I, I, I specialize in those.

Yeah, yeah.

But, um, here, here's what I, I feel reasonably confident about.

I, I think that the, there are serious threats to the business model of the university, but I'm not sure that those are all related to AI.

I think a lot of them are related to demographics, certainly American universities.

You know, the, um, the, the share of, you know, the basically the s- the cohort size of high school graduates is starting to shrink, and that'll put pressure on the number of universities.

I think that's different than putting pressure on the basic model of like, do you go to university? I think many universities, especially small private colleges in the Northeast where we have more population decline, uh, will go out of business.

So, so is there something the institution can do to, uh, ensure that that happens more rarely than it now does?

David Deming is the Dean of Harvard College and a professor in economics, education, and public policy.

With higher education, I think again, you see it in several ways.

So one again is just enrollment declines.

And again, that's an aggregate decline, but, but it masks really different situations.

So for example, colleges in the South are actually seeing slight enrollment increases over this period, and the projection is they will continue to because the population's actually increasing in the South because of migration.

Whereas colleges in New England, you're seeing a wave of closures in colleges up here because this is a declining population part of the country.

But again, then the question, David, is how do colleges adjust to that? And one way they do is, you know, you can try to discount the price to bring in more people.

How likely is it that one direct effect of the decline in enrollment is a better quality education for a lot of students? I mean, if you talk about supply and demand, if the supply goes down, then the college and university are gonna have to try a lot harder to really deliver what they need to deliver.

Do you want to kind of lay out, first of all, your position on it, and then we can ask you some questions?

So I wrote a convocation speech that I delivered to students on the day before the first day of classes.

I talked about the three eras of undergraduate education.

My argument was that we're entering a place because of AI, but not only AI, where we need to embrace a more communal aspect.

And I talked a little bit about how that relates to AI policies.

I sent an email to students the first day of class outlining my goals for the year at the college.

which is something I did last year too, is say like, what are we trying to accomplish? And one of them was trying to work with faculty to develop a set of advisory guidelines about AI use in classes.

How do you how do you think about this problem?

What does that mean?

Yeah.

So, um, here's what it means.

I, I think that, uh, we have to account and honestly acknowledge the fact that everybody, not just our students, but everybody is using AI all the time for everything, and we have to design our education around that reality.

And so what I said in my email was actually I favor what I would call a barbell strategy to, um, dealing with the challenges of AI, which is that you either have an enforceable way to ban it, and I would support that in many cases.

Like, I actually think using the AI to do the writing for you and the thinking for you is bad.

Um, but as a 47-year-old man, like, I have developed my skills and habits of mind to do that.

... which can only happen or can happen most specially in the community that we call a college campus?

So, yeah, a couple of questions in there.

Yeah.

So let me first take the question of attribution, which is a really hard one.

So we know that like it's a fact that the unemployment rate for new college graduates is higher.

than it has been in a long time and is elevated relative to the unemployment rate of other groups and has been since the pandemic, basically.

So this is a fact.

It's like 5.6%.

It's like everything's fine here.

And so talk to me a little bit about how you would define your founder mindset.

Yeah, so first of all, you're right.

It- we're not that, you know, on paper, we don't have that much in common.

I've never founded anything.

I'm an academic.

I'm a scholar.

I'm an egghead, and I've been working for many years on issues that I think we jointly care about, so maybe that's the connection, things like labor markets, skills, AI, jobs, what does it mean to be successful in the world, thinking about young people's career paths.

It's, it's potentially diminishing their educational experience.

And so maybe you can give us a picture of really where we are in that whole transition.

Yeah, happy to do that.

So this is a paper, as you mentioned, it's joint work with Chris Ong and Larry Summers, um, that is called, um, Technological Disruption in the Labor Market.

And what we did in that paper is try to say, you know, can we, in a principled way, measure the rate of job change over a long period of time in the US and ask the question like, are things changing faster than ever? And that required some data work and some assumptions about how to measure change.

And so what we did was we said, okay, let's divide all work into major categories of occupations.

So it's things like agriculture, blue-collar work, you know, manufacturing, construction, things like that, um, clerical work, sales, management.

So like pretty broad categories.

Where are we on that?

Uh, a- are you also concerned that there, there's something sort of uniquely spooky about AI in terms of its ability to replace this entire suite of jobs that's so disproportionately concentrated at that lower, um, part of the corporate ladder?

I am concerned about the, um, what you mentioned, which is how do we kind of, if we're, if we're replacing entry-level white-collar work with AI i- in the medium run, how do we train the next generation of people who are gonna be business leaders, decision makers? How are they gonna learn to do the job if they're not, if they're not, you know, learning the ropes at the bottom of the ladder, as you say? So I- I'm super concerned about that.

Um, however, I'm not sure it's really different than other technologies.

If you think about farming, okay, there are still farmers in the US.

There are many fewer of them, but actually it's a quite high-paid, um, high-skill occupation.

So you're making really high-stakes decisions about how to use your land optimally, whether to use different technologies to optimize, you know, crop rotation and, like, what market should you sell in and how should you hedge, you know, against the, the risk that you'll have a bad weather season in the futures market? And there's all kinds of things you do that you basically replace the lower rung of farming, the manual labor of actually tilling and plowing the fields, and y- what you've got left is the higher order things that, that are left in the job.

And so I do think, that's why I think it'll be disruptive, because we'll see that what firms expect from white-collar office workers is just gonna be ratcheted up very quickly.

So what, David, what, w- what should high schools and colleges be teaching now in order to give people skills that they can actually use in the workforce rather than just essentially lie about their intelligence to teachers who themselves might be lying by creating their, um, their curricula on AI as well?

So, you know, what do you learn from your surveys and other sources about the share of working age Americans who actually use generative AI tools in the workplace? I mean, how prevalent is it?

Yeah.

So before I tell you about the results, let me briefly explain our approach to it and why I think it's the right approach.

So there's a lot of surveys out there that ask people, do you use generative AI? But they're often just based on what I call convenience samples.

So you kind of send a survey out to a bunch of people on the internet and you ask them.

And the critical question is, are the people who are answering these questions representative of the average American worker or the average American citizen or citizen of any other country? And, you know, it's hard to know.

And so what we did in our survey was try to get at some underlying ground truth about this by creating a survey that is linked to the current population survey, which is the survey that is the most important source of labor market information.

So we're trying to get to the billion-dollar question of, is this really going to propel a productivity boom that matters at the macro level?