Every tech company now seems to have their own AI: Google Gemini. OpenAI’s ChatGPT. MetaAI. Spending for AI is reaching record highs, powering a big boom for the stock market. Even the White House wants in on the fun.
So are we in an AI bubble — an overblown investment period that’s bound to deflate? Yes, argues Paul Kedrosky, a partner with SK Ventures and a fellow at MIT’s Initiative on the Digital Economy. But not the bubble everyone thinks we are in. “AI is obviously a hugely important technology,” Kedrosky told Today, Explained co-host Noel King. So what, then?
It’s the money going into the AI infrastructure like data centers that concerns Kedrosky: “We’re spending this prodigious amount of money on the underlying infrastructure for AI with probably no likelihood of recovering most of that cost, and a significant likelihood that most of those assets become worthless because of the speed at which they depreciate.”
What happens when the bubble pops? And can past bubbles tell us anything about what is to come?
Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full episode, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.
How much money is going into these data centers?
It’s going to be on the order of trillions now. Forecasts are in excess of $2 trillion in data center spending ahead. But an increasing fraction of the money that’s being spent on all of these things that allow us to distribute AI, like electricity, is coming from debt. And debt comes with obligations. You don’t get to just walk away from it. So that makes this moment even more perilous.
If AI is so important, why does it not make sense for trillions of dollars to be rushing in? Isn’t this what we should be doing?
We should be. But the problem, of course, is that there’s this idea of what’s called a rational bubble. Everybody thinks they’re doing the right thing, but when you add everybody’s “right thing” together, you end up with a prodigious amount of waste.
It’s no different than if you go back to the 19th-century railroad bubbles in both the UK and the US. There was simply too much track, too many enthusiastic railroad builders building almost adjacent tracks to the same locations. And this led to an incredible amount of waste. But it also led to company failures and various market crises across the 19th century in the US and repeatedly in the UK. It’s not as simple as saying, “Well, this is important, so we should build it and not care what it costs and not care about the consequences.”
If so many smart people think that we are in a bubble, why is money still flowing into data centers and other AI infrastructure at the rate that it is?
I’m not convinced that many people think it is a bubble. As I talk to people in technology, the most common response I get is not only is this not a bubble, but it’s probably the most important technology of our lifetime. We have an opportunity to build a super-intelligence, a god-like intelligence on top of all of these chips and buildings and this AI electricity thing we’re creating. And to say we should slow down at this point, according to the technology community, is just a huge error. But there are people outside of technology who say, “Oh, this is an incredible amount of spending.” The Bank of England said it. Other people are cautioning about it, but not inside of technology.
The United States and humanity broadly has had no shortage of bubbles throughout history. You mentioned the railroads; walk us through some famous American bubbles.
The railroad is probably among the most prominent in the US and that was, again, an enthusiasm for the idea. The same thing happened in the ’20s during electrification. In the 1920s we went from a single-digit percentage of rural areas having access to electricity, [to] by the end of the decade it was more or less ubiquitous. Everyone had access to electricity. But at the same time, that gave rise to this proliferation of utility companies, of ventures that were doing all kinds of questionable things in terms of overspending. You could argue that electrification and the frenzy around it gave rise to the stock market rise of the ’20s, which led to the crash of ’29 and helped precipitate the Great Depression.
People are pretty familiar with the telecom and dot-com bubbles, but the closest historical analogy to what’s happening now genuinely is railroads and electrification. In the same way that we don’t need to have two sets of tracks to Philadelphia, we probably don’t need the same number of companies delivering what are called these large language models, these AI models that people are using. These will naturally shrink.
How destructive are bubbles and what do they tend to destroy?
All of them do immense damage. It’s a question of how big the bubble is and where the damage goes.
So if you’re just holding an index fund and thinking you’re being very conservative, you’re actually soaking in AI right now. If everything reverses, goes 20 or 30 percent in the other direction, you’re much poorer than you were. That’ll change your spending. And that has implications for recessions.
Isn’t it always the case that the bubble bursts and then what it leaves behind is, maybe not something beautiful, but something workable?
That’s kind of a line of patter from the technology community. But the reality is almost every financial, every technology revolution has caused huge damage and can take decades before we get back to where we were before. And as the famous line in economics goes, in the long run, it may work out, but in the long run we’re also all dead.
