Prompts now, pollutants later: Report claims data centers are harming the environment to the tune of $25 billion and inducing a debt on the health of current and future generations | Daily Reports Online
- Data centers and their energy requirements are causing pollution
- This pollution is causing knock-on costs for healthcare and the environment
- A cost of as much as $25 billion is theorized, but it could be higher
The surge of AI and its demand for data centers could be costing the US economy $25 billion in environmental damage and causing serious health complications for those living in the vicinity of data centers.
These figures come from a new working paper written by Nicholas Z. Muller, an economist at Carnegie Mellon University, and published by the National Bureau of Economic Research.
The paper examined around 2,800 operational data centers on their energy requirements, and examined the impact of additionally generated air pollutants and greenhouse gases on the environment, the health of US citizens, and its cost on the economy.
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Lung disease, heart conditions, premature mortality
In the paper, Muller calculates the $25 billion gross external damages (GED) figure by calculating not only the artificial intelligence usage within data centers (to which he attributes a figure of $3.7 billion), but also the wider, indirect costs of the pollutants caused by generating the necessary energy to power data centers.
Muller’s paper theorizes that the planned expansion of data center construction could increase associated damages by up to 85% in the near term.
These costs include the additional burden on healthcare facilities and day-to-day medical requirements by local residents, which Muller attributes to the negative effects of exposure to the airborne pollutantPM2.5, which can cause lung disease, heart conditions, and higher rates of premature mortality.
There are also wider social costs associated with pollutants and greenhouse gasses that are yet to materialize, but nonetheless are being emitted from the additional energy sources being constructed or revived to fuel the boom in demand for energy.
The Trump administration’s stance against renewable energy sources means that legislation has been put forward to revive a number of previously decommissioned fossil fuel power plants in order to provide for the extra demand, and in turn are releasing more pollutants and greenhouse gases.
These external costs are not borne by the tech companies funding the construction of data centers, who instead enjoy significant tax breaks for their investments in new construction projects, leading to less tax revenue to fund the construction of the additional infrastructure needed to power and transfer electricity to power data centers.
The Trump administration did introduce the Ratepayer Protection Pledge to bind the additional costs of energy production to tech companies, but the pledge is entirely voluntary and bears very little in the way of accountability, timelines, or provisions. Some communities in the US are now experiencing skyrocketing energy costs due to the energy demands of data centers.
There are also the issues with the employment provided by data centers. While the initial construction may provide a boost in jobs, the effect is largely temporary. Many data centers are automated and require little supervision to operate.
Muller’s paper does calculate that the economic costs of environmental damage and healthcare related costs are small when compared to the potential productivity gains produced by AI, but residents living in the vicinity of data centers may disagree with this assessment.
There is now a growing anti-data center sentiment across the US, with numerous grass-root, local resident groups opposing the construction of data centers, leading to major project delays and cancellations. There also appears to be a general downward trend in the opinion of AI, with up to 71% of US citizens believing that AI could cause permanent job loss, and almost half (47%) believing it will have a negative effect on humanity.
Via Fortune
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