mlsanityData to 14 Oct 2026

Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits

arXiv 2403.14791 ↗First posted 21 Mar 2024cs.CY cs.AIcited by 9

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Abstract (arXiv)

General purpose AI, such as ChatGPT, seems to have lowered the barriers for the public to use AI and harness its power. However, the governance and development of AI still remain in the hands of a few, and the pace of development is accelerating without a comprehensive assessment of risks. As a first step towards democratic risk assessment and design of general purpose AI, we introduce PARTICIP-AI, a carefully designed framework for laypeople to speculate and assess AI use cases and their impacts. Our framework allows us to study more nuanced and detailed public opinions on AI through collecting use cases, surfacing diverse harms through risk assessment under alternate scenarios (i.e., developing and not developing a use case), and illuminating tensions over AI development through making a concluding choice on its development. To showcase the promise of our framework towards informing democratic AI development, we run a medium-scale study with inputs from 295 demographically diverse participants. Our analyses show that participants' responses emphasize applications for personal life and society, contrasting with most current AI development's business focus. We also surface diverse set of envisioned harms such as distrust in AI and institutions, complementary to those defined by experts. Furthermore, we found that perceived impact of not developing use cases significantly predicted participants' judgements of whether AI use cases should be developed, and highlighted lay users' concerns of techno-solutionism. We conclude with a discussion on how frameworks like PARTICIP-AI can further guide democratic AI development and governance.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 30 of its 118 references that are in the map. First posted on arXiv 21 Mar 2024.

Builds on

30 of 118 references.

References · 30

  1. 2017Deep reinforcement learning from human preferencescited by 3,912
  2. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,720
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  4. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 437
  5. 2020Participatory Research for Low-resourced Machine Translation: A Case Study in African Languagescited by 159
  6. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 157
  7. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
  8. 2022Power to the People? Opportunities and Challenges for Participatory AIcited by 138
  9. 2023NLPositionality: Characterizing Design Biases of Datasets and Modelscited by 94
  10. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 92
  11. 2023The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practicecited by 87
  12. 2023Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Codingcited by 82
18 more
  1. 2023Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Supportcited by 75
  2. 2023Managing extreme AI risks amid rapid progresscited by 48
  3. 2022The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligencecited by 42
  4. 2023Prompt2Model: Generating Deployable Models from Natural Language Instructionscited by 41
  5. 2019Ask Not What AI Can Do, But What AI Should Do: Towards a Framework of Task Delegabilitycited by 36
  6. 2023Queer In AI: A Case Study in Community-Led Participatory AIcited by 34
  7. 2023Detecting LLM-Generated Text in Computing Education: A Comparative Study for ChatGPT Casescited by 32
  8. 2021Envisioning Communities: A Participatory Approach Towards AI for Social Goodcited by 30
  9. 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
  10. 2023AHA!: Facilitating AI Impact Assessment by Generating Examples of Harmscited by 26
  11. 2022A Human Rights-Based Approach to Responsible AIcited by 20
  12. 2023Embedding-based Retrieval with LLM for Effective Agriculture Information Extracting from Unstructured Datacited by 16
  13. 2022Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Reportcited by 14
  14. 2023Ethical Frameworks and Computer Security Trolley Problems: Foundations for Conversationscited by 11
  15. 2020Security and Machine Learning in the Real Worldcited by 9
  16. 2023"That's important, but...": How Computer Science Researchers Anticipate Unintended Consequences of Their Research Innovationscited by 8
  17. 2024Close to Human-Level Agreement: Tracing Journeys of Violent Speech in Incel Posts with GPT-4-Enhanced Annotationscited by 7
  18. 2023Is the U.S. Legal System Ready for AI's Challenges to Human Values?cited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 3.

9 papers.