
Action (2)
  • AI Tool Adoption
    Engineers must be qualified in the technical fields when using AI tools
  • Cursory Design Review
    Inadequate review may indicate lack of qualification to verify AI generated work
State (3)
  • AI Tool Unfamiliarity
    Undertaking work with an unfamiliar tool violates qualification requirement
  • Untested AI Tool Reliance
    Relying on an unproven tool exceeds qualified expertise
  • Engineer A Writing Shortfall
    Writing shortfall suggests lack of qualification in technical communication
Constraint (2)
  • Engineer A Tool Substitution Limit
    Assignments must be undertaken based on the engineer's own qualification, not AI substitution.
  • Engineer A Judgment Substitution Boundary
    Qualification by experience requires independent judgment rather than reliance on AI.
Principle (2)
  • Competence in AI-Assisted Environmental Work
    Requires undertaking assignments only when qualified, matching competence assessment.
  • Responsible Charge over AI-Assisted Design
    Undertaking design assignments without proper involvement violates qualification requirements.
Role (2)
  • Engineer A Environmental Engineer
    Undertaking contaminant analysis requires qualification by education or experience
  • Engineer A Design Engineer
    Undertaking design assignments requires specific technical qualification
Event (2)
  • AI Design Generation
    Engineer must be qualified in the specific technical field before using AI to generate designs
  • Design Error Discovery
    Errors reveal lack of qualification in the technical area used with AI
Resource (1)
  • BER Case 90-6
    This prior case establishes precedent on qualification requirements for specific technical assignments
Capability (2)
  • Engineer A Self-Assessment
    Engineer must assess if qualified by education or experience for the assignment
  • Engineer A Groundwater Data Analysis
    Undertaking this analysis requires proper qualification
II.2.b board + analysis 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.
How this applies in the case (showing 3 of 20)
Obligation
Engineer A Design Review Duty
Engineers must not sign documents not prepared under their direction requiring thorough review of AI-generated designs
Action
Report Sealing and Submission
Sealing documents not adequately reviewed or under direction violates this provision
State
Responsible Charge Lapse
Documents were not adequately prepared under the engineer's direction and control
Obligation (2)
  • Engineer A Design Review Duty
    Engineers must not sign documents not prepared under their direction requiring thorough review of AI-generated designs
  • Engineer A Responsible Charge QA Duty
    The responsible engineer must ensure documents are properly reviewed before signing consistent with this provision
Action (2)
  • Report Sealing and Submission
    Sealing documents not adequately reviewed or under direction violates this provision
  • Cursory Design Review
    Signing off without proper review of AI generated content violates this provision
State (5)
  • Responsible Charge Lapse
    Documents were not adequately prepared under the engineer's direction and control
  • Cursory Review of AI Plans
    Insufficient review means signing documents without full competence verification
  • Sealed Draft Report
    Sealing a draft not fully vetted violates control requirement
  • Deficient AI Design Documents
    Signing deficient documents not properly directed violates this provision
  • Engineer B Review Unavailable
    Lack of independent review undermines proper direction and control
Constraint (2)
  • Engineer A Signature Direction Control Boundary
    This provision directly defines the prohibition on signing documents outside competence or control.
  • Engineer A Seal State Law Limit
    Sealing documents relates to competence and direction and control requirements.
Principle (2)
  • Responsible Charge in Sealing
    Provision prohibits sealing documents not prepared under one's direction and control, directly matching sealing responsibility.
  • Responsible Charge over AI-Assisted Design
    Failure to be involved in design preparation violates this signing/control requirement.
Role (1)
  • Engineer A Responsible Charge Engineer
    Signing documents not fully prepared or verified under direct control violates this provision
Event (2)
  • AI Design Generation
    Signing AI generated plans not prepared under direct control violates this provision
  • Mentor Retirement
    Loss of mentor oversight raises risk of signing work not under proper direction and control
Resource (2)
  • BER Case 98-3
    This prior case addresses signing documents not prepared under the engineers direct control
  • NSPE Position Statement No. 10-1778
    This position statement addresses signing and sealing documents generated with AI assistance
Capability (2)
  • Engineer A Report Direction Control
    Signing requires the report be prepared under the engineers direction and control
  • Engineer A AI Report Verification
    Verification ensures the engineer has competence over AI generated content before signing
III.3 board + analysis Engineers shall avoid all conduct or practice that deceives the public.
How this applies in the case (showing 3 of 18)
Obligation
Engineer A AI Citation Duty
Omitting AI use disclosure could deceive the public about authorship of the work
Action
Design AI Disclosure Omission
Omitting disclosure of AI use deceives the public about work origin
State
Uncited AI Tool Use
Not disclosing AI use can deceive the public about authorship
Obligation (2)
  • Engineer A AI Citation Duty
    Omitting AI use disclosure could deceive the public about authorship of the work
  • Engineer A Draft Disclosure Duty
    Failing to identify a draft could deceive the client and public about the document's status
Action (2)
  • Design AI Disclosure Omission
    Omitting disclosure of AI use deceives the public about work origin
  • Report Sealing and Submission
    Submitting reports without disclosing AI involvement deceives the public
State (3)
  • Uncited AI Tool Use
    Not disclosing AI use can deceive the public about authorship
  • Technical Authority Citation Omission
    Omitting citation deceives public about the true source of work
  • Absent AI Disclosure Guidelines
    Lack of disclosure norms can lead to deceptive practice toward the public
Constraint (2)
  • Engineer A Safety Feature Omission Bar
    Omitting safety features would deceive the public about the design's adequacy.
  • Engineer A Judgment Substitution Boundary
    Failing to verify AI-generated content could mislead the public about engineering accuracy.
Principle (3)
  • Honesty in AI-Assisted Report Writing
    Provision against deceiving the public relates to honesty in AI-assisted content.
  • Transparency of AI Contribution
    Undisclosed AI use could deceive the public about authorship and process.
  • Public Welfare in AI Design Errors
    Undetected errors in AI-generated documents could mislead the public regarding safety compliance.
Role (2)
  • Engineer A Public Responsibility
    Deceptive or unverified AI-generated content could mislead the public
  • Engineer A Responsible Charge Engineer
    Failure to verify AI outputs risks deceiving reliant parties
Event (2)
  • AI Report Generation
    Presenting AI generated reports as independently verified deceives the public
  • AI Design Generation
    Presenting AI generated designs without proper review deceives the public
Capability (2)
  • Engineer A Draft Status Disclosure
    Failing to disclose draft status could deceive the public
  • Engineer A Accurate Representation
    Accurate representation prevents deceiving the public
III.8.a board + analysis Engineers shall conform with state registration laws in the practice of engineering.
How this applies in the case (showing 3 of 10)
Obligation
Engineer A Responsible Charge QA Duty
Acting as engineer in responsible charge relates to conforming with state registration law requirements
Action
Report Sealing and Submission
Sealing documents must conform to state registration laws requiring proper professional oversight
State
Responsible Charge Lapse
Failure to maintain responsible charge violates state registration practice standards
Obligation (1)
  • Engineer A Responsible Charge QA Duty
    Acting as engineer in responsible charge relates to conforming with state registration law requirements
Action (1)
  • Report Sealing and Submission
    Sealing documents must conform to state registration laws requiring proper professional oversight
State (1)
  • Responsible Charge Lapse
    Failure to maintain responsible charge violates state registration practice standards
Constraint (1)
  • Engineer A Seal State Law Limit
    Conforming to registration laws directly governs when a seal may be applied per state law.
Principle (2)
  • Responsible Charge in Sealing
    Sealing in conformity with state law reflects compliance with registration laws.
  • Responsible Charge over AI-Assisted Design
    Maintaining responsible charge is required under state registration laws for practice.
Role (1)
  • Engineer A Responsible Charge Engineer
    Must conform with state registration laws when serving as engineer of record
Event (1)
  • AI Design Generation
    Using AI to perform engineering design must still conform to state registration and licensure laws
Resource (1)
  • NSPE Position Statement No. 10-1778
    This position statement discusses compliance with state licensure laws when using AI tools
Capability (1)
  • Engineer A Report Direction Control
    Maintaining direction and control aligns with state registration law requirements
III.9 board + analysis Engineers shall give credit for engineering work to those to whom credit is due, and will recognize the proprietary interests of others.
How this applies in the case (showing 3 of 11)
Obligation
Engineer A Citation Credit Duty
This provision directly requires giving credit for engineering work as stated in the obligation
Action
Design AI Disclosure Omission
Failing to credit AI tool contribution violates recognition of proprietary interests
State
Uncited AI Tool Use
Failing to credit the AI tool violates proprietary recognition duty
Obligation (1)
  • Engineer A Citation Credit Duty
    This provision directly requires giving credit for engineering work as stated in the obligation
Action (1)
  • Design AI Disclosure Omission
    Failing to credit AI tool contribution violates recognition of proprietary interests
State (3)
  • Uncited AI Tool Use
    Failing to credit the AI tool violates proprietary recognition duty
  • Technical Authority Citation Omission
    Omitting citation fails to give credit to the AI source
  • Absent AI Disclosure Guidelines
    Lack of guidelines contributes to failure to credit AI-generated content
Constraint (1)
  • Engineer A Signature Direction Control Boundary
    Giving proper credit relates to only signing work prepared under one's own direction and control.
Principle (2)
  • Credit Attribution in AI Report
    Provision requires giving credit for work, matching the need for citations of AI-generated content sources.
  • Intellectual Honesty in AI Text
    Verifying originality relates to recognizing proprietary interests of others.
Event (2)
  • AI Report Generation
    Failing to credit AI tool or acknowledge its contribution misrepresents authorship
  • AI Design Generation
    Claiming sole credit for AI generated designs ignores proprietary interests
Capability (1)
  • Engineer A Accurate Representation
    Giving proper credit relates to accurately representing the source of work
Cross-Case Connections
View Extraction
Explicit Board-Cited Precedents 2 Lineage Graph

Cases explicitly cited by the Board in this opinion. These represent direct expert judgment about intertextual relevance.

Principle Established:

It is ethical for an engineer to sign and seal documents prepared using computer-assisted drafting and design (CADD) systems, whether prepared by the engineer or others under their direction and control, so long as the technology is not used as a substitute for engineering judgment.

Citation Context:

The Board cited this case as a historical parallel establishing that new drafting/design technology (CADD) can ethically be used and sealed by an engineer, provided the engineer maintains competency and does not use it as a substitute for judgment, foreshadowing the analysis of AI use.

Relevant Excerpts
discussion: "Almost 35 years ago, in BER Case 90-6, the BER looked at a hypothetical involving an engineer's use of computer assisted drafting and design tools."
discussion: "In BER Case 90-6, the BER determined that it was ethical for an engineer to sign and seal documents that were created using a CADD system whether prepared by the engineer themselves or by other engineers working under their direction and control."

Principle Established:

Technology such as CD-ROM design tools may have an important place in engineering practice, but it must never replace or substitute for engineering judgment; engineers must not offer services in areas where they lack competence merely because a technological tool enables them to do so.

Citation Context:

The Board cited this case to address the omission of key safety features and lack of competency oversight in AI-generated design documents, using it to show that technology must never replace engineering judgment, while distinguishing Engineer A's overall competence from the incompetent engineer in that case.

Relevant Excerpts
discussion: "BER Case 98-3 discussed a solicitation by mail for engineers to use new technology to help gain more work."
discussion: "In its discussion in BER Case 98-3, the BER reviewed several cases involving engineering competency, and concluded it would be unethical for an engineer to offer facilities design and construction services using a tool like this CD-ROM based on the facts presented in the case."
discussion: "To begin, it is the BER's view that under the facts, unlike the situation of BER Case 98-3, Engineer A is not incompetent."
discussion: "The BER notes that in BER Case 98-3, the BER stated that technology must not replace or be used as a substitute for engineering judgement."
discussion: "BER Case 98-3 emphasized that engineers must acknowledge significant contributions by others."
Implicit Similar Cases 10 Similarity Network

Cases sharing ontology classes or structural similarity. These connections arise from constrained extraction against a shared vocabulary.

Component Similarity 48% Facts Similarity 38% Discussion Similarity 43% Provision Overlap 10% Outcome Alignment 100% Tag Overlap 25% Principle Overlap 45%
Shared provisions: I.1 Same outcome mixed View Synthesis
Component Similarity 57% Facts Similarity 44% Discussion Similarity 42% Provision Overlap 7% Outcome Alignment 50% Tag Overlap 33% Principle Overlap 65%
Shared provisions: I.1 View Synthesis
Component Similarity 56% Facts Similarity 35% Discussion Similarity 40% Provision Overlap 13% Outcome Alignment 50% Tag Overlap 27% Principle Overlap 60%
Shared provisions: I.1, I.2 View Synthesis
Component Similarity 49% Facts Similarity 40% Discussion Similarity 44% Provision Overlap 7% Outcome Alignment 100% Tag Overlap 8% Principle Overlap 40%
Shared provisions: II.1.c Same outcome mixed View Synthesis
Component Similarity 53% Facts Similarity 50% Discussion Similarity 43% Outcome Alignment 100% Principle Overlap 49%
Same outcome mixed View Synthesis
Component Similarity 54% Facts Similarity 49% Discussion Similarity 45% Provision Overlap 15% Outcome Alignment 50% Tag Overlap 33% Principle Overlap 45%
Shared provisions: III.8.a, III.9 View Synthesis
Component Similarity 47% Facts Similarity 36% Discussion Similarity 49% Provision Overlap 22% Outcome Alignment 50% Tag Overlap 33% Principle Overlap 49%
Shared provisions: II.2.a, II.2.b View Synthesis
Component Similarity 49% Facts Similarity 46% Discussion Similarity 42% Provision Overlap 18% Outcome Alignment 50% Tag Overlap 40% Principle Overlap 40%
Shared provisions: II.2.a, II.2.b View Synthesis
Component Similarity 54% Facts Similarity 43% Discussion Similarity 46% Provision Overlap 17% Outcome Alignment 50% Tag Overlap 8% Principle Overlap 55%
Shared provisions: I.1, I.5 View Synthesis
Component Similarity 44% Facts Similarity 24% Discussion Similarity 44% Outcome Alignment 100% Tag Overlap 18% Principle Overlap 50%
Same outcome mixed View Synthesis
Questions & Conclusions (3 board)
View Extraction
Board Board question 1

Was Engineer A’s use of AI to create the report text ethical, given that Engineer A thoroughly checked the report?

Board conclusion Engineer A's use of AI in report writing was partly ethical, and partly unethical. Engineer A was competent and did thoroughly review and verify the AI-generated content, ensuring accuracy and compliance with professional standards. However, Engineer A did not obtain client permission to disclose private information, nor did Engineer A document required technical citations. Ethical use of AI to create the report text must satisfy all pertinent requirements.
Resolved by: The board credited Engineer A's competence and verification efforts as satisfying accuracy obligations while separately weighing the unmet confidentiality-consent and citation duties as independent failures, yielding a split rather than unitary judgment. (confidence 0.82)
I.2. II.1.c. III.9. 3 principles 3 facts Conditions Narrative
Implicit (1)

Did Engineer A's act of inputting Client W's confidential groundwater and site data into an open-source AI platform constitute an unauthorized disclosure of client information, regardless of whether the AI-generated text was later verified?

AnalyticalThe Board's finding that Engineer A failed to obtain client permission to disclose private information can be extended: the confidentiality violation crystallized at the moment Client W's groundwater and site data were entered into the open-source AI platform, independent of whether the resulting text was later verified or accurate. Thorough post-hoc review of AI output cannot retroactively cure an unauthorized disclosure that occurs upstream in the data-input stage, particularly where the platform's data retention and reuse practices are unknown to the engineer. This suggests the ethical breach under II.1.c is best understood as a discrete act of disclosure, not a data-quality issue remediable by verification.
Resolved by: The board treated confidentiality as an act-based duty triggered at the moment of unauthorized data input, outweighing any consequentialist offset from subsequent verification or accuracy of the resulting text. (confidence 0.85)
II.1.c. 3 principles 3 facts Conditions Narrative
AnalyticalQ101: The unauthorized disclosure occurred at the moment Engineer A entered Client W's confidential groundwater and site data into the open-source AI platform, independent of whether the AI-generated text was later verified for accuracy. Confidentiality under II.1.c is a duty tied to the act of disclosure itself; subsequent verification of the resulting text addresses accuracy and originality concerns but does nothing to cure the prior unauthorized transmission of client data to a third-party system of unknown retention and use practices.
Resolved by: The board treats confidentiality as breached at the moment of unauthorized transmission, so subsequent verification of the AI-generated text's accuracy cannot offset or cure the prior disclosure. (confidence 0.85)
II.1.c. 1 principle 3 facts Conditions Narrative
Principle tension (1)

How should the Confidentiality of Client W Information be balanced against the practical efficiency gains of using open-source AI tools that require inputting client data into third-party systems of unknown data retention practices?

AnalyticalQ201: The tension between confidentiality and efficiency should be resolved in favor of confidentiality as a threshold constraint, not a factor to be balanced against convenience. Where an AI tool's data-handling practices are unknown, engineers should either obtain informed client consent before inputting proprietary data, or use de-identified/anonymized data sufficient to preserve analytical utility without exposing protected information.
Resolved by: Confidentiality is treated as a threshold gate that must be satisfied before efficiency considerations are even weighed, not as one factor traded off against convenience. (confidence 0.85)
II.1.c. 2 principles 3 facts Conditions Narrative
AnalyticalConfidentiality of Client W Information and the practical efficiency of using an open-source AI tool were never actually balanced, because Engineer A never paused to weigh them: client data was input into a third-party platform of unknown retention and training practices without first obtaining consent or assessing the tool's data-handling policies. This suggests that in AI-assisted practice, confidentiality obligations under II.1.c. function as a threshold gate that must be cleared before efficiency considerations are even relevant, not as a factor to be traded off against them. Because Engineer A's technical competence and thorough fact-checking could not cure the upstream disclosure, the case demonstrates that procedural competence in verifying AI output is a separate ethical dimension from the prior, non-negotiable duty to protect client information before it is ever shared with an AI system.
Resolved by: The board treated confidentiality as a threshold duty that must be satisfied before efficiency considerations become relevant, rather than as a factor to be balanced against efficiency gains. (confidence 0.80)
II.1.c. 3 principles 3 facts Conditions Narrative
Theoretical (2)

From a deontological perspective, did Engineer A fulfill the duty of confidentiality under II.1.c by inputting Client W's proprietary information into an open-source AI tool without first obtaining consent?

AnalyticalQ301: From a strict deontological reading of II.1.c, Engineer A did not fulfill the confidentiality duty. The duty not to reveal client facts or data without prior consent is unconditional and act-based; it is breached the moment the data is transmitted to an outside system without consent, regardless of the AI tool's actual security or the client's subsequent satisfaction with the resulting work product.
Resolved by: Under a strict deontological reading, the duty of confidentiality is treated as absolute and is breached at the moment of unauthorized transmission, with no balancing against downstream tool security or client outcomes permitted. (confidence 0.85)
II.1.c. 1 principle 3 facts Conditions Narrative

From a consequentialist perspective, does the fact that Client W ultimately found the draft report satisfactory justify Engineer A's undisclosed and unverified use of AI in drafting the introductory section?

AnalyticalQ302: A consequentialist framing focused solely on Client W's satisfaction is insufficient to justify Engineer A's undisclosed and initially unverified AI drafting. Consequentialist analysis in a professional ethics context must account for broader systemic harms beyond a single client's experience, including risks to public trust in engineering authorship, potential downstream reliance by third parties on unattributed AI content, and precedent effects on the profession's credibility.
Resolved by: The board rejects a narrow consequentialist framing that weighs only client satisfaction against convenience, insisting that broader systemic harms to public trust and professional credibility must also enter the calculus. (confidence 0.80)
III.3. III.9. 2 principles 3 facts Conditions Narrative
Counterfactual (2)

If Engineer A had not thoroughly cross-checked the AI-generated report against professional journal articles and search-engine queries, would the Board still have found the report-writing conduct partly ethical rather than wholly unethical?

AnalyticalQ401: Had Engineer A not cross-checked the AI-generated report against professional journal articles and search-engine queries, the Board would very likely have found the report-writing conduct wholly unethical rather than partly ethical. The thorough verification was the specific factor that satisfied the accuracy and competence elements of the Board's analysis; without it, the report would have suffered from unverified accuracy in addition to the confidentiality and citation deficiencies already found.
Resolved by: The board weighs the presence of thorough verification against the separate persistent deficiencies in confidentiality and citation, concluding that verification alone was enough to shift the report conduct from wholly unethical to partly ethical. (confidence 0.50)
I.2. III.9. 3 principles 3 facts Conditions Narrative

If Engineer A had not input Client W's information into the open-source AI software, would the Board still have found a confidentiality problem in Engineer A's use of AI to draft the report?

AnalyticalQ404: The confidentiality problem identified by the Board is specifically tied to the act of inputting Client W's proprietary groundwater and site data into the open-source AI tool. Had Engineer A instead used only publicly available or non-proprietary information to draft the report, no confidentiality violation under II.1.c would have arisen from the AI use itself, though the citation and disclosure concerns regarding AI-generated text would remain unaffected.
Resolved by: The board separated the confidentiality question from the transparency/citation question, treating them as independent issues rather than aspects of a single tradeoff. (confidence 0.78)
II.1.c. I.5. 3 principles 3 facts Conditions Narrative
Board Board question 2

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?

Board conclusion The use of AI-assisted drafting tools by Engineer A was not unethical per se. However, Engineer A’s misuse of the tool, by failing to maintain Responsible Charge over the AI tool and its output before sealing the document and providing it to Client W, was unethical.
Resolved by: The board weighed the general permissibility of adopting AI as a drafting aid against the non-negotiable duty of responsible charge before sealing, finding the tool itself acceptable but the insufficient pre-sealing oversight determinative of unethical conduct. (confidence 0.80)
I.2. II.2.b. III.8.a. 3 principles 3 facts Conditions Narrative
Implicit (2)

Why did Engineer A apply thorough verification to the report but only a cursory review to the engineering design documents, and does this disparity suggest a failure to recognize that sealed design documents carry greater public safety risk than a draft report?

AnalyticalThe Board's responsible-charge finding can be deepened by noting an internal inconsistency in Engineer A's conduct: applying rigorous, multi-source verification to the report while giving only a cursory review to the sealed design documents suggests Engineer A implicitly (and incorrectly) treated the two AI outputs as carrying different risk profiles, when in fact the design documents—bearing Engineer A's seal and governing physical infrastructure with public safety implications—warranted at least equivalent, if not greater, scrutiny than the report. This disparity indicates that the lapse in responsible charge was not merely a matter of insufficient time or diligence but reflected a misjudgment about where professional risk was concentrated, undermining the presumption that professional judgment alone can substitute for adequate review calibrated to consequence severity.
Resolved by: The board weighed Engineer A's discretionary professional judgment about where to allocate review effort against the objectively higher public-safety stakes of sealed design documents, concluding that judgment cannot substitute for scrutiny calibrated to consequence severity. (confidence 0.80)
I.1. II.2.b. III.8.a. 3 principles 3 facts Conditions Narrative
AnalyticalQ102: The disparity between Engineer A's thorough review of the report and cursory review of the sealed design documents suggests a misapplication of risk-based judgment. Sealed engineering plans carry direct public safety consequences and trigger the heightened obligations of II.2.b and I.1, whereas a draft report explicitly labeled as such carries comparatively lower immediate risk. Engineer A's failure to allocate greater scrutiny to the higher-risk work product indicates an inconsistent, rather than risk-calibrated, approach to reviewing AI output.
Resolved by: The board balances the differing risk profiles of the two work products, concluding that safety-critical sealed documents warranted at least the same or greater scrutiny than the lower-risk draft report, which Engineer A failed to provide. (confidence 0.78)
I.1. II.2.b. 3 principles 3 facts Conditions Narrative

Given that Engineer B's retirement left Engineer A without a mentor for quality assurance review, did Engineer A have an obligation to secure an alternative qualified human reviewer before relying on an unfamiliar AI tool as a substitute for that review function?

AnalyticalThe Board's analysis does not directly address whether Engineer A's loss of mentor-based quality assurance created an independent obligation to secure alternative human review before relying on an unfamiliar AI tool as a substitute for that function. Since AI tools cannot exercise professional judgment or bear responsibility, the disappearance of Engineer B's review capacity arguably heightened, rather than diminished, Engineer A's duty to seek some form of qualified peer or supervisory review, especially for sealed design documents; using an untested AI tool as a functional replacement for human mentorship, rather than as a supplement to it, may itself represent a distinct lapse in professional judgment separate from the review-adequacy failure the Board identified.
Resolved by: The board weighs the practical loss of mentor review against the ongoing professional duty of independent oversight, concluding the loss increases rather than relaxes the need for human review. (confidence 0.70)
I.2. II.2.a. II.2.b. 3 principles 3 facts Conditions Narrative
Also discussed in: C203
Principle tension (2)

Does Review Adequacy of AI Output conflict with Responsible Charge over AI-Assisted Design when Engineer A applied rigorous verification to the report but only a high-level review to the design documents, despite both originating from the same unfamiliar AI tool?

AnalyticalQ202/Q204: Yes, a genuine conflict exists. Engineer A's own professional judgment determined that a high-level review of the design documents was sufficient, yet that same judgment proved miscalibrated when the AI output later revealed misaligned dimensions and omitted safety features. This indicates that 'professional judgment primacy' cannot be self-certifying; it must be anchored to objective, risk-proportionate review protocols, especially for documents destined for sealing under II.2.b.
Resolved by: The board subordinates Engineer A's self-declared professional judgment to an objective, risk-proportionate review standard because judgment that later proves miscalibrated cannot be treated as self-validating, especially where public safety is at stake. (confidence 0.85)
II.2.b. 3 principles 3 facts Conditions Narrative
AnalyticalThe case reveals that Review Adequacy of AI Output is not a fixed standard but must scale with the risk and finality of the work product. Engineer A applied rigorous, multi-source verification to the report text but only a cursory review to the sealed design documents, even though both originated from the same unfamiliar AI tool. This asymmetry shows that Responsible Charge over AI-Assisted Design cannot be satisfied by a uniform review effort; instead, the level of scrutiny must be calibrated to the document's downstream consequences (a revisable draft versus a sealed engineering document that directly implicates public safety). Where Engineer A treated both outputs with equivalent methodological trust despite their unequal stakes, the principle of Public Welfare in AI Design Errors was subordinated to convenience, and the tension was not resolved but simply avoided until Client W's discovery of the deficiencies forced it into the open.
Resolved by: The board weighed the unequal downstream consequences of the two AI outputs (revisable draft versus sealed safety document) against Engineer A's uniform trust in the tool, finding that equal treatment improperly subordinated public welfare to convenience. (confidence 0.82)
II.2.b. III.8.a. I.1. 3 principles 3 facts Conditions Narrative

How should Professional Judgment Primacy in AI Use be reconciled with Public Welfare in AI Design Errors, given that Engineer A's own professional judgment approved a cursory review of design documents that later proved to omit required safety features?

Also discussed in: C205 C301
Theoretical (2)

Did Engineer A act with professional integrity, in the virtue-ethical sense, when conducting only a cursory review of the AI-generated design documents before affixing their professional seal?

AnalyticalQ303: Viewed through a virtue-ethics lens, Engineer A's cursory review before sealing the design documents reflects a deficiency in professional prudence and diligence rather than a deliberate ethical lapse. The act of sealing is a public trust gesture that calls for the virtue of thoroughness commensurate with the gravity of the representation being made; a rushed review, even if well-intentioned, falls short of the integrity the sealing act demands.
Resolved by: The board weighs the virtue of efficient practice against the virtue of thoroughness demanded by the public trust act of sealing, and finds the rushed review insufficiently commensurate with that trust even absent bad intent. (confidence 0.50)
II.2.b. III.8.a. I.1. 3 principles 3 facts Conditions Narrative

From a deontological perspective, did Engineer A satisfy the duty of maintaining responsible charge required before sealing engineering documents whose substantive content was generated by an unfamiliar AI tool?

AnalyticalQ304: Under a deontological view of responsible charge, Engineer A did not satisfy the duty because responsible charge requires the sealing engineer to have personally and substantively verified the engineering content prior to sealing, not merely to have made superficial site-specific adjustments to AI output from an unfamiliar tool. The duty is process-oriented and non-delegable, meaning the AI's role as a drafting aid does not reduce Engineer A's independent verification obligation.
Resolved by: The board treats the non-delegable duty of personal verification as overriding any efficiency benefit gained from relying on AI drafting, so the duty is not satisfied merely because some adjustments were made. (confidence 0.50)
III.8.a. II.2.b. I.2. 3 principles 3 facts Conditions Narrative
Counterfactual (2)

If Engineer B had remained available to provide mentorship and quality-assurance review, would the Board still have concluded that Engineer A failed to maintain responsible charge over the AI-generated design documents?

AnalyticalQ402: Even if Engineer B had remained available for mentorship, the Board would likely still have found a responsible charge lapse, because the duty to maintain responsible charge over sealed documents rests personally with the sealing engineer and cannot be fully discharged through a mentor's informal review. Availability of Engineer B might have reduced the likelihood of errors reaching the client, but it would not substitute for Engineer A's own obligation to verify AI output before sealing.
Resolved by: The board weighs the mitigating effect of available mentorship (reducing error likelihood) against the non-transferable nature of the sealing engineer's personal verification duty, and finds mentorship insufficient to discharge that duty. (confidence 0.50)
III.8.a. II.2.b. 3 principles 3 facts Conditions Narrative

If Client W had not discovered the misaligned dimensions and omitted safety features in the AI-generated design documents, would the Board still have concluded that Engineer A's cursory review constituted a misuse of the AI tool and a lapse in responsible charge?

AnalyticalQ403: The Board's conclusion regarding misuse of the AI tool and lapse in responsible charge rests on the adequacy of Engineer A's review process, not on the discovery of actual errors. Even if Client W had not caught the misaligned dimensions and omitted safety features, the cursory review itself would still constitute a failure to maintain responsible charge, since the standard concerns the diligence exercised before sealing rather than whether errors happen to surface afterward.
Resolved by: The board weighs the process-based standard of pre-sealing diligence against the outcome-based fact of client discovery, concluding that outcome is irrelevant to whether the misuse and lapse occurred. (confidence 0.50)
II.2.b. III.8.a. I.1. 3 principles 3 facts Conditions Narrative
Board Board question 3

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?

Board conclusion 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). However, at the time of the BER’s review of this case there is no universal guideline mandating AI disclosure in engineering work. Ethical principles favor transparency when AI plays a substantial role in generating work products. To uphold ethical standards, engineers integrating AI into their practice should adopt rigorous verification processes and consider disclosing AI involvement when it plays a significant role in the final product.
Resolved by: The board balanced the absence of a formal disclosure mandate, which favors no strict obligation, against the aspirational principle of transparency when AI substantially shapes a work product, resulting in a permissive but transparency-encouraging conclusion. (confidence 0.78)
I.5. III.3. III.9. 3 principles 3 facts Conditions Narrative
Implicit (1)

Should Engineer A have disclosed to Client W that the AI drafting tool being used for both the report and the design documents was new to the market and entirely unfamiliar to Engineer A, independent of any later disclosure of AI use generally?

AnalyticalBeyond the Board's transparency recommendation, a distinct obligation exists that does not depend on resolving the broader AI-disclosure debate: under III.9, engineers must give credit for engineering work to those to whom credit is due. Because the AI-generated introduction was polished enough that Client W perceived two different authorial voices, this suggests Engineer A's failure to cite the AI tool was not merely a matter of optional transparency but potentially implicated a distinct intellectual honesty and credit-attribution duty, separate from confidentiality or competence concerns, that exists independent of whether industry-wide AI disclosure norms have yet solidified.
Resolved by: The board separates the unresolved industry-wide AI-disclosure debate from a narrower, code-based credit-attribution duty, holding that the latter survives independent of how the former is eventually settled. (confidence 0.72)
III.9. 3 principles 3 facts Conditions Narrative
AnalyticalQ103/Q104: Beyond any general AI-disclosure question, Engineer A's competence obligations under I.2 and II.2.a arguably required flagging to Client W that the drafting tool was new to market and entirely unfamiliar, and required Engineer A to seek an alternative qualified human reviewer once Engineer B retired. Substituting an untested AI tool for the lost mentorship function, without securing comparable independent review, left a quality-assurance gap that Engineer A's own competence duty should have prompted them to fill.
Resolved by: The board weighs the convenience of adopting a new AI tool against the competence duty to disclose its novelty and to fill the resulting quality-assurance gap, finding the competence duty should have prevailed. (confidence 0.73)
I.2. II.2.a. 3 principles 3 facts Conditions Narrative
Principle tension (1)

How should Transparency of AI Contribution be balanced against Intellectual Honesty in AI Text and Credit Attribution in AI Report when no professional citation standard currently mandates disclosure, yet the AI-generated introduction was polished enough that Client W perceived the report as written by two different authors?

AnalyticalQ203: Even absent a formal citation standard for AI-generated text, the fact that Client W perceived the report as written by two different authors is itself evidence that the AI's contribution was substantial enough to trigger the spirit of III.9's credit-attribution principle. Intellectual honesty does not depend on the existence of a specific rule; the stylistic discontinuity noticed by the client demonstrates that failure to disclose AI involvement created a misleading impression of authorship.
Resolved by: The board weighs the absence of a formal rule against the substantive evidence of misleading impression, concluding that intellectual honesty obligations under III.9's spirit apply even where no explicit AI citation rule exists. (confidence 0.80)
III.9. 3 principles 3 facts Conditions Narrative
AnalyticalThe Board's treatment of Transparency of AI Contribution as aspirational rather than mandatory, absent a governing citation standard, illustrates a broader prioritization principle: codified duties (competence, confidentiality, responsible charge) take precedence over emerging normative expectations (AI disclosure) until the profession formalizes the latter into enforceable rules. Yet the Board's simultaneous recommendation that engineers 'consider disclosing' AI involvement shows that Intellectual Honesty in AI Text and Credit Attribution in AI Report are treated as values in tension with, but not yet enforceable against, the current Code text (III.9., I.5.). This gap is precisely what allowed Engineer A's uncited use of AI to remain technically compliant even though it produced a report so stylistically inconsistent that Client W perceived two different authors—showing that formal compliance and substantive intellectual honesty can diverge when governing standards lag behind technological practice.
Resolved by: The board prioritized codified, enforceable duties over the not-yet-codified expectation of AI disclosure, treating transparency as aspirational rather than binding given the absence of a governing standard. (confidence 0.75)
III.9. I.5. 3 principles 3 facts Conditions Narrative
Decisions & Arguments (6)
View Extraction

Should Engineer A conduct a full, risk-calibrated independent technical review of the AI-generated design documents before sealing them, or rely on a high-level (cursory) review of the AI output?

Options considered:
O1 Perform a rigorous, risk-calibrated review of the AI-generated design documents, independently verifying dimensions, calculations, and required safety features before sealing. Board's choice
O2 Review the AI output only at a high level, treating it as functionally equivalent to validated CAD software output requiring minimal independent scrutiny.
O3 Since mentor Engineer B has retired, secure an alternative qualified human reviewer to check safety-critical elements of the AI output while personally handling the remaining review.
Argument structure (Toulmin):
Claim Unless the AI tool had been independently validated for this specific application and the omitted features were not actually safety-critical, in which case a high-level review might satisfy the standard of care.

Engineer A should have conducted a rigorous, risk-calibrated technical review of the AI-generated design documents, including independent verification of dimensions and required safety features, before sealing and delivering them to Client W, rather than a merely cursory high-level check.

Grounds

Engineer A used an AI-assisted drafting tool new to the market to generate engineering design documents, reviewed the design only at a high level before sealing and submitting it to Client W, and Client W subsequently discovered misaligned dimensions and omitted required safety features.

Warrant

Engineers must hold paramount the safety, health and welfare of the public; an engineer in responsible charge must provide an experience-based quality assurance review of AI-generated output, outlining solution guidelines and constraints and challenging rather than blindly accepting the tool's recommendations; professional judgment cannot be treated as self-validating merely because it was exercised in good faith.

Backing

NSPE Code I.1, II.2.b, II.2.a

Rebuttal

Would not apply if Engineer A possessed specialized prior knowledge or supplementary checks that made the high-level review functionally equivalent to a thorough one, or if the omitted safety features were not reasonably detectable within the ordinary standard of care.

Engineer A Responsible Charge QA Duty

Should Engineer A disclose the AI's substantial contribution and cite the AI tool and pertinent technical authorities to Client W, or treat the AI output as ordinary drafting software requiring no citation?

Options considered:
O1 Proactively inform Client W that AI assisted in drafting the report and design documents, and cite the AI software and any pertinent technical authorities used. Board's choice
O2 Treat the AI tool as internal drafting software equivalent to CAD or word processors, providing no disclosure or citation beyond internal project records.
O3 Withhold information about AI use unless Client W specifically asks, otherwise submit the work product without citation.
Argument structure (Toulmin):
Claim Provided the AI's contribution is substantial enough to be perceptible or to implicate authorship attribution; the obligation weakens where the AI functions as ordinary drafting software with no distinguishable authorial voice.

Engineer A should have disclosed the AI's substantial contribution to the report and design documents and cited the AI tool and pertinent technical authorities it may have drawn upon, rather than submitting the work product without any AI attribution.

Grounds

Engineer A used an AI tool to draft the introductory section of the report and portions of the design documents, did not disclose this use to Client W, and did not cite the AI software or any technical authorities it relied on; Client W observed that the report read as though written by two different authors.

Warrant

Engineers must give credit for engineering work to those to whom credit is due; best practice favors transparency when AI substantially contributes to a work product, even though no universal guideline currently mandates AI disclosure.

Backing

NSPE Code III.9, I.5

Rebuttal

Would not apply if professional norms treat AI strictly as a tool akin to software or a calculator rather than a contributing author, or if no disclosure standard exists and the client raised no concern about authorship or originality.

Engineer A AI Citation Duty

Should Engineer A obtain Client W's consent, use de-identified data, or input Client W's full confidential data into the open-source AI platform without consent?

Options considered:
O1 Seek Client W's explicit prior consent before uploading any proprietary groundwater or site data into the open-source AI platform.
O2 Strip proprietary identifiers from the data before inputting it into the AI tool, preserving analytical utility while avoiding disclosure of confidential client information.
O3 Upload Client W's complete proprietary data into the open-source AI platform without first obtaining consent, prioritizing drafting efficiency.
Argument structure (Toulmin):
Claim Unless Client W had given prior express or implied consent to the use of third-party AI tools, or unless the AI platform contractually guaranteed no retention or reuse of the data.

Engineer A should have obtained Client W's prior consent, or used de-identified data, before uploading Client W's confidential groundwater and site information into the open-source AI platform.

Grounds

Engineer A input Client W's confidential groundwater and site data into an open-source AI interface to help generate the report, without first securing Client W's consent, and the platform's data retention and reuse practices were unknown to Engineer A.

Warrant

Engineers must not reveal facts, data, or information about a client's affairs without prior consent; this duty attaches to the act of disclosure itself and is not cured by subsequent verification of the resulting text's accuracy.

Backing

NSPE Code II.1.c

Rebuttal

Would not apply if Client W had given informed consent to the use of open-source AI tools, or if the data uploaded had been fully de-identified such that no confidential client information was actually disclosed.

Engineer A Client Consent Confidentiality Duty

Should Engineer A obtain client consent or de-identify data before inputting Client W's confidential groundwater and site data into an open-source AI platform, or proceed to input the raw data without consent for efficiency?

Options considered:
O1 Secure Client W's informed consent regarding third-party AI tool use and data handling practices before uploading any proprietary site data.
O2 Proceed to enter Client W's groundwater and site data directly into the open-source AI platform without seeking consent, prioritizing drafting efficiency.
O3 Strip identifying details from the groundwater and site data before inputting it into the AI tool, preserving analytical utility while protecting client confidentiality.
Argument structure (Toulmin):
Claim Unless Client W had given informed consent to third-party tool use or the platform contractually guaranteed no retention or reuse of the data.

Engineer A should have secured Client W's informed consent, or used de-identified data, before entering the confidential groundwater and site data into the open-source AI platform.

Grounds

Engineer A entered Client W's groundwater and site data into an open-source AI platform of unknown data retention practices while drafting the report; no prior consent was sought from Client W for this data transfer.

Warrant

Engineers shall not reveal facts, data, or information about a client's business without prior consent (II.1.c); this confidentiality duty is a threshold gate that must be cleared before efficiency or competence considerations become relevant, and it is not satisfied merely by later verifying the accuracy of AI output.

Backing

NSPE Code II.1.c

Rebuttal

Would not apply if Client W had given implicit or explicit consent to use third-party AI tools, or if the platform was verifiably non-retentive of uploaded data, in which case the confidentiality breach would not have occurred.

Engineer A Client Consent Confidentiality Duty Engineer A Competence Duty

Should Engineer A apply rigorous, risk-proportionate verification (or secure an alternative qualified reviewer) to the AI-generated design documents before sealing, or rely on a cursory high-level review consistent with the effort applied to the report?

Options considered:
O1 Conduct thorough, multi-source verification of the AI-generated design documents equal to or exceeding the effort applied to the report, given their higher public safety stakes and sealing requirement. Board's choice
O2 Rely on a brief, high-level review of the AI-generated design documents, trusting the tool's demonstrated reliability from report drafting to extend to the design outputs.
O3 Secure an independent qualified peer or supervisory reviewer to replace the lost mentorship function before sealing AI-generated design documents.
Argument structure (Toulmin):
Claim Presumably, unless the design content was of sufficiently low complexity or Engineer A possessed compensating specialized expertise that made the cursory review functionally equivalent to a thorough one.

Engineer A should have applied review effort to the AI-generated design documents proportional to their public safety risk, at least equal to the verification given the report, and should have secured an alternative qualified reviewer after Engineer B's retirement, rather than conducting only a cursory review before sealing.

Grounds

Engineer A gave the AI-generated report thorough, multi-source verification but only a high-level review to the sealed design documents from the same unfamiliar AI tool; the design documents later were found to contain misaligned dimensions and omitted required safety features; Engineer B, the prior mentor providing QA review, had retired.

Warrant

Engineers must hold paramount the safety of the public (I.1); engineers may only affix their seal to documents they have prepared or reviewed and are in responsible charge of (II.2.b). Professional judgment cannot be self-certifying; it must be anchored to risk-proportionate review protocols, especially where a customary human QA check (the mentor) is no longer available.

Backing

NSPE Code I.1, II.2.b

Rebuttal

Would not apply if Engineer A reasonably and correctly believed the design documents required less scrutiny due to prior familiarity with the design domain, or if firm QA procedures independently validated the AI output; this defense is defeated by the actual discovery of misaligned dimensions and omitted safety features.

Engineer A Responsible Charge QA Duty Engineer A Design Review Duty

Should Engineer A explicitly cite and credit the AI's substantial contribution to the report text, or treat the AI drafting tool as an uncited internal tool akin to ordinary software?

Options considered:
O1 Explicitly document the AI tool's role in drafting the report text and attribute credit consistent with III.9's credit-attribution duty. Board's choice
O2 Use the AI to draft report content without citation, treating it as functionally equivalent to standard drafting software that requires no attribution.
O3 Verbally inform Client W that AI assisted in drafting the report without including a formal technical citation within the report itself.
Argument structure (Toulmin):
Claim Unless the AI's contribution was merely stylistic phrasing rather than substantive technical content, or industry practice genuinely equates AI drafting tools with ordinary software requiring no citation.

Engineer A should have cited or otherwise credited the AI's substantial contribution to the report's drafted text, even though no universal AI-disclosure standard yet exists, because Client W perceived a stylistic discontinuity indicating two different authorial voices.

Grounds

Engineer A used AI to generate the report's introductory text; Client W later observed that the report read as though written by two different authors; no citation or credit for the AI's contribution was included; Engineer A thoroughly reviewed and verified the AI-generated content before sealing and submission.

Warrant

Engineers shall give credit for engineering work to those to whom credit is due (III.9); competing warrant: engineers may treat drafting software as an uncited internal tool, akin to CAD software, when no code provision or industry standard mandates attribution.

Backing

NSPE Code III.9

Rebuttal

Would not apply if professional norms treat AI purely as a tool like software rather than a contributing author, or if no disclosure or citation standard yet exists and Client W's perception of dual authorship was merely a subjective inference rather than a material misrepresentation.

Engineer A Citation Credit Duty Engineer A AI Citation Duty
Event Timeline (13)
13 sequenced 7 actions 6 events
Case timeline
Engineer B, Engineer A's mentor and supervisor who previously provided quality assurance reviews, retired and became unavailable to Engineer A in a work capacity.
Facing delivery of both a report and design documents without Engineer B's review and mentorship, Engineer A chose to use open-sourced AI software new to the market, with which Engineer A had no prior experience, for drafting.
Causal-normative reasoning(confidence 0.75)
Because AI Tool Adoption was guided by the obligation to perform services only in areas of competence yet proceeded without adequately verifying that competence boundary, it set in motion the chain leading to Confidential Data Input and the eventual exposure of protected information.
State changes (1)
  • began: Untested AI Tool Reliance
Engineer A entered information provided by Client W into the open-source AI interface to generate the report draft and preliminary designs, without obtaining Client W's consent, which the Board characterized as placing the client's private information in the public domain.
Violates (1)
  • Client Confidentiality (Code II.1.c)
Causal-normative reasoning(confidence 0.85)
Confidential Data Input violates Client Confidentiality precisely because it directly causes Confidential Information Exposure, illustrating how the convenience of using the AI tool was purchased at the cost of a core duty to protect client data.
State changes (1)
  • began: Client W Data Public Domain Exposure
Uploading Client W's private information into the open-source AI interface placed the client's confidential information into the public domain without prior consent from Client W.
State changes (1)
  • began: Client W Data Public Domain Exposure
The open-sourced AI software synthesized the information Engineer A input and produced a first draft of the comprehensive contaminant report after a few refining prompts.
State changes (1)
  • began: Uncited AI Tool Use
The AI-assisted drafting tools generated a preliminary design of the plans, including basic layouts and technical specifications, that contained misaligned dimensions and omitted key safety features required by local regulations.
State changes (2)
  • began: AI Design Error Safety Hazard
  • began: Deficient AI Design Documents
Engineer A conducted a thorough review of the AI-generated report, cross-checking key facts against professional journal articles, running search engine queries to verify originality, and personalizing the wording, keeping the document under Engineer A's direction and control.
Fulfills (1)
  • Direction and Control (Code II.2.b)
Causal-normative reasoning(confidence 0.70)
Thorough Report Review fulfills the Direction and Control obligation and is guided by the duties to avoid deceptive acts and to work only within competence, which matters because this review was the intended checkpoint for catching AI-introduced errors before the report was sealed and submitted, yet its outcome still allowed problems to surface later as a Report Inconsistency Observation.
Engineer A completed only a cursory review of the AI-generated design plans, adjusting certain elements for site-specific conditions, and failed to detect misaligned dimensions and omitted safety features required by local regulations.
Violates (2)
  • Direction and Control (Code II.2.b)
  • Responsible Charge (Code III.8.a)
Causal-normative reasoning(confidence 0.80)
Because Engineer A's cursory review of AI-generated designs directly caused the Design Error Discovery that later forced Client W's Revision Instruction, the failure to exercise the direction and control and responsible charge required by the Code shows how skipping careful human oversight of AI output let a flawed design nearly proceed unchecked, undermining the paramount duty to protect public safety and welfare.
State changes (2)
  • began: AI Design Error Safety Hazard
  • began: Responsible Charge Lapse
Engineer A submitted the draft report to Client W for review, marking it clearly as a draft and applying their seal consistent with state law, but chose not to cite the use of AI software or its large language models.
Violates (1)
  • Give Credit for Engineering Work (Code III.9)
Causal-normative reasoning(confidence 0.80)
Report Sealing and Submission violates the duty to Give Credit for Engineering Work because sealing the report as the engineer's own product while omitting the AI tool's role directly precipitates the later Report Inconsistency Observation, exposing the misrepresentation embedded in the submission.
State changes (2)
  • began: Uncited AI Tool Use
  • began: Sealed Draft Report
Engineer A did not cite or disclose the AI-assisted drafting tools used to generate the engineering design documents when providing them to Client W.
Violates (1)
  • Give Credit for Engineering Work (Code III.9)
Causal-normative reasoning(confidence 0.75)
Since this omission sits alongside the AI-driven design and reporting process that produced the inconsistencies Engineer A later noticed, failing to disclose the AI tool's role denies proper credit for the work actually performed and obscures the true authorship and reliability of outputs feeding into decisions like the design revision.
State changes (1)
  • began: Uncited AI Tool Use
During Client W's review, the client noted the report read as if written by two different authors, with the AI-generated introduction exceptionally polished and the data analysis section needing minor edits, though the report was otherwise satisfactory.
Client W discovered misaligned dimensions and an omission of key safety features required by local regulations in the AI-generated design documents, errors that Engineer A's cursory review had failed to detect.
State changes (2)
  • began: AI Design Error Safety Hazard
  • began: Omitted Safety Features Violation
After identifying misaligned dimensions and omitted safety features required by local regulations, Client W raised concerns about the design's accuracy and reliability and instructed Engineer A to revise the plans to meet professional and regulatory standards.
Causal-normative reasoning(confidence 0.80)
Revision Instruction is guided by the duty to hold paramount public safety, health, and welfare, which matters because it is the corrective response triggered by the Design Error Discovery that arose from an inadequately reviewed AI-generated design, showing the obligation functioning as a safeguard against propagating a flawed design into practice.
Narrative (3 main characters)
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Opening Context

Written in second person from the engineer's point of view, so you read the case as the professional experienced it. Underlined names link to the character's profile below.

You are Engineer A, an environmental engineer retained by Client W to prepare a comprehensive report on the manufacture, use, and characteristics of an organic compound identified as an emerging contaminant of concern, along with engineering design documents for modifications to groundwater infrastructure at the site. The work requires you to analyze more than a year of groundwater monitoring data specific to Client W's site. You have relied in past projects on quality assurance reviews from your mentor, Engineer B, particularly for technical writing, but Engineer B has recently retired and is no longer available to review your work. To meet the deadlines for both the report and the design documents, you have begun using an open-source AI tool, new to the market and unfamiliar to you, to draft narrative sections of the report and to generate preliminary engineering plans and specifications. This involves entering Client W's groundwater and site data into the platform and incorporating the AI-generated content into documents you will ultimately seal and submit under your license. You now face a series of decisions about data handling, verification, disclosure, and professional responsibility as you finalize this work.

Main characters (3)

Each card shows the roles a person holds and the tensions those roles raise for them. A single person may carry several roles in the case, and a tension between obligations can implicate more than one person at once. Click Show all tensions for the full list.

Engineer A Roles in this case: Environmental EngineerResponsible Charge EngineerDesign EngineerPublic Responsibility

Guided by: Transparency About Draft and AI Use, Competence in AI-Assisted Environmental Work, Honesty in AI-Assisted Report Writing

Tension between Engineer A Client Consent Confidentiality Duty and Engineer A Competence Duty

Attaches to role: Environmental Engineer

If safeguarding public safety requires disclosing information that the client considers confidential, Engineer A faces a direct conflict between the paramount duty to protect the public and the constraint to keep client data confidential without consent.

Attaches to role: Environmental Engineer

Tension between Engineer A Responsible Charge QA Duty and Engineer A Design Review Duty

Attaches to role: Environmental Engineer

Engineer A's responsibility to exercise personal, accountable professional judgment while in responsible charge can be compromised if AI-generated analysis or mentor guidance is allowed to substitute for that independent judgment, weakening the quality assurance oversight the duty demands.

Attaches to role: Responsible Charge Engineer

Engineer A's duty to maintain and demonstrate professional competence can be undermined if AI tools are relied upon beyond the limits appropriate for tool substitution, allowing automated outputs to stand in for the engineer's own expertise and increasing the risk of undetected errors in the final work product.

Attaches to role: Design Engineer

Tension between Engineer A Citation Credit Duty and Engineer A AI Citation Duty

Attaches to role: Environmental Engineer
Client W Roles in this case: Client

If safeguarding public safety requires disclosing information that the client considers confidential, Engineer A faces a direct conflict between the paramount duty to protect the public and the constraint to keep client data confidential without consent.

Engineer A's duty to maintain and demonstrate professional competence can be undermined if AI tools are relied upon beyond the limits appropriate for tool substitution, allowing automated outputs to stand in for the engineer's own expertise and increasing the risk of undetected errors in the final work product.

Engineer B Roles in this case: Mentor Engineer

Engineer A's responsibility to exercise personal, accountable professional judgment while in responsible charge can be compromised if AI-generated analysis or mentor guidance is allowed to substitute for that independent judgment, weakening the quality assurance oversight the duty demands.

The Board’s deliberation

How the Board of Ethical Review resolved the case, verbatim from its published conclusions.

Engineer A's use of AI in report writing was partly ethical, and partly unethical. Engineer A was competent and did thoroughly review and verify the AI-generated content, ensuring accuracy and compliance with professional standards. However, Engineer A did not obtain client permission to disclose private information, nor did Engineer A document required technical citations. Ethical use of AI to create the report text must satisfy all pertinent requirements.
The use of AI-assisted drafting tools by Engineer A was not unethical per se. However, Engineer A’s misuse of the tool, by failing to maintain Responsible Charge over the AI tool and its output before sealing the document and providing it to Client W, was unethical.
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). However, at the time of the BER’s review of this case there is no universal guideline mandating AI disclosure in engineering work. Ethical principles favor transparency when AI plays a substantial role in generating work products. To uphold ethical standards, engineers integrating AI into their practice should adopt rigorous verification processes and consider disclosing AI involvement when it plays a significant role in the final product.
Opening States (1)
AI Tool Unfamiliarity
Summary
  • Using AI tools to help draft engineering reports is acceptable only if the engineer maintains competence and independently verifies all generated content before it is relied upon.
  • Engineers remain fully responsible for the accuracy and quality of their work product regardless of whether AI assisted in producing it, so responsible charge cannot be delegated to a tool.
  • Transparency about the use of AI, including proper attribution or disclosure, is necessary to preserve trust and honesty in engineering documentation.

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