The rapid expansion of artificial intelligence (AI) is poised to create significant environmental and health challenges, according to a groundbreaking study by researchers from the University of California, Riverside, and the California Institute of Technology. The study, titled "The Unpaid Toll: Quantifying the Public Health Impact of AI," reveals alarming projections about the air pollution consequences of AI's escalating energy consumption.

By 2030, electricity generation for AI data centers could lead to an additional 1,300 premature deaths annually, marking a 36% increase in asthma-related fatalities. The researchers examined emissions of nitrogen dioxide, sulfur dioxide, and fine particulate matter from power plants and diesel generators associated with AI facilities.

The study estimates that by 2030, AI-related electricity consumption could trigger approximately 600,000 asthma-symptom cases annually. The public health burden is projected to reach $20 billion, surpassing the health costs of coal-based U.S. steelmaking and rivaling emissions from California's entire automobile fleet.

Particularly concerning is the impact of diesel generators used for backup power in data centers. In Virginia, home to a high concentration of data centers, these generators could cause between 130 to 190 additional deaths annually if operating at full capacity. The health effects extend beyond state borders, affecting neighboring regions and disproportionately impacting economically disadvantaged communities.

The researchers call for greater transparency from tech giants leading large-language-model training, noting that companies like Amazon, Google, Microsoft, and Meta do not currently detail the air pollution impacts of their AI operations in annual sustainability reports.

This study underscores the urgent need for the AI industry to address its growing environmental footprint. As AI continues to evolve and expand, balancing technological advancement with environmental responsibility will be crucial for sustainable development in the energy sector.