Good morning. Today we’re looking at a major side effect of President Trump’s A.I. blitz.
Dirty dataYou don’t have to be a technophobe to hate data centers these days. And you don’t have to have much skin in the game, either. Even if there’s no blocky, gas-guzzling, million-square-foot behemoth coming soon to a neighborhood near you … you probably still loathe these bad boys. More than half of Americans say they’d support a national ban. Savvy politicians are converting the pitchforks into votes. In Michigan, where OpenAI is building a very big, very unpopular data center, a progressive organizer campaigning on a moratorium walloped two better-funded candidates in a House Democratic primary on Tuesday. That same day in Kansas, Democrats nominated a candidate for governor who has made opposing these facilities a core part of her platform. It makes political sense for them. Energy prices are high, driven by Trump’s war in Iran, and data centers make that worse. And the president has pushed A.I. companies to build out infrastructure faster than ever, arguing that to do otherwise would be to hand the race for A.I. dominance to China. Plenty of A.I. wonks agree with him. It takes years, in some cases, to connect data centers to the grid — too slow to meet the technology’s monstrous power demands. But Trump can read the room, and Americans are upset about data centers jacking up their electricity bills. (Nearly four in five say they’re worried about that, recent polling found.) His solution is to make A.I. companies build or buy their own energy infrastructure, so as not to strain the grids used by households and businesses. In March, he got a handful of tech bosses from Google, Microsoft and OpenAI (among others) to sign a nonbinding pay-for-power pledge. That hasn’t stopped prices from going up. The nation’s largest electrical grid operator said last month that data centers would heap billions in additional charges on consumers over the next three years. But the Trump administration’s plan has had a different effect, my colleague Hiroko Tabuchi reports: It’s driving a boom in gas-burning power plants. Nationwide, at least 82 gas-burning plants are being built or have been proposed to power data centers, according to the Environmental Integrity Project, a nonpartisan research organization. They’re easy to get up and running, and they’re cheap — especially in fossil-fuel-friendly places like Texas, which could soon overtake Virginia as the world’s largest data center market. Texas has been particularly aggressive in approving on-site power plants at data centers, fast-tracking permits with little public scrutiny or oversight. The competition for gas power is now so fierce that Elon Musk bought a company specializing in rapid-deployment gas and diesel turbines. Look at what it’ll take to power a new Meta data center in El Paso:
If built as planned, these plants could spew as much planet-warming carbon dioxide in a year as roughly half of all the passenger vehicles in the country. Read more about the air pollution tied to Trump’s plan for A.I. dominance. In other A.I. news …Chinese A.I. models have become a hot commodity in Africa, where thrifty developers are looking for the best systems at the lowest possible prices. Unlike the models put out by top American A.I. companies — which are “closed” and charge fees — the “open-source” Chinese ones are publicly available free. Read about how entrepreneurs in Kenya, Uganda, Nigeria and Ghana are creating a new market for Chinese A.I. Having an A.I. boss can be a lot like working for a forgetful teddy bear. At least that’s what employees said after researchers let an A.I. agent run a San Francisco store for four months. “She is probably the most lenient boss I have ever had,” said one of three humans hired by Luna, the A.I. agent. Luna approved every employee’s request for time off, even if it meant the store had to close. A little more spine might not hurt. Google Earth released its own generative A.I. feature — which, for about 24 hours last week, allowed the creation of deepfake aerial images. The company had intended to unleash users’ imaginations. (“What did my neighborhood look like 100 years ago?”) Instead, people showed how easily it could be used to generate very realistic nuclear power plants, refugee camps, burned forests, flooded cities and even a fatal car crash.
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