Tackling Climate Change with Machine Learning

Peetak Mitra · Maria João Sousa · Mark Roth · Jan Drgona · Emma Strubell · Yoshua Bengio



The focus of this workshop is the use of machine learning to help address climate change, encompassing mitigation efforts (reducing greenhouse gas emissions), adaptation measures (preparing for unavoidable consequences), and climate science (our understanding of the climate and future climate predictions). Specifically, we aim to: (1) showcase high-impact applications of ML to climate change mitigation, adaptation, and climate science, (2) discuss related research directions to which the ML community can contribute, (3) brainstorm mechanisms to scale early academic research to successful, viable deployments, and (4) encourage fruitful collaboration between the ML community and a diverse set of researchers and practitioners from climate change-related fields. Building on our past workshops on this topic, this workshop particularly aims to explore the theme of climate change-informed metrics for AI, focusing both on (a) the domain-specific metrics by which AI systems should be evaluated when used as a tool for climate action, and (b) the climate change-related implications of using AI more broadly.

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