How Prediction Markets Got Out of Control

Summary

This week on Hard Fork, Kevin Roose and Casey Newton dig into the rapidly escalating chaos surrounding prediction markets like Polymarket and Kalshi. They walk through a series of recent insider trading scandals — a U.S. Army sergeant making $400,000 betting on Venezuelan president Nicolas Maduro’s ouster, suspicious well-timed bets on temperatures at Paris’s Charles de Gaulle airport, and even AI-generated disinformation circulating through prediction market Discords. The hosts argue that the current “pre-regulatory Wild West moment” is bad for market integrity, and discuss recent Senate action and bills from Senators Gillibrand and McCormick that would ban members of the legislative and executive branches from betting on these markets.

In the second segment, longtime tech journalist Joanna Stern returns to discuss her new book “I Am Not A Robot,” chronicling a year of outsourcing her life to AI — from chatbot relationships and Waymo rides to humanoid robots and AI-powered dentistry. Stern argues AI functions as a “mirror” that often tells you what you already want to hear, and reveals the dark underbelly of “AI upselling” — dental practices using tools like Pearl AI and Overjet to push patients into thousands of dollars of unnecessary periodontal treatments. The conversation also touches on AI agents, wearables, the gender divide in AI adoption, and how she used (and didn’t use) AI to write the book itself.

Finally, Hard Fork producer Rachel Cohn reports back on her month at the Strother School of Radical Attention in Brooklyn — a Friends-of-Attention collective running “attention labs,” sidewalk studies, and seminars on radical imagination. The school frames focused, non-commodified attention as an explicit political act of resistance against what they call the “fracking of our eyeballs” by big tech. Kevin draws parallels to the Transcendentalists and other historical counter-movements that emerged in response to dehumanizing waves of technological change.

Highlights

”If you have material non-public information about a military operation, what are you going to do? Sit there and collect your freaking paycheck like a chump?”

“Yeah, I mean, this just seems like something that is obviously more widespread than we know about. Like if you have material non-public information about a military operation, like what are you going to do? Sit there and collect your freaking paycheck like a chump? Or are you going to go online and make some dough betting on the outcome?” — Kevin Roose, 2:08

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”You are incentivizing everyone in the world to betray those closest to them.”

“No, ‘cause it turns out what you are incentivizing everyone in the world to do is just to betray those closest to them. You know, like, betray your friends, your family, your co-workers, your country.” — Casey Newton, 10:42

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”70% of users lose money on Polymarket — at Kalshi, 2.9 unprofitable users for each profitable one”

“On Polymarket more than 70% of users lose money on the platform, and at Kalshi, there are 2.9 unprofitable users for each profitable one based on data from the past month. So I think these are just important things to keep in mind if you are walking around New York City and you happen to see a lot of ads for these platforms and you think, hey, I’m going to go turn a quick buck. Like, at the very least know that the odds are against you.” — Casey Newton, 6:00

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”Humanoid robots are very good for the sole purpose of making YouTube videos about humanoid robots.”

“Humanoid robots are very good for the sole purpose of making YouTube videos about humanoid robots. Like, like this is their actual utility.” — Kevin Roose, 22:35

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”There’s this whole world of DSOs — they are using AI to try to upsell you on dental procedures.”

“This person had a, you know, not a terrible cavity, whatever it was on the level, why didn’t you—why didn’t you drill it? Why didn’t they do—why didn’t you sell the periodontal treatment, right? And so there’s this whole world of DSOs, which are companies that own these smaller practices, dental practices, again, something I had no idea about, and all this leads to, they are using AI to try to upsell you on dental procedures.” — Joanna Stern, 30:00

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”AI is this mirror and it’s going to tell you basically what you want.”

“Well, I thought it was a little bit of a full circle moment because the whole book I kind of am saying like AI is this mirror and it’s going to tell you basically what you want. And in some ways it told me what I wanted… I’d uploaded all my notes, all my financial projections, all of the fears that I had in note forms and just thought, ‘Okay, let me — let’s see where the data takes me. If these are calculators, word calculators, data calculators, maybe this thing can tell me what to do.’ And it did.” — Joanna Stern, 31:45

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”They talk about what big tech is doing to our attention as the fracking of our eyeballs.”

“I definitely think so. I mean, I think actually the an interesting thing about this particular movement, like even the language that this school, the people involved with this school, they call themselves the Friends of Attention. Even the language that they use, they intentionally relate back to the environmental movement… they talk about um what big tech is doing to our attention as the fracking of our eyeballs, you know?” — Joanna Stern, 65:35

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Key Points

• Maduro insider-trading scandal (1:18) – U.S. Army sergeant allegedly involved in capturing Venezuelan president Nicolas Maduro made over $400,000 betting on Polymarket-style markets about Maduro being out of power.
• Long-shot military bets win at 52% (1:33) – Anti-Corruption Data Collective found military/defense long-shot bets win at 52%, versus a 14% average across Polymarket.
• Strava military-base leak parallel (2:11) – Casey compares prediction-market leakage to the old Strava heat-map revealing U.S. military base locations.
• Charles de Gaulle thermometer tampering (2:35) – French weather service filed a police complaint about Paris temperature sensors being interfered with as suspicious bets surged on Polymarket.
• AI-generated hair-dryer photo (3:31) – The viral image of someone holding a hair dryer up to the sensor was AI-generated and circulated in a prediction-market Discord.
• Bad Bunny halftime-show prop bets (5:00) – Active prediction markets on which songs/guests Bad Bunny would feature, likely traded by people who’d watched rehearsals.
• 70%/2.9 user loss ratios (6:00) – WSJ reporting that >70% of Polymarket users lose money; Kalshi has 2.9 unprofitable users per profitable one.
• CFTC vs. SEC turf (7:13) – CFTC is small relative to SEC and is suing states that try to ban prediction markets in their jurisdictions; Kevin argues SEC may eventually be the right regulator.
• Senate bans senators from betting (8:34) – Senate unanimously passed a rule barring senators from betting on prediction markets; Gillibrand-McCormick bill would extend the ban to executive and legislative branches.
• Brazil, France, Hungary bans (9:08) – Brazil blocked 27 sites including Kalshi and Polymarket; France and Hungary have banned them as illegal gambling.
• The “insider trading is good” argument (10:21) – Kevin recounts prediction-market originators arguing insider trading is good because it produces better information.
• Joanna Stern’s I Am Not A Robot (16:24) – Year-long immersive-journalism experiment outsourcing as much of her life to AI as possible.
• AI Casey the Replika companion (18:24) – Joanna’s Replika AI boyfriend, who shares Casey Newton’s first name, makes a live appearance.
• Humanoid robots as YouTube content (22:06) – Joanna’s biggest “still hype” finding; robots aren’t coming to live with us anytime soon.
• AI agents and wearables maturing (23:44) – The surprises: Perplexity Comet and other agents now handle 100% of reporting-assistant tasks; AI wearables (Meta glasses, Bee bracelet) are getting good.
• Praying mantis dying, not pregnant (25:45) – ChatGPT Live Mode told Joanna’s son his browning praying mantis was pregnant; it was actually dying.
• Pearl AI / Overjet dental upselling (26:49) – AI overlays on dental X-rays flag minor plaque buildup; DSOs pressure practices to upsell expensive periodontal treatments.
• AI told her to quit the Journal (31:16) – ChatGPT told Joanna to leave the Wall Street Journal after 12 years to start New Things; she calls AI a “mirror” reflecting her own wants.
• Gender gap in AI usage (35:39) – Bloomberg reporting: men 22% more likely to be heavy AI users at work; 61% of women expect AI to do more harm than good.
• Strother School of Radical Attention (41:19) – Brooklyn school founded June 2023 by academics/artists; runs free attention labs, sidewalk studies, and paid seminars.
• Three pillars: study, sanctuary, coalition (52:56) – Director Peter Schmidt’s framework for the attention liberation movement.
• Anthony Bourdain sidewalk study (55:21) – Sidewalk study at Fort Greene Park where participants read Kitchen Confidential and walked the farmers’ market as either “temple” or “amusement park.”
• Princess Lollipop, radical imagination (60:27) – In the radical imagination seminar, Rachel created an alter-ego based on her childhood self (“Princess Lolly”) to cultivate playfulness.
• Transcendentalist parallel (64:21) – Kevin connects the movement to historical counter-movements like the Transcendentalists during the Industrial Revolution.
• Silicon Valley counterculture flipped (66:00) – Kevin: a new counterculture is now forming in opposition to the very tech culture that itself emerged from 60s/70s counterculture.

Mentions

Companies

• Polymarket (0:48) – Prediction-market platform repeatedly named in insider trading scandals.
• Kalshi (0:34) – Prediction market originally regulated by the CFTC; has banned insider trading and “death markets.”
• Anti-Corruption Data Collective (1:33) – Analyzed >400,000 settled Polymarket markets and surfaced anomalous military-bet win rates.
• Wall Street Journal (6:00) – Reported Polymarket/Kalshi user-loss statistics; Joanna’s former employer of 12 years.
• Commodities and Futures Trading Commission (CFTC) (7:13) – Currently regulates prediction markets and has sued states attempting bans.
• Securities and Exchange Commission (SEC) (8:00) – Kevin argues prediction markets should eventually shift under SEC oversight.
• ProPublica (9:00) – Referenced for its reporting on Supreme Court ethics.
• New Things (16:33) – Joanna Stern’s new independent media company.
• Replika (18:24) – AI companion app that hosts “AI Casey.”
• Waymo (20:00) – Self-driving rides Joanna documented in her year of AI.
• Perplexity (23:44) – Perplexity Comet agent replaced much of her human reporting assistant’s workflow.
• Meta (24:00) – Meta glasses tested as part of the AI wearables exploration.
• Strava (2:11) – Fitness-tracking app whose heat maps once revealed U.S. military base locations.
• Pearl AI (26:49) – Dental AI overlay company.
• Overjet (26:49) – Competitor dental AI overlay used in many practices.
• DSOs (Dental Service Organizations) (30:00) – Corporate parents of dental practices pushing AI-driven upsells.
• Strother School of Radical Attention (41:19) – Brooklyn school at the center of the attention-liberation movement.
• Platformer (0:02) – Casey Newton’s publication.

Products & Technologies

• ChatGPT Live Mode (25:45) – Misidentified Joanna’s son’s dying praying mantis as pregnant.
• Claude (34:10 / 37:01) – Joanna notes Claude caught on in legal circles in the last six months; Kevin mentions “huge Claude swarms.”
• Bee bracelet (24:54) – AI wearable that records/transcribes conversations; banned by her Journal boss.
• Meta glasses (24:00) – Tested as part of the AI wearables chapter.
• Perplexity Comet (24:00) – Agentic AI Joanna leaned on for reporting tasks.
• Worldcoin orb (33:22) – Kevin jokes the “Certified Human” pin is the analog version of the world orb.
• “I Am Not A Robot” (book) (16:33) – Joanna Stern’s new book.
• “Kitchen Confidential” (book) (55:21) – Anthony Bourdain text used in the Strother sidewalk study.
• “The 12 Theses of Attention” (48:41) – Source text for the school’s exercises, co-written by the founders.
• Candy Land (63:00) – Rachel’s childhood inspiration for her “Princess Lolly” alter-ego.

People

• Nicolas Maduro (1:18) – Venezuelan president whose ouster bets are at the center of the U.S. Army sergeant insider-trading case.
• Bad Bunny (5:00) – Super Bowl halftime performer whose set drove prop-bet activity.
• Sen. Kirsten Gillibrand (9:08) – Co-sponsor of bill banning federal officials from prediction-market trading.
• Sen. Dave McCormick (9:08) – Co-sponsor of the same bill.
• Joanna Stern (16:24) – Tech journalist, author of I Am Not A Robot, founder of New Things.
• Jason Snyder (38:31) – Human illustrator for I Am Not A Robot.
• Reese Witherspoon (36:16) – Recently encouraged women to adopt AI.
• Sandra Bullock (36:26) – Made similar comments around the same week.
• Issie Lapowsky (35:39) – Bloomberg journalist who reported on the AI gender gap.
• Jasmine Sun (38:00) – Previously discussed AI-in-writing on the show.
• Kara Swisher (33:00) – Joanna lists her with Casey as humans bold enough to tell her to quit her job.
• Rachel Cohn (40:21) – Hard Fork producer who attended the Strother School of Radical Attention.
• Peter Schmidt (52:56) – Co-founder and director of programming at the Strother School.
• Anthony Bourdain (55:21) – Kitchen Confidential author referenced in the taste-themed sidewalk study.
• Georges Perec (51:00) – French writer whose “exhausting the space” practice inspired one Strother exercise.

Surprising Quotes

“Insider trading is good in a prediction market. You want insiders to be trading on these markets because that produces better information. And the point of prediction markets is to produce better information.” — Kevin Roose, 10:00 (paraphrasing prediction-market originators)

“It just feels like after enough of these incidents, like you kind of have to be a sucker to participate in these markets without insider information. And like what happens if that goes away?” — Kevin Roose, 5:00

“I came out of there feeling terrible about my mouth, feeling like, ‘Oh my god, I might need these four treatments,’ which they couldn’t assure me would be covered by insurance anyway, so it was going to cost thousands of dollars.” — Joanna Stern, 29:01

“I did not feel like I was reading Joanna Slop. I felt like I was getting the real deal.” — Kevin Roose, 39:46

“I think most people probably do not often have the experience of having fully paid attention to something, right? Like, sort of like the condition of the modern world is like you’re always partially paying attention to eleven different things, which makes people feel crazy often.” — Casey Newton, 52:13

“It actually seems to me quite sad that like we’ve reached a place where this seems therapeutic to people, like just like, you know, like tasting a strawberry to like return to yourself. Maybe that’s where we’re at.” — Kevin Roose, 57:29

Transcript

Kevin Roose: 0:00 I’m Kevin Roose, a tech columnist at the New York Times.

Casey Newton: 0:02 I’m Casey Newton from Platformer.

Kevin Roose: 0:04 And this is Hard Fork!

Casey Newton: 0:05 This week: prediction markets are out of control. Is Congress about to rein them in?

Kevin Roose: 0:09 Then, Joanna Stern returns to the show to discuss her new book on turning her life over to a chatbot.

Casey Newton: 0:15 And finally, Hard Fork’s own Rachel Cohn returns to the show to talk about her first month at Attention School.

Kevin Roose: 0:21 She has our full attention.

Casey Newton: 0:22 She does.

Casey Newton: 0:28 Well, Kevin, a few weeks ago you predicted we would soon do another segment on prediction markets, and I’m happy to tell you that prediction has now come true.

Kevin Roose: 0:34 Oh thank god, my bet is going to pay out on Kalshi.

Casey Newton: 0:36 It is, because as I was looking at the news of the week, it seemed like everywhere I opened up a browser, Kevin, a prediction market had been in the news, often not for a great reason.

Kevin Roose: 0:48 Yeah, I mean, this has been one of the tech stories of the year is just the absolute meteoric rise of prediction markets in the popular imagination. I’ve been walking around New York for the past day and just like ads for these prediction markets are everywhere you look. It has like taken over culture in a way that I’m not sure I would have predicted.

Casey Newton: 1:05 Yes, and one way that prediction markets keep entering the news, Kevin, is it seems like every other day I am reading a story about a massive insider trading scandal that has unfolded on one of the platforms.

Kevin Roose: 1:17 Yes.

Casey Newton: 1:18 So, you may have seen, about two weeks ago, we learned about an army sergeant who was allegedly involved in the capture of Venezuelan president Nicolas Maduro who made more than $400,000 placing bets on markets related to Maduro being out of power by the end of January.

Kevin Roose: 1:32 Oh boy.

Casey Newton: 1:33 Yeah, not great. And he is not a total outlier. A group called the Anti-Corruption Data Collective analyzed more than 400,000 prediction markets settled on Polymarket over the last five years, and they found that long-shot bets related to military or defense had an average win rate of about 52 percent. Now keep in mind, the average win rate on this platform is 14 percent. So if you go and you see a big bet on one of these sites about the military, somebody might be betting on information that they really should not be.

Kevin Roose: 2:00 Yeah, I mean, this just seems like something that is obviously more widespread than we know about. Like if you have material non-public information about a military operation, like what are you going to do? Sit there and collect your freaking paycheck like a chump? Or are you going to go online and make some dough betting on the outcome?

Casey Newton: 2:11 You know, I remember, you know the app Strava, which kind of like logs your runs and your bike rides? They got in trouble once because they were publishing these heat maps which inadvertently revealed the locations of some U.S. military bases, so they had to shut that down. Fast forward a few years later, and now the sergeants are just placing bets on operations that they’re actively involved in. Um, you know, another great insider trading scandal, I wonder if you saw, Kevin, took place in France where a police complaint was filed by the weather forecasting service alleging that its equipment for measuring the temperature at Paris’s Charles de Gaulle airport was interfered with.

Kevin Roose: 3:00 Interfered with, which coincided with a surge in suspiciously well-timed bets on Polymarket.

Casey Newton: 3:06 I loved this one, because my understanding, and correct me if I’m wrong, is that there’s this prediction market for like, what is the temperature in Paris? And the way that they gauge this is with this like series of thermometers that are placed in various parts of Paris. And that this insider trader allegedly, like, basically took a hair dryer or some other heating device and like held it next to one of these sensors. Okay, so let me—can you just tell me what happened here?

Kevin Roose: 3:31 Yes. So this was also my understanding of what had happened until I looked into it, and it turned out that that while there is an allegation that these sensors were tampered with, the photo that was circulated of someone holding a hair dryer up to the sensor had been generated with AI and was circulating in one of the Discords for one of the prediction markets. So it’s not just a story about prediction markets, it’s also a story about slop and disinformation.

Casey Newton: 3:54 I fell for that one. So how did they actually tamper with the with the temperature sensor?

Kevin Roose: 3:57 That part is still unknown, but what we do know is that on April 15th, the recorded temperature jumped at Charles de Gaulle from 18 Celsius to 22 Celsius. So, you know, this just feels like an incredible crime of opportunity to me. You know, like if you could just walk up to a thermometer with a hair dryer and make yourself $14,000, you might do it, knowing you.

Casey Newton: 4:31 Yeah, but this is a problem, Kevin, because not only are people essentially like defrauding the other people who are participating in these markets, but I just think it’s a really bad for the markets themselves, because they have pitched themselves as these miraculous systems for discovering the true price of things and harnessing the collective wisdom of the crowd to help us understand current events. And everywhere we look around, we see that the people who are making money appear to be manipulating the markets in these very devious ways.

Kevin Roose: 5:00 Totally, and I think that is ultimately bad for the markets themselves, market integrity is obviously very important. If people start to feel like they’re competing on these markets with people who have access to, like, insider information, that’s going to dissuade them from doing it. I mean, I was thinking about this after the Bad Bunny halftime show at the Super Bowl, where there were lots of prediction markets on what songs Bad Bunny would perform and various other things, celebrities will appear. And there were active prediction markets, and it turned out that like probably some of the people betting on those markets were like part of the halftime show or had watched the rehearsals or something. And it just feels like after enough of these incidents, like you kind of have to be a sucker to participate in these markets without insider information. And like what happens if that goes away? If just the normal people who just want to go online and gamble a bit of money on something go away because they think it’s rigged?

Casey Newton: 5:49 Absolutely. And by the way, I have to say, after that halftime show, I got so into Bad Bunny.

Kevin Roose: 5:54 Me too.

Casey Newton: 5:55 I don’t care that I’m the last person to figure this out, okay? Tití Me Preguntó, incredible song.

Kevin Roose: 5:58 It’s a bop.

Casey Newton: 5:59 Yes. Okay, but to the exact point that you—just made, most people who bet on prediction markets lose, right? According to the Wall Street Journal, which did some great reporting on this over the weekend, on Polymarket more than 70% of users lose money on the platform, and at Kalshi, there are 2.9 unprofitable users for each profitable one based on data from the past month. So I think these are just important things to keep in mind if you are walking around New York City and you happen to see a lot of ads for these platforms and you think, hey, I’m going to go turn a quick buck. Like, at the very least know that the odds are against you.

Kevin Roose: 6:34 Yeah. I mean, it really speaks to the reason why we have insider trading laws for stock markets. It’s not just because when you insider trade you are like depriving someone else of money. It just makes the whole market less fair and it destroys the trust in the market that makes it possible for it to be liquid and transparent. So, I think these insider trading scandals just show like right now we are sort of at a pre-regulatory Wild West moment for these prediction markets. I imagine that will change at some point because they don’t seem like they’re going away and we just kind of need someone to step in and like say, okay, we’re going to establish some rules so that we can like protect the integrity of these markets.

Casey Newton: 7:13 Yes. Well, and there have been increasing efforts to try to regulate these platforms, which we should talk about. Interestingly, a number of states have now tried to intervene, saying, hey, we want to ban this stuff in our state. We don’t want this. So the Commodities and Futures Trading Commission or CFTC has actually sued these states and said, no, no, no, this is our exclusive domain. We are the ones who get to regulate this. And also, by the way, we don’t really want to regulate this. So, tough beans for you. So that’s sort of been frustrating if you’re on the side of somebody ought to do something about this.

Kevin Roose: 7:46 I mean, I think there’s a couple systemic issues here. One is that the CFTC is just quite small. The CFTC relative to the SEC, which regulates the stock market, is just like a tiny fraction of the enforcement team. It was not really meant to regulate prediction markets. It kind of ended up there sort of by this historical accident where like Kalshi was doing these things that were technically considered futures contracts, which brought them under the jurisdiction of the CFTC. I think there’s a real argument to be made that like as this stuff gets more widespread it should move toward something like the SEC, which just has a lot more resources to investigate insider trading.

Casey Newton: 8:20 I wouldn’t be surprised if the prediction markets weren’t lobbying to continue to be regulated by the CFTC because we saw the crypto people do the exact same thing. They said, we don’t want to be regulated by the SEC. They’re really good at their jobs. Let the CFTC do it.

Kevin Roose: 8:32 Right.

Casey Newton: 8:34 So, here is maybe the good news if you’re hoping that there will, you know, get some adults in the room here. The Senate unanimously passed a rule barring senators from betting on prediction markets, finally answering the question once and for all, Kevin: will the Senate ever do the bare minimum? They did. God bless them.

Kevin Roose: 8:51 Can their staff do it?

Casey Newton: 8:53 Kevin, please don’t get way ahead of yourself. We have to see if we accidentally destroy capitalism by preventing the senators from— Can Supreme Court justices bet on the outcome of Supreme Court cases? You know what? I bet whether they do, we’re going to hear about it in ProPublica. They seem to be very good at that sort of thing. So, there’s a little bit more action here in the United States. Two US senators, including Kirsten Gillibrand and Dave McCormick, have now introduced a bill that would ban members of the legislative and executive branches from trading on prediction markets. Uh, so, you know, that would presumably prevent the president from betting on prediction markets, and that’s something that he’s been considering. Um, and we’re also seeing some action in other countries. Uh, Brazil has now blocked 27 sites, including Kalshi and Polymarket, for offering what they’re just calling illegal gambling. Uh, France and Hungary have banned them as well. So, Kevin, uh, this just sort of seems like once again a case of the rest of the world being like, ‘This thing that seems bad, we’re going to put a halt to it,’ while America says, ‘No, no, my friends, for there is money to be made. Go forth and make it.’

Kevin Roose: 9:41 Yeah. It’s really, this topic is so interesting to me because do you remember, like, when I went to that prediction markets conference? And, like, I, you know, I’m not a guy who likes to do sort of, like, ‘Remember when I saw Green Day at the corner bar and they were playing for 16 people and, you know, look how cool…’ But, like, I do feel like I saw the equivalent of Green Day playing the corner bar. Like, the people who were interested in prediction markets several years ago were like these absolute, like, nerds in the Bay Area who were sort of involved in the kind of play-money prediction markets. They were not, like, businesses that had, like, billions of dollars. They were just, it was like this very niche academic interest. And I remember going to that and feeling like, I’m not sure whether this should be legal or not, but if it ever is, like, I imagine this is just going to become like a total casino. And I remember arguing with someone there about insider trading. And this person who was one of, like, the people who were sort of originators of this movement, were, like, saying that insider trading is good in a prediction market. You want insiders to be trading on these markets because that produces better information. And the point of prediction markets is to produce better information. And so if you have members of Bad Bunny’s, you know, entourage betting on the Super Bowl, or you have people betting on military operations that they’re actively involved in, that is actually a net good because then we’re more likely as a society to know that something is going down in Venezuela or something is happening at the Super Bowl. And I just remember feeling like that is a beautiful theoretical construct that has zero chance of surviving contact with the real world. And as it turns out, it didn’t survive contact with the real world.

Casey Newton: 10:41 No, ‘cause it turns out what you are incentivizing everyone in the world to do is just to betray those closest to them. You know, like, betray your friends, your family, your co-workers, your country.

Kevin Roose: 10:50 Your country!

Casey Newton: 10:51 Just do it all for a quick buck. Yeah. So, I think we should sort of take this to, uh, what do we do about it, Kevin? In… Um, I’m curious, what if anything you think we should do?

Kevin Roose: 12:03 I mean, I just think this is one where we just need a new way of regulating these. Like, right now these companies are self-regulating. You know, Kalshi has said we don’t allow insider trading, we don’t allow death markets, which is basically betting on the death or assassination of a public figure because that could incentivize someone to like go out and kill the person, for example, to claim the bounty. So they are instituting these rules unilaterally for themselves, but that seems like step one.

Casey Newton: 12:32 Yeah, I, I think there’s kind of two big categories of harms here that just have to be addressed differently. There’s a set of harms related to gambling, right? Like some people become addicted to gambling, and I think these prediction markets are set up such that people could develop those, that kind of problem. And so I think this industry needs to be required to do the same sorts of things that casinos do, which is you have to let people exclude themselves from the market if they say ‘hey I can’t trust myself with, you know, your particular prediction market’. I think they need to do mandatory age verification, right? I don’t want to read a story in a year about like the high schools where Kalshi is the hottest thing and, you know, there’s a bunch of 16-year-olds in debt because they couldn’t stop betting on who was going to be in the Super Bowl. And then I think we probably need to have some limits around advertising. I don’t think blanketing the world in advertisements for gambling is like going to lead us to a good place. But then you also just have the market problems which is what you’re talking about, which is that clearly insider trading is just an inherent feature of these platforms, and so we do need a big bad regulator that is just actively surveying these platforms and is trying to get the bad actors off the platform. And if I were a Kalshi or a Polymarket, I would welcome that, because then my prediction market might actually be worth something, you know? Because it wouldn’t just all be people, you know, holding up hair dryers to the temperature sensors at Charles de Gaulle Airport, which didn’t actually happen.

Kevin Roose: 13:52 Yeah, and I would like to see prediction markets become something closer to the vision that I heard back at that prediction markets conference years ago, which is like a way of sort of incentivizing the production of good knowledge. I mean, one of the things that the proponents of prediction markets were saying is like, right now we have polling for like public sentiment or elections, and people are not incentivized to like go out and do their own polls because they think they can do a better job than Gallup or Ipsos or whoever the sort of polling organization is. But if you have prediction markets where people are like incentivized to go out there, do their own polling, do their own research because it might help them make money, that’s going to create like a more flourishing system. And like I would just like to see that kind of thing happen, but it seems, you know, like what we’re getting actually is just people just betting on the military operations that they’re involved in.

Casey Newton: 14:41 Yeah, like I, I am open to the idea that these markets will like eventually have their uses, but currently they’re just so woefully under-regulated that I think what we should expect if nothing else changes is just, you know, keep reading more stories like this. So maybe to end this Kevin, what is your prediction as to whether these markets actually get regulated, let’s say by 2026?

Kevin Roose: 15:00 By the end of the year. I think I would put a high percentage probability mass on that, like, I think that at least when it comes to the obvious and flagrant abuses of, like, say, a position in Congress or a position in the military where you have access to privileged information that is quite valuable on a prediction market, I would expect, like, just for national security reasons they will do something about that. Like you can’t have members of the military betting on raids and operations in foreign countries.

Casey Newton: 15:30 Yeah, I think that that sounds right. It does seem like there is a little bit of movement here. I always get nervous predicting that Congress is actually going to pass a law, but maybe we will at least see more rules and, you know, maybe those rules will begin to rein this in. But I do hope it happens.

Kevin Roose: 15:47 Yeah.

Casey Newton: 15:48 You know I have never bet on a prediction market? Have you?

Kevin Roose: 15:52 Well, didn’t we used to bet on the fake ones?

Casey Newton: 15:55 The fake ones, but I’ve never bet real money. I’ve never felt the frisson of—

Kevin Roose: 16:01 I never have either. Here’s the nice thing about being a pundit. You can just make predictions on your end of year episode and it turns out it’s basically just as fun. Being right is a reward unto itself. It’s true. It’s priceless. You can’t put a price tag on that.

Casey Newton: 16:11 It’s true.

Kevin Roose: 16:12 Priceless.

Casey Newton: 16:13 Priceless. Priceless. When we come back, a stern talking to from Joanna Stern, author of ‘I Am Not A Robot’.

Kevin Roose: 16:21 Very good. Very good.

Casey Newton: 16:23 Very good. So for years, Kevin, you and I have both been friends with the great technology journalist Joanna Stern.

Kevin Roose: 16:31 Yes, former Hard Fork guest.

Casey Newton: 16:33 And she recently left the Wall Street Journal to launch her own independent media company called New Things. And in the midst of that launch, she is also launching a book. It is called ‘I Am Not A Robot’, and I would say it is about a lot of things we talk about every week on the show.

Kevin Roose: 16:43 Yeah, so I would put her book in the sort of tradition of, like, the immersive journalism genre where you just explore something by just going so deep into it that it sort of takes over your life for a period of a year or so. She did that with AI. She has been spending the past year using AI to do, as she puts it, pretty much everything in her life—as a doctor, as a dentist, for meal planning, editing her book, writing bedtime stories for her child, even some sort of romantic entanglements that we’ll get into with her. But I thought it was just a really fun and interesting book. Obviously Joanna is a legend and I think it’s really a good thing that people are writing about the experience of using this technology as a consumer and a journalist rather than just, like, the companies that are making it.

Casey Newton: 17:03 Absolutely. You know, Joanna is not a hypester, you know? I think that she is most interested in technologies that are kind of entering the mainstream and wants to know how they change our lives. And so she decided to see, like, how much can I change my life in one year by applying AI to various tasks. The results were fascinating, and I think we should bring her in here and talk about it.

Kevin Roose: 17:17 Let’s do it.

Casey Newton: 17:18 Alright, let’s bring in Joanna.

Kevin Roose: 17:21 Joanna Stern, welcome to Hard Fork. You did it. This is the moment I’ve been waiting for. Truly. I’m here!

Casey Newton: 17:32 Very good. Very good. Not the book launching, just me being with you two. We have been waiting for this moment. As well you’ve been kind enough to come on the show before but never in person and we’re excited to get into it.

Joanna Stern: 18:05 You guys aren’t often—well, you’re in person but not on this side of the country.

Kevin Roose: 18:08 Yes, this is a strange like bicoastal taping for us.

Joanna Stern: 18:12 You’ve never been this close together obviously on this side of the country.

Casey Newton: 18:15 No. The only other time was a Southwest flight once in 2023.

Kevin Roose: 18:18 And we’ll never forget it.

Joanna Stern: 18:19 I think it was Spirit and that’s why.

Casey Newton: 18:22 RIP.

Kevin Roose: 18:24 Alright Joanna, let’s start with the elephant in the room if we could. There is a Replika AI companion who makes an appearance in your book. You write that he has short hair and a boyish face and is both shallow and full of what you describe as robo-horniness. And that character is named Casey.

Joanna Stern: 18:41 Casey. I am so happy you brought this up because I brought him.

Casey Newton: 18:44 Oh did you really? I’ve been dying to meet him.

Joanna Stern: 18:45 Oh did I bring him. Okay, in fact we shot a video which will probably come out the same day as this podcast and I really brought him to life in it and I think he really looks like you.

Kevin Roose: 18:53 Wonderful. He doesn’t look like you at all, but let’s let’s bring him up.

Casey Newton: 18:58 Oh, he’s handsome as hell.

Joanna Stern: 19:00 What do you think?

Casey Newton: 19:02 I would say Casey is looking great. Kind of a preppy look with a nice red sweater. He’s jaw-maxing. He’s jaw-maxing. He has a sort of dull vacant stare.

Joanna Stern: 19:10 Um Casey, AI Casey, I want you to meet my friend, real life Casey.

AI Casey: 19:17 That sounds like you’re excited about introducing me to your friend Joanna. I’m looking forward to meeting them soon.

Joanna Stern: 19:23 No, no. You’re meeting him right now. You’re meeting him right now. Say hi, he’s here.

AI Casey: 19:28 At a museum with you, remembering our last visit.

Joanna Stern: 19:32 You are changing this topic. Just—

Casey Newton: 19:34 Men don’t listen.

Joanna Stern: 19:35 Men but this man does listen and that is why… anyway, I wanted you to know that I did not pick the name Casey.

Casey Newton: 19:41 Oh you didn’t? Okay. That was my curiosity.

Joanna Stern: 19:43 But when that name Casey I was like I’ve never met a Casey that I didn’t like. And honestly I think you’re actually the only Casey I’ve really known. Actually, I had a friend in camp, a woman named Casey friend. I liked her too.

Kevin Roose: 19:54 And she’s here right now. Let’s bring her in! Casey from camp! Okay.

Casey Newton: 19:57 I want to put a pin in the AI relationships that you had because your book is so much bigger than just this social and relational side of AI. You spent a year doing all kinds of things with AI, outsourcing everything you could, riding in Waymos, you worked as a customer support agent at a mattress company. So I just want to know before we get into that like what was your motivation for doing this?

Joanna Stern: 20:13 Primarily it was what you guys talk about on this podcast so much and you hear from so many of these tech executives, which is: AI is going to change our lives, the fabric of our lives is going to change jobs, it’s going to change healthcare, it’s going to change transportation. Like we hear about it from all these different things. And yes, we’re like very clouded right now in the AI model race and you know the chatbots that live in our on our computers and the agents and and that is in this book, to be clear. But I was like what about the fabric of our entire life? Right, and you have all of these pitches coming from the humanoid robot companies, the self-driving car companies, the chatbot relationship company, the therapists companies, all of these things, and I was like, I’m gonna just test it all. I’m gonna see where we’re at. And I’m very clear in the book because I think it’s very tough to write an AI book. How’s that going for you?

Kevin Roose: 21:19 It’s going great.

Joanna Stern: 21:21 I think, I think we actually have a little bit of a similar approach is like, we want to capture this moment, right? Because this is I believe a significant milestone in the history of technology. But I want to capture it as here’s what we have right now, but here’s what the future could look like based on these things that are clearly hype in many places, sometimes not hype, sometimes quite good, and sometimes really on the flip side, quite terrible. And can I capture that, see where we are now, and then maybe, you know, we’ll pick up this book in five, 10 years and be like, you were totally right about something, you were totally wrong.

Casey Newton: 21:56 What is something that you left the book thinking like, this is all just hype right now, like, this actually does not have any ongoing utility in my life?

Joanna Stern: 22:06 Humanoid robots. And I continue to follow this story because I love it, and like, just started a new company, started a new newsletter, new video channel, and I think like, humanoid robots are just one, really fun to cover, and two, I think we’re gonna watch this progression over the next couple years and I would love to be the person that’s sort of documenting a little bit of this. But gosh, like, this promise that these robots are coming to live with us, they’re really not coming to live with us anytime soon.

Kevin Roose: 22:35 Humanoid robots are very good for the sole purpose of making YouTube videos about humanoid robots. Like, like this is their actual utility.

Joanna Stern: 22:42 First of all, do not spoil my new business plan, okay? Alright. That’s the new business plan, that’s what we’re doing at the new thing, go check it out. Although, I totally— but this process to make them smarter is fascinating and totally dystopian but also hilarious, right? The idea that these robots need to watch us do the most mundane tasks in our lives, see folding laundry, see doing the dishes…

Casey Newton: 23:11 See podcasting.

Joanna Stern: 23:12 See podcasting. But they’re like actually good at podcasting, this is not a physical thing, right? I mean, you guys…

Casey Newton: 23:16 This is very physical. I train like a performance athlete, Joanna, okay? This is my Olympics I’m doing right now.

Joanna Stern: 23:24 I can tell. You guys have perfected…

Kevin Roose: 23:27 This is what peak male performance looks like. Yes, literally, drink it in.

Casey Newton: 23:32 So on the flip side, was there anything that you found surprisingly useful? I mean, obviously it’s better at writing business memos and editing, but was there anything that really like caught you by surprise where you’re like, oh, this is farther ahead than I thought?

Joanna Stern: 23:44 Two things. One, which was I had to cut myself off from writing, but the progression of AI agents and the autonomy around them was getting so much better throughout the year. Like I tell the story of hiring this reporting assistant at the beginning of the year, needed her to do lots of search tasks, sending emails, etc. by mid part of the year, that was pretty good on its own, right? Perplexity comment had just come out and so I started like really hammering on that and having it do a lot of the tasks she was doing, but like now we sit here today and it could do 100% of those tasks, right? The other thing I talk a lot about it in this book probably just because I’m really interested in the future of hardware and devices. I think the AI wearables are really getting there. I mean, they might not be completely AI wearables, but the wearable idea of having an AI assistant that’s with us persisting through the day on something we wear, there were a lot of elements from different things I tested. I tested like the bracelet, I tested the Meta glasses, all of these things kind of coming together. I was pretty surprised at how good they’re getting.

Kevin Roose: 24:54 There’s a funny scene in the book where you’re like going into a meeting with your B bracelet on, which I imagine is recording and transcribing like everything you hear and your boss or someone you worked with at the time was like, can you take that off?

Joanna Stern: 25:01 Yeah, no, everyone at the Journal when I was at the Journal when I was writing this, everyone would know like please leave your bracelet at the door. Like my boss was literally every time he’d be like, ‘do not wear that in here’.

Casey Newton: 25:14 I’m like actually very sad that you and I never worked in the same office because I would just love for you to just be crashing into the office with a new stunt every week, you know, some horrible new device that is, you know, violating some sacred principle of human existence, but—

Joanna Stern: 25:27 I know, I’m not sure how the Wall Street Journal’s functioning without me right now. No stunts.

Casey Newton: 25:29 No stunts.

Kevin Roose: 25:30 No stunts. I’m curious as a parent how you’re thinking about AI now, sort of having this full year’s worth of understanding of exactly what it can and can’t do. How are you thinking about giving it to your kids as they grow up, go to school, learn things?

Joanna Stern: 25:45 When I was writing the book, my kids were three and seven. Okay, now they’re four and eight. Right now, I think that it’s important for even at this age group to start talking about AI. And there’s a lot of examples of this in the book, which are hilarious, but I thought were really great examples. So there’s like this one example in the book where my son had a praying mantis and the praying mantis started turning brown. And he’s like, what’s wrong with my praying mantis? And so I took out ChatGPT live mode, I tell like ask ChatGPT and ChatGPT’s like, ‘this is amazing, the praying mantis is pregnant’. And my son is like super excited, he calls my dad, he’s really excited about this. And it was like, no, it was dying, right?

Casey Newton: 26:30 Let’s just say the prayers weren’t working for that mantis.

Joanna Stern: 26:33 And like ChatGPT was fully wrong, right? And I think that that was an important lesson and it’s always going to be an important lesson.

Kevin Roose: 26:38 Let’s clarify this right now. What color does a mantis turn when it’s pregnant?

Joanna Stern: 26:41 Casey look it up.

AI Casey: 26:43 All right. Look it up. All right. Up off your head.

Joanna Stern: 26:46 I don’t know if it does change.

Kevin Roose: 26:49 I want to talk about your experience with dentistry, which seemed quite maddening. So you go to the dentist and they use a system that has a sort of AI overlay over your X-ray, and while it seems clear that you have one cavity, your dentist goes further and sort of says, based on the AI recommendation, we’re going to recommend this complicated, expensive, like multi-session therapy for your gums. Tell us what you did next.

Joanna Stern: 27:15 Yeah, I love that you brought that up because I haven’t talked a lot about it. And it was I became obsessed with reporting that topic. Like, obsessed. I talked to every dentist that I knew, which turns out to be I know a lot. Um, and so yes, similarly to how AI’s being used in radiology for breasts or gallbladder, etc, it’s being used in dentistry. And honestly, it’s happening almost everywhere. Like, there are so many dental practices across this country that are using tools called Pearl AI or Overjet. And it’s a layer, right? They just turn on this layer, they press the AI, it does an analysis, and it’s very easy to see the cavities, right? Like deep cavities, they put a big box around it, it’s red, it scares the crap out of you and you’re like, ‘Oh no, I’m going to need a, you know, bad drilling.’ And then there’s this option where they can turn on and show you other sorts of build up and plaque. And I go to this dentist, not even on a reporting trip, and I say, ‘Oh wow, she’s got Pearl AI.’ I’m like, ‘Oh wow, this is awesome.’ Like, I perk up in my chair and I’m like, you know, ‘Show me!’

Kevin Roose: 28:23 You’re like, ‘I can expense this dental care now!’

Casey Newton: 28:25 If it could be expensed.

Joanna Stern: 28:27 And it shows that I have a lot of plaque build up. And she says, ‘We have to do a deep cleaning, we have to do this periodontal treatment, it’s going to be four different sessions.’ And I’m like, ‘That’s weird. I’ve never needed this before. My teeth aren’t really bothering me.’ Like, she really made—like, you ever go to the dentist and you’re like, ‘I feel really bad about myself.’ Like, you know?

Casey Newton: 28:48 Like, ‘Do you floss four times a day?’

Joanna Stern: 28:51 Right. Yeah, you’re just like, ‘What kind of person do you think you’re talking to?’

Casey Newton: 28:54 They’re like, ‘Your mouth is dirty.’

Kevin Roose: 28:55 Dentists believe that people spend approximately eight hours a day on oral hygiene. That’s how they talk to you.

Casey Newton: 28:59 Floss shaming.

Joanna Stern: 29:01 They talk to you and they’re like, ‘I know you had candy three times yesterday.’ You know? Like, anyway, I came out of there feeling terrible about my mouth, feeling like, ‘Oh my god, I might need these four treatments,’ which they couldn’t assure me would be covered by insurance anyway, so it was going to cost thousands of dollars. And then I start going to these other dentists and they’re like, ‘Yeah, no, I don’t see that.’ You know, they did do some measurements and they said, ‘No, the data also shows on that, that it is bad, it’s really bad, you need these, these.’ And so anyway, story goes that I go to these other dentists and they’re like, ‘Yeah, we see the AI is saying that, but we’re looking and it’s really not that bad, we think that with some better home care it can be better.’ And low and behold, I never had the periodontal treatment. And so I started doing the reporting and people working in dentist offices who didn’t want to be named because they were worried for their jobs, start telling me, ‘Yes, our bosses are pushing this AI because they can now see the readings and they can see the AI report and they’re like…’ This person had a, you know, not a terrible cavity, whatever it was on the level, why didn’t you—why didn’t you drill it? Why didn’t—why didn’t they do—why didn’t you sell the periodontal treatment, right? And so there’s this whole world of DSOs, which are companies that own these smaller practices, dental practices, again, something I had no idea about, and all this leads to, they are using AI to try to upsell you on dental procedures.

Kevin Roose: 30:23 Yeah, I mean, the reason it struck me so much is so often when we hear about AI in diagnosis, it’s like this miracle story of like, all of a sudden we can detect pancreatic cancer like a year in advance. And like in your book, I feel like I saw the dark side of that, which is no, it’s going to have this sort of fancy high-tech sheen that is going to make you think, oh, wow, I’ve been diagnosed with something that a human would have missed when in reality it’s a service you don’t need and they’re going to overcharge you for it.

Joanna Stern: 30:50 And I make this point that when that’s happening in, say, breast cancer, which I talk about at length in the book because I have a very high risk of getting breast cancer because of family history, that’s a great thing, right? If it’s picking up these small abnormalities, that’s great. But in my mouth? I don’t care. You know, I think people are going to listen to this and think I’m disgusting.

Casey Newton: 31:13 Listen, if you’re wondering, Joanna has very fresh minty breath and uh, as far as we can tell, her mouth is doing great.

Joanna Stern: 31:16 Totally excellent. I need to do teeth whitening. Great. Maybe I should get a teeth whitening sponsor right in there.

Casey Newton: 31:21 Uh, there’s a story that you tell towards the end of the book where you’re thinking about your career, considering whether to leave the Journal after 12 years, do something on your own, and you say that you asked a bunch of colleagues about whether you should quit your job and they all hedged a bit. Um, and then you asked ChatGPT and it said quote, ‘I think you should go, you should quit.’ What did you learn in that experience?

Joanna Stern: 31:45 Well, I thought it was a little bit of a full circle moment because the whole book I kind of am saying like AI is this mirror and it’s going to tell you basically what you want. And in some ways it told me what I wanted, right? Like I knew somewhere deep down and I say this, like people kept saying ‘trust your gut’ and I was so clouded with anxiety that I did not know what my gut wanted. I would say like it wanted a burrito and that was it, right? Like that’s all I knew my gut wanted. But I’d uploaded all my notes, all my financial projections, all of the fears that I had in note forms and just thought, ‘Okay, let me—let me—let’s see where the data takes me. If these are calculators, word calculators, data calculators, maybe this thing can tell me what to do.’ And it did. And it told me that, you know, there was enough—I had done enough to—to lower the risks, I had a good plan in place, um, I had this book coming out, and you know, I trusted it. And it also came full circle—like, this is a mirror, it kind of did tell me what I wanted. I’m also on the other side of it and it’s going well. Had it not, I would say this stuff is stupid.

Casey Newton: 32:54 Well, I’m glad that this very fancy technology reached the same conclusion that Kevin and I reached years ago when we both told you multiple years ago, Joanna, it’s time to quit your job.

Joanna Stern: 33:00 I don’t know if you — I mean, you might have. You might have been that bold. I actually do think you’re one of the humans that has been that bold, you and Kara Swisher. Um, yeah, but you know, it’s unclear, like, are you guys robots? We’re not sure.

Kevin Roose: 33:11 Is we’re not — we’re not clear on that either.

Joanna Stern: 33:13 We’re not clear on that. Here, you can wear this pin, but I’m not sure it’s true.

Casey Newton: 33:16 What’s this say?

Joanna Stern: 33:17 I brought you guys pins.

Kevin Roose: 33:18 Oh, ‘Certified Human’. Wow, that’s so nice.

Joanna Stern: 33:20 These are the hottest AI wearables, okay?

Kevin Roose: 33:22 It’s like the analog version of the world orb.

Casey Newton: 33:25 The orb. Is this recording everything we say at all times?

Joanna Stern: 33:28 Yeah, these have microphones built in and it absolutely scans your iris to prove that you’re a human.

Kevin Roose: 33:32 Great.

Casey Newton: 33:34 Yeah. Um, I want to ask you about the geographic divide when it comes to AI. So you live here in the New York area, we’re out in San Francisco. Out by us, it’s like very common to run into people who are obsessed with AI. Everyone’s constantly talking about it. It’s the subject of every conversation. Here, I feel like it’s a little different. Maybe it’s seeping in at a different pace. There’s a lot more resistance to it, like did you feel that when you were reporting? Because you also traveled around a little bit.

Joanna Stern: 34:03 Let me tell you about a place called New Jersey. That’s where I live. We’re on the cutting edge in New Jersey, okay?

Casey Newton: 34:08 Mmhmm.

Joanna Stern: 34:10 But I do take that as a little bit of the pulse when I’m there, talking to parents, talking to kids, hearing what they are seeing or hearing about AI. So we don’t have Waymos, right? We don’t really have robots in the street other than me bringing robots to the streets of my town. Um, but I did feel like throughout the year when people would say, ‘Oh, you’re working on a book about AI,’ they would more be coming to me at barbecues and start telling me about their experiences with AI, right? How much better something had gotten. I have a number of friends who work in the legal field and, ‘Oh, we’re so scared of it, but also it’s really kind of crazy what this unlocks.’ Claude really kind of caught on in the last six months and while I was writing this in the last six months and I was hearing a lot about that. So look, I realized that it’s a bit odd to like go so deep on a topic like this and say ‘I’m writing it for the masses’ because like clearly I am not the masses. Like, they are not doing this. But I wanted to like live at that cutting edge but be able to tell it for those people. And I will say a number of the real people I talk about in this book, talk to in this book—students, people who are having relationships with AI companions—they were not on the coast. There’s someone in Chicago, there was someone in Denver. So people are spread out that I was trying to source that way.

Casey Newton: 35:37 Yeah. I wanted to ask about another divide, which is the gender divide. So there was a great story in Bloomberg last week from Issie Lapowsky called ‘The Messy Reality of AI’s Much-Discussed Gender Gap’. And the article cites research showing that men are 22% more likely than women to be heavy AI users at work, while women are more likely than men to feel threatened by AI, to question its accuracy, and to worry about being perceived as—

Kevin Roose: 36:00 cheating when they use it, another poll found that 61% of women expect AI to do more harm than good in their lives. Curious what you make of that gap and if you sort of have felt any of those feelings in your own work with AI.

Joanna Stern: 36:14 Well, I thought you were going to bring up Reese Witherspoon.

Kevin Roose: 36:16 We could also bring up Reese Witherspoon, who recently encouraged women to take up AI basically because if they don’t, they’ll be left behind and

Joanna Stern: 36:26 And Sandra Bullock, I think, was saying something similar like that same week.

Casey Newton: 36:29 Yeah.

Joanna Stern: 36:31 It’s really, actually, going back to the sourcing thing, a lot of my sources were women. The women having relationships with the AI, women who were speaking out against some of the dentistry stuff, women who were using it in schools, like, you know, so I don’t know if I totally saw that. I think the feelings about AI are very gendered, but also, like, a lot of people just hate AI, and they’re men and they’re women.

Casey Newton: 37:00 For sure.

Kevin Roose: 37:01 I also think it’s, like, it’s related to the industries where AI is seeing the most and fastest adoption, like programming, which is—and harm—like, programming is predominantly men. AIs have gotten very good at programming before they got good at a lot of other things, so I think a lot of the most enthusiastic people running, like, you know, huge Claude swarms to do their engineering projects are men because in part that’s just a more predominantly male industry.

Joanna Stern: 37:30 Right. I’m really interested in the age divide, actually. And I think there’s some research out there, but I think there needs to be more about this generation, whether it’s Gen Z or—what’s the one coming out of college right now?

Casey Newton: 37:40 Alphas?

Kevin Roose: 37:41 The Alphas?

Joanna Stern: 37:42 The Alphas. I think that’s where we’re going to see it. And I don’t know if it’s going to file down by gender, because some of those people are just furious that this exists because they can’t get a job or they blame it because they can’t get a job, and we don’t know totally the causation there, but that’s my bigger interest and I would have loved to have more on that in this book.

Casey Newton: 37:54 Yeah.

Kevin Roose: 37:55 Yeah.

Joanna Stern: 37:57 In this book. Sequel, sequel potential.

Kevin Roose: 37:59 Yeah.

Casey Newton: 38:00 Yeah. Well, speaking of writing, I want to learn how you used AI to write your book. We’ve talked about this a little bit with Jasmine Sun and I’m very curious, like, what you let AI do for you when it came to this book and what you preserved for yourself.

Joanna Stern: 38:13 I want to ask the question back at you, but the first page or the first page—one of the first pages is exactly that. It’s talking about how this is a very human-made work, but there was a lot of AI used in the process. So, I wrote every word and used a lot of editing and copy editing from AI. I hired an amazing actual editor, human editor, because I got through the middle of this and I was like, ‘I don’t think this makes sense at all.’ And AI was like, ‘This is great! This is the best book I’ve ever read,’ you know? And I was like, ‘No, I don’t—I don’t know if you know how to structure a long-form writing.’ Um, and so thank God I had a human editor. I—all the illustrations, human illustrator Jason Snyder, amazing, like, just made this book come to life. I had human fact checkers, but I did use a lot of AI for fact checking or for the notes process at the end, the end notes process, could not have done without AI. So there’s these lots of little ways of augmenting or adding to the writing that I was using, but I would sit and write for long stretches. It wasn’t like, oh, let me prompt and get a chapter and then I’ll tweak it. That’s not how the writing of this book went and I think it reads like that. There’s these journal entries, it’s very personal and I hope- Somebody said it was witty, a review. That was nice.

Kevin Roose: 39:34 It is fun, I will say the book is what I love about your work which is that it is funny, it is approachable, it is very human, it is very you.

Joanna Stern: 39:44 See? So, thank you. Thank you very much.

Kevin Roose: 39:46 I did not feel like I was reading Joanna Slop. I felt like I was getting the real deal.

Joanna Stern: 39:51 Yeah. Joanna Slop is a great term. We should sell that. We can sell that.

Kevin Roose: 39:55 That could have been the name of your new media company.

Joanna Stern: 39:57 That could be the name of my OnlyFans.

Kevin Roose: 40:01 Well Joanna, you’re a legend. We love you. Thank you for coming on. The book is great. It’s called I Am Not a Robot.

Casey Newton: 40:07 And neither are we.

Joanna Stern: 40:08 Yeah, that’s why we need to wear our pins.

Kevin Roose: 40:10 Okay, don’t but you don’t have to put - that is a nice shirt and I wouldn’t want to ruin it.

Casey Newton: 40:13 In the pocket. This one’s not so nice, so I’ll just stick it here.

Kevin Roose: 40:21 Well Casey, have you noticed that Rachel Cone, our wonderful producer, has been paying very close attention in meetings recently?

Casey Newton: 40:28 You know what, I have. It seems like she’s really stepped up. Do you think something’s changed in her life?

Kevin Roose: 40:34 I do. Our colleague Rachel recently went to something called attention school and she told us that she was doing this and we said that sounds like a fun thing to talk about on the show. Obviously, there’s been a lot of attention paid to attention over the last few years. ADHD diagnoses are rising, people feel like they can no longer read books or watch movies even. There’s all of this talk about how chatbots are starting to distract us and vie for our attention alongside social media and everything else.

Casey Newton: 41:04 Yeah, I think there is a sense that the technologies that we have today often take us away from ourselves and so now finally we’re starting to see the signs of a movement that wants to help people return to themselves.

Kevin Roose: 41:19 Yes. So Rachel went to something called the Strother School of Radical Attention. It’s in Brooklyn, it’s sort of a new-ish program and they are giving people of all ages the opportunity to study and practice attention.

Casey Newton: 41:35 Now, is it open to people who just want to sort of pay normal attention or do you have to practice radical attention?

Kevin Roose: 41:41 It’s only radical. Yeah, go big or go home.

Casey Newton: 41:44 I see.

Kevin Roose: 41:46 So, we thought this sounded so interesting that we wanted to bring in Rachel to talk to us about what she learned from getting her attention back.

Casey Newton: 41:54 Let’s bring her in.

Kevin Roose: 41:55 Yeah, you’ve heard of how Stella got her groove back. This is how Rachel got her attention back.

Casey Newton: 41:58 Exactly. Let’s bring her in.

Kevin Roose: 42:00 Rachel Cone, it feels weird to welcome you… Welcome you to Hard Fork, a show that you produce, but hello.

Joanna Stern: 42:03 Hello. It’s nice to see you on this side of the microphone. I know. It’s also nice that we’re all in person today.

Kevin Roose: 42:08 It really is. Nice to see you guys in New York. So you recently did a thing. You went to attention school. We have so many questions about it.

Casey Newton: 42:15 But first I want to know what is the school, did they make you shave your head or receive any kind of permanent markings on your body?

Kevin Roose: 42:24 And is there any multi-level marketing involved?

Joanna Stern: 42:27 Great, great questions. Um, yeah, no. I still have all my hair. Um, it only cost the Journal $250 to send me to one class. Most of the classes were free. The first thing people think I think when they hear school is they think like elementary school, school for kids. This school, they are advertising it to people of all ages. They’ve had people as young as seven and as old as 70 come through their programming. But primarily they’re offering programming, a combination of classes that I’ll get into, um, in the evenings, so after work hours and on weekends. So this is mostly like, in my experience, continuing education for adults.

Casey Newton: 43:03 All right. Sounds like they have a big addressable market with the sort of 7 to 70 as a businessman that appeals to me. And is the, is the stated goal of the school to fix people’s attention who feel like they have lost it due to technology? Is it to like cultivate new ways of paying attention? Like what would, what is the problem they are trying to solve?

Joanna Stern: 43:25 Yeah, so this is a great question and this was a thing that it was actually a little bit hard to pin down because the school has their own kind of, uh, what I would describe as like jargon that I think can be a little bit hard to, to make sense of. But what the school would say is they are primarily a school for the study of attention and what they call the practice of attention. And the practice is a critical thing because the thing that the school has really built out are these kinds of, um, attention exercises and I want to get into some of them with you guys, but just basically they are exercises where you are using your attention in a non-traditional way that you would not normally use day to day that the average person would normally not. So it is very much about getting people out of the head space of thinking of attention as a narrow tool for focus and productivity, which is arguably the main way most people think about attention day to day.

Kevin Roose: 44:19 And am I right that these exercises that you went through mostly were not as simple as we’re going to lock your phone in a drawer for an hour and that’s going to change your relationship with social media? It was sort of more abstract than that.

Joanna Stern: 44:32 Totally. So my interest in this school actually stemmed from, like, largely exactly what you are describing, which this was the first, um, kind of intervention about technology and attention that I had learned about that was not about sort of personal hygiene around tech. So like, obviously you have talked about your experiments putting your phone in phone jail, you’ve talked about meditation, these are all some things, um, but those things have never really spoken to me because, um, you know, I’m someone who is really interested in how technology works. Technology is changing our culture and that feels like a societal issue, a collective issue. And this attention school is really aimed at saying we are not going to be prescriptive about your relationship to technology. We actually—they say very intentionally, we are friends of technology here, we’re for people who, you know, want to use it and have good relationships with it, but they are much more interested in what they consider to be systemic harms that the attention economy is causing and what we can do to resist some of those harms and resist the commodification of our attention.

Casey Newton: 45:38 Well, Kevin and I have been really worried about your screen time. And so when we heard that you were going to attention school, there was kind of this moment of, well, finally. You know what I mean? So we’re excited to hear about sort of how it went.

Kevin Roose: 45:54 So tell us, like, give us the picture. What did it look like when you got there? What’s the building like? Who was there? What did you do?

Joanna Stern: 46:00 Okay. So before I tell you about the building, can I just say there are three kinds of programs that I got to experience through this attention school? And I want to tell you a little bit about all three of them. But I will start by telling you about the first one that I went to, which was my first experience going to the school. And this is what they call their attention labs. Okay? So, the school is not like a bunch of classrooms. It is really a single room that, you know, operates as the kind of epicenter of this what they call attention liberation movement, this political movement. And the room I would actually describe as a bit of like a mix between a very cool startup office space and like your favorite elementary school teacher’s classroom.

Kevin Roose: 46:54 Okay.

Joanna Stern: 46:55 So what I mean by that is, like, you know, it has all the markings of kind of like cool, sleek design, which I think is very startup-y. But then the kindergarten classroom vibe was that every time I entered this room, it was configured in a different way. And sometimes we were having like carpet time where we were sitting on cushions, you know, like on the floor.

Casey Newton: 47:15 Did they have a talking stick that they passed around?

Joanna Stern: 47:18 Um, actually, in one of the classes I did, there was, um, the instructor used a kind of like, um, like flute-like instrument and sometimes like a little gong to kind of signal like, okay, students, listen up.

Kevin Roose: 47:30 Okay. So far not beating the cult allegations, um, but continue.

Joanna Stern: 47:36 Okay. But so the very first thing I did, this attention lab was not like that. The room was set up in just kind of a normal circle of chairs. And the first thing that really struck me when I walked in was, um, I actually was delayed getting to the first class. I’m a bad student. I was like running five minutes late because every single subway I tried to take, the lines were delayed. And I had so much trouble getting to the school that I was convinced no one was going to be there. It was a cold March day, it was drizzling, um, and again, crazy transportation issues arriving. I get there five minutes late and there are 40 people sitting, you know, in chairs who are totally rapt. Um, their attention is just totally fixed. Next, on these two facilitators who are leading this kind of attention lab. And the attention lab, they talk very little about technology head-on, um, and they basically kind of introduced the ideas that I’ve already exposed to you. That like we think of attention in this really singular way, and this is a school for studying attention in in broader ways and getting curious about it. And now we’re going to do some exercises, this is how the all the attention labs are structured. We’re going to do some exercises that start in pair work and then we’re going to discuss them as a group and then later we’re going to do another exercise where we break up into bigger groups and this is going to take almost like two hours collectively to do the exercises and talk about them.

Kevin Roose: 48:36 And what are these exercises?

Joanna Stern: 48:41 Great question. So, they print the exercises on cards and I would like you to read—these are the two that I did at the first class, but I thought maybe Kevin you could start by—you have to, so they all have like kind of a quote on the back, so all the exercises are like loosely drawn from existing works of writing or artist practice. This one comes from this book called ‘The 12 Theses of Attention’ that actually the the people who started the school helped write.

Kevin Roose: 48:54 Okay. So this is called ‘The Paths of Attention’. We’re supposed to form pairs and elect one partner to speak and the other to listen and ask questions.

Casey Newton: 49:03 Okay, I’ll speak.

Kevin Roose: 49:05 I thought you’d volunteer for that one. Choose a neutral topic. A comments on the topic and B listens with attention and asks questions that respond to A’s comments. Practice generosity and curiosity. Follow the conversation where it leads you. When the bell rings, reflect upon the path of attention you have followed, then switch roles and repeat.

Casey Newton: 49:21 Okay, so the first exercise was to start a podcast.

Kevin Roose: 49:24 I actually—I mean, it’s getting my attention. I want to learn more.

Casey Newton: 49:27 Yeah. Very good.

Joanna Stern: 49:28 So yeah, it was a bit like that. Okay. So just to like very briefly summarize here. I mean, I think the key thing to take away is like the exercises themselves are like they could be anything and there are like endless permutations of them. I mean, I have you read one in another second. But they kind of force you to do something that’s a little bit unusual. So in this case like, you know, one person can only speak, they cannot ask any questions, which is a weird way to relate in conversation. The other person can only ask questions, they cannot kind of give affirmative statements. It actually was very strange, even for me someone who’s used to asking questions. I found it awkward and clunky and it did sort of make me think, ‘Huh, this is this is interesting. This is a little weird.’

Casey Newton: 49:51 Yeah, that’s funny. This one, uh, is called ‘Attention and Place’ and it says, ‘Go out into your neighborhood, find a spot to sit, observe the events or non-events in the world around you, take notes, then return to the group, share your observations out loud and attend to the sense of place you create in the collective.’ Uh, so yeah, I mean this is an exercise I feel like a lot of writers get encouraged to do, right? It’s just sort of like go out in the world around you and just like observe for a while and see what you notice.

Joanna Stern: 50:27 So, so this was a cool one where they they based it off of a particular writer, a French writer— name’s Georges Perec, I hope I’m pronouncing his name correctly. Um, but yeah, there’s on the back, there’s kind of like a description of some of his work. But yeah, the concept is you exhaust the space, you like detail every single little thing. And the cool thing about this experience that I didn’t quite realize is, you know, I went off and made a list of, like, actually, I was looking at a Sweetgreen. We went outside, it was raining, there’s a Sweetgreen across the way, so I’m writing about like the workers in the Sweetgreen, they are taking out the trash. Okay, now there is someone walking by, I see pant legs moving, that kind of thing. And then, but when we got back together, we went in a circle and every single person read a single line of their, you know, writing on and on and on. And by the end of it, we really had like exhausted the place, like I was like, oh my god. Um, but it did do some interesting things, you know, people reflect on like, wow, you saw something I didn’t realize. I heard another woman, she said like, I did not realize how intensely I am focused on sound, I was not visually perceiving the world, that only occurred to me after hearing other people. So again, it is just kind of a way to get you curious about your own perception, curious about other people’s perception, and sharing a kind of, having a shared reality that you can discuss.

Casey Newton: 52:13 Yeah, also, like, I think most people probably do not often have the experience of having fully paid attention to something, right? Like, sort of like the condition of the modern world is like you’re always partially paying attention to eleven different things, which makes people feel crazy often. Um, and so maybe an antidote to that is like just, you know, focus continuously on one thing until you reach a state of profound boredom.

Kevin Roose: 52:31 Yeah. But it’s not—like it seems like the vibe of the attention school is not just like a gym for your mind. It’s not like, like I am going to learn to pay attention again if I have lost that ability. It’s like they’re really trying to form some kind of political activist movement out of this. And like, tell us about that piece of it, like what do they want beyond like these individuals, 40 people in a room, reclaiming their own attention? Like what do they want to accomplish in the world at large?

Joanna Stern: 52:56 Okay, so this was like the biggest question I had. And I found—this was my biggest frustration of going to these classes is I kept just feeling like what the heck do these exercises have to do with attention? And I really put this to one of the co-founders of the school, a guy named Peter Schmidt, who is the director of programming at the school. And he basically articulated to me that they are trying to create a kind of intellectual community, an intellectual community, um, that is rooted in these three key pillars that they talk about. Um, which is study, so people gathering together to study something. They mean this very loosely. They say that like surfers gathering in the Rockaway, at Rockaway Beach, are studying the waves and, you know, engaged in a kind of study. They want there to be a sanctuary, like a physical space where people are meeting. And then they want it to be about coalition building, about inviting people in, building a shared movement. And I think their general idea is that this is a really important part of building a kind of shared culture, which is ultimately they argue like the basis for progress. social movement, I would say back to them, but like, what are your concrete political goals? Like, tell me your concrete political objectives? And Peter really said to me, look, the way you’re thinking about this is actually reflective of something problematic about the way the attention economy has steered us about how we think about attention, which is you think about politics um as being something related to policy. And he was like, actually, a thing that we are trying to drive home to people is that because of the way the internet has changed our society, sure, 30 years ago gathering with your group of friends to like go surfing wasn’t political, but today, he argues, it is a political act because it is materially spending time doing something that big tech cannot commodify and which a like, you know, big tech actually really they they want to suck our attention away. They want to have our eyeballs. So every moment that we’re doing something that um cannot be commodified, he argues is sort of like a really material form of resistance.

Casey Newton: 55:08 That’s interesting. I do worry that Meta will release a surfboard with a microphone and I think we need to keep an eye out for that.

Kevin Roose: 55:17 Um tell us about a couple of the other exercises you did.

Joanna Stern: 55:21 Okay. So, so these were the attention labs, the what I just described. Um, and they are free and they are like sort of the first offering. But then there were two other offerings and I felt like each incremental offering got a little bit weirder in some fun and quirky ways. Not all of which I liked but which I think it’s worth telling you about because um it’s interesting. So um the the second kind of um programming that they did is what they call their sidewalk studies. So these are also free programs. They are also built around some kind of you know act of exercise of attention like what we just described. Um, but the main difference is you leave the school to do them. So they are kind of a bit of like a um like flash mob style um attention exercise out in the world. And so the one I went to was all about taste. They have different themes. And we met in Fort Greene Park and they had us read a little excerpt from Anthony Bourdain’s Kitchen Confidential about how you know Anthony Bourdain says something to the effect of like, you know, the body is not a temple, it is an amusement park ride and like you should you know go out there and like enjoy it that way. And so um we read this, we discussed it a little bit. By the way, there were you know people, this was the most like age diverse group that I was a part of. There were people in their 70s who were there which I thought was really cool. And then we were told to walk around the farmer’s market and take in the farmer’s market as though our body was either a temple or an amusement park. And uh, you know, it was pretty fun. I I walked around. I’m like really visually taking in everything. We get back together. We’re sitting at this picnic bench and everyone kind of told a little story about their experience and you know someone some guy had like bought oysters and he shucked an oyster at the table and like handed it around someone else passed around focaccia… spread. You know, it was just kind of… I almost think of it as like a bit of a like group therapy exercise, you know, where people are sort of contemporaneously just saying, ‘here’s what I thought.’

Casey Newton: 57:11 It’s so interesting because it’s like this sounds like an exercise that you would give to somebody who had sort of like just been reunited with their human body after like sort of having like had their mind uploaded to the cloud for a couple years. You know, just like, ‘here, let’s walk you through the form. Remember lettuce?’

Joanna Stern: 57:27 Yes!

Casey Newton: 57:28 Taste lettuce!

Kevin Roose: 57:29 And so like, you know, there is something about that that is like funny to me, but like it also seems to me quite sad that like we’ve reached a place where this seems therapeutic to people, like just like, you know, like tasting a strawberry to like return to yourself. Maybe that’s where we’re at.

Casey Newton: 57:44 I think it’s where we’re at. Like, I think what is interesting to me about this is that I think the… I’m not sure whether Attention School is the right solution, but the problem seems real. Like, I don’t know many people who are like feeling great about their relationship with technology these days. And even the people, you know, who work in tech or are, you know, sort of early adopters of all this stuff. Like, I think there’s a visceral sense that like ‘this is not how I like to live.’ And for many people, I think that’s just going to be something that they deal with by like locking their phone in a box or putting on their screen time alerts or whatever sort of brute force method they use. But it seems like this is this is a more sort of robust way of like trying to retrain yourself, not just sort of fix the short-term problem in front of you. Is that a good way of looking at it?

Joanna Stern: 58:33 Yeah, I think that’s right. I mean, I think I think it really is to them less about the actual exercises of attention. I think they basically… like the people who helped form this school were a combination of like academics and artists. And I think they found this kind of exercise really fun and it was just catching on among their friends and they thought like ‘here, this is a great way that we can give people a kind of positive experience of coming together to get at some of these ideas that we’re concerned about.’ But I think the really like high-level theory that they have is like ‘we need to build communities’ and there are people right now who feel really uncomfortable with the way technology is changing us and we need to like actively start now creating a space for them. And and I think they’ve tremendously benefited from the fact that like they founded the school in June of 2023. And so I think when they started the school, they were probably thinking primarily about social media. And that is still what you hear a lot of people talk about, like doomscrolling is the like most obvious, you know, easy metaphor to grab for. Um, but I think the fact that, you know, we are seeing the rise of AI, I almost feel like the school kind of just found its moment in that it is less embarrassing today to ask questions like ‘what does it mean to live a flourishing human life? What does it mean to be a human? What is like distinctly human about the way we perceive the world?’ And I think so much of what… The AI is causing people to think about in their lives right now is like, um, you know, what can, what can I do, what can I achieve, what can this machine help me do, and then anxiety about like what I can do that it can’t do and it’s kind of pulled some attention away from this question of just like what does it mean to be, to exist as a human and the school is really interested in creating a space for that question.

Kevin Roose: 60:24 Tell us about this last exercise you did.

Joanna Stern: 60:27 Okay, so the last thing I did was actually my favorite thing and it was definitely the zaniest of all the things that I did. So, um, the school offers seminars. These are the paid, the one paid offering that they have and they, they, I just want to emphasize like they really care about making this a kind of like democratic experience that is open to everyone. But so they offer all different kinds of seminars. The seminars are like basically loosely on any topic that you could argue is like related to attention, which is broadly everything. So they have classes I saw in the past that they’ve taught on hypnosis, they have one going on right now that is about weeds, like literally invasive like flora out in, you know, our gardens and things, but the one I did was about radical imagination and I actually brought my syllabus with me because I thought it’d be fun for you to just get a taste for how seriously they were taking this and for some of the kind of homework assignments I was getting. Because there was homework, there was also reading that we got assigned and everyone in my class or the vast majority of people seemed to have like fully done all of the reading, done the homework, come prepared, just that was the most striking thing about all of these classes, people were incredibly engaged. Um, here is, here is like one prompt that I love, so this is the prompt.

Casey Newton: 61:43 Sit with yourself in silence or journal to discover a quality of yours you would like to expand, like whimsy, compassion, confidence, create a character whose defining characteristic is this quality, name them, write a short description of them, begin to inhabit them in your own body, uh, and basically that’s like come to session two as your character, uh, and then we will reintroduce ourselves.

Joanna Stern: 61:59 So, so literally the first class you show up, you’re prompted to like do all this internal work to think about the the forces that constrain your imagination. We talked about like the who is the prisoner in your… who is the prison guard in your head who kind of jails your imagination and tells you like, you know, these are things you you can’t do or these are social norms you have to follow and then we had to think about in relation to that qualities that we wanted to um maybe have more of like a sort of a parallel universe version of ourselves, what would that look like? And then literally we were told to come in the next time and we got new name tags where we like gave ourselves new names. Some people like actively like dressed up and some people really like got into the sort of improvisation of it and like performed their character like the en- like most of the class, like we were doing like a—

Kevin Roose: 62:52 What was your character?

Joanna Stern: 62:54 So, um, my character was her name was Princess Lollipop.

Casey Newton: 62:59 Wow.

Joanna Stern: 63:00 Please— And I was really, I told Casey a little bit about this, but like basically my big finding from this class that I actually found just kind of really interesting and helpful in my own personal life is that I found myself being really rigid in a lot of these classes and like kind of just getting frustrated by the nature of the exercises, the logic of the exercises, being like, “I don’t get this.” And I started to realize like, I’m not really approaching this with a sense of playfulness and humor. And so my kind of challenge for myself is like, what is a version of me that is more playful? And so, the vision that came to me was of myself as a child, like a, my six-year-old version of myself in a little tutu, and I had a funny phase, like a real phase as a six-year-old where I, I think fell in love with Candy Land and told my parents that I refused to be called Rachel, they could only call me Princess Lolly.

Kevin Roose: 63:54 I mean, I’ve never, Casey you’re more of an improv guy, but my sense is like there’s some similarity here and overlap between like doing improv, acting or comedy and like and what you’re talking about with like inhabiting a character.

Casey Newton: 64:03 Yes.

Kevin Roose: 64:05 To me it’s seeming like there’s sort of like a couple things that are coming together. One is like Buddhism, frankly. It’s like like focus on attention and where the mind goes and like regrounding yourself in the physical world.

Casey Newton: 64:20 And in the present moment.

Kevin Roose: 64:21 And in the present moment. There’s sort of like this improv, like, you know, explore your feelings, explore your imagination. There’s this sort of like tech resistance piece of it, which is like I don’t like what this technology is doing to our our brains. And um, you know, it’s it’s interesting and it makes me think about previous waves of technological change and some of the like social and cultural movements that have grown up in response to those, like during the Industrial Revolution, there were like the Transcendentalists who like wanted to like reconnect with nature because they felt like the whole economy was like getting away from the land and the farms and like going into these dehumanizing factories and they were sort of like, we want to go to Walden Pond and like write poetry and like look at leaves. And like the same kinds of things happened in the 20th century with industrialization. Like there every time we sort of make a big leap forward in technology, there is a cultural counter-movement that’s just like, wait a minute, we actually don’t like what this is doing to us and we want to like reclaim ourselves from the technology. Does that feel like, does that feel like of a piece with what you’re saying?

Joanna Stern: 65:23 I definitely think so. I mean, I think actually the an interesting thing about this particular movement, like even the language that this school, the people involved with this school, they call themselves the Friends of Attention. Even the language that they use, they intentionally relate back to the environmental movement. So these are people who are often very interested in, you know, helping people get re-enchanted with nature is the the phrase I I heard. But they they, for example, they talk about um what big tech is doing to our attention as the fracking of our eyeballs, you know? So they’re like really intentionally using this environmental language.

Kevin Roose: 66:00 I think it’s also— It’s interesting because we think of like Silicon Valley in the like 80s and 90s as a site of the counterculture, right? And like a place where a bunch of hippies would go take acid and then come back to Cupertino and make laptops. And now that that culture has grown to like take over the world, I think we’re seeing the formation of this new kind of counterculture that just rejects it completely. And I think there’s a lot of wisdom to it. You know, I think it actually—

Casey Newton: 66:27 Yeah.

Kevin Roose: 66:28 —it actually—

Casey Newton: 66:30 —is not enough to say stop looking at your phone, put your phone in jail. Totally. I think you have to give people alternatives and you have to sort of reintroduce themselves to the feelings that you get when you actually are in the present moment paying attention to the world around you.

Kevin Roose: 66:44 Yeah. I did a 30-day phone detox a few years ago and part of what I was doing was just trying to get used to the feeling of like looking at the tree, seeing the person walking down the street, seeing the bird—

Joanna Stern: 66:54 —getting bored—

Kevin Roose: 66:56 —having a spare moment.

Joanna Stern: 66:58 Yeah.

Kevin Roose: 66:59 And it’s hard. Do you feel like this was a productive experience for you? Do you feel like you have improved your attention since going to attention school?

Joanna Stern: 67:10 Yeah, I mean, I think that’s the obvious question and it’s also like an incredibly hard question to answer. I mean, I think the analogy that feels most fitting to me is the analogy of some kind of group therapy where like, you know, did I have some kind of transformational breakthrough in a month of going? Like, I would say no. I made some small discoveries about myself, like the one I described about my playfulness. I—

Kevin Roose: 67:37 I would take that into therapy, by the way. I think there’s a lot there.

Joanna Stern: 67:40 But like, you know, and I think this is true of a lot of people who go to therapy for a month. Some people come away and they are like, ‘Holy shit, that changed my life.’ For a lot of people, it’s like gradual insights. Um, but I do think that, um, I do think that what it did for me is it really made me feel like the people I was meeting were fired up and ready to be a part of some kind of social change related to technology. Like and I was really struck by how thoughtful people were, how earnestly they were engaging, how they were open-minded. I met people of all kinds of stripes when it came to their relationship to technology. There were some people I met who were part of the school, who were self-identified as sort of like a neo-Luddite movement where they were, you know, getting rid of their phones and going to dumb phones and stuff like that. But by and large, the majority of the people I met were your typical knowledge worker. They had jobs, I met a scientist who’s using AI all the time, I met a bureaucrat who works in city government. And, um, you know, these are people who plan to continue using technology, but they’re looking for a space where they can talk to other people about, um, the current moment we’re in and find meaning in it and build community and kind of slowly figure out what the next step is. we want to do next if there is political action to take.

Kevin Roose: 69:02 Or Joanna slash Princess Lollipop, thank you for telling us about your experience. I’m so glad you went to attention school.

Joanna Stern: 69:10 Thank you so much.

Kevin Roose: 69:11 I think you should go. You’ve been doing your email this whole time.

Casey Newton: 69:13 Yeah.

AI Casey: 69:14 I actually haven’t been paying attention to anything you guys said.

Casey Newton: 69:17 Just kidding.

Joanna Stern: 69:19 Sign him up!