The Unpaid Toll: Quantifying and Minimizing the Public Health Impact of AI

Abstract: The surging demand for AI has led to a rapid expansion of energy-intensive data centers, impacting the environment through escalating carbon emissions and water consumption. While significant attention has been paid to AI’s growing environmental footprint, the public health burden, a hidden toll of AI, has been largely overlooked. Specifically, from chip manufacturing to data center operations, AI’s lifecycle contributes significantly to air quality degradation over a large area through emissions of cross-state criteria air pollutants, including fine particulate matter. These emissions pose serious public health risks, yet they remain absent from today’s AI risk assessments.

In this talk, I will first present a principled methodology to model pollutant emissions across AI’s lifecycle and quantify the public health impacts. The findings reveal that the total public health burden of U.S. AI data centers in 2030 is valued at up to more than $20 billion per year, comparable to that of California’s on-road emissions. Then, I will present Health-informed AI, a new research direction that: (1) mitigates AI’s adverse health effects while promoting public health equity; and (2) leverages AI to help people make health-informed decisions to improve public health.

Bio: Shaolei Ren is an Associate Professor of Electrical and Computer Engineering at the University of California, Riverside. His research strives to build socially and environmentally responsible computing, with a broad emphasis on AI, sustainability, and public health. His work has generated societal impacts, including influencing AI policies adopted in governance guidelines by international organizations and governments such as the United Nations, UNESCO, WHO, and the Government of Canada, and driving industry innovations such as the first real-time water footprint reporting tool for computing. It has also increased public awareness of responsible AI, with coverage in over 1,000 major media outlets across ~100 countries including The Associated Press, The Wall Street Journal, and The Washington Post. He is a recipient of the NSF CAREER Award (2015) and several paper awards, including at ACM e-Energy (2024, 2016) and IEEE ICC (2016). He earned his Ph.D. from the University of California, Los Angeles.