Artificial intelligence (AI) is increasingly being used to help tackle climate change, from optimizing electrical grids to emulating climate models and monitoring biodiversity. As such applications grow, however, it is becoming clear that high-powered AI tools often fall short. Methods designed using standard benchmarks may fail to capture the constraints or objectives of specific real-world problems, while a “one size fits all” approach ignores information that can be leveraged in specific use cases. In this talk, we show how application-driven design can lead to AI algorithms that are highly impactful in the fight against climate change. We will also consider ways that AI is used in ways that contribute to climate change, and how to better align the use of AI overall with climate goals.
David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila Quebec AI Institute. He is a Co-founder and Chair of Climate Change AI and serves as Scientific Co-director of Sustainability in the Digital Age and co-lead of the Global Climate Center on AI and Biodiversity Change (ABC). Dr. Rolnick received his Ph.D. in Applied Mathematics from MIT. He is an AI2050 Fellow and a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review’s 2021 list of “35 Innovators Under 35.”
