Power to the People? Opportunities and Challenges for Participatory AI
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Abstract (arXiv)
Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining momentum: the increased attention comes partly with the view that participation opens the gateway to an inclusive, equitable, robust, responsible and trustworthy AI.Among other benefits, participatory approaches are essential to understanding and adequately representing the needs, desires and perspectives of historically marginalized communities. However, there currently exists lack of clarity on what meaningful participation entails and what it is expected to do. In this paper we first review participatory approaches as situated in historical contexts as well as participatory methods and practices within the AI and ML pipeline. We then introduce three case studies in participatory AI.Participation holds the potential for beneficial, emancipatory and empowering technology design, development and deployment while also being at risk for concerns such as cooptation and conflation with other activities. We lay out these limitations and concerns and argue that as participatory AI/ML becomes in vogue, a contextual and nuanced understanding of the term as well as consideration of who the primary beneficiaries of participatory activities ought to be constitute crucial factors to realizing the benefits and opportunities that participation brings.
Key facts. Cited by 137 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Sep 2022.
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Citing papers per year: 2022: 5; 2023: 30; 2024: 41; 2025: 37; 2026: 24.
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- 2023Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordiacited by 119
- 2023Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agentscited by 5
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- 2026Small-world Networks of Agents Brainstorm AI Risks to Support Ideation21 Sep 2026
- 2026Value-Sensitive Delegation in Everyday AI Agent Use: Evidence from OpenClaw18 Sep 2026
- 2025Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation21 Jul 2025
- 2023Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia6 Dec 2023
- 2023Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents23 Oct 2023
- 2022Improving alignment of dialogue agents via targeted human judgements28 Sep 2022
- 2024Collective Constitutional AI: Aligning a Language Model with Public Inputcited by 120
- 2023Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackcited by 86
- 2023The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Valuescited by 53
- 2024Beyond Preferences in AI Alignmentcited by 46
- 2024The Future of Open Human Feedbackcited by 10
- 2025Evaluating the Effectiveness of Direct Preference Optimization for Personalizing German Automatic Text Simplifications for Persons with Intellectual Disabilitiescited by 0
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- 2024Beyond Preferences in AI Alignment30 Aug 2024
- 2024The Future of Open Human Feedback15 Aug 2024
- 2024Collective Constitutional AI: Aligning a Language Model with Public Input12 Jun 2024
- 2023The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values11 Oct 2023
- 2023Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback9 Mar 2023
- 2023Bias and Fairness in Large Language Models: A Surveycited by 626
- 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
- 2023The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practicecited by 86
- 2023A Benchmark for Learning to Translate a New Language from One Grammar Bookcited by 74
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- 2024Participation in the age of foundation modelscited by 32
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- 2023Building Socio-culturally Inclusive Stereotype Resources with Community Engagementcited by 25
- 2024The Impossibility of Fair LLMscited by 22
12 most cited of 124 All 124 (JSON)
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- 2026The Benchmark Trap: Structures of Power and Injustice in AI Evaluations15 Aug 2026
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- 2026Decolonizing Linguistic Policies in Automated Speech Recognition: A Framework for Cross-Culturally Competent Speech AI6 Aug 2026
- 2026A Cross Community Agenda for Speech AI22 Jul 2026
- 2026Unsafe at any AUC: Unlearned Lessons from Sociotechnical Disasters for Responsible AI15 Jul 2026
- 2026Editorial Alignment: A Participatory Approach to Engaging Editorial Expertise in LLM-mediated Knowledge Dissemination18 Jun 2026
- 2026AI Pluralism and the Worlds It Misses15 Jun 2026
- 2026Can Data Work be Reparative?8 Jun 2026
- 2026AI From the Margins (AIM): Rethinking Participatory AI Design Through the Lived Experience of Minoritized Communities31 May 2026
- 2026The Illusion of Opting in AI-Mediated Consequential Decisions27 May 2026
- 2026Building Arabic NLP from the Ground Up: Twenty Years of Lessons, Failures, and Open Problems20 May 2026
12 newest of 124 All 124 (JSON)