Climate Change AI

The Climate Change AI Summer School is designed to educate and prepare participants with a background in artificial intelligence AI and/or a background in a climate change-related field to tackle major climate problems using AI. Our 2023 session consisted of two independent components an open-to-all virtual program which was held between June-August 2023 and drew 10K registered participants and a selective in-person program which was held from August 14-18, 2023 in Montreal, Canada and hosted 30 participants. Courses were conducted by members of Climate Change AI and world-renowned experts in AI and climate change.

CCAIs conferences and events promote education, networking, and knowledge-sharing. In 2023, we organized one-day workshops at top AI and machine learning venues ICLR, AAAI Fall Symposium, and NeurIPS to facilitate discussion and exchange on topics at the intersection of AI and climate change. These workshops drew several hundreds of participants, and collectively featured over 200 accepted research papers.

Artificial intelligence AI and machine learning ML offer a powerful suite of tools to accelerate climate change mitigation and adaptation across different sectors. However, the lack of high-quality, easily accessible, and standardized data often hinders the impactful use of AI/ML for climate change applications. In this project, Climate Change AI aims to identify and catalog critical data gaps that impede AI/ML applications in addressing climate change, and lay out pathways for filling these gaps. In particular, we identify candidate improvements to existing datasets, as well as wishes for new datasets whose creation would enable specific ML-for-climate use cases. An initial catalog of data gaps has been published on our website. We hope that researchers, practitioners, data providers, funders, policymakers, and others will join the effort to address these critical data gaps.