Every now and then you read something that seems so fundamentally misguided that it serves as a template how not to think about the economy. In this case it is the guest essay by a former Biden economic official in The New York Times. Its basic premise: “A.I. is vacuuming up so much of our land, talent, semiconductor chips, building materials — and, above all, so much of our money, that it is beginning to crowd out the rest of the economy. In other words, A.I. isn’t merely compensating for the weakness in the rest of the economy. It is, at least in part, causing it.”

So, why is AI a problem and what should be done? AI is a problem primarily because:

Jason Thomas, research head at the investment firm Carlyle, noted in a January report that data center investment may be swelling to the point that it could consume virtually all the private money available for new, non-housing investments. Researchers, economists and other market analysts are ringing the same alarm. They are particularly worried that the deluge of investment, much of which is plowed into data centers, is beginning to starve the rest of the economy of the money it needs (to say nothing of the talent and physical materials). The money flowing to A.I. is bypassing some of our country’s highest priorities.

How does capital get allocated in financial markets? To the highest bidder. Capital will flow to the highest, risk-adjusted rate of return. If the expected return on AI exceeds other private investments, the capital will flow there. If these other activities are bigger priorities, why don’t they show a higher return? What happens when AI sucks up all the capital in the United States? More flows in from across the globe.

In short, it is inconceivable that AI is literally starving the remainder of capital market participants. There is more than enough capital in global capital markets. It may be true that competition from AI is making capital more expensive and harder to get, but there is no right to cheap, easy capital.

If it turns out that there is less money in AI than currently believed, returns will fall and capital will flow elsewhere. But in the meantime, what does the author suggest that the United States do?

The federal government and the Federal Reserve should see that vital sectors — such as housing, entrepreneurship, energy infrastructure and critical supply chains — don’t starve as we continue building A.I. This could take the form of discounted lending to boost investment to these areas. Shortages in almost all these critical sectors are known inflation culprits. With inflation reigniting, the deflationary potential of investing in these branches is reason enough to do this.

Next, policymakers could develop an honest to goodness industrial policy for A.I. — subsidies, tax incentives, regulations and different ownership structures — that prioritizes deploying the technology for the kind of economy we want to live in: inexpensive, with clean energy, biomedical breakthroughs and advanced manufacturing.

Ah, so the solution is to have the government allocate the capital! Amtrak, Solyndra, the GSEs, high-speed rail, and the dozens of other failures will be licking their chops. When the government allocates capital, capital will go to the cronies. No thanks.

And what, exactly, is an “honest to goodness industrial policy for A.I.”? Next-generation cronyism. The left has run this playbook since the New Deal, with no sustained success. The new populists on the left and right may not realize what they are up to, but the disappointments they are about to reap will clear things up.

AI is not your friend, your foe, or anything special in between. It is a set of capital-intensive technologies that may or may not be especially productive. Let the market sort that out.