mlsanityData to 14 Oct 2026

Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"

arXiv 2111.01122 ↗First posted 1 Nov 2021cs.AI cs.CY cs.HCcited by 26

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Abstract (arXiv)

There is a growing consensus in HCI and AI research that the design of AI systems needs to engage and empower stakeholders who will be affected by AI. However, the manner in which stakeholders should participate in AI design is unclear. This workshop paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices via a survey of recent published research and a dozen semi-structured interviews with AI researchers and practitioners. Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design and articulates a set of empirical findings that in ensemble detail out the contemporary landscape of participatory practice in AI design. These findings can help bootstrap a more principled discussion on how PD of AI should move forward across AI, HCI, and other research communities.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 6 of its 61 references that are in the map. First posted on arXiv 1 Nov 2021.

Builds on

6 of 61 references.

References · 6

  1. 2020Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamicscited by 31
  2. 2020Bridging Machine Learning and Mechanism Design towards Algorithmic Fairnesscited by 30
  3. 2021A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfarecited by 23
  4. 2020Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systemscited by 16
  5. 2020What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Designcited by 14
  6. 2018Mechanism Design for Social Goodcited by 13

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 10; 2024: 7; 2025: 2; 2026: 3.

26 papers.

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  1. 2023AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asiacited by 54
  2. 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Servicescited by 29
  3. 2022Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethicscited by 28
  4. 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
  5. 2023Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiencescited by 21
  6. 2022Seamful XAI: Operationalizing Seamful Design in Explainable AIcited by 20
  7. 2023Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experiencecited by 18
  8. 2023`It is currently hodgepodge'': Examining AI/ML Practitioners' Challenges during Co-production of Responsible AI Valuescited by 18
  9. 2022Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholderscited by 15
  10. 2023Scaling Laws Do Not Scalecited by 13
  11. 2023Going public: the role of public participation approaches in commercial AI labscited by 11
  12. 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AIcited by 9
14 more
  1. 2022Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliancecited by 7
  2. 2024Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Usecited by 6
  3. 2023Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agentscited by 5
  4. 2023Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Educationcited by 5
  5. 2024From Fake Perfects to Conversational Imperfects: Exploring Image-Generative AI as a Boundary Object for Participatory Design of Public Spacescited by 3
  6. 2024Multi-Group Proportional Representation in Retrievalcited by 2
  7. 2024Operationalizing the Blueprint for an AI Bill of Rights: Recommendations for Practitioners, Researchers, and Policy Makerscited by 2
  8. 2024Integrating ESG and AI: A Comprehensive Responsible AI Assessment Frameworkcited by 2
  9. 2025The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participationcited by 1
  10. 2026Key Considerations for Domain Expert Involvement in LLM Design and Evaluation: An Ethnographic Studycited by 1
  11. 2024Reimagining AI in Social Work: Practitioner Perspectives on Incorporating Technology in their Practicecited by 0
  12. 2025BiaSWE: An Expert Annotated Dataset for Misogyny Detection in Swedishcited by 0
  13. 2026Information Access of the Oppressed: Freirean Design for Emancipatory Information Accesscited by 0
  14. 2026A Framework for Generating Valid Context-Specific Benchmarks through Expert Guidancecited by 0