Because contrails create more than a third of global aviation’s carbon emissions, “if the whole aviation industry took advantage of this single A.I. breakthrough,” says Dave Patterson, a computer-science professor emeritus at UC Berkeley and a Google researcher, “this single discovery would save more CO₂ than the CO₂ from all A.I. in 2020.”

Patterson’s analysis predicts that A.I.’s carbon footprint will soon plateau and then begin to shrink, thanks to improvements in the efficiency with which A.I. software and hardware use energy. One reflection of that efficiency improvement: as A.I. usage has increased since 2019, its percentage of Google data-center energy use has held at less than 15 percent. And while global internet traffic has increased more than twentyfold since 2010, the share of the world’s electricity used by data centers and networks increased far less, according to the IEA.

However, data about improving efficiency doesn’t convince some skeptics, who cite a social phenomenon called “Jevons paradox”: Making a resource less costly sometimes increases its consumption in the long run. “It’s a rebound effect,” Ren says. “You make the freeway wider, people use less fuel because traffic moves faster, but then you get more cars coming in. You get more fuel consumption than before.” If home heating is 40 percent more efficient due to A.I., one critic recently wrote, people could end up keeping their homes warmer for more hours of the day.

“A.I. is an accelerant for everything,” Dodge says. “It makes whatever you’re developing go faster.” At the Allen Institute, A.I. has helped develop better programs to model the climate, track endangered species, and curb overfishing, he says. But globally A.I. could also support “a lot of applications that could accelerate climate change. This is where you get into ethical questions about what kind of A.I. you want.”

If global electricity use can feel a bit abstract, data centers’ water use is a more local and tangible issue—particularly in drought-afflicted areas. To cool delicate electronics in the clean interiors of the data centers, water has to be free of bacteria and impurities that could gunk up the works. In other words, data centers often compete “for the same water people drink, cook, and wash with,” says Ren.

In 2022, Ren says, Google’s data centers consumed about 5 billion gallons (nearly 20 billion liters) of fresh water for cooling. (“Consumptive use” does not include water that’s run through a building and then returned to its source.) According to a recent study by Ren, Google’s data centers used 20 percent more water in 2022 than they did in 2021, and Microsoft’s water use rose by 34 percent in the same period. (Google data centers host its Bard chatbot and other generative A.I.s; Microsoft servers host ChatGPT as well as its bigger siblings GPT-3 and GPT-4. All three are produced by OpenAI, in which Microsoft is a large investor.)

As more data centers are built or expanded, their neighbors have been troubled to find out how much water they take. For example, in The Dalles, Oregon, where Google runs three data centers and plans two more, the city government filed a lawsuit in 2022 to keep Google’s water use a secret from farmers, environmentalists, and Native American tribes who were concerned about its effects on agriculture and on the region’s animals and plants. The city withdrew its suit early last year. The records it then made public showed that Google’s three extant data centers use more than a quarter of the city’s water supply. And in Chile and Uruguay, protests have erupted over planned Google data centers that would tap into the same reservoirs that supply drinking water.

Most of all, researchers say, what’s needed is a change of culture within the rarefied world of A.I. development. Generative A.I.’s creators need to focus beyond the technical leaps and bounds of their newest creations and be less guarded about the details of the data, software, and hardware they use to create it.

Some day in the future, Dodge says, an A.I. might be able—or be legally obligated—to inform a user about the water and carbon impact of each distinct request she makes. “That would be a fantastic tool that would help the environment,” he says. For now, though, individual users don’t have much information or power to know their A.I. footprint, much less make decisions about it.

“There’s not much individuals can do, unfortunately,” Ren says. Right now, you can “try to use the service judiciously,” he says.