AI created as much carbon pollution this year as New York City and guzzled up as much H20 as people consume globally in water bottles, according to new estimates.
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To crunch these numbers, de Vries-Gao built on earlier research that found that power demand for AI globally could reach 23GW this year — surpassing the amount of electricity used for Bitcoin mining in 2024. While many tech companies divulge total numbers for their carbon emissions and direct water use in annual sustainability reports, they don’t typically break those numbers down to show how many resources AI consumes. De Vries-Gao found a work-around by using analyst estimates, companies’ earnings calls, and other publicly available information to gauge hardware production for AI and how much energy that hardware likely uses.
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Once he figured out how much electricity these AI systems would likely consume, he could use that to forecast the amount of planet-heating pollution that would likely create. That came out to between 32.6 and 79.7 million tons annually. For comparison, New York City emits around 50 million tons of carbon dioxide annually.
Data centers can also be big water guzzlers, an issue that’s similarly tied to their electricity use. Water is used in cooling systems for data centers to keep servers from overheating. Power plants also demand significant amounts of water needed to cool equipment and turn turbines using steam, which makes up a majority of a data center’s water footprint. The push to build new data centers for generative AI has also fueled plans to build more power plants, which in turn use more water and (and create more greenhouse gas pollution if they burn fossil fuels). AI could use between 312.5 and 764.6 billion liters of water this year, according to de Vries-Gao. That reaches even higher than a previous study conducted in 2023 that estimates that water use could be as much as 600 billion liters in 2027.