Finding Meaning (and Money) in the AI Age

Summary

Podcast Summary: "Finding Meaning (and Money) in the AI Age"

Podcast: What's Your Problem?
Host: Jacob Goldstein
Guest: Betsy Stevenson (Labor Economist, University of Michigan)
Release Date: June 18, 2026

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Episode Overview

This episode of "What's Your Problem?" with Jacob Goldstein explores how artificial intelligence is reshaping our economic landscape, drawing parallels to earlier technological revolutions. Goldstein interviews Betsy Stevenson, a prominent labor economist, about the challenges and opportunities posed by AI, focusing on how we can ensure broad benefits, preserve human purpose, and craft effective policies in the AI-driven future. The conversation ranges from historical lessons to current impacts in education, and bold policy ideas for sharing AI’s wealth.

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Key Discussion Points and Insights

1. The Central Problem: Broadly Shared Benefits from AI

• Theme: How can society ensure AI’s productivity gains are widely and equitably shared?
• Quote: “How can we create a world where the benefits of AI are broadly shared, where lots of people benefit? Almost everybody benefits.” — Jacob Goldstein [03:09]

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2. Lessons from Economic History: Engels’ Pause

• Parallel to Industrial Revolution:
  • The Industrial Revolution initially improved productivity but not worker wages; instead, it increased inequality and even reduced life expectancy — a phenomenon called "Engels' Pause."
  • Quote: “Workers … got nothing. Real wages in England … stagnated. So they did not grow for the majority of workers. And actually life expectancy fell.” — Betsy Stevenson [05:13]
• Why It Matters Today:
  • AI threatens to repeat history, with productivity gains not automatically translating into widespread prosperity.
  • The incentives to replace expensive workers (now: American white-collar workers) with machines closely parallel the Industrial Revolution’s dynamics.
  • Quote: “Where are workers right now expensive?... It’s American white collar workers.” — Betsy Stevenson [07:12]

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3. Another Lesson: Home Labor Automation and the Search for Meaning

• The Home Automation Analogy:
  • Mid-20th-century labor-saving devices (washing machines, dishwashers) freed homemakers from drudgery, but first raised standards (“the house has to be cleaner…”), and then led to a loss of purpose for many women, identified by Betty Friedan as “the problem that has no name.”
  • Memorable Quote: “I didn’t fight to get women out from behind the Hoover just to get them on the board of Hoover.” — Germaine Greer, cited by Betsy Stevenson [12:18]
• AI’s Meaning Crisis:
  • The loss of meaning and identity risks recurring as AI automates intellectual and creative work.
  • Japanese concept of "ikigai" (purpose for living) becomes increasingly relevant as we navigate post-work identities.
  • Quote: “The problem that has no name. The housewife whose skills are devalued by automation. It’s not a money problem, it’s a meaning problem.” — Jacob Goldstein [13:07]

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4. AI’s Impact on Learning and Productive Struggle

• Modern Academic Dilemmas:
  • AI tools like ChatGPT enable cognitive offloading, undermining students’ engagement with “productive struggle” — the vital process of wrestling with difficult problems.
  • Quote: “The productive struggle is that it’s awful… But you would do it again because actually it’s probably meeting that ikigai.” — Betsy Stevenson [17:06]
  • Student feedback: “School’s not as fun as it used to be.” — Betsy Stevenson quoting a graduate student [19:08]
• Assessment Challenges:
  • Traditional essays are becoming obsolete as students use AI for assignments. Authentic engagement and unique perspectives are harder to foster and assess.
  • “We have a dozen beautifully crafted summaries from AI. We don’t have a discussion.” — Betsy Stevenson [24:06]

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5. Policy Solutions for an AI Economy

A. Tax Reform: Balancing Capital and Labor

• Current Problem:
  • Favorable tax treatment of capital versus labor encourages automation over employment.
  • Quote: “Right now we have a tax system that is rewarding what is currently happening, which is the labor share of income is going down, and the share of income...by capital is going up.” — Betsy Stevenson [29:31]
• Prescription:
  • Raise capital gains taxes, reduce labor (income) taxes to encourage employment and more equitable outcomes.
  • Discussion: Revenue-neutral reforms could blunt AI-driven inequality but have distributional tradeoffs.

B. The “Data Dividend” Proposal

• Rationale:
  • AI relies on the accumulated work and knowledge of society — the “commons.”
  • Tech giants shouldn’t profit alone from collective human contributions.
  • Quote: “When Sam Altman says, I envision a world where cognition is sold to you by the token, I’m like, wait, he’s envisioning a world in which he sucked up all of human cognition and now he’s going to sell it back to us? Well, I’d like him to pay us for it first.” — Betsy Stevenson [31:31]
• Policy Model:
  • Tax AI companies’ use of public data; redistribute as a universal “data dividend” (like Alaska’s oil fund).
  • Quote: “You belong. You’re part of this. We built this together and we all get to benefit.” — Betsy Stevenson [33:02]

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6. The Challenge of Meaning and Community

• Work as Social Anchor:
  • Decline in community engagement (as described by Robert Putnam in "Bowling Alone") has loaded too much meaning onto work.
  • Transitions must “pull” people toward new opportunities, not just “push” them out of old ones (e.g., failed transitions out of manufacturing for men).
  • Quote: “You have a ton of men who still are thinking, there are no jobs for me, because the only jobs being created are in health care and healthcare jobs are so feminized.” — Betsy Stevenson [37:29]
• Building New Sources of Meaning:
  • Policy could incentivize volunteering, support “third spaces” (like cafes, clubs), and require community engagement for benefits like the data dividend.
  • Quote: “Whether it’s your data dividend is a function of logging community service hours.” — Betsy Stevenson [38:47]

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7. Advice for the Next Generation

• Risk and Uncertainty:
  • Young people face more career uncertainty than prior generations.
  • Skills needed: adaptability, curiosity, and (uniquely human) creativity.
  • Quote: “Your creativity is unique to you. Everybody’s creativity is like a fingerprint. And I think that we will have a desire for bespoke human creativity even as AI starts to do things.” — Betsy Stevenson [42:33]
• Enduring Human Exchange:
  • Regardless of AI’s advance, human needs and social exchange create ongoing opportunities.
  • “As long as you learn how to be attentive to other people’s needs, you will find your space in this world.” — Betsy Stevenson [43:46]

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8. Lightning Round Highlights

• Sources of Meaning Beyond Work:
  • Betsy is “really into birds” and finds joy in nature, especially birdwatching in Australia. [47:17]
• Family Economics in Practice:
  • Betsy often volunteers to drive her teens, prioritizing parent-child connection over convenience—even as a former Lyft board member! [48:41]
• On Children and AI:
  • “They didn’t ask for it and they don’t really want it.” — Betsy Stevenson, on her kids’ attitudes toward AI [51:24]
• Favorite Personal Use of AI:
  • Vacation planning—finding optimal destinations within specific travel constraints. [52:49]

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Notable Quotes & Timestamps

• “Real wages … stagnated. So they did not grow for the majority of workers. And actually life expectancy fell.” — Betsy Stevenson [05:13]
• “I didn’t fight to get women out from behind the Hoover just to get them on the board of Hoover.” — Jermaine Greer, cited by Betsy Stevenson [12:18]
• “School’s not as fun as it used to be.” — Student quoted by Betsy Stevenson [19:08]
• “We have a dozen beautifully crafted summaries from AI. We don’t have a discussion.” — Betsy Stevenson [24:06]
• “Raise the capital gains tax, lower taxes on wages...” — Jacob Goldstein [30:31]
• “We built this together and we all get to benefit.” — Betsy Stevenson [33:02]
• “People want to interact with people. I really, really believe that.” — Betsy Stevenson [39:06]
• “As long as you learn how to be attentive to other people’s needs, you will find your space in this world.” — Betsy Stevenson [43:46]

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Structure & Timestamps for Key Segments

• Main Discussion & Economic History Lessons: [03:07–14:41]
• Productive Struggle & Teaching Today: [15:32–24:15]
• Policy Solutions (Tax, Data Dividend): [27:13–34:27]
• Meaning in an AI World: [35:09–43:55]
• Lightning Round / Personal Insights: [47:07–54:27]

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Tone & Closing Remarks

The conversation maintains an optimistic yet realistic tone, respecting both the anxieties and hopes AI provokes. Stevenson encourages policies that foster inclusion, distribute benefits, and support human meaning—insisting that while AI holds enormous promise, it must be shaped by society and government, not just market forces. As Goldstein summarizes, “...we don’t need to let it just happen to us. It is something that we have some control over and we should take it.” [54:27]

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For listeners who want to understand the economic, psychological, and policy implications of AI—and how we might secure both prosperity and purpose in the AI age—this episode is essential.

Transcript

[Betsy Stevenson]

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[Jacob Goldstein]

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[Jacob Goldstein]

Pushkin.

[Podcast Announcer]

I'm Jacob Goldstein, and this is what's yous Problem?

[Jacob Goldstein]

My guest today is Betsy Stevenson.

[Podcast Announcer]

Betsy is a labor economist at the University of Michigan. She's worked in Washington. She was the chief economist at the Department of Labor. She was on President Obama's Council of Economic advisors.

[Jacob Goldstein]

And I wanted to talk with her

[Podcast Announcer]

because she's recently written a couple of really interesting papers about AI.

[Jacob Goldstein]

The problem Betsy is thinking about ultimately

[Podcast Announcer]

boils down to how can we create a world where the benefits of AI are broadly shared, where lots of people benefit? Almost everybody benefits.

[Jacob Goldstein]

In our conversation, Betsy and I talked

[Podcast Announcer]

about a few different things.

[Jacob Goldstein]

We talked about what history, economic history, has to teach us about what's happening now with AI. We talked about the effects of AI that she is seeing as a college teacher.

[Podcast Announcer]

And we also discussed the public policies

[Jacob Goldstein]

that Betsy thinks might help us live

[Podcast Announcer]

better in an AI world.

[Jacob Goldstein]

I appreciate the way Betsy focuses on

[Podcast Announcer]

meaning as well as on money when she thinks about AI and its implications.

[Jacob Goldstein]

And I also appreciate the way that

[Podcast Announcer]

she balances her worries about AI with hopes about how AI might make life better.

[Betsy Stevenson]

I'm not anti AI at all. I'm very pro AI. The pro is that AI will make us so productive that we can all have much higher living standards than we have right now. That AI will give us enormous bounty, that it will cure diseases, that it will solve problems. So the fear is not the productivity gains. The fear is always around. Does one person get the productivity gains and all the income and other people just lose work?

[Jacob Goldstein]

Did you have a moment yourself when you realized that AI, generative AI, is a big deal?

[Betsy Stevenson]

I think when ChatGPT came out, that's what then led me to think about it as, okay, we have had an utterly transformative technological change before, and that was when human strength got made completely redundant by machine strength.

[Jacob Goldstein]

So let's talk about the Industrial Revolution. You have walked us up to the Industrial Revolution, and in particular, let's talk about Engels Pause, named for Friedrich Engels, Robin to Karl Marx's Batman. What was Engels Pause?

[Betsy Stevenson]

So Engels Pause is a period of time, and I should say that phrase was coined by the economic historian Robert Allen. I love that phrase that he coined. So I want to make sure he gets his credit. And then I want to explain to you what happened is that we got this amazing technology that allowed us to produce a lot more. And the workers who were living in that era, who were born at the dawn of this revolution, got nothing. Yeah, right. So real. What do I mean by got nothing? Real wages in England, in the uk, where this technology was being developed, stagnated. So they did not grow for the majority of workers. And actually life expectancy fell.

[Jacob Goldstein]

They got less than nothing. Nothing would have been great compared to what they got.

[Betsy Stevenson]

Well, that created a lot of agitation and frustration. And so what did we get? What we get out of that is descriptions of this era by authors like Charles Dickens. And then we get writers like Marx and Engels who start talking about how this just doesn't work. It doesn't work if real people, the workers are being, you know, treated as an appendage of a machine dragged under the juggernaut of capitalism.

[Jacob Goldstein]

And so this, this period is like basically what, 1800 to 1850 or something. Right.

[Betsy Stevenson]

1760 to like 1840. And the, the reason the Industrial Revolution came to the UK was because it was the most advanced economy around and the workers were most expensive and the returns to capital were highest. So that's actually really an important part of the story. It didn't go to France. Those peasants weren't as expensive as the.

[Jacob Goldstein]

There wasn't as much of an incentive to create machines that could do the work people could do because the people were cheaper.

[Betsy Stevenson]

Exactly. Yeah, exactly. So this is. Now you're starting to like, see the dots I'm going to connect here. Like, where are workers right now? Expensive.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

In the United States.

[Jacob Goldstein]

And even. Which workers are expensive?

[Betsy Stevenson]

Which workers are expensive? Where are the incentives to replace workers with machines? And it's American white collar workers.

[Podcast Announcer]

Yes.

[Jacob Goldstein]

So, right. So the incentives are aligned. The cautionary tale in Engels pause is you can have huge productivity gains without wages going up. And I should add that in the long run, wages have gone up a lot. Right. Like Marx and Engels came along at a moment where it was like, look, there's the Industrial Revolution and wages don't go up and the rich guys who own the capital get all the money. But in the long run, that in fact has not happened. And like wages today are higher than they have ever been. Nobody will believe me if I say it, and people will get mad if I say it. But it's true.

[Betsy Stevenson]

Of course it's true. I mean, at the end of the day, wages can't go up unless we get technological change.

[Jacob Goldstein]

Well, right, but they don't have to, is the point of this story. And yet they have in the long run.

[Betsy Stevenson]

Exactly. So they don't have to. So that's why Engelspaws is a cautionary tale.

[Podcast Announcer]

Yeah.

[Betsy Stevenson]

And so then the question is, what are the institutional and societal frameworks we need to make sure that they do.

[Jacob Goldstein]

Right, to make sure that productivity gains are shared by workers as well as by the owners of capital, which in this case is basically the people who own the four frontier AI companies.

[Podcast Announcer]

If we're being reductive about it.

[Betsy Stevenson]

Exactly.

[Jacob Goldstein]

Okay, so that's one I want to do. One more historical story that you tell that, frankly, was more surprising to me that I hadn't heard before in this context, before we get to the present and then to the future. And that one is about labor saving devices in the home in the mid 20th century. The story of sort of, you know, the washing machine and the dishwasher and what that meant for economics and for meaning in people's life, which you talk about in a recent paper. Tell me about that.

[Betsy Stevenson]

You know, women have already gone through a transition where their work was completely replaced by machines and they had to adapt. And that's because women played big roles inside the home as homemakers who baked food from scratch, who kept houses clean, who did all the things somebody needed to do at home. And then they got vacuum cleaners and dishwashers and prepackaged foods. And the first thing that happens is the standards and expectations rise. So the first thing that happens is the houses have to be cleaner, the food has to be nicer, everything has to be done better. So they use all of this technological improvement, these productivity gains. Yeah. To just produce more home stuff. And that lasts for a little while, but it starts to really gnaw at some women. And that's when we get a problem that has no name. And Betty Friedan basically says the problem is women really have nothing to do at home.

[Jacob Goldstein]

This is the Feminine Mystique, published in what, 1960 or so.

[Betsy Stevenson]

Yeah, right. Why are the housewives so bored? They're bored because robots can do all their jobs and they need something more. And, you know, if you go back to your, you know, 1970s, 80s feminist literature, you see that some of them are advocating for women getting into the workplace, creating new identities as, you know, breadwinners as career women, which happened at a profound level.

[Jacob Goldstein]

Right. I think that shift is underappreciated. Like the. I mean, people know, at a superficial level, oh, yes, women entered the workforce, but when you look at a macro level, it is a profound transformation that happened in a relatively short period of time.

[Betsy Stevenson]

A profound transformation not only in what women do, but how they see themselves. That happened very quickly over, like, you know, one to two generations. Women went from, you know, seeing themselves as, you know, potentially happy housewives to wanting more. They expect more from their marriages. They expect more from their life. They expect more from themselves as independent, intellectual creatures. And one of the things I found interesting to tie it to this current moment is not every feminist thought or thinks that women need to enter the labor force to have this richer identity.

[Jacob Goldstein]

Yeah. There's this amazing quote in your paper. You know what it's gonna be? You're smiling. You say it.

[Betsy Stevenson]

I know. It is, like, my favorite quote. I feel like I need it up on my office bulletin board, which is. I didn't fight to get women out from behind to Hoover just to get them on the board of Hoover.

[Jacob Goldstein]

Yes. Hoover, the vacuum cleaner. Yes.

[Betsy Stevenson]

Right. And Hoover was a big brand of vacuum cleaner back in the day. And that's Jermaine Greer. And she's pointing out. No, that's not the. The point is not to swap one form of drudgery.

[Jacob Goldstein]

Yeah. Which is profound and different. Right. Like, I guess because of my age or, you know, whatever. The universe I live in is the universe of, like, oh, yes, women have jobs like men, and men help out around the house, and, like, this is the happy new equilibrium. But this quote is something entirely different and interesting in the context of AI.

[American Military University Advertiser]

Right.

[Jacob Goldstein]

What we're walking toward. I mean, the sort of. These two. I like these two stories in parallel, because the Engels Paws story is the one we're always thinking about and talking about, which is money and essentially labor versus capital. Right. That's every day everybody's talking about. The other one is meaning. The problem that has no name. The housewife whose skills are devalued by automation. It's not a money problem, it's a meaning problem. Right. And this idea that. No, no, the point is not just to go to work. The point is find some new source of meaning. Like, oh, this is interesting when one thinks about AI.

[Betsy Stevenson]

Yeah. It's a meaning and identity. So, you know, the. The Japanese have this concept of meaning called ikigai.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

That I pay a lot of attention to. And I just was in Japan about a year ago discussing a paper where they were using in their national survey, they're surveying people on their. Their life satisfaction, their subjective well being, happiness, and on their ikigai.

[Jacob Goldstein]

Yeah. And just to be clear, just define ikigai.

[Betsy Stevenson]

Ikigai is your purpose for living.

[Jacob Goldstein]

Okay.

[Betsy Stevenson]

Your purpose for living. And so it's kind of, what is the thing that drives you? What is it that you care about every day? What do you up and do? And so for people, their purpose could be really small, like tending their garden. I get up every day and I tend my garden because my garden's important to me. And my purpose of maintaining a beautiful garden is contributing to this world in some way.

[Podcast Announcer]

Yeah.

[Jacob Goldstein]

And we have these sort of set ones. Well, the big one for lots of us. Is work. Right. Or a big one. And a relevant one in the context of what we're talking about is work. So we've set the table now in a nice way. And so I want to, I want to talk a little bit about the present and then I want to talk about the future. I want to return to money and meaning. But the present is really interesting to me and I feel like kind of under discussed in the context of AI. Like everybody mostly talks about what's it going to be like if whatever the AI takes our jobs. But a lot is happening right now. And so I'm curious about your experience of AI in the present, both as a teacher and as an economist. Right. How has AI changed being a college teacher?

[Betsy Stevenson]

Oh, so there's so many things in there. So one thing that's obvious is that the students are struggling with the idea of productive struggle. And I think the reason for that is cognitive offloading is too easy.

[Jacob Goldstein]

So there's a lot of. You said a lot of semi jargony things in there. Like productive struggle is interesting. I get it. I think. But what's productive struggle?

[Betsy Stevenson]

So productive struggle, I mean, I talk about this with my 13 year old. Productive struggle is sitting in the math class and not knowing how to do the problem and just sitting with that and trying to figure out how you would solve it. How are you going to figure out how to do the math problem? And you don't. It feels frustrating. But you can stay in that moment of frustration and you can work through it. And you know what, it's super satisfying when you get to the other end.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

The productive struggle is that it's awful. Like, I don't know, I bet you've had this in your career. Have you ever sat there writing something and been like, this is the worst thing ever?

[Jacob Goldstein]

Oh yeah, I hated writing. I wrote a book and that was my experience of writing a book. I was unhappy for a year, basically.

[Betsy Stevenson]

But you're.

[Jacob Goldstein]

I'm happy that I wrote the book. I am happy that I wrote the book and I would do it again, so.

[Betsy Stevenson]

Yes, exactly. But you would do it again. You would do it again because actually it's probably meeting that icky guy. Yeah, it was, it wasn't fun.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

But it was purposeful. You did it with purpose and it made you feel like you were on a journey to somewhere good in your brain and your heart and your soul. But you gotta have enough incentives to want to be on that path because it's not actually fun.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

And that's like, I see that as I said, I got a 13 year old in seventh grade. We talk about productive struggle a lot. Productive.

[Jacob Goldstein]

I'm bringing that one home. I'm bringing that. I got two teenagers putting it in my dad tool belt.

[Betsy Stevenson]

Productive struggle is like, this isn't fun. I'm not gonna tell you it's fun. I'm not gonna tell you it's not that hard, buddy. Just, you know, I'm gonna say, oh, yeah, this sucks, but we're gonna go through it and then we're gonna get to the other side. We're gonna be glad because now you're gonna know how to do, you know, a multi equation algebra problem.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

And a lot of like how we process the world as a place we wanna be is through something's hard and then we achieve it and then we feel pride.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

And that is an important set of emotions and I think that AI is robbing students of that.

[Jacob Goldstein]

So. Okay, so that's an interesting sort of macro ish college teacher problem. So basically they don't have any incentives to do the work because they can just get ChatGPT to do it for them. Claude to do it for them.

[Betsy Stevenson]

Yes. And so then when you're asking them to do things, you know, they're, they're struggling, but they also are not having fun learning. I had a student who presented, I taught an AI policy class and she actually presented on this topic and she said school's not as fun as it used to be.

[Jacob Goldstein]

Wow.

[Betsy Stevenson]

And she was a graduate student who was doing a master's and she was one of those students who'd been a great student in high school, great student in college, and she was doing great in her master's degree. But she really described it as, I no longer have productive struggle with the aha moment.

[Jacob Goldstein]

It's the problem that has no name.

[Betsy Stevenson]

Yes. We're already getting to the problem that has no name.

[Jacob Goldstein]

Yeah. Do you feel it in your own work?

[Betsy Stevenson]

So I feel like I have to be very careful. And I definitely see myself where I get lazy. So I use the word cognitive offloading. There's a problem I could wrestle with, or ChatGPT could wrestle with it and then I could just much more easily absorb it. But the research does show when you stop the struggle, you stop the learning.

[Jacob Goldstein]

I mean, the dream. Right. The sort of Pollyanna ish version is the model. The AI allows you to struggle at a higher level. Right. Like it gets somewhere, it gets through some work that you could have done, but that wouldn't really push any frontiers. And it gets you to this new place. And then you struggle, but you struggle better or you struggle farther or something. Like, I think I, AI, can write better still than just AI. I think I can write a better podcast script for me than Claude can. And so maybe not forever, but at least for now. And so then how can I use it optimally? How can I use it to whatever, be more efficient or be smarter?

[Betsy Stevenson]

So I'll give you a couple of examples of how I've used it recently. So I was writing, I was participating in a little debate and I had to have my five minute opening statement. And I just went back and forth and asked a ton of questions to ChatGPT. And then I followed the links to the sources it found, and then that made me come back with more questions and ask about more sources. And it was, it was like, basically I would have given that to a research assistant. Yeah, would have come back and said, here, look at these five, you know, sources. And that would be really helpful. But I'll tell you the other funny thing was I drafted my five minute opening and then I pasted it in and I said, fact check this and tighten it. And it immediately gave me back just like a rewrite. And I wrote that was sloppy. I want you to go line by line and fact check it. I'll do my own tightening, thanks.

[Jacob Goldstein]

Yes.

[Betsy Stevenson]

And it was like, whoops, okay, your

[Jacob Goldstein]

right to push back. Did I give you that one? Your right to push back.

[Betsy Stevenson]

Yeah. It then complimented me on my, yes, great job. But the line by line fact checking was amazing. Like, it gave me an external source for everything I said. And then it said, oof, this claim seems a little maybe over the top. Do you really want to make it?

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

So then it finally gave me some negative feedback because I made it go line by line and tell me, where's the external source that justifies it? So it is on how we use it, but I don't think we're training young people right now properly on how to use it.

[Jacob Goldstein]

Are you getting better at helping your students use it? Getting better. Like, it seems like what you want is to figure out a way that your students can use AI and still have the productive struggle.

[Betsy Stevenson]

I think we're really in the. I would say that at the end of this semester, I found that there are changes I'll make for next year.

[Jacob Goldstein]

So it's tough times. So you're saying it's tough times, right?

[Betsy Stevenson]

I'm saying the students are getting worse quite quickly on this domain. And so the speed at which I need to address it is getting faster.

[Jacob Goldstein]

Like, do you feel like you're going to have to start making the students do work in class?

[Betsy Stevenson]

Boy, that like, I definitely think I have to change the assignments and the way that I assess them because having them write an essay at home is useless now.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

Yeah. In one of my classes, one of the best sets of essays I got was from a student who couldn't answer a single question I asked in class about his essays because he clearly didn't write them, but he obviously knew how to prompt well. So chatgpt wrote me some beautiful essays.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

I was telling another instructor, yeah, I loved reading those essays as I prepared for class because I knew it was a really good summary of what I needed to cover that day. But because they were reading summaries and he was the best at the class at prompting. But the students who. I could see the authenticity in students who might have used AI to help them a little bit. But the actual genuine things that they were noticing from the reading that they thought were most relevant, it was clearly authentic to them and their approach. And then when I have a dozen unique perspectives. Now we have a discussion.

[Jacob Goldstein]

Yeah, right.

[Betsy Stevenson]

We have a dozen beautifully crafted summaries from AI. We don't have a discussion.

[Jacob Goldstein]

After the break, Betsy and I talk about the future.

[Podcast Announcer]

We talk about money and, and meaning and purpose in an AI world. I'm not like a coffee connoisseur, but recently I tried coffee from a company called Perc and I loved it.

[Jacob Goldstein]

And I'm not just saying that because

[Podcast Announcer]

this is an ad for Perk though.

[Jacob Goldstein]

This is an ad for Perc.

[Podcast Announcer]

I really did think the coffee was delicious. Perc has lots of different coffees to choose from and they color code their bags. The blue bags are mild coffee. The pink bags are wild coffee.

[Jacob Goldstein]

You can find the coffee that matches

[Podcast Announcer]

your vibe and get 15% off your next order with promo code [e-mail] that's P E R C coffee.com promo code problem. When you own your own business, you own every decision. Now own the card that rewards you for it. The Chase Sapphire Reserve for Business card brings the best sapphire reserve benefits to business owners who expect hard working rewards. Designed to meet the needs of business owners at scale, this pay in full card elevates your travel experience and offers premium benefits and value toward business services that'll take your business to the next level, fuel your business and maximize rewards. With 8x points on all purchases through Chase Travel, 3x points on social media and search engine advertising, annual partnership credits and more make every journey more rewarding with a $300 annual travel credit and access to a network of airport lounges. Whether you're looking for pre flight productivity or time to rest and recharge. Chase Sapphire Reserve for Business it's the card that gives back all you put in. Learn [e-mail] ReserveBusiness Chase for Business make more of what's Yours Accounts subject to credit approval restrictions and limitations apply. Cards are issued by JPMorgan Chase Bank NA member FDIC.

[Jacob Goldstein]

Did you ever notice how you spend

[Podcast Announcer]

hours shopping online only to pause right before you hit buy? Now that tiny hesitation, the one where you wonder if it's trustworthy, can make or break the sale. Now, with AI changing the way we

[Jacob Goldstein]

discover and compare things, that split second

[Podcast Announcer]

trust question matters more than ever. That's where PayPal comes in. For more than 25 years, PayPal has been a leader in online payments. And now they're at the forefront of agentic commerce, making it work for businesses, letting them maintain control of their brand and their customer relationships.

[Jacob Goldstein]

So even as the way we shop

[Podcast Announcer]

changes, the moment that matters most still feels familiar and deeply dependable. Built for payments, growth and agentic PayPal open built for all business. Visit PayPalOpen.com to get started.

[Jacob Goldstein]

Let's go to the long term, right? You have written this paper where you have you sort of lay out kind of what your worries are and what you think we should do in response to your worries. So one, it's kind of a classic but interesting in this context is how much we tax capital gains, basically profits from investments versus how much we tax labor work. Right? Income tax. Talk about your view on that.

[Betsy Stevenson]

So the historic view on taxing labor versus taxing capital is that people are going to work and they're going to work sort of no matter whether you tax them or you don't. So we tax labor income because we need revenue. So in contrast, the idea was that people really like to consume today. And so getting them to invest their money in something that they're going to not get any money for a long time. You know, they invest in a new factory and that's going to give them purchasing power in 10 years, but nothing today. So they're going to have to give up purchasing power today in order to build a factory. Well, we figured that they needed a lot of incentives to do that because people like spending today. So how do I get you to give up spending today in order to save and invest in that factory? Well, I don't want to tax that Behavior. And so we have traditionally put more of our taxes on labor than on capital investments. So if I go out and I work and I make $100,000, I pay more in taxes than if I, you know, if I invest and I'm starting to make $100,000 a year off of my investment.

[Jacob Goldstein]

Yes.

[Betsy Stevenson]

And I think with AI, it's going to start to change how we should think about that, because it makes capital cheaper, because it's a smaller tax wedge.

[Jacob Goldstein]

So if you have a choice between employing somebody and, well, paying for AI, buying a bunch of AI tokens that cost the same amount as the person, the tax system makes you prefer the AI investment to the human being.

[Betsy Stevenson]

Exactly.

[Jacob Goldstein]

Under our current rules. Okay, yeah.

[Betsy Stevenson]

So the tax system prefers capital investment over human labor. And so right now we have a tax system that is rewarding what is currently happening, which is the labor share of income is going down, and the share of income that's generated by investments by capital is going up. And that also creates a revenue problem. You might have heard the US is running some debt, but it's also creating a disincentive to hire people over capital that we probably want to move the other direction. We actually probably want to subsidize hiring people and maybe just slow down a little bit the rate at which companies are moving towards capital substitution.

[Jacob Goldstein]

So concretely, does this boil down to raise the capital gains tax, lower taxes

[Betsy Stevenson]

on wages, and make it up by

[Jacob Goldstein]

raising the capital gains tax, the revenue neutral version? Yeah. I mean, to be clear, from the point of view of the employer, lowering the income tax, not the payroll tax, but the income tax, you don't care about that as the employer. I mean, it might make workers a little bit more willing to work.

[Betsy Stevenson]

At the margin. Yes, it should make workers a little bit more willing to work. And that means, frankly, you could pay them a little bit less. And that is, in fact, what the data says happens. So this would show up as savings and compensation costs to employers.

[Jacob Goldstein]

So higher income taxes.

[Betsy Stevenson]

A lot of people are probably really disappointed right now. Wait, wait, you mean the employers capture a cut in labor income taxes? Yeah, yeah, that's what happens.

[Jacob Goldstein]

Okay, so that's one. So you also have this idea you call the data dividend, which is very good. It reminds me of your time in Washington. What's the data dividend?

[Betsy Stevenson]

So, I mean, the thing that's Most remarkable about AI is we've all built it. OpenAI didn't build AI. Anthropic didn't build AI. They're training on every word. I've ever written. Every word my grandparents wrote, every word my grandparents grandparents wrote, you know, all. It's not just, you know, I, yes, have speeches in the public domain, but I really mean it more more broadly than that. All of the knowledge of humanity is what has trained these AIs. So when Sam Altman says, I envision a world where cognition is sold to you, by the token, I'm like, wait, he's envisioning a world in which he sucked up all of human cognition and now he's going to sell it back to us? Well, I'd like him to pay us for it first. And that shared resource, that public good, that all of human cognition that has trained these models that should give each and every one of us a stake in the benefits. And that's what the data dividend's about. So think about it like the Alaska Permanent Fund. Alaska's sitting on a bunch of oil. That oil belongs to the citizens of Alaska. And every year they get a check from the government that says, this is your share of what we made off the oil.

[Jacob Goldstein]

Yeah, it's such an interesting. If I was an economist, I'd move to Alaska and just study that for my whole life.

[Betsy Stevenson]

There are many economists who have studied it and it turns out it doesn't. People still go to work. But now I'm going to get beyond. It's more than economics. So from an economics perspective, that puts a certain amount of consumption in every Alaskan's hands. A data dividend could put a certain amount of consumption in everybody's hands, but it does more than that. It also says, you belong, you are part of this. And so when we developed this, everybody's probably heard a lot about like universal basic incomes, but it's not about giving losers a handout. That language infuriates me. You belong. You're part of this. We built this together and we all get to benefit. That's what we have to recognize. And those are the models that institutional models and frameworks we're going to have to build for this to be something that's successful, that levels up everybody.

[Jacob Goldstein]

Not to bring crass details to this elevated discourse, but like in practice is the thing you're talking about the sort of frontier AI companies paying some kind of tax that is then distributed to everybody in America? Is that fundamentally the thing you're imagining?

[Betsy Stevenson]

Yeah. What's wrong with that? I mean, they could have paid for all the data they've used, but we had this model where we put a bunch of stuff in the commons that's not how we envisioned the commons. We didn't create the commons so one company could capitalize on all of it. And that I think it means that we have to think about how we want to treat the commons in this new era. Because it can't just be one company sucks the whole thing up and then we all lose. I think it's an institutional failure to let people get rich off of what's in the commons and then try to sell it back to us. I don't want my own cognition sold back to me.

[Jacob Goldstein]

So we've been talking mostly about the money piece, although you started talking about meaning in there, but let's talk more about meaning. I mean, we sort of frame this in those two ways, right? The meaning piece in some ways is harder to figure out for me. I mean, the money piece is like, well, if productivity goes up, there's gonna be more money. And like, that's a good starting place. And then hopefully we could figure it out. The meaning piece seems squishier and harder. Like, what do we do about meaning if there is, in fact, a lot of unemployment and we have solved money?

[Betsy Stevenson]

Well, you know, the person who really identified that we were on a really negative trajectory on meaning was Bob Putnam, who wrote a book called Bowling alone in the 90s. And there, what he was saying is, we're abandoning our communities. We don't bowl in bowling leagues anymore, even though we bowl just as often. We just go and do it by ourselves or in small groups. And what that has meant is that we've loaded too much onto work. So work is becoming our community. Our people refer to their work. Family. Yeah, right. So we have successful transitions and unsuccessful. So we talked about women successfully transitioned outside the home, and it developed new identities, new meaning, new purpose. People successfully transitioned out of agriculture. You know, it. You know, even since 2000, we went from 40% of the globe working in agriculture to about 25% today. And there's no agricultural meaning crisis. And what that meant was people were pulled out of agriculture by opportunity. Now, let's compare that with what happened with manufacturing, where men have been pushed out of manufacturing, not pulled, not pulled by opportunity, pushed by closures and factory closures that have left nothing in its wake, no alternative. And that's what I think is a really important lesson for us to think about from a meaning and identity perspective. Because you have a ton of men who still are thinking, there are no jobs for me, because the only jobs being created are in health care and healthcare. Jobs are so feminized.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

And so that real identity and meaning crisis exists and it's spilling into family formation and having a lot of negative effects. And I think it is a warning to us that we have to figure out how to pull people out of opportunities that are closing into something that's better rather than letting them get pushed off a cliff.

[Jacob Goldstein]

But how?

[Betsy Stevenson]

Well, one thing to do is to start to build more community networks, to try to find ways to reward volunteer work, to reward community involvement. You know, there are lots of things people do outside of work that build meaning. That could be being a member of a club, it can be, you know, volunteering at a particular organization.

[Jacob Goldstein]

I mean, I know what the things

[Betsy Stevenson]

are, but like how do we do it?

[Jacob Goldstein]

Yeah, I mean, as you pointed out, somebody wrote whatever 40 years ago, 30 years ago, that we're not doing it anymore. And that was before we had phones and you know, things to just lock up our brains all day. Like everything, even with jobs is going in the opposite direction. People are becoming less and less and less social.

[Betsy Stevenson]

Well, this is why I think about putting something together that creates rewards. Whether it's your data dividend is a function of logging community service hours.

[Jacob Goldstein]

Uh huh. You gotta leave the house to get your data dividend. You gotta go talk to a human being face to face.

[Betsy Stevenson]

Right. And you know, people want to interact with people. I really, really believe that.

[Jacob Goldstein]

I mean, are there like, you know, are there successful examples of this, like people leaving agriculture to go into manufacturing? That is fundamentally the market solving the problem. Right. And a weird potential outcome we're looking at is like there is not a market to solve the problem. And like the notion that you can have some kind of top down solution to this problem of meaning.

[Betsy Stevenson]

Well, we could have, look, one thing we could do is government could start to subsidize third spaces and draw them in. So we could choose to make third spaces all tax free, no property tax on public space.

[Jacob Goldstein]

That's the Starbucks act of 2020.

[Betsy Stevenson]

If Starbucks is going to let you in without buying anything, then they get a property tax reduction. Right. You start to think of creative ways to pull people into the community so they do things. And honestly, an afternoon at Starbucks is a refreshing way to engage with humans. Talking to the baristas, seeing the people who go around the same time you do every day, those small moments of connection actually are really important to people, more important than they realize, or they would prioritize them more.

[Jacob Goldstein]

So you teach teenagers and very young adults, and you are the mother of one teenager, two teenagers, teenagers of two teenagers, like, what do you tell the kids? As a labor economist who has studied AI, what is your professional advice for the children?

[Betsy Stevenson]

Oh, I mean, I. It's. It's. I'm going to say, actually, I find it really hard. I was at a. I gave a talk at Syracuse, and it was a big talk on AI and afterwards, a young man came up to me and he said, I'm risking everything to be here. I borrowed so much money, and how do I know my investments are not going to go down the tube? And I almost cried for him because I can't tell him his investment's not going to go down the tubes. I don't know. And I think I want. Just remember that when you're talking to young people, remember the amount of risk and uncertainty they're facing. It's like nothing you and I faced. And I took all sorts of crazy gambles, but I didn't have a spotlight on me, first of all. I didn't have the risk of everything being on camera, everything being documented. And I could know with some certainty if I studied the field like economics, things are going to be okay for me. I knew I was a math econ major because I wanted to reduce economic uncertainty in my life. I'd grown up with a lot of it, and I was like, these are two majors. They're going to pay off. I can work in finance. Yeah. I could work at a corporation.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

I could, you know, grow up to be an econ teacher or a math teacher. I had a lot of bases covered.

[Jacob Goldstein]

Yeah.

[Betsy Stevenson]

And I don't. There's almost nothing I can tell kids now where I'm like, this will work for you. But what I do tell them is adaptability is going to really matter. Curiosity is your friend. And creativity, despite everything you hear about AI, your creativity is unique to you. Everybody's creativity is like a fingerprint. And I think that we will have a desire for bespoke human creativity even as AI starts to do things. So I. I think at the end of the day, what I use to say, ultimately there'll be something to do is to realize all exchange from the beginning of time to now is two human beings, one of whom want something that they cannot provide themselves, and the other one can provide it. I do not think AI is going to eliminate all of our needs. We will still be looking to each other to fulfill those needs. And as long as you learn how to be attentive to other people's needs, you will find your space in this world.

[Jacob Goldstein]

We'll be back in a minute with the lightning round.

[Podcast Announcer]

I'm not like a coffee connoisseur, but recently I tried coffee from a company called Perc and I loved it.

[Jacob Goldstein]

And I'm not just saying that because

[Podcast Announcer]

this is an ad for Perc though.

[Jacob Goldstein]

This is an ad for Perc.

[Podcast Announcer]

I really did think the coffee was delicious. The bag I'm drinking at the moment was grown in Peru. Perc sources coffee from all over the world.

[Jacob Goldstein]

They have lots of different kinds of

[Podcast Announcer]

coffee to choose from and they color code their bags. Blue bags are more mild coffee and pink bags are more wild coffee.

[Jacob Goldstein]

That Peruvian coffee I'm drinking now is

[Podcast Announcer]

wild and if you're on the fence, I recommend trying wild.

[Jacob Goldstein]

The other morning I had my first

[Podcast Announcer]

sip and I thought of that Will Ferrell line in old school where he

[Jacob Goldstein]

hits the beer bong and then he

[Podcast Announcer]

says once it hits your lips, it's so good. Find the coffee that matches your vibe

[Jacob Goldstein]

and get 15% off your next order

[Podcast Announcer]

with promo code [e-mail] that's P E R C coffee.com promo code perk problem when you own your own business, you own every decision. Now own the card that rewards you for it. The Chase Sapphire Reserve for Business card brings the best Sapphire Reserve benefits to business owners who expect hard working rewards. Designed to meet the needs of business owners at scale, this Pay in Full card elevates your travel experience and offers premium benefits and value toward business services that'll take your business to the next level, fuel your business and maximize rewards. With 8x points on all purchases through Chase Travel, 3x points on social media and search engine advertising, annual partnership credits and more. Make every journey more rewarding with a $300 annual travel credit and access to a network of airport lounges. Whether you're looking for pre flight productivity or time to rest and recharge, Chase Sapphire Reserve for Business it's the card that gives back all you put in. Learn [e-mail] reserve business chase for Business make more of what's yours Accounts subject to credit approval restrictions and limitations apply. Cards are issued by JPMorgan Chase Bank NA member FDIC did you ever notice how you spend hours shopping online only to pause right before you hit buy? Now that tiny hesitation, the one where you wonder if it's trustworthy, can make or break the sale. Now with AI changing the way we

[Jacob Goldstein]

discover and compare things that split second

[Podcast Announcer]

trust question matters more than ever. That's where PayPal comes in. For more than 25 years, PayPal has been a leader in online payments and now they're at the forefront of agentic commerce, making it work for businesses, letting them maintain control of their brand and their customer relationships.

[Jacob Goldstein]

So even as the way we shop

[Podcast Announcer]

changes, the moment that matters most still feels familiar and deeply dependable. Built for payments, growth and agentic. PayPal open. Built for all business. Visit paypalopen.com to get started.

[Jacob Goldstein]

Let's finish with the lightning round.

[Betsy Stevenson]

All right.

[Jacob Goldstein]

What is something other than family and work that gives you meaning in life?

[Betsy Stevenson]

Birds.

[Podcast Announcer]

Oh, birds.

[Betsy Stevenson]

I really like birds.

[Jacob Goldstein]

You got a list? You like that kind of birder?

[Betsy Stevenson]

No, but I really, I enjoy nature and wildlife. And when we go to Australia, I am very into the Australian birds. And I really like. If you've ever spent time with, like, cockatoos or other parrots, they're so smart and they're really, like, a joy to interact with.

[Jacob Goldstein]

I should say that you're. What do you call Justin? Your life partner. Your common law husband. Is Australian.

[Betsy Stevenson]

Is Australian.

[Jacob Goldstein]

And, like, do people, like, hang out with cockatoos and parrots in Australia? Is that just, like, a thing? I don't know.

[Betsy Stevenson]

Yeah. Like, I go down to the park and I feed them all the time and they'll eat right out of my hand. And the Australians are like, stop feeding the cockatoos. I'm like, no, it's so awesome. And don't do it away from people's houses, though, because otherwise they will throw a little tanty and knock on the wood to get you to bring out the nuts.

[Jacob Goldstein]

Good to know. I'll keep that in mind. So I know you've done a fair bit of work on the economics of

[Podcast Announcer]

family life, and I'm curious if there's

[Jacob Goldstein]

any insights from that that are, like, useful to you in your own daily life.

[Betsy Stevenson]

Well, I guess thinking about the what you should make versus buy and how to really think hard through opportunity costs, cost benefit analysis to make that decision. And you might be surprised. Like, you know, I told you I was on the board of Lyft, and Justin's always like, why do you act like a Lyft driver for our teenager when you could actually pay for a lift? And I'm like, because they talk more in the car. Every parent heard this thing where your teenager tells you something that they wouldn't tell you if they weren't in the car side by side with you and trapped there for a little while.

[Jacob Goldstein]

Yes.

[Betsy Stevenson]

So, I mean, I spent a Saturday like 2 weeks ago driving for 4 hours to get my daughter from a track meet to a friend's house for Promotion, like, it was just ridiculous, but it's building a connection that I can't get elsewhere. So if you think about what cost benefit analysis says, it never says do or don't do something. It says only do them when the benefits exceed the costs. And so I'm very good at thinking through non financial benefits and financial benefits and non financial costs and financial costs and making decisions that I feel really comfortable with.

[Jacob Goldstein]

That was a 10 of 10 answer. Most Underrated economist of all time.

[Betsy Stevenson]

Well, I mean, there's a lot, actually. I'm going to give you a. I just wrote the foreword to a book of Australian women in economics.

[Jacob Goldstein]

Okay.

[Betsy Stevenson]

And actually there were some just absolutely incredible women in that book because they were using the insights of family life and bringing it into economics. And you know, you're like mid-1800s, late 1800s Australia. So, you know what was really powerful about the book is it was like, wait, let's just celebrate the people that succeeded despite the fact that they did it against lots of odds and maybe they didn't have traditional male success, but they were there, they did get their degree, they did do their work, and let's learn about them. And so that I would say was a big eye opener to me. So there's a lot of underrated, particularly women or minority economists that we don't think about at all.

[Jacob Goldstein]

What's one thing your kids have taught you about AI?

[Betsy Stevenson]

They didn't ask for it and they don't really want it.

[Jacob Goldstein]

Yeah, my kids are also anti AI. Like, it's weird. I'm way more into it than they are.

[Betsy Stevenson]

Yeah, that's where we're at in your household. But I think what they taught me is, I didn't ask for this. It's going to upend my life. I don't know how to live with it. And why do I have to do this? You didn't have to. Why do I have to navigate this thing?

[Jacob Goldstein]

I mean, I also didn't ask for it and I also would prefer that it not exist. But it does exist.

[Betsy Stevenson]

Right. But it, you know, they've also taught

[Grainger Advertiser]

me

[Betsy Stevenson]

how hard it is living under a spotlight. Yeah, they live in the spotlight. I mean, when my son was 8, he said, no more social media of me, please, Mom. Oh, yeah, never. And I have not put a, posted a photo of him on social media since maybe he was even seven. It was just like, no, I don't want this big digital footprint.

[Jacob Goldstein]

Smart kid. That's like a humble brag right there.

[Betsy Stevenson]

But it was, I thought it was really interesting at such a young. I mean, it's worrisome at such a young age to be so cognizant of what that means.

[Jacob Goldstein]

It's tough to be a smart kid. Okay, last one. What's your favorite way to use AI that has nothing to do with work.

[Betsy Stevenson]

Plan vacations. Spring break. I was like, I have four days. I want a nonstop flight. I want to travel no more than four hours, three hours. Where should I go? And it was like. It kept pushing me to the beach. And I was like, no, I don't want a beach. It's like, fine, go to Arizona. So we did.

[Jacob Goldstein]

How was it?

[Betsy Stevenson]

It was amazing. I had never hiked in the Grand Canyon before, and now I am determined that I'm going to do the Rim to Rim hike from the North Rim to the South Rim.

[Jacob Goldstein]

You do it in a day. You go down and up.

[Betsy Stevenson]

Well, some people do that, but I'm not insane. I'm going to do it in two days.

[Jacob Goldstein]

And you camp on the river.

[Betsy Stevenson]

You camp on the river? Yeah.

[Jacob Goldstein]

That sounds incredible.

[Betsy Stevenson]

Yeah, that's where. See, there's a lot of things to do if we don't work so much.

[Jacob Goldstein]

Yes. Although, I'll be honest, I like working better than hiking. I mean, I like hiking. I love exercise.

[Betsy Stevenson]

Have you seen birds?

[Jacob Goldstein]

I'm not. I like birds. But, like, if I could do some work, you know, I mean, I'm interested in some work. You know what I mean? Like, me too.

[Betsy Stevenson]

Me too.

[Jacob Goldstein]

Like, if I could work a few hours a day. The other thing is, like, I mean, if there's. If we're really dreaming big, like, if there's a universe where, like, I don't need to worry about money and I can make a podcast and people like it. That's actually the part that I like. Right. And so, you know, that's fine, I think.

[Betsy Stevenson]

Aren't we entering that era where we're all just creating content for each other? So as long as we get paid.

[Jacob Goldstein]

Yeah, yeah. Or donate the money. Anything else you want to say or talk about?

[Betsy Stevenson]

I think, like, as a thing to remember is, like, we can't actually improve our living standards without an increase in productivity. And so that's the reason why we can't be totally afraid of AI, but we do need to realize that we're responsible for how our society responds to it. We don't need to let it just happen to us. It is something that we have some control over and we should take it. And so this is where we need to start to have that. How should we spend our new wealth. We should think of it collectively. I'd like to spend some of it on vacation. I'd like to spend some of it on national healthcare. But I definitely want us to get it. And that's what AI, that's its potential is. It's going to give us the wealth that could get us those things.

[Jacob Goldstein]

Thank you for being so generous with your time.

[Betsy Stevenson]

Yeah, it was awesome to talk to you. This was super fun.

[Jacob Goldstein]

Betsy Stevenson is a professor at the

[Podcast Announcer]

Gerald R. Ford School of Public Policy at the University of Michigan. Today's show was produced by Gabriel Hunter Chang and edited by Lydia Jean Cott. Our engineer this week was Hansdale.

[Jacob Goldstein]

She we're always looking for ideas for who to talk to and what to

[Podcast Announcer]

cover on the show. You can email us at Problemushkin FM.

[Jacob Goldstein]

You can find me on xacobgoldstein. You can find me on LinkedIn. I'm Jacob Goldstein. Thank you very much for listening to the show and we'll be back next

[Podcast Announcer]

week with another episode. I'm not like a coffee connoisseur, but recently I tried coffee from a company called Perc and I loved it.

[Jacob Goldstein]

And I'm not just saying that because

[Podcast Announcer]

this is an ad for Perk though.

[Jacob Goldstein]

This is an ad for Perc.

[Podcast Announcer]

I really did think the coffee was delicious.

[Jacob Goldstein]

Perc has lots of different coffees to

[Podcast Announcer]

choose from and they color code their bags. The blue bags are mild coffee, the pink bags are wild coffee. You can find the coffee that matches your vibe and get 15% off your next order with promo code [e-mail] that's P E R C coffee.com promo code

[Grainger Advertiser]

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[Betsy Stevenson]

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