How AI Could Reduce Inequality

Summary

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Podcast Summary: "How AI Could Reduce Inequality"

Podcast: What's Your Problem? Host: Jacob Goldstein (iHeartPodcasts and Pushkin Industries)
Guest: Dr. David Autor, Labor Economist, MIT
Date: July 9, 2026
Summary covers content from approximately 02:16 – 51:06.

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Overview

In this episode, Jacob Goldstein explores with labor economist David Autor a provocative question: Could the rise of artificial intelligence (AI) actually reduce, rather than increase, economic inequality? Building on Autor's influential research into the impacts of past technological revolutions (like computers), the conversation dives into how AI’s unique characteristics might alter who benefits and who gets left behind, the risks and dislocations involved, and what policy responses could ease society through disruptive change.

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Key Discussion Points & Insights

The Historical Impact of Technology on Inequality

(02:17 – 10:00)

• Computers Increased Inequality:

  • Autor describes how traditional computers (pre-AI) mechanized “routine tasks” that could be codified, shifting work away from clerical and repetitive middle-skill jobs.
  • Highly educated professionals benefitted by automating the “grunt work,” letting them focus on cognitive, value-added tasks.
  • Less-educated workers lost access to many office and factory jobs, often moving into low-paid services ("socially valuable work, but…poorly paid" – [04:59], Autor).

• Bookkeepers vs. Accountants Example:

  • Automation empowered accountants (more specialized, college-educated) to increase productivity and value ([06:12–06:36]).
  • Bookkeeping was de-specialized, with pay and skill requirements falling ([06:58], Autor).

• "Hollowing out the Middle":

  • The key division: college vs. non-college workers.
  • "[The] earnings differential between college and non-college was always substantial, and then around 1980, it started rising and rising…and now the college-high school differential…is about 75%." ([09:04–09:29], Autor)

AI as a Different Kind of Technology

(10:00 – 21:00)

• AI's Potential to Level Expertise:

  • AI can enable more people to do tasks traditionally limited to highly trained professionals, potentially reducing wage gaps.
  • "[AI] is a force multiplier for your expertise…" ([14:31], Autor)

• Guilds and Occupational Barriers:

  • Example: Nurse practitioners expanded access to medical care but faced resistance from doctors' associations. AI might similarly open up "guild-protected" fields.

• Expertise & Tools:

  • "It doesn't mean anyone can do anything…But given that, with better tools, I can do more." ([14:31], Autor)
  • AI makes entering fields like software development, legal practice, and design easier, but those jobs may become less specialized and less highly paid ([16:27], Autor).

• Superstar/Scalability Limits:

  • Unlike entertainment, services like healthcare and law are "congestible"—i.e., no one doctor or lawyer can serve everyone at once, meaning work will still be distributed ([21:33], Autor).

AI, Services, and the New Middle Class

(21:00 – 29:08)

• Services Dominate Modern Economies:

  • We spend more on services (healthcare, education, law) because we haven’t dramatically improved productivity in these sectors.
  • AI could bring professional services "down in price while increasing the set of jobs available to people" ([11:51], Autor).

• Potential Shift:

  • AI could create more opportunities for middle-skill, non-college-credentialed workers within professional fields.
  • "It's somewhat expertise leveling. It creates competition where we desperately need it and creates opportunity…" ([29:08], Autor)

• But…Disruption Will Be Painful:

  • Devaluation of expertise in some fields (e.g., translation, medical transcription, call centers) will happen rapidly.
  • "I'm very worried about people who work in call centers… It's very disruptive, psychically damaging, economically scarring for people to have their expertise suddenly devalued." ([29:17–30:00], Autor)

Policy Responses for a Changing Labor Market

(31:44 – 41:43)

• Three Main Policy Recommendations:

  1. Wage Insurance:

     • Helps people transition by softening the income shock when moving to lower paid work post-displacement.
     • “It got people back to work faster…It was so effective it paid for itself.” ([33:33], Autor)

  2. Retraining at Scale:

     • Updated sectoral training programs (construction, healthcare tech, repair) that match real regional demand.
     • Acknowledges U.S. has lagged in scaling successful models, referencing Denmark’s effective programs ([36:06–37:10], Autor).

  3. Universal Basic Capital:

     • Instead of a universal basic income (which may lack political support), give every citizen—starting at birth—a small fund of capital (e.g., $1,000 in an S&P 500 ETF).
     • "It diversifies people… It gives you an ownership stake, almost like a voting stake in the economy." ([38:10–40:45], Autor)
     • "It's a very small step…but says: look, everyone now…I'm not just a claimant, I'm a contributor." ([40:33–40:45], Autor)

• Underlying Message:

  • All three policies are "no regrets." Even if AI does not lead to mass unemployment, they'll improve resilience and opportunity ([41:53], Autor).
  • "If there's going to be an AI dividend...we want to make sure people are brought along..." ([42:18], Autor)

• Core Anxiety Around AI:

  • Quoting Ted Chiang: "When people are saying, oh, people are scared of automation, they're scared of machines. They're not scared of automation, they're scared of capitalism." ([43:30], Autor)
  • Ultimately, it's about the trust in society’s ability to ensure that rising productivity benefits everyone, not just “claimants” but “contributors”.

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Notable Quotes & Memorable Moments

• On AI as Skill "Leveler":

  “The potential for AI is to enable more people to do that expert work and bring down its price while increasing the set of jobs available to people.”
  — David Autor ([11:39])

• Experience with Professional Guilds:

  “They have not been welcomed by the American Medical Association. Not at all. They’ve fought very hard to limit their scope of practice...”
  — David Autor, on nurse practitioners ([13:06])

• Limits of AI Replacement:

  “There’s no doctor who can serve 2 billion people simultaneously.”
  — David Autor ([21:44])

• On Displacement and Transition:

  “Most people are doing the best paid thing they can do...if that work becomes less valuable...there’s not an equally good job.”
  — David Autor ([30:00])

• On Universal Basic Capital:

  “Everyone now, hey, I’m not just a claimant, I’m a contributor. I own part of the capital.”
  — David Autor ([40:33])

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Timestamps for Key Segments

• The impact of computers (historical context): 03:22–09:33
• Bookkeepers vs. accountants; Uber analogy: 05:44–07:58
• Hollowing out of the middle: 08:40–09:25
• How AI might be different: 10:00–16:27
• Medicine, nurse practitioners and guilds: 12:31–14:24
• AI as force multiplier—design, law, software: 14:31–19:52
• Constraints on ‘superstar’ effects in services: 21:33–24:55
• Disruption and the need for new policies: 28:07–41:53
• Three buckets of policy: wage insurance, retraining, universal basic capital: 31:53–41:43
• Underlying anxieties and society’s contract: 42:18–43:48

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Lightning Round & Final Reflections

• On teaching in the age of AI:
  "[MIT students] are building the tools for everyone else to take the shortcuts and not learn anything. And they know how to use the tools well..." ([48:47], Goldstein/Autor).
• Reassurance to young listeners:
  "There's never been a technology that's made old people great at the cost of young people…I'm aware of. Almost all new technologies are developed and pioneered…by younger generation…" ([49:54], Autor).

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Takeaways

• Traditional computers increased economic polarization, but AI could—if policy is proactive—enable a new middle class by spreading professional-class productivity.
• The transition will still entail significant disruption and psychic cost, especially for those with eroding expertise.
• Society should invest in policies (wage insurance, retraining, universal basic capital) to ensure the AI dividend is broadly shared and to maintain social trust during rapid change.
• While fears about AI are real and justified, it ultimately isn’t the technology but the social/economic systems that determine who benefits.

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For anyone who missed the conversation, this episode offers a nuanced, hopeful—but realistic—framework for thinking about AI, inequality, and the future of work, complete with grounded examples, historical context, and concrete policy ideas.

Transcript

[Jacob Goldstein]

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[David Autor]

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[Jacob Goldstein]

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[Jacob Goldstein]

This is what's yous Problem?

[Podcast Host / Interviewer]

And my guest today is David Autor. David is a labor economist at mit, and among other things, he's done really influential work on how new technology affected American workers over the past several decades. In particular, his work makes a compelling case that computers contributed to rising inequality in the late 20th and early 21st centuries.

[David Autor]

So.

[Podcast Host / Interviewer]

So I was interested, and I was pleasantly surprised when I recently read some new work of his that suggested that AI might actually drive inequality down.

[Jacob Goldstein]

It's a nuanced story and it's a

[Podcast Host / Interviewer]

really interesting case that he makes.

[Jacob Goldstein]

And of course, we don't actually know what's gonna happen.

[Podcast Host / Interviewer]

But whatever happens, David Otter's framework is

[Jacob Goldstein]

a really useful way for thinking about

[Podcast Host / Interviewer]

the way technology affects work, affects who, who does what, who makes how much money.

[Jacob Goldstein]

So to start, I asked him to

[Podcast Host / Interviewer]

talk about what happened when computers started to become common in offices back in the 1980s.

[David Autor]

So, you know, information technology, the computer was different from many other technologies that preceded it. And what made computers different, traditional computers, like pre AI computers, is that they followed rules and, and you could write a program to accomplish a task that you would previously have thought of as a cognitive procedure. It required all these if thens, all these steps, gathering information, doing calculation and making things that we thought of were exclusively in the mind's dominion. And so that codification took out a lot of the routine tasks in the work that people did. How that affected work was really quite nuanced. So people who did bookkeeping and accounting, they spent much, much less of their time on data tabulation, data calculation, and much more on scenario planning, on forecasting, on forensics, trying to find errors. And so among technical, professional, managerial work, it made work more productive and it made more specialized. It eliminated a lot of the grunt work and enabled people to focus on the abstract problems. But for the other group of people whose work was simplified, whether it was in the kind of stock and inventory clerks, whether it was people who were working as cashiers, who used to have to know how to be able to make change and keep track of numbers and so on, it made the work simpler and less specialized. And in the case of production work, it eliminated sort of certain types of production jobs, certain types of office jobs, because they could be more or less fully automated. And that had the effect of taking people with high school degrees and some college and making their skills less valuable in offices, less valuable in factories and assembly lines. And so it shifted the weight of employment for people without college degrees away from offices, away from factories and towards a lot of services, you know, food service, cleaning, security, entertainment, recreation, home health aides. And that's socially valuable work. But it's poorly paid. And there's a number of reasons why it's poorly paid. I don't want to oversimplify, but one of them is it's not specialized, right? People can do it without training or certification.

[Jacob Goldstein]

So one example that I find helpful in thinking about the kind of dynamics you're talking about is looking at accountants versus bookkeepers. Accountants focus more on the big picture, typically have a college degree, often a special license. Bookkeepers focus more on the day to day look at, you know, money coming

[Podcast Host / Interviewer]

in and out of a business.

[Jacob Goldstein]

They don't typically have as much training as accountants. And so I mean, can you just talk about how computers affected accountants versus bookkeepers.

[David Autor]

So for accountants, it was the story of essentially eliminating the supporting work, the inexpert work, the drudge work, and. And allowing them to focus on the cognitively demanding stuff. Right. To do the problem solving, to do the forecasting, to do the scenario planning, to do the forensics of finding errors and issues and so on.

[Jacob Goldstein]

Accountants can be better. Accountants because of computers. Exactly. They can figure out more complicated ways to save people money on their taxes or to find errors or whatever. And so it's good for accountants and other similar, you know, sort of professionals with a high amount of expertise. Right. And then the computer is a tool that's making them better at their jobs. What is it doing to the bookkeepers?

[David Autor]

So it's making their work less specialized. Less specialized. Right. And so many more people can do it. And therefore it doesn't have to pay as well. It may grow. Right. Because firms like, well, look, it's cheaper than it used to be, it's more productive than it used to be, and lots of people can do it. And we see this often. Right. So like another nice. Another example, this is ride hailing.

[Jacob Goldstein]

Right?

[David Autor]

Ride hailing software. You know the phone apps, right? Uber. Uber. Uber, exactly. Yeah, Uber And Lyft. Right. They changed the work of taxi and chauffeur service a number of ways. They made it much easier to enter and so on. But one thing they did is they entirely eliminated the expertise that was required to drive. Because you used to have to know your way around a place to drive.

[Jacob Goldstein]

Yeah. Famously in London. Right. There's a test that the. You had to know every street in London or something to be a cab

[David Autor]

driver in London to get a bike. Yeah. Take about three years of memory memorization. It was an incredibly rigorous feat.

[Jacob Goldstein]

And then now you can just get a map on your phone. Like now that knowledge is just profoundly obsolete. It's such a wild shift.

[David Autor]

Exactly. It's totally economically stranded. Right. It's still out there, but it isn't useful. It has no scarcity value. Right. Because everybody else gets it on their phone. So what did this do? It eliminated the expertise requirement to do this work, but it made the work very productive. So what? We have several hundred percent more people in this walk of life in driving chauffeur service than we did 20 years ago. But the pay of taxi drivers, chauffeurs, have fallen relative to the average. So this dynamic of simplifying work, enabling more people to do it, but at lower rates of pay, that's one of the kind of directions that automation can push, but it can push in the other, just like those accountants.

[Jacob Goldstein]

So you have this phrase, at least I associate the phrase with you, that describes this phenomenon, the hollowing out of the middle. And it seems like this is roughly, as a sort of crude measure, college degree, not college degree, seems like a way to draw the line for who on average benefited from the arrival of computers and who on average was hurt by it. Is that about right?

[David Autor]

Absolutely. I mean, that has been over the last 40 years, has been the huge economic dividing line, Right. The earnings differential between college and non college was always substantial, and then around 1980, it started rising and rising and it rose for 30 years and then has plateaued at that point. So now the college high school differential on average is about 75%.

[Jacob Goldstein]

So people with college degrees make 75% more per hour?

[David Autor]

On average? Per hour, yeah, on average. So huge, huge difference.

[Jacob Goldstein]

So, okay, now we have set the table for the arrival of AI, right? This is a story, a true story of what's happened over the last several decades because of computers. Now we have this new kind of technology showing up at our doorstep. You've written a story about how AI might arrive quite differently in the labor force than computers did. Right. With different distributional effects. Tell me about that.

[David Autor]

Yeah, so over the last, you know, really, over the last four decades, we've become a society dominated by services. You know, we spend 20% of GDP on healthcare and education. It's like, you know, so back in the, you know, 1940, right. We spent a lot more money on, you know, cars and appliances and food and clothing.

[Jacob Goldstein]

Food, food was a huge part of the household budget in 1940, and now it's 10% instead of 30 or 40 or something.

[David Autor]

Right, but why. So the mixed news in that is why do we spend less on those things? Partly because we've gotten really productive with them. They've gotten really cheap, right. All these services like healthcare, like education, like law, we've not gotten more productive with them, Right. We just have expensive people doing them. And those people have gotten more expensive as the services become more necessary. They've not gotten faster with them. And so this creates a distribution of income that very much favors the professional class and the guilds of people, be they lawyers, be they doctors, be they professors, right. You know, engineers, architects, you know, contractors. And so that's not a great scenario for most people. You know, if you're a professional, you're on both sides of that transaction. Like, you know, yes, you have to pay a ton to a lawyer and to send your kid to college, but on the other hand, you're paid a lot to, you know, do marketing, whatever it is that you do. But for most people, most people are not in that line of work. Right. Only know 40% of US workers have a college degree. Most of them are not highly paid professionals. And so most people are only on the side of the transaction where they pay a lot of money for those services. So the potential for AI is to enable more people to do that expert work and bring down its price while increasing the set of jobs available to people. Right.

[Jacob Goldstein]

So there's two sides of the coin. You're sort of packing into that last half of the sentence. Right. So you're saying more people could do jobs that are now done by a small guild of experts.

[David Autor]

Exactly.

[Jacob Goldstein]

So that's good for the people doing the jobs. And also if that happened, it would bring down the price of those services. So that's good for everybody, that's good

[David Autor]

for customers, like that.

[Jacob Goldstein]

Sounds like a lot to ask for. What is an example? What do you think of it?

[Podcast Host / Interviewer]

Sure.

[David Autor]

But let me also say not everybody loves that story. Who doesn't love that story? The people at the top of that

[Jacob Goldstein]

pyramid, the people in the guilds. That's why they're in a guild. But so let's do an example. Cause it'll become much clearer. Like you've written about doctors and nurse practitioners, Right. In this context.

[David Autor]

So, you know, nurse practitioners, you know, they're registered nurses who have an additional master's degree and that enables them to diagnose, treat and prescribe. In many states, they can prescribe. Not all of them. It depends. You know, there's different rules. And they. Now that really encroaches on the territory that used to be wholly owned by physicians. Right. And, and you know, this. They have not been welcomed by, by the American Medical Association. Not at all. They've got very hard to limit their scope of practice. And in fact, you know, the nurse practitioners, basically it's been an, you know, they started 60 years ago, like trying to create a credential, a curriculum, a scope of practice. They, you know, fought their way. And it's only in the last 20 years they've grown and they're expected to grow a lot, but always facing great pushback from the medical establishment. Why? Because they're encroaching on their expert territory. That's very threatening. So I think, like the, you know, the growth of nurse practitioners has in many ways been good for the labor market and good for patients. Right. It's brought down costs and is the evidence.

[Jacob Goldstein]

I haven't looked at the evidence. On this in particular, the evidence is

[David Autor]

not, there's, there isn't enough evidence on this.

[Podcast Host / Interviewer]

Okay.

[David Autor]

So I mean, I.

[Jacob Goldstein]

There isn't clear evidence one way or the other.

[David Autor]

That's right.

[Jacob Goldstein]

Okay.

[David Autor]

There's one paper I know of, but it's in a very, very limited scope. So I would, it's in the Veterans Administration anyway. But I think, like, from a, from a, like, like I brought my kids to the pediatrician and I began bringing my kids to the pediatrician. There were no nurse practitioners and I would wait hours to see the pediatrician. He was terrific. But then it was like a half day lost by the time my kids were 10, right? I would just go into the pediatrician's office and boom, I would see a nurse practitioner. And it was so great. And they were attentive, right? And they were knowledgeable. They're up to date and they were accessible. And of course, and that's a high pay job and it's growing rapidly. So now that's not a function of AI, Clearly.

[Jacob Goldstein]

Right? Okay, so now we have this structure. Bring AI into the story. Now, how does AI bear on the story?

[David Autor]

So AI gives people tools to accomplish complicated things that might be out of reach without those tools. But let me be clear, it doesn't mean anyone can do anything. Doesn't mean I can just go into doctors often. Be a nurse practitioner, right? You need to have domain knowledge, right? I have to understand, like, what do I do if someone starts bleeding or has a heart attack. I need to understand, you know, a ton of things. But given that with better tools, I can do more. Right? So AI can help with diagnosis, right? It can help figure out how a medical practitioner should allocate their time and attention. An appointment with a nurse practitioner, even in a clinic, maybe 12 minutes, maybe 20 minutes. There's a ton that could happen. Having a tool that says, hey, here's the medical record, this is what we saw last time. Here's your high priority item, and here's the right resources. And then between the AI and yourself, you can say, okay, now I can triage this and decide, should I send this person home, Should I refer them upward? Can I from them now? And so it's a force multiplier for your expertise, Right. It enables you to go further. And that would be true whether, if you're doing legal work, if you're doing accounting work, if you're developing software. Software is an area where AI is going to allow lots and lots of entry. A lot more people can do software using AI because they don't have to understand as much of the kind of engineering of coding. Now, as you hear, software is going to exist at many levels. The people who are training AI models, running data centers, doing enterprise software, they will be very specialized, very highly paid, but there will be a lot more software. That's like Uber drivers. Right. Oh, I want someone to vibe code an app for my home to do X, Y and Z. I can easily find someone who can write that software for me because they'll just use an AI. Probably you won't do it yourself. Probably you'll still hire someone.

[Jacob Goldstein]

I mean, that's not obvious to me. Why do you say probably you won't do it yourself?

[David Autor]

There's, you know, for example, you can easily build a website, Right. Using wix or Squarespace. But most people who have a business, they hire someone to build a website for them. Why? Well, one, there's a lot of design that goes into it. It's not just a matter of getting it running. Right. And two, there's a lot of back end behind it in terms of oh, it's going to take payments, oh, it's going to, you know, but these things seem aiable so that, you know, it could change. But there are many, many things that you could in theory do for yourself.

[Jacob Goldstein]

I would not want to be in the website building business right now.

[David Autor]

I don't know.

[Jacob Goldstein]

Right. Does that not like.

[David Autor]

I'm not sure.

[Jacob Goldstein]

You can definitely do design and backend work with whatever.

[Podcast Host / Interviewer]

Claude.

[David Autor]

We'll see.

[Jacob Goldstein]

Yeah, we'll see.

[David Autor]

I think the likelihood is there will be more entry. It'll come in at lower cost, but more people will be able to do it and you know, just like the Uber example. So I think there will be more demand for software because it's cheaper. There'll be more people who can produce good software at lower cost. It will be less specialized and therefore I suspect it'll be numerically large, but it won't be as well paid as the typical software job.

[Jacob Goldstein]

So you'll have more software engineers and the median software engineer will make less than they make today.

[David Autor]

Yeah, and they won't have a degree in engineering. Right, right.

[Jacob Goldstein]

They'll just be somebody who's good at vive coding.

[David Autor]

I mean like, you know, website design now is primarily done by people who are designers, not programmers.

[Jacob Goldstein]

Yes, but design is something that AI is getting, it's getting better at.

[David Autor]

Absolutely, that's right.

[Jacob Goldstein]

So what are some other domains? I mean, you mentioned the law.

[David Autor]

So law is a good example, but again, law is a guild.

[Jacob Goldstein]

I could See, law being more hollowing out of the middle though, right? Like more, you know, you don't need to hire the junior lawyer. You don't need to hire or at least as many junior lawyers. You don't need to hire as many paralegals. You can have one lawyer with an army of agents.

[David Autor]

It's possible. But I think in many cases you want a knowledgeable, reliable, trustworthy person working with you.

[Jacob Goldstein]

Yeah. You the client, you the person who needs a lawyer.

[David Autor]

But you would like them to be efficient and cheap. Right. So you'd like them to be able to write a contract for you in an hour rather than a day.

[Jacob Goldstein]

Yeah. There are the sort of software first versions of this already, right. There's legal zoom has existed since before AI, actually for kind of routine things

[David Autor]

like a will or whatever. I mean, so in many cases, something is not legal unless it's done by a lawyer. Like if a lawyer doesn't sign it, it doesn't count.

[Jacob Goldstein]

This is the guild part, right?

[David Autor]

That's right. But even so, you could say, well, look, you know, more lawyers can offer some of these services at lower prices if they can do them effectively.

[Jacob Goldstein]

Yeah. Or you could have one lawyer with 100 call them paralegals plus AIs, and the lawyer is signing it, and the paralegal is talking to the customer and working with it.

[David Autor]

Okay. But even so, that would, in many ways would be a better world, right. Legal services would be cheaper and there'd be this whole layer of people who are doing that intermediate role. Right. As opposed to going to one very expensive person. And hopefully in the good scenario, there's a layer of people who are not just doing grunt work. They have some specialized knowledge. They're using the tools. Right. Often to use these tools, well, you have to know something.

[Jacob Goldstein]

So this is an important point, right? Because it's easy for me to imagine the world where you actually don't have to know much to use the tool. Well, right. And that this sort of current moment we're in is just the, you know, the foothills of real AI and it'll look like some terrible scratchy TV broadcast from 90 years ago in 10 years. Do you know what I mean? And so it seems totally likely that the AI could get good enough that you wouldn't need a paralegal like that. The paralegal wouldn't add value because the AI would just figure out what you needed better than a paralegal would.

[David Autor]

I don't want to dismiss that possibility, but I do think in many cases you're ultimately Going to want another person involved in what you're doing, whether for its medical care, whether it's for law, whether it's for design. And so you will want a person who has better tools and some specialized knowledge, but they will not be as expensive, they will be more productive. And let me say that, and this is something else to bear in mind. Many of these services that we're talking about, about law, design, contracting, even restaurants, they don't lend themselves to a superstar type model where one person does all the work. In entertainment, we have Taylor Swift, she can entertain 2 billion people at a time. And so it actually crowds out. It's hard in movies, in music, the superstars crowd out everybody else. And that used to be true in a time when we didn't have broadcast, we didn't have television.

[Jacob Goldstein]

Right. There was an opera house in every frontier town.

[David Autor]

But this can't be true in medicine, it can't be true in law, it can't be true in restaurants, it can't be true in contracting in many of these services because they're congestible, people have finite capacity. There's no doctor who can serve 2 billion people simultaneously.

[Jacob Goldstein]

Did you see the movie Her? You're describing the part right before the big reveal in that movie.

[David Autor]

It's a lot of hands on work and there's a lot of communication and I think so someone's gonna see the best doctor, someone's gonna see the median doctor, Someone's gonna see the 25th percentile doctor. Right. And if those doctors have better tools and better supports and decision supports, they will be better doctors.

[Jacob Goldstein]

Well, sure, that part is the easy part, but I feel like that's neither here nor there with respect to what we're talking about.

[David Autor]

No, no, no, that's very critical because it means that. It means that just because some doctor has AI, right? That doctor does not crowd out all the other workers.

[Jacob Goldstein]

Yeah, I mean, Dr. Is like a weird case. That is not like most things, right? Like, doc, like you care about having a person in the room, at least for now, when it's a doctor, more than you care about it with almost anything else. Right. Like with most legal stuff, I mean, unless it was some huge thing. As long as you, like everybody used the AI and you knew it was fine, you would just use the AI. Do you know what I mean? Like, for sure, at least in a lot of cases, yes, some people want a person, but do you know what I mean?

[David Autor]

I'm following what you're saying.

[Jacob Goldstein]

Somebody who's a teenager now, like they don't want to talk to a person. They would rather not talk to a person if they could. I know teenagers. Yeah. They live in my house.

[David Autor]

Yeah. I think medicine is maybe, is the strongest example. So.

[Jacob Goldstein]

Yeah, medicine is the strongest example. Yes. You want a person, you want a doctor or a nurse and it's, you're scared and.

[David Autor]

Well, I mean, let's first remember that medicine is a huge part of employment. It's also about 20% of US employment, healthcare, and it's growing. Health is sort of the ultimate luxury good. It's the one thing that as you get more and more affluent, you want to spend more and more on.

[Podcast Host / Interviewer]

Right.

[David Autor]

Because you don't want more and more food. Some people can have 100 cars, but most people are good with two. But your longevity and your well being, those are kind of fundamental to everything else that you do. And so, and you look at all these billionaire bros, right? Who are, you know, they have their blood boys and they're, you know, and they're spending infinite, you know, why are they doing that? Right. Why is healthcare becoming a larger and larger part of expenditure over time? Right. Because we're getting more affluent and so it matters more and they're getting more effective. Right. You know, there was 100 years ago it wasn't clear it was good for your health to go see a doctor. Right.

[Jacob Goldstein]

It was quite possibly bad for you.

[David Autor]

Exactly. Now there's just an amazing number of things and that number is expanding. So we will spend more on health services. It will be a larger part of employment. And of course we're aging, right? I mean our population is getting older. So it's not at all crazy to think this will be remain. And I don't care how much AI you throw in there, it's not going to shrink in terms of employment. It's going to be, it'll provide more services, ideally at lower cost and make it more accessible, but it's not going to become small. So although it is a special case, it's not like a little edge case.

[Jacob Goldstein]

It's a big special case.

[David Autor]

It's a big special case. Exactly.

[Jacob Goldstein]

We'll be back in just a minute.

[Podcast Host / Interviewer]

You probably think of Walmart and as

[Jacob Goldstein]

the store that carries just about everything

[Podcast Host / Interviewer]

under the sun and maybe not as the place to discover small brands. Well, two things can be true at the same time because Walmart is home to thousands of small brands founded by people who had an idea, took a chance and built something of their own. Behind everyone is a real story and a lot of hard work. So why not take a little time to recognize all the people building small brands across the country and support everything they're creating? Walmart is proud to give those brands a place on its shelves and online. It's never been easier to find and support small brands, so take a look at Walmart. You might come across something new, something unexpected, or a brand whose story speaks to you. You never know what you're missing until you look Discover thousands of small [e-mail] when you own your own business, you own every decision. Now own the card that rewards you for it. The Chase Sapphire Reserve for Business card brings the best Sapphire Reserve benefits to business owners who expect hard working rewards. Designed to meet the needs of business owners at scale, this Pay in Full card elevates your travel experience and offers premium benefits and value toward business services that'll take your business to the next level, fuel your business and maximize rewards with 8x points on all purchases through Chase Travel, 3x points on social media and search engine advertising, annual partnership credits and more. Make every journey more rewarding with a $300 annual travel credit and access to a network of airport lounges. Whether you're looking for pre flight productivity or time to rest and recharge. Chase Sapphire Reserve for Business it's the card that gives back all you put in. Learn [e-mail] ReserveBusiness Chase for Business make more of what's yours Accounts subject to credit approval restrictions and limitations apply. Cards are issued by JPMorgan Chase Bank NA member FDIC.

[Jacob Goldstein]

Did you ever notice how you spend

[Podcast Host / Interviewer]

hours shopping online only to pause right before you hit buy? Now that tiny hesitation, the one where you wonder if it's trustworthy, can make or break the sale. Now, with AI changing the way we discover and compare things, that split second trust question matters more than ever. That's where PayPal comes in.

[Jacob Goldstein]

For more than 25 years, PayPal has

[Podcast Host / Interviewer]

been a leader in online payments, and now they're at the forefront of agentic commerce, making it work for businesses, letting them maintain control of their brand and their customer relationships.

[Jacob Goldstein]

So even as the way we shop

[Podcast Host / Interviewer]

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[Jacob Goldstein]

I want to go back to the macro idea, right? So you have this argument, this story about how computers before AI essentially contributed to rising inequality, right? Like if you were in the top, whatever, 20% of the distribution computers are good for you. If you were in the middle, they were bad for you.

[David Autor]

That's correct.

[Jacob Goldstein]

In short, what's the macro story for AI?

[David Autor]

So I don't want to oversimplify. I think it's quite nuanced. It's possible that it will enable more competition in these high end services that we can spend so much money on and that could contribute to lowering inequality somewhat and sort of growing back. A different middle, right? A middle set of software engineers, a middle set of kitchen designers and contractors, A middle set of very skilled prepare people who, you know, there's a, there's a ton of knowledge and expertise involved. It's not all, you know, comes from college degrees. Right. People who are in the trades, who do electrical work, who do plumbing, who do, you know, construction.

[Jacob Goldstein]

I mean, people in the trades have been doing pretty well, Right, exactly. Avoided this hollowing out of the middle because a computer can't whatever, fix your, fix the wiring in your house.

[David Autor]

Yeah, absolutely not. That's right. And I think AI can actually be helpful and we already see examples of this. Right. You know, you can solve a harder problem. So that would create a better middle, a different middle. It wouldn't be the same middle. And so it's somewhat expertise leveling. Right. It creates competition where we desperately need it and creates opportunity for people who have appropriate skills, foundational expertise. Right. It's got to be, you got to know something about medicine, you got to know something about the trades, you got to know something about law, you need to know something about software. But maybe not as much. Right. You could imagine we have a four year healthcare degree, right. Where you learn a bunch of stuff and then you're ready to do a lot of services, a lot of health services. So that would be a world where there's more opportunity for middle skilled workers and lower prices. And so that would have less inequality. But I want to say that even if that's true my scenario, and there's less inequality, there's going to be a ton of disruption. Right. Because we're talking about expertise and sometimes being vacated. Right. If you're a medical transcriptionist, that job is almost gone, Right. If you're a language translator, some will remain and they'll be highly, highly skilled. Right. But there'll be fewer of them. I'm very worried about people who work in call centers. Right. There's several million of them. It's very disruptive, psychically damaging, economically scarring for people to have their expertise suddenly devalued the thing they know how to do for most people. Most people are doing the best paid thing they can do not everybody, right? Some people are podcasting, but ouch. Or professors, right? Many professors could, you know, there are higher paying things they could do. They love what they do. So most people are doing, you know, they don't have that luxury, right? They're doing the job that pays them the best income they can get. And if that work becomes less valuable, there's not an equally good job. Right. They're gonna have to. And that's like, why is loss of manufacturing work so devastating? Many cases, it's often specialized work that is relatively highly paid. And the alternative work for someone with that education is not going to be as good. So there's going to be a lot of change. And I expect AI to devalue some forms of expertise really rapidly. Others will become more valuable. And it's not the same people who are on the upside and downside. You could say the average is great, but no one experiences the average. And so even if you say, oh yeah, that could be a better world, it's like, yeah, but we don't get to that world overnight. And there's a lot of change that happens along the way and we should be investing and preparing for that.

[Jacob Goldstein]

So let's talk about that. I mean, and then we can be like, there's the policy we. And then there's like, I'm some guy, what should I do? So, like, what do we do on

[David Autor]

both of those levels? Let's start with the policy we. Yeah. Okay. So there are three buckets of things that I think are very important. One of them is to help people transition between jobs. So the first of those is wage insurance. Wage insurance is like, you work at a manufacturing job, you're making $50,000 a year, $25 an hour, you lose that job and you know, manufacturing is going down, there's not an equivalent job. And the next job you can get is 15 bucks an hour, $30,000 a year. And you say, I'm not gonna take that job. That's like beneath my dignity. And so you don't. And then you spend a long time looking. And that has its own costs. And people, the longer they're out of labor force, the harder they find again. So wage insurance says, hey, hey, we understand that we're going to make up half the difference between your $25 an hour job and your $15 an hour job up to a finite amount of time, up to two years, up to $8,000 total. And we're not telling you, stay in a low wage job forever, by all means, get a Better job. And we have evidence on it. Not enough, as much as we want. But during the 2010s, right, as part of the Trade Adjustment act, there was an experiment done with wage insurance. The result of this policy experiment was it got people back to work faster. And it was so effective that it paid for itself, in other words, by the reductions in unemployment insurance payments and the increase in tax revenue from people working. It was self funding. Now that's on a limited base of evidence. These were displaced manufacturing workers. They were older. But there are now major pilot studies underway, working with states. You know, more details will be revealed soon. They're quite expensive and they're, you know, they're funded to try this at a larger scale.

[Jacob Goldstein]

So wage insurance. This is one idea.

[David Autor]

That's right. And I'll call it. It's a no regrets idea in the sense that we won't be sorry we did it even if there isn't a jobs apocalypse. Right. It's a good idea. It was a good idea 20 years ago, it's a good idea now. It'll still be a good idea. And the idea is people are making transitions and those transitions are frictional, they're costly, it's psychically damaging. And when people are out of work for a long time, that has its own costs. You would like to facilitate them going back to work even while they continue to search.

[Jacob Goldstein]

And like I feel like subsidizing work, essentially paying people to work politically, it feels good.

[David Autor]

It does.

[Jacob Goldstein]

And frankly, for the people, like, I mean, work is valuable in our society and like you can feel different ways about that. But I basically feel good about that and like subsidizing people to work seems good to me frankly.

[David Autor]

And I think that fits with the American psyche. Right. Our political system is very hostile towards people who are not working. Right. If you're not working and you're not a kid and you're not elderly, what is wrong with you? Right. Is the kind of message. That's why we constantly, we're always putting these work requirements.

[Jacob Goldstein]

I mean, you're not making a normative statement. Just to be clear. You're describing the sort of political vibes.

[David Autor]

Yeah, no, no, clearly. No, no, I do not. I'm not endorsing that view at all. I'm just saying that that appears to be the perspective to the politicians. Right. That's why they say, oh, you can't get, you know, snap unless you're working. You can't get Medicare. You know, they're constantly trying to condition things on work. So this says it says, okay, like this is about supporting people to work. Okay, that's one thing. One. Okay, two. Two is we need to do retraining at scale much more effectively.

[Jacob Goldstein]

Yeah, retraining seems like it never works.

[David Autor]

Okay, See, that's what everybody says, but in fact, that's kind of based on old wisdom. We now know much more about.

[Jacob Goldstein]

Is AI really good at retraining people?

[David Autor]

No, we don't know that, but we do know of really effective training programs. Now, they're small, so like Project Quest Europe, Jewish Vocational Services, Goodwill. They're what are called sectoral training programs. They train people for specific occupations and activities. Right. So it could be construction, it could be a medical, technical, it could be diesel repair, et cetera. But we don't know how to scale those at a very large scale. So what folks are working on now is trying to evaluate those things in real time using big data, without experiments. And so you can actually measure the incremental earnings that are coming out of these programs and then recycle some of that incremental revenue to feed back into these programs. Because we need to have a phalanx of options available to people. Right.

[Jacob Goldstein]

I mean, that one. Maybe I just am out of date on it, but, you know, like your own work on the effect of competition from China on, you know, workers in the US and the first part of the century. Like, it's interesting to me that you found more recently that, like, the towns that were really impacted by. That the towns have come back to some extent. Right. But the specific workers who were displaced have not.

[David Autor]

That's correct. But that we did nothing to retrain them. Right. I mean, there was no policy in place. Right.

[Jacob Goldstein]

So you think it's a policy? You think. You think a policy could have helped the person who was somewhat 50 to take my approximate age. Got laid off. Yeah. Okay.

[David Autor]

Yeah. I mean, it's not a panacea, but it's something. And you know, other countries do this much more effectively than we do. Right. You know, Denmark. Right.

[Jacob Goldstein]

I was afraid you were going to say Denmark. It's always Denmark.

[David Autor]

I know, I know. Everyone's like, you know, don't tell me about Scandinavia. Like, it's not a real place. I don't even believe it exists.

[Jacob Goldstein]

It doesn't map to the U.S. right.

[David Autor]

Well, I agree. I think that's absolutely right. We can't do the den, the Danish system. But it's a. It's an existence proof of. You can do it. Well, right. They're effective.

[Jacob Goldstein]

They can do it.

[David Autor]

Well, it can be Right. So that's why my main, second major policy is to send all unemployed workers to Denmark where they can be retrained. I just think that's.

[Jacob Goldstein]

And have an incredible safety net and swim in the harbor in Copenhagen.

[Podcast Host / Interviewer]

Exactly.

[David Autor]

It's going to.

[Jacob Goldstein]

What's number three?

[David Autor]

Okay. Number three is what I call universal basic capital. Other people call it that as well. So let me distinguish it. Universal basic income is the notion that, you know, whether you're working or not. We just write you check every month from the largesse of the Tech Bros. Or whatever.

[Podcast Host / Interviewer]

Yes.

[David Autor]

I don't think the political economy of that is viable for the same reason we just had the conversation about. We don't like to. As a country, we're just not supportive of people who are not working or we don't believe in unconditional transfers. So universal basic capital is a little different idea. It says, look at the time you were born, we're going to give you an endowment of capital. It doesn't have to be a lot of. You can call them.

[Jacob Goldstein]

Does capital mean stock? Can we just say stock? Is that what you mean?

[David Autor]

We call them Trump accounts. Right. Which is what exists already, right?

[Jacob Goldstein]

Yes.

[David Autor]

And it's a. It's an asset. You can, you know, it's. You can't spend it until you're of age.

[Jacob Goldstein]

So like, just. Just to be a little more specific, the notion is like the government will. Whatever, a fund, an ETF, a mutual fund that tracks the S&P 500.

[David Autor]

That would be a great way to do it.

[Jacob Goldstein]

Give $1,000 to every baby.

[David Autor]

Exactly.

[Jacob Goldstein]

And you now own $1,000 of S&P 500 stock and you can't touch it till you're 18, is that what you're thinking?

[David Autor]

Exactly. And you can invest in it further. Right. Just like you can. You have tax advantage 401k savings. Right.

[Jacob Goldstein]

You have like a 529. Like a college savings account or something. Exactly.

[David Autor]

Yeah. So, like, what is the purpose of this? It does three things. One is it diversifies people. Right. So most people's lifetime income is bound up in the value of their skills and expertise. And it's always vulnerable. It's always risky.

[Jacob Goldstein]

Right. It's labor. Most people make most of their money from working.

[David Autor]

Exactly. From their labor.

[Jacob Goldstein]

That's what you're saying.

[David Autor]

It's always risky to have all your eggs in one basket. Right. Especially if you do something specialized and all of a sudden that thing becomes obsolete. That's really risky. So one is, it gives you. It's by no means a Complete diversification start. But it's a start. Right. And especially with tax. That's one thing. Two, if we think we're entering a world where capital is going to rise in value relative to labor. Right. That there'll be less. Then you especially want to have people have money and capital. Right?

[Podcast Host / Interviewer]

Yeah.

[Jacob Goldstein]

Meaning if more of the national income is going to go to companies, go to the owners of shares of stock and less is going to go to labor. Right. The two places it can go. Then you want more people to own stock if you want everybody to prosper.

[David Autor]

Exactly. That's right. And labor is. Everyone is born in the good scenario with one worker themselves who works for them. But capital is not like that.

[Podcast Host / Interviewer]

Right.

[Jacob Goldstein]

Some people are born with a lot and most people are born.

[David Autor]

Most people are born with zero. That's right. And the third thing it does is universal base capital, again is it gives them an ownership stake, almost like a voting stake in the economy.

[Jacob Goldstein]

Yes. Well, I mean most companies you have voting rights if you own stock. Although not all.

[David Autor]

Exactly. And so if we were. I'm very worried about a society where more people are seen as claimants without being seen as contributors.

[Jacob Goldstein]

So claimant rather than contributor. That's the universal basic income world. That's the world where the machines take our jobs and people just get a check every month or whatever.

[David Autor]

I don't morally oppose that. Let me be clear. I just don't think it's. I don't think our body politicians tolerates it.

[Jacob Goldstein]

Yes, well, and our structures of meaning and of value are not well set up for that.

[David Autor]

That I also agree with. That's even a secondary point. So that's. So universal capital says, you know, again, it's a very small step in the way, but says, look everyone now, hey, I'm not just a claimant, I'm a contributor. I own part of the capital.

[Jacob Goldstein]

And in this universe is the government just buying shares in the in stock and everything and giving it to people.

[David Autor]

Sure. But it's not that hard to do. Like there's only about 4 million babies born a year in the United States. Right. So if you had to write them each a check for $1,000, that's 4 billion bucks. Right. That's less than we spend on, you know, I don't know, anything you can. Anything, any bomb you can drop.

[Jacob Goldstein]

Yes, yes.

[David Autor]

So it's not.

[Jacob Goldstein]

But I mean, so $1,000, I suppose compounding it becomes non trivia.

[David Autor]

That's right. And you can do more than that. Right. You could even say to billionaires Say, hey, you know what? Here's a tax advantage way that you could donate to the public, take your shares and just throw them into the baby bond fund and they will be distributed.

[Jacob Goldstein]

That's nice, right? Yeah, that's interesting. I mean, it's sort of a distributed sovereign wealth fund, right? It sort of rhymes with the sovereign wealth fund.

[David Autor]

That's, that's exactly, exactly what it is. Exactly what it is. But a sovereign wealth fund, right? You don't get to choose your own investments. You can't say, I need to take it out today.

[Jacob Goldstein]

No, it's not yours in the way that what you're proposing would be yours.

[David Autor]

So, you know, and again, none of these policies, the three I talked about, you know, wage insurance, you know, modernized training, they're small.

[Jacob Goldstein]

Ish. Right? They're.

[Podcast Host / Interviewer]

They're smallish.

[David Autor]

That's right. None of them is. And I think we need big, we face big challenges. These are around the edges, but they're all what I call no regrets policies. Right. We won't be sorry we did them. Even if the worst doesn't come to pass. These are things that are just, they are wise in terms of helping people make transitions and giving people diversification. In the good scenario, if we use it well, we're going to become more affluent, but that doesn't mean we're going to have. That will be well shared. Right. We need a society which says, look, if there's going to be an AI dividend, meaning we become more productive. We want to make sure that people are brought along. Right? That if your expertise becomes devalued, that there's new ways to train that get you back in the labor market, that your portfolio, your income sources are more diversified. The science fiction writer Ted Shang said, look, when people are saying, oh, people are scared of automation, they're scared of machines. They're not scared of automation, they're scared of capitalism. They're scared of their work will be automated and there'll be nothing left for them. They won't get paid. It's not that people are opposed to higher productivity or things being more convenient. They're opposed to losing their livelihoods. And AI could produce a lot of higher productivity and a lot of convenience automation, but put a lot of people out of work, at least temporarily during the transition. Right? So no wonder people are afraid of it. Right? No wonder people are opposed. No wonder people are angry about data centers. They don't trust our social and political systems to ensure them and make sure they're brought along. So it's very understandable. So I would like to take the edge off of some of that. I would like to have policies that help support the challenges you help people through those challenging things that some of them are likely to ahead even in the good scenarios.

[Jacob Goldstein]

We'll be back in a minute with the lightning round.

[Podcast Host / Interviewer]

You probably think of Walmart as the

[Jacob Goldstein]

store that carries just about everything under

[Podcast Host / Interviewer]

the sun and maybe not as the place to discover small brands. Well, two things can be true at the same time because Walmart is home to thousands of small brands founded by people who had an idea, took a chance and built something of their own. Behind every one is a real story and a lot of hard work. So why not take a little time to recognize all the people building small brands across the country and support everything they're creating? Walmart is proud to give those brands a place on its shelves and online. It's never been easier to find and support small brands. So take a look at Walmart. You might come across something new, something unexpected, or a brand whose story speaks to you. You never know what you're missing until you look Discover thousands of small [e-mail] when you own your own business, you own every decision. Now own the card that rewards you for it. The Chase Sapphire Reserve for Business card brings the best Sapphire Reserve benefits to business owners who expect hard working rewards. Designed to meet the needs of business owners at scale, this Pay in Full card elevates your travel experience and offers premium benefits and value toward business services that'll take your business to the next level, fuel your business and maximize rewards. With 8x points on all purchases through Chase Travel, 3x points on social media and search engine advertising, annual partnership credits and more. Make every journey more rewarding with a $300 annual travel credit and access to a network of airport lounges. Whether you're looking for pre flight productivity or time to rest and recharge, Chase Sapphire Reserve for Business it's the card that gives back all you put in. Learn [e-mail] reservebusiness chase for business make more of what's yours Accounts subject to credit approval restrictions and limitations apply. Cards are issued by JPMorgan Chase Bank NA member FDIC.

[Jacob Goldstein]

Did you ever notice how you spend

[Podcast Host / Interviewer]

hours shopping online only to pause right before you hit Buy? Now that tiny hesitation, the one where you wonder if it's trustworthy, can make or break the sale. Now with AI changing the way we discover and compare things, that split second, trust question matters more than ever. That's where PayPal comes in.

[Jacob Goldstein]

For more than 25 years.

[Podcast Host / Interviewer]

PayPal has been a leader in online payments, and now they're at the forefront of agentic commerce, making it work for businesses, letting them maintain control of their brand and their customer relationships.

[Jacob Goldstein]

So even as the way we shop

[Podcast Host / Interviewer]

changes, the moment that matters most still feels familiar and deeply dependable. Built for payments, growth and agentic. PayPal open. Built for all business. Visit paypalopen.com to get started.

[Jacob Goldstein]

Let's finish with the lighting round. Okay. What's the most peril you've ever been in on a sailboat?

[David Autor]

Actually, I went. I took my. I went sailing during a hurricane.

[Jacob Goldstein]

Bad idea. Yeah.

[David Autor]

And I got knocked over six times.

[Jacob Goldstein]

On purpose?

[David Autor]

Well, no, I tried to stay upright.

[Jacob Goldstein]

No, no. Did you go sailing in a Hurricane Lee?

[David Autor]

Yeah, I went sailing in Hurricane Lee a couple years ago in New Hampshire on a.

[Jacob Goldstein]

A couple years ago. I was gonna ask if you were 14.

[David Autor]

No, no, no. I was 59, but I. I have an ultralight RS Aero. It's like a laser and it's super fast and it's very competent even in high winds. And I really wanted to try it out. It was small lake, people were like, I. My neighbors were all there with the cameras. I assumed that if I started to drown, they would have, I don't know,

[Jacob Goldstein]

sent the footage to see.

[David Autor]

Exactly, exactly. So, yeah, that was perilous. That was. That was exciting.

[Jacob Goldstein]

And did you capsize?

[David Autor]

Six times. Six times.

[Jacob Goldstein]

Six times.

[David Autor]

It was exhausting. It was completely exhausting.

[Jacob Goldstein]

It's like a little boat and you can kind of lean and ride it.

[David Autor]

Yeah. You have to climb on the dagger board and pull it up and then throw. You have to do what's called the walrus, where you, like, sort of throw yourself out of the water into the center of the boat. Otherwise it capsizes back on you. So that was fun.

[Jacob Goldstein]

What's it like teaching college students in the age of A.I.

[Podcast Host / Interviewer]

at the dawn of A.I.

[David Autor]

the students I teach are MIT students, and it's a great.

[Jacob Goldstein]

So they're really good at prompting.

[David Autor]

They're really good. They're super motivated. It's a real luxury. So I don't worry that they.

[Jacob Goldstein]

It's perhaps never been a better moment to be an MIT student than right now.

[David Autor]

That's right. And to be an MIT professor because I don't worry that they're going to take all the shortcuts and not learn anything. They're super hardworking. So I feel like they're just powered up.

[Jacob Goldstein]

They're building the tools for everyone else to take the shortcuts and not learn

[David Autor]

anything and they know how to use the tools well, right? So I feel like I can push them harder and say, go figure this out. Right?

[Jacob Goldstein]

Well, are you building AI into your classes or just assume they're going to use AI to figure things out and that's good.

[David Autor]

My curriculum assumes they're using AI. Like for example, I've down weighted out of class exams, right? I still get problem sets and they're hard, but they don't count as much. You have to do it on exams or on your papers. So I expect they're using it, but they know that eventually they will have to demonstrate the knowledge. But I can throw the harder stuff at them, say, you'll solve this. I can also say, hey, this can't be as badly written as it is right now because you have better tools, so go do it again. And of course, when I'm building my lectures, I can incorporate new material more quickly because I can build slides and master stuff faster myself.

[Jacob Goldstein]

Most peril you've ever been in on a motorcycle.

[David Autor]

You're always in parallel on a motorcycle.

[Jacob Goldstein]

Yes, that is the correct answer. Anything else we should talk about?

[David Autor]

I will say I think a lot of young people are extremely anxious about AI and I understand why. But I also think they are the group that's going to use it well, better than the rest of us and figure out what to do with it. There's never been a technology that's made old people great at the cost of young people that I'm aware of. Almost all new technologies are developed and pioneered and ultimately figured out by younger generation that figures out what to do with it. And so I think businesses are now looking very hard to find AI native kits. I think there's a lot of risk. I understand the uncertainty and the fear. I don't want to diminish that. But I was thinkers opportunity.

[Podcast Host / Interviewer]

David Autor is a labor economist at mit. Please let us know what you think

[Jacob Goldstein]

of the show, what you want to

[Podcast Host / Interviewer]

hear more of, what you want to hear less of. Particular guest ideas.

[Jacob Goldstein]

You can email us at problemushkin fm. I read all the emails.

[Podcast Host / Interviewer]

You can also find me at on x or on LinkedIn. Really do appreciate all the messages that we get.

[Jacob Goldstein]

Today's show was produced by Gabriel Hunter Chang and Trina Menino.

[Podcast Host / Interviewer]

It was engineered by Hans Dale. She and edited by Lydia Jean Cott.

[Jacob Goldstein]

I'm Jacob Goldstein and we'll be back

[Podcast Host / Interviewer]

next week with another episode of what's yous Problem? When you think about discovering small brands, what store pops into your mind? Well, it should be Walmart. Seriously. Walmart has thousands of small brands and they're all in one place. Just go online or in store, discover and shop. It could not be easier. Every one of these brands has a real story and real people behind it. They're true American success stories and you can find them all at Walmart. Discover thousands of small [e-mail] today. This is Malcolm Gladwell from Revisionist History. Life moves fast at American Military University. They're ready to help you keep up. AMU's flexible, affordable online programs in cybersecurity, IT space studies and more are designed for service members, veterans and their families. AMU provides the support you need to take the next step wherever life takes you. American Military University Made for what's next. Learn more at AMU Apus Edu if

[David Autor]

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[Jacob Goldstein]

This is an iHeart podcast.

[David Autor]

Guaranteed Human.