Tyler Cowen | AI will change everything, just not all at once
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How does Tyler Cowen describe living in the pre‑AI and post‑AI worlds?
So 30 years from now, you're going to look back and just marvel at the world you lived in. And you'll say, I had the privilege in living in two completely different worlds, the pre-AI world and the post-AI world.
I thought we could just start off with AI productivity. And I think one of the things that I'm very surprised to see is that despite the intelligence of these models, it's not really showing up much in the macro data. Why do you think it's the case that, for example, we haven't seen more call center automation and call center unemployment yet?
We haven't figured out how to use the very best models. So people at work, they use them all the time for what I call freelancing. You're supposed to write a memo. It might have taken you four hours. Now you use Claude. It takes you 10 minutes with some polish-up work. That's converted into leisure time. That's a big impact. It's not measured. The aggregate boost in leisure and fun is actually pretty large today, I believe. But the real advances will come when we can use AIs to make science more effective, quicker at getting to the truth, better at testing hypotheses. That, I think, could take 10 years or more in many areas. We'll see some advances quite soon. You could say coding is, in fact, a kind of science.
Those advances are here already. But profitability is always a constraint. The human bottlenecks in any process are always a constraint. So the AI takeoff, in my view, will be a bit slower than what many people are expecting.
And so you're predicting sort of 0.5% growth as a function of AI. What would make you update that to 2% plus?
Well, a boost of 0.5%. So if the normal U.S. rate is, say, 2%, we'll be at 2.5%, which, by the way, is enough to fix our problems with budget deficit. This is an issue for Europe as well. If I saw all of our highly inefficient institutions just leaping on the AI bandwagon and working as hard as they possibly could to integrate it institutionally, I would update my estimates immediately. There's no logical barrier to that. I just think it's highly, highly unlikely. You look at the percentage of, say, even the U.S. economy that is massively inefficient, it's pretty high. Well, there's government, there's a nonprofit sector, there's a lot of higher education, the worst parts of our healthcare institutions.
Add those all up, you can debate the number, but I think it's at least 40%. of our economy, maybe 50%, is just awfully sluggish, and it will take a long time. And in many cases, you'll need startups to displace incumbent institutions, and that can take a generation.
And how about the unbottlenecked parts of the economy? Would you say there aren't many, or that those basically won't make up for the slowness of the rest of the economy?
There aren't many, but some are very important, so coding is the obvious one, and there the revolution already has arrived. How much more productive can you make the rest of the economy with much better coding? I'd say that's an open question, but if you look at the United States, 1995 to 1998, we had a big boost in information technology, just basic software and also inventory management, and then productivity went up about half a percentage point. So we know half a percentage point gain is possible. You then have to ask, well, isn't AI a whole lot better than what we did back then? I would say yes, but the quality of AI is not the bottleneck. It's the human adoption and use of it. And then I think, again, we're stuck at 0.5%, give or take.
But you're assuming in all of those domains that you always have the human bottleneck. That's right. If you take something like call centers, for example, at some point you will remove the human bottleneck. We're moving from the co-pilot era now towards agents that can run these tasks autonomously without any human retraining. Wouldn't that update your view?
I think call centers will be much more fully automated in less than 10 years. Again, what percent of the economy are they outside of, say, Hyderabad? It's pretty small. The progress will creep along sector by sector.
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Chapters
8 chapters
1
How does Tyler Cowen describe living in the pre‑AI and post‑AI worlds?
0:00–6:31
2
Why isn’t AI productivity showing up in macro‑economic data?
6:31–12:05
3
What are the ‘human bottlenecks’ and institutional inertia that slow AI adoption?
12:05–18:05
4
Which sectors (like call centers) will see AI‑driven automation first and why?
18:05–23:35
5
Why might India become a global leader in AI implementation?
23:35–29:01
6
When intelligence becomes cheap, what new assets become valuable?
29:01–35:59
7
How will AI reshape the future of work, initiative, and charisma?
35:59–42:32
8
What aesthetic crisis does AI‑enabled wealth create for architecture and design?
42:32–48:19