The following is a rushed transcript and may contain errors. It will be updated.

Taya Graham:

Hello, my name is Taya Graham and welcome to the Inequality Watch Report, a show that examines government policy and action through the lens of extreme economic inequality, the existential issue of our time. Today, we’re going to discuss a technology which we’ve been told will transform our lives, an invention that has been touted as the ultimate arbiter of our collective futures, whether we like it or not. Of course, I’m talking about artificial intelligence, but with the promise also comes doubt and questions and most of all, a lack of clarity on how we’ll impact the working people of this country. AI leaders have casually warned us that their products could eliminate 40 to 50% of white collar jobs more than the losses in the Great Depression. They’ve promised that technology will be so disruptive that even staunch capitalists have discussed providing a UBI or universal basic income for Americans who will be left out.

They’ve borrowed money at such predigious rates to fund data centers that even Wall Street is beginning to just say no. And now some of the biggest names are saying it’s not working out as planned and an America’s already historic wealth imbalance and government hamstrung by the self-interested impulses of a single man. And you have a situation that could brew a toxic stew of making the already rich even richer and leaving the rest of us even further behind amid all the societal chaos and upheaval. And are the cracks just starting to show? Just this week, one of technology’s greatest apostles made accusations that AI has become a nemesis for his business and others. And capitalists who have gladly loaned billions to build data centers throughout the country are now starting to push back at the ever increasing demand for cash. Of course, the point of this show is to examine this topic through the lens of inequality and how it affects our political and social institutions and what it means for working people.

And to do so, we are about to be joined by an economist who has been thinking and writing about this very topic with insight and clarity, Dean Baker. But first, I want to check in with my co-host, Stephen.

Stephen Janis:

Oh, hey Taya, how you doing?

Taya Graham:

Steve and Janice, it’s great to have you. Thank

Stephen Janis:

You for having me on.

Taya Graham:

Now first, can you give us a broad overview of how inequality and AI are teaming up?

Stephen Janis:

I think in a way, this is the greatest American kind of ripoff in the sense that they’ve spent about the past four or five years mining all our data, taking everything we posted online, and they’re regurgitating it back to us and want to charge us for it in some way. And so to me, I think what is most missing for me besides the promise of huge economic disruption is what the value proposition is for the American people. I mean, they took everything that we wrote and now they want to repackage it and sell it as some sort of deity that we have to worship. And so I’m a little worried, a little worried, a lot worried that we’re all going to be casualties of a great wealth concentrator, which remember, OpenAI was supposed to be a nonprofit. Now it’s a for-profit company. All these huge IPOs, I’m afraid they’re just taking everything we’ve created, sell it back to us and become even richer, and there’ll be a greater concentrate of wealth and power.

So it’s just a bit concerning to me.

Taya Graham:

Actually, Steven, when you mentioned it turning into a deity, we already have some issues with AI psychosis. Maybe we should discuss that on our next show. Yeah,

Stephen Janis:

We’re just going to be praying to the AI deity and offering 19.95 a month to it. So yeah.

Taya Graham:

Actually, that’s about right. And now I want to introduce our guest, Dean Baker. Dean Baker is the co-founder and senior economist at the Center for Economic and Policy Research. For decades, he’s written about inequality, labor markets, financial bubbles, corporate power, and economic policy. He’s also written extensively about AI and how it’ll affect everyday workers and even journalists just like us. He wrote the book Rigged: How Globalization and the Rules of the Modern Economy were structured to make the rich richer, and its newest project is the AI Bubble Monitor. Dean Baker, thank you so much for joining us.

Dean Baker:

Thanks a lot for having me on.

Taya Graham:

Well, we’re glad to have you. Yeah, absolutely. And I have the honor of doing the first question. And so my first question for you is this. Artificial intelligence has been described as the biggest technological revolution since the internet, and yet you’ve argued that the economic data simply doesn’t support a lot of the claims being made. What are people missing here?

Dean Baker:

Yeah, so I think to a very large extent, we have people who are really good at hype. People like Sam Altman, of course, Elon Musk, absolute master of hype. These are the Donald Trumps of the business world. They’re selling this stuff and they’ve been very successful. I mean, Elon Musk just had his SpaceX initial public offering, which is primarily AI. I mean, that’s their own assessment. I’m not trying to attribute things to them. If you read their registration statement, they say 90% of their expected market is in AI. So SpaceX is an AI company. So they’re looking to get rich by this. And I don’t mean necessarily because they’re going to have huge profits. They have huge stock prices. So Elon Musk became a trillionaire, not because SpaceX has enormous profits. It actually loses money hand over fist. He became a trillionaire because the stock price is ridiculously high.

So step one, is it creating inequality? Absolutely. By a stock bubble, bloated bubble. Now, in terms of what it delivers, they’re saying this, is it going to have massive impact? I’m sure it will. And the model I look to is the internet. Had massive impact. Does that mean that it’s going to lead to mass unemployment? Well, a lot of people lost their jobs to the internet. I mean, Amazon put a lot of small sellers out of retailers out of business.

Taya Graham:

Absolutely.

Dean Baker:

But you still have a lot of retailers there and everyone didn’t lose their job. I think think of AI the similar way. It will change the economy in a lot of different ways, but that doesn’t mean everyone’s going to lose their job. And if we look at the data, we look at productivity, which is what that means. If people are losing jobs, that means we’re producing more in an hour of output. They’ve actually been very weak the last three quarters. Now it’s erratic. So I’ve followed the data for a long time. So I know you could have real weak quarter and next quarter could be really weak. And then we’ll come around the second half of 226 and who knows, be 5%. Very rapid productivity growth. Could happen. But the point is we’re not seeing it. And there have been a number of economists I’ve tried to look through this very carefully and look at sector by sector, look at retail, look at healthcare, look at the different sectors of the economy.

And invariably, they find relatively modest impact of the studies I’ve seen. And I’m sure we missed some, but these are credible studies. The highest number was a half percent a year increase, half a percentage point a year increase in annual productivity growth, which matters. I mean, that’s noticeable, but that’s not massive unemployment. And one of the leading economists in the world, Darin Asamiglu, Nobel Prize winner, he had it at just seven hundredths of 1%.

Taya Graham:

Wow.

Dean Baker:

These people could all be wrong, but they’ve tried to be very careful in it and they find very modest impacts. I shouldn’t say very modest. I mean, again, a half percentage point a year. If you had that, that would be a big deal. But the internet, when we had the internet in the ’90s, the internet boom is about one and a half percentage points a year. So we’ve seen this.

Stephen Janis:

Wow. Dean, that’s kind of. But these people are hyping valuations. They’re borrowing billions and billions of dollars, I think, based on a higher rate of return. I mean, is this like a house of cards? I mean, they’re hyping this over and over again saying it’s going to be transformative. But now you’re saying the impact so far has not been. Does that put at risk all these billions of dollars they’ve thrown at this problem?

Dean Baker:

Absolutely. And this is why I’m calling it a bubble. I’m old enough, I’ve been through two really big economy moving bubbles. In the ’90s, we had the tech bubble. And I was out there saying, “This is bad news. It’s going to burst. It’s going to burst.” And it did. It burst in 2001. The S&P 500 big stock index fell 50% from peak to trough. The NASDAQ where you had most of the tech stocks, that fell 80%. And it had a huge impact on the economy. I mean, for stock investors, I go, “You should know what you’re doing. Many don’t, but you should know what you’re doing. So I can’t cry too much.” But it had a big impact on the economy. We lost jobs into the 2000 recession. We didn’t get them back till 2005. That was the longest period with our positive job growth since the Great Depression.

We had a longer one after the Great Recession. But that was a big recession from the standpoint of the labor market. Also, real wage growth just stopped. We’d been seeing good real wage growth in the late ’90s, just stopped almost instantly. So that was a really bad story. And then we had the housing bubble. Again, same story. And that town in turn was more severe. We had close to 10 million people lose their home to foreclosure. The unemployment rate peaked at near 10% in 2009.

So bubbles can have very bad consequences. So that’s why I’m very worried about this one. They’re selling this and Elon Musk undoubtedly is stuffing his pockets. And Sam Altman and the others, they’re stuffing their pockets. But no, I don’t see that these stock prices make sense. And when does the music stop? I don’t know. Both those bubbles went way longer than I expected them to. But all I could say is the sooner it bursts, the better it will be for the country.

Taya Graham:

It was really interesting that you compared the AI investment boom to the dot-com bubble. Maybe you could just go into a little bit more depth about some of the similarities that really concern you. Yeah.

Dean Baker:

Well, there are two things there. One, from the standpoint of the firms, that you started to see companies that were just pushing nonsense in essence. I’m going back to the dot-com. So it became almost a joke. And I shouldn’t say almost a joke. It was a joke. And this was in the business press. So the Wall Street Journal used to highlight the most ridiculous initial public offerings. So people were coming up with crazy public offerings and they could still raise hundreds of millions, even billions of dollars in their first issue. There was one company even that took the cake. I wish I could remember the name. They said, “We don’t know how we can make a profit.” So you work from the assumption, okay, they’re not profitable today, but they have this great plan, software, whatever it is. And two years, three years, four years, they’re going to be a next Microsoft.

That’s what people were betting on. And of course they weren’t. But you had one literally said, “We don’t even know how we’ll make a profit.” So you had a huge amount of misdirected capital. And that was, of course, a huge voice for the economy. But the standpoint of the stock market, again, I was saying we want stock investors or we think they should be knowledgeable. They aren’t. And people were spending based on their stock wealth. So you had a lot of people that were saying, “Oh, I had money in the NASDAQ and just doubled,” which it might well have. A lot of people owned stocks in the NASDAQ and over two years they would’ve doubled. So they said, “Oh, I’m going to buy a new car, get a bigger house, go on a big vacation.” Well, when those prices plummeted, that consumption stopped. So it was a very, very big hit to the economy.

And I worry very. I should add one more thing on the craziness that companies discovered that if they added dot-com to their name, their stock price would go up five or 10%. We’re seeing that today. If you add AI to your name, and someone did that, I’m trying to remember what it was. I think it was- Was it like

Stephen Janis:

Diapers.com? I think, wasn’t there like diapers.com or something or something?

Dean Baker:

Yeah. And their stock price went up five or 10%, which tells you. I mean, it’s utterly nuts. You’re the same company. It doesn’t matter whether you call yourself. Com AI or anything. You’re the same company. It shouldn’t make any sense.

Stephen Janis:

Well, now speaking of a bubble, Palantir CEO, Alex Carp, had kind of a meltdown on CNBC. Let me play a little bit of it so you can watch it. And maybe you can explain what he saw. It sounded to me like he was panicking, but it was hard to figure out what he was talking about. David, if you could play that clip and we’ll just watch it and we come back, we’ll talk about it.

Alex Carp:

Everyone who uses LLMs on the battlefield runs on top of our ontology. And our clients are just, to say they’re unhappy with the Frontier Labs is to say I’m welcome at the Berkeley faculty. It’s like there’s just a level of discomfort and loss of trust that also made it really, really –

Stephen Janis:

Okay. Unpack that. What do you mean by that?

Alex Carp:

Well, you have, okay, so when you’re using large language models, at this point, everyone technical realizes they’re like a critical resource. To make them valuable in an enterprise like battlefield context or regulated context or manufacturing, you have to have what’s called an application layer. We have this thing called ontology that now everyone’s copying, but defacto, it takes a large language model. It makes it safe and useful and precise. So safe because it doesn’t touch your unlearning data, safe because it prevents the large language model from caching your data and replicating your business. Safe because it doesn’t transfer your IP of how to fight secret data, top secret data or in a clinical context. So the general way these things were sold, and again, these people are. Sam and Dario, there’s nothing more fun than debating Dario in private. So I’m not throwing shade at them,

Taya Graham:

But

Alex Carp:

Something has gone completely wrong. And the basic view among enterprises in this country is I’m going to chill lax and waste my time with tokens. I’m going to get no value and they’re going to get my IP.

Stephen Janis:

Okay, Dean, like I said, I haven’t heard the word ontology since my religious studies class in undergraduate, but it sounds to me like there’s buyers remorse or panicking among the top people, including Mr. Carp. What’s your take on what he’s saying? Does he sound like he’s panicking?

Dean Baker:

He sounds panicking. And just to be clear, I don’t know Alex Carp, never met him. But as best I could tell, he’s an odd guy. But as best I can tell, his complaints are first and foremost that you have companies spending a lot of money on AI and you had a lot of companies that were spending literally hundreds of millions a month. And they weren’t getting anything obvious for that. So they were actually encouraging their staff, their mid-level staff. So I was mentioning, I was talking about Amazon, where they literally had a leaderboard where people were posting how much AI they were using. And I don’t know if they got a bonus or whatever it was exactly, but the more AI, the better off you were. And just like to me, Amazon’s obviously a big business in any ways very successful, at least from their vantage point of profits.

Why would you ever encourage people to use AI for the sake of using AI? And the analogy I’ve

Taya Graham:

Made is

Dean Baker:

It’s like using paper. Oh, I used five reams of paper today. And you go, okay, great. What’d you do? I mean, that’s kind of nuts, but that’s what they were literally doing. So you’ve had companies looking to cut back hugely on the AI they use because they want to see that they’re actually getting something for it. And in many cases, their conclusion was that they weren’t. The other part of the story that he’s raising, Carp is raising, is they’re worried. They don’t know what’s happening with their data. So when you’re running your programs through Anthropic, through OpenAI and whoever else, they have your data. So using the example of Amazon, that data’s worth a huge amount. We know, we complain about that. Amazon, they know everything we’ve purchased, what we’ve looked at. They have an enormous amount of data on us. That’s a lot of money to them.

They don’t want to give that away for nothing to Anthropic, to OpenAI, whoever. And they don’t know whether they are or they aren’t. So that’s what he was talking about. He’s saying you need software that regulates the usage. And as it is, a lot of companies don’t have that. Again, I’m not going to advertise for your software. I have no idea what it does, but you probably don’t want to give these AI companies all your data.

Taya Graham:

Actually, Steven and I go and cover Capitol Hill, and we saw Senator Bernie Sanders arguing that if AI creates extraordinary wealth, then the public deserves a share of that wealth. And he announced an AI sovereign wealth fund proposal. And I think he’s talking about a 50% stake for Americans. Now at first glance, this sounds like a progressive idea, but I read your article. Why do you disagree?

Dean Baker:

Yeah, I’m a big Bernie Sanders fan, known him for years. I have enormous respect for him, but I really think this goes down the wrong path. To start with, just from the word go, if you’re giving the US government a large stake in the AI companies, you’re giving Donald Trump a large stake in AI companies. I know that’s not Bernie’s intention, but look at what the Supreme Court has been saying. I’ll guarantee you, this isn’t even a debatable point given the recent Supreme Court rulings. If we get the ability through an ownership stake to put people in top positions in Anthropic and OpenAI, whoever else we might buy a stake in or take a stake in, Donald Trump is going to pick those people. It doesn’t matter how they wrote in the law. That’s what the Supreme Court has said. The unitary executive, he decides, I can’t imagine in the current environment wanting to give more power to Donald Trump.

In general, I’m not sure I want the government to have a 50% stake, but certainly not Donald Trump. So that to my mind’s a no-brainer. Secondly, from the standpoint of regulation, we know there’s all sorts of ways we need to regulate AI. It’s not an option. They want to build data centers everywhere. Do you want a data center in your backyard? Should we be able to tear down Grand Canyon to put a data? That’s their dream. That’s what they want to do. We already are having massive battles on this. I don’t trust that with the government having a direct stake that we would get the right outcomes. I don’t trust we’d get the right outcomes anyhow. But I think we really tilt the playing field and just the environmental issues, that’s just one of them. When you’re talking about ownership of data, access to privacy, there’s a whole range of issues that come up with AI that are unavoidable.

I mean, it’s not a question, oh, we should leave it to the market. There is no market. We’re setting the rules. So I worry very much about that. The third point is just what I was saying before. A huge amount of this is hype. And unfortunately, I think Bernie’s feeding the hype. Oh, they’re going to have massive wealth. I don’t see that. I think there’ll be big profitable companies here, just like going back to the ’90s. You look at the providers of internet, Cisco and Verizon and Comcast, they’re big companies. They’re profitable. They aren’t earth shaking. They aren’t the biggest companies in the world. So why are we contributing to the hype? I don’t think that’s a productive thing to do.

Stephen Janis:

Yeah. Yeah, go ahead, Ed. No, go ahead.

Taya Graham:

I was going to say, when I was reading your article on your substack, Dean Baker, that your first objection wasn’t really economic, that was more political. And I was just wondering why you think having a government-owned AI investment fund would be particularly dangerous under the Trump administration? Or could you just not trust any administration with it?

Dean Baker:

I’d have problems with any administration, but let’s just focus on Donald Trump. Donald Trump has made it clear. He sees the government as his tool to enrich himself, to enrich his friends. So he will put his friends in top positions there. He will have his friends, people contribute to his campaign or give him kickbacks. They will be the ones that get contracts from these companies. He’s anti – DEI. Well, women in top positions, forget it. Blacks in top positions, forget it. He’s applied that through government as much as he could. You’re just giving them a whole new area to apply this in. And again, if AI, I don’t think it’ll be the massive thing, at least these companies will be the massive things that they’re hyping. But again, I don’t want to give Donald Trump yet more power.

Stephen Janis:

Wow. Well, listen, to your idea of Bubble Watch, which I think is kind of fascinating, well, also terrifying. So for example, in the private credit markets, people started to panic and private credit is lending a lot of money for these data centers. Last week, IBM lost 20.% of its value in one day because people were panicking about software. Where do you see this starting to unravel? I mean, we’re not economists, but we’re people that read. What should we be looking at? What should anyone be looking at actually to see where this bubble’s going to start to unravel if indeed it does?

Dean Baker:

Okay. Well, let me be as honest I can be on this. I didn’t know until this date, I can’t tell you what caused the collapse of the stock bubble or for that matter, the housing bubble. I mean, I could all point to all sorts of vulnerabilities, but when they collapsed and why? Both went on much longer than I ever thought they would. I’ll say that. So I’m saying that now what I have been looking to and will continue to look to is increasingly the companies, and these are big companies, these are Meta, Alphabet, the biggest companies in the world. They’re having to borrow. So even though they’re very profitable, they’re undertaking such massive investments that they’re having to borrow. And you’re seeing a very interesting story here that investors in bonds are starting to get worried. We actually saw this with SpaceX. It was really striking.

One of my AI bubble monitors was about this, that SpaceX bonds are being sold at a discount, meaning that bond buyers see a risk that it actually could default, that they might actually go bankrupt. So here on the one hand, you have stock investors going, “Oh, SpaceX is going to be the most profitable company in the history of the world.” You have bond investors going, “It might go bankrupt. It might not be able to pay its bills.” So I would look at the bond market and it seems to be. I recently saw some data showing that there’s much less interest in Alphabet, Meta, the hyperscalers are called, that are involved in building the data centers for AI. There’s much less interest in their bonds than for other investment grade debt. And that’s who I’d look to first, because if it ends up being the case that you can’t get the bond issues to finance it, then it’s going to fall apart.

We may be seeing the beginnings of that. I mean, it’s a little early, but we may be seeing the beginnings of that. So if they start to cut back their lending, this thing could collapse fairly quickly.

Taya Graham:

If we can, I just would like to pivot for a moment to affordability. I’m pretty sure I’m not the only one out there seeing their gas, their car insurance, their groceries going through the roof. There are so many Americans that are struggling with housing costs and healthcare costs and groceries and childcare and utility bills. And I was just wondering how much of today’s affordability crisis has to do with AI, will be impacted by AI, and how much stems from our much broader economic policy?

Dean Baker:

I would say most of it is broader economic problems, but I will say one that I can pin on AI, and that’s a housing market, particularly in areas like the Bay Area. So you actually saw this when you had the SpaceX, their initial public offering, you suddenly had all these people that were doing well, obviously, were highly paid engineers in positions at SpaceX, but they’re maybe getting hundreds of thousands a year. Maybe some are getting low millions. They suddenly have 10, 20, 30 million because there’s SpaceX stock, and that’s what the evaluation would be. They suddenly turn around and go, “Oh, I want a really big house.” Well, there’s only so many really big, really nice houses in the Bay Area. So those go through the roof. And there is a trickle down here. Trickle down not in a good way. So if you’re a lawyer, you’re doing well, you make three or 400,000 a year.

Well, suddenly the home that you were looking to buy, which would’ve been a million you might have been able to afford, now it’s two or three or four million. So you look at a middle-class house and you’re suddenly prepared to pay one and a half million for that. So then the person who’s a teacher or a firefighter that maybe, maybe, maybe could have scraped together enough to buy that for five or 600,000,

No way on earth they could pay one and a half million for that. So there is a direct impact on housing, not necessarily nationwide. I don’t know how much it affects things in Ames, Iowa, but certainly in tech centers like in the Bay Area, like Seattle, other places where there are likely a lot of people involved in the AI economy.

Stephen Janis:

Dean, when the Great Recession hit, even though it was caused by bankers’ greed, a lot of it really the working class suffered. Do you think AI could have the same impact if it does start to collapse, that it will hurt working people and that the bankers will catch a cold and will catch the flu or whatever? Do you see it trickling down again to people who had nothing to do with this, what I would call a mess at this point?

Dean Baker:

Yeah, because that’s the problem with bubbles when they start driving the economy, because our economy does not turn well. So what happened in the ’90s, we were being driven by the tech bubble. Tech bubble collapses. Nothing else to come in its place. In fact, what came in its place, it took a couple years to do it, a few years to do it, the housing bubble. And then that collapsed and well, that took a long time to recover from it. We really didn’t get back to a strong labor market, lower levels unemployment till 2016, 2017. So what I worry is that the AI bubble’s definitely driving the economy, both through investment in AI stuff, AI related stuff, and then also the consumption effect that people go, “Oh wow, I now have five million in the stock market,” which some of these people do. And then they go out and spend a lot of money, housing being one thing, they get cars.

So those stocks go through the floor. Suddenly nothing’s driving the economy and we start to see the unemployment rate rise. Wages don’t keep pace with prices. It’s a bad picture.

Taya Graham:

I actually just went to a doctor’s appointment to go to radiology, just getting exams, and they said to me, “Oh, would you like to get the AI version of this and pay an extra $40?” And I said, “Well, how’s it different than my normal exam?” And they said, “Well, actually, technology is pretty much the same.” So I’m wondering how much are they overselling how beneficial this technology actually is and how much of it is just pure hype?

Dean Baker:

They’re hugely overselling it. Again, I’m not down on the ground in all these businesses, but you hear accounts of this. So you have a lot of companies where software coding, where it’s probably at the biggest impact, where they do AI and it’s often very useful, but the problem is it makes mistakes. So you still need someone who really knows the coding to check it. And I think that’s a good story really everywhere. You could use the AI, it could be very helpful, but you still have to check it. I know my own usage, which is very limited. I had it do a reference section for me. I was writing a paper and I was going, I can type up. I’m sure there’s software that could do it too, but I was going, okay, if I type it up, it’s going to take me two or three hours and I’ll make mistakes because I’m a sloppy typist.

So I’ll have AI do it and did it for me in, I don’t know, 20 seconds or something. I still had to review it because it had some references that were improper, but it was certainly much, much faster than if I had to type it myself. So I think there’s going to be a learning process. We will be able to use AI, use it beneficially, and there will be a productivity gain, but nothing like what they’re telling us.

Stephen Janis:

Dean, why do, in your estimation, we’ve heard all the incredible stories about tax incentives for data centers. If these companies are going to be so profitable and so amazing and going to create all this value, why do they need whopping tax incentives to build out these data centers? I just don’t get it. I don’t understand. And I’m not asking you to explain for them, but what do you think is the operative motive here of having all these tax breaks?

Dean Baker:

Well, there’s a crude joke with the punchline I could use because they can.

But there is a logic that from the standpoint of a state or county, they’re saying, look, we have people lined up that want our data center and we’re taking bids from all of them. So you have to beat the others. And from the standpoint of the county or state, they’re going, “Well, this will create some number of jobs.” They lie about the number. And it’ll create some amount of tax revenue. And they might go, “Well, we’re better off even giving them an incentive. Give them 50 million off on their taxes.” And you can’t say that’s necessarily wrong because in some cases it probably is right. In many cases it will be wrong. And certainly if they end up going under, it almost certainly will be wrong because having a big data center sitting there that does nothing is not going to make your county or state more attractive for people to live in or for other businesses to come and invest in.

Taya Graham:

We’ve talked about a wealth fund and even a UBI. What do policymakers need to do to protect workers and make sure that if this actually really makes generational wealth, that working people can benefit? Or maybe I should just say, if you have a magic wand and you could design your own AI policy, what would you want it to look like? Or what do you want policymakers to do?

Dean Baker:

Well, I’d go into the old bag of tricks and just start using them and ramping them up. So one of the things we used to do shorten the work week. We haven’t done that. We had the Fair Labor Cancan Act 1937. It’s almost a hundred years now. We’re getting close. So we thought 40 hours was right then. How about making it 36, 32? That would be a great thing to do. Raising minimum wage, make it easier for workers to organize. We have it so stacked against workers organizing unions now it’s become near impossible because employers could. It’s illegal to fire people, but what’s the sanction? What’s the punishment? So someone’s organizing a union. Elon Musk says you’re out the door. You could file a National Labor Relations Board complaint. Good luck. Maybe they’ll rule for you two years later, you’ll get your job back.

Kind of moot at that point. So we have a basket of things. Also, again, finishing the welfare state. Every other country in the world has universal healthcare. We should have universal Medicare. So those are some good steps. Again, I’m not opposed to UBI, but I just think back to under President Biden, he wanted to have the expanded child tax card. He put it in as a pandemic measure. He wanted to extend it and he couldn’t get that. He had Democrats opposing him. So the idea, this is children. We’re talking about a relatively small sum of money for children. He couldn’t get that through. So can we get a UBI through? Yeah, maybe, but that looks like a real uphill battle for me. I’d rather stick to the old favorites that we know work. And there’s a Well, lot of political support for them.

Taya Graham:

Okay, Steven. Well, obviously I’m in the wrong line of work because it turns out that you can lose millions or even billions of dollars and somehow make money. Is this dystopian enough for you? I mean, what are your thoughts here? I’m obviously in the wrong line of work. Well,

Stephen Janis:

Like I was kind of alluding to before, I feel like we’re kind of participating in new theology. The value here is purely theocratic, that there’s some divine power that is being burked in a lab that we’re going to have to pay penance to, whether or not it makes our lives better or not, and whether it has any influence on anything we do. So I was really glad to hear Dean kind of cut through all that BS and give us sort of a pragmatic view of what’s actually going on. And one thing, I don’t want to refer to the Tower of Babel, but that was an awfully tall tower of cards. And when AI comes bursting down on all top of us, I think it’s going to be quite cataclysmic. So yeah, apocalyptic is probably in line there.

Taya Graham:

That’s a great point. I mean, everyone is so excited. They’re hoping for artificial general intelligence where they’re going to be curing cancer and saving the world. Which would be great. And all I just do is see people losing jobs.

Stephen Janis:

Yeah. I’m waiting for the cure for cancer. I

Taya Graham:

Would be so happy to see it. I would be so happy to have AI genuinely help people. Not just help students cheat on their home.

Stephen Janis:

Or not just create 100,000 songs on Spotify every day. I think it would be more useful for humanity. Just my opinion.

Taya Graham:

Steven, you know me, as always, whether it’s on our show, the Police Accountability Report or our coverage on Capitol Hill, my concern is the working people of this country. And just like with all the other tech upheavals, the elite who taught them, forget those who are going to be impacted by them. And this particular iteration could really be devastating. And that’s why we have to remain vigilant. If AI actually lives up to the hype, the concentrated power it would confer would be absolutely death to a democracy. I mean, that much wealth in so few hands is simply unsustainable. I mean, it will literally adulterate the process of governance with self-interest, and it’s going to warp accountability around the curvature of a technology that seems more and more singular in its appetite for resources. And I do mean a literal appetite for land and water. And that is why we’ll continue to report on it and have discussions with innovative thinkers like Dean Baker.

And that’s why we will continue to report to you from the nation’s capital, asking questions about how the government by and for the people will actually protect them from the ravages of AI Avaris. And that’s why independent journalists like Steven and I will continue to investigate and try to comprehend and share with you the truth because that’s all we have in the end, for better or worse. Thank you for joining us for our inequality watch report. And as always, we’re reporting for you.