https://themarkup.org/hello-world/2023/07/08/ai-environmental-equity-its-not-easy-being-green

A few months ago, I spoke with Shaolei Ren, as associate professor of computer science at University of California, Riverside, and his team about their research into the secret water footprint of AI. Recently, Ren and his team studied how AI’s environmental costs are often disproportionately higher in some regions than others, so I spoke with him again to dig into those findings.

His team, which includes UC Riverside Ph.D. candidates Pengfei Li and Jianyi Yang, and Adam Wierman, a professor in the Department of Computing and Mathematical Sciences (CMS) at the California Institute of Technology, looked into a path toward more equitable AI through what they call “geographical load balancing.” Specifically, this approach attempts to “explicitly address AI’s environmental impacts on the most disadvantaged regions.”

Ren and I talked about why it’s not easy being green and what tangible steps cloud service providers and app developers could take to reduce their environmental footprint.