PASS 3: Temporal Dynamics
Case 7: Use of Artificial Intelligence in Engineering Practice
Timeline Overview
OWL-Time Temporal Structure 10 relations time: = w3.org/2006/time
Extracted Actions (7)
Volitional professional decisions with intentions and ethical contextDescription: 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.
Temporal Marker: At project outset, after Engineer B's retirement instant
Fluent Transitions:
- AI Reliance Without Human QA Support
Mental State: deliberate
Intended Outcome: Compensate for lost mentorship and lack of confidence in technical writing while delivering both work products to Client W
Foreseen Unintended Effects:
- Unfamiliarity with the tool's accuracy and originality of generated content
Guided By Principles:
- Perform Services Only in Areas of Competence
Required Capabilities:
Field classification (triples vs literals)
guidedByPrinciple: Perform Services Only in Areas of CompetencerequiresCapability: Familiarity with AI tool functionality; Professional judgment in tool selectioninitiates: AI Reliance Without Human QA Support
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: At project outset, after Engineer B's retirementeventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Compensate for lost mentorship and lack of confidence in technical writing while delivering both work products to Client WforeseenUnintendedEffectscontent: Unfamiliarity with the tool's accuracy and originality of generated contenttextReferencescontent: 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.temporalExtentcontent: instanttemporalSequencecontent: 2withinCompetenceassessment: True
RDF JSON-LD
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"@id": "http://proethica.org/ontology/case/7#Action_AI_Tool_Adoption",
"@type": "proeth:Action",
"proeth:description": "Facing delivery of both a report and design documents without Engineer B\u0027s 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.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:foreseenUnintendedEffects": [
"Unfamiliarity with the tool\u0027s accuracy and originality of generated content"
],
"proeth:guidedByPrinciple": [
"Perform Services Only in Areas of Competence"
],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"AI Reliance Without Human QA Support"
],
"proeth:intendedOutcome": "Compensate for lost mentorship and lack of confidence in technical writing while delivering both work products to Client W",
"proeth:requiresCapability": [
"Familiarity with AI tool functionality",
"Professional judgment in tool selection"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "At project outset, after Engineer B\u0027s retirement",
"proeth:temporalSequence": 2,
"proeth:textReferences": [
"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."
],
"proeth:withinCompetence": true,
"rdfs:label": "AI Tool Adoption"
}
Description: 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.
Temporal Marker: During report and design document drafting instant
Fluent Transitions:
- Client Confidentiality Breach
Mental State: deliberate
Intended Outcome: Enable the AI software to synthesize the client's information into a draft report and preliminary design documents
Foreseen Unintended Effects:
- Exposure of client's private information through an open-source platform
Obligation Engagement:
- Client Confidentiality (Code II.1.c)
Required Capabilities:
Field classification (triples vs literals)
violatesObligation: Client Confidentiality (Code II.1.c)requiresCapability: Understanding of data privacy implications of open-source AI toolsinitiates: Client Confidentiality Breach
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: During report and design document draftingeventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Enable the AI software to synthesize the client's information into a draft report and preliminary design documentsforeseenUnintendedEffectscontent: Exposure of client's private information through an open-source platformtextReferencescontent: 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.; 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.temporalExtentcontent: instanttemporalSequencecontent: 3withinCompetenceassessment: True
RDF JSON-LD
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"@id": "http://proethica.org/ontology/case/7#Action_Confidential_Data_Input",
"@type": "proeth:Action",
"proeth:description": "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\u0027s consent, which the Board characterized as placing the client\u0027s private information in the public domain.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:foreseenUnintendedEffects": [
"Exposure of client\u0027s private information through an open-source platform"
],
"proeth:fulfillsObligation": [],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Client Confidentiality Breach"
],
"proeth:intendedOutcome": "Enable the AI software to synthesize the client\u0027s information into a draft report and preliminary design documents",
"proeth:raisesObligation": [],
"proeth:requiresCapability": [
"Understanding of data privacy implications of open-source AI tools"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "During report and design document drafting",
"proeth:temporalSequence": 3,
"proeth:textReferences": [
"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.",
"When Engineer A uploaded Client W\u2019s information into the AI open-source interface, this was tantamount to placing the Client\u2019s private information in the public domain."
],
"proeth:violatesObligation": [
"Client Confidentiality (Code II.1.c)"
],
"proeth:withinCompetence": true,
"rdfs:label": "Confidential Data Input"
}
Description: 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.
Temporal Marker: After receiving the AI-generated first draft of the report interval
Fluent Transitions:
- Report Under Direction and Control
Mental State: deliberate
Intended Outcome: Ensure the accuracy and originality of the AI-generated report content before submission
Obligation Engagement:
- Direction and Control (Code II.2.b)
Guided By Principles:
- Avoid Deceptive Acts
- Perform Services Only in Areas of Competence
Required Capabilities:
Field classification (triples vs literals)
fulfillsObligation: Direction and Control (Code II.2.b)guidedByPrinciple: Avoid Deceptive Acts; Perform Services Only in Areas of CompetencerequiresCapability: Environmental engineering expertise; Groundwater data analysis; Technical fact verificationinitiates: Report Under Direction and Control
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: After receiving the AI-generated first draft of the reporteventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Ensure the accuracy and originality of the AI-generated report content before submissiontextReferencescontent: 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; Engineer A also made minor adjustments to some of the wording to personalize the content.temporalExtentcontent: intervaltemporalSequencecontent: 7withinCompetenceassessment: True
RDF JSON-LD
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"proeth": "http://proethica.org/ontology/intermediate#",
"proeth-case": "http://proethica.org/ontology/case/7#",
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"time": "http://www.w3.org/2006/time#"
},
"@id": "http://proethica.org/ontology/case/7#Action_Thorough_Report_Review",
"@type": "proeth:Action",
"proeth:description": "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\u0027s direction and control.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:fulfillsObligation": [
"Direction and Control (Code II.2.b)"
],
"proeth:guidedByPrinciple": [
"Avoid Deceptive Acts",
"Perform Services Only in Areas of Competence"
],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Report Under Direction and Control"
],
"proeth:intendedOutcome": "Ensure the accuracy and originality of the AI-generated report content before submission",
"proeth:raisesObligation": [],
"proeth:requiresCapability": [
"Environmental engineering expertise",
"Groundwater data analysis",
"Technical fact verification"
],
"proeth:temporalExtent": "interval",
"proeth:temporalMarker": "After receiving the AI-generated first draft of the report",
"proeth:temporalSequence": 7,
"proeth:textReferences": [
"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",
"Engineer A also made minor adjustments to some of the wording to personalize the content."
],
"proeth:violatesObligation": [],
"proeth:withinCompetence": true,
"rdfs:label": "Thorough Report Review"
}
Description: 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.
Temporal Marker: During design document preparation, before submission to Client W interval
Fluent Transitions:
- Design Deficiency and Public Safety Risk
- Responsible Charge Lapse
Mental State: deliberate
Intended Outcome: Finalize the preliminary design documents efficiently by relying on the AI-assisted drafting output
Foreseen Unintended Effects:
- Undetected errors in AI-generated plans
- Potential regulatory noncompliance
Obligation Engagement:
- Direction and Control (Code II.2.b)
- Responsible Charge (Code III.8.a)
Guided By Principles:
- Hold Paramount Public Safety, Health, and Welfare
Required Capabilities:
Field classification (triples vs literals)
violatesObligation: Direction and Control (Code II.2.b); Responsible Charge (Code III.8.a)guidedByPrinciple: Hold Paramount Public Safety, Health, and WelfarerequiresCapability: Design verification and quality assurance review; Knowledge of local regulatory requirementsinitiates: Design Deficiency and Public Safety Risk; Responsible Charge Lapse
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: During design document preparation, before submission to Client WeventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Finalize the preliminary design documents efficiently by relying on the AI-assisted drafting outputforeseenUnintendedEffectscontent: Undetected errors in AI-generated plans; Potential regulatory noncompliancetextReferencescontent: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.; the identified errors suggest insufficient review, which could compromise public welfare and impinge on Engineer A’s ethical and professional obligationstemporalExtentcontent: intervaltemporalSequencecontent: 8withinCompetenceassessment: True
RDF JSON-LD
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"time": "http://www.w3.org/2006/time#"
},
"@id": "http://proethica.org/ontology/case/7#Action_Cursory_Design_Review",
"@type": "proeth:Action",
"proeth:description": "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.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:foreseenUnintendedEffects": [
"Undetected errors in AI-generated plans",
"Potential regulatory noncompliance"
],
"proeth:fulfillsObligation": [],
"proeth:guidedByPrinciple": [
"Hold Paramount Public Safety, Health, and Welfare"
],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Design Deficiency and Public Safety Risk",
"Responsible Charge Lapse"
],
"proeth:intendedOutcome": "Finalize the preliminary design documents efficiently by relying on the AI-assisted drafting output",
"proeth:raisesObligation": [],
"proeth:requiresCapability": [
"Design verification and quality assurance review",
"Knowledge of local regulatory requirements"
],
"proeth:temporalExtent": "interval",
"proeth:temporalMarker": "During design document preparation, before submission to Client W",
"proeth:temporalSequence": 8,
"proeth:textReferences": [
"Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.",
"the identified errors suggest insufficient review, which could compromise public welfare and impinge on Engineer A\u2019s ethical and professional obligations"
],
"proeth:violatesObligation": [
"Direction and Control (Code II.2.b)",
"Responsible Charge (Code III.8.a)"
],
"proeth:withinCompetence": true,
"rdfs:label": "Cursory Design Review"
}
Description: 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.
Temporal Marker: At report submission to Client W instant
Fluent Transitions:
- Undisclosed AI Contribution to Report
Mental State: deliberate
Intended Outcome: Deliver a polished, verified draft report to Client W for review
Foreseen Unintended Effects:
- Client unaware of the extent of AI contribution to the report
Obligation Engagement:
- Give Credit for Engineering Work (Code III.9)
Required Capabilities:
Field classification (triples vs literals)
violatesObligation: Give Credit for Engineering Work (Code III.9)requiresCapability: Authority to seal engineering documents; Environmental engineering expertiseinitiates: Undisclosed AI Contribution to Report
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: At report submission to Client WeventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Deliver a polished, verified draft report to Client W for reviewforeseenUnintendedEffectscontent: Client unaware of the extent of AI contribution to the reporttextReferencescontent: 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.temporalExtentcontent: instanttemporalSequencecontent: 9withinCompetenceassessment: True
RDF JSON-LD
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"proeth": "http://proethica.org/ontology/intermediate#",
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"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#",
"time": "http://www.w3.org/2006/time#"
},
"@id": "http://proethica.org/ontology/case/7#Action_Report_Sealing_and_Submission",
"@type": "proeth:Action",
"proeth:description": "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.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:foreseenUnintendedEffects": [
"Client unaware of the extent of AI contribution to the report"
],
"proeth:fulfillsObligation": [],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Undisclosed AI Contribution to Report"
],
"proeth:intendedOutcome": "Deliver a polished, verified draft report to Client W for review",
"proeth:raisesObligation": [],
"proeth:requiresCapability": [
"Authority to seal engineering documents",
"Environmental engineering expertise"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "At report submission to Client W",
"proeth:temporalSequence": 9,
"proeth:textReferences": [
"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."
],
"proeth:violatesObligation": [
"Give Credit for Engineering Work (Code III.9)"
],
"proeth:withinCompetence": true,
"rdfs:label": "Report Sealing and Submission"
}
Description: 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.
Temporal Marker: At design document submission instant
Fluent Transitions:
- Undisclosed AI Contribution to Design Documents
Mental State: deliberate
Intended Outcome: Present the design documents as Engineer A's work product without noting the AI tools used
Foreseen Unintended Effects:
- Client misunderstanding about the origin and reliability of the design work
Obligation Engagement:
- Give Credit for Engineering Work (Code III.9)
Required Capabilities:
Field classification (triples vs literals)
violatesObligation: Give Credit for Engineering Work (Code III.9)requiresCapability: Professional transparency in attributioninitiates: Undisclosed AI Contribution to Design Documents
descriptioncontent: 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.hasAgentcontent: Engineer AtemporalMarkercontent: At design document submissioneventRoleContextcontent: Licensed Environmental EngineerhasMentalStatecontent: deliberateintendedOutcomecontent: Present the design documents as Engineer A's work product without noting the AI tools usedforeseenUnintendedEffectscontent: Client misunderstanding about the origin and reliability of the design worktextReferencescontent: Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents.temporalExtentcontent: instanttemporalSequencecontent: 10withinCompetenceassessment: True
RDF JSON-LD
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"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#",
"time": "http://www.w3.org/2006/time#"
},
"@id": "http://proethica.org/ontology/case/7#Action_Design_AI_Disclosure_Omission",
"@type": "proeth:Action",
"proeth:description": "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.",
"proeth:eventRoleContext": "Licensed Environmental Engineer",
"proeth:foreseenUnintendedEffects": [
"Client misunderstanding about the origin and reliability of the design work"
],
"proeth:fulfillsObligation": [],
"proeth:hasAgent": "Engineer A",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Undisclosed AI Contribution to Design Documents"
],
"proeth:intendedOutcome": "Present the design documents as Engineer A\u0027s work product without noting the AI tools used",
"proeth:raisesObligation": [],
"proeth:requiresCapability": [
"Professional transparency in attribution"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "At design document submission",
"proeth:temporalSequence": 10,
"proeth:textReferences": [
"Again, Engineer A did not cite the AI-assisted drafting tools they used to generate the engineering design documents."
],
"proeth:violatesObligation": [
"Give Credit for Engineering Work (Code III.9)"
],
"proeth:withinCompetence": true,
"rdfs:label": "Design AI Disclosure Omission"
}
Description: 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.
Temporal Marker: After Client W's review of the deliverables instant
Fluent Transitions:
- Design Revision Required
Mental State: deliberate
Intended Outcome: Obtain corrected design documents that satisfy all necessary professional and regulatory standards
Guided By Principles:
- Hold Paramount Public Safety, Health, and Welfare
Required Capabilities:
Field classification (triples vs literals)
guidedByPrinciple: Hold Paramount Public Safety, Health, and WelfarerequiresCapability: Ability to review deliverables against regulatory requirementsinitiates: Design Revision Required
descriptioncontent: 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.hasAgentcontent: Client WtemporalMarkercontent: After Client W's review of the deliverableseventRoleContextcontent: ClienthasMentalStatecontent: deliberateintendedOutcomecontent: Obtain corrected design documents that satisfy all necessary professional and regulatory standardstextReferencescontent: 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.temporalExtentcontent: instanttemporalSequencecontent: 13withinCompetenceassessment: True
RDF JSON-LD
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"@id": "http://proethica.org/ontology/case/7#Action_Revision_Instruction",
"@type": "proeth:Action",
"proeth:description": "After identifying misaligned dimensions and omitted safety features required by local regulations, Client W raised concerns about the design\u0027s accuracy and reliability and instructed Engineer A to revise the plans to meet professional and regulatory standards.",
"proeth:eventRoleContext": "Client",
"proeth:guidedByPrinciple": [
"Hold Paramount Public Safety, Health, and Welfare"
],
"proeth:hasAgent": "Client W",
"proeth:hasMentalState": "deliberate",
"proeth:initiates": [
"Design Revision Required"
],
"proeth:intendedOutcome": "Obtain corrected design documents that satisfy all necessary professional and regulatory standards",
"proeth:requiresCapability": [
"Ability to review deliverables against regulatory requirements"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "After Client W\u0027s review of the deliverables",
"proeth:temporalSequence": 13,
"proeth:textReferences": [
"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."
],
"proeth:withinCompetence": true,
"rdfs:label": "Revision Instruction"
}
Extracted Events (6)
Occurrences that trigger ethical considerations and state changesDescription: 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.
Temporal Marker: Before Engineer A was retained by Client W instant
Fluent Transitions:
- Loss of Mentorship Support
- Unreviewed Work Product Risk
- Mentor Quality Assurance Available
Field classification (triples vs literals)
initiates: Loss of Mentorship Support; Unreviewed Work Product Riskterminates: Mentor Quality Assurance Available
descriptioncontent: 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.temporalMarkercontent: Before Engineer A was retained by Client WtextReferencescontent: But Engineer B recently retired and was no longer available to Engineer A in a work capacity.eventTypecontent: exogenoustemporalExtentcontent: instanttemporalSequencecontent: 1confidenceassessment: 0.95
RDF JSON-LD
{
"@context": {
"proeth": "http://proethica.org/ontology/intermediate#",
"proeth-case": "http://proethica.org/ontology/case/7#",
"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#",
"time": "http://www.w3.org/2006/time#"
},
"@id": "http://proethica.org/ontology/case/7#Event_Mentor_Retirement",
"@type": "proeth:Event",
"proeth:confidence": "0.95",
"proeth:description": "Engineer B, Engineer A\u0027s mentor and supervisor who previously provided quality assurance reviews, retired and became unavailable to Engineer A in a work capacity.",
"proeth:eventType": "exogenous",
"proeth:initiates": [
"Loss of Mentorship Support",
"Unreviewed Work Product Risk"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "Before Engineer A was retained by Client W",
"proeth:temporalSequence": 1,
"proeth:terminates": [
"Mentor Quality Assurance Available"
],
"proeth:textReferences": [
"But Engineer B recently retired and was no longer available to Engineer A in a work capacity."
],
"rdfs:label": "Mentor Retirement"
}
Description: 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.
Temporal Marker: At the moment Engineer A input Client W's information into the AI software instant
Fluent Transitions:
- Client Confidentiality Breach
- Client Information Confidentiality
Caused By Action: Action_Confidential_Data_Input
Field classification (triples vs literals)
causedByAction: http://proethica.org/ontology/case/7#Action_Confidential_Data_Inputinitiates: Client Confidentiality Breachterminates: Client Information Confidentiality
descriptioncontent: 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.temporalMarkercontent: At the moment Engineer A input Client W's information into the AI softwaretextReferencescontent: 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.eventTypecontent: automatictemporalExtentcontent: instanttemporalSequencecontent: 4confidenceassessment: 0.9
RDF JSON-LD
{
"@context": {
"proeth": "http://proethica.org/ontology/intermediate#",
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},
"@id": "http://proethica.org/ontology/case/7#Event_Confidential_Information_Exposure",
"@type": "proeth:Event",
"proeth:causedByAction": "http://proethica.org/ontology/case/7#Action_Confidential_Data_Input",
"proeth:confidence": "0.9",
"proeth:description": "Uploading Client W\u0027s private information into the open-source AI interface placed the client\u0027s confidential information into the public domain without prior consent from Client W.",
"proeth:eventType": "automatic",
"proeth:initiates": [
"Client Confidentiality Breach"
],
"proeth:temporalExtent": "instant",
"proeth:temporalMarker": "At the moment Engineer A input Client W\u0027s information into the AI software",
"proeth:temporalSequence": 4,
"proeth:terminates": [
"Client Information Confidentiality"
],
"proeth:textReferences": [
"When Engineer A uploaded Client W\u2019s information into the AI open-source interface, this was tantamount to placing the Client\u2019s private information in the public domain."
],
"rdfs:label": "Confidential Information Exposure"
}
Description: 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.
Temporal Marker: After Engineer A input Client W's information into the AI software instant
Fluent Transitions:
- AI-Generated Report Draft Exists
- Uncited AI Contribution
Caused By Action: Action_Confidential_Data_Input
Field classification (triples vs literals)
causedByAction: http://proethica.org/ontology/case/7#Action_Confidential_Data_Inputinitiates: AI-Generated Report Draft Exists; Uncited AI Contribution
descriptioncontent: 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.temporalMarkercontent: After Engineer A input Client W's information into the AI softwaretextReferencescontent: after a few refining prompts, received a first draft of the report generated by the AI softwareeventTypecontent: automatictemporalExtentcontent: instanttemporalSequencecontent: 5confidenceassessment: 0.93
RDF JSON-LD
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Description: 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.
Temporal Marker: After Engineer A entered Client W's information into the AI drafting software instant
Fluent Transitions:
- AI-Generated Design Documents Exist
- Latent Design Errors
- Public Safety Risk
Caused By Action: Action_AI_Tool_Adoption
Field classification (triples vs literals)
causedByAction: http://proethica.org/ontology/case/7#Action_AI_Tool_Adoptioninitiates: AI-Generated Design Documents Exist; Latent Design Errors; Public Safety Risk
descriptioncontent: 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.temporalMarkercontent: After Engineer A entered Client W's information into the AI drafting softwaretextReferencescontent: relied on the AI-assisted drafting tools to generate a preliminary design of the plans, including basic layouts and technical specificationseventTypecontent: automatictemporalExtentcontent: instanttemporalSequencecontent: 6confidenceassessment: 0.92
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Description: 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.
Temporal Marker: When Client W reviewed the draft report instant
Fluent Transitions:
- Client Transparency Concern
Caused By Action: Action_Report_Sealing_and_Submission
Field classification (triples vs literals)
causedByAction: http://proethica.org/ontology/case/7#Action_Report_Sealing_and_Submissioninitiates: Client Transparency Concern
descriptioncontent: 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.temporalMarkercontent: When Client W reviewed the draft reporttextReferencescontent: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.eventTypecontent: outcometemporalExtentcontent: instanttemporalSequencecontent: 11confidenceassessment: 0.88
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Description: 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.
Temporal Marker: When Client W reviewed the design documents instant
Fluent Transitions:
- Known Design Deficiency
- Regulatory Noncompliance Risk
- Client Reliability Concern
- Latent Design Errors
Caused By Action: Action_Cursory_Design_Review
Field classification (triples vs literals)
causedByAction: http://proethica.org/ontology/case/7#Action_Cursory_Design_Reviewinitiates: Known Design Deficiency; Regulatory Noncompliance Risk; Client Reliability Concernterminates: Latent Design Errors
descriptioncontent: 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.temporalMarkercontent: When Client W reviewed the design documentstextReferencescontent: 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.eventTypecontent: outcometemporalExtentcontent: instanttemporalSequencecontent: 12confidenceassessment: 0.93
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"rdfs:label": "Design Error Discovery"
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Causal Chains (8)
NESS test analysis: Necessary Element of Sufficient SetCausal 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.
Necessary Factors (NESS):
- Engineer B's retirement removing quality assurance and mentorship support
- Engineer A's lack of confidence in their own technical writing
- Obligation to deliver both the report and design documents to Client W
Sufficient Factors:
- Combination of lost mentorship + writing insecurity + delivery obligation was enough to prompt the turn to AI tools
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
Mentor Retirement
Engineer B retires and is no longer available to Engineer A in a work capacity -
Loss of Quality Assurance Support
Engineer A can no longer rely on guidance and quality assurance reviews to refine report drafts -
Delivery Pressure
Engineer A still must deliver both the report and the engineering design documents -
AI Tool Adoption
Engineer A opts to use open-sourced AI software and AI-assisted drafting tools despite having no previous experience with them
Field classification (triples vs literals)
cause: Mentor Retirementeffect: AI Tool AdoptionresponsibleAgent: Engineer A
causalLanguagecontent: 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.necessaryFactorscontent: Engineer B's retirement removing quality assurance and mentorship support; Engineer A's lack of confidence in their own technical writing; Obligation to deliver both the report and design documents to Client WsufficientFactorscontent: Combination of lost mentorship + writing insecurity + delivery obligation was enough to prompt the turn to AI toolscounterfactualcontent: Had Engineer B remained available for review and mentorship, Engineer A would likely have followed the prior workflow of drafting and receiving quality assurance review rather than adopting an unfamiliar AI toolcausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'Mentor Retirement', 'proeth:description': 'Engineer B retires and is no longer available to Engineer A in a work capacity'}; {'proeth:step': 2, 'proeth:element': 'Loss of Quality Assurance Support', 'proeth:description': 'Engineer A can no longer rely on guidance and quality assurance reviews to refine report drafts'}; {'proeth:step': 3, 'proeth:element': 'Delivery Pressure', 'proeth:description': 'Engineer A still must deliver both the report and the engineering design documents'}; {'proeth:step': 4, 'proeth:element': 'AI Tool Adoption', 'proeth:description': 'Engineer A opts to use open-sourced AI software and AI-assisted drafting tools despite having no previous experience with them'}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
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"proeth:element": "Delivery Pressure",
"proeth:step": 3
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"proeth:description": "Engineer A opts to use open-sourced AI software and AI-assisted drafting tools despite having no previous experience with them",
"proeth:element": "AI Tool Adoption",
"proeth:step": 4
}
],
"proeth:cause": "Mentor Retirement",
"proeth:counterfactual": "Had Engineer B remained available for review and mentorship, Engineer A would likely have followed the prior workflow of drafting and receiving quality assurance review rather than adopting an unfamiliar AI tool",
"proeth:discoveredInSection": "facts",
"proeth:effect": "AI Tool Adoption",
"proeth:necessaryFactors": [
"Engineer B\u0027s retirement removing quality assurance and mentorship support",
"Engineer A\u0027s lack of confidence in their own technical writing",
"Obligation to deliver both the report and design documents to Client W"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
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],
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}
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.
Necessary Factors (NESS):
- Decision to use the open-source AI software as the drafting mechanism
- Need to supply client-provided information for the AI to synthesize a draft
Sufficient Factors:
- The chosen AI workflow required inputting Client W's information to generate content, making the upload a direct consequence of the adoption decision
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
AI Tool Adoption
Engineer A opts to use open-sourced AI software for the report and design documents -
Data Gathering
Engineer A gathers the relevant information provided by Client W -
Confidential Data Input
Engineer A inputs Client W's information into the open-source AI software to generate drafts
Field classification (triples vs literals)
cause: AI Tool Adoptioneffect: Confidential Data InputresponsibleAgent: Engineer A
causalLanguagecontent: 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.necessaryFactorscontent: Decision to use the open-source AI software as the drafting mechanism; Need to supply client-provided information for the AI to synthesize a draftsufficientFactorscontent: The chosen AI workflow required inputting Client W's information to generate content, making the upload a direct consequence of the adoption decisioncounterfactualcontent: If Engineer A had drafted manually or used a closed, secure tool, Client W's information would not have been entered into an open-source interfacecausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'AI Tool Adoption', 'proeth:description': 'Engineer A opts to use open-sourced AI software for the report and design documents'}; {'proeth:step': 2, 'proeth:element': 'Data Gathering', 'proeth:description': 'Engineer A gathers the relevant information provided by Client W'}; {'proeth:step': 3, 'proeth:element': 'Confidential Data Input', 'proeth:description': "Engineer A inputs Client W's information into the open-source AI software to generate drafts"}responsibilityTypeassessment: directwithinAgentControlassessment: True
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}
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"proeth:cause": "AI Tool Adoption",
"proeth:counterfactual": "If Engineer A had drafted manually or used a closed, secure tool, Client W\u0027s information would not have been entered into an open-source interface",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Confidential Data Input",
"proeth:necessaryFactors": [
"Decision to use the open-source AI software as the drafting mechanism",
"Need to supply client-provided information for the AI to synthesize a draft"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
"The chosen AI workflow required inputting Client W\u0027s information to generate content, making the upload a direct consequence of the adoption decision"
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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.
Necessary Factors (NESS):
- Uploading Client W's private information into the AI interface
- The open-source nature of the AI software
- Absence of Client W's prior consent
Sufficient Factors:
- Uploading confidential client data into an open-source interface was itself sufficient to place the information in the public domain
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
Confidential Data Input
Engineer A enters Client W's private information into the open-source AI interface -
Open-Source Processing
The open-source system processes and retains the client's data outside a protected environment -
Confidential Information Exposure
Client W's private information is effectively placed in the public domain without consent, contrary to Code section II.1.c
Field classification (triples vs literals)
cause: Confidential Data Inputeffect: Confidential Information ExposureresponsibleAgent: Engineer A
causalLanguagecontent: 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.necessaryFactorscontent: Uploading Client W's private information into the AI interface; The open-source nature of the AI software; Absence of Client W's prior consentsufficientFactorscontent: Uploading confidential client data into an open-source interface was itself sufficient to place the information in the public domaincounterfactualcontent: Without the upload to the open-source interface (or with a secure, private tool), Client W's confidential information would not have been exposedcausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'Confidential Data Input', 'proeth:description': "Engineer A enters Client W's private information into the open-source AI interface"}; {'proeth:step': 2, 'proeth:element': 'Open-Source Processing', 'proeth:description': "The open-source system processes and retains the client's data outside a protected environment"}; {'proeth:step': 3, 'proeth:element': 'Confidential Information Exposure', 'proeth:description': "Client W's private information is effectively placed in the public domain without consent, contrary to Code section II.1.c"}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
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"proeth:element": "Confidential Information Exposure",
"proeth:step": 3
}
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"proeth:cause": "Confidential Data Input",
"proeth:counterfactual": "Without the upload to the open-source interface (or with a secure, private tool), Client W\u0027s confidential information would not have been exposed",
"proeth:discoveredInSection": "discussion",
"proeth:effect": "Confidential Information Exposure",
"proeth:necessaryFactors": [
"Uploading Client W\u0027s private information into the AI interface",
"The open-source nature of the AI software",
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Causal Language: 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 and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.
Necessary Factors (NESS):
- Existence of the AI-generated first draft
- Engineer A's awareness of unfamiliarity with the AI tool's accuracy and originality
- Engineer A's technical competence to verify content
Sufficient Factors:
- AI-generated draft of uncertain accuracy + Engineer A's professional diligence was enough to prompt cross-checking against professional sources
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
AI Report Generation
The AI software synthesizes Client W's information and produces a first draft of the report -
Recognition of Uncertainty
Engineer A, unfamiliar with the tool's accuracy and originality, distrusts the raw output -
Thorough Report Review
Engineer A cross-checks key facts against professional journal articles and verifies phrasing via search queries, then personalizes wording
Field classification (triples vs literals)
cause: AI Report Generationeffect: Thorough Report ReviewresponsibleAgent: Engineer A
causalLanguagecontent: 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 and verifying the phrasing by running search engine queries to ensure the content did not match any existing language.necessaryFactorscontent: Existence of the AI-generated first draft; Engineer A's awareness of unfamiliarity with the AI tool's accuracy and originality; Engineer A's technical competence to verify contentsufficientFactorscontent: AI-generated draft of uncertain accuracy + Engineer A's professional diligence was enough to prompt cross-checking against professional sourcescounterfactualcontent: Without the AI-generated draft, this specific verification exercise (fact cross-checking and plagiarism searches) would not have occurred; without Engineer A's diligence, the review might have been cursory as with the designscausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'AI Report Generation', 'proeth:description': "The AI software synthesizes Client W's information and produces a first draft of the report"}; {'proeth:step': 2, 'proeth:element': 'Recognition of Uncertainty', 'proeth:description': "Engineer A, unfamiliar with the tool's accuracy and originality, distrusts the raw output"}; {'proeth:step': 3, 'proeth:element': 'Thorough Report Review', 'proeth:description': 'Engineer A cross-checks key facts against professional journal articles and verifies phrasing via search queries, then personalizes wording'}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
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{
"proeth:description": "Engineer A cross-checks key facts against professional journal articles and verifies phrasing via search queries, then personalizes wording",
"proeth:element": "Thorough Report Review",
"proeth:step": 3
}
],
"proeth:cause": "AI Report Generation",
"proeth:counterfactual": "Without the AI-generated draft, this specific verification exercise (fact cross-checking and plagiarism searches) would not have occurred; without Engineer A\u0027s diligence, the review might have been cursory as with the designs",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Thorough Report Review",
"proeth:necessaryFactors": [
"Existence of the AI-generated first draft",
"Engineer A\u0027s awareness of unfamiliarity with the AI tool\u0027s accuracy and originality",
"Engineer A\u0027s technical competence to verify content"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
"AI-generated draft of uncertain accuracy + Engineer A\u0027s professional diligence was enough to prompt cross-checking against professional sources"
],
"proeth:withinAgentControl": true
}
Causal Language: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
Necessary Factors (NESS):
- Submission of the draft report to Client W for review
- Stylistic disparity between the AI-polished introduction and the data-analysis section
- Nondisclosure of the AI software used to draft the report
Sufficient Factors:
- A report containing AI-generated polished text alongside Engineer A's own edits, submitted without AI disclosure, was sufficient for the client to perceive two different authors
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
AI Report Generation
AI produces an exceptionally polished introductory section -
Report Sealing and Submission
Engineer A submits the sealed draft report without citing AI use -
Client Review
Client W reviews the report and notes uneven quality between sections -
Report Inconsistency Observation
Client W comments that the report reads as if written by two different authors
Field classification (triples vs literals)
cause: Report Sealing and Submissioneffect: Report Inconsistency ObservationresponsibleAgent: Engineer A
causalLanguagecontent: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.necessaryFactorscontent: Submission of the draft report to Client W for review; Stylistic disparity between the AI-polished introduction and the data-analysis section; Nondisclosure of the AI software used to draft the reportsufficientFactorscontent: A report containing AI-generated polished text alongside Engineer A's own edits, submitted without AI disclosure, was sufficient for the client to perceive two different authorscounterfactualcontent: Had Engineer A disclosed the AI's substantial contribution or harmonized the writing throughout, the client's confusion about authorship would likely have been avoided; per the discussion, 'proactive disclosure could have prevented misunderstandings and strengthened trust'causalSequencecontent: {'proeth:step': 1, 'proeth:element': 'AI Report Generation', 'proeth:description': 'AI produces an exceptionally polished introductory section'}; {'proeth:step': 2, 'proeth:element': 'Report Sealing and Submission', 'proeth:description': 'Engineer A submits the sealed draft report without citing AI use'}; {'proeth:step': 3, 'proeth:element': 'Client Review', 'proeth:description': 'Client W reviews the report and notes uneven quality between sections'}; {'proeth:step': 4, 'proeth:element': 'Report Inconsistency Observation', 'proeth:description': 'Client W comments that the report reads as if written by two different authors'}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
{
"@context": {
"proeth": "http://proethica.org/ontology/intermediate#",
"proeth-case": "http://proethica.org/ontology/case/7#",
"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#"
},
"@id": "http://proethica.org/ontology/case/7#CausalChain_5",
"@type": "proeth:CausalChain",
"proeth:causalLanguage": "The Client commented that the report read as if written by two different authors but was otherwise satisfactory.",
"proeth:causalSequence": [
{
"proeth:description": "AI produces an exceptionally polished introductory section",
"proeth:element": "AI Report Generation",
"proeth:step": 1
},
{
"proeth:description": "Engineer A submits the sealed draft report without citing AI use",
"proeth:element": "Report Sealing and Submission",
"proeth:step": 2
},
{
"proeth:description": "Client W reviews the report and notes uneven quality between sections",
"proeth:element": "Client Review",
"proeth:step": 3
},
{
"proeth:description": "Client W comments that the report reads as if written by two different authors",
"proeth:element": "Report Inconsistency Observation",
"proeth:step": 4
}
],
"proeth:cause": "Report Sealing and Submission",
"proeth:counterfactual": "Had Engineer A disclosed the AI\u0027s substantial contribution or harmonized the writing throughout, the client\u0027s confusion about authorship would likely have been avoided; per the discussion, \u0027proactive disclosure could have prevented misunderstandings and strengthened trust\u0027",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Report Inconsistency Observation",
"proeth:necessaryFactors": [
"Submission of the draft report to Client W for review",
"Stylistic disparity between the AI-polished introduction and the data-analysis section",
"Nondisclosure of the AI software used to draft the report"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
"A report containing AI-generated polished text alongside Engineer A\u0027s own edits, submitted without AI disclosure, was sufficient for the client to perceive two different authors"
],
"proeth:withinAgentControl": true
}
Causal Language: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
Necessary Factors (NESS):
- Existence of AI-generated preliminary plans and specifications
- Engineer A's reliance on the AI output without proper oversight
- Absence of Engineer B's quality assurance function
Sufficient Factors:
- AI-generated plans combined with Engineer A's choice to rely on them 'without proper oversight' was sufficient to produce only a high-level review
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
Confidential Data Input
Engineer A enters Client W's information into the AI software for design generation -
AI Design Generation
AI-assisted drafting tools generate preliminary plans including basic layouts and technical specifications -
Cursory Design Review
Engineer A completes only a cursory review, adjusting certain elements for site-specific conditions, failing to maintain Responsible Charge
Field classification (triples vs literals)
cause: AI Design Generationeffect: Cursory Design ReviewresponsibleAgent: Engineer A
causalLanguagecontent: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.necessaryFactorscontent: Existence of AI-generated preliminary plans and specifications; Engineer A's reliance on the AI output without proper oversight; Absence of Engineer B's quality assurance functionsufficientFactorscontent: AI-generated plans combined with Engineer A's choice to rely on them 'without proper oversight' was sufficient to produce only a high-level reviewcounterfactualcontent: Had Engineer A applied the same thorough scrutiny used for the report — the level of scrutiny required for human-created work — the review would not have been cursorycausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'Confidential Data Input', 'proeth:description': "Engineer A enters Client W's information into the AI software for design generation"}; {'proeth:step': 2, 'proeth:element': 'AI Design Generation', 'proeth:description': 'AI-assisted drafting tools generate preliminary plans including basic layouts and technical specifications'}; {'proeth:step': 3, 'proeth:element': 'Cursory Design Review', 'proeth:description': 'Engineer A completes only a cursory review, adjusting certain elements for site-specific conditions, failing to maintain Responsible Charge'}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
{
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"proeth": "http://proethica.org/ontology/intermediate#",
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"rdfs": "http://www.w3.org/2000/01/rdf-schema#"
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"@id": "http://proethica.org/ontology/case/7#CausalChain_6",
"@type": "proeth:CausalChain",
"proeth:causalLanguage": "Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.",
"proeth:causalSequence": [
{
"proeth:description": "Engineer A enters Client W\u0027s information into the AI software for design generation",
"proeth:element": "Confidential Data Input",
"proeth:step": 1
},
{
"proeth:description": "AI-assisted drafting tools generate preliminary plans including basic layouts and technical specifications",
"proeth:element": "AI Design Generation",
"proeth:step": 2
},
{
"proeth:description": "Engineer A completes only a cursory review, adjusting certain elements for site-specific conditions, failing to maintain Responsible Charge",
"proeth:element": "Cursory Design Review",
"proeth:step": 3
}
],
"proeth:cause": "AI Design Generation",
"proeth:counterfactual": "Had Engineer A applied the same thorough scrutiny used for the report \u2014 the level of scrutiny required for human-created work \u2014 the review would not have been cursory",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Cursory Design Review",
"proeth:necessaryFactors": [
"Existence of AI-generated preliminary plans and specifications",
"Engineer A\u0027s reliance on the AI output without proper oversight",
"Absence of Engineer B\u0027s quality assurance function"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
"AI-generated plans combined with Engineer A\u0027s choice to rely on them \u0027without proper oversight\u0027 was sufficient to produce only a high-level review"
],
"proeth:withinAgentControl": true
}
Causal Language: 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.
Necessary Factors (NESS):
- AI-generated errors (misaligned dimensions, omitted safety features) present in the plans
- Engineer A's failure to detect these errors during the cursory review
- Client W's own review of the design documents
Sufficient Factors:
- Undetected AI errors passing through insufficient review into the deliverable, combined with client review, was sufficient for the errors to be discovered by the client; per the discussion, 'the identified errors suggest insufficient review, which could compromise public welfare'
Responsibility Attribution:
Agent: Engineer A
Type: direct
Within Agent Control:
Yes
Causal Sequence:
-
AI Design Generation
AI tools produce plans containing misaligned dimensions and omitting key safety features -
Cursory Design Review
Engineer A's high-level review fails to detect the errors -
Deliverable Submission
Flawed design documents reach Client W without disclosure of AI involvement -
Design Error Discovery
Client W notices misaligned dimensions and omission of key safety features required by local regulations
Field classification (triples vs literals)
cause: Cursory Design Revieweffect: Design Error DiscoveryresponsibleAgent: Engineer A
causalLanguagecontent: 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.necessaryFactorscontent: AI-generated errors (misaligned dimensions, omitted safety features) present in the plans; Engineer A's failure to detect these errors during the cursory review; Client W's own review of the design documentssufficientFactorscontent: Undetected AI errors passing through insufficient review into the deliverable, combined with client review, was sufficient for the errors to be discovered by the client; per the discussion, 'the identified errors suggest insufficient review, which could compromise public welfare'counterfactualcontent: Had Engineer A performed a comprehensive verification, the misaligned dimensions and omitted safety features would likely have been caught before submission, and Client W would not have discovered themcausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'AI Design Generation', 'proeth:description': 'AI tools produce plans containing misaligned dimensions and omitting key safety features'}; {'proeth:step': 2, 'proeth:element': 'Cursory Design Review', 'proeth:description': "Engineer A's high-level review fails to detect the errors"}; {'proeth:step': 3, 'proeth:element': 'Deliverable Submission', 'proeth:description': 'Flawed design documents reach Client W without disclosure of AI involvement'}; {'proeth:step': 4, 'proeth:element': 'Design Error Discovery', 'proeth:description': 'Client W notices misaligned dimensions and omission of key safety features required by local regulations'}responsibilityTypeassessment: directwithinAgentControlassessment: True
RDF JSON-LD
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"proeth": "http://proethica.org/ontology/intermediate#",
"proeth-case": "http://proethica.org/ontology/case/7#",
"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#"
},
"@id": "http://proethica.org/ontology/case/7#CausalChain_7",
"@type": "proeth:CausalChain",
"proeth:causalLanguage": "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.",
"proeth:causalSequence": [
{
"proeth:description": "AI tools produce plans containing misaligned dimensions and omitting key safety features",
"proeth:element": "AI Design Generation",
"proeth:step": 1
},
{
"proeth:description": "Engineer A\u0027s high-level review fails to detect the errors",
"proeth:element": "Cursory Design Review",
"proeth:step": 2
},
{
"proeth:description": "Flawed design documents reach Client W without disclosure of AI involvement",
"proeth:element": "Deliverable Submission",
"proeth:step": 3
},
{
"proeth:description": "Client W notices misaligned dimensions and omission of key safety features required by local regulations",
"proeth:element": "Design Error Discovery",
"proeth:step": 4
}
],
"proeth:cause": "Cursory Design Review",
"proeth:counterfactual": "Had Engineer A performed a comprehensive verification, the misaligned dimensions and omitted safety features would likely have been caught before submission, and Client W would not have discovered them",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Design Error Discovery",
"proeth:necessaryFactors": [
"AI-generated errors (misaligned dimensions, omitted safety features) present in the plans",
"Engineer A\u0027s failure to detect these errors during the cursory review",
"Client W\u0027s own review of the design documents"
],
"proeth:responsibilityType": "direct",
"proeth:responsibleAgent": "Engineer A",
"proeth:sufficientFactors": [
"Undetected AI errors passing through insufficient review into the deliverable, combined with client review, was sufficient for the errors to be discovered by the client; per the discussion, \u0027the identified errors suggest insufficient review, which could compromise public welfare\u0027"
],
"proeth:withinAgentControl": true
}
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.
Necessary Factors (NESS):
- Client W's discovery of misaligned dimensions and omitted safety features
- Client W's concern about accuracy, reliability, and regulatory compliance
Sufficient Factors:
- Discovery of safety-related and regulatory deficiencies in the plans was sufficient to trigger the instruction to revise
Responsibility Attribution:
Agent: Client W (issuing the instruction); Engineer A (creating the conditions requiring it)
Type: shared
Within Agent Control:
Yes
Causal Sequence:
-
Design Error Discovery
Client W discovers misaligned dimensions and omission of key safety features -
Client Concern
Client W raises concerns about the accuracy and reliability of the engineering design -
Revision Instruction
Client W instructs Engineer A to revise the plans to satisfy professional and regulatory standards
Field classification (triples vs literals)
cause: Design Error Discoveryeffect: Revision InstructionresponsibleAgent: Client W (issuing the instruction); Engineer A (creating the conditions requiring it)
causalLanguagecontent: 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.necessaryFactorscontent: Client W's discovery of misaligned dimensions and omitted safety features; Client W's concern about accuracy, reliability, and regulatory compliancesufficientFactorscontent: Discovery of safety-related and regulatory deficiencies in the plans was sufficient to trigger the instruction to revisecounterfactualcontent: Without discovering the errors, Client W would have had no basis to raise concerns or instruct a revision; the flawed plans might have proceeded, risking regulatory noncompliance and safety hazardscausalSequencecontent: {'proeth:step': 1, 'proeth:element': 'Design Error Discovery', 'proeth:description': 'Client W discovers misaligned dimensions and omission of key safety features'}; {'proeth:step': 2, 'proeth:element': 'Client Concern', 'proeth:description': 'Client W raises concerns about the accuracy and reliability of the engineering design'}; {'proeth:step': 3, 'proeth:element': 'Revision Instruction', 'proeth:description': 'Client W instructs Engineer A to revise the plans to satisfy professional and regulatory standards'}responsibilityTypeassessment: sharedwithinAgentControlassessment: True
RDF JSON-LD
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"proeth-case": "http://proethica.org/ontology/case/7#",
"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#"
},
"@id": "http://proethica.org/ontology/case/7#CausalChain_8",
"@type": "proeth:CausalChain",
"proeth:causalLanguage": "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.",
"proeth:causalSequence": [
{
"proeth:description": "Client W discovers misaligned dimensions and omission of key safety features",
"proeth:element": "Design Error Discovery",
"proeth:step": 1
},
{
"proeth:description": "Client W raises concerns about the accuracy and reliability of the engineering design",
"proeth:element": "Client Concern",
"proeth:step": 2
},
{
"proeth:description": "Client W instructs Engineer A to revise the plans to satisfy professional and regulatory standards",
"proeth:element": "Revision Instruction",
"proeth:step": 3
}
],
"proeth:cause": "Design Error Discovery",
"proeth:counterfactual": "Without discovering the errors, Client W would have had no basis to raise concerns or instruct a revision; the flawed plans might have proceeded, risking regulatory noncompliance and safety hazards",
"proeth:discoveredInSection": "facts",
"proeth:effect": "Revision Instruction",
"proeth:necessaryFactors": [
"Client W\u0027s discovery of misaligned dimensions and omitted safety features",
"Client W\u0027s concern about accuracy, reliability, and regulatory compliance"
],
"proeth:responsibilityType": "shared",
"proeth:responsibleAgent": "Client W (issuing the instruction); Engineer A (creating the conditions requiring it)",
"proeth:sufficientFactors": [
"Discovery of safety-related and regulatory deficiencies in the plans was sufficient to trigger the instruction to revise"
],
"proeth:withinAgentControl": true
}
Allen Temporal Relations (10)
Interval algebra relationships with OWL-Time standard properties| From Entity | Allen Relation | To Entity | OWL-Time Property | Evidence |
|---|---|---|---|---|
| Engineer B providing mentorship and quality assurance reviews |
before
Entity1 is before Entity2 |
Engineer B's retirement |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Previously, Engineer A had relied on guidance and quality assurance reviews by their mentor and supe... [more] |
| Engineer B's retirement |
before
Entity1 is before Entity2 |
Engineer A retained by Client W |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Engineer B recently retired and was no longer available to Engineer A in a work capacity. Faced with... [more] |
| Engineer A observing the groundwater monitoring site |
overlaps
Entity1 starts before Entity2 and ends during Entity2 |
Engineer A retained by Client W to prepare the report and design documents |
time:intervalOverlaps
http://www.w3.org/2006/time#intervalOverlaps |
This work required Engineer A to perform an analysis of groundwater monitoring data from a site Engi... [more] |
| Engineer A inputting Client W's information into the AI software |
before
Entity1 is before Entity2 |
receiving the first draft of the report |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Engineer A input the information gathered from Client W into the AI software, and, after a few refin... [more] |
| AI generation of the report draft |
before
Entity1 is before Entity2 |
Engineer A's thorough review and cross-checking of the report |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Not being familiar with the full functionality of the AI software... Engineer A conducted a thorough... [more] |
| Engineer A's thorough review and personalization of the report |
before
Entity1 is before Entity2 |
submission of the sealed draft report to Client W |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Engineer A also made minor adjustments to some of the wording to personalize the content... and subm... [more] |
| AI-assisted generation of preliminary design documents |
before
Entity1 is before Entity2 |
Engineer A's cursory review and site-specific adjustments |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
relied on the AI-assisted drafting tools to generate a preliminary design of the plans... Engineer A... [more] |
| submission of the draft report and design documents |
before
Entity1 is before Entity2 |
Client W's review |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
When Client W reviewed the draft report, Client W noted that the section analyzing the groundwater m... [more] |
| Client W's identification of errors in the design documents |
before
Entity1 is before Entity2 |
Client W's instruction to Engineer A to revise the plans |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
Client W raised concerns about the accuracy and reliability of the engineering design and instructed... [more] |
| the case events (report and design document preparation) |
before
Entity1 is before Entity2 |
the Discussion section's retrospective ethical analysis |
time:intervalBefore
http://www.w3.org/2006/time#intervalBefore |
The Discussion section retrospectively analyzes these events against NSPE Code provisions and prior ... [more] |
About Allen Relations & OWL-Time
Allen's Interval Algebra provides 13 basic temporal relations between intervals. These relations are mapped to OWL-Time standard properties for interoperability with Semantic Web temporal reasoning systems and SPARQL queries.
Each relation includes both a ProEthica custom property and a
time:* OWL-Time property for maximum compatibility.