How AI could help rebuild the middle class

17 May 2023 · 21 min

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Planet Money Episode Summary: How AI Could Help Rebuild the Middle Class

Episode Overview In this episode of *Planet Money*, the discussion revolves around the potential of artificial intelligence (AI) to reshape the labor market and possibly restore the middle class, which has been shrinking for over four decades. The episode features insights from David Autor, a prominent labor economist at MIT, who shares his perspectives on how AI could be a force for greater economic equality.

Key Themes and Discussions

The Current State of the Labor Market

  • Technological Inequality: For the past 40 years, technology, particularly computers, has contributed to growing inequality, leading to a shrinking middle class.
  • Job Polarization: Higher-skilled jobs have become more valuable while middle-skill jobs have diminished, leading to a workforce split between elite workers and low-skilled labor.

Historical Context

  • Industrial Revolution: Introduced mass production and transformed labor, initially displacing skilled artisans but eventually creating more middle-skilled jobs as machines became more complex.
  • Computer Era: Starting around 1980, automation began to eliminate many middle-skilled jobs while enhancing the productivity and earnings of elite workers.

Potential of AI

  • Empirical Studies: Recent studies suggest AI might help narrow the productivity gap. For instance, the use of ChatGPT in a software company increased productivity among lower-skilled workers while having little effect on higher-skilled employees.
  • Reversing Trends: Unlike previous technological advances, AI may empower lower-skilled workers, potentially reversing the trend of shrinking middle-class job opportunities.

Good vs. Bad Scenarios

  • Optimistic Scenario: AI lowers the cost of elite expertise, making it more accessible and potentially increasing the value of middle-skilled jobs. For example, AI can enhance the capabilities of roles currently reserved for highly educated professionals.
  • Example: Nurse practitioners performing tasks usually done by doctors, facilitated by AI tools.
  • Pessimistic Scenario: AI could further entrench inequality by concentrating wealth among those who own AI technologies while devaluing expertise across many professions, leading to job losses for lower-skilled workers.

The Role of Policy

  • Autor emphasizes the need for smart government policies to navigate the transitions AI brings to the labor market. The hope is to harness AI's potential while mitigating its risks.
  • There is a belief that even if certain jobs may become less valuable, the overall productivity gain could lead to a wealthier society.

Societal Concerns

  • Broader Implications: While the labor market may be the least concerning aspect of AI's rise, there are significant worries regarding its misuse, such as misinformation, surveillance, and potential autonomous weapons.
  • Adaptability and Value of Human Labor: Despite the rise of AI, humans retain advantages like adaptability, emotional intelligence, and physical presence in jobs where direct human interaction is essential.

Conclusion The episode concludes with a cautious optimism about the potential of AI to restore the middle class. However, it highlights that achieving this requires proactive measures from various sectors, including government, education, and industry.

Key Takeaways

  • AI has the potential to either improve or worsen economic inequality.
  • Historical context is crucial to understanding current labor market challenges.
  • Proactive policies and strategic implementation of AI are essential for fostering an equitable economic future.
  • Human adaptability and unique skills will remain valuable in the AI-driven economy.

This episode serves as a critical examination of the intersection between emerging technology and economic structure, urging listeners to consider both the opportunities and challenges that lie ahead.

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0:00Support comes from our 2025 lead sponsor of Planet Money, Amazon Ads. Less than half of customers fully trust their financial institutions. Amazon Ads helps financial brands build that trust through relevant ads using first-party signals to reach the right customers. More at advertising.amazon.com. This is Planet Money from NPR. It's been about six months since ChatGPT was released to the public. And basically, from the moment that happened, it felt like this seismic shift. Because all of a sudden, people everywhere realized just how powerful artificial intelligence already is. They began using this AI chatbot to do all sorts of things.

0:47To write raps, to take the bar exam, to identify bugs in computer code and fix them. I mean, all that stuff is pretty cool. But at the same time, there's been all this doom and gloom about AI. Will it take our jobs? Will it derail democracy? Will it kill us all? And these aren't like off the wall questions. Like serious people are asking these questions right now. Yeah, it's kind of easy to fall into this like doom spiral these days. But then a couple of weeks ago, I saw something that gave me like this little glimmer of hope. It was a study that looked at this customer service department of a big software company.

1:24And they started using ChatGPT to help workers get better at their jobs. And interestingly enough, it worked. Like, it made the less skilled workers at this company much more productive. And at the same time, it didn't do much for workers at the top. So basically, AI narrowed the productivity gap between lower skilled workers and workers with more skills. And Greg, I think it's fair to say you read a lot of economic studies. Probably too many. And yet, you have been telling me, you've been telling all of us, that this finding felt really big to you because it's different from how we usually understand the way technology affects workers.

2:02Yeah, there's a whole generation of research looking at the effects computers have had on the labor market. And over and over again, what economists find is that for decades now, computers have been this major force for increasing inequality. What this study shows is that AI could be different. And when I saw that, I was like, you know what? I want to talk to David Otter. David Otter, professor at MIT, widely regarded as one of the greatest labor economists in the world. Otter led a lot of that research that found computers were this force for a shrinking middle class. And I wanted to find out if he thinks maybe this new technological era we're in is going to be different.

2:41If maybe AI could be a force for greater equality. Right. So hello and welcome to Planet Money. I'm Nick Fountain. And I'm Greg Groselsky. And Greg, today's show is going to be a little different. We found your conversation with David Otter so interesting, so illuminating, so prescient that we're just going to run it. Today in the show, the American middle class has been shrinking for more than 40 years. Could AI help reverse that trend?

3:33Thank you. retirement, buying a home, or managing debt. Using rich first-party insights, Amazon Ads connects brands with the right audiences where they browse, buy, and stream. Learn more at advertising.amazon.com. When David Otter thinks about how AI will affect the future of work, he actually looks to the past. He sees two major turning points when technology fundamentally changed our economy. The first turning point was a long time ago. We're talking about the Industrial Revolution, when machines began to replace work that had previously been done by hand. So prior to the Industrial Revolution, there was a lot of artisans, people who did all the steps in making a product, right?

4:25So whether it's a piece of clothing or building a house or a tool, Well, the era of mass production created an alternative way of making things. And it was basically breaking things down into a series of small steps that would be, you know, accomplished in sequence, often by machines, managers, and pretty low-skill workers, right? And so a lot of artisanal skill was displaced. I mean, the Luddites rose up for a reason. Potter says that at first, the factory jobs that displaced the artisans required less skill and also paid less. So kind of a bummer. But then machines got more complex and so did the things they could make.

5:06You know, we're talking automobiles instead of textiles. And so factory owners started to need workers with more skills. Over time, that work became more skill demanding because people had to follow formal rules. And if you're using a lot of expensive equipment and making precise products and using expensive inputs, you need people who are kind of can follow those rules well. So this created what you might think of as the kind of middle skill, what I would call mass expertise, right? This is like the golden era that we hear a lot about in the United States, this time when people could graduate from high school with basic reading and math skills and then go out and find gainful employment.

5:47You know, jobs on factory floors or jobs in offices where workers had to understand how to compile paper records or deal with basic financial transactions. For people who didn't have four-year college degrees, these were the relatively better paid jobs, right? They're better paid than, for example, food service, cleaning, security, and so on. And the reason is that food service, cleaning, security, they're valuable pursuits. They do important things in the world, but most people can do them. And so they're not going to be well remunerated. For work to be well paid, especially in an industrial economy, it needs to be expert work of some sort.

6:24By expert, But I mean, one, you need a certain body of knowledge or competency to accomplish a thing. That thing must be worth accomplishing, right? And not everyone can do it. And so it did the case that the kind of industrial era helped really grow the middle class. It created this tailwind where people with a reasonable amount of education all of a sudden made them highly productive in offices, highly productive in factories, highly productive in sales. And so, yeah, it created this huge rising tide that was relatively equalizing. Now, I don't want to say it's only technology, right? There are institutions that went with this.

6:57There was democracy. There was obviously the system that educated people, but the technology helped. So, OK, the Industrial Revolution, it killed off jobs for skilled artisans. But then it created a whole bunch of new jobs for middle-skill workers, jobs that gave opportunities to Americans without a college degree. That's turning point number one. The second big turning point is computers. This is what a lot of David Otter's research has focused on. He finds that in the computer era, starting around 1980 or so, all of those middle-skilled jobs that emerged from the Industrial Revolution, they started getting automated away.

7:38Think robots taking jobs on assembly lines, or computer software taking jobs from administrative office workers. At the same time, computers made higher-skilled workers much better at their jobs. This elite group benefited a bunch from using email, building spreadsheets, searching the internet, I don't know, like trading stocks and information instantaneously all over the world. So if you're a highly educated worker, if you're a doctor or an attorney or a marketer or researcher, those people are highly strongly complimented by this sort of automation of these information processing and routine tasks.

8:18on the other hand if you are someone who does like dexterous manual work like food service cleaning security entertainment recreation there's really not much complementarity there at all right doesn't make you much better doesn't make you worse however you have lots of people in the middle who are now being pushed out of those middle skill occupations and it's just not very easy to move up right if you're an adult and you're displaced from your manufacturing job it's very unlikely you're a law degree or medical degree. So you're going to more likely end up driving a truck, working in a restaurant, working as a security guard.

8:50And so the computer era actually devalued that mass expertise and massively amplified demand for elite expertise, which has been really not so great, right? It's just me - Not great if you're not an elite worker, because it's pretty great if you're an elite worker. It's true. It's been a great four decades for elite workers, especially in the United States. But to put it in crude words, technological change over the last few decades has increased inequality. Sure. And now it feels like maybe, just maybe we're in a new era. I was already starting to think this, and then this new empirical study came out by Eric Brynjolfsson, Danielle Lee, and Lindsay Raymond that looked at what happened to a software company and its workers after the company adopted an old version of ChatGPT.

9:33And they basically find that this AI system makes their workforce much more productive. But more interesting to this conversation, they found that only some workers benefited from it. And it was actually the less experienced, lower skilled workers that benefited from use of the technology. And the more experienced, higher skilled workers saw little or no benefit. And to me, that kind of, it seems to be like reversing what we've been seeing, where it's complementing the bottom and not really doing much for the top. And I just want to get your reaction to those findings. Sure. And actually, my students, Shikhad Noy and Whitney Zhang also have a paper where they did a sort of a related experiment, working with people doing writing tasks.

10:12And these are people who are college educated and do like advertising copy and so on. And some use chat GPT and some didn't. And basically they found that using the large language model, it made everyone more productive by saving them a lot of time, but it pulled up the bottom very considerably. So the people who were only pretty poor writers on this scale became average and people who were excellent became a little better. And so it reduced productivity inequality. So it's very consistent with the paper by Rynolfsen and Lee and Raymond. So that's interesting. I didn't know about that study. So now we have two empirical studies that are showing that it's pulling the bottom up and maybe doing a little for the top, but maybe not doing much.

10:57So there's a big implication there. Yes. There's a big possibility there. So the good scenario is one where AI makes elite expertise cheaper and more accessible, right? So right now, if you want to do a lot of medical procedures, you need a medical degree. That takes a decade, right? And that makes those people scarce, expert, and expensive. But you can imagine that with the right tools, you could devolve some of those tasks to people who know something about medicine and healthcare, but they don't have to have that level of education. And then they could do much more. And we already have an example of that, right?

11:34So the nurse practitioner, nurse practitioner is a nurse who has an additional master's degree. My sister's a nurse practitioner. Okay, great. And so nurse practitioners are well-paid, right? The median pay is about$150 ,000 a year. And they do many of the things that only medical doctors were allowed to do, right? They diagnose, they prescribe, they treat, right? And how has that come to pass? Well, partly it's a change in medical norms and scope of practice boundaries. Partly they're enabled by technology, right? There's a machine that says, don't put those two prescriptions together. That would be a problem.

12:06And this set of symptoms is associated with this constellation of diseases. Check the following. And you can imagine many ways in which people with foundational skills in something could use AI to make that expertise go further. So the good scenario is basically where AI lowers the cost of elite expertise, makes it more available, and increases the value of basically the middle-skilled workers of the future. That's my good scenario. So to translate, potentially AI good for the middle class. Could be. Good for rebuilding the middle class. That's like the hope. That's the good scenario. That's like the headline.

12:48And not just hope, we got to make it happen. That's the headline right there. Like David Otter hopes that AI is good for the middle class. No, no, no. Let's use AI to reinstate the middle class. What it will take to make that happen. And also the other scenario David Otter imagines, the one that doesn't go so well for workers. That's after the break.

13:17This message comes from Capital One with the Venture X Card. Earn unlimited double miles, a$300 annual Capital One travel credit, and access to airport lounges. Capital One, what's in your wallet? Terms apply. Details at CapitalOne.com. This message comes from Charles Schwab. When it comes to managing your wealth, Schwab gives you more choices, like full-service wealth management and advice when you need it. You can also invest on your own and trade on Thinkorswim. Visit schwab.com to learn more. Waylon Wong here with a plug for our latest bonus episode, where we take you insider reporting on social media influencers.

13:58There's kind of a magic number where it becomes, I can do this for a living, and that's less than 1%. And yet some Gen Zers say it's their dream job. I mean, that way I can earn money as I'm just like at home, just playing video games. Follow us down that rabbit hole and hear how our Indicator series on the dark and mysterious economy of influencers came together. That's in our latest bonus episode available now for our Planet Money Plus supporters. If that's not you, it could be. Learn more at plus.npr.org. So for years, David Otter has been looking at the effect of technology on the labor market, and he finds that computers made elite workers better at their jobs and much richer.

14:41But at the same time, computers also made a bunch of good middle-class jobs disappear. Otter thinks maybe AI could help reverse that trend, lift a whole bunch of workers back into the middle class by helping them get better at writing or research or, I don't know, creating complicated legal documents. Basically, AI could allow them to do jobs currently reserved for the upper echelon of the labor market. That's what David Otter calls the good scenario. But even in this good scenario, no, there's going to be a disruption of people who are currently making, I don't know,$100 ,000 to$200 ,000 a year or something like that.

15:21All of a sudden, it doesn't make as much sense to pay those people as much anymore because you have a whole pipeline of people who now do that job. That's correct. It's possible that basically you will see some expensive expert work just less in demand, that you will need fewer managers for certain types of decision making, that more legal work will be done by machines as opposed to by lawyers, and that you'll have lawyers, but they're supervisory and there are fewer of them. So yeah, I think it's possible. But in the long run, that means fewer people have to go to a college, which is expensive.

15:55And it also matters, right? This is not a zero-sum game, right? If it makes us all more productive, we're wealthier as a result of that. So even if it just places on what you do, but then the rest of what you do, you do it 10 times as fast, that's a gain in productivity. So you're hopeful on the labor market thing contingent on smart government policy, essentially. Smart government, smart private sector, smart philanthropy, smart universities. And so maybe that will involve some disruption of people at the top. But you know what? They've been doing so well for so long that maybe, you know, you got to crack some eggs to make an omelet.

16:30That's right. And I don't think they're just going to be thrown out of the top. You're not going to say, that's right. I love that though. I don't think they're all going to be just like thrown out of the top floor of office buildings. I, you know, this is, these things happen gradually. Yeah. So that's the optimistic scenario. I just want to bounce off the dystopian kind of, and maybe this isn't, I mean, the truly dystopian is they become sentient and kill us all. But the dystopian economic – Or we – actually, the more likely dystopian is some – we use it to kill one another. Yeah. Okay. So putting that aside, putting human existence aside, I'm focusing on the economics.

17:10Other than that, how was the play, Mrs. Lincoln? Yes. I can still imagine like a narrative or a potential future where it's actually AI is inequality increasing. So one scenario, obviously, companies who own these systems will get insanely rich. But then there's also the downstream effects where there's a whole bunch of industries where a bunch of people used to do the job, but now only you need one or two people to do it. So what do you think about that sort of pessimistic potential? I don't want to rule it out. So you can imagine a world where you just need a few super experts overseeing everything and everything else is done by machines, right?

17:51So that's one possibility. Another possibility is one where like no one's labor is scarce, right? That's not a good world because then we have lots of productivity, but nobody who owns it, just the owners of capital, right? Then we have to have a revolution and blah, blah, blah. It's not going to work out well, right? Those things never work out well. So I don't view those scenarios as highly likely. One thing to recognize is that we are actually in a period of sustained labor scarcity because of demographics, right? We have very low fertility rates. We have large populations who are retiring and we have radically restricted immigration.

18:27And so the U.S. population is growing at its slowest rate since the founding of the nation. And most industrialized countries, and China as well, by the way, are facing this problem of they're getting smaller and older or their populations are not growing. That's a world where we need a lot more automation, actually, to enable us to do the things we need to do, including care for the elderly. So I'm not worried about us running out of work and running out of jobs, Stu. I am worried about the devaluation of expertise. Just for clarity, though, because you just said, I am concerned about the devaluation of expertise.

19:02But also, though, it sounded like you were excited about the devaluation of expertise because then anybody could do it. I'm worried about a world where no one's labor is scarce. But let me give you an example of what I mean by this. For example, you might say, oh, Waze makes everyone an expert driver. right but no actually it doesn't it doesn't make anyone an expert driver it has the expertise right so there was a time when london taxi cab drivers needed to know all the highways and byways of london which is a it took years to master right it was an incredible feat of memorization and then that made them really expert they could get you around london better than any other driver well now you don't need to know that you just need a phone right and that's good for passengers it's good for consumers but it devalues the expertise that would you call that de-skilling Deskilling, essentially de-skilling.

19:50I would say it devalues the expertise. So I realize that's not, didn't meet you halfway there. But what I mean is - It sounds like de-skilling to me because they used to have a skill that was, oh, I guess it was a valuable skill and now they still have that skill. They still have the skill, it's just not needed. But it's just less valuable. It's not scarce, right? So the expertise of being a London cabbie has been substantially devalued. Okay, so yeah, that's one of Otter's big worries that what happened to London cabbies kind of happens to the entire labor force, that AI makes human expertise kind of irrelevant.

20:24It devalues it. But David Otter doesn't actually think that will happen, at least not for all workers and not anytime soon. He says people still have all of these advantages over AI. Like we're more adaptable. We have more common sense. We're better at relating to other people, not to mention we have bodies. We have arms and legs and we move around in the world. Like there's a bunch of things about being a human that still have advantages in the marketplace. So AI raises all of these different possibilities. Some more promising, some kind of scary, some very scary. And I just want to end by getting sort of the big picture gut check from David Otter.

21:05I'm curious where your head is at. Like, because where are you? Because you seem hopeful that it could rebuild the middle class if we channel it. But then it's also like there's all these other who knows where this is going. Yeah, I mean, I think there's an optimistic, there's a positive scenario for the labor market. But that's the labor market side. I think there's many reasons for concern about how AI could be misused in all kinds of other ways, right? From misinformation to control of critical systems to surveillance and monitoring and coercion to very, very dangerous weapons, smart weapons that can autonomously do all kinds of terrible things.

21:48So I think there's lots of reasons to be scared about how it can be used. The irony is the labor market is the least scary part of this at the moment in my mind. Well, thank you very much. I really appreciate it. Sure thing, Greg. It was a pleasure speaking with you. Thanks. This was really a lot of fun. If you enjoyed this episode, we've got more AI content on the way. Next week, we will be launching a three-part series where we try to figure out whether we can replace all planet money with AI. Yeesh. If you just want more insightful planet money content about the economy from a real-life human being, subscribe to the newsletter that I write.

22:30You can find it at npr.org slash Planet Money newsletter. This episode was produced by Dave Blanchard and edited by Molly Messick. It was fact-checked by Sierra Juarez and engineered by Catherine Silva. Jess Jang is Planet Money's acting executive producer. I'm Greg Grzalski. This is NPR. Thanks for listening.

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From the publisher
For the last four decades, technology has been mostly a force for greater inequality and a shrinking middle class. But new empirical evidence suggests that the age of AI could be different. We speak to MIT's David Autor, one of the greatest labor economists in the world, who envisions a future where we use AI to make a wider array of workers much better at a whole range of jobs and help rebuild the middle class.

This episode was produced by Dave Blanchard and edited by Molly Messick. It was fact-checked by Sierra Juarez and engineered by Katherine Silva. Jess Jiang is Planet Money's acting executive producer.

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