Social Environment Design
Abstract
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 for 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 policy-making. By solving these challenges, we hope to achieve various social welfare objectives, thereby promoting more ethical and responsible decision making.
Cite
@article{arxiv.2402.14090,
title = {Social Environment Design},
author = {Edwin Zhang and Sadie Zhao and Tonghan Wang and Safwan Hossain and Henry Gasztowtt and Stephan Zheng and David C. Parkes and Milind Tambe and Yiling Chen},
journal= {arXiv preprint arXiv:2402.14090},
year = {2024}
}
Comments
ICML 2024 Position Paper. Website at https://sed.eddie.win