Not Cool Ep 16: Tackling Climate Change with Machine Learning, part 1

How can artificial intelligence, and specifically machine learning, be used to combat climate change? In an ambitious recent report, machine learning researchers provided a detailed overview of the ways that their work can be applied to both climate mitigation and adaptation efforts. The massive collaboration, titled “Tackling Climate Change with Machine Learning,” involved 22 authors from 16 of the world's top AI institutions.  On Not Cool episodes 16 and 17, Ariel speaks directly to some of these researchers about their specific contributions, as well as the paper's significance more widely. Today, she’s joined by lead author David Rolnick; Priya Donti, author of the electricity systems chapter; Lynn Kaack, author of the transportation chapter and co-author of the buildings and cities chapter; and Kelly Kochanski, author of the climate prediction chapter. David, Priya, Lynn, and Kelly discuss the origins of the paper, the solutions it proposes, the importance of this kind of interdisciplinary work, and more.

Topics discussed include:

-Translating data to action

-Electricity systems

-Transportation

-Buildings and cities

-Climate prediction

-Adaptation

-Demand response

-Climate informatics

-Accelerated science

-Climate finance

-Responses to paper

-Next steps

-Challenges