Is using AI bad for the environment?
Not at the level of your own use, and many of the figures in circulation are wrong by orders of magnitude. The aggregate question is the one that bites: how much power the data-center buildout draws and where that power comes from. Utilities and siting decisions move that far more than how often any one person opens a chatbot.
AI Energy & Data CentersAI Infrastructure
1. The circulating numbers keep failing basic checks
Andy Masley, who taught physics for seven years, fact-checks AI environmental claims, and the largest error he has found personally is a water figure in the book Empire of AI that is off by a factor of about 4,500. One of the two errors behind it: the author’s source had mixed up liters and cubic meters, and a cubic meter is a thousand liters. The published figure implied that each resident of an 88,000-person community outside Santiago was using about a tenth of a liter of water a day, for everything. That is a number anyone could have sanity-checked, and for six months nobody did. Same chapter, second problem: the claim that AI would consume half as much water as all of Britain by 2027, where the study being cited puts the figure at roughly 5%.
2. One prompt is a rounding error in your day
Masley’s comparisons, for the conversation you actually have at a party: a single prompt probably emits about what printing a fifth of a page of a book does, or running a space heater for half a second, or driving four feet. On water, his estimate is roughly one eight-hundred-thousandth of your daily use. Anything you do on a computer carries a small climate cost relative to almost everything else in a day, which is why “I ran a thousand searches today” was never a confession.
3. Overstating the number carries its own environmental cost
Masley’s hedged read of what followed the Santiago coverage: activist pressure, possibly built on the bad figure, appears to have pushed Google toward air cooling instead of water cooling for that proposed data center, which has not been built. Air cooling takes considerably more energy, so he suspects the redesign would mean higher emissions in exchange for saving water. His corrected estimate puts the facility at about 25% of the water in one section of Santiago, but about 3% of the municipal supply. As of September 2026, Google says it has not decided whether to go ahead with the redesigned, air-cooled project. Environmental policy is a series of trade-offs, and you cannot price a trade-off with a number that is wrong by three orders of magnitude.
4. The constraint that binds is the grid
Cisco’s Jeetu Patel names infrastructure as the first hard constraint on AI: not enough power, compute, network bandwidth, or data-center capacity to meet demand. His framing is that infrastructure is the input and intelligence is the output, and the goal is generating tokens at the lowest kilowatt and the lowest dollar. That problem is expensive, contested, and unresolved. It is also a different problem from whether you should feel bad for sending a prompt.
Why it matters
Individual guilt and grid policy are two different conversations, and running them together costs you both. Bad numbers lose more than an argument. On Masley’s read, one of them may have pushed the cooling design of a proposed data center the wrong way, which is what it costs to reason from a figure nobody checked.
Hear it from the guest
“The number that she gave for this community basically implied that the average person there was consuming about point one liters a day, which is something like a fifth of a single bottle of water”
“Sending a prompt probably emits as much as printing a fifth of a single page of a book, or it's like running a space heater for about half a second, or driving your car for about four feet or something like that.”
Quotes lightly edited to remove filler words.
From the conversation
This explainer is drawn from these episodes — each carries its full transcript.
