Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics
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Abstract (arXiv)
Numerous toolkits have been developed to support ethical AI development. However, toolkits, like all tools, encode assumptions in their design about what work should be done and how. In this paper, we conduct a qualitative analysis of 27 AI ethics toolkits to critically examine how the work of ethics is imagined and how it is supported by these toolkits. Specifically, we examine the discourses toolkits rely on when talking about ethical issues, who they imagine should do the work of ethics, and how they envision the work practices involved in addressing ethics. Among the toolkits, we identify a mismatch between the imagined work of ethics and the support the toolkits provide for doing that work. In particular, we identify a lack of guidance around how to navigate labor, organizational, and institutional power dynamics as they relate to performing ethical work. We use these omissions to chart future work for researchers and designers of AI ethics toolkits.
Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 16 of its 101 references that are in the map. First posted on arXiv 17 Feb 2022.
Builds on
16 of 101 references.
References · 16
- 2018Datasheets for Datasetscited by 1,371
- 2018Model Cards for Model Reportingcited by 1,068
- 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
- 2019Measurement and Fairnesscited by 299
- 2018Improving fairness in machine learning systems: What do industry practitioners need?cited by 262
- 2020Participation is not a Design Fix for Machine Learningcited by 110
- 2021Re-imagining Algorithmic Fairness in India and Beyondcited by 102
- 2019Problem Formulation and Fairnesscited by 85
- 2021Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Supportcited by 61
- 2019FairSight: Visual Analytics for Fairness in Decision Makingcited by 59
- 2021Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviorscited by 47
- 2021Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systemscited by 27
4 more
- 2021Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"cited by 26
- 2020Principles to Practices for Responsible AI: Closing the Gapcited by 25
- 2020Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberationcited by 24
- 2018Data Science as Political Action: Grounding Data Science in a Politics of Justicecited by 14
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Citing papers per year: 2022: 2; 2023: 5; 2024: 8; 2025: 7; 2026: 6.
28 papers.
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- 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
- 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible MLcited by 26
- 2022The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairnesscited by 21
- 2023Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practicecited by 15
- 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
- 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Developmentcited by 10
- 2023Responsible AI Research Needs Impact Statements Toocited by 7
- 2024Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Usecited by 6
- 2023A Systematic Literature Review of Human-Centered, Ethical, and Responsible AIcited by 5
- 2024Law and the Emerging Political Economy of Algorithmic Auditscited by 5
- 2025A Toolkit for Compliance, a Toolkit for Justice: Drawing on Cross-sectoral Expertise to Develop a Pro-justice EU AI Act Toolkitcited by 4
- 2023The Value-Sensitive Conversational Agent Co-Design Frameworkcited by 3
16 more
- 2024Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teamscited by 3
- 2024Thoughtful Adoption of NLP for Civic Participation: Understanding Differences Among Policymakerscited by 3
- 2024Legacy Procurement Practices Shape How U.S. Cities Govern AI: Understanding Government Employees' Practices, Challenges, and Needscited by 3
- 2025Talking About the Assumption in the Roomcited by 2
- 2025Co-Producing AI: Toward an Augmented, Participatory Lifecyclecited by 2
- 2023Positive AI: Key Challenges in Designing Artificial Intelligence for Wellbeingcited by 1
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Modelscited by 1
- 2025AI LEGO: Scaffolding Cross-Functional Collaboration in Industrial Responsible AI Practices during Early Design Stagescited by 1
- 2026What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safetycited by 1
- 2026From Reflection to Repair: A Scoping Review of Dataset Documentation Toolscited by 1
- 2026Trustworthy AI Posture (TAIP): A Framework for Continuous AI Assurance of Agentic Systems at Horizontal and Vertical scalecited by 1
- 2025Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systemscited by 0
- 2025Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistantscited by 0
- 2026Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping Softwarecited by 0
- 2026To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systemscited by 0
- 2026Design Concept: Scaffolding Geopolitical Reflection Among Tech Workerscited by 0
- 2026Design Concept: Scaffolding Geopolitical Reflection Among Tech Workers31 Jul 2026
- 2026To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems30 Apr 2026
- 2026Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping Software13 Apr 2026
- 2026From Reflection to Repair: A Scoping Review of Dataset Documentation Tools17 Feb 2026
- 2026Trustworthy AI Posture (TAIP): A Framework for Continuous AI Assurance of Agentic Systems at Horizontal and Vertical scale15 Feb 2026
- 2026What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safety26 Jan 2026
- 2025Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistants28 Nov 2025
- 2025Co-Producing AI: Toward an Augmented, Participatory Lifecycle31 Jul 2025
- 2025Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems26 May 2025
- 2025A Toolkit for Compliance, a Toolkit for Justice: Drawing on Cross-sectoral Expertise to Develop a Pro-justice EU AI Act Toolkit22 May 2025
- 2025AI LEGO: Scaffolding Cross-Functional Collaboration in Industrial Responsible AI Practices during Early Design Stages15 May 2025
- 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development25 Feb 2025
16 more
- 2025Talking About the Assumption in the Room18 Feb 2025
- 2024Legacy Procurement Practices Shape How U.S. Cities Govern AI: Understanding Government Employees' Practices, Challenges, and Needs7 Nov 2024
- 2024Thoughtful Adoption of NLP for Civic Participation: Understanding Differences Among Policymakers30 Oct 2024
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models17 Oct 2024
- 2024Position: Towards Bidirectional Human-AI Alignment13 Jun 2024
- 2024Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use21 May 2024
- 2024Law and the Emerging Political Economy of Algorithmic Audits3 Apr 2024
- 2024Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams15 Mar 2024
- 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototyping23 Feb 2024
- 2023Responsible AI Research Needs Impact Statements Too20 Nov 2023
- 2023The Value-Sensitive Conversational Agent Co-Design Framework18 Oct 2023
- 2023Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice10 Jun 2023
- 2023Positive AI: Key Challenges in Designing Artificial Intelligence for Wellbeing12 Apr 2023
- 2023A Systematic Literature Review of Human-Centered, Ethical, and Responsible AI10 Feb 2023
- 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML6 Oct 2022
- 2022The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairness19 Feb 2022
- 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
- 2024Position: Towards Bidirectional Human-AI Alignment13 Jun 2024
- 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
- 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible MLcited by 26
- 2022The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairnesscited by 21
- 2023Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practicecited by 15
- 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Developmentcited by 10
- 2023Responsible AI Research Needs Impact Statements Toocited by 7
- 2024Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Usecited by 6
- 2023A Systematic Literature Review of Human-Centered, Ethical, and Responsible AIcited by 5
- 2024Law and the Emerging Political Economy of Algorithmic Auditscited by 5
- 2025A Toolkit for Compliance, a Toolkit for Justice: Drawing on Cross-sectoral Expertise to Develop a Pro-justice EU AI Act Toolkitcited by 4
- 2024Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teamscited by 3
- 2024Thoughtful Adoption of NLP for Civic Participation: Understanding Differences Among Policymakerscited by 3
12 most cited of 25 All 25 (JSON)
- 2026Design Concept: Scaffolding Geopolitical Reflection Among Tech Workers31 Jul 2026
- 2026To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems30 Apr 2026
- 2026Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping Software13 Apr 2026
- 2026From Reflection to Repair: A Scoping Review of Dataset Documentation Tools17 Feb 2026
- 2026What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safety26 Jan 2026
- 2025Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistants28 Nov 2025
- 2025Co-Producing AI: Toward an Augmented, Participatory Lifecycle31 Jul 2025
- 2025Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems26 May 2025
- 2025A Toolkit for Compliance, a Toolkit for Justice: Drawing on Cross-sectoral Expertise to Develop a Pro-justice EU AI Act Toolkit22 May 2025
- 2025AI LEGO: Scaffolding Cross-Functional Collaboration in Industrial Responsible AI Practices during Early Design Stages15 May 2025
- 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development25 Feb 2025
- 2025Talking About the Assumption in the Room18 Feb 2025
12 newest of 25 All 25 (JSON)