Tackling Climate Change with Machine Learning
ACM Computing Surveys2022Vol. 55(2), pp. 1–96
Citations Over TimeTop 10% of 2022 papers
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman‐Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan David Sherwin, S. Karthik Mukkavilli, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio
Abstract
Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the ML community to join the global effort against climate change.