Empire of AI is wildly misleading about AI water use
Deep Dives
Explore related topics with these Wikipedia articles, rewritten for enjoyable reading:
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Water footprint
13 min read
The article centers on the distinction between water withdrawal and water consumption for AI data centers. Understanding water footprint methodology—including the difference between blue, green, and grey water—provides essential context for evaluating claims about AI's environmental impact.
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Data center
13 min read
The article critiques claims about data center water and energy use. A technical understanding of how data centers actually work, including their cooling systems and infrastructure requirements, helps readers evaluate the competing claims about resource consumption.
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Cooling tower
11 min read
The distinction between consumptive and non-consumptive water use in the article relates directly to how cooling systems work at both data centers and power plants. Understanding evaporative cooling versus closed-loop systems explains why withdrawal numbers are so much larger than consumption numbers.
Note: the author took the time to respond to me below. While I’m very grateful, the materials she sent actually seems to confirm my main criticism and I’m now very confident a key number in the book is 1000x too large and needs to be revised. I summarize everything in my reply here.
I was taking a break from posting about AI and the environment, but after reading parts of Karen Hao’s book Empire of AI, I’ve stumbled on such wildly misleading claims that have so far gone unaddressed that I’ve felt the need to counter them here. Within 20 pages, Hao manages to:
Claim that a data center is using 1000x as much water as a city of 88,000 people, where it’s actually using about 0.22x as much water as the city, and only 3% of the municipal water system the city relies on. She’s off by a factor of 4500. This is the single largest error in any popular book that I’ve found on my own, and to my knowledge I’m the first person to notice it.
Imply that AI data centers will consume 1.7 trillion gallons of drinkable water by 2027, while the study she’s pulling from says that only 3% of that will be drinkable water, and 90% will not be consumed, and instead returned to the source unaffected.
Paint a picture of AI data centers harming water access in America, where they don’t seem to have caused any harm at all.
Frame Uruguay as using an unacceptable amount of water on industry and farming, where it actually seems to use the same ratio as any other country.
Frame the Uruguay proposed data center as using a huge portion of the region’s water where it would actually use ~0.3% of the municipal water system, without providing any clear numbers.
These are all the significant mentions of data centers using water in the book. Read in this light, the chapter becomes somewhat ridiculous, because the rest includes descriptions of brutal acts of torture and plunder under colonialism, and then frames data center water use as a continuation of that same colonialism. If instead you see data centers using water in other countries as part of a simple trade the countries are making to get more taxable industry in the area, and that doesn’t seem to harm water access, the central narrative thrust of the ...
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