Thirsty Bots Are Drinking Our Scarce Water

In various Noema essays, we have sought to underscore the material basis of the information/clean energy economy. Far from the myth of de-materialization, the extraction and use of resources — from cobalt, copper and rare earth elements for energy storage batteries to burning fossil fuels to power data server farms — is no less than that of the maligned industrial smokestack era.

Now, we are learning that generative AI is not just sucking up our abundant content, but also drinking our scarce water.

According to a new study by University of California Riverside researchers, roughly two weeks of training for GPT-3 consumed about 700,000 liters of freshwater. The global AI demand is projected by 2027 to account for 4.2-6.6 billion cubic meters of water withdrawal, which is more than the total annual water withdrawal of Denmark or half of the United Kingdom.