Mitigating the Public Health Impacts of AI Data Centers

This Harvard Business Review article examines how the rapid expansion of AI data centers is creating significant public health consequences through air pollution, including fine particulate matter (PM2.5) and nitrogen dioxide (NO2). The authors estimate respiratory-related health costs could reach $20 billion per year in the United States by 2028. Written by researchers from UC Riverside and Caltech, the piece highlights that data centers not only strain power grids but also contribute to criteria air pollutants with well-established causal links to adverse health outcomes, particularly for vulnerable populations.