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And basically, from the moment that happened, it's not like this seismic shift. Because all of a sudden, people everywhere realize just how powerful artificial intelligence already is. They began using this AI chat bot to do all sorts of things. To 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 follow into this like, doom spiral these days.
But then a couple weeks ago, I saw something that gave me this little glimmer of hope. It was a study that looked at this customer service department of a big software company. And they started using chat GPT 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, even 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. Yeah, there's a whole generation of research looking at the effects computers have had on the labor market. 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 arrow we're in is going to be different. If 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 Ruselsky. I'm going to be a little different.
We found your conversation with David Otter. It's 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?
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? So whether it's a piece of clothing or building house or a tool, the air 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 accomplished in sequence, often by machines, managers and pretty low-scale workers. And so a lot of artisanal skill was displaced. The lot of it rose up for a reason. Otter 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. They're talking automobiles instead of textiles.
And so factory owners started to need workers with more skills. Over time, that work became more skilled in adding. 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 can follow those rules well.
So this created what you might think of as the kind of middle skill that 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. You 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 for your college degrees, these were the relatively better paid jobs, right?
They're better paid than for example, food service, cleaning, security. And the reason is that food service can secure their 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 industrial economy.
It needs to be expert work of some sort. By expert, 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. I don't want to say it's only technology, right? There are institutions that went with this.
There was democracy. There was obviously the system that educated people, but the technology helped. So okay, the industrial revolution, it killed off jobs for skilled artisans, but then it created a whole bunch of new jobs for middle school workers. Companies 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 school jobs that emerged from the industrial revolution, they started getting automated away.
Think robots taking jobs on assembly lines or computer software taking jobs from administrative office workers. At the same time, computers made higher school 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 re-king tasks.
On the other hand, if you are someone who does like Dextrous Manual work, like food service, cleaning, security, and payment recreation, there's really not much complementarity there at all. It doesn't make you much better. It doesn't make you worse. It's not very easy to move up.
If you're an adult and you're just placed for your manufacturing job, it's very unlikely you're going to get a law degree or medical degree. So you're going to more likely end up driving a truck, working in a restaurant, working in a security guard. And so the computer area actually devalue that mass expertise and massively amplified demand for elite expertise, which has been really not so great. It's not great if you're not a elite worker, because it's pretty great if you're an elite worker.
It's been a great four decades for elite workers, especially in those days. But to put in and crude words, technological change in over the last few decades has increased inequality. And now it feels like maybe a lot of people are not going to be able to do that. So in crude words, technological change in over the last few decades has increased inequality.
And now it feels like maybe just maybe we're in a new era, like, you know, I was already starting to think this and then this new empirical study came out by Eric Bernielson, Danielle Lee, and Lindsey Raymond, that looked at what happened to a software company and its workers after the company adopted an old version of ChatCHP team. 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 school 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, I should get annoying with these, I also have a paper where they did a sort of a related experiment working with people doing writing tasks. And these are people who are college educated and do like advertising, copying 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 pulled up the bottom very considerably. So 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 Reynoldsen 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. So 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. So right now, if you want to do a lot of medical procedures, you need a medical degree. That takes a decade. 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 have 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 are having an example of that. So the nurse practitioner, peer-spectators who has an additional master's degree, they're a nurse practitioner.
Okay, great. And so nurse practitioner are well paid. Their median pay is about $150,000 a year. And they do many of the things that only medical doctors were allowed to do.
They diagnose, they prescribe, they treat. And how is that compatible? Partly it's a change in medical norms and scope of practice. Partly they're enabled by technology.
There's a machine that said, don't put those two prescriptions together. That would be a problem. And 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 and something could use AI to make that expertise go further.
So the goods scenario is basically where AI lowers the cost of elite expertise, makes it more available and increases the value of basic and middle skill workers in the future. That's my good scenario. So to translate potentially AI good for the middle class, good for rebuilding the middle class. That's like the whole.
That's the good scenario. That's like the headline. And 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. We live long here with a plug for our latest bonus episode where we take you inside a reporting on social media influencers. There's kind of a magic number where it becomes, I can do this for a living and that's less than 1%.
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 at rabbit hole and hear how our indicator series on the dark and mysterious economy of influencers came together. That's our latest bonus episode available now for our Planet Money Plus supporters.
If that's not you, it could be. Learn more at plus.mpr.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.
But at the same time, computers also made a bunch of good middle class jobs disappear. Other things, maybe AI could help reverse that trend, lift a whole bunch of workers back into the middle class, like 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. All 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. That basically, you will see some expensive expert work just less in demand, that you will need fewer managers, 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 fewer of them.
So, yeah, I think it's possible. But in the long run, that means fewer people have to go to college, which expensive. And it also matters, right? This is not a zero-sum game.
If it makes us all more productive, we're wealthier as a result of that. So you have to displace this on what you do, but 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 evolve some disruption of people at the top. You know what? They've been doing so well for so long that maybe you got to crack some eggs and make it on what? That's right.
I don't think they're just going to be thrown out of the top. I don't think they're all going to be thrown out of the top floor of office buildings. These things happen gradually. Yeah.
So that's the optimistic scenario. I just want to bounce off the dystopian kind of, and maybe this is the truly dystopian as they become sentient and kill us all. 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, focusing on the economics. Other than that, how is the blame? It's just like it.
I can still imagine like a narrative or a potential future where it's actually AI is inequality increasing. So one scenario, obviously, like companies who own these systems will get insanely rich, but then there's also like 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 future? I don't want to rule out.
So you can imagine a world where you just need a few super experts overseeing everything and everything else is done by machines. So that's one possibility. Another possibility is one where no one's labor is scarce. That's not a good world because then we have lots of productivity, but nobody who owns it, just the owners' capital.
Then we have to have a revolution and it's not going to 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. We have very low fertility rates.
We have large populations who are retiring and we have radically restricted immigration. And so the US population is growing at its lowest rate since the founding of the nation. And most industrialized countries and China as well, by the way, are facing this problem of 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 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. I am worried about the devaluation of expertise. Well, just for clarity though, because you just said I am concerned about the devaluation of expertise. But also though it sounded like you were excited about the devaluation of expertise.
No, no. Anybody can do it. I worry about world where no one's labor scarce. But let me give you an example of what I mean by this.
Like for example, you might say, oh, Waze makes everyone an expert driver. But no, actually it doesn't make anyone an expert driver. It has the expertise. So there was a time when let me taxi cab drivers needed to know all the highways and bivalways of London, which is a years to master.
It was 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 pastors. It's good for consumers.
So I'm not going to use expertise. Would you call that de-skilling, essentially de-skilling? And it devalues expertise. So I realized that's not in the chat with her.
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 value skill and now they still have that skill. They still have the skill that's valuable.
It's not scary, 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. It 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. I'm curious where your head is at. Like, where are you?
Because you seem hopeful that it could rebuild the middle class if we channel it. But then there's all these other who knows where this is going. Yeah, I think there's an optimistic, there's a positive scenario for 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 controlled critical systems to surveillance and monitoring and coercion to very, very dangerous weapons, smart weapons that can autonomously do all kinds of terrible things. So I think there's lots of reasons to be scared about how it can be used.
The irony is that labor market is the least scary part of this at the moment. Well, thank you very much. I really appreciate it. Sure thing, Greg.
It was a pleasure speaking to you. Thanks. It 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. You 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 Katherine Silva. This is Jay, and this is Planet Money's acting executive producer. I'm Greg Vysalski.
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