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ICML 2024PosterAccept (Poster)

Position: Social Environment Design Should be Further Developed for AI-based Policy-Making

Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David Parkes, Milind Tambe, Yiling Chen

Humanity Unleashed Founding Labs · Harvard University, Harvard University · Harvard University · University of Oxford · Salesforce Research

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摘要

Artificial Intelligence (AI) holds promise as a technology that can be used to improve government and economic policy-making. This paper proposes a new research agenda towards this end by introducing **Social Environment Design**, a general framework for the use of AI in automated policy-making that connects with the Reinforcement Learning, EconCS, and Computational Social Choice communities. The framework seeks to capture general economic environments, includes voting on policy objectives, and gives a direction for the systematic analysis of government and economic policy through AI simulation. We highlight key open problems for future research in AI-based policymaking. By solving these challenges, we hope to achieve various social welfare objectives, thereby promoting more ethical and responsible decision making.