The Unpaid Toll: Quantifying the Public Health Impact of AI
arxiv.org
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, AI's lifecycle, from chip manufacturing to data center operation, significantly degrades air quality through emissions of criteria air pollutants such as fine particulate matter, substantially impacting public health. This paper introduces a methodology to model pollutant emissions across AI's lifecycle, quantifying the public health impacts. Our findings reveal that training an AI model of the Llama3.1 scale can produce air pollutants equivalent to more than 10,000 round trips by car between Los Angeles and New York City. The total public health burden of U.S. data centers in 2030 is valued at up to more than $20 billion per year, double that of U.S. coal-based steelmaking and comparable to that of on-road emissions of California. Further, the public health costs unevenly impact economically disadvantaged communities, where the per-household health burden could be 200x more than that in less-impacted communities. We recommend adopting a standard reporting protocol for criteria air pollutants and the public health costs of AI, paying attention to all impacted communities, and implementing health-informed AI to mitigate adverse effects while promoting public health equity.

Also covered in Futurism from where I quote:

And unfortunately, the public cost of AI doesn’t end there. New research by academics at UC Riverside and Caltech is warning that AI data centers are also taking a massive toll on human health, in the form of diseases like cancer and asthma.

The issue of air pollution is easy to overlook, because in most cases, the data centers are powered by local coal burning plants, which tend to be disproportionately located near low-income and working-class communities. It also seems wherever they go, AI data centers drive up the local cost of electricity, saddling their host communities with a burden not shared by the rest of the country, let alone by Silicon Valley or big tech’s Wall Street investors.

AI’s air pollution impacts can be best summarized like the nuclear meltdown of Chernobyl — the deadly toxins spread far and wide with no respect for distance, affecting those in, around, and far away from the actual data center itself.

“The data centers pay local property taxes to the county where they operate,” Ren said in a press blurb about the study. “But this health impact is not just limited to a small community. Actually, it travels across the whole country, so those other places are not compensated at all.”

A Google spokesperson said that the paper “promotes an inaccurate emissions estimate generated under false pretenses, undermining the progress of clean energy resource growth and creating a false narrative of health harms.”