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A conversation with Jared Bernstein and Jason Furman

Marketing note: I have a new ebook, Navigating the Chaos: Chronicles of Economic and Political Madness, which uses material from this Substack to construct a thematic narrative of the past two years and the issues that Democrats must now address to build an enduring progressive movement. Available from Amazon, Kobo, Bookshop, and Nook.

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TRANSCRIPT: Paul Krugman in Conversation with Jared Bernstein and Jason Furman

(recorded 11/12/26)

Paul Krugman: Today I’m talking with Jared Bernstein and Jason Furman, both of whom have been writing, as I have, about AI. Is it a bubble? If it is a bubble, what happens when it bursts? What’s it doing to the economy? All things AI. Hopefully, we can stay off of honeypots for the most part. But is it a bubble? I am surprisingly uncertain in my own judgment here. So, we can talk about the scope of it, but what can we make of this huge, huge investment in a very new technology?

Jared Bernstein: Well, when I’m being disciplined, I describe it as probably a bubble. I should start out by saying almost everything I’m going to say for the next X minutes is going to be speculative. And also, I’d like to underscore that, for all my concerns about a bubble and a bubble bursting, I think AI is likely to be a significant productivity enhancer, perhaps even transformational in that regard. So I don’t want to lose that. But in terms of your basic question, my work on this is with Ryan Cummings, and we started sniffing a bubble in the sector over a year ago, and we had a piece in The New York Times to that effect. We thought that the gap between the spend of the hyperscalers and the labs—the actual spending that they were doing and the expected spending—the gap between that and plausible earnings projections suggested bubble dynamics. So in later work, we were able to roughly quantify that gap. And others did a similar exercise. And I know you, Paul in particular, you’ve written about that. There’s a Brookings paper on this, which further raised our bubble antennae.

Actually, at this point, the diagnosis is pretty widely agreed upon, although there are doubts. And I share yours as well, Paul, with the added worry—now, this wasn’t quite there when we first started writing in October of last year—of leverage, that is. A lot of the spend was initially financed through cash flow. And some of these companies have big cash flows—not the freestanding labs, but the Metas and the Amazons—and now there’s the added worry of leverage because there’s so much more borrowing.

Last point on this: I do think it’s a good question for people who have the position I have as to whether you’ve personally divested in the sector. And I will say that I partially have, in that there is no SpaceX in my portfolio at this point in time.

Krugman: Let me ask you, Jason, for your take. I have some thoughts also.

Jason Furman: Well, first of all, I’ll do the investment advice first. All of my financial assets are basically in Vanguard Global ETF. So I have every single company on the planet Earth, or at least I aspire to have every single company on planet Earth. And so in that sense, I think with the sort of “your money’s where your mouth is” test, I’m implicitly saying it’s not a bubble.

I wake up different days taking different sides of this argument. It doesn’t feel like this is the type of network that previous technologies were—like Google Search becoming the best, or Facebook becoming the best. Everyone basically needed to use it, and they could end up with, in the case of Google, 90% of the search market. For this, I can use Claude, you can use ChatGPT, and I know Jared is just obsessed with Grok—maybe I wasn’t supposed to tell people that, Jared?—but it all works just fine. Moreover, if you go to Claude and say, “The bills are too high, what should I do?” it’ll say, “Try ChatGPT, and here’s a file to download and instructions for how to upload it to ChatGPT.” So there just doesn’t seem to be anything keeping people on these.

Moreover, the more they improve, the more for most purposes you can use older models. It’s like cars that used to go 200 miles an hour and now they go 1,000 miles an hour. For race car drivers, that’s a great thing; they want the latest car. For most of the rest of us, the old one is perfectly fine. So that is the “it’s a bubble” story.

On the other side, though, I have two reasons why I’m cautious about going too far with that. One is, I first personally called the Tesla bubble in April 2017. That is when Tesla’s market cap exceeded both Ford and General Motors. At the time, Tesla was making fewer than 100,000 cars, and these other companies were making like 10 million cars. And it seemed insane to me. It seemed like a massive bubble. Tesla’s up about 2,000% since I made that bubble call. And yes, it may collapse one day, but there’s no collapse that’s going to make me correct in my April 2017 call. And that’s happened over and over again with people.

And then the second thing that gives me pause is small probabilities of infinity, which is: you don’t need that high a probability of Anthropic taking over everything in the world to justify its valuation. So bottom line: I would not be at all surprised if it was a bubble. I would not argue strongly against it being a bubble, but I’m just too humble to believe any of my analysis or act on it.

Krugman: So, I’ll give you my take. I kind of look at the size of the CapEx and the experience that we had from the dot-coms, which was that it was a really big technology, but the big spenders didn’t capture much of the gains. So it is hard to understand the valuations. On the other hand, people who understand the technology better than—well, it’s not hard to understand better than I do, because I understand very little of it, something about matrices—but Azeem Azhar, whom I’ve talked with, has all of these reasons why it actually does make sense.

And there’s a funny thing: I kind of look for the sociological correlates. I’m certainly older than you, Jason, and I remember the late ‘90s when bars had CNBC on the TV instead of sports—that sort of popular enthusiasm. And I remember the housing bubble when there were shows like Flip This House, and I don’t see that now. There doesn’t seem to be the same kind of popular obsession with investing in this stuff. And the actual CapEx is being undertaken largely by established companies, where their cash flow is no longer enough to pay for the investment, but it’s not the little guy in the street who’s driving this.

Sometimes I look at the scale of this, and instead of this being naive individual investors, one possibility is that, except for Jensen Huang and so on, most of the people doing this have been in the tech business and have been billionaires for a long, long time, and sometimes I think that what’s actually happening is just they’re trying to repeat their former glory. One interpretation of the whole AI boom is that it’s basically a tech-bro midlife crisis. But anyway.

Bernstein: I’ll throw a couple of numbers here and take the bubble side of the argument, with the strong caveat that it’s all speculation, and I think we’ve all been clear and will continue to underscore that. So today, the CapEx for the industry basically has been north of $1 trillion. That’s since 2024. And the planned CapEx is around $6 trillion through 2030. And by the way, the chips wear out after five to six years. So this is what we did in some of our analysis. If you assume a break-even of about 10% of the cost of capital, or even a lower hurdle—a 3% to 4% hurdle rate, which is pretty standard—you quickly get numbers like the fact that their revenues so far appear to be a little bit south of $300 billion. And to justify that spend, given the assumptions I’ve mentioned on returns, they need to be $2 trillion to $3 trillion. So they’re off by multiples relative to where they need to be.

If you look at their operati…



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