Chapter 1: Is AI currently in a bubble?
Giving the AI boom a bubble score. From American Public Media, this is Marketplace Tech. I'm Megan McCarty Carino. Is AI a bubble? It's the trillion-dollar question in the economy. So we decided to look to history for some answers. David A. Kirsch is a historian and management professor at the University of Maryland.
He co-authored the book Bubbles and Crashes, the Boom and Bust of Technological Innovation. He looked at patterns over 150 years of technological breakthroughs, from broadcast radio to rayon, and came up with a model of the conditions that most often lead to bubbles.
The four factors that we looked at were the presence of uncertainty, so uncertainty
Chapter 2: What historical patterns lead to technological bubbles?
Is it a technology that people know how to use or is it a technology that people don't know how to use or how it will generate value? Does it happen in the presence of novice investors? These are investors who might be inexperienced or might not have seen technologies similar to the new technology in the past. Does the technology arrive in a way that investors can invest in it?
So is it something where we can go to our Schwab account and buy something that reflects the technology? Finally, what are the nature of the narratives surrounding the technology? Is it a technology that has a magic to it that says, oh, we can do this, we can do that? There are lots of narratives, or is it a pretty straightforward technology?
So when we look at those four factors and we say, well, that can be the recipe for a boom if all four of those factors are there. And if there's a boom, then there can be a bust. We don't actually have a theory of the bust because it's very hard to know when you have a boom, will the technology kind of catch up and in fact deliver on its promise?
Or will there be an over-commitment, over-investment overenthusiasm, and even a very impressive technology may still not be able to deliver in the timeframe that investors require.
You have focused on bubbles that kind of bubble up around technological innovations, but some of the best-known bubbles in history have formed around things that aren't techie at all, you know, tulip mania, of course, the housing bubble. But are technological innovations kind of especially prone to bubble dynamics?
Yes, they are, for the reason that new technology destroys expertise. It naturally generates a type of uncertainty. Lots of people call and ask, well, is there an AI bubble, this and that? And I said, the first thing, if anyone tells you they know the answer, they're wrong because nobody has seen what AI does to the highly developed capitalist economy. This is happening for the first time.
So there's because in technological innovations are by nature new. Nobody knows what's going to happen. So in that sense, that uncertainty piece is more likely to ride in on the back of technology. OK, tulips, who knew what color tulip would spring from the bulb? But that's a different type of uncertainty than uncertainty associated with technological change.
What role has infrastructure played historically in these tech booms and busts?
It's been very important as almost like a timekeeper for the bubbles. If you think about, you know, it took decades to build out the railways or took decades to build out the electrical distribution infrastructure for electricity.
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Chapter 3: What are the four key factors that indicate a bubble?
If I go through it, you know, the uncertainty for sure is there. lots of novice investors, everybody wants in. The narratives, again, there isn't a better technology than this AI overlord to kind of generate scary dreams. I think where it might come up a little short is on the pure plays, because there really haven't been that many IPOs. Most of the
Early energy around AI investing was focused on NVIDIA, which did, of course, turn it into the most valuable company on Earth. Not quite sure why. I think if we start getting a real big slew of IPOs, potentially massive IPOs, then I think we really would be eight out of eight. Right now, I sort of put it at seven out of eight. So, you know, it's bubbling, but maybe not quite at max.
We'll be right back. You're listening to Marketplace Tech. I'm Megan McCarty Carino. We're back with David Kirsch, professor at the University of Maryland. Talk to me about the uncertainty piece, because, I mean, in some ways it seems extremely obvious. Of course, we don't, you know, we've never had this technology before. We don't know exactly how it's going to slot into things.
But I think at times... you know, from business leaders, from tech leaders, there sounds like there's a lot of certainty about how valuable this is going to be and, you know, how it's going to be used and how it's going to replace all labor and that kind of thing. Like, how would you kind of define the uncertainty landscape for AI?
The example I might use is, say, aviation, where it took 30, more than 30 years to go from Kitty Hawk to DC-3. It took 30 some years before we actually got a plane that people would pay money to fly in and actually have reasonable expectation that they'd get out at the other end in one piece.
And, you know, to your infrastructure question, there was an enormous amount of physical infrastructure that had to be built and airports and whatnot, but also a lot of organizational infrastructure to allow planes landing patterns and weather prediction and communication systems and norms around how to use the technology.
Over that period, there were three or four completely different business models. So there was the barnstorming era where people would go to a farm and pay money to Watch a daredevil stand on a wing. And then there was military aviation and World War I. And then there was airmail. And then finally, there was commercial aviation. Maybe right now the chatbots are like the wing walkers.
Who knows what the actual business model is going to be that produces value for customers.
Are there ways in which the AI boom diverges from your bubble criteria in important ways?
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Chapter 4: How do narratives affect technology bubbles?
They're used to, you know, swapping in and out of hedge funds and doing all sorts of sophisticated things. But that still doesn't make them more experienced in this context.
So to your eye, does it look like AI is becoming too big to fail?
I tend to look at it at an economic level. And I think the technology is clearly going to do something. It's already built its way, kind of wormed its way into our lives in some important ways. I think too big to fail tends to conjure the idea of government intervention. I'm not sure... The government would intervene to save chat.
But if, you know, chat and Google and Anthropic all somehow went offline on the same day, would that be a crisis? Probably would, because there are a lot of other systems that rely on those frontier labs models.
It's wormed its way into our systems, but I think it will, you know, in a few more years, it will be very deeply ingrained in our organizations and in our lives and in our home technology and in all sorts of other places. At that point, even if the companies fail, the technology would still succeed.
That was David Kirsch at the University of Maryland. His book is called Bubbles and Crashes. This conversation was part of our recent AI and You series. You can find the whole thing on our website, marketplace.org. Daniel Shin produced this episode. Jesus Alvarado also produces our show. And special thanks to producer Maria Hollenhorst as well.
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Chapter 5: What role does infrastructure play in tech booms and busts?
Gary O'Keefe is our engineer. Daisy Palacios is the supervising producer. Nancy Fargali is the executive producer. I'm Megan McCarty Carino, and that's Marketplace Tech. This is APM.