Scott Detrow (1:51)

From npr, I'm Scott Detrow.

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Connor Donovan (3:11)

It's consider this from NPR. AI CEOs talk a lot about the

Scott Detrow (3:15)

potential of AI to cure diseases, generate

Connor Donovan (3:18)

enormous wealth, solve some of humanity's most vexing problems. But as you heard earlier, they're also surprisingly direct in talking about the potential downsides. And a big one, one that we're all of the sudden hearing a lot more about is what it could mean for our jobs. It is easy to panic when you start reading about computers replacing humans. So we wanted some perspective from people who are watching AI's impact on the economy closely. I called up Kelsey Piper, a staff writer at the Argument, and Martha Gimble, executive director of the Yale Budget Lab, to get a sense of this AI moment and some possible AI futures. Let's start with that.

Scott Detrow (3:53)

It feels like in the past few weeks this conversation about AI job loss has bubbled out of the tech world and into the mainstream. I mean, I for one have gotten like a half dozen texts from freaked out friends sending stuff around like, what's going on here, Martha?

Connor Donovan (4:06)

Why do you think this is happening right now?

Martha Gimble (4:08)

I think part of it is that there legitimately has been an acceleration in what the technology can do over just the last couple of months. I think there's also a broader issue which is that people are just incredibly anxious about the economy right now and where it's going. If you look at, you know, whether people think they're going to lose their job in six months relative to where the unemployment rate currently is, they're really negative. And then of course, when people are piling on saying that we aren't going to have any jobs in two years, that's not going to help.

Scott Detrow (4:42)

That that does create some anxiety. Kelsey, you have been covering AI since, you know, since ChatGPT was a twinkle in Sam Altman's eye.

Connor Donovan (4:50)

Can you explain to us some specific examples of what these models can do

Scott Detrow (4:56)

now that they couldn't do a year ago? Six months ago?

Kelsey Piper (4:58)

Yeah. So the biggest launch in the last six months has been the wide launch of agent models, which are, instead of just responding to you in a chat screen, they go out and do things. The biggest thing they do is code. They are really remarkably good at writing code. A year ago I was hearing from people. It's nice because you can, like, ask it some questions and it will speed up your coding. Six months ago I was hearing from people. It's kind of like having a grad student that you can ask to run some analyses for you. Now I'm hearing from programmers. I don't really write code anymore. I just write a spec and then the AI builds the code that I asked them to build.

Scott Detrow (5:37)

So this is a specific thing that gets better and better and more and more autonomous. And that is a real trend that is happening.

Kelsey Piper (5:43)

Very much so.

Scott Detrow (5:44)

Okay. So, Martha, a lot of jobs are theoretically at risk, but I want to start by looking at what we actually know. Already you and your colleagues at the

Connor Donovan (5:52)

Budget Lab have been looking at the actual data. What does it show so far, at

Scott Detrow (5:56)

least about AI related job loss?

Martha Gimble (5:58)

That there really isn't any. Certainly at the macroeconomic level, you can look at the technology and you can see the potential to. But you need to remember that technological related labor market disruption is not instantaneous. It happens in the context of IT policies, company concerns about liability, broader economic growth trends.

Kelsey Piper (6:20)

And so I think it's really important

Martha Gimble (6:21)

to keep all of those things in mind when talking about what jobs are going away, becoming more popular, and how fast this may happen.

Connor Donovan (6:30)

That is what is happening now.

Scott Detrow (6:31)

That is what has been happening over the past year.

Connor Donovan (6:33)

That doesn't mean things couldn't change going forward.

Scott Detrow (6:35)

And I know you and your colleagues

Connor Donovan (6:36)

have compared this in many ways to the Industrial Revolution.

Scott Detrow (6:40)

Why is that a good way to think about this?

Martha Gimble (6:43)

I think the thing about the Industrial Revolution is you did see a really big shock to labor. I think sometimes you hear economists talk and we will say at the end of technological change, living standards are higher. We are always better off. I do want to emphasize the period of disruption can be really, really hard for people. I am very grateful that I have a job that is more highly paid and I have higher living standards than the weavers did. I also would not have wanted to be a weaver during that time period. You know, their lives became really, really hard. And I do think we need to think about is our social safety net prepared for the type of disruption that could possibly be coming.

Scott Detrow (7:33)

And Kelsey, I know you spend a lot of time, you know, really optimistically thinking about worst case scenarios of AI.

Kelsey Piper (7:39)

Yep.

Scott Detrow (7:39)

Where does the Industrial Revolution type scenario fit there? Like, do you think that is the high end worst case scenario? Or how are you thinking about this right now when you think about what could happen over the next five to 10 years?

Kelsey Piper (7:50)

Yes. So I think Martha is entirely right that we have not yet seen significant AI associated job loss. I think almost everybody who's worried about this, what they're doing is not so much, oh, I've already lost my job to AI. Most of what people are saying is, all right, imagine that we learned the new class of students entering the workforce in 2028 was going to be 10 million people, 100 million people, and all of them are willing to work for pennies. You know, maybe in the long run, the economy will end up being much wealthier because of this huge influx of productive labor. But as people who will be competing with that productive labor, we are not necessarily thrilled. So if you think that that's is going millions and millions of AI agents that will work basically for free, then I think people are completely right to be scared of that. You know, that will probably, in the absence of very decisive policy action, make your life worse.

Connor Donovan (8:47)

Both of you are saying in different

Scott Detrow (8:48)

ways, a lot of the outcome will depend on policies. Federal government policy, state government policy. Are you seeing those policies being carried out? Serious conversations in any way, shape or form right now?

Kelsey Piper (9:02)

I think that right now the government is being caught very flat footed. But one thing that we saw with COVID was that if a shock does hit very suddenly and affect a huge share of the American public, Congress can move into action very fast. But that's not the only way this is guaranteed to happen. And if instead you have much more creeping job loss and disruptions, I think it's very easy to imagine Congress not getting their act together.

Scott Detrow (9:28)

I want to end with this tsunami of Internet takes that started this conversation. A lot of them kind of ended with, here's what you can do as an individual. And I personally veer between like, okay, I need to learn a lot more about how these large language model programs work and incorporate into my job. Or I want to go entirely analog. I hate this all and I'm just going to get offline. Both of you think about this a lot more than most people. What is like one thing you would say to somebody in the job market right now, Martha?

Martha Gimble (9:56)

I mean, one thing, frankly, I would say is to take some of the takes that are circulating out there with a grain of salt. People are not thinking enough about what are the barriers to get things established and going in companies, how long it takes for companies and workers to figure things out. There's also a question of what people want. I'm sure that at some point in the future someone could build maybe a robot that could raise my child. For me, I'm not having a robot raise my toddler. And I think that's a pretty common reaction. And so we have to see how consumers respond as well.

Scott Detrow (10:32)

What about you, Kelsey?

Kelsey Piper (10:34)

Yeah, I think it is worth keeping in mind that it is both true that AI is a really big deal. And at the same time, a lot of takes are hysterical. A lot of takes are selling you something. Anybody in particular who's like, you have only a few years to become a millionaire or you're like consigned to permanent poverty? I don't think that's true. Often when you into it, they're trying to convince you to gamble, which is one of those ways to, in fact, make sure you end up in poverty. There is certainly a ton of nonsense out there.

Scott Detrow (11:02)

That is Kelsey Piper, staff writer for the Argument, and Martha Gimble, executive director and co founder of the Yale Budget Lab, two very smart human beings. Thank you so much to both of you for talking to us about this.

Martha Gimble (11:14)

Thank you for having me.

Kelsey Piper (11:15)

Yeah. Thanks so much.

Connor Donovan (11:17)

This episode was produced by Connor Donovan. It was edited by Courtney Dorning.

Scott Detrow (11:21)

Our executive producer is Sami Yenigun.

Connor Donovan (11:25)

It's consider this from npr.

Scott Detrow (11:27)

I'm Scott Detrow.

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