Federal regulators, responding to Energy Secretary Chris Wright's request, just ordered grid operators to connect big power users faster, so the country can feed the data centers that AI runs on.

The push came because the United States is racing China for the lead in AI, and that race runs on computing power. The push unfortunately ran straight into state and local officials who want those data centers built anywhere but near them.

That fight is the visible edge of a larger one. Nationwide, lawmakers are moving to restrict AI based on speculative harms, and every time they do, the public is the one that pays.

Blocking or delaying a technology carries a real cost, but it never lands on a ledger, so no one is ever charged for it: the renter who never found a unit, the patient who lost access to care, the shopper who paid more and the consumers who must rely on foreign technologies. None of those people get a hearing, because a cost no one records costs no one an election.

The pattern is not new, but it’s one legislators keep repeating, and each time they target the technology rather than the harm.

The data-center fight is a clear case. Neighbors object over theoretical concerns about noise, water and power draw, and those complaints are loud even if not factually grounded.

The cost of blocking the buildout is quieter and lands on everyone else: Americans don’t stop needing AI, they just get it slower and pay more for it, while the computing power and the jobs that come with it move to countries that let it get built. Because the grid and the buildout cross state lines, these matters belong at the federal level, lest NIMBYism grinds innovation to a halt.

Algorithmic rental pricing, software that reads local market data and suggests rents, has also become the villain in a dozen statehouses. California, New York, and other states and localities have banned it outright or are considering banning it.

But what is the harm?

The software was never what set rents; it just reports on what the market is currently bearing given supply-and-demand trends in any one given area. The algorithm does not change those conditions. In fact, in Austin, Texas, rents fell despite the use of this AI because the city rapidly expanded its housing supply. Supply went up, and prices came down, all without any form of tech regulations.

Then there are the states barring AI from mental healthcare.

Last year, Nevada and Illinois prohibited AI systems from providing therapy. While parents and healthcare providers should ensure that teens do not use AI as a replacement for professional health consults, the laws ban the tool rather than address the harm. They do nothing for the person at 2 in the morning, wrestling with anxiety, who can no longer ask a general-purpose chatbot how to get through the night; even if the responses would be identical to those that the user might get from a book. The legislative response addresses a potential problem by taking a resource away from the people most likely to benefit from it.

None of this means AI gets a pass. Where a company breaks the law, enforce the law. The antitrust and consumer-protection statutes we already have reach most of these harms. Where a real harm appears, lawmakers should name it and match the remedy to it. What legislators should not do is ban a technology because the platform is an easier target for them than the conduct.

The approach is simple: before lawmakers restrict anything, two questions should come first. What specific harm are we addressing? And can the laws we already have handle it? Most of the time, the answer to the second is yes. The rest of the time, the work is to define the harm, not to ban the tool.

Caution about new technology feels responsible, but it is usually misguided, and when lawmakers get it wrong, the bill comes due for someone who never got a vote.

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ABOUT THE WRITER

Gregory S. McNeal is a professor of law and public policy at Pepperdine University. He wrote this for InsideSources.com.

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