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Tackling Climate Change with Machine Learning

Created by MG96

External Public cs.CY cs.AI cs.LG stat.ML

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Citations
704
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810
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Authors

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 Luccioni Tegan Maharaj Evan D. Sherwin S. Karthik Mukkavilli Konrad P. Kording Carla Gomes Andrew Y. Ng Demis Hassabis John C. Platt Felix Creutzig Jennifer Chayes Yoshua Bengio
Project Resources

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Abstract

Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning 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 machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.

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