Dec 14, 2020

Jennifer Chayes at NeurIPS ’20: ML Community Must Work With Interdisciplinary Experts

From Synced Review

NeurIPS 2020 | Machine Learning Vs Climate Change

Climate change is one of the greatest threats humans have ever faced, with increasingly severe consequences feared as sea levels rise, ecosystems falter, and natural disasters multiply. Tackling climate change is a huge and complex challenge, where it’s hoped that AI-powered efforts can play an equally huge and beneficial role...

It’s crucial for the ML community to work with disciplinary experts to identify the urgent problems and figure out where and how to use ML as tools to implement climate change strategies, says Jennifer Chayes, associate provost of the Division of Computing, Data Science, and Society, and dean of the School of Information at UC Berkeley. Chayes was one of the workshop’s keynote speakers.

“I started out as a mathematical physicist, and we would take physics problems from the world and we would abstract them until they were gorgeous models, but that’s not the way we’re going to tackle climate change,” Chayes explains. When researchers deal with climate problems — as is the case with many urgent challenges facing society — they usually don’t have sufficient clean datasets. That’s where ML can really help...


Last updated:

January 5, 2021