Is using AI bad for the environment?

What AI Actually Costs 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. That is settled by utilities and siting decisions, not by how often you open a chatbot.

1. The circulating numbers keep failing basic checks

Andy Masley taught physics for seven years before he started fact-checking 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. His 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 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 at that data center. Air cooling takes considerably more energy, so the likely result is higher emissions in exchange for water the municipal system was not short of. His corrected estimate puts the facility at about 3% of the municipal supply. 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. One of them pushed the cooling decision at a working data center the wrong way, which is what it costs to reason from a figure nobody checked.