Is AI Actually Stealing Your Job? The Truth About the Current Labor Market | Ep. 22

Larry Port (00:00):
Dream job or nightmare? It’s hard to know if a career that looks great on paper will actually lead you to the life you want to live. So welcome to DreamJob Cafe. I’m Larry Port. I’ll be asking different professionals the questions you won’t find anywhere else. So grab a coffee, settle in. This is Dream Job Cafe. Sponsored by Wayspark.co, where we help people navigate careers in a crazy world.

(00:25):
Hey everybody. I’m Larry Port, and this is a new type of episode for the DreamJob Cafe Podcast. I don’t have a guest today where I’m interviewing them about what it is that they do or how to prepare for an interview or something like that for the job market. What I have today is kind of what I like to do, which is research what’s happening with the labor markets and AI and all this kind of stuff. And I have a lot of thoughts about this. And there’s a lot being published through The Wall Street Journal and the New York Times and a lot of different other publications. So I’m always trying to keep up to speed with what’s being done. And there’s a lot of academic research coming out. There’s just a lot of economic reports that come out from the Bureau of Labor Statistics, there’s think tanks.

(01:13):
Everybody kind of wants to know what’s going on with AI in the labor market. Are we all going to be laid off? And there’s a lot of people that think that yes, we are. But the truth of the matter is that the data right now suggests that that’s not really what’s happening. And there’s a lot to this. But what I thought I would do is I would review what’s going on in the press right now and why it may be counterintuitive to think that, oh, just because AI is out there, it’s not going to gobble up everybody’s jobs. That said, I am an optimist and I always like to look on the bright side of things. But to me, the arguments for us not having all of our jobs consumed by AI is a strong one. I do think that there will be winners and losers in this economy.

(02:01):
And I think that if there’s a lot of work that you do that’s especially white collar work that’s very routine, that’s an area that we may have problems. But I think for the most part, the offsets, the gains from new types of employments are going to be better than the losses that we’re going to see. And that’s not just my opinion, that’s shared by the Brookings Institution, that’s shared by the New York Fed, that’s shared by the World Economic Forum and their 2025 Future of Work Report. So it’s kind of all over the place, but let’s kind of just dig into it and I’ll go through some of the recent headlines. All right. So another new thing we’re doing with the DreamJob Cafe is we’re starting a YouTube channel. So this is going to be on YouTube if you want to watch there. And if you want to just listen to it and take a look at the slide decks, we’re also going to be publishing the slide so you’ll be able to download those if you go to the show notes.

(03:00):
So I’m calling this new segment, by the way, the WTF Is Up Report. So it’s the Wayspark WTF Is Up Report. Wayspark is the company that sponsors this podcast. It’s my company. So here we go. So the first article in the WTF Is Up Report is this one. This is from the New York Times. The headline is all scary, but I think that’s just clickbait. But I would have to say, and I’ll include a link to this article unlocked in my notes for this episode, that this is probably the best article to read that kind of goes over this uncertainty about what is actually happening in the job market. Is it AI or is it something else? So the headline, which could change based on what link you click on, but the subheadline is artificial intelligence could reshape work, but for now, a low higher, low fire labor market is the main impediment for young people seeking employment.

(03:57):
There’s no doubt that it’s hard right now for young people to find a job in the spring of 2026. But this isn’t the first time it’s been hard for young graduates to find work upon graduation. This happened to me when I was graduating school in the early ’90s. Actually, I graduated in the mid ’90s, but the people that were graduating in the early ’90s who really had a hard time. This happened after the economic collapse in 2008 and it was happening during COVID. But I think the issue is that because AI is developing so rapidly in the backdrop, is this what’s causing everything? At least that’s what people are concerned about. So people are seeing two things happening simultaneously, a bad job market for entry level work, and they’re saying also AI transforming work, and they’re kind of putting those two things together, but it might not necessarily be the case.

(04:51):
So this is from the article. It says, although AI may be replacing some entry level jobs on the margins, there is little evidence that it is the main culprit. I’ll repeat that. There’s little evidence that it’s the main culprit, at least not yet. Rather, many economists believe employment challenges for young people with college degrees stem more from the low hire, low fire dynamics in the labor market. And there’s a lot of different reasons why we’re in a low higher, low fire dynamic. Part of the reason a lot of software engineers were laid off was because there was a lot of talent hoarding. So there were major talent wars between the big companies like Facebook and Microsoft and Amazon and these big technology companies that needed as much brain power as they could get. And a lot of times these people were kept on the bench.

(05:43):
So part of the major layoffs had to do with getting rid of all this extra talent, right? That’s one dynamic. So what else do they point out? Well, if you look at these trends, it’s kind of like what I was talking about before. So this is kind of a chart which is an unemployment rate for all people. If you see one bad trend that we’re seeing is that the number of people, and you can see the gray line is all the workers and the yellowish line is people without a degree, and the orange line are people with a degree. And normally you see all workers have a higher unemployment rate than young people. That’s upside down right now. Now young people are more unemployed than all workers. So that’s not good. That is definitely not good. This was the case back in COVID as well, I will say.

(06:38):
And if you see those without a college degree, you see that big spike that was COVID where a lot of people didn’t have any work. And you see a huge uptick in unemployment in 2010. We’re not where we were in 2010, 2009, that was after the economic collapse. We’re not there. In fact, historically, we’re kind of in the middle, if you were to draw lines to this graph, right? It is going up, but where we currently stand is somewhere in the middle. So this kind of gives a little bit of context is that yes, it is a problem. It’s always a problem when not enough people can find work, to be honest, but across the entire spectrum of people, it’s not as bad as it has been in recent history by a wide margin. So that’s one thing to keep in mind. In terms of why they’re slow to … Why people aren’t getting jobs so quickly, there’s a number of explanations, but one is, and this is another reason for maybe Gen Z people to get mad at the boomers.

(07:42):
And if that’s how you feel, listen, whatever, I don’t want to go there. But part of the reality is that there’s just more older workers in the workforce. The article goes on to say, since the 1970s, the share of older workers in the labor force, particularly in private sector white collar jobs, has grown as life expectancy has increased and Americans have worked longer. I mean, one thing that’s also not being mentioned here is that most people get their healthcare through their employers. And when you’re older, you’re going to have more healthcare problems and that insurance becomes more valuable. So the whole way that our health insurance works in this country also contributes to people like sticking around their jobs longer, which impacts youth employment. Anyhow, this economist Pardue says, this has created a congestion in the workplace resulting in less progression for mid and early career employees who would otherwise have moved up the career ladder.

(08:42):
When more senior workers retired, basically there’s people at the top who are gumming up all the works without as much improvement in their ranks, without as much movement rather in their ranks. Many businesses found they did not need to replace as many entry level workers. And the quote is, “As the US population has aged, older workers are continuing to hold onto their positions.” That is showing up in terms of diminished job prospects for younger workers. So that’s another explanation. So there’s multiple explanations for why this is going on. It’s not just that AI is coming in and wiping out jobs. So there’s kind of an opinion economist that writes for The Wall Street Journal. His name is Greg Ip. This came out last month and this was kind of an interesting response to what happened where Jack Dorsey … Jack Dorsey is the guy who started Twitter and now he has a payments company and he laid off 4,000 people and he said he was just being honest.

(09:45):
We’re going to have to do this because AI’s going to do it. I’m just the first to the table. Okay, maybe, maybe not. So Greg Ip’s argument is basically going into history and looking at these disruptions. He says, neither theory, history, nor the latest data. That’s true. The latest data too suggests recession driven by AI dislocation is likely. So what Mr. Ipp says here is that if such a revolution were upon us, we should see some sign of it. We don’t, at least not yet. Now, he also says at least not yet, which is like what the New York Times article said. “The ranks of software developers widely assumed to be acutely vulnerable to AI because ClaudeCode can write software development are up 5% in January. That’s 2026 from a year earlier, a pace largely consistent with the past 23 years. That’s according to labor department data analyzed by James Besson, executive director of the Technology and Policy Research Initiative at Boston University.

(10:53):
So heavy hitters, looking at all this stuff. That’s the good news if you’re feeling like, ” Oh, shit, this situation is hopeless for me. “A lot of people are looking at this. Heavy, heavy hitters are looking at this. What this guy says, Greg Ip, he says,” In reality, businesses are risk averse and consumers creatures of habit. Radiologists were supposed to lose their jobs to offshoring and then to AI because a radiologist’s job is to be able to look at a scan, a digital image and identify things. And so everybody was always predicting that these jobs were going to go away because they could just send the jobs to India for overnight processing, but they didn’t because patients and providers like having humans around to explain their medical images. This is another one that’s kind of mind-boggling. Since Google Translate launched in 2006, the number of human translator and interpreter employees in the US has risen 73%, which is kind of mind-blowing.

(11:56):
So this is like a big topic of conversation. You have the people in the AI companies that are losing their minds that we’re going to create this general intelligence and it’s going to completely screw us up, but not everybody feels that way. So this book is written by Reid Hoffman and Greg Beto. Reed Hoffman, I don’t know who Greg Beto is. I’m assuming he’s a ghostwriter, but Reid Hoffman is the guy who started and runs LinkedIn. And I’m just going to read from the introduction to his book because I just started it and that’s all the further I’ve gotten, by the way, but it’s particularly germane to this discussion. So he writes this. “Throughout history, new technologies have regularly sparked visions of impending dehumanization and societal collapse. The printing press, the power loom, the power loom is where the Luddite term came from, the telephone, the camera, and the automobile all face significant skepticism, and sometimes even violent opposition on their way to becoming mainstays of modern living.

(12:59):
“So as a case in point, he points this thing out, and this is kind of an interesting story. 15th century, so you’re in the 1400 now, doommongers argue that the printing press would dramatically destabilize society by enabling heresy and misinformation and by undermining the authority of the clergy and the scholars. Well, that kind of did happen, if I’m not mistaken, I do think that the Protestant Reformation was driven by the printing press, but anyhow, let’s keep going. The telephone was characterized as a device that could display the intimacy of in- person visits and also make friends too transparent to one another. It’s really crazy when you look back on these inventions, what the concerns were. In the early decades of the cars ascent, this one is wild, critics claimed it was destroying family life with unmarried men choosing to save up for model Ts instead of getting married and having kids and married men resorting to divorce to escape the pressures of consumptions that cars help create.

(14:09):
They talk about stuff that happened in the 1950s. When I was a kid growing up, ATMs were introduced, automatic telling machines, everybody thought there’s going to be no bank work. And what happens is that we kind of endure. We like the face-to-face interaction. So that’s one argument is that just because it’s there doesn’t mean we’re going to use it. People still use candles. People still listen to vinyl records. There are technologies that have come in to replace these things, but we choose to use certain items for certain things. And it appears that one of the things that we’re seeing in the workforce so far is that people still want humans around. They still want their bank tellers and they still want their radiologists to be face-to-face. So the other thing that I consumed recently that I thought you might be interested in was a podcast for those of you that don’t like to read.

(15:04):
So there is a very interesting series called The Last Invention, and it’s about AI. And in the last episode, episode 11, he interviews, the journalist interviews three AI, he calls them skeptics. I don’t know that they’re necessarily skeptics. They might just have a different take than the AI doomers out there. The first skeptic can skip over that guy. He has nothing interesting to say. He just sounds like a kind of crazed conspiracy theorist. The second and third ones are worth listening to, but I want to highlight the third one. The second one has kind of more of a technical argument, but the third one goes along these lines. And his whole thing is that AI is going to roll out, but it’s not going to have the kind of pivot event that everybody’s anticipating, which is going to cause kind of widespread societal collapse. So he argues that it is more like everything else, that it just takes a long time for things to roll out.

(16:13):
And he points to the electrification of America. The electrification of America is a big thing that people talk about when they talk about how ideas and technology changes. Nicholas Carr in the book, The Big Switch, talks about the electrification of America and how cloud computing is likely to follow a similar trajectory, and he’s largely right. So the electrification of America is one of these things that people point to, and it took a long, long time. It just didn’t happen overnight. And this field of how technology is transmitted and used by people, the term is called diffusions. And there was a seminal work on this by a guy named Everett Rogers, and his book is called The Diffusions of Innovations. And you’re probably familiar with maybe the technology adoption lifecycle curve where you had early adopters and you had late laggards and things like that, but this field is studied.

(17:14):
And what the author is saying, and his name is very long, and I’m going to butcher it, so I’m not going to say it, but they say that the speed of diffusion is inherently limited by the speed at which not only individuals, but also organizations and institutions can adapt to technology. So it’s not just the fact that AI is invented, but it’s how fast can people communicate with one another to figure out how to use it inside of their workplaces and inside of government institutions and any other organizations where people have to work together. So in the academic paper, the authors write, “As an example, Paul A. David’s analysis of electrification shows that the productivity benefits took decades to fully materialize.” Electric dynamos were everywhere, but in the productivity statistics for nearly 40 years after Edison’s first central generating station. This was not just technological inertia.

(18:14):
Factory owners found that electrification did not bring substantial efficiency gains. So there’s market forces at play as well. And you’re starting to see this as well too, where you’ve started to see a lot of CEOs say that they’re planning on reducing their workforces, but then recently they’ve been saying that the gains they’re seeing from AI are not all that, at least not yet. So everything’s kind of like a wait and see, and it’s at least not yet. But if we’re going to look at the current evidence, and if we’re going to take a look at history, I think humans have a lot to root for here. So my advice to you is to maybe read about this stuff, follow the links in the show notes and make your own informed decision, but I think we’re in good shape. And with that, I’ll let you go.

(19:07):
And thank you for listening. If you like this show, please like it or send it to your friends. And if you can, please be grateful for something today.

Larry Port (19:16):
Thanks for listening. Don’t forget to like and subscribe to DreamJob Cafe on Spotify, Apple Podcasts, or wherever you listen. And don’t forget to check out Wayspark.co, where we help people navigate careers in a crazy world.