AI is revolutionizing various sectors, promoting creativity, and tackling critical societal issues. The potential of AI ranges from human-like robots to managing droughts, offering seemingly limitless opportunities. However, the surge in AI demand is accompanied by the rapid growth of large data centers filled with energy-intensive servers. These vast facilities not only strain already burdened power networks but also generate air pollution, including harmful particles, leading to considerable respiratory health effects that could cost up to $20 billion annually in the US by 2028.

Shaolei Ren, an associate professor at the University of California, Riverside specializing in electrical and computer engineering, conducts research on AI, energy, and society. His emphasis on sustainable AI has influenced global AI governance and ethical standards, enriched educational materials for K–12 students, and inspired innovations in industries like real-time ecological impact assessment tools.

Adam Wierman holds the Carl F. Braun Professorship in Computing and Mathematical Sciences at Caltech. His research endeavors aim to make our interconnected systems sustainable and robust. He is renowned for pioneering algorithms for eco-friendly data centres, widely adopted by industry, as well as his contributions to heavy-tailed distributions highlighted in his collaborative publication, The Fundamentals of Heavy Tails.