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The AI Job Crisis Andrew Yang Saw Coming

Prof G Markets

Fri Apr 24 2026

Summary

Prof G Markets: The AI Job Crisis Andrew Yang Saw Coming

Date: April 24, 2026
Hosts: Scott Galloway, Ed Elson
Guest: Andrew Yang
Main Theme:
Exploring the AI-driven job crisis, labor market disruptions, and potential policy solutions with 2020 presidential candidate Andrew Yang, who first sounded the alarm on automation and the need for Universal Basic Income (UBI).

Episode Overview

This episode confronts the reality of AI's accelerating impact on the labor market, a trend Andrew Yang had warned about years ago. Hosts Scott Galloway and Ed Elson engage Yang in a candid debate about whether job loss is truly spiking, which populations are most at risk, and what American policymakers—and Silicon Valley—should be doing. The conversation covers recent labor data, skepticism around layoffs attributed to AI (“AI washing”), and a detailed back-and-forth on potential solutions, including UBI, negative income tax, and the retraining and future of America's workforce.

Key Discussion Points & Insights

1. AI’s Real-World Impact on Jobs

(05:08 – 14:09)

Current Layoff Data:
- 55,000 layoffs attributed to AI in the previous year; rising unemployment among recent college graduates (up to 5.6%, the highest outside pandemic years).
- Recent mass layoffs at Oracle (30,000 jobs) and other tech companies (Amazon, Pinterest, Block) are increasingly blamed on AI.
“AI Washing” Phenomenon:
- Companies use AI as an excuse for layoffs that may also stem from overhiring or other factors.
- Not all layoffs are directly due to AI, but there’s clear executive intent to “do more with less” and eventually automate tasks currently performed by humans.

Andrew Yang (11:25):

“One of the convos I relate to people was with CEO of a publicly traded tech company who told me flat out, ‘we’re going to fire 15% of workers this year, then another 20% two years from now...’ And he's not alone. I've had maybe a dozen CEOs with similar conversations."

Labor Participation & Entry-Level Crunch:
- Labor force participation declining; computer science grads struggling for jobs that were easy to secure a few years back.
- The “canary in the coal mine” is arguably college grads, especially in white-collar, junior roles.

2. Debate: How Severe is the AI Job Crisis?

(14:09 – 19:23)

Skepticism from Scott Galloway:
- Historical pattern: Every tech revolution sparks short-term job losses, but eventually yields new jobs and higher productivity (e.g., the PC, automation in auto industry).
- Unemployment is still low; where is the strong data that AI is truly decimating jobs?

Scott Galloway (12:39):

“Where’s the actual evidence that AI is destroying jobs?...It looks so far like it's being used to augment workers' productivity, which ideally would lend itself to higher wages.”

Yang’s Counterpoints:
- Labor force participation stats obscure those who've simply stopped looking for work.
- Severe drop in entry-level hiring, particularly in fields previously considered secure.
- Companies openly redirecting layoff savings into AI infrastructure (data centers over offices), highlighting a structural shift.

Andrew Yang (16:25):

“The compute infrastructure is the new human being.”

3. Policy Solutions for an AI-Disrupted Labor Market

(19:23 – 26:00)

Retraining Skepticism:
- Retraining programs for displaced workers have shown little effectiveness (0-15% efficacy). “Learn to code” is no longer relevant in an AI-driven world.
Yang’s Proposals:
- Universal Basic Income (Freedom Dividend):
  - UBI as a backbone policy to handle broad displacement (“just distribute the money as quickly as we can”).
  - Also open to negative income tax, child tax credits, and direct youth employment subsidies.
- Targeted Incentives:
  - Subsidies for companies hiring young workers.
  - Destigmatizing and investing in trades and vocational programs; “no robot plumbers for the foreseeable.”
- International Models:
  - Praising German apprentice culture; US needs more apprenticeships and less college degree fixation.

Notable Quote:
Andrew Yang (21:38):

“Trying to train workers who've been laid off in various jobs to compete against AI strikes me as a loser... It's chasing moving goalposts.”

Scott Galloway (24:02):

“I don't think it's fair to say that those efforts (retraining) have failed and to give up on it. My sense is...an apprentice culture and more vocational training could have real ROI.”

Discussion of Means-Testing vs. Universality:
- Galloway is wary of purely universal benefits ("I don't think anyone on this call should be getting [UBI]") and supports policies targeting the economically strained.

4. Historical Lessons: Did Previous Automation Waves Really Help Everyone?

(33:17 – 38:57)

Three Lessons:
- The “it all worked out” narrative of past automation is often glossed over; it fueled massive inequality and left many behind, especially in manufacturing and local journalism.
- Yang warns, “AI is to white collar work what the robot arms were to factory work.”
CEO Confidentials:
- Yang recounts breakfasts with CEOs who are cutting staff dramatically, watching revenues soar, and admitting that “capital displaces labor—with the help of AI.”

Andrew Yang (36:59):

“That’s pretty much where the K shape started...the wealth inequality thing started to get really out of control. The AI equivalent...story’s going to be the same thing, except times a thousand.”

5. Silicon Valley Wakes Up to Inequality—and Their Own Unpopularity

(38:57 – 41:59)

AI CEOs (Anthropic, OpenAI) Now Calling for Regulation & Taxes:
- Dario Amodei (Anthropic CEO) admitted half of entry-level white collar jobs may disappear in five years, and called to tax AI companies.
- OpenAI proposes a “New Deal” with capital gains tax hikes and redistribution policies.
- Yang is skeptical of the sincerity: “It’s very easy for them to say tax me, knowing full well it’s not going to happen.”

Scott Galloway (41:10):

“You’re talking about a group of people who would fuck their sister for a nickel. And we fall for this shit. Literally every couple years we have a new hero who says, regulate me in hushed tones and a t-shirt (Sam Altman) ... and then they deploy thousands of lawyers to get in the way of any regulation.”

6. What Policy Would Actually Work—And Pass?

(44:45 – 46:55)

Negative Income Tax as a Compromise:
- Means-tested safety net ideas (negative income tax, expanded child tax credit) may be more politically feasible than pure UBI.
- “If we wound up with a negative income tax, I would be pumped because that would alleviate poverty at scale.”
- Estimated cost: several hundred billion dollars, but offset by spending multiplier.
The Political Moment:
- Galloway predicts policies addressing the AI labor crisis will define politicians' careers going forward, with renewed interest in proposals Yang introduced back in 2018-20.

7. Society At a Tipping Point: Social Unrest & Elite Self-Interest

(47:48 – 50:33)

Growing Social Tension:
- Yang references recent high-profile violence and dangerous polarization; predicts social unrest will push elite support for redistribution out of “enlightened self interest.”
- Not all tech elites are sincere; “some are already headed to the bunker.”
Yang:

“We’re nearing that point...even if you don’t think these are tremendous human beings...Some kind of investment in the general public would not be a terrible move, if only just to make them look better.” (48:55)

Notable Quotes & Memorable Moments

AI’s Impact on White Collar Work:
- “AI is to knowledge work what the robots were to factory work.”
  — Andrew Yang (33:17)
Cynicism About Silicon Valley’s “Tax Us” Rhetoric:
- “We keep falling for this notion that some Jesus-like figure from the technology sector is going to tax himself. It’s never happened.”
  — Scott Galloway (41:10)
The Case for Negative Income Tax as Policy:
- “If you make less than [$35,000], then we true you up to that level...I’d be thrilled with anything that alleviates poverty.”
  — Andrew Yang (45:13)
On Tech Layoffs and Reinvestment:
- “Oracle is making a $50 billion bet on AI and it needed the money...if we cut these workers, we’re gonna save $8 billion and plow that into data centers.”
  — Andrew Yang (16:25)

Important Timestamps

| Topic | Timestamp | |-------------------------------------- |------------ | | Show start & setup | 01:50 | | Framing AI’s labor threat | 05:08–07:58 | | Yang explains his early warnings | 06:55 | | “AI washing” vs. real job losses | 09:41–11:52 | | Debate on real vs. perceived crisis | 12:39–19:23 | | Policy solutions (UBI, negative income tax, retraining debates) | 20:44–27:07 | | Data on college grads impacted | 31:10–34:52 | | Inequality origins: manufacturing & information revolutions | 35:25–38:57 | | Tech CEOs calling for tax/regulation | 38:57–41:59 | | Means-tested vs. universal solutions | 44:45–46:55 | | Social unrest & elite self-preservation | 47:48–50:33 | | Real talk: Are Silicon Valley elites sincere? | 50:33–51:47 | | Closing reflections & policy outlook | 53:47–64:21 |

Personal & Social Reflections

Parenting in the AI Era:
- Yang shares his own challenges: his 13-year-old son tells him it would be easier to have an AI girlfriend; the family struggles with screen time and the psychological effects of digital life.
- “If you show me a household where the kids aren’t on screens, they have a much, much better shot at flourishing.” (60:07)
Yang’s Current Initiatives:
- Promoting his new company, Noble Mobile (incentivizes less screen time); supporting independent, reform-minded Senate candidates.
Legacy & Influence:
- Both Galloway and Elson credit Yang for mainstreaming the idea of direct economic support and believe his moment for national policy influence has arrived.

Concluding Thoughts

This episode pits optimism against warning as AI’s effect on the labor market shifts from theory to reality. Andrew Yang’s dire predictions are playing out—especially for young, college-educated workers—while the political establishment and the tech elite struggle to keep up with a crisis that’s no longer hypothetical. The roundtable acknowledges that sweeping solutions like UBI may not be politically feasible yet but sees strong momentum for targeted policies. In the end, the episode calls for policymakers to move fast with creative, large-scale solutions—or risk deeper division, unrest, and long-term socio-economic harm.

Listen if you want:

A BS-free debate on whether AI is truly destroying jobs—right now.
Honest discussion about who is getting hurt, who stands to benefit, and what needs to change.
Policy ideas from the man who brought guaranteed income to the mainstream.
The inside scoop on how Silicon Valley’s attitudes are shifting as their own popularity nosedives.

“The question is not if AI will cause labor market dislocation, but how we choose to respond—and who we choose to protect.”

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Transcript

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A (0:57)

Learn more@betterment.com TLH terms Adobe Acrobat, your team's home base. Collaborate within a shared PDF space. You've got your docs, your plans, your specs and then invite the crew to build what's next? They talk off the teamwork. Here's an updated render. They think that this design could be a contender. And when somebody wonders what's the next steps? AI helps you finish the rest. Bolts are tight. Now your plan's refined. Run a smoother business when you're on the line. Do that with Acrobat. Learn more@adobe.com Dothatwith Acrobat.

D (1:30)

Today's number 100. That's the age of the world's oldest animal, a tortoise named Jonathan. True story. I worked at a zoo for several years where my job was circumcising elephants. The pay wasn't very good, but the tips were huge.

C (1:50)

Listen to me.

E (1:51)

Markets are bigger than us.

C (1:52)

What you have here is a structural

E (1:53)

change in the wealth distribution.

B (14:09)

Well, there are a couple of data points I would home in on. Number one is that the labor force participation rate keeps on dropping where you've had at least a couple hundred thousand Americans raise their hands and say I'm not even going to look anymore. And so the unemployment rate misses that Group placement rates have collapsed for particular populations, particularly computer science grads coming out of various units, universities where you had programs that had placement rates of 94% at high salaries and those have flipped. Now you have computer science grads. By the way, I ran into a computer science grad out of ucla, Scott, which is an awesome institution and he was not able to find a job and was doing odd jobs and Uber to make ends meet, which would have been unthinkable. I mean that's a great program. Very, very bright kid. And he was looking for six months and was probably getting AI fueled responses. I mean like at this point applying for a job often can be like bot to bot sort of thing. So you're seeing a couple of populations that are getting very, very adversely impacted. And what CEOs say to me, as they say to you, I'm sure is the easiest people to fire are the people you haven't hired yet. So when you talk about this slow to hire, slow to fire, there's like a ladder being pulled up. I suppose for a lot of entry level workers that would have shown up. I think I saw one stat about the number of recent college graduates that are getting hired into various tech companies where it used to be double digits and now it's dropped to single digits. So there's. To me, that population is the canary in the coal mine. And if you play out what happens to that population over time, unfortunately, their school loans don't get forgiven, they get sent home. I met some of these kids. I'm sure some of them reach out to you all the time. And the question is, what happens for that generation? Meanwhile, you have the middle managers who are all freaking out and stressed and you can argue, look, some of them are getting laid off because of various excesses. But the 30,000 Oracle workers that Edge talked about got laid off. Maybe they didn't get replaced by AI, but Oracle is making a $50 billion bet on AI and it needed the money. Like it looked up and said, you know what, if we cut these workers, we're going to save $8 billion and we're just going to plow that into data centers. The amount of money that we're spending on building data centers just surpassed the amount of money we're spending on office buildings for the first time. So you can see very literally that the compute infrastructure is the new human being.

B (21:38)

Yeah, yeah, yeah. Really stupid. And I think that the retraining aspect is chasing moving goalposts. And my joke is that I'm now past 50, so if I don't get dumber or slower in a given month, it's a good month. Whereas AI is going to double in power and efficacy in that month. So trying to train workers who've been laid off in various jobs to compete against AI strikes me as a loser. It strikes me as like the next generation learned to code or we're going to retrain the laid off manufacturing workers. So that's not great news, obviously. One thing I think you could argue for that most people would accept is some kind of subsidy or incentive to hire a young person out of school where you could have entry level workers, you get a tax break or some kind of match in credit or incentive to take on a young person. And the great thing there is that after the young person's in your organization, then they can become awesome and contribute. And you might not have hired them initially, but maybe the government can assist you on that level. That to me is a sensible policy and I've actually advised various policymakers on that they haven't done anything with it. One of the reasons why I was so pro universal basic income and still am is that it will catch the, it will fill in the gaps. Like we're bad at retraining, we're going to be bad at targeted policy. Political figures are great at talking about it and not doing it. Like no one will actually see what happened to the displaced workers. So if you were to take an AI dividend and at this point there are a lot of folks in AI who are arguing for a version of this and just start distributing it to workers of any age and stage, it would 100% facilitate with successful transitions, with, with people being able to switch fields or switch jobs or switch regions or whatever it takes. And so I'm still Mr. Let's distribute the money as quickly as we can. Especially now that AI has minted or is in the process of minting several trillion dollar companies and there hasn't been meaningful tax on any of it.

C (31:10)

We're back with Prof. G Markets. We're having these policy discussions and it seems that I still feel as though in order to figure out what the correct policy is, we need to be in agreement, or at least some semblance of agreement on diagnosing what the problem is. And so I just go back to whether AI is indeed having a significant impact on the labor market. And I think one thing that I just want to point out and see if Andrew, maybe you have thoughts on is the fact that what we're really talking about here is the college graduate employment situation where college grads. The unemployment rate for recent college grads is historically very, very high. And perhaps even more interestingly, the unemployment rate for college grads is now higher than for non college grads. And that never used to be the case. And I feel like that is relevant because, I mean, we say the young people are the canary in the coal mine when it comes to AI. I feel like the more relevant thing to say is that young college grads are the canary in the coal mine because that's the area of work where AI can actually have an impact. It's not really having an impact in terms of blue collar jobs yet, but it is having a level of impact in the white collar workforce. We are seeing that in the college grad unemployment data. And then when we look at actual tech companies, whether or not it's AI washing, we are seeing data that suggests that jobs are being lost in that realm. And so I guess I just, I mean, it seems as though, yes, we haven't had a clear picture of data that tells us that yes, AI has come in and completely transformed the labor market, but it seems like to the extent that AI is quite a nascent technology, it's doing all the things that you would expect if it were to do that in the future. And so I'm sort of waiting for someone to show me data that like, no, AI isn't doing all of the things that Andrew Yang had predicted it would do in over the long term. Point being, we're not in the long term yet. I just want to see if you have thoughts on that.

D (42:34)

So I know a lot of these guys reach out to you in addition to. And there's like 80% overlap with what you're. You did normalize the notion. And I think this is. I think you had more impact than people acknowledge or are aware of because people just got used to the idea. You normalize the idea of, well, why wouldn't you just give people money? Why wouldn't you just lift people up and that would be good for the economy? The multiplier effect, reduce anxiety in the country. That happiness, unfortunately, in this nation is directly correlated to economic sustainability. Before it was like, oh no, that's not American. And people are coming to grips with that. And I think you had a lot of, I don't know, I think a lot of that was driven by you. So quite frankly, I just don't think UBI is politically tenable. But what might be politically tenable is universal safety net that everyone has certain rights to healthcare, access to childcare. You know, I just don't think Ed Elson should be getting income. I don't think anyone on this call should be getting. And it's the universal part that bothered me about your branding that basic income works for me. If you were advising the next presidential candidate on a specific policy to try and level up, I wouldn't even say young people. I think it should just be people who are economically strained, because I think that's what you were trying to do, is to make a healthier, happier, more prosperous nation, the kind of nation that. Where the values should reflect our prosperity. I'm not trying to put words in your mouth, but I know you fairly well and I think you would agree with that if you were advising anyone. You may BE of these 40 Democrats who claim they're not running for president but will come on our podcast if I text them within five seconds. What would you suggest in terms of an economic policy that likely could pass, that the American public would embrace? Because my sense of ubiquitous is it conceptually it works, but I just don't think practically it's feasible. So just for a moment, if you had to calibrate UBI and advise a Democratic presidential campaign on what type of policies you would propose, what would those look like?

B (54:09)

I'm here to do as much good as I can. So first I want to put a plug in for the backdrop. Some of you can see it, but I'm the head of a company called Noble Mobile that's trying to save people money right now on your wireless bills. And then we give you up to $20 back at the end of every month based upon any data you don't use. So it's even an incentive to doom scroll less to maybe try and get a date where you're not on your phone the whole time. So that's a joy. And the reason we started Noble Mobile was that there are a lot of folks who, like me and Scott, who actually wanted their financial lives to be better now, today, and not based upon my being in office or being able to implement UBI or a lot of these things. So that's one thing I'm doing. Now, to Scott's question, in the bigger sense, I'm trying to help various good people get into office in November with a little bit of a different bent than a lot of other folks who do this work. So this morning I was on a call with a guy I'm supporting named Seth Bodnar, who's running for U.S. senate in Montana. And the reason why it's unusual is that he's running as an independent. He's a former Special Operations commander in the U.S. airborne. He graduated first in his class from West Point, so he's a stud. He was the president of the University of Montana until a couple months ago where he said, screw it, I'm going to run for U.S. senate. And in Montana, a Democrat would not be able to win, but as a military veteran who's running as an independent, by the way, Seth Bodnar, first month he raised more money than every other candidate combined, including the Republican, and he's been endorsed by John Tester. So if you can get someone like Seth Bodnar into the US Senate, all Senate votes count the same. You know, like you could have like a sane, public spirited, patriotic senator out of a traditionally red state in Montana. And so that's the kind of candidate I'm boosting and trying to help. Help in the goal of rationalizing our politics come January of next year.