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Round Table

Feb. 4, 2026, 5:00 a.m. ET

Credit...Illustration by The New York Times

David AutorAnton Korinek and Natasha Sarin

David Autor is a professor at M.I.T. Anton Korinek is a professor at the University of Virginia. Natasha Sarin is the president of the Budget Lab at Yale.

David Leonhardt, an Opinion editorial director, hosted an online conversation with three economists about the effects that artificial intelligence is — or isn’t — already having on employment and about how big a transition society is facing.

**David Leonhardt: **Before we look toward the future, let’s talk about the present. I know there is debate among economists about whether A.I. has already led to a meaningful amount of job loss. What do you each think?

**David Autor: **The evidence is inconclusive. The most widely discussed findings document a slower pace of hiring of young workers in occupations that seem exposed to A.I., such as computer programming and customer support. But the hiring downturn starts in the spring of 2022, before the release of ChatGPT in November of 2022. The timing is a puzzle.

Something that did occur simultaneously with the downturn is a sharp rise in the Federal Reserve’s fund rates. This is a plausible explanation for the slowdown. Other recent economic turbulence — including tariffs — may also play a role. Indeed, hiring in these same A.I.-exposed occupations has been sensitive to business cycles and interest rates going back well before the current A.I. era. A.I. may play a role in the recent hiring trends, but it’s quite possible that it does not.

That said, there’s every reason to believe that advancing A.I. will fundamentally change hiring and skill requirements across much of the economy. In many cases, I think we’ll see fewer people doing this work, and those who do it will be more expert, solving the thorny problems that A.I. currently cannot solve on its own. From colleagues at tech firms, I understand that they’re still hiring sophisticated software developers, but they no longer need journeyman coders. We’ll eventually see that in the data, if we’re not seeing it already.

**Natasha Sarin: **Yes, despite all the vibes and anecdotes you hear about A.I. labor market displacement, there just isn’t evidence in the data that has happened in a meaningful way so far. Youth unemployment tends to be a leading indicator of economic downturns, even before A.I.

My colleagues at the Yale Budget Lab and Brookings have dug into this in a few different ways. We don’t find differences in employment in the last few years in the occupations most exposed to A.I. and those least exposed. The lines look the same.

That shouldn’t be too surprising. It’s been only three years since the mass introduction of this technology, and it takes firms — and all of us! — time to understand how to deploy it in ways that are going to be transformative.

I do think that firms are looking at a weakening economy and will try to shrink and reshape the work force with A.I. In terms of what that means for the labor market going forward, I am not in the doomsday camp. Historically, we’ve had lots of technological disruption, but disruptions also create new opportunities.

**Anton Korinek: **I agree that the employment data so far is ambiguous. But I want to offer a different lens: the investment data.

The leading A.I. labs aren’t making hundred-billion-dollar bets because they expect A.I. to have minor effects on the labor market. They are betting on achieving artificial general intelligence (A.G.I.), which could substitute for human labor across much of the economy. And the investment numbers are staggering. In the past year alone, Alphabet, Meta, Microsoft and Amazon have collectively spent more than $300 billion, primarily on A.I. infrastructure. This is more than triple what they spent just a few years ago.

As I think about the eventual employment effect, I’m struck that this huge spending isn’t creating many jobs even at the A.I. companies themselves. It is notable how few people work at these labs. OpenAI has roughly 4,000 employees and is valued around $500 billion. Anthropic has about 2,300 employees at a $350 billion valuation. Either way, that’s roughly seven or eight employees per billion dollars of market capitalization. Compare that to Walmart, which has 2,200 employees per billion dollars of value. The equivalent number at Ford is about 3,000.

So I think we may be asking the wrong question. The employment effects we are looking for may simply be lagging indicators of a transformation that’s already locked in by the capital being deployed. A.I. may ultimately be beneficial by revolutionizing scientific discovery, health care and human well-being. But we should be preparing now for the possibility of significant labor market disruption, rather than waiting for it to show up conclusively in the statistics.

**Autor: **Good provocation, Anton. Although I personally think we should ban the phrase “the leading A.I. labs,” followed by some homage to their collective wisdom. These guys are gamblers. They are not oracles.

Their bets might pay off. But why does it follow that this will end work for the rest of us? Their success could simply create tons of value elsewhere in the economy — more scientific discoveries, better health care, transportation, education, legal services, manufacturing, construction, etc.

Silicon Valley has never employed very many workers, but its rise over the last three decades has coincided with robust employment growth and historically low unemployment rates.

Or look to history. New technologies don’t merely replace labor in existing industries; new technologies create entirely new industries. Centuries ago, there were no automobiles, airplanes or telecommunications, and those industries all employ people.

**Korinek: **The bets are not limited to the labs but are supported by investors who have hundreds of billions of dollars in the game. Still, you are right that their success is not guaranteed. They are betting on relationships such as scaling laws, which predict that more computing power will lead to more powerful A.I. systems. So far, they have had a good track record, but we cannot be sure that these relationships will continue to hold. Incidentally, the same is true of empirical relationships in economics: In the past, new technologies have led to rising employment and wages, but we cannot be sure that this will be true in the future.

**Sarin: **I am not super swayed by the fact the labs are making big bets. If you work at these firms, haven’t you somewhat drunk the Kool-Aid?

**Leonhardt: **Natasha, you pointed out that technological disruption has never before caused humanity to run out of jobs, despite centuries of Luddite-like worries to the contrary. Can you sketch out a relatively optimistic scenario, in which A.I. is revolutionary but does not create mass unemployment?

**Sarin: **This time could be different, and this revolution could reduce the need for labor as a whole. Then maybe the world would shift to some version of the 15-hour workweek John Maynard Keynes famously predicted.

More likely, new jobs will come in, as they have in the past, and will offset jobs that are less necessary in a world where we all have laptops and don’t need typists. There will be winners and losers. The losers may include first-year law firm associates and graduate students in economics, who spent years honing skills that A.I.can effortlessly perform. I don’t want to minimize the possible disruption. How well we manage this transition will be the result of choices we make, and it will be important to retrain the work force.

But the gains will be real, too. People will have more access to legal services and other services that software can provide. There will also be new occupations to monitor and supervise A.I. work product. It is not a foregone conclusion — and it’s not even likely, in my mind — that productivity growth from A.I. will shrink employment overall. If history is any guide, technological progress, even from really revolutionary, life-changing, universally adopted technology, may change the way that we work, but not the fact that we work.

Autor: I agree that when we worry about the number of jobs, we are worrying about the wrong thing. We should be worried instead about the commodification of human expertise, since expertise is what gives labor its economic value. Without it, many workers may not be able to earn good wages

In the artisanal era, most goods were handmade by skilled artisans: wagon wheels by wheelwrights, clothing by tailors, shoes by cobblers, timepieces by clockmakers, firearms by blacksmiths. Artisans spent decades mastering their trades, and their expertise was revered. But the value of many forms of artisanal expertise was decimated during the Industrial Revolution of the 18th and 19th centuries, and many artisans themselves never recovered.

Even as innovations spurred a surge in productivity, it was five decades before working-class living standards began to rise. In its initial incarnation, the Industrial Revolution displaced expert work while leaving humans to perform the simple, grueling, inexpert work of feeding what the poet William Blake termed “dark satanic mills.”

**Sarin: **The Industrial Revolution seems a good analogy for this moment. One fact from Daron Acemoglu and Simon Johnson, the M.I.T. economists and recent Nobel laureates, that I find compelling: Real wages for weavers more than halved in the first two decades of the 1800s.

**Leonhardt: **My sense is that this is part of what you fear, Anton — that even if A.I. leads to big overall gains for economic output, it will hurt many more workers than it helps, at least in the medium term. Is that right? And what should we do to reduce that risk?

**Korinek: **Yes and no. If A.I. continues to advance only modestly, then the Industrial Revolution-scale disruption that Natasha and David are describing seems quite plausible: there will be a painful transition, but ultimately new jobs will emerge, as they always have. But I worry that we are thinking too small. If the quest for artificial general intelligence succeeds, we are not looking at another Industrial Revolution. For two centuries, labor has been the scarcest factor in our economy, leading to wages that have risen far above preindustrial levels. Human workers were the bottleneck, and being the bottleneck made us valuable. But if labor itself becomes optional for the economy, that would be very different.

When a machine can do a worker’s job, the worker’s wage eventually falls toward the machine’s cost. Yes, new jobs will emerge as they always do. But the machines will learn them faster and do them more cheaply. The reassuring historical patterns depended on humans being needed to run the economy. Remove that bottleneck, and we are facing something qualitatively different: a permanent shift in who, or what, captures the gains from economic growth.

The good news is that artificial general intelligence would generate enormous economic gains. The same forces that may diminish the value of labor would also dramatically increase total output. The challenge is ensuring that humans share in that abundance when our labor is no longer required to generate it. Historically, wages have been the primary mechanism for broadly distributing the benefits of economic growth. We may soon need new mechanisms that decouple income from labor: broad-based capital ownership, universal basic income or approaches we haven’t yet imagined. We need to start building those institutions now.

**Sarin: **It is less obvious to me than it is to Anton that we should be building new institutions now to deal with the possibility that we’re at the end of the Industrial Age. Maybe that will happen one day. But when? And which jobs are most at risk? And who is going to capture the gains? Surely they should help to finance any policy solution. It is perhaps boring to say but we have tools to help deal with labor market shocks, be they from A.I. or from anything else. We should strengthen them, for example by reforming our unemployment insurance system and providing more support for job search and worker retraining.

Autor: I agree that A.I. could ultimately undermine labor scarcity. If so, this would be a wrenching societal challenge that I’m not at all sure we’d manage successfully. We should begin to insure against this possibility. Two ideas that my M.I.T. colleague Neil Thompson and I sketch in a recent essay are “Universal Basic Capital” and “Wage Insurance”:

Universal basic capital would grant every person a meaningful ownership stake in productive assets at birth. Every baby could receive a stock-market portfolio. Unlike universal basic income, which requires continuous political support for redistribution, U.B.C. creates permanent stakeholders in the automated economy. It would potentially provide income through capital returns rather than ongoing transfers and hedge against the risk that A.I. will displace labor. Even if no such scenario comes to pass, it would broaden stock ownership, which would be a good thing.

We also may need policies to help workers who lose jobs soon. I favor wage insurance. Displaced workers often must accept significant wage cuts to find a new job. Wage insurance can help ease these tough transitions. It does this by subsidizing part of the wage gap — say, 50 percent of it — for a few years. By doing so, it persuades more people to stay in the work force rather than rely on government benefits. The Obama administration showed that this approach can work.

Sarin: I don’t think we are going to be great at predicting what new tools we need in the policy tool kit at a moment when there is so much uncertainty about how A.I. will change the labor market. So rather than fight yesterday’s war without anything like complete information, I’d advocate getting better at learning about what types of workers are being impacted by labor market changes in real time. We could do that, among other ways, by collecting better data about firms are using A.I. and then combining that with jobs data to help us spot labor market displacement as it occurs.

We should also get better at helping workers who’ve lost their jobs, for whatever reason. And we should right our fiscal ship and bring down the federal debt so we have the capacity to spend money in the future.

The A.I. transition may be hugely challenging no matter what, but we should put ourselves in the best position to manage it.

David Autor is a professor of economics at M.I.T. and a faculty co-director of the Stone Center on Inequality and Shaping the Future of Work.

Anton Korinek is a professor of economics at the University of Virginia and faculty director of the Economics of Transformative AI Initiative.

Natasha Sarin is a professor at Yale Law School, a co-founder of the Budget Lab at Yale and a former Treasury Department official.

Source photographs by KIM JAE-HWAN and AFP via Getty Images.

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