Erik Brynjolfsson

Mm-hmm.

You might wonder then, but we've heard about a lot of research that's been done, research coming out of Stanford and their Digital Economy Lab led by Erik Brynjolfsson, where they have found that actually, as you're pointing out, like, young people are increasingly having a hard time getting jobs.

And what's-- my colleague Martha Gimbel often says, like, you know, "It's really unfortunate that Sam Altman introduced ChatGPT at the same time that the Federal Reserve desi- decided to be in a tightening moment," because there are other things happening in the macroeconomy where youth unemployment or youth lack of employment tends to be a leading indicator of the fact that we're just starting to experience an economy that's cooling.

So we can't separate the two.

[chuckles] Uh, so, so your confidence level...

I, I did an interview with Erik Brynjolfsson not so long ago, and, uh, I don't think I'm reading into it, I think he was fairly plain, that he's been a little disappointed with sort of the return on investment we've seen, even though he, you know, it's still early and he's written some of the, you know, the, the most important research on how long it takes to incorporate these technologies.

But he seems disappointed about the return of these technologies so far while being optimistic that, you know, that there was gonna be a big return and big productivity gains and all that.

Are you just a little disappointed at sort of the pace of real world adoption and deployment?

I have a long-standing history of following chess and AI in chess, where I've seen how well that'd gone and how many problems it conquered, and I've spent a lot of time visiting the major labs and talking to people, and I feel I'm pretty well informed, and most economists are busy doing other things, which is fine.

But I think in terms of knowledge of AI and taking seriously what the lab people say, I'm just ahead of most economists.

But someone like Erik Brynjolfsson, uh, I'm not ahead of him in this regard.

He lives in the Bay Area.

And he, I think he pushed for a definition which is like can do eighty percent of the work that humans can do.

We haven't met that one either, right? You know, it can do maybe a bunch of tasks that people can do, but doing a whole job is harder, right? Eric, Eric Brynjolfsson has always made the distinction between doing tasks and doing jobs.

There are lots of tasks that current AI can do.

I don't doubt that.

Give me the setup, because I want to understand what data they are looking at that the monthly government reports are missing entirely.

Eric Brynjolfsson, Bharat Chandar, and Ryu Chen at the Stanford Digital Economy Lab published an update on August 12th.

They call the project Canaries in the Coal Mine, and they use actual payroll records rather than household surveys.

Payroll records, instead of survey responses, is a meaningful methodological upgrade because it means they are watching what employers actually did rather than what a sample of households said they thought was happening.

That was Clara Shy of the New Work Foundation.

If you enjoyed this episode, please check out my conversation with Stanford economist Eric Brynjolfsson from May of this past year.

Lastly, please rate and review us.

Thank you for listening.

Um, job growth continues in those industries.

I think there's been a lot of, yes theory, but really important theory work done, not by my team, but by people like Erik Brynjolfsson at Stanford or, um, Luis Garicano at London School of Economics, um, about why...

Those are just two examples, but they've done great work.

About why we haven't seen the job displacement yet.

Nobody gets counted.

Erik Brynjolfsson at Stanford has the numbers that make this visible in a way that is hard to argue with.

His team has been tracking this for nearly four years using ADP payroll data covering roughly one in six American workers.

Here is what they found as of this summer.