Litcius/Paper detail

Tackling Climate Change with Machine Learning

Lynn H. Kaack, David Rolnick, Priya L. Donti, 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, Mukkavilli, Karthik, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio

2022OPUS 4 (Zuse Institute Berlin)870 citationsDOI

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.

Topics & Concepts

Climate changeWonderComputer scienceGreenhouse gasJoin (topology)HumanityGlobal warmingData sciencePolitical sciencePsychologyLawCombinatoricsEcologySocial psychologyMathematicsBiologyAir Quality Monitoring and ForecastingTraffic Prediction and Management TechniquesEnergy Load and Power Forecasting