
Ever since artificial intelligence became a topic of popular conversation, the environmental cost of all these large-language models and the massive server farms that make them possible has been the subject of much concern. Every week or two, it seems, there is another article about the vast appetite these systems have for both power and water, the greenhouse-gas emissions, etc. and the impact on the environment. So I found it interesting to read Google’s assessment of these factors in a recently published study entitled “Measuring the environmental impact of delivering AI at Google Scale.” The company also wrote a blog post summarizing some of the numbers, in which it said that the average Gemini prompt “uses 0.24 watt-hours of energy, emits 0.03 grams of carbon dioxide equivalent, and consumes 0.26 milliliters – or about five drops – of water.” The overall per-prompt energy impact, according to Google’s scientists, is “equivalent to watching television for less than nine seconds.”
Since Google runs Gemini and obviously wants to understate how much power and water it uses, you might be skeptical of these results, as I (and others) were when the paper was released. The Verge, for example, wrote a piece quoting a number of experts who said that the Google study was misleading because it “omits some key data.” What key data? If you read the article, it says that Google only looked at the direct water and power use of its server farms and related AI equipment – that is, the amount of water and electricity that these systems consumed while running Gemini queries – as wellrather than looking at the indirect use. That would include water consumed by power companies that generate the electricity to power these data centers, whether it’s water to drive electrical turbines or to cool gas or nuclear power systems. From the Verge article:
“They’re just hiding the critical information,” says Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside. “This really spreads the wrong message to the world.” Ren has studied the water consumption and air pollution associated with AI, and is one of the authors of a paper Google mentions in its study. A big issue experts flagged is that Google omits indirect water use in its estimates. Its study included water that data centers use in cooling systems to keep servers from overheating. As a result, with Google’s estimate, “You only see the tip of the iceberg,” says Alex de Vries-Gao, founder of the website Digiconomist and a PhD candidate at Vrije Universiteit Amsterdam Institute for Environmental Studies who has studied the energy demand of data centers.
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