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.
