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Tackling Climate Change with Machine Learning

  • 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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Metadaten
Document Type:Article
Language:English
Author(s):Lynn KaackORCiD, David Rolnick, Priya L. Donti, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew S. Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra S. Luccioni, Tegan Maharaj, Evan D. Sherwin, Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio
Parent Title (English):ACM Computing Surveys
Publication year:2022
Publishing Institution:Hertie School
First Page:1
Last Page:96
Related URL:https://dl.acm.org/doi/10.1145/3485128
DOI:https://doi.org/10.1145/3485128
Release Date:2021/10/07
Volume:55
Issue:2
Article Number:42
Licence of document (German):Metadaten / metadata
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