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

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 devel- opment 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.

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Institutions

Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2024-10-16
DOI
https://doi.org/10.1609/aies.v7i1.31698
Citations
3
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
1.58

Funders

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article

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

Maarten Sap, Tadayoshi Kohno, Inyoung Cheong, Liwei Jiang et al.
3 citations
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Ethics and Social Impacts of AI
1.58
article

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

Maarten Sap, Tadayoshi Kohno, Inyoung Cheong, Liwei Jiang, Jimin Mun, Jenny Liang, Yejin Choi, Nicole DeCairo
article en
3 citations

Abstract

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 devel- opment 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.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 7(1)
University of Washington (US), Allen Institute (US), Carnegie Mellon University (US)
National Science Foundation, John D. and Catherine T. MacArthur Foundation, Silicon Valley Community Foundation, University of Washington, Carnegie Mellon University, Defense Advanced Research Projects Agency
Openalex Percentile: Top 13%
Ethics and Social Impacts of AI
1.58
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