Position: Social Environment Design Should Be Further Developed for AI-Based Policy-Making
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 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.
Cite
Text
Zhang et al. "Position: Social Environment Design Should Be Further Developed for AI-Based Policy-Making." International Conference on Machine Learning, 2024.Markdown
[Zhang et al. "Position: Social Environment Design Should Be Further Developed for AI-Based Policy-Making." International Conference on Machine Learning, 2024.](https://mlanthology.org/icml/2024/zhang2024icml-position/)BibTeX
@inproceedings{zhang2024icml-position,
title = {{Position: Social Environment Design Should Be Further Developed for AI-Based Policy-Making}},
author = {Zhang, Edwin and Zhao, Sadie and Wang, Tonghan and Hossain, Safwan and Gasztowtt, Henry and Zheng, Stephan and Parkes, David C. and Tambe, Milind and Chen, Yiling},
booktitle = {International Conference on Machine Learning},
year = {2024},
pages = {60527-60540},
volume = {235},
url = {https://mlanthology.org/icml/2024/zhang2024icml-position/}
}