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
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 analyses of
international frameworks, based on (modifications of) RICE-N, an AI-driven
integrated assessment model (IAM). In particular, RICE-N supports modeling
regional decision-making using AI agents. Furthermore, the IAM then models the
climate-economic impact of those decisions into the future.
  Whereas the first track focused only on performance metrics, the proposals
submitted to the second track were evaluated both quantitatively and
qualitatively. The quantitative evaluation focused on a combination of (i) the
degree of mitigation of global temperature rise and (ii) the increase in
economic productivity. On the other hand, an interdisciplinary panel of human
experts in law, policy, sociology, economics and environmental science,
evaluated the solutions qualitatively. In particular, the panel considered the
effectiveness, simplicity, feasibility, ethics, and notions of climate justice
of the protocols. In the third track, the participants were asked to critique
and improve RICE-N.