Tackling Climate Change with Machine Learning

In plain words: Machine learning experts mapped where their tools could cut greenhouse gases or help people cope with a changing climate, from smarter grids to disaster response. They found gaps these tools could fill if built with experts in those fields, and listed research and business ideas.

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.

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, et al.
arXiv:1906.05433 · cs.CY, cs.AI, cs.LG, stat.ML · submitted Jun 10, 2019 · updated Nov 5, 2019
abstract · pdf · html · For additional resources, please visit the website that accompanies this paper: https://www.climatechange.ai/