AI Regulation Has a Fundamental Problem. We’re Regulating Based On What Might Happen.

There is a problem plaguing America’s approach to artificial intelligence, from data centers and the AI industry itself to tax policy and far beyond. It is not rooted in any single policy. Rather, it lies in the how: the way policymakers are choosing to approach AI in the first place. 

According to Mani Basharzad, a research associate at the Institute of Economic Affairs and an Asia Freedom Fellow at the London School of Economics, the central problem is that too many people want to regulate AI based on the effects it could have, rather than the effects it is having. The distinction matters, not only because one approach is more practical, but because too much legislation is being built around worst-case scenarios that are increasingly proving not to come true.

AI regulation is being built around predictions, not evidence. @ManiBasharzad argues we should be careful not to kill tomorrow’s innovation trying to prevent problems that haven’t happened. pic.twitter.com/uhTkL0kKaT

— Foundation for Economic Education (@feeonline) August 12, 2026

Attitudes toward the AI industry increasingly appear rooted in a left-wing impulse: judging policy by its intentions rather than its effects. Conservatives, by contrast, should focus on the practical consequences of AI, not the theoretical future people see in their minds. After all, how can policymakers reliably assess AI’s real-world effects when the industry has not yet had sufficient time to fully integrate its products and services into the American economy? 

Basharzad points to a viral open letter, titled “We Must Act Now,” that calls for immediate action against AI. Its signatories include an unusual mix of economists, policymakers, and academics of all political persuasions, including Joseph Stiglitz, Paul Krugman, Alex Tabarrok, Tyler Cowen, and Niall Ferguson. 

Their concerns center on three questions: how powerful AI could become over time; how it could reshape the economy on a scale exceeding the Industrial Revolution leading to real economic displacement; and whether policymakers should impose guardrails immediately, before it is too late. Yet each point rests on predictions about AI’s future effects, effects that remain impossible to measure with great accuracy today.

The threats posed by AI, according to Basharzad, are surprisingly thin on any evidence beyond, of course, public references to fictional dystopian futures. Even in economic terms, he points out that, in response to the letter, Stanford economist John Cochrane remarked: “You see AI everywhere, except in productivity and labor statistics.” 

This is because AI has failed to bring about the massive economic displacement that many expected. In fact, many predictions have yielded the opposite effects. AI data centers are improving the towns in which they are built: electricity prices are falling, home values are rising, tax revenue is increasing, and, more broadly, entry-level jobs are vastly expanding at companies adopting AI.

Basharzad argues that, amid increasing calls for government to “act now,” economists in particular must become more skeptical. Conservatives, as a political group, should share that skepticism. Our instinct should not be to regulate or control. It should be faith in the free market, and faith in the adaptive and innovative capacities of our fellow man. After all, economic failures are typically the result of government policy, not technology. Why should this time be any different?

Basharzad's solution? "We should do nothing about AI."

The more we sit back, observe, study, and watch the data pile up, the more capable we will be of taking targeted approaches to the very real problems that are bound to arise. We can also prevent the Left from turning AI into a useful bipartisan issue in upcoming elections. 

We are supposed to oppose the regulatory instinct of the Left. Yet, it appears that many on our own side have come to embrace it. Let’s force that tide to begin to turn.

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