AI For Global Climate Cooperation 2023 Competition Proceedings
Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa,, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng

TL;DR
This paper presents the proceedings of the 2023 AI for Global Climate Cooperation competition, which aimed to develop AI-driven international climate frameworks using simulations to promote collaboration, mitigate climate change, and balance economic growth.
Contribution
It introduces a novel interdisciplinary competition utilizing AI and climate-economic modeling to design and evaluate international climate cooperation protocols.
Findings
Proposals improved climate mitigation and economic productivity metrics.
Qualitative assessments emphasized effectiveness, feasibility, and ethics of proposed protocols.
The competition fostered innovative AI-based approaches to global climate policy design.
Abstract
The international community must collaborate to mitigate climate change and sustain economic growth. However, collaboration is hard to achieve, partly because no global authority can ensure compliance with international climate agreements. Combining AI with climate-economic simulations offers a promising solution to design international frameworks, including negotiation protocols and climate agreements, that promote and incentivize collaboration. In addition, these frameworks should also have policy goals fulfillment, and sustained commitment, taking into account climate-economic dynamics and strategic behaviors. These challenges require an interdisciplinary approach across machine learning, economics, climate science, law, policy, ethics, and other fields. Towards this objective, we organized AI for Global Climate Cooperation, a Mila competition in which teams submitted proposals and…
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Taxonomy
TopicsClimate Change Policy and Economics
