"AI is transforming industries, fueling innovation, and addressing some of society's most urgent challenges. From humanoid robotics to drought management, AI's promise can feel boundless. Yet as demand for AI accelerates, so does the unprecedented expansion of warehouse-scale data centers packed with power-hungry computing servers. These massive facilities not only strain already stressed power grids but also create air pollution, including fine particulate matter, resulting in significant respiratory-related health consequences that are estimated to cost up to $20 billion per year in the United States by 2028."
"Shaolei Ren is an associate professor of electrical and computer engineering at the University of California, Riverside. His research broadly focuses on AI, energy, and society. His work on sustainable AI has informed international AI governance and ethics guidelines, contributed to K-12 educational materials, and driven industry innovations such as real-time ecological footprint reporting tools. is the Carl F. Braun Professor in the Department of Computing and Mathematical Sciences at Caltech."
"His research strives to make the networked systems that govern our world sustainable and resilient. He is best known for his work spearheading the design of algorithms for sustainable data centers, which has seen significant industry adoption, as well as his work on heavy tails, including his coauthored book, Adam Wierman The Fundamentals of Heavy Tails."
AI is driving rapid innovation across sectors, from humanoid robotics to drought management, and increasing demand for compute. The surge in AI workloads is prompting unprecedented construction of warehouse-scale data centers filled with power-hungry servers. These facilities strain stressed electrical grids and increase air pollution, including fine particulate matter, which causes respiratory health harms. Respiratory-related consequences are projected to impose economic costs up to $20 billion per year in the United States by 2028. Research on sustainable AI, energy-aware algorithms, and real-time ecological-footprint reporting has influenced governance guidelines, education, and industry practices while advancing solutions for more sustainable, resilient networked systems.
Read at Harvard Business Review
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