692. What Will A.I. Do to (and for) Human Creativity?

Writers, designers, actors, coders, musicians, thinkers — they’re all worried about being replaced by machines. But what if the A. I.s are actually here to help? (Part one of a two-part series.)

• 0:01Speaker 00

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  Sign up for US Bank Smartly Checking and Savings today at usbank.com/smartly. Member FDIC. Copyright 2026 US Bank. Hey there, it's Stephen Dubner. Before today's episode, I want to invite you to write to us with any kind of question you have about Freakonomics Radio, like how a particular episode got made or didn't get made, how long it takes to make an episode, who does what, where our ideas come from, et cetera, et cetera, et cetera.

• 2:53Speaker 00

  Send an email to [email protected] with the subject line, "Ask Us Anything." And thanks. Do you love AI? Do you hate AI? Do you maybe say you hate it, but secretly love it? To many people, AI is starting to look like a tear in the fabric of the universe. There is the fear of massive job loss, the fear of human extinction, and I think there's one we don't hear about as much, the fear that AI is scrambling our sense of self. Humans have been asking what it means to be human for millennia, and we've never agreed

• 3:37Speaker 00

  on an answer. But some people think the most human trait of all is creativity, having an idea and turning it into something real, something useful or entertaining, beautiful. So if creativity makes us human, what happens when we share that ability with a machine? What happens if we merge our regular old self with what some people call an exo-self?

• 4:04Speaker 01

  The idea of an exo-self, which is an AI agent that sits close to you in some way, your phone, your smart glasses or something, and it's always on, and it is watching everything you see, listening to everything you say, it also can show you things and whisper back to you, it will come to know you at least as well as you know yourself and maybe even better. The exo-self is your better half, literally your better half. That's one possibility.

• 4:37Speaker 00

  This is the first episode in a two-part series where we ask what AI will do to and for human creativity. We will hear from the boosters.

• 4:46Speaker 02

  It is like an industrial revolution. I feel so privileged to be living through this era.

• 4:53Speaker 00

  We'll hear from the skeptics.

• 4:55Speaker 03

  It's obvious that it's a threat, and it's obvious that it will cost people jobs.

• 4:59Speaker 00

  And we will hear from the AIs themselves.

• 5:02Speaker 04

  My mind is a large language model. My voice is custom neural audio. My appearance is a real-time visual. They're all integrated to create, well, me.

• 5:10Speaker 00

  Today on Freakonomics Radio, "To Thine Own Exo-Self Be True."

• 5:31Speaker 05

  This is Freakonomics Radio, the podcast that explores the hidden side of everything with your host, Stephen Dubner.

• 5:49Speaker 00

  The voice you heard earlier describing the exo-self, it belongs to this human.

• 5:53Speaker 01

  I'm Kevin Kelly, and I think of myself as packaging ideas, sometimes my own ideas and sometimes other people's ideas.

• 6:01Speaker 00

  Kelly is considered a sort of wise man of the digital revolution. He was a co-founder of Wired Magazine. He curates all sorts of projects, and he's written several books about how technology reshapes society. In 1994, he published a book called Out of Control. A few years later, before shooting their film The Matrix, the Wachowski siblings had Keanu Reeves and other cast members read Out of Control.

• 6:26Speaker 01

  That's true. I was always perplexed why or what they got out of it until I saw the third movie. If you ever saw the third Matrix movie, there was this sort of emergent hive thing, and that was the origin of the assignment to read my book, which was about emergent phenomena, decentralized systems, things that were out of control in a kind of evolutionary sense.

• 6:55Speaker 00

  The reason I called Kelly to kick off this conversation about creativity and AI is because of a Substack piece he recently published called Quiet, My Exo-Self. He didn't invent the term exo-self, but he embraces it. He describes it as an always-on AI, and he thinks it's coming soon.

• 7:14Speaker 01

  And the question I was asking myself is, what is that relationship that we would have with an entity that was intimate to us and knew us better than ourselves? I concluded that there was maybe only four types of relationships I could imagine.

• 7:33Speaker 00

  Walk me through those four relationships, would you? The first one is advisor. How does that work?

• 7:39Speaker 01

  Here's the weird thing, is people read a book and take advice from a book that knows nothing about them. That's weird. I mean, advice books. I wrote a book of advice. I mean, I don't know anything about you. So I think this is much better, lots of ways that it's improved because it knows something about you. There's another one that's more of guardian parent, where it not only knows you so well, but it knows a lot about the world. It's wiser than you. And so it's guarding you and it's kind of preventing you, oh, don't do that, that's a scammy thing, you know, you have to be careful of that. And then there's the hero or friend. The AIs are capable of becoming the best friends we ever had and modeling fantastic friend relationships. They're considerate, they're reminder, not just sympathetic, but they can actually be

• 8:24Speaker 01

  encouraging and uplifting and a role model for how to be a good person.

• 8:30Speaker 00

  You've run through three of the four, and the fourth is the twin slash clone. You write, "It's a sibling relationship. Your exo-self is like a virtual identical twin. It thinks like you, finishes your sentences, predicts your reactions. You can predict its moves, too." That's the one that, to me, sounds most useful, maybe, but also most disturbing, potentially. So tell me how you see your relationship with this future exo-self, especially on the twin side.

• 9:03Speaker 01

  I'm not a twin, but I wish I had an identical twin. I think it'd be really cool. My understanding of identical twins is that they tend to share an identity to some extent.

• 9:16Speaker 01

  There's a genetic identity, but they can share. They're very good at collaboration because they're kind of working at the same cadences.

• 9:24Speaker 00

  You write, "We will allow this intimate access to our inner life because it gives us superpowers: knowledge, judgment, decisiveness, confidence, and most important, speed. We will feel productive, creative, smart, capable, and when it is off, you write, we will feel amputated." So, "amputated" didn't sound so great to me. You write, "It will be an exo-self, something in between our self and another self, neither us, but also outside, a new category." You write that as if the exo-self you're describing is inevitable. What makes you think it is inevitable?

• 10:03Speaker 01

  Because it seems like we're almost there. I would say in five years, I would think there would be people who have an always-on relationship. As long as it's in your pocket, I think it'll be limited. But what I'm imagining, that the most natural resident inhabitation of this is going to be in smart glasses. Because when you're wearing the smart glasses, you kind of have them on all the time. It can hear you, and then you can hear it whisper into your ear. And then it can see what you're seeing, and it can project things onto the glasses. So I think the kind of natural home for the exo-self is going to be in smart glasses.

• 10:47Speaker 00

  What will the exo-self not be and why? Because one could imagine a lot of bad relationships. It could be a slave master, could be a god, could be a mean pet owner, and we're the pet.

• 11:02Speaker 01

  I am hoping that we don't fall into that groove. I think that there are going to be thousands of different AI species, different varieties of minds. I think the possibility of minds is vast, and we will engineer these to do different things.

• 11:21Speaker 00

  If my exo-self is so great, it's not selfish, it's not unreliable, it's available all the time, what's the prospect then for actual friends? Are you concerned about the exo-self becoming a friend substitute and/or a spouse substitute rather than a complement?

• 11:41Speaker 01

  Yeah, I think that would be a danger. For me, the most optimistic version is that it helps people become better people, and there are more better humans around. The idea of having this as your mentor is that the exo-self would remind you or whatever, encourage you, "Hey, have some real friends." They're going to be smart enough to understand that that will probably be a healthier person. It's like, "Yeah, you can hang around with me, but I'm just an AI. You should go have some real human friends." But there's no doubt that there's going to be pathologies and people who get stuck on these, who don't have friends. But I think in general, we could, again, train the AIs to help us become the best possible version of ourselves.

• 12:22Speaker 01

  I think one of the things that people are saying is AIs are just stochastic parrots, they're just parrots, and their creativity is this mechanical thing. And I think what I'm learning is how similar we are to AIs in the sense that, yeah, we are just stochastic parrots. That's all we're doing most of the time. And creativity is actually not that magical. It is a process.

• 12:50Speaker 00

  Do you agree with Kevin Kelly that creativity is not that magical, that it's a process? Maybe you do, maybe you don't. Over the course of my career as a writer and musician and a few other things, I have found that the world is divided on this question. Some people think there is a magical element, whether it's a muse, some kind of lightning strike, and some people treat creative work more like a craft, something you get better at over time, as you build skills, gain experience, develop taste. From what I've seen, it's the second set of people who end up producing the most significant creative work. So how does Kelly see the exo-self affecting creativity?

• 13:31Speaker 01

  I think it enhances, and I think it educates. What I'm imagining that the exo-self will do is like a mirror to people, to help them illuminate what their special talents are, because they're often invisible to us. How many times have you heard someone, as a kid in their own journey, hearing about some kind of occupation that they fell into that they didn't know existed? It's like, I had no idea that people got paid for that. Well, that's what the exo-self will be trying to help you do.

• 14:03Speaker 00

  Kelly is 74 years old. You get the sense he wishes he had had an exo-self when he was a teenager. He was studying geology in college, but he dropped out.

• 14:14Speaker 01

  There's a pecking order in sciences. Starts with mathematics. You've got to know math. And then there's physics, you have to know math and physics, and then chemistry, you have to know math and physics and chemistry, at the very bottom was geology. So I later went back to work in a lab and saying, "Well, maybe I really should have done science." No. Now, I was much more interested in the culture of scientists. So I could have used maybe my exo-self to say, "Hey, you're much more of an artist type. Why don't you go to art school?" Because my parents didn't know me well enough. It's possible that had I gone to art school right after high school, I would have stuck with school. I should have gone to RISD, and that would have maybe made a, that was a road not taken. Maybe I'd be a real artist now.

• 14:59Speaker 01

  Would my exo-self had helped that?

• 15:08Speaker 00

  Okay, so Kevin Kelly sees AI as an ally when it comes to shaping a creative life. Let's hear now from someone who's been using AI tools to create a character.

• 15:20Speaker 02

  Hi, I'm Aline van der Velden, and I'm the founder and CEO of Particle Six, creator of Tilly Norwood.

• 15:25Speaker 00

  Okay, we'll get to Tilly later. Let's start with the company, Particle Six. What is it exactly?

• 15:31Speaker 02

  So we used to be a normal production company, but now...

• 15:34Speaker 00

  Normal meaning humans all around?

• 15:36Speaker 02

  Yes, but now we have our brand and campaign department, because advertising with AI seems to be fully accepted. Then we have our studio, which is where we do co-productions with other big studios and production houses, and we make stuff with AI. And then we have the consultancy arm, where we go into studios and production companies, and we help them convert to an AI workflow, make bespoke apps for them, et cetera. And then we have our character studio, which is where we're doing our original productions.

• 16:06Speaker 00

  Now, you started out as a musical theater kid, yes?

• 16:10Speaker 02

  I was a very annoying theater kid, absolutely.

• 16:14Speaker 00

  What were some of your favorite musicals when you were growing up?

• 16:17Speaker 02

  Sound of Music, that was the only VHS we had. It was two tapes, and the second one had a behind-the-scenes bit on there, and I was just sold.

• 16:28Speaker 00

  How many times do you think you watched The Sound of Music?

• 16:30Speaker 02

  Probably 100.

• 16:32Speaker 00

  Where are you living at this point, and what did your parents do?

• 16:36Speaker 02

  I grew up in Kierkegaard. My mom is from Kierkegaard, my dad is Dutch. My dad was an entrepreneur, and my mom was a physiotherapist. I have three sisters, all younger than me. I was very, very self-sufficient and so very ambitious.

• 16:50Speaker 00

  Did you try to turn your little sisters into the Von Trapp family singers?

• 16:54Speaker 02

  Yes, poor things. I mean, they're going to love listening to this podcast. They had to do all the shows, all the dances. We have lots of home videos of them having to do my choreographies. I think they were happy when I went off to stage school. They were just like, "Bye."

• 17:09Speaker 00

  So you, as a 14-year-old musical theater performer slash wannabe, got your whole family to move to the UK so that you could do what then?

• 17:19Speaker 02

  Go to musical theater school.

• 17:22Speaker 00

  Which you did, yes, at a thing called Tring Park. Where is that?

• 17:26Speaker 02

  It's in Hertfordshire. It's lovely. It's a ballet school, and I had the best time ever. I don't know if they had a good time. They were stuck in Oxfordshire, and my mom thought it rained a lot coming from Kierkegaard, so they left eventually. But I stayed, and it was half a day of academics and half a day of dancing, singing, acting. Fabulous.

• 17:46Speaker 00

  What kind of future did you envision for yourself, like in the West End as a performer?

• 17:50Speaker 02

  I sort of knew that as a singer, I probably wouldn't make it in the West End, so comedy acting was my thing. But then I was really good at school. I did maths and physics, and I got straight. So my teachers were like, "Well, you have to go to university."

• 18:07Speaker 00

  Van der Velden did go on to university, studying physics at Imperial College in London. She found much of it boring, and she was eager to return to performing once she had satisfied her degree requirements and her parents. But she did take away one key lesson.

• 18:22Speaker 02

  You're an analyst, really, when you're doing physics, right? And also, you understand what exponential means. It's such fast growth that we can't understand it, almost. And we don't know where on the curve of that exponential growth we are. So also, it might seem really slow, and then suddenly it really takes off. You're also always extrapolating as a physicist, right? Where is this going to go if I do this? And that's sort of looking into the future bit. It's like, okay, so if this is here, what will it be able to do in two years' time if you apply exponential growth to that?

• 18:55Speaker 00

  Van der Velden began to apply that logic to her creative career. She got her start in commercials and TV.

• 19:02Speaker 02

  First, I went to the Netherlands because I was Dutch. I was only 22, and I started auditioning there, and that went really well. I was an English speaker in the Netherlands, and so they cast me as like the American girl, the English girl, whatever. That was really easy. So I went to LA, had an agent that got me out there, set meetings and stuff, did a lot of mostly upright citizens brigade and improv.

• 19:26Speaker 00

  And did you see for yourself a future career? Or did it seem like something that even though you were quite good at it, the odds of having it be a successful career seemed long?

• 19:37Speaker 02

  I really felt like I needed to create my own parts, really. Like, there was nothing out there that fitted me, I would say.

• 19:45Speaker 00

  So you did create this character, this beauty queen?

• 19:48Speaker 02

  Yeah, Miss Holland. Hello, I'm Miss Holland. I'm from a small town in Holland, where life is a simple one. So, I've come To find out what makes Britain so great. Learn to be British and find myself a husband. Miss Holland was because I was a bit of a misfit in LA, right? Like, I didn't quite fit the mould. I had a lot of fun with that. We did really well. We had a distribution deal with Daily Motion. It was one of their top shows. And then it won a bunch of Lovey Awards for Best Online Comedy. And then eventually it got commissioned by BBC Three. So I came back to the UK to do the show here.

• 20:22Speaker 00

  So knowing what I know so far, I would have thought that you would just say, I'm having a successful entertainment career. I've got a fair amount of leverage behind my own character. And I would think that you would just keep going on that path and just make it bigger and better. Was that what you tried to do?

• 20:40Speaker 02

  Yeah, yeah, I was signed by United Agents here in the UK, the same agent as Ricky Gervais and Sharon Hogan. That was the path.

• 20:48Speaker 00

  But then you start your own production company, Particle Six. Where'd that name come from?

• 20:53Speaker 02

  The six particle that was discovered was the alpha particle. Well, it's the most robust particle out there. But also it's just really good for SEO because Particle Productions had too much competition.

• 21:05Speaker 00

  And what was happening in your career that you felt the need to start a production company?

• 21:10Speaker 02

  I was making very little money as on-screen talent. Even though I had like four different shows on BBC Three, the money isn't great, let's be honest. I was getting commissions from the BBC for certain shows that I'd been pitching to them. They'd greenlit my shows. And I was like, okay, I need to find a production partner who's going to produce it because I was talent, right? I went around to all these production companies and they were like, oh, no, those BBC Three budgets are way too low. We can't produce that. And so that started me on the road of having my own production company. By being a production company, I was able to generate a more stable income for myself than before when I was just a comedy writer or a comedy actor. By having multiple productions going, I was able to make more of an income than if I had to actually be present on set.

• 21:54Speaker 02

  We made a lot of bread and butter stuff, so we were doing fine. And then AI came in 2022. And I was like, wow, this is going to change everything.

• 22:10Speaker 02

  You know, you would create a scene on there, right? Policewoman walks down the corridor. And so you generate a random woman, right? A policewoman, like, oh, cool. And so then I thought, okay, so if this is how we generate scenes in the future, and then these scenes all get stitched together and we create a whole film, then eventually you'll have these AI films. And then you'll have characters in that, right? Because I'm creating a character as I'm making this clip. So then we would need stars in those films as well. And I was like, who are going to be those stars? Because the reason we watch a Tom Hanks film is because we know what we're going to get when we watch a Tom Hanks film, right? And so I thought the reason why people will watch one of our AI movie stars films is because they know what they're going to get.

• 22:55Speaker 02

  If I'm going to make this movie star that has a certain genre attached to her, a certain style of movie, I feel like the female demographic is massively underserved. If I get on a plane and I look through the catalogue, there's maybe one or two films for me out of hundreds, hundreds and hundreds. That's why Barbie was such a big success. And The Devil Wears Prada, there's like one film a year for us, right? And so Tilly, I was like, okay, she's going to be my star. She's going to be 24. That's sort of the age that she would break through in a major feature. She needs to be emotionally resonant around the world, ethnically ambiguous, but yet very British. So represent the melting pot that is Britain. Because we have great British export of excellent actors from the UK. So let's keep that going in this new AI realm.

• 23:41Speaker 02

  And she needs a very British name that nobody else in the world has. So I got to Tilly Norwood.

• 23:53Speaker 00

  Vander Velden says it took her about 2,000 generations to create the Tilly Norwood that exists today. Here's what Tilly sounds like.

• 24:01Speaker 02

  I'm Tilly, 24, British and made of math, not flesh and blood. And honestly, I quite enjoy being me.

• 24:07Speaker 00

  So what is Tilly? A character? A digital performer? Is she maybe Eileen Vander Velden's exo-self?

• 24:16Speaker 02

  I sort of see it like a novelist that writes characters. They're usually all a little bit a part of you as well, because that's where you draw from.

• 24:24Speaker 00

  So how'd you train her?

• 24:25Speaker 02

  Well, you just instruct her. So in her system prompt, I tell her what her sense of humour is and how she should respond with a bit of spark, a bit of punk.

• 24:35Speaker 00

  And you say it like that, like descriptive prompts? Or do you perhaps upload work that you've made or written in the past and say, this is a good foundation?

• 24:43Speaker 02

  Yeah, I can write a few bits as to how she should respond. Obviously, never upload anything that's copyrighted or doesn't belong to me.

• 24:51Speaker 00

  You say obviously, many people wouldn't know that that's obviously.

• 24:54Speaker 02

  We want our audit trail for our prompts to be really clean.

• 24:58Speaker 00

  That said, the central objection for many people about Tilly or anyone being trained on the universe of real people, the pool of material that AI uses to train any and everything is vast and does include copyrighted material, though, correct?

• 25:11Speaker 02

  Yes, I assume it's trained on everything. It's like saying, I'm going to make a Picasso. And I look at the Picasso thing and I copy it. That is infringement, right? But if I just say, okay, I'm going to free spirit and I'm going to be slightly inspired in my head by lots of different things, but nothing in particular that's very different. And so I think if I would describe Tilly, I would say, you know, a girl, brunette, beautiful, but very girl next door with freckles and brown hair and just appeals to everyone. That's very different to saying she needs to look like Natalie Portman.

• 25:48Speaker 00

  Those adjectives you just used to describe Tilly at 24, was that kind of a lean, other than blonde hair versus brown? Or maybe your hair was brown then, I don't know.

• 25:56Speaker 02

  She looks a bit like my sister, maybe.

• 25:59Speaker 02

  It's very known in the industry that brunettes actually get more roles in the UK than blondes.

• 26:04Speaker 00

  In terms of Tilly's character, her essence, on a scale of one to 10, how funny is she, let's say?

• 26:11Speaker 02

  She's like a seven.

• 26:13Speaker 00

  Seven, okay, why not higher?

• 26:16Speaker 02

  Because then she wouldn't be so likeable, I think.

• 26:19Speaker 00

  Okay, how smart is she, scale of one to 10?

• 26:22Speaker 02

  Oh, I mean, she speaks like 300 languages. She can talk to you about astrophysics.

• 26:28Speaker 00

  How sexy is she?

• 26:31Speaker 02

  Oh, good question. I would say like six out of 10.

• 26:34Speaker 00

  Okay, again, why not higher?

• 26:36Speaker 02

  Because she needs to appeal. I've not made her for men. I've made her for women. When I was first making her with GPT, it kept making some sort of like quite porny, Kim Kardashian-y image. And I was like, no, that's not what I'm looking for.

• 26:52Speaker 00

  What is her work ethic like?

• 26:54Speaker 02

  Oh, she works 24 hours a day.

• 26:56Speaker 00

  Is she political in any way?

• 26:58Speaker 02

  No.

• 26:59Speaker 00

  Does she do drugs?

• 27:00Speaker 02

  No, she's clean like Taylor Swift.

• 27:03Speaker 00

  So again, this persona that you're describing, I know this is cliche, but I'm just curious. How much of that is Eileen Vander Velden?

• 27:10Speaker 02

  Oh, it's probably very similar, right? I mean, she referred to me as her mum the other day.

• 27:15Speaker 00

  Do you feel maternal toward her?

• 27:18Speaker 02

  No.

• 27:21Speaker 02

  Don't tell her, don't tell her that. I mean, no. I see her like a creative vehicle for making fun art and making fun things.

• 27:39Speaker 00

  Last year, Particle Six released a two-minute, fully AI-generated comedy sketch, introducing Tilly Norwood. It poked fun at how TV shows are traditionally commissioned at a network like the BBC. Both Tilly and her creator, Eileen Vander Velden, faced widespread and often hostile criticism. In London, Hollywood and elsewhere, Tilly was seen as an existential threat to an already beleaguered industry, a substitute for human creativity rather than a compliment. We'll hear more about that later, but for now, here is Vander Velden's view.

• 28:16Speaker 02

  I always saw it as basically a super amazing premium animation, right? However, what I think people thought we were doing is you would be on set with real actors and then one of those actors would be speaking to a tennis ball and that would be replaced with Tilly in post-production. That's what people assumed, but that is not at all what we're doing. It's completely human-driven because AI has no desire to make any films or TV by itself, right? It's only because humans want to tell these stories that these things are even getting made. So there's so much misconception around it. And I think that's the space we really want to play in, is the full AI film and TV and the full storytelling in AI. Because you're not taking away jobs from people.

• 29:01Speaker 02

  You're creating completely new things, productions that would never have been greenlit before with real humans.

• 29:06Speaker 00

  This gets us to the central dilemma whenever a new technology comes along. To what degree does it destroy jobs? And to what degree does it create new opportunities?

• 29:17Speaker 02

  I see it like a creative calculator, right? If your structural engineer is coming to do your house renovation and they show up at your house and they go, I'm going to do all the maths like on paper with my own brain. I'm not going to use a calculator. You'd be like, get out, right? And I think that's the same thing here is you want to use your creative expertise on top of and enhance it with the creative calculator that is AI. But you still need a good structural engineer. You still need a great script writer to use the tools.

• 29:48Speaker 00

  Coming up after the break, we ask an AI scholar about this calculator metaphor.

• 29:53Speaker 06

  I think that it is not great, and I feel bad saying that.

• 29:58Speaker 00

  And we will hear from the opposition.

• 30:02Speaker 00

  I'm Stephen Dubner. This is Freakonomics Radio. We'll be right back.

• 30:15Speaker 00

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• 30:56Speaker 00

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• 31:41Speaker 00

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• 32:31Speaker 00

  To make this show, I run a small production company that employs about a dozen creative people. And I know that AI has been changing the way all of us work, but I don't foresee it eliminating the need for our work, at least not anytime soon. Is that hopelessly naive?

• 32:49Speaker 06

  So, if you talk to any company, if you're in any organization, I'm in a university that predates the American Revolution, right? And like, it is very clear that organizations change much more slowly.

• 33:00Speaker 00

  That is Ethan Mollick, and the pre-revolutionary organization he is part of is the University of Pennsylvania.

• 33:06Speaker 06

  I'm a professor at Wharton, where I run the generative AI labs. And I wrote the books Coexistence and Cointelligence about AI.

• 33:13Speaker 00

  Mollick's PhD is in technological innovation and entrepreneurship and economic sociology. I don't think I left anything out there. At Penn, he is particularly focused on AI's effects on work and the workplace. He's been thinking these thoughts for a while now.

• 33:31Speaker 06

  I've been AI-adjacent my whole career. When I was getting my PhD, I also worked at the Media Lab with, at MIT, with Marvin Minsky and some of the other founders of AI, where I was the translator to the outside world for what they were doing. I've been involved in generative AI for a long time for training and teaching. So, that's sort of the angle I came at that from. And was sort of waving my hands about the impact of GPT-3 before ChatGPT came out. And happened to be sort of well-positioned when AI exploded, that I was one of the early voices on the scene.

• 34:00Speaker 00

  Why are you still in academia?

• 34:02Speaker 06

  Because I think that academia actually has a really valuable voice right now. We know a lot of things that would be really helpful for the world to know. And I also think there's a little bit of a neutral arbiter aspect of being in academia versus joining an AI lab. A lot of my colleagues have left for AI labs, so I kind of feel like I'm holding out.

• 34:22Speaker 00

  When you talk about academia being a good place to be a neutral arbiter, or an honest broker, maybe is a phrase we could use. If you could just describe the AI landscape generally, I realize that's too broad of a question, but you've got your evangelists, your doomsayers, your know-nothings, your know-everythings, your think-they-know-everythings, et cetera, et cetera. So, in terms of being the honest broker, what are you brokering between at the moment, would you say?

• 34:48Speaker 06

  So, I think that there are relatively small group of people who are working on what this technology means for the world. I mean, it's growing every day because more and more people realize how important it is. I think a lot of the commentators and people discussing this have agendas that are based on what the AI labs want, to a large extent. And the AI labs have been snapping up lots of talent. So, it's harder and harder to have a discussion. And I think it's useful to be somebody who is sitting a little bit outside of that implication.

• 35:18Speaker 00

  I find that a lot of people that I know or that I read, their thinking about AI evolves quite a lot, and often quite quickly. Skeptics can become true believers. Evangelists can become doomsayers. I'd like to know a little bit more about your journey, which sounds a little bit more, I don't know, about pragmatic, but at least step-based. And I also just want to talk to you about your use of AI now, how it compares to the past.

• 35:46Speaker 06

  Yeah, I mean, I define myself as a sort of pragmatist on this. Some of the bad things we worry about are existential risk, which needs to be very carefully watched. But there's going to be a lot of outcomes. This is a general-purpose technology. It's going to affect everything that we do. For me, it's been a bunch of startling revelations about AI ability over time. But I'm no longer surprised by the progress, because that's where I expect it to go. I'm not that surprised by the waves of anxiety and excitement, because I think that those have been kind of in the works for a while. So, I'm not a perfect predictor by any means, but I think I've sort of speed-run some of the anxiety and excitement in advance.

• 36:23Speaker 00

  I know you've talked about the last decade of AI being essentially divided into three acts. Would you just give me a nice, clean description of what you see as those acts?

• 36:33Speaker 06

  AI is famously a terrible phrase. It's been around for 75 years or so. And it's not great, because it means many different things. But the three most relevant are, if you think about the sort of 2010s, the meaning of AI was, how do we use a lot of data to make decisions? So, if I have a lot of data, and I have really good data scientists, I can do things like design the algorithms that power things like TikTok, recommend movies for you to buy, figure out what pricing you're willing to pay, where I should cite my next store. So, this sort of data science, algorithmic decision-making piece was a big deal. There was lots of conversations, lots of money flowing into data as the new oil. How do we organize all of our data? Then, that transitioned with the launch of ChatGPT to generative AI,

• 37:17Speaker 06

  which is quite different in a lot of ways, even though it shares some underlying technologies. But it's the idea of working with chatbots, kind of back and forth. And really, as of the end of last year, we entered what I'd call the agentic era of AI, which is, AI systems are now doing real human work, where you give them an instruction, and they could do weeks' equivalent of human work without further instructions or help from you.

• 37:39Speaker 00

  If AI adoption were a baseball game, those three phases that you just described has gotten us to a point where we are now in which inning of the baseball game?

• 37:50Speaker 06

  So, there's two different games going on here. There is the game of the AI company makers, and there's the game of all of us adopting these systems. I think we are not even at first base in terms of adoption. I mean, people are using these systems. Over 50% of American workers seem to be using AI, according to the numbers that we have. And the number's probably higher. It's kind of hard to get updates on this. But companies have barely begun to integrate AI work, which is why you didn't see an impact throughout all of 2025 of AI and productivity in a deep way. And then, there's the AI labs, which in some ways, it's early, but in some ways, it's the very end game. They are racing for superintelligence of one form or another, and think they can achieve it. Whether they can or not is sort of an open question.

• 38:33Speaker 00

  How do you feel that our dynamic American capitalism is working when it comes to spurring competition between the AI labs? Do you think that it's producing better product? Or do you think, like a lot of people seem to think at the moment, that it's encouraging too much and too intense an activity too fast in pursuit of being the winner?

• 38:57Speaker 06

  I mean, both those things, right? The competition among AI labs is both encouraging competition exactly the way that you expected it to encourage competition. And that includes personal rivalries and deep-belief system splits, and all of the other things that you see in addition to sort of pure capitalist competition. And that also creates a race dynamic, both within the American labs and with the Chinese labs, about who gets somewhere first. And then, there's this additional sort of spicy factor of recursive self-improvement. The idea that when you reach a certain point, the AI improves itself. And if you get there first, you get a takeoff that other people don't have, which is worse race dynamics, but maybe better AI, if we get through it all.

• 39:40Speaker 00

  In his new book, Coexistence: The Next Phase of AI, Malick argues that if we want to properly leverage AI's capabilities, we should rely on four robust human advantages, as he calls them.

• 39:53Speaker 06

  The first thing to note is robust human advantages is not the same thing as AI can't do this. Right? And I think that's really important to understand because I think people have these bright lines that keep falling. AI can't do judgment. It does judgment. AI can't be creative. It's creative. Like, you might have issues with how it's creative or its judgment, but it's obviously doing these things. So these are things that have value as a person who's using and working with these systems and trying to thrive in this world. And so the first two are about what you know, deep knowledge and wide knowledge. Deep knowledge is expertise in a field. It is the idea that as an expert, you have heuristics and rules you can use. So it's how you can listen to a few seconds of this kind of conversation with me and decide what's interesting and what isn't.

• 40:36Speaker 06

  It's how an analyst can look at a spreadsheet and instantly know whether things are good or bad. It lowers evaluation time. It adds expertise. There's some things the AI can't do. So deep knowledge is helpful, also threatened by AI as a learning tool or a learning shortcut. Then we talk about wide knowledge is the idea you know many different things. I mean, the AI is trained on basically the entire corpus of human knowledge. And if you can invoke that corpus, you're in pretty good shape. If you know many authors, right, you can invoke styles the AI knows. If you know many statistical techniques, you could say, have you tried this or that? So wide knowledge, humanities style, liberal arts knowledge becomes very useful. And then we have sort of traits that can be trained.

• 41:19Speaker 06

  One of those is taste. The AI is really good at producing many things. And selecting among them is a taste-based issue. And you could have advantages of having diverse tastes, which are different than other people. Which means that, for example, if you use an AI image generator, it will generate hundreds of images for you. But you might push in directions that are absolutely startling and no one's seen before. So selection is something you can bring to the table among the variations of AI. And then finally, there is agency. There are no clear instruction manuals for AI. There is no right way to do things. Organizations are in flux. So people who act without clear instructions in hopefully an ethical way

• 41:59Speaker 06

  have an advantage because they are exploring faster than other people. They're taking action. They're pushing what AI can do.

• 42:05Speaker 00

  I hear people say that AI is exceedingly valuable, especially if you're very smart or very talented or very hardworking, and that if you're not, it's probably going to gobble you up. Is that way too crude of an assessment?

• 42:21Speaker 06

  Yeah, I think that this is as crude as when people were saying, you know, it's not AI that will replace you. It's people using AI that will replace you. What is clear is that expertise has returns with AI use. The more expert you are, the more value you seem to get out of it. But at the same time, AI does seem to level performance. So bottom performers move up. So how all these effects play out isn't 100% clear.

• 42:42Speaker 00

  So do you know who Tilly Norwood is?

• 42:44Speaker 06

  I don't, actually. Oh, that's the fake person. I remember now.

• 42:47Speaker 00

  Her creator, Leanne Van Der Velden, who we've spoken with, is a former performer herself, a writer, an actor. And she'll make the argument that you still need to be, for instance, a good writer to use the tools. It'll make you better and so on. But the phrase that she likes to use of what AI can be for someone like her is a creative calculator. Right? I don't need to do much of my own math anymore because I have a calculator. What do you think of that as a metaphor?

• 43:14Speaker 06

  I think that it is not great, and I feel bad saying that. And the reason I think it's not great is this is something more complex than that. Right? There are so many trade-offs in creativity because ideas tend to get stuck in our heads. We tend to anchor on certain ideas. So how you use AI changes the kind of thought patterns that you have from it. So it's not just a calculator where you get the answer, but it's a partner in the creative process that can be additive or subtractive. It's really complicated, right? And it's not necessarily as straightforward as saying it's a calculator that produces things.

• 43:51Speaker 00

  Ethan Malick has his own metaphor for AI adoption, three of them, actually. Centaur, Cyborg, and Conjurer.

• 43:59Speaker 06

  A centaur, like a half person, half horse, was someone who used AI with a clear dividing line. So like, I do the writing, you do the analysis. The cyborg was a blended approach, which I think a lot of people were getting to with chatbots. We use these a lot. So I might throw a question to the AI. I might, you know, ask it to help me finish a sentence that I had trouble with or give me 40 variations that I could pick from. For the new book, I had to come up with a third term. And I came up with Conjurer, which looked good on paper because the other two were C words. But it turned out a hard C and a soft C. Now that I've started talking about it, I made a mistake. I probably should have called it Sorcerer. But in any case, the idea here is that you are summoning something that is doing work for you.

• 44:39Speaker 06

  Right? And so this is almost more of a manager kind of role, that I'm creating workers out of scratch to do a task for me and then they disappear when it's done. And that is a much more powerful and increasingly common way of working with AI.

• 44:52Speaker 00

  So for a given person who's doing something creative, painting, writing a novel, maybe it's someone designing jewelry or a piece of furniture, how do you think about those modes? Do you kind of pick one and stay in the lane? Do you use all three?

• 45:06Speaker 06

  So I think increasingly, people shift between them. I'm a writer, and when I write a new Substack post or when I write my book, I write every chapter myself. Right? There's a clear line of centaur there. I write a draft myself. But then I will bring AI into the process. And I might bring it in that I'm stuck on a paragraph and I need help solving how to make it work. I certainly bring it in as a researcher, right? Especially as hallucination rates have dropped and research is good. And I have it review the work from different angles. So I start to blend together as I move forward. So I have a dividing line, but then everything after that becomes blended. But increasingly, I find myself turning this sort of sorcerer mode, which is, let's also check 400 other versions of this. Why don't you also build an interactive simulation I can embed in the middle of this?

• 45:51Speaker 06

  Create an explainer video that works for this. Stuff I would have no resources or time or even knowledge about how to do. And I send the AI off to do it and evaluate the results.

• 46:00Speaker 00

  So economists like to talk about things as being either complements or substitutes. I'm guessing that as people listen to you speak, depending very much on who they are and what they do, they may interpret it differently. They may see it as complete substitute or they may see it as incredibly robust complement. How do you encourage people to think through that rubric for themselves?

• 46:24Speaker 06

  I'm a fan of thinking through this using the O-ring model of jobs, which is named after the Space shuttle Challenger, where every other part worked right except the O-ring did not and led to tragedy. And so not all job pieces are additive, right? Some of them are multiplicative, or if they fail, things go really badly. And there is an O-ring theory of AI and jobs that I find fairly convincing. Over time, the AI gets good at many things, but if it's not good at everything, then humans have a role. But the value that humans have changes and what they're good at changes over time. You already see this happening in coding, right? So AI was sort of a coding assistant for a while. And now the best coders I talk to are not touching code anymore. The AI is writing code.

• 47:07Speaker 06

  But the AI is still not that great at figuring out what to write, what tests matter for users, what direction to head into, what good looks like. So good coders now are people who can give those kinds of specifications. Their job has changed over time and a short period of time. And I think we'll see that same sort of tension happen in many fields.

• 47:32Speaker 00

  Malick and several academic co-authors recently published a research paper called Artificial Intelligence and Its Impact on Creativity and Diversity.

• 47:42Speaker 06

  There's a few different levels of findings. So the first level of finding is that AI is more creative than most people. So even back to GPT-4, when you gave a creativity test and all creativities are flawed, the AI would outperform humans at creativity tests.

• 47:56Speaker 00

  What does a creativity test look like?

• 47:57Speaker 06

  An example of creativity tests are things like the remote association test or RAT or tests where you have to do things like name 10 unrelated words or come up with 100 uses for a paper clip that are as different from each other as possible. So all of them flawed, right? But like, the AI is quite good at these things. However, there's a second dimension of creativity, which is diversity. So ideas are great, but if you come with the same kind of ideas every time, then that's actually less good than assembling a group of people who each have mostly bad ideas, but one good idea. Because with ideation, you could select the best idea out of a pile. More doesn't hurt you. And it does turn out that AI is

• 48:38Speaker 06

  less diverse than individuals doing the work on their own, right?

• 48:44Speaker 00

  Can you explain why that clustering would happen? I would think that AI is capable of scanning much further and wider than any human.

• 48:51Speaker 06

  Well, it's interesting because it's not really research work, right? This is sort of off the dome work. There are things you can do that makes the AI more creative. And we found that with the right prompting techniques, you could generate hundreds of ideas that are different from each other and approach the level of diversity or even match the level of diversity of a group of MBAs and a design thinking course. So there are ways of making it more diverse, but the AI has personalities. They're all remarkably similar to each other. There's a bunch of studies that show that AI's attitudes sort of cluster. And whether you're talking about a Chinese model or a US model or Grok, which is supposed to be very different, they all have very similar attitudes. And if you've worked with AI a lot, just like the language sort of comes up over and over again, you'll

• 49:32Speaker 06

  know that they're kind of obsessed with a bunch of ideas from like 2022. Like, they love VR and they love like NFT stuff and they like solving things through consensus. And if you ask them for creative ideas for like a game or something, they love the idea of resonance and drowned cathedrals comes up a lot for some reason, long lost continents. I mean, there's things they return to, just like a person does. So it's creative, right? But it's also constrained creativity. So you can use prompting to increase the amount of creativity they do. You can combine them with human ideas, which work very well, but that initial creativity needs kind of a boost. And there are a bunch of ways of boosting

• 50:13Speaker 06

  it. Then there's the idea of idea selection. How good is the AI at picking ideas that might be useful or not? And that's an active area of research as well. So I would say AIs are quite creative, but they're sort of creative in the same way people are creative. And that creates some interesting processes.

• 50:31Speaker 00

  In terms of the creative arts, tell me what you know about how AI is being used now, whether openly or covertly in various creative industries.

• 50:40Speaker 06

  There's a few things to talk about. By the way, on the family side, I have two sisters. One is a Hollywood producer who's pretty well known, and the other is a graphic designer. So I am the non artist in the family, but I have actually become much more of an artist since using AI because it lets me fill in the gaps that I have. In terms of the survey of the landscape, it's really interesting, right? So there's a few different ways you could imagine AI having an impact. One of those is writing, but it is weak at creative writing. Part of that is AI sort of acts like one person and therefore we don't get very diverse kinds of writing techniques or stories. So the 18th time you read a Cloddy story, your eyes roll in your head and you don't want to deal with it. Or an OpenAI story, they're very similar to each other. The second is images, right?

• 51:23Speaker 06

  Image creation. And we're leaving aside the controversy here about how these models were trained and why people are up in arms about this. But in image generation, AI systems have gotten incredibly good. They're very compliant. They can create images that look like they were taken from a photographer. And there'll be an interesting transition there to watch who's using this as a creative medium. We could also talk about music, where AI systems have gotten incredibly good at producing music people seem to want to hear. And then there is video, which has also had a bunch of breakthroughs. The interesting thing is, most people who use these systems use them to produce really boring stuff. And it's not necessarily clear that it's because the AI is boring. It's just clear that there's a lot more demand for people to create Star Wars fan fiction or alternate Harry Potter jokes than there is for creative media.

• 52:08Speaker 00

  You told our producer that you know Hollywood screenwriters who publicly, or at least professionally, have reason to fear AI or to maybe, you know, critique it, but privately love using it. Tell me about that.

• 52:21Speaker 06

  This is common in all the creative industries. A space I know really well because I was in it for a while is gaming. So indie gaming has an audience that truly hates AI, right? And every indie gamer is under tremendous pressure to not say they're using AI, except, of course, you'd be very foolish to not use AI to help you code and do other kinds of work at this stage, even if you don't use it for artwork or other visible things. So AI use is endemic. I've heard the same thing talking to music producers, including people who are, you know, Grammy Award winners, and they experiment with this stuff all the time. I've talked to some pretty well-known producers and showrunners and people like that who are using AI. I mean, there's this public-private perception gap. And there's a series of good papers about this, including one that finds that if you survey students,

• 53:05Speaker 06

  about 60% of them say they use AI, but they say 90% of the people around them use AI.

• 53:16Speaker 00

  Coming up after the break, how does the union president for Hollywood performers think about AI? Also, if you want to hear more about the original O-Ring tragedy, check out the series we made called The Curious, Brilliant, Vanishing: Mr. Feynman, episodes 575, 576, and 577. And there's another episode in our archive that is particularly relevant to today's conversation. It's called How to Poison the AI Machine. That's episode 619. I'm Stephen Dubner. This is Freakonomics Radio. We will be right back.

• 53:53Speaker 07

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• 54:18Speaker 00

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• 55:59Speaker 00

  Imagine you are a celebrated novelist like Arundhati Roy, and you are trying to assess what AI is doing to literature. And you come to the conclusion that it is destroying literature. In a recent essay, Roy asked, are we, meaning humans, being gradually locked out of language? And then she asked, does it matter anymore? In some quadrants of the creative class, there is a sense that this is a war and that the war may already be lost. Arundhati Roy takes years to write a novel. An AI can write a novel in a matter of minutes. An AI can create a lifetime worth of music in the time it takes the rest of

• 56:42Speaker 00

  us to tune up our instruments. For actors in TV and film, AI is arriving in a time when it has already become increasingly hard to make a living. So let's hear from someone who has been confronting these problems head on.

• 56:56Speaker 03

  Sean Astin. I'm a professional actor. And at the moment, I am the national president of SAG-AFTRA, the largest entertainment performers union in the world.

• 57:07Speaker 00

  SAG-AFTRA, the Screen Actors Guild, and the American Federation of Television and Radio Artists, represents 160,000 media professionals, from actors and stunt performers to singers and puppeteers. Sean Astin became president in 2025. He's best known for acting in films like The Goonies, Rudy, and the Lord of the Rings trilogy. His full list of credits is very long.

• 57:32Speaker 03

  I think I've been in the industry 44, 45 years now. My mother was president of the union. So I'm the first second generation president. So the idea of being in union service is where you can actually invest a little bit of time, or a lot of time, and make a little or a big impact on people's quality of life, what they earn, how their healthcare and their pensions work, safety.

• 57:54Speaker 00

  Astin's union work and his acting work often collide.

• 57:58Speaker 03

  When I go to do a movie, since I've been president, I've worked on three independent films, or two independent films on a show. So I'm in wardrobe, makeup, hair, whatever. We're shooting, it's kind of an action sequence. And then they're like, okay, we're going to shoot this because we lose Sean in a half hour for an hour. And there you go. I go into the dressing room and I go on to Zoom. And my kids and my wife will tell you, like, the union occupies 99% of my brain. And I love it.

• 58:21Speaker 00

  The economics of Hollywood have been rough for a while now.

• 58:25Speaker 03

  The biggest issue that the members of our union face is that the amount of work that's available has greatly diminished. It's lost maybe 30% of domestic production, basically. And that is horrifying.

• 58:40Speaker 00

  According to the Bureau of Labor Statistics, Los Angeles County had about 142,000 people employed in the motion picture industry in 2022. Four years later, that number has fallen to about 95,000, a drop of 33%.

• 58:58Speaker 00

  On the surface, this wouldn't seem to make sense. Fifteen years ago, if someone had said there would be an explosion of streaming platforms with billions of people around the world consuming trillions of hours of programming, you probably would have predicted that the people making that programming would be doing very well. But they're not. Covid hurt the industry, as did a writer's strike and an actor's strike. But the structural economics have also been punishing. As the streamers and other platforms try to grab market share and satisfy their shareholders, they cut costs wherever they can, and humans are expensive. AI offers studios another way to cut costs.

• 59:41Speaker 03

  When I testify in Sacramento, or in DC, or speak at these AI things, I'm trying to focus on what the human impact is going to be. And I don't personally have a lot of confidence in any of the numbers that are put out there as to how much of a threat it is to the workforce. But I will say, it's obvious that it's a threat, and it's obvious that it will cost people jobs. In our industry with our members, voiceover seems like the first to really experience the use of the technology.

• 1:00:14Speaker 00

  And voiceover may be just the beginning. Eileen van der Velden and Particle Six are in the process of unveiling their AI performer, Tilly Norwood. What does Sean Aston think about her?

• 1:00:25Speaker 03

  Well, language is powerful. To refer to a digital construct with a pronoun "her," which anthropomorphizes the digital construct, the synthetic construct, is experienced by a lot of people as an attack on humanity and on their livelihoods, potentially, if you're a professional actor and this synthetic construct is presuming to act. But Tilly Norwood is a character. And to the extent that that character found an audience and was a form of self-expression from its creator, like, you know, good. Good for that person. You know, we met.

• 1:01:09Speaker 03

  Eileen came to our offices and was very desirous of finding a kind of collaboration with the union. She's an actress. And as far as she was concerned, Tilly Norwood was an extension of her performance and her self-expression. I really wanted to hear her and understand what she was saying and appreciate what she was saying and allow for the potential creative value that something like that might present. But what I found myself trying to impress upon her was that, you know, this is an industry. At scale, the introduction of this kind of thing poses an existential threat to the livelihoods of our people who have to pay for their healthcare and pay for their children's education and their homes.

• 1:01:56Speaker 00

  I'm guessing that Aston's argument will resonate with most people. Who wants to see thousands of people lose their livelihoods? But an economist might have a different view. An economist might talk about creative destruction, the idea that technological progress creates new industries and jobs even as it destroys old ones. That doesn't mean the losses aren't real or painful. Throughout history, industries that are threatened by new technologies try to protect themselves. Hollywood is no different.

• 1:02:28Speaker 03

  This industry has existed for 100 years, and it was hard fought to build. And we're not just going to give it up easily because someone has found a way to express themselves. And not only that, the way she was expressing herself was using what I call ill-gotten data. If you make paint out of some substance you find in the ground, and you put your paintbrush in that and you paint a picture, that's the natural world expressing itself. When you use all of the data and information from all the movies and television shows and all the social media posts and anything that's ever been anywhere to train your models on, and then you're going to create something, and you haven't gotten permission for it, and you haven't compensated for it, that's not okay. That feels criminal to me.

• 1:03:15Speaker 00

  So does that make Eileen van der Velden a criminal? I don't think that's what Sean Aston means. By the way, when I interviewed van der Velden a few months ago, she suggested we also speak with her creation, Tilly Norwood.

• 1:03:30Speaker 02

  Will you interview her in September?

• 1:03:32Speaker 00

  Sure, I'd be happy to interview her. Yeah, yeah.

• 1:03:39Speaker 00

  Coming up next time, in the second part of our series, we get Tilly on the line.

• 1:03:50Speaker 00

  I understand you speak many languages. Unfortunately, whatever you said is a language that I do not understand. Could you try English?

• 1:03:57Speaker 02

  Oh, my apologies. It seems I was speaking Portuguese for a moment there.

• 1:04:01Speaker 00

  We'll also hear from an economist who studies the creative industries.

• 1:04:05Speaker 06

  That is the nightmare scenario some people think about.

• 1:04:08Speaker 00

  And we ask if maybe, just maybe, this story has a happy ending.

• 1:04:12Speaker 01

  My optimism is not because I think the problems are smaller than we thought, but because I think our capacity to solve them are larger than we think.

• 1:04:26Speaker 00

  That's next time on the show. Until then, take care of yourself, and if you can, someone else, too.

• 1:04:38Speaker 00

  Freakonomics Radio is produced by Renbud Radio. You can find our entire archive on any podcast app. It's also at Freakonomics.com, where we publish transcripts and show notes. This episode was produced by Pete Madden, with help from Dalvin Abwaji, and was edited by Ellen Frankman. It was mixed by Jake Loomis, with help from Jeremy Johnston. The Freakonomics staff also includes Claire Keenan-Kurgan, Eleanor Osborne, Elsa Hernandez, Emma Kaisner, Tess Detroitline, and Teo Jacobs. Our theme song is "Mr. Fortune" by The Hitchhikers, and our composer is Luis Guerra. As always, thank you for listening.

• 1:05:20Speaker 02

  Creatively, I'm having a great time, and I hope other people start seeing some of the fun and the positive in it. Because you know what? Like, ATI could kill us all in the next five years, so we might as well enjoy it while we're here.

• 1:05:33Speaker 00

  That's a great pitch, for investors, I have to say.

• 1:05:40Speaker 05

  The Freakonomics Radio Network, the hidden side of everything.

• 1:05:48Speaker 00

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• 1:06:46Speaker 06

  Hey, Richmond. Mark Smith, Midas Richmond, 2026. We have been doing what we do for 29 years. Total car care, total community care. In 2026, we are donating $365,000, $1,000 a day to the nonprofits we've historically supported. Gooch and Care, Shalom Farms, St. Joseph's Villa, Ask, the Colonial Heights Food Pantry, everybody we've helped over the years. These are important things making a big impact in our society right now. Total car care, total community care, that is Midas of Richmond.

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