38 entities 10 actions 8 events 10 causal chains 9 temporal relations
Timeline Overview
Action Event 18 sequenced markers
Thorough Report Review After receiving the AI-generated report draft, before submission
Cursory Design Document Review After receiving AI-generated design documents, before submission
Supervisor Retirement Before project deliverables were due, over a year into site observation
Client Data Exposure During AI-assisted drafting phase, before submission
AI Report Generation During drafting phase, before thorough review
AI Design Generation During drafting phase, before cursory review
Project Acceptance At project initiation, after Engineer B's retirement
AI Tool Adoption for Report During report preparation phase
Client Data Upload to AI During both report and design document preparation phases
Draft Report Sealing and Submission At report submission
AI Tool Adoption for Design During design document preparation phase
Design Document Submission At design document submission
Dual Deliverable Pressure Concurrent with project execution phase
Report Stylistic Inconsistency Upon Client W's review of submitted report
Design Defect Discovery Upon Client W's review of submitted design documents
Revision Instruction Issued After Client W's review of design documents
OWL-Time Temporal Structure 9 relations time: = w3.org/2006/time
Engineer A's site observation and data gathering time:intervalBefore project deliverables due date
Engineer B's retirement time:intervalBefore Engineer A's use of AI software for dual deliverables
Engineer B's mentorship and QA reviews time:intervalBefore Engineer B's retirement
AI generation of initial report draft time:intervalBefore Engineer A's thorough review and cross-checking of the report
AI generation of preliminary design documents time:intervalBefore Engineer A's cursory review of design documents
Engineer A's thorough review of the report time:intervalBefore submission of draft report to Client W
Engineer A's cursory review of design documents time:intervalBefore submission of design documents to Client W
submission of both deliverables to Client W time:intervalBefore Client W's review and identification of issues
Client W's identification of issues in design documents time:intervalBefore Client W's instruction to Engineer A to revise the plans
Extracted Actions (10)
Volitional professional decisions with intentions and ethical context

Description: Engineer A accepted the dual engagement from Client W to produce a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications, without securing alternative quality assurance support after Engineer B's retirement.

Temporal Marker: At project initiation, after Engineer B's retirement instant

Fluent Transitions:
Initiates (2)
  • Dual Deliverable Obligation
  • Reduced Quality Assurance Support State

Mental State: deliberate

Intended Outcome: Fulfill professional engagement and deliver required work products to Client W

Foreseen Unintended Effects:

  • Reduced quality assurance coverage due to absence of Engineer B
Obligation Engagement:
At stake (1)
  • Undertake Assignments Only When Qualified
Fulfills (1)
  • Perform Services Within Competence
Guided By Principles:
  • Professional Competency
  • Public Safety
Required Capabilities:
Environmental engineering expertise Technical report writing Engineering design and review Quality assurance oversight
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • fulfillsObligation: Perform Services Within Competence
  • guidedByPrinciple: Professional Competency; Public Safety
  • initiates: Dual Deliverable Obligation; Reduced Quality Assurance Support State
  • raisesObligation: Undertake Assignments Only When Qualified
Literal extractions (kept for synthesis)
  • description content: Engineer A accepted the dual engagement from Client W to produce a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications, without securing alternative quality assurance support after Engineer B's retirement.
  • hasAgent content: Engineer A
  • temporalMarker content: At project initiation, after Engineer B's retirement
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Fulfill professional engagement and deliver required work products to Client W
  • foreseenUnintendedEffects content: Reduced quality assurance coverage due to absence of Engineer B
  • temporalExtent content: instant
  • temporalSequence content: 2
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Environmental engineering expertise; Technical report writing; Engineering design and review; Quality assurance oversight
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Project_Acceptance",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A accepted the dual engagement from Client W to produce a comprehensive contaminant report and engineering design documents for groundwater infrastructure modifications, without securing alternative quality assurance support after Engineer B\u0027s retirement.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Reduced quality assurance coverage due to absence of Engineer B"
  ],
  "proeth:fulfillsObligation": [
    "Perform Services Within Competence"
  ],
  "proeth:guidedByPrinciple": [
    "Professional Competency",
    "Public Safety"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Dual Deliverable Obligation",
    "Reduced Quality Assurance Support State"
  ],
  "proeth:intendedOutcome": "Fulfill professional engagement and deliver required work products to Client W",
  "proeth:raisesObligation": [
    "Undertake Assignments Only When Qualified"
  ],
  "proeth:requiresCapability": [
    "Environmental engineering expertise",
    "Technical report writing",
    "Engineering design and review",
    "Quality assurance oversight"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "At project initiation, after Engineer B\u0027s retirement",
  "proeth:temporalSequence": 2,
  "proeth:violatesObligation": [],
  "proeth:withinCompetence": true,
  "rdfs:label": "Project Acceptance"
}

Description: Engineer A decided to use new, open-source AI language processing software to generate an initial draft of the contaminant report rather than drafting it independently or seeking an alternative expert reviewer.

Temporal Marker: During report preparation phase interval

Fluent Transitions:
Initiates (2)
  • AI-Assisted Report Drafting State
  • Client Confidential Data in Public Domain State

Mental State: deliberate

Intended Outcome: Compensate for reduced writing confidence and lack of mentorship by using AI to produce a workable first draft efficiently

Foreseen Unintended Effects:

  • Uncertainty about AI output accuracy and originality
  • Potential confidentiality exposure from uploading client data to open-source platform
Obligation Engagement:
At stake (2)
  • Client Confidentiality
  • Direction and Control Over Work Product
Fulfills (1)
  • Perform Services Within Competence
Guided By Principles:
  • Technological Innovation in Engineering Practice
  • Professional Competency
Required Capabilities:
Familiarity with AI tool capabilities and limitations Judgment to evaluate AI-generated technical content Environmental engineering domain expertise
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • fulfillsObligation: Perform Services Within Competence
  • guidedByPrinciple: Technological Innovation in Engineering Practice; Professional Competency
  • initiates: AI-Assisted Report Drafting State; Client Confidential Data in Public Domain State
  • raisesObligation: Client Confidentiality; Direction and Control Over Work Product
Literal extractions (kept for synthesis)
  • description content: Engineer A decided to use new, open-source AI language processing software to generate an initial draft of the contaminant report rather than drafting it independently or seeking an alternative expert reviewer.
  • hasAgent content: Engineer A
  • temporalMarker content: During report preparation phase
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Compensate for reduced writing confidence and lack of mentorship by using AI to produce a workable first draft efficiently
  • foreseenUnintendedEffects content: Uncertainty about AI output accuracy and originality; Potential confidentiality exposure from uploading client data to open-source platform
  • temporalExtent content: interval
  • temporalSequence content: 4
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Familiarity with AI tool capabilities and limitations; Judgment to evaluate AI-generated technical content; Environmental engineering domain expertise
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_AI_Tool_Adoption_for_Report",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A decided to use new, open-source AI language processing software to generate an initial draft of the contaminant report rather than drafting it independently or seeking an alternative expert reviewer.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Uncertainty about AI output accuracy and originality",
    "Potential confidentiality exposure from uploading client data to open-source platform"
  ],
  "proeth:fulfillsObligation": [
    "Perform Services Within Competence"
  ],
  "proeth:guidedByPrinciple": [
    "Technological Innovation in Engineering Practice",
    "Professional Competency"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "AI-Assisted Report Drafting State",
    "Client Confidential Data in Public Domain State"
  ],
  "proeth:intendedOutcome": "Compensate for reduced writing confidence and lack of mentorship by using AI to produce a workable first draft efficiently",
  "proeth:raisesObligation": [
    "Client Confidentiality",
    "Direction and Control Over Work Product"
  ],
  "proeth:requiresCapability": [
    "Familiarity with AI tool capabilities and limitations",
    "Judgment to evaluate AI-generated technical content",
    "Environmental engineering domain expertise"
  ],
  "proeth:temporalExtent": "interval",
  "proeth:temporalMarker": "During report preparation phase",
  "proeth:temporalSequence": 4,
  "proeth:violatesObligation": [],
  "proeth:withinCompetence": true,
  "rdfs:label": "AI Tool Adoption for Report"
}

Description: Engineer A entered Client W's private project information into the open-source AI software interface to generate report content and design documents, effectively placing confidential client data into a public-domain platform without obtaining Client W's prior consent.

Temporal Marker: During both report and design document preparation phases instant

Fluent Transitions:
Initiates (1)
  • Client Confidential Data in Public Domain State

Mental State: deliberate

Intended Outcome: Provide the AI software with sufficient project context to generate relevant and accurate draft content

Foreseen Unintended Effects:

  • Potential exposure of confidential client information to the public domain
Obligation Engagement:
Violates (1)
  • Client Confidentiality
Guided By Principles:
  • Respect for Client Privacy
  • Avoid Deceptive Acts
Required Capabilities:
Understanding of data privacy implications of open-source AI platforms Client confidentiality management
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • violatesObligation: Client Confidentiality
  • guidedByPrinciple: Respect for Client Privacy; Avoid Deceptive Acts
  • initiates: Client Confidential Data in Public Domain State
Literal extractions (kept for synthesis)
  • description content: Engineer A entered Client W's private project information into the open-source AI software interface to generate report content and design documents, effectively placing confidential client data into a public-domain platform without obtaining Client W's prior consent.
  • hasAgent content: Engineer A
  • temporalMarker content: During both report and design document preparation phases
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Provide the AI software with sufficient project context to generate relevant and accurate draft content
  • foreseenUnintendedEffects content: Potential exposure of confidential client information to the public domain
  • temporalExtent content: instant
  • temporalSequence content: 5
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Understanding of data privacy implications of open-source AI platforms; Client confidentiality management
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Client_Data_Upload_to_AI",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A entered Client W\u0027s private project information into the open-source AI software interface to generate report content and design documents, effectively placing confidential client data into a public-domain platform without obtaining Client W\u0027s prior consent.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Potential exposure of confidential client information to the public domain"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Respect for Client Privacy",
    "Avoid Deceptive Acts"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Client Confidential Data in Public Domain State"
  ],
  "proeth:intendedOutcome": "Provide the AI software with sufficient project context to generate relevant and accurate draft content",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Understanding of data privacy implications of open-source AI platforms",
    "Client confidentiality management"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "During both report and design document preparation phases",
  "proeth:temporalSequence": 5,
  "proeth:violatesObligation": [
    "Client Confidentiality"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "Client Data Upload to AI"
}

Description: Engineer A conducted a thorough review of the AI-generated report draft, cross-checking key facts against professional journal articles, verifying phrasing through search engine queries to check for copied language, and making minor wording adjustments to personalize the content.

Temporal Marker: After receiving the AI-generated report draft, before submission interval

Fluent Transitions:
Initiates (1)
  • Report Under Engineer Direction and Control State
Terminates (1)
  • Unverified AI Report Draft State

Mental State: deliberate

Intended Outcome: Ensure factual accuracy, originality, and professional quality of the report before submission to Client W

Foreseen Unintended Effects:

  • Review may not catch all deficiencies given unfamiliarity with AI output characteristics
Obligation Engagement:
Fulfills (2)
  • Direction and Control Over Work Product
  • Perform Services Within Competence
Guided By Principles:
  • Professional Competency
  • Public Safety
Required Capabilities:
Technical knowledge to fact-check environmental contaminant content Critical evaluation of AI-generated text Environmental engineering domain expertise
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • fulfillsObligation: Direction and Control Over Work Product; Perform Services Within Competence
  • guidedByPrinciple: Professional Competency; Public Safety
  • initiates: Report Under Engineer Direction and Control State
  • terminates: Unverified AI Report Draft State
Literal extractions (kept for synthesis)
  • description content: Engineer A conducted a thorough review of the AI-generated report draft, cross-checking key facts against professional journal articles, verifying phrasing through search engine queries to check for copied language, and making minor wording adjustments to personalize the content.
  • hasAgent content: Engineer A
  • temporalMarker content: After receiving the AI-generated report draft, before submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Ensure factual accuracy, originality, and professional quality of the report before submission to Client W
  • foreseenUnintendedEffects content: Review may not catch all deficiencies given unfamiliarity with AI output characteristics
  • temporalExtent content: interval
  • temporalSequence content: 8
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Technical knowledge to fact-check environmental contaminant content; Critical evaluation of AI-generated text; Environmental engineering domain expertise
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Thorough_Report_Review",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A conducted a thorough review of the AI-generated report draft, cross-checking key facts against professional journal articles, verifying phrasing through search engine queries to check for copied language, and making minor wording adjustments to personalize the content.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Review may not catch all deficiencies given unfamiliarity with AI output characteristics"
  ],
  "proeth:fulfillsObligation": [
    "Direction and Control Over Work Product",
    "Perform Services Within Competence"
  ],
  "proeth:guidedByPrinciple": [
    "Professional Competency",
    "Public Safety"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Report Under Engineer Direction and Control State"
  ],
  "proeth:intendedOutcome": "Ensure factual accuracy, originality, and professional quality of the report before submission to Client W",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Technical knowledge to fact-check environmental contaminant content",
    "Critical evaluation of AI-generated text",
    "Environmental engineering domain expertise"
  ],
  "proeth:temporalExtent": "interval",
  "proeth:temporalMarker": "After receiving the AI-generated report draft, before submission",
  "proeth:temporalSequence": 8,
  "proeth:terminates": [
    "Unverified AI Report Draft State"
  ],
  "proeth:violatesObligation": [],
  "proeth:withinCompetence": true,
  "rdfs:label": "Thorough Report Review"
}

Description: Engineer A chose not to disclose the use of AI language processing software or cite its contributions when submitting the draft report to Client W, and did not include citations to the AI-generated content or the large language models used.

Temporal Marker: At report submission instant

Fluent Transitions:
Initiates (1)
  • Undisclosed AI Contribution to Report State

Mental State: deliberate

Intended Outcome: Submit the report as a professional work product without drawing attention to AI involvement, consistent with then-current absence of universal mandatory disclosure guidelines

Foreseen Unintended Effects:

  • Potential client misunderstanding about authorship
  • Failure to give credit to AI contributions as required by attribution norms
Obligation Engagement:
Violates (2)
  • Credit and Attribution for Engineering Work
  • Avoid Deceptive Acts
Guided By Principles:
  • Transparency and Attribution
  • Professional Integrity
Required Capabilities:
Awareness of professional attribution norms Judgment about disclosure obligations for AI-assisted work
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • violatesObligation: Credit and Attribution for Engineering Work; Avoid Deceptive Acts
  • guidedByPrinciple: Transparency and Attribution; Professional Integrity
  • initiates: Undisclosed AI Contribution to Report State
Literal extractions (kept for synthesis)
  • description content: Engineer A chose not to disclose the use of AI language processing software or cite its contributions when submitting the draft report to Client W, and did not include citations to the AI-generated content or the large language models used.
  • hasAgent content: Engineer A
  • temporalMarker content: At report submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Submit the report as a professional work product without drawing attention to AI involvement, consistent with then-current absence of universal mandatory disclosure guidelines
  • foreseenUnintendedEffects content: Potential client misunderstanding about authorship; Failure to give credit to AI contributions as required by attribution norms
  • temporalExtent content: instant
  • temporalSequence content: 9
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Awareness of professional attribution norms; Judgment about disclosure obligations for AI-assisted work
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_AI_Disclosure_Omission_for_Report",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A chose not to disclose the use of AI language processing software or cite its contributions when submitting the draft report to Client W, and did not include citations to the AI-generated content or the large language models used.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Potential client misunderstanding about authorship",
    "Failure to give credit to AI contributions as required by attribution norms"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Transparency and Attribution",
    "Professional Integrity"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Undisclosed AI Contribution to Report State"
  ],
  "proeth:intendedOutcome": "Submit the report as a professional work product without drawing attention to AI involvement, consistent with then-current absence of universal mandatory disclosure guidelines",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Awareness of professional attribution norms",
    "Judgment about disclosure obligations for AI-assisted work"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "At report submission",
  "proeth:temporalSequence": 9,
  "proeth:violatesObligation": [
    "Credit and Attribution for Engineering Work",
    "Avoid Deceptive Acts"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "AI Disclosure Omission for Report"
}

Description: Engineer A applied their professional seal to the draft report consistent with state law and submitted it to Client W with language clearly identifying it as a draft.

Temporal Marker: At report submission instant

Fluent Transitions:
Initiates (1)
  • Sealed Draft Report Submitted State
Terminates (1)
  • Dual Deliverable Obligation for Report

Mental State: deliberate

Intended Outcome: Fulfill the contractual deliverable and assert professional responsibility over the report content in accordance with state licensure requirements

Foreseen Unintended Effects:

  • Sealing a document with undisclosed AI contributions and without full citation of technical authority sources
Obligation Engagement:
Fulfills (2)
  • Direction and Control Over Work Product
  • Perform Services Within Competence
Violates (1)
  • Credit and Attribution for Engineering Work
Guided By Principles:
  • Professional Competency
  • Responsible Charge
Required Capabilities:
Environmental engineering expertise sufficient to take responsible charge of the report Understanding of sealing obligations under state law
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • fulfillsObligation: Direction and Control Over Work Product; Perform Services Within Competence
  • violatesObligation: Credit and Attribution for Engineering Work
  • guidedByPrinciple: Professional Competency; Responsible Charge
  • initiates: Sealed Draft Report Submitted State
  • terminates: Dual Deliverable Obligation for Report
Literal extractions (kept for synthesis)
  • description content: Engineer A applied their professional seal to the draft report consistent with state law and submitted it to Client W with language clearly identifying it as a draft.
  • hasAgent content: Engineer A
  • temporalMarker content: At report submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Fulfill the contractual deliverable and assert professional responsibility over the report content in accordance with state licensure requirements
  • foreseenUnintendedEffects content: Sealing a document with undisclosed AI contributions and without full citation of technical authority sources
  • temporalExtent content: instant
  • temporalSequence content: 10
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Environmental engineering expertise sufficient to take responsible charge of the report; Understanding of sealing obligations under state law
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Draft_Report_Sealing_and_Submission",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A applied their professional seal to the draft report consistent with state law and submitted it to Client W with language clearly identifying it as a draft.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Sealing a document with undisclosed AI contributions and without full citation of technical authority sources"
  ],
  "proeth:fulfillsObligation": [
    "Direction and Control Over Work Product",
    "Perform Services Within Competence"
  ],
  "proeth:guidedByPrinciple": [
    "Professional Competency",
    "Responsible Charge"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Sealed Draft Report Submitted State"
  ],
  "proeth:intendedOutcome": "Fulfill the contractual deliverable and assert professional responsibility over the report content in accordance with state licensure requirements",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Environmental engineering expertise sufficient to take responsible charge of the report",
    "Understanding of sealing obligations under state law"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "At report submission",
  "proeth:temporalSequence": 10,
  "proeth:terminates": [
    "Dual Deliverable Obligation for Report"
  ],
  "proeth:violatesObligation": [
    "Credit and Attribution for Engineering Work"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "Draft Report Sealing and Submission"
}

Description: Engineer A decided to use AI-assisted drafting tools, which were new to the market and with which Engineer A had no prior experience, to generate preliminary engineering design documents including basic layouts and technical specifications for the groundwater infrastructure modifications.

Temporal Marker: During design document preparation phase interval

Fluent Transitions:
Initiates (2)
  • AI-Assisted Design Document Drafting State
  • Client Confidential Data in Public Domain State

Mental State: deliberate

Intended Outcome: Efficiently generate preliminary design documents to meet project deliverable requirements without the benefit of Engineer B's oversight

Foreseen Unintended Effects:

  • Risk of errors in AI-generated designs given Engineer A's unfamiliarity with the tool and absence of comprehensive review process
Obligation Engagement:
At stake (3)
  • Direction and Control Over Work Product
  • Responsible Charge
  • Hold Paramount the Safety, Health, and Welfare of the Public
Guided By Principles:
  • Technological Innovation in Engineering Practice
  • Professional Competency
Required Capabilities:
Proficiency with AI drafting tool capabilities and limitations Engineering design expertise for groundwater infrastructure Regulatory knowledge for local safety requirements
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • guidedByPrinciple: Technological Innovation in Engineering Practice; Professional Competency
  • initiates: AI-Assisted Design Document Drafting State; Client Confidential Data in Public Domain State
  • raisesObligation: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public
Literal extractions (kept for synthesis)
  • description content: Engineer A decided to use AI-assisted drafting tools, which were new to the market and with which Engineer A had no prior experience, to generate preliminary engineering design documents including basic layouts and technical specifications for the groundwater infrastructure modifications.
  • hasAgent content: Engineer A
  • temporalMarker content: During design document preparation phase
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Efficiently generate preliminary design documents to meet project deliverable requirements without the benefit of Engineer B's oversight
  • foreseenUnintendedEffects content: Risk of errors in AI-generated designs given Engineer A's unfamiliarity with the tool and absence of comprehensive review process
  • temporalExtent content: interval
  • temporalSequence content: 12
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Proficiency with AI drafting tool capabilities and limitations; Engineering design expertise for groundwater infrastructure; Regulatory knowledge for local safety requirements
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_AI_Tool_Adoption_for_Design",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A decided to use AI-assisted drafting tools, which were new to the market and with which Engineer A had no prior experience, to generate preliminary engineering design documents including basic layouts and technical specifications for the groundwater infrastructure modifications.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Risk of errors in AI-generated designs given Engineer A\u0027s unfamiliarity with the tool and absence of comprehensive review process"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Technological Innovation in Engineering Practice",
    "Professional Competency"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "AI-Assisted Design Document Drafting State",
    "Client Confidential Data in Public Domain State"
  ],
  "proeth:intendedOutcome": "Efficiently generate preliminary design documents to meet project deliverable requirements without the benefit of Engineer B\u0027s oversight",
  "proeth:raisesObligation": [
    "Direction and Control Over Work Product",
    "Responsible Charge",
    "Hold Paramount the Safety, Health, and Welfare of the Public"
  ],
  "proeth:requiresCapability": [
    "Proficiency with AI drafting tool capabilities and limitations",
    "Engineering design expertise for groundwater infrastructure",
    "Regulatory knowledge for local safety requirements"
  ],
  "proeth:temporalExtent": "interval",
  "proeth:temporalMarker": "During design document preparation phase",
  "proeth:temporalSequence": 12,
  "proeth:violatesObligation": [],
  "proeth:withinCompetence": true,
  "rdfs:label": "AI Tool Adoption for Design"
}

Description: Engineer A performed only a cursory review of the AI-generated engineering design documents, adjusting certain elements to align with site-specific conditions but not conducting a comprehensive verification of dimensions, safety features, or regulatory compliance.

Temporal Marker: After receiving AI-generated design documents, before submission interval

Fluent Transitions:
Initiates (3)
  • Public Safety Risk State
  • Regulatory Noncompliance Risk State
  • Insufficient Oversight of Design Documents State

Mental State: deliberate

Intended Outcome: Adapt the AI-generated plans to the site context and prepare them for submission without expending the full review effort applied to the report

Foreseen Unintended Effects:

  • Undetected errors in dimensions and omission of safety features required by local regulations
Obligation Engagement:
Violates (4)
  • Direction and Control Over Work Product
  • Responsible Charge
  • Hold Paramount the Safety, Health, and Welfare of the Public
  • Undertake Assignments Only When Qualified
Guided By Principles:
  • Professional Competency
  • Public Safety
  • Responsible Charge
Required Capabilities:
Comprehensive engineering design review Regulatory compliance verification Dimensional accuracy checking Safety feature validation for groundwater infrastructure
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • violatesObligation: Direction and Control Over Work Product; Responsible Charge; Hold Paramount the Safety, Health, and Welfare of the Public; Undertake Assignments Only When Qualified
  • guidedByPrinciple: Professional Competency; Public Safety; Responsible Charge
  • initiates: Public Safety Risk State; Regulatory Noncompliance Risk State; Insufficient Oversight of Design Documents State
Literal extractions (kept for synthesis)
  • description content: Engineer A performed only a cursory review of the AI-generated engineering design documents, adjusting certain elements to align with site-specific conditions but not conducting a comprehensive verification of dimensions, safety features, or regulatory compliance.
  • hasAgent content: Engineer A
  • temporalMarker content: After receiving AI-generated design documents, before submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Adapt the AI-generated plans to the site context and prepare them for submission without expending the full review effort applied to the report
  • foreseenUnintendedEffects content: Undetected errors in dimensions and omission of safety features required by local regulations
  • temporalExtent content: interval
  • temporalSequence content: 14
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Comprehensive engineering design review; Regulatory compliance verification; Dimensional accuracy checking; Safety feature validation for groundwater infrastructure
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Cursory_Design_Document_Review",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A performed only a cursory review of the AI-generated engineering design documents, adjusting certain elements to align with site-specific conditions but not conducting a comprehensive verification of dimensions, safety features, or regulatory compliance.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Undetected errors in dimensions and omission of safety features required by local regulations"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Professional Competency",
    "Public Safety",
    "Responsible Charge"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Public Safety Risk State",
    "Regulatory Noncompliance Risk State",
    "Insufficient Oversight of Design Documents State"
  ],
  "proeth:intendedOutcome": "Adapt the AI-generated plans to the site context and prepare them for submission without expending the full review effort applied to the report",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Comprehensive engineering design review",
    "Regulatory compliance verification",
    "Dimensional accuracy checking",
    "Safety feature validation for groundwater infrastructure"
  ],
  "proeth:temporalExtent": "interval",
  "proeth:temporalMarker": "After receiving AI-generated design documents, before submission",
  "proeth:temporalSequence": 14,
  "proeth:violatesObligation": [
    "Direction and Control Over Work Product",
    "Responsible Charge",
    "Hold Paramount the Safety, Health, and Welfare of the Public",
    "Undertake Assignments Only When Qualified"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "Cursory Design Document Review"
}

Description: Engineer A chose not to disclose the use of AI-assisted drafting tools when submitting the engineering design documents to Client W, providing no indication that the plans and specifications were substantially generated by AI software.

Temporal Marker: At design document submission instant

Fluent Transitions:
Initiates (1)
  • Undisclosed AI Contribution to Design Documents State

Mental State: deliberate

Intended Outcome: Submit the design documents as a professional work product without separately identifying AI as a contributing tool

Foreseen Unintended Effects:

  • Client W unaware of AI involvement and therefore unable to apply appropriate scrutiny or make informed decisions about the reliability of the designs
Obligation Engagement:
Violates (2)
  • Credit and Attribution for Engineering Work
  • Avoid Deceptive Acts
Guided By Principles:
  • Transparency and Attribution
  • Professional Integrity
Required Capabilities:
Awareness of professional attribution norms for AI-assisted design work Judgment about transparency obligations to clients
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • violatesObligation: Credit and Attribution for Engineering Work; Avoid Deceptive Acts
  • guidedByPrinciple: Transparency and Attribution; Professional Integrity
  • initiates: Undisclosed AI Contribution to Design Documents State
Literal extractions (kept for synthesis)
  • description content: Engineer A chose not to disclose the use of AI-assisted drafting tools when submitting the engineering design documents to Client W, providing no indication that the plans and specifications were substantially generated by AI software.
  • hasAgent content: Engineer A
  • temporalMarker content: At design document submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Submit the design documents as a professional work product without separately identifying AI as a contributing tool
  • foreseenUnintendedEffects content: Client W unaware of AI involvement and therefore unable to apply appropriate scrutiny or make informed decisions about the reliability of the designs
  • temporalExtent content: instant
  • temporalSequence content: 15
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Awareness of professional attribution norms for AI-assisted design work; Judgment about transparency obligations to clients
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_AI_Disclosure_Omission_for_Design",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A chose not to disclose the use of AI-assisted drafting tools when submitting the engineering design documents to Client W, providing no indication that the plans and specifications were substantially generated by AI software.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Client W unaware of AI involvement and therefore unable to apply appropriate scrutiny or make informed decisions about the reliability of the designs"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Transparency and Attribution",
    "Professional Integrity"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Undisclosed AI Contribution to Design Documents State"
  ],
  "proeth:intendedOutcome": "Submit the design documents as a professional work product without separately identifying AI as a contributing tool",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Awareness of professional attribution norms for AI-assisted design work",
    "Judgment about transparency obligations to clients"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "At design document submission",
  "proeth:temporalSequence": 15,
  "proeth:violatesObligation": [
    "Credit and Attribution for Engineering Work",
    "Avoid Deceptive Acts"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "AI Disclosure Omission for Design"
}

Description: Engineer A submitted the AI-generated engineering design documents to Client W without comprehensive review, without disclosure of AI use, and without verifying that all elements satisfied applicable professional and regulatory standards, including local safety feature requirements.

Temporal Marker: At design document submission instant

Fluent Transitions:
Initiates (3)
  • Deficient Design Documents Submitted State
  • Public Safety Risk State
  • Regulatory Noncompliance Risk State
Terminates (1)
  • Dual Deliverable Obligation for Design Documents

Mental State: deliberate

Intended Outcome: Fulfill the contractual deliverable for engineering design documents and advance the project for Client W's review

Foreseen Unintended Effects:

  • Risk that undetected errors could cause regulatory noncompliance or safety hazards if the documents were acted upon
Obligation Engagement:
Violates (4)
  • Hold Paramount the Safety, Health, and Welfare of the Public
  • Direction and Control Over Work Product
  • Responsible Charge
  • Undertake Assignments Only When Qualified
Guided By Principles:
  • Public Safety
  • Responsible Charge
  • Professional Competency
Required Capabilities:
Comprehensive design review and verification Regulatory compliance assurance Responsible charge over engineering plans and specifications
Within Competence: Yes
Field classification (triples vs literals)
Relations (structural triples)
  • violatesObligation: Hold Paramount the Safety, Health, and Welfare of the Public; Direction and Control Over Work Product; Responsible Charge; Undertake Assignments Only When Qualified
  • guidedByPrinciple: Public Safety; Responsible Charge; Professional Competency
  • initiates: Deficient Design Documents Submitted State; Public Safety Risk State; Regulatory Noncompliance Risk State
  • terminates: Dual Deliverable Obligation for Design Documents
Literal extractions (kept for synthesis)
  • description content: Engineer A submitted the AI-generated engineering design documents to Client W without comprehensive review, without disclosure of AI use, and without verifying that all elements satisfied applicable professional and regulatory standards, including local safety feature requirements.
  • hasAgent content: Engineer A
  • temporalMarker content: At design document submission
  • eventRoleContext content: Licensed Environmental Engineer
  • hasMentalState content: deliberate
  • intendedOutcome content: Fulfill the contractual deliverable for engineering design documents and advance the project for Client W's review
  • foreseenUnintendedEffects content: Risk that undetected errors could cause regulatory noncompliance or safety hazards if the documents were acted upon
  • temporalExtent content: instant
  • temporalSequence content: 16
  • withinCompetence assessment: True
Derived (reconstructable from the graph)
  • requiresCapability: Comprehensive design review and verification; Regulatory compliance assurance; Responsible charge over engineering plans and specifications
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Action_Design_Document_Submission",
  "@type": "proeth:Action",
  "proeth:description": "Engineer A submitted the AI-generated engineering design documents to Client W without comprehensive review, without disclosure of AI use, and without verifying that all elements satisfied applicable professional and regulatory standards, including local safety feature requirements.",
  "proeth:eventRoleContext": "Licensed Environmental Engineer",
  "proeth:foreseenUnintendedEffects": [
    "Risk that undetected errors could cause regulatory noncompliance or safety hazards if the documents were acted upon"
  ],
  "proeth:fulfillsObligation": [],
  "proeth:guidedByPrinciple": [
    "Public Safety",
    "Responsible Charge",
    "Professional Competency"
  ],
  "proeth:hasAgent": "Engineer A",
  "proeth:hasMentalState": "deliberate",
  "proeth:initiates": [
    "Deficient Design Documents Submitted State",
    "Public Safety Risk State",
    "Regulatory Noncompliance Risk State"
  ],
  "proeth:intendedOutcome": "Fulfill the contractual deliverable for engineering design documents and advance the project for Client W\u0027s review",
  "proeth:raisesObligation": [],
  "proeth:requiresCapability": [
    "Comprehensive design review and verification",
    "Regulatory compliance assurance",
    "Responsible charge over engineering plans and specifications"
  ],
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "At design document submission",
  "proeth:temporalSequence": 16,
  "proeth:terminates": [
    "Dual Deliverable Obligation for Design Documents"
  ],
  "proeth:violatesObligation": [
    "Hold Paramount the Safety, Health, and Welfare of the Public",
    "Direction and Control Over Work Product",
    "Responsible Charge",
    "Undertake Assignments Only When Qualified"
  ],
  "proeth:withinCompetence": true,
  "rdfs:label": "Design Document Submission"
}
Extracted Events (8)
Occurrences that trigger ethical considerations and state changes

Description: Engineer B, Engineer A's mentor and supervisor, retired before project deliverables were due, removing the primary quality assurance resource from the project.

Temporal Marker: Before project deliverables were due, over a year into site observation instant

Fluent Transitions:
Initiates (2)
  • Reduced QA Support
  • Unsupervised Practice State
Terminates (2)
  • Active Supervision State
  • QA Resource Available State

Causes State Change: Engineer A lost access to supervisory oversight and quality assurance support, leaving the project without a senior review resource.

Field classification (triples vs literals)
Relations (structural triples)
  • initiates: Reduced QA Support; Unsupervised Practice State
  • terminates: Active Supervision State; QA Resource Available State
Literal extractions (kept for synthesis)
  • description content: Engineer B, Engineer A's mentor and supervisor, retired before project deliverables were due, removing the primary quality assurance resource from the project.
  • temporalMarker content: Before project deliverables were due, over a year into site observation
  • eventType content: exogenous
  • causesStateChange content: Engineer A lost access to supervisory oversight and quality assurance support, leaving the project without a senior review resource.
  • temporalExtent content: instant
  • temporalSequence content: 1
  • severity assessment: high
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Supervisor_Retirement",
  "@type": "proeth:Event",
  "proeth:causesStateChange": "Engineer A lost access to supervisory oversight and quality assurance support, leaving the project without a senior review resource.",
  "proeth:description": "Engineer B, Engineer A\u0027s mentor and supervisor, retired before project deliverables were due, removing the primary quality assurance resource from the project.",
  "proeth:eventType": "exogenous",
  "proeth:initiates": [
    "Reduced QA Support",
    "Unsupervised Practice State"
  ],
  "proeth:severity": "high",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "Before project deliverables were due, over a year into site observation",
  "proeth:temporalSequence": 1,
  "proeth:terminates": [
    "Active Supervision State",
    "QA Resource Available State"
  ],
  "rdfs:label": "Supervisor Retirement"
}

Description: Engineer A faced concurrent deadlines for both the comprehensive contaminant report and the groundwater infrastructure design documents, creating compounded workload pressure.

Temporal Marker: Concurrent with project execution phase interval

Fluent Transitions:
Initiates (2)
  • Elevated Workload State
  • Resource Deficit State

Causes State Change: Engineer A operated under elevated workload conditions with two simultaneous major deliverables and no supervisory backup.

Caused By Action: Action_Project_Acceptance

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_Project_Acceptance
  • initiates: Elevated Workload State; Resource Deficit State
Literal extractions (kept for synthesis)
  • description content: Engineer A faced concurrent deadlines for both the comprehensive contaminant report and the groundwater infrastructure design documents, creating compounded workload pressure.
  • temporalMarker content: Concurrent with project execution phase
  • eventType content: automatic_trigger
  • causesStateChange content: Engineer A operated under elevated workload conditions with two simultaneous major deliverables and no supervisory backup.
  • temporalExtent content: interval
  • temporalSequence content: 3
  • severity assessment: medium
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Dual_Deliverable_Pressure",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_Project_Acceptance",
  "proeth:causesStateChange": "Engineer A operated under elevated workload conditions with two simultaneous major deliverables and no supervisory backup.",
  "proeth:description": "Engineer A faced concurrent deadlines for both the comprehensive contaminant report and the groundwater infrastructure design documents, creating compounded workload pressure.",
  "proeth:eventType": "automatic_trigger",
  "proeth:initiates": [
    "Elevated Workload State",
    "Resource Deficit State"
  ],
  "proeth:severity": "medium",
  "proeth:temporalExtent": "interval",
  "proeth:temporalMarker": "Concurrent with project execution phase",
  "proeth:temporalSequence": 3,
  "rdfs:label": "Dual Deliverable Pressure"
}

Description: When Engineer A uploaded client monitoring data and site information to the open-source AI software, that proprietary client data was transmitted to and processed by a third-party system outside Engineer A's control.

Temporal Marker: During AI-assisted drafting phase, before submission instant

Fluent Transitions:
Initiates (2)
  • Confidentiality Risk State
  • Third-Party Data Exposure State
Terminates (1)
  • Client Data Confidentiality State

Causes State Change: Client W's confidential site data entered a third-party AI system, creating a potential confidentiality breach outside Engineer A's control.

Caused By Action: Action_Client_Data_Upload_to_AI

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_Client_Data_Upload_to_AI
  • initiates: Confidentiality Risk State; Third-Party Data Exposure State
  • terminates: Client Data Confidentiality State
Literal extractions (kept for synthesis)
  • description content: When Engineer A uploaded client monitoring data and site information to the open-source AI software, that proprietary client data was transmitted to and processed by a third-party system outside Engineer A's control.
  • temporalMarker content: During AI-assisted drafting phase, before submission
  • eventType content: outcome
  • causesStateChange content: Client W's confidential site data entered a third-party AI system, creating a potential confidentiality breach outside Engineer A's control.
  • temporalExtent content: instant
  • temporalSequence content: 6
  • severity assessment: high
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Client_Data_Exposure",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_Client_Data_Upload_to_AI",
  "proeth:causesStateChange": "Client W\u0027s confidential site data entered a third-party AI system, creating a potential confidentiality breach outside Engineer A\u0027s control.",
  "proeth:description": "When Engineer A uploaded client monitoring data and site information to the open-source AI software, that proprietary client data was transmitted to and processed by a third-party system outside Engineer A\u0027s control.",
  "proeth:eventType": "outcome",
  "proeth:initiates": [
    "Confidentiality Risk State",
    "Third-Party Data Exposure State"
  ],
  "proeth:severity": "high",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "During AI-assisted drafting phase, before submission",
  "proeth:temporalSequence": 6,
  "proeth:terminates": [
    "Client Data Confidentiality State"
  ],
  "rdfs:label": "Client Data Exposure"
}

Description: The open-source AI software produced a draft of the comprehensive contaminant report based on the data and inputs provided by Engineer A.

Temporal Marker: During drafting phase, before thorough review instant

Fluent Transitions:
Initiates (2)
  • AI-Drafted Report Exists
  • Unverified Content State

Causes State Change: A machine-generated draft report existed and was available for Engineer A's review.

Caused By Action: Action_AI_Tool_Adoption_for_Report

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Report
  • initiates: AI-Drafted Report Exists; Unverified Content State
Literal extractions (kept for synthesis)
  • description content: The open-source AI software produced a draft of the comprehensive contaminant report based on the data and inputs provided by Engineer A.
  • temporalMarker content: During drafting phase, before thorough review
  • eventType content: automatic_trigger
  • causesStateChange content: A machine-generated draft report existed and was available for Engineer A's review.
  • temporalExtent content: instant
  • temporalSequence content: 7
  • severity assessment: low
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_AI_Report_Generation",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Report",
  "proeth:causesStateChange": "A machine-generated draft report existed and was available for Engineer A\u0027s review.",
  "proeth:description": "The open-source AI software produced a draft of the comprehensive contaminant report based on the data and inputs provided by Engineer A.",
  "proeth:eventType": "automatic_trigger",
  "proeth:initiates": [
    "AI-Drafted Report Exists",
    "Unverified Content State"
  ],
  "proeth:severity": "low",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "During drafting phase, before thorough review",
  "proeth:temporalSequence": 7,
  "rdfs:label": "AI Report Generation"
}

Description: The submitted report exhibited a stylistic inconsistency noted by Client W, who observed that the document read as if written by two different authors, likely reflecting the blending of AI-generated and human-reviewed content.

Temporal Marker: Upon Client W's review of submitted report instant

Fluent Transitions:
Initiates (2)
  • Client Concern State
  • Authorship Attribution Question State

Causes State Change: Client W identified a quality concern in the report, signaling that the document's authorship was inconsistent even if factually adequate.

Caused By Action: Action_Thorough_Report_Review

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_Thorough_Report_Review
  • initiates: Client Concern State; Authorship Attribution Question State
Literal extractions (kept for synthesis)
  • description content: The submitted report exhibited a stylistic inconsistency noted by Client W, who observed that the document read as if written by two different authors, likely reflecting the blending of AI-generated and human-reviewed content.
  • temporalMarker content: Upon Client W's review of submitted report
  • eventType content: outcome
  • causesStateChange content: Client W identified a quality concern in the report, signaling that the document's authorship was inconsistent even if factually adequate.
  • temporalExtent content: instant
  • temporalSequence content: 11
  • severity assessment: low
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Report_Stylistic_Inconsistency",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_Thorough_Report_Review",
  "proeth:causesStateChange": "Client W identified a quality concern in the report, signaling that the document\u0027s authorship was inconsistent even if factually adequate.",
  "proeth:description": "The submitted report exhibited a stylistic inconsistency noted by Client W, who observed that the document read as if written by two different authors, likely reflecting the blending of AI-generated and human-reviewed content.",
  "proeth:eventType": "outcome",
  "proeth:initiates": [
    "Client Concern State",
    "Authorship Attribution Question State"
  ],
  "proeth:severity": "low",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "Upon Client W\u0027s review of submitted report",
  "proeth:temporalSequence": 11,
  "rdfs:label": "Report Stylistic Inconsistency"
}

Description: The open-source AI software produced draft groundwater infrastructure design documents, including dimensions and safety feature specifications, based on inputs provided by Engineer A.

Temporal Marker: During drafting phase, before cursory review instant

Fluent Transitions:
Initiates (2)
  • AI-Drafted Design Exists
  • Unverified Design Content State

Causes State Change: A machine-generated draft of the design documents existed and was available for Engineer A's review, containing unverified technical specifications.

Caused By Action: Action_AI_Tool_Adoption_for_Design

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Design
  • initiates: AI-Drafted Design Exists; Unverified Design Content State
Literal extractions (kept for synthesis)
  • description content: The open-source AI software produced draft groundwater infrastructure design documents, including dimensions and safety feature specifications, based on inputs provided by Engineer A.
  • temporalMarker content: During drafting phase, before cursory review
  • eventType content: automatic_trigger
  • causesStateChange content: A machine-generated draft of the design documents existed and was available for Engineer A's review, containing unverified technical specifications.
  • temporalExtent content: instant
  • temporalSequence content: 13
  • severity assessment: high
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_AI_Design_Generation",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_AI_Tool_Adoption_for_Design",
  "proeth:causesStateChange": "A machine-generated draft of the design documents existed and was available for Engineer A\u0027s review, containing unverified technical specifications.",
  "proeth:description": "The open-source AI software produced draft groundwater infrastructure design documents, including dimensions and safety feature specifications, based on inputs provided by Engineer A.",
  "proeth:eventType": "automatic_trigger",
  "proeth:initiates": [
    "AI-Drafted Design Exists",
    "Unverified Design Content State"
  ],
  "proeth:severity": "high",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "During drafting phase, before cursory review",
  "proeth:temporalSequence": 13,
  "rdfs:label": "AI Design Generation"
}

Description: Client W's review of the submitted design documents revealed misaligned dimensions and omitted safety features required by local regulations, constituting a failure of the design deliverable to meet regulatory and professional standards.

Temporal Marker: Upon Client W's review of submitted design documents instant

Fluent Transitions:
Initiates (4)
  • Public Safety Risk
  • Regulatory Non-Compliance State
  • Design Revision Required State
  • Client Confidence Impaired State
Terminates (2)
  • Design Adequacy State
  • Regulatory Compliance State

Causes State Change: The design documents were identified as non-compliant and technically deficient, creating a public safety risk and triggering a revision requirement.

Caused By Action: Action_Cursory_Design_Document_Review

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_Cursory_Design_Document_Review
  • initiates: Public Safety Risk; Regulatory Non-Compliance State; Design Revision Required State; Client Confidence Impaired State
  • terminates: Design Adequacy State; Regulatory Compliance State
Literal extractions (kept for synthesis)
  • description content: Client W's review of the submitted design documents revealed misaligned dimensions and omitted safety features required by local regulations, constituting a failure of the design deliverable to meet regulatory and professional standards.
  • temporalMarker content: Upon Client W's review of submitted design documents
  • eventType content: outcome
  • causesStateChange content: The design documents were identified as non-compliant and technically deficient, creating a public safety risk and triggering a revision requirement.
  • temporalExtent content: instant
  • temporalSequence content: 17
  • severity assessment: critical
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Design_Defect_Discovery",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_Cursory_Design_Document_Review",
  "proeth:causesStateChange": "The design documents were identified as non-compliant and technically deficient, creating a public safety risk and triggering a revision requirement.",
  "proeth:description": "Client W\u0027s review of the submitted design documents revealed misaligned dimensions and omitted safety features required by local regulations, constituting a failure of the design deliverable to meet regulatory and professional standards.",
  "proeth:eventType": "outcome",
  "proeth:initiates": [
    "Public Safety Risk",
    "Regulatory Non-Compliance State",
    "Design Revision Required State",
    "Client Confidence Impaired State"
  ],
  "proeth:severity": "critical",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "Upon Client W\u0027s review of submitted design documents",
  "proeth:temporalSequence": 17,
  "proeth:terminates": [
    "Design Adequacy State",
    "Regulatory Compliance State"
  ],
  "rdfs:label": "Design Defect Discovery"
}

Description: Client W raised concerns about the defective design documents and formally instructed Engineer A to revise the plans to correct the identified deficiencies.

Temporal Marker: After Client W's review of design documents instant

Fluent Transitions:
Initiates (2)
  • Design Revision Required State
  • Project Remediation Phase State
Terminates (1)
  • Design Submission Complete State

Causes State Change: Engineer A became obligated to revise the design documents, and the project moved into a remediation phase rather than proceeding to implementation.

Caused By Action: Action_Design_Document_Submission

Field classification (triples vs literals)
Relations (structural triples)
  • causedByAction: http://proethica.org/cases/7#Action_Design_Document_Submission
  • initiates: Design Revision Required State; Project Remediation Phase State
  • terminates: Design Submission Complete State
Literal extractions (kept for synthesis)
  • description content: Client W raised concerns about the defective design documents and formally instructed Engineer A to revise the plans to correct the identified deficiencies.
  • temporalMarker content: After Client W's review of design documents
  • eventType content: outcome
  • causesStateChange content: Engineer A became obligated to revise the design documents, and the project moved into a remediation phase rather than proceeding to implementation.
  • temporalExtent content: instant
  • temporalSequence content: 18
  • severity assessment: high
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#Event_Revision_Instruction_Issued",
  "@type": "proeth:Event",
  "proeth:causedByAction": "http://proethica.org/cases/7#Action_Design_Document_Submission",
  "proeth:causesStateChange": "Engineer A became obligated to revise the design documents, and the project moved into a remediation phase rather than proceeding to implementation.",
  "proeth:description": "Client W raised concerns about the defective design documents and formally instructed Engineer A to revise the plans to correct the identified deficiencies.",
  "proeth:eventType": "outcome",
  "proeth:initiates": [
    "Design Revision Required State",
    "Project Remediation Phase State"
  ],
  "proeth:severity": "high",
  "proeth:temporalExtent": "instant",
  "proeth:temporalMarker": "After Client W\u0027s review of design documents",
  "proeth:temporalSequence": 18,
  "proeth:terminates": [
    "Design Submission Complete State"
  ],
  "rdfs:label": "Revision Instruction Issued"
}
Causal Chains (10)
NESS test analysis: Necessary Element of Sufficient Set

Causal Language: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.

Necessary Factors (NESS):
  • AI-generated polished introduction section
  • Engineer A's own writing style in the data analysis section
  • Juxtaposition of the two within one report
Sufficient Factors:
  • Combination of AI-generated polished prose alongside human-drafted content produced a noticeable stylistic mismatch
Counterfactual Test: Had the entire report been written in a uniform voice (or fully harmonized by Engineer A), the inconsistency would not have been observed
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. AI Report Generation
    AI produces a highly polished introduction section
  2. Thorough Report Review
    Engineer A reviews and makes only minor wording adjustments
  3. Draft Report Sealing and Submission
    Report submitted with mixed authorial voices
  4. Report Stylistic Inconsistency
    Client W observes the report reads as if written by two authors
Field classification (triples vs literals)
Relations (structural triples)
  • cause: AI Report Generation
  • effect: Report Stylistic Inconsistency
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: The Client commented that the report read as if written by two different authors but was otherwise satisfactory.
  • necessaryFactors content: AI-generated polished introduction section; Engineer A's own writing style in the data analysis section; Juxtaposition of the two within one report
  • sufficientFactors content: Combination of AI-generated polished prose alongside human-drafted content produced a noticeable stylistic mismatch
  • counterfactual content: Had the entire report been written in a uniform voice (or fully harmonized by Engineer A), the inconsistency would not have been observed
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'AI Report Generation', 'proeth:description': 'AI produces a highly polished introduction section'}; {'proeth:step': 2, 'proeth:element': 'Thorough Report Review', 'proeth:description': 'Engineer A reviews and makes only minor wording adjustments'}; {'proeth:step': 3, 'proeth:element': 'Draft Report Sealing and Submission', 'proeth:description': 'Report submitted with mixed authorial voices'}; {'proeth:step': 4, 'proeth:element': 'Report Stylistic Inconsistency', 'proeth:description': 'Client W observes the report reads as if written by two authors'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_4febf78b",
  "@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 a highly polished introduction section",
      "proeth:element": "AI Report Generation",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A reviews and makes only minor wording adjustments",
      "proeth:element": "Thorough Report Review",
      "proeth:step": 2
    },
    {
      "proeth:description": "Report submitted with mixed authorial voices",
      "proeth:element": "Draft Report Sealing and Submission",
      "proeth:step": 3
    },
    {
      "proeth:description": "Client W observes the report reads as if written by two authors",
      "proeth:element": "Report Stylistic Inconsistency",
      "proeth:step": 4
    }
  ],
  "proeth:cause": "AI Report Generation",
  "proeth:counterfactual": "Had the entire report been written in a uniform voice (or fully harmonized by Engineer A), the inconsistency would not have been observed",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "Report Stylistic Inconsistency",
  "proeth:necessaryFactors": [
    "AI-generated polished introduction section",
    "Engineer A\u0027s own writing style in the data analysis section",
    "Juxtaposition of the two within one report"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Combination of AI-generated polished prose alongside human-drafted content produced a noticeable stylistic mismatch"
  ],
  "proeth:withinAgentControl": true
}

Causal Language: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report

Necessary Factors (NESS):
  • Loss of Engineer B's quality assurance and mentorship
  • Engineer A's lack of confidence in technical writing
  • Need to deliver the report
Sufficient Factors:
  • Combination of mentor unavailability + writing insecurity + delivery deadline drove adoption of AI software
Counterfactual Test: Had Engineer B remained available for review, Engineer A would likely have relied on mentorship rather than adopting unfamiliar AI software
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. Supervisor Retirement
    Engineer B retires, removing prior QA review and mentorship
  2. Dual Deliverable Pressure
    Engineer A faces concurrent report and design deadlines without support
  3. AI Tool Adoption for Report
    Engineer A decides to use open-source AI software to draft the report
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Supervisor Retirement
  • effect: AI Tool Adoption for Report
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: 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
  • necessaryFactors content: Loss of Engineer B's quality assurance and mentorship; Engineer A's lack of confidence in technical writing; Need to deliver the report
  • sufficientFactors content: Combination of mentor unavailability + writing insecurity + delivery deadline drove adoption of AI software
  • counterfactual content: Had Engineer B remained available for review, Engineer A would likely have relied on mentorship rather than adopting unfamiliar AI software
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'Supervisor Retirement', 'proeth:description': 'Engineer B retires, removing prior QA review and mentorship'}; {'proeth:step': 2, 'proeth:element': 'Dual Deliverable Pressure', 'proeth:description': 'Engineer A faces concurrent report and design deadlines without support'}; {'proeth:step': 3, 'proeth:element': 'AI Tool Adoption for Report', 'proeth:description': 'Engineer A decides to use open-source AI software to draft the report'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_5c444053",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "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",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer B retires, removing prior QA review and mentorship",
      "proeth:element": "Supervisor Retirement",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A faces concurrent report and design deadlines without support",
      "proeth:element": "Dual Deliverable Pressure",
      "proeth:step": 2
    },
    {
      "proeth:description": "Engineer A decides to use open-source AI software to draft the report",
      "proeth:element": "AI Tool Adoption for Report",
      "proeth:step": 3
    }
  ],
  "proeth:cause": "Supervisor Retirement",
  "proeth:counterfactual": "Had Engineer B remained available for review, Engineer A would likely have relied on mentorship rather than adopting unfamiliar AI software",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "AI Tool Adoption for Report",
  "proeth:necessaryFactors": [
    "Loss of Engineer B\u0027s quality assurance and mentorship",
    "Engineer A\u0027s lack of confidence in technical writing",
    "Need to deliver the report"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Combination of mentor unavailability + writing insecurity + delivery deadline drove adoption of AI software"
  ],
  "proeth:withinAgentControl": true
}

Causal Language: Faced with the need to deliver both the report and the engineering design documents without the review by and mentorship from Engineer B, Engineer A opted to use open-sourced artificial intelligence (AI) software to create an initial draft of the necessary report and to use AI-assisted drafting tools to generate preliminary design documents

Necessary Factors (NESS):
  • Concurrent deadlines for report and design
  • Absence of Engineer B's support
  • Availability of AI-assisted drafting tools
Sufficient Factors:
  • Combination of time pressure + lack of mentorship + availability of AI tools led to adoption for design
Counterfactual Test: Without the concurrent pressure and loss of support, Engineer A may not have turned to an unfamiliar AI drafting tool for design work
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. Dual Deliverable Pressure
    Engineer A faces concurrent report and design deadlines
  2. AI Tool Adoption for Design
    Engineer A decides to use AI-assisted drafting tools for design documents
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Dual Deliverable Pressure
  • effect: AI Tool Adoption for Design
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: 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
  • necessaryFactors content: Concurrent deadlines for report and design; Absence of Engineer B's support; Availability of AI-assisted drafting tools
  • sufficientFactors content: Combination of time pressure + lack of mentorship + availability of AI tools led to adoption for design
  • counterfactual content: Without the concurrent pressure and loss of support, Engineer A may not have turned to an unfamiliar AI drafting tool for design work
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'Dual Deliverable Pressure', 'proeth:description': 'Engineer A faces concurrent report and design deadlines'}; {'proeth:step': 2, 'proeth:element': 'AI Tool Adoption for Design', 'proeth:description': 'Engineer A decides to use AI-assisted drafting tools for design documents'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_5acad349",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "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",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A faces concurrent report and design deadlines",
      "proeth:element": "Dual Deliverable Pressure",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A decides to use AI-assisted drafting tools for design documents",
      "proeth:element": "AI Tool Adoption for Design",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "Dual Deliverable Pressure",
  "proeth:counterfactual": "Without the concurrent pressure and loss of support, Engineer A may not have turned to an unfamiliar AI drafting tool for design work",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "AI Tool Adoption for Design",
  "proeth:necessaryFactors": [
    "Concurrent deadlines for report and design",
    "Absence of Engineer B\u0027s support",
    "Availability of AI-assisted drafting tools"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Combination of time pressure + lack of mentorship + availability of AI tools led to adoption for design"
  ],
  "proeth:withinAgentControl": true
}

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):
  • Possession of Client W's confidential information
  • Use of an open-source (public) AI interface
  • Absence of client consent to public disclosure
Sufficient Factors:
  • Uploading confidential client data into an open-source AI interface was enough to expose it to the public domain
Counterfactual Test: Had Engineer A not uploaded the data, or used a secure/private tool with consent, exposure would not have occurred
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. AI Tool Adoption for Report
    Engineer A selects open-source AI software
  2. Client Data Upload to AI
    Engineer A enters Client W's private information into the interface
  3. Client Data Exposure
    Confidential information effectively placed in the public domain
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Client Data Upload to AI
  • effect: Client Data Exposure
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: 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.
  • necessaryFactors content: Possession of Client W's confidential information; Use of an open-source (public) AI interface; Absence of client consent to public disclosure
  • sufficientFactors content: Uploading confidential client data into an open-source AI interface was enough to expose it to the public domain
  • counterfactual content: Had Engineer A not uploaded the data, or used a secure/private tool with consent, exposure would not have occurred
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'AI Tool Adoption for Report', 'proeth:description': 'Engineer A selects open-source AI software'}; {'proeth:step': 2, 'proeth:element': 'Client Data Upload to AI', 'proeth:description': "Engineer A enters Client W's private information into the interface"}; {'proeth:step': 3, 'proeth:element': 'Client Data Exposure', 'proeth:description': 'Confidential information effectively placed in the public domain'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_81a40fff",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "When Engineer A uploaded Client W\u0027s information into the AI open-source interface, this was tantamount to placing the Client\u0027s private information in the public domain.",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A selects open-source AI software",
      "proeth:element": "AI Tool Adoption for Report",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A enters Client W\u0027s private information into the interface",
      "proeth:element": "Client Data Upload to AI",
      "proeth:step": 2
    },
    {
      "proeth:description": "Confidential information effectively placed in the public domain",
      "proeth:element": "Client Data Exposure",
      "proeth:step": 3
    }
  ],
  "proeth:cause": "Client Data Upload to AI",
  "proeth:counterfactual": "Had Engineer A not uploaded the data, or used a secure/private tool with consent, exposure would not have occurred",
  "proeth:discoveredInSection": "discussion",
  "proeth:effect": "Client Data Exposure",
  "proeth:necessaryFactors": [
    "Possession of Client W\u0027s confidential information",
    "Use of an open-source (public) AI interface",
    "Absence of client consent to public disclosure"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Uploading confidential client data into an open-source AI interface was enough to expose it to the public domain"
  ],
  "proeth:withinAgentControl": true
}

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):
  • Input of Client W's gathered information
  • Refining prompts provided to the AI
  • Functioning AI language processing software
Sufficient Factors:
  • Inputting client data plus refining prompts was enough for the AI to generate a first draft report
Counterfactual Test: Without the data input and prompts, the AI would not have produced the draft report
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. Client Data Upload to AI
    Engineer A inputs Client W information into the AI
  2. AI Report Generation
    AI produces a first draft of the report
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Client Data Upload to AI
  • effect: AI Report Generation
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: 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.
  • necessaryFactors content: Input of Client W's gathered information; Refining prompts provided to the AI; Functioning AI language processing software
  • sufficientFactors content: Inputting client data plus refining prompts was enough for the AI to generate a first draft report
  • counterfactual content: Without the data input and prompts, the AI would not have produced the draft report
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'Client Data Upload to AI', 'proeth:description': 'Engineer A inputs Client W information into the AI'}; {'proeth:step': 2, 'proeth:element': 'AI Report Generation', 'proeth:description': 'AI produces a first draft of the report'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_27c4e3bd",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "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.",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A inputs Client W information into the AI",
      "proeth:element": "Client Data Upload to AI",
      "proeth:step": 1
    },
    {
      "proeth:description": "AI produces a first draft of the report",
      "proeth:element": "AI Report Generation",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "Client Data Upload to AI",
  "proeth:counterfactual": "Without the data input and prompts, the AI would not have produced the draft report",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "AI Report Generation",
  "proeth:necessaryFactors": [
    "Input of Client W\u0027s gathered information",
    "Refining prompts provided to the AI",
    "Functioning AI language processing software"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Inputting client data plus refining prompts was enough for the AI to generate a first draft report"
  ],
  "proeth:withinAgentControl": true
}

Causal Language: Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans, including basic layouts and technical specifications.

Necessary Factors (NESS):
  • Input of Client W's gathered information into the AI
  • Use of AI-assisted drafting tools
  • Reliance on the tools to generate plans
Sufficient Factors:
  • Inputting data and relying on AI-assisted drafting tools was enough to generate preliminary design plans
Counterfactual Test: Without adopting and feeding the AI drafting tool, the preliminary AI-generated design would not exist
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. AI Tool Adoption for Design
    Engineer A decides to use the AI-assisted drafting tool
  2. AI Design Generation
    AI produces preliminary design documents with layouts and specifications
Field classification (triples vs literals)
Relations (structural triples)
  • cause: AI Tool Adoption for Design
  • effect: AI Design Generation
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans, including basic layouts and technical specifications.
  • necessaryFactors content: Input of Client W's gathered information into the AI; Use of AI-assisted drafting tools; Reliance on the tools to generate plans
  • sufficientFactors content: Inputting data and relying on AI-assisted drafting tools was enough to generate preliminary design plans
  • counterfactual content: Without adopting and feeding the AI drafting tool, the preliminary AI-generated design would not exist
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'AI Tool Adoption for Design', 'proeth:description': 'Engineer A decides to use the AI-assisted drafting tool'}; {'proeth:step': 2, 'proeth:element': 'AI Design Generation', 'proeth:description': 'AI produces preliminary design documents with layouts and specifications'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_33362a75",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "Engineer A entered the information gathered from Client W into the AI software and relied on the AI-assisted drafting tools to generate a preliminary design of the plans, including basic layouts and technical specifications.",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A decides to use the AI-assisted drafting tool",
      "proeth:element": "AI Tool Adoption for Design",
      "proeth:step": 1
    },
    {
      "proeth:description": "AI produces preliminary design documents with layouts and specifications",
      "proeth:element": "AI Design Generation",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "AI Tool Adoption for Design",
  "proeth:counterfactual": "Without adopting and feeding the AI drafting tool, the preliminary AI-generated design would not exist",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "AI Design Generation",
  "proeth:necessaryFactors": [
    "Input of Client W\u0027s gathered information into the AI",
    "Use of AI-assisted drafting tools",
    "Reliance on the tools to generate plans"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Inputting data and relying on AI-assisted drafting tools was enough to generate preliminary design plans"
  ],
  "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):
  • AI-generated plans containing misaligned dimensions and omitted safety features
  • Only a cursory (insufficient) review by Engineer A
  • Failure to detect the errors before submission
Sufficient Factors:
  • Combination of AI-generated defects + insufficient review allowed defects to remain in submitted documents
Counterfactual Test: Had Engineer A conducted a comprehensive verification process, the misaligned dimensions and omitted safety features would likely have been caught and corrected before Client review
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. AI Design Generation
    AI produces plans with misaligned dimensions and missing safety features
  2. Cursory Design Document Review
    Engineer A reviews only superficially, missing the defects
  3. Design Document Submission
    Defective documents submitted to Client W
  4. Design Defect Discovery
    Client W identifies misaligned dimensions and omitted safety features
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Cursory Design Document Review
  • effect: Design Defect Discovery
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to align with site-specific conditions.
  • necessaryFactors content: AI-generated plans containing misaligned dimensions and omitted safety features; Only a cursory (insufficient) review by Engineer A; Failure to detect the errors before submission
  • sufficientFactors content: Combination of AI-generated defects + insufficient review allowed defects to remain in submitted documents
  • counterfactual content: Had Engineer A conducted a comprehensive verification process, the misaligned dimensions and omitted safety features would likely have been caught and corrected before Client review
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'AI Design Generation', 'proeth:description': 'AI produces plans with misaligned dimensions and missing safety features'}; {'proeth:step': 2, 'proeth:element': 'Cursory Design Document Review', 'proeth:description': 'Engineer A reviews only superficially, missing the defects'}; {'proeth:step': 3, 'proeth:element': 'Design Document Submission', 'proeth:description': 'Defective documents submitted to Client W'}; {'proeth:step': 4, 'proeth:element': 'Design Defect Discovery', 'proeth:description': 'Client W identifies misaligned dimensions and omitted safety features'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_e2ef42fd",
  "@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": "AI produces plans with misaligned dimensions and missing safety features",
      "proeth:element": "AI Design Generation",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A reviews only superficially, missing the defects",
      "proeth:element": "Cursory Design Document Review",
      "proeth:step": 2
    },
    {
      "proeth:description": "Defective documents submitted to Client W",
      "proeth:element": "Design Document Submission",
      "proeth:step": 3
    },
    {
      "proeth:description": "Client W identifies misaligned dimensions and omitted safety features",
      "proeth:element": "Design Defect Discovery",
      "proeth:step": 4
    }
  ],
  "proeth:cause": "Cursory Design Document Review",
  "proeth:counterfactual": "Had Engineer A conducted a comprehensive verification process, the misaligned dimensions and omitted safety features would likely have been caught and corrected before Client review",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "Design Defect Discovery",
  "proeth:necessaryFactors": [
    "AI-generated plans containing misaligned dimensions and omitted safety features",
    "Only a cursory (insufficient) review by Engineer A",
    "Failure to detect the errors before submission"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Combination of AI-generated defects + insufficient review allowed defects to remain in submitted documents"
  ],
  "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 review of the design documents
Sufficient Factors:
  • Discovery of defects in the design documents was enough to prompt a formal revision instruction
Counterfactual Test: Had no defects been discovered, Client W would not have instructed Engineer A to revise the plans
Responsibility Attribution:

Agent: Client W
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. Design Defect Discovery
    Client W finds defects in the submitted design
  2. Revision Instruction Issued
    Client W formally instructs Engineer A to revise the plans
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Design Defect Discovery
  • effect: Revision Instruction Issued
  • responsibleAgent: Client W
Literal extractions (kept for synthesis)
  • causalLanguage content: 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.
  • necessaryFactors content: Client W's discovery of misaligned dimensions and omitted safety features; Client W's review of the design documents
  • sufficientFactors content: Discovery of defects in the design documents was enough to prompt a formal revision instruction
  • counterfactual content: Had no defects been discovered, Client W would not have instructed Engineer A to revise the plans
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'Design Defect Discovery', 'proeth:description': 'Client W finds defects in the submitted design'}; {'proeth:step': 2, 'proeth:element': 'Revision Instruction Issued', 'proeth:description': 'Client W formally instructs Engineer A to revise the plans'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_0f11ccf1",
  "@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 finds defects in the submitted design",
      "proeth:element": "Design Defect Discovery",
      "proeth:step": 1
    },
    {
      "proeth:description": "Client W formally instructs Engineer A to revise the plans",
      "proeth:element": "Revision Instruction Issued",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "Design Defect Discovery",
  "proeth:counterfactual": "Had no defects been discovered, Client W would not have instructed Engineer A to revise the plans",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "Revision Instruction Issued",
  "proeth:necessaryFactors": [
    "Client W\u0027s discovery of misaligned dimensions and omitted safety features",
    "Client W\u0027s review of the design documents"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Client W",
  "proeth:sufficientFactors": [
    "Discovery of defects in the design documents was enough to prompt a formal revision instruction"
  ],
  "proeth:withinAgentControl": true
}

Causal Language: When Client W reviewed the draft report, Client W noted that the section analyzing the groundwater monitoring data would benefit from minor edits for grammar and clarity, but found the introduction discussing the contaminant's manufacture, use, and characteristics to be exceptionally polished.

Necessary Factors (NESS):
  • Submission of the draft report to Client W
  • Presence of stylistically divergent sections in the report
Sufficient Factors:
  • Submitting the stylistically mixed report to the client was enough to enable the client's observation of inconsistency
Counterfactual Test: Without submission to Client W, the inconsistency would not have been noted by the client
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. Draft Report Sealing and Submission
    Engineer A seals and submits the draft report to Client W
  2. Report Stylistic Inconsistency
    Client W notes the report reads as if written by two different authors
Field classification (triples vs literals)
Relations (structural triples)
  • cause: Draft Report Sealing and Submission
  • effect: Report Stylistic Inconsistency
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: When Client W reviewed the draft report, Client W noted that the section analyzing the groundwater monitoring data would benefit from minor edits for grammar and clarity, but found the introduction discussing the contaminant's manufacture, use, and characteristics to be exceptionally polished.
  • necessaryFactors content: Submission of the draft report to Client W; Presence of stylistically divergent sections in the report
  • sufficientFactors content: Submitting the stylistically mixed report to the client was enough to enable the client's observation of inconsistency
  • counterfactual content: Without submission to Client W, the inconsistency would not have been noted by the client
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'Draft Report Sealing and Submission', 'proeth:description': 'Engineer A seals and submits the draft report to Client W'}; {'proeth:step': 2, 'proeth:element': 'Report Stylistic Inconsistency', 'proeth:description': 'Client W notes the report reads as if written by two different authors'}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_37f829e3",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "When Client W reviewed the draft report, Client W noted that the section analyzing the groundwater monitoring data would benefit from minor edits for grammar and clarity, but found the introduction discussing the contaminant\u0027s manufacture, use, and characteristics to be exceptionally polished.",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A seals and submits the draft report to Client W",
      "proeth:element": "Draft Report Sealing and Submission",
      "proeth:step": 1
    },
    {
      "proeth:description": "Client W notes the report reads as if written by two different authors",
      "proeth:element": "Report Stylistic Inconsistency",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "Draft Report Sealing and Submission",
  "proeth:counterfactual": "Without submission to Client W, the inconsistency would not have been noted by the client",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "Report Stylistic Inconsistency",
  "proeth:necessaryFactors": [
    "Submission of the draft report to Client W",
    "Presence of stylistically divergent sections in the report"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Submitting the stylistically mixed report to the client was enough to enable the client\u0027s observation of inconsistency"
  ],
  "proeth:withinAgentControl": true
}

Causal Language: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review

Necessary Factors (NESS):
  • Substantial AI contribution to the report
  • Engineer A's decision not to cite the AI use
  • Absence of disclosure to the client
Sufficient Factors:
  • Use of AI plus a deliberate choice not to cite it produced the disclosure omission
Counterfactual Test: Had Engineer A chosen to disclose, the omission and resulting transparency concern would not have arisen
Responsibility Attribution:

Agent: Engineer A
Type: direct
Within Agent Control: Yes

Causal Sequence:
  1. AI Tool Adoption for Report
    Engineer A uses AI to draft the report
  2. AI Disclosure Omission for Report
    Engineer A chooses not to cite the AI's contribution
Field classification (triples vs literals)
Relations (structural triples)
  • cause: AI Tool Adoption for Report
  • effect: AI Disclosure Omission for Report
  • responsibleAgent: Engineer A
Literal extractions (kept for synthesis)
  • causalLanguage content: Engineer A did not cite their use of AI-software or its large language models, and submitted the draft report to Client W for review
  • necessaryFactors content: Substantial AI contribution to the report; Engineer A's decision not to cite the AI use; Absence of disclosure to the client
  • sufficientFactors content: Use of AI plus a deliberate choice not to cite it produced the disclosure omission
  • counterfactual content: Had Engineer A chosen to disclose, the omission and resulting transparency concern would not have arisen
  • causalSequence content: {'proeth:step': 1, 'proeth:element': 'AI Tool Adoption for Report', 'proeth:description': 'Engineer A uses AI to draft the report'}; {'proeth:step': 2, 'proeth:element': 'AI Disclosure Omission for Report', 'proeth:description': "Engineer A chooses not to cite the AI's contribution"}
  • responsibilityType assessment: direct
  • withinAgentControl assessment: True
RDF JSON-LD
{
  "@context": {
    "proeth": "http://proethica.org/ontology/intermediate#",
    "proeth-case": "http://proethica.org/cases/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/cases/7#CausalChain_548e8fbd",
  "@type": "proeth:CausalChain",
  "proeth:causalLanguage": "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",
  "proeth:causalSequence": [
    {
      "proeth:description": "Engineer A uses AI to draft the report",
      "proeth:element": "AI Tool Adoption for Report",
      "proeth:step": 1
    },
    {
      "proeth:description": "Engineer A chooses not to cite the AI\u0027s contribution",
      "proeth:element": "AI Disclosure Omission for Report",
      "proeth:step": 2
    }
  ],
  "proeth:cause": "AI Tool Adoption for Report",
  "proeth:counterfactual": "Had Engineer A chosen to disclose, the omission and resulting transparency concern would not have arisen",
  "proeth:discoveredInSection": "facts",
  "proeth:effect": "AI Disclosure Omission for Report",
  "proeth:necessaryFactors": [
    "Substantial AI contribution to the report",
    "Engineer A\u0027s decision not to cite the AI use",
    "Absence of disclosure to the client"
  ],
  "proeth:responsibilityType": "direct",
  "proeth:responsibleAgent": "Engineer A",
  "proeth:sufficientFactors": [
    "Use of AI plus a deliberate choice not to cite it produced the disclosure omission"
  ],
  "proeth:withinAgentControl": true
}
Allen Temporal Relations (9)
Interval algebra relationships with OWL-Time standard properties
From Entity Allen Relation To Entity OWL-Time Property Evidence
Engineer A's site observation and data gathering before
Entity1 is before Entity2
project deliverables due date time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
groundwater monitoring data from a site Engineer A had been observing for over a year
Engineer B's retirement before
Entity1 is before Entity2
Engineer A's use of AI software for dual deliverables time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
Faced with the need to deliver both the report and the engineering design documents without the revi... [more]
Engineer B's mentorship and QA 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]
AI generation of initial 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
Engineer A conducted a thorough review of the report, cross-checking key facts against professional ... [more]
AI generation of preliminary design documents before
Entity1 is before Entity2
Engineer A's cursory review of design documents time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to ali... [more]
Engineer A's thorough review of the report before
Entity1 is before Entity2
submission of draft report to Client W time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
Engineer A ... submitted the draft report to Client W for review, including language to clearly iden... [more]
Engineer A's cursory review of design documents before
Entity1 is before Entity2
submission of design documents to Client W time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
Engineer A completed a cursory review of the AI-generated plans and adjusted certain elements to ali... [more]
submission of both deliverables to Client W before
Entity1 is before Entity2
Client W's review and identification of issues time:intervalBefore
http://www.w3.org/2006/time#intervalBefore
When Client W reviewed the draft report ... Client W, however, noticed several issues with the AI-ge... [more]
Client W's identification of issues in 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]
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.