Can the U.S. Rein in Prediction Markets? + Joanna Stern on Her Year of A.I. Experiments + Our Producer Goes to Attention School
Kevin RooseCasey NewtonJoanna SternRachel Cohn
Prediction markets have reached a scale where privileged information is becoming the edge, undermining the claim that prices represent collective intelligence. An Army sergeant allegedly connected to Nicolás Maduro’s capture made more than $400,000, while analysis of 400,000 Polymarket markets found military and defense long shots won 52% of the time versus a 14% platform average. Casey Newton’s verdict: without inside information, “you kind of have to be a sucker to participate.”
The consumer economics already resemble gambling more than reliable information production. More than 70% of Polymarket users lose money, and Kalshi recently had 2.9 unprofitable users for every profitable one; suspicious Super Bowl and temperature bets further weaken confidence. Market integrity is not cosmetic: insider advantages destroy the trust required for markets to remain “liquid and transparent.”
Regulatory pressure is rising, but the CFTC’s small size and jurisdictional fight leave enforcement thin. Proposed measures range from age verification, self-exclusion and advertising limits to surveillance of insider trading; the Senate barred senators from betting, while a Gillibrand-McCormick bill would cover legislative and executive officials. Brazil blocked 27 sites, including Kalshi and Polymarket, and France and Hungary imposed bans, while Kevin Roose put “high probability mass” on U.S. action against flagrant military or congressional abuses by year-end.
Joanna Stern’s year of AI experiments found agents and wearables progressing much faster than humanoid robots. A reporting assistant’s research and email workload went from requiring a human early in the year to, in Stern’s assessment, being 100% automatable now; persistent assistants across the Bee bracelet and Meta glasses also felt increasingly plausible. Robots coming to live with consumers, however, are “really not coming to live with us anytime soon.”
Dental AI supplied the episode’s clearest warning about monetized machine judgment. An AI overlay helped a dentist recommend four sessions of periodontal treatment costing potentially thousands, but other dentists found that better home care was sufficient. Staff later told Stern that practice owners used AI reports to question why clinicians had not drilled or sold treatments—the “fancy high-tech sheen” can turn probabilistic detection into an upsell engine.
Stern’s most useful AI was a mirror and editor, not an autonomous author or trustworthy authority. ChatGPT wrongly declared her dying praying mantis pregnant, yet helped her decide to leave The Wall Street Journal after processing her plans, projections and fears: “It kind of did tell me what I wanted.” She wrote every word of her book herself, using AI for editing, fact-checking and endnotes while relying on humans for long-form structure, illustration and fact-checking.
Attention School treats degraded attention as a collective political problem, not merely a screen-time habit. Its exercises restore perception, play and shared physical experience, while its founders cast every uncommodified moment as resistance to the “fracking of our eyeballs.” Rachel Cohn reported no transformation after one month, but found an unusually engaged community of ordinary technology users seeking alternatives before AI further reshapes daily life.
1. Prediction markets are rewarding access before insight
Casey Newton calls prediction markets one of the year’s defining technology stories: once a niche academic interest among Bay Area “absolute nerds,” they now occupy the popular imagination and advertise across New York. Kevin Roose’s early fear—that legalization would produce “a total casino”—looks less theoretical now.
An Army sergeant allegedly involved in Nicolás Maduro’s capture made more than $400,000 betting that Maduro would be out of power by the end of January. The Anti-Corruption Data Collective’s broader finding is harder to dismiss: across more than 400,000 settled Polymarket markets over five years, military and defense long shots won about 52%, versus 14% for the platform overall.
Kevin Roose’s Strava analogy captures the escalation: military activity was once exposed inadvertently through exercise heat maps; now personnel may be directly monetizing operations they participate in. Newton’s sardonic incentive test: why “collect your freaking paycheck like a chump” when privileged information can be wagered online?
2. Manipulation and misinformation corrode the product together
At Paris Charles de Gaulle Airport, the recorded temperature jumped from 18°C to 22°C on April 15 amid suspiciously timed Polymarket bets and an allegation that measuring equipment was interfered with. How it was tampered with remains unknown.
The photograph seemingly showing someone heating the sensor with a hairdryer was itself AI-generated and circulated in a prediction-market Discord. Roose’s correction matters: the episode is simultaneously about possible market manipulation and “slop and disinformation”—even the supposed evidence of cheating was synthetic.
Super Bowl markets on Bad Bunny’s songs and celebrity guests created another obvious information asymmetry: performers, rehearsal attendees or entourage members could trade against outsiders. After enough such incidents, Newton argues, ordinary participants will conclude that “you kind of have to be a sucker” to bet without inside information.
3. The house is winning while trust is disappearing
More than 70% of Polymarket users lose money, according to reporting cited by Roose. At Kalshi, recent data showed 2.9 unprofitable users for every profitable user—the relevant baseline for anyone seeing ubiquitous ads and imagining “a quick buck.”
Roose links those losses to the purpose of insider-trading law: the harm is not merely transferring money from one participant to another. Persistent unfairness destroys the confidence that lets a market remain “liquid and transparent,” eventually driving away recreational users and weakening prices as information signals.
That creates a direct conflict with the industry’s pitch. These markets are supposed to discover “the true price of things” through collective wisdom, yet their most conspicuous winners increasingly appear to be people who can alter an outcome or know it in advance.
4. The regulatory gap is structural, not accidental noise
States have tried to ban prediction markets, but the CFTC has sued to defend its exclusive jurisdiction. The hosts’ framing is stark: the federal regulator says the field is its domain while showing limited appetite and capacity to police it.
Roose says the CFTC is only a fraction of the SEC’s enforcement scale and inherited prediction markets through a “historical accident”: Kalshi’s products qualified as futures contracts. Newton would not be surprised if platforms lobbied to remain there, comparing the preference with crypto firms wanting the CFTC rather than an SEC that is “really good at their jobs.”
The Senate unanimously barred senators from prediction-market betting. Senators Kirsten Gillibrand and Dave McCormick also introduced a bill covering legislative and executive officials; Roose immediately asked whether Senate staff could do it, leaving other privileged actors as an obvious question.
Brazil blocked 27 sites, including Kalshi and Polymarket, as illegal gambling; France and Hungary also imposed bans. America’s contrasting posture, in Newton’s caricature: “For there is money to be made. Go forth and make it.”
5. Useful markets require both gambling controls and enforcement
One early prediction-market originator argued that insider trading improved prices: Bad Bunny’s entourage or military personnel could reveal information society would otherwise lack. Roose calls that “a beautiful theoretical construct” with “zero chance of surviving contact with the real world”; Newton says the actual incentive is to betray friends, family, coworkers and country.
Roose separates two harm classes. Gambling controls should include self-exclusion, mandatory age verification and advertising limits, preventing a future in which Kalshi becomes “the hottest thing” in high schools and 16-year-olds accumulate debt betting on the Super Bowl.
Newton says market integrity needs a “big, bad regulator” actively surveilling trades and removing bad actors. He argues Kalshi and Polymarket should welcome that oversight because their prices might then become useful rather than reflecting whoever can manipulate a sensor or exploit confidential access.
Roose still wants the original knowledge-production vision: monetary incentives could fund independent polling and research better than today’s institutional model. By year-end, he assigns high odds to rules targeting blatant congressional and military abuses, especially because wagering on overseas operations creates a national-security problem.
6. Stern’s experiment separates near-term tools from theatrical promises
Joanna Stern built I Am Not a Robot around a simple challenge to executive rhetoric: if AI will change jobs, healthcare, transportation and “the fabric of our lives,” she would test those claims across an entire year. The result is deliberately time-bound—a snapshot readers can revisit in five or 10 years to see where she was “totally right” or wrong.
Her experiment ranged from an AI companion named Casey, described as shallow and full of “robo-horniness,” to Waymos, customer support, medicine, parenting, meal planning and book production. The point was not that every tool worked, but that the present contains things “clearly hype,” “sometimes quite good” and sometimes “quite terrible.”
Humanoid robots landed firmly in the hype category for domestic use: “They’re really not coming to live with us anytime soon.” Stern nevertheless finds their training compelling and dystopian—machines must observe humans folding laundry, washing dishes and performing other mundane physical tasks.
7. Agents and persistent wearables moved fastest during the year
At the year’s start, Stern hired a reporting assistant for research and email tasks. By midyear, Perplexity Comment was performing much of that work reasonably well; by the interview, she judged that an agent could do “100% of those tasks.”
Wearables also surprised her. No single device completed the vision, but elements from the Bee bracelet, Meta glasses and other products suggested an AI assistant could persist throughout the day on something worn rather than opened on a computer.
That persistence already raised a social boundary: the bracelet’s apparent recording and transcription prompted Stern’s Wall Street Journal colleagues to insist, “Please leave your bracelet at the door.” Her boss repeatedly told her, “Do not wear that in here”—a useful boundary on ambient assistants before their technical promise is mistaken for permission.
Parenting supplied a cleaner warning. When Stern’s son’s praying mantis turned brown, ChatGPT live mode enthusiastically announced it was pregnant; the mantis was dying. For her four- and eight-year-olds, AI literacy therefore starts with exposure plus the recurring lesson that the system can be “fully wrong.”
8. Dental AI turns detection into a sales incentive
A dentist showed Stern a Pearl AI overlay that placed vivid boxes around cavities and highlighted plaque buildup, then recommended deep cleaning and periodontal treatment across four sessions. The work might not be covered by insurance and could cost thousands of dollars, despite Stern having no comparable history or troubling symptoms.
Other dentists saw the same AI reading but judged the condition “really not that bad” and recommended better home care. Stern never received the periodontal treatment, making the disagreement more consequential than a routine false alarm.
Anonymous dental-office workers then described the organizational mechanism: dental service organizations could inspect AI reports and ask clinicians why a cavity was not drilled or periodontal treatment was not sold. The system did not merely support diagnosis; it gave owners a standardized dashboard for pressuring treatment volume.
Stern preserves the medical nuance. Detecting tiny abnormalities can be valuable in breast-cancer screening, especially given her family risk, but more sensitivity is not automatically better in every context. Roose’s darker formulation: AI’s authority can make an unnecessary service feel like something “a human would have missed.”
9. The best chatbot advice reflected Stern’s own accumulated evidence
When Stern considered leaving The Wall Street Journal after 12 years, colleagues hedged; ChatGPT said, “I think you should go. You should quit.” She had supplied notes, financial projections, fears and risk-reduction plans, letting the system organize evidence she felt too anxious to interpret.
Her conclusion is deliberately double-edged: AI is “this mirror,” and “it kind of did tell me what I wanted.” The decision has worked so far, but she concedes, “Had it not, I would say this stuff is stupid”—a reminder that perceived wisdom is often judged retrospectively by outcome.
Stern wrote every word of the book, using AI for copy editing, fact-checking assistance and an endnotes process she says would otherwise have been impossible. A human editor repaired long-form structure after the model responded, “This is great. This is the best book I’ve ever read”; humans also handled illustration and fact-checking.
She resists a simple gender narrative despite figures showing men 22% more likely to be heavy workplace users and 61% of women expecting more harm than good. Industry composition partly explains adoption, while Stern sees the age divide as more urgent: younger workers blame AI for scarce jobs, although she stresses that causation remains unclear.
10. Attention School rejects productivity as attention’s only purpose
Brooklyn’s Struthers School of Radical Attention serves people from 7 to 70, though evening and weekend programs largely resemble adult continuing education. Most offerings are free; the seminar Rachel Cohn attended cost The Times $250.
The school does not prescribe phone abstinence or treat technology as an enemy. It asks participants to study and practice attention beyond narrow focus and productivity, while confronting systemic harms and the “commodification of our attention.”
In one paired exercise, one person could speak but not question, while the listener could ask questions but not make affirmative statements. Even as a professional interviewer, Cohn found the constraint awkward and clunky—which was the point: it exposed habits normally hidden inside conversation.
A Georges Perec-inspired exercise asked participants to “exhaust” a neighborhood space through observation. Cohn recorded Sweetgreen workers, trash and passing pant legs; when participants shared one line each, they constructed a collective place and revealed perceptual differences, including one woman’s realization that she attended intensely to sound rather than sight.
11. Attention becomes resistance when unmonetized life forms community
The school’s movement rests on study, sanctuary and coalition building, but Cohn repeatedly pressed for concrete political objectives. Co-founder Peter Schmidt’s answer challenged the premise: politics need not begin with policy when gathering to surf, observe or talk spends time that technology companies cannot monetize.
A sidewalk study made that theory bodily. After reading Anthony Bourdain’s contrast between the body as temple and “an amusement park ride,” participants explored a farmers market, then shared oysters, focaccia and perceptions—an exercise Roose likened to reintroducing a cloud-uploaded mind to lettuce and strawberries.
In a paid radical-imagination seminar, participants identified the “prison guard” constraining their imagination, then created characters embodying qualities they wanted to expand. Cohn revived her six-year-old alter ego, Princess Lollipop, after realizing that rigidity and impatience were preventing her from approaching the program playfully.
Roose connects the school to Buddhism, improv and earlier countercultures such as the Transcendentalists’ response to industrialization. Newton adds Silicon Valley’s former countercultural roots and the newer counterculture rejecting its dominance. Its “Friends of Attention” deliberately borrow environmental language—“re-enchanted with nature” and the “fracking of our eyeballs”—to describe extraction and repair.
Cohn’s honest assessment: one month produced no transformational breakthrough, only gradual insights resembling group therapy. Yet the engaged mix of scientists, civil servants, knowledge workers and a minority of neo-Luddites convinced her that people want a place to ask what a flourishing human life means while continuing, in most cases, to use technology.
Full transcript
Well, Kevin, very nice to be with you here in New York City.
Reunited at last.
Are you having a great time in New York this week?
I am. Yes. I got to see some friends last night and go to Brooklyn. I'm not seeing a show, but I am staying in Times Square, so I feel like I'm seeing a show every morning.
Wonderful. Well, I've also been out on the town, going to cool parties and meeting new people. I met this gay guy the other day who said he was a listener to the show.
Oh.
And I said, “Oh, hi.” And he said, “Oh, you're from Hard Fork. Which one are you?” And I said, “I'm the gay one.” And he said, “I thought you both were gay.” And I had to explain to him that straight people also perform a cappella. That blew his mind. It completely blew his mind.
Wow.
But, yeah.
I feel like I have talked about my wife a non-negligible amount on this show.
Yeah. It's reaching Borat levels of talking about one's wife. And yet still, people don't always pay close attention to what they're listening to, and we're going to get into that later in the episode.
Yeah.
Yeah.
Is it because they think people sense some sort of chemistry between us? Is that a thing?
No, he specifically said that he did not think that we had any chemistry.
Okay, so we're just platonic.
Yeah. No, it's completely platonic.
Yeah.
I think it's great, though, because it just goes to show you can listen to a podcast for a long time and still not really understand anything you're listening to. We should keep that in mind as we plan our segments. You know?
That's very good.
It's not all going to come across.
That's incredible.
I'm Kevin Roose, a tech columnist at The New York Times.
I'm Casey Newton from Platformer.
And this is Hard Fork. This week, prediction markets are out of control. Is Congress about to rein them in? Then Joanna Stern returns to the show to discuss her new book on turning her life over to a chatbot. And finally, Hard Fork's own Rachel Cohn returns to the show to talk about her first month at Attention School.
She has our full attention. She does.
1. Prediction Markets Hit the Mainstream
Well, 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.
Oh, thank God. My bet is going to pay out on Kalshi.
It is, because as I was looking at the news of the week, it seemed like everywhere I opened up a browser tab, Kevin, a prediction market had been in the news, often not for a great reason.
Yeah, I mean, this has been one of the tech stories of the year: the absolute meteoric rise of prediction markets in the popular imagination. I've been walking around New York for the past day, and ads for these prediction markets are everywhere you look. It has taken over culture in a way that I'm not sure I would have predicted.
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.
Yes.
So you may have seen that about 2 weeks ago, we learned about an Army sergeant who was allegedly involved in the capture of Venezuelan President Nicolás Maduro and made more than $400,000 placing bets on markets related to Maduro being out of power by the end of January.
Oh, boy.
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 5 years, and they found that long-shot bets related to military or defense had an average win rate of about 52%. Now, keep in mind, the average win rate on this platform is 14%. So if you go and see a big bet on one of these sites about the military, somebody might be betting on information that they really should not be.
Yeah, I mean, this just seems like something that is obviously more widespread than we know about. If you have material, nonpublic information about a military operation, what are you going to do? Sit there and collect your freaking paycheck like a chump? Are you going to go online and make some dough betting on the outcome?
You know, I remember—you know the app Strava, which logs your runs—
Yes.
—and your bike rides?
I remember this.
They got in trouble once because they were publishing these heat maps, which inadvertently revealed the locations—
I remember this.
—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.
Yes.
Another great insider-trading scandal, I wonder if you saw, 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, which coincided with a surge in suspiciously well-timed bets on Polymarket.
I love this one because my understanding—and correct me if I'm wrong—is that there's this prediction market for the temperature in Paris. The way that they gauge this is with a series of thermometers—
Yeah.
—that are placed in various parts of Paris, and this insider trader allegedly basically took a hair dryer or some other heating device and held it next to one of these sensors.
Okay, so—
Can you just tell me what happened here?
Yeah, yes. So this was also my understanding of what had happened until I looked into it, and it turned out 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.
I fell for that one.
So how did they actually tamper with the temperature sensor?
That part is still unknown, but what we do know is that on April 15, the recorded temperature jumped at Charles de Gaulle from 18 degrees Celsius to 22 degrees Celsius. This just feels like an incredible crime of opportunity to me. If you could walk up to a thermometer with a hair dryer and make yourself $14,000, you might do it, knowing you.
Yeah.
2. Market Integrity Starts Cracking
But this is a problem, Kevin, because not only are people essentially defrauding the other people who are participating in these markets, but I just think it's really bad for the markets themselves. 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.
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 insider information, that's going to dissuade them from doing it. I was thinking about this after the Bad Bunny halftime show at the Super Bowl—
Mm-hmm.
—where there were lots of prediction markets on what songs Bad Bunny would perform and various other things.
Which celebrities would appear.
Celebrities would appear, and there were active prediction markets. It turned out that probably some of the people betting on those markets were part of the halftime show or had watched the rehearsals or something. After enough of these incidents, you kind of have to be a sucker to participate in these markets without insider information.
Yes.
And what happens if the normal people who just want to go online and gamble a little bit of money on something go away because they think it's rigged?
Absolutely. And by the way, I have to say, after that halftime show, I got so into Bad Bunny.
Me too.
I don't care that I'm the last person to figure this out, okay? “Tití Me Preguntó,” incredible song.
It's a bop, yeah.
It's a bop. Okay. But to the exact point that you just made, most people who bet on prediction markets lose.
Mm-hmm.
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 happen to see a lot of ads for these platforms, and you think, “Hey, I’m going to go turn a quick buck.” At the very least, know that the odds are against you.
Yeah. It speaks to the reason why we have insider trading laws for stock markets. It’s not just because when you insider-trade, you are 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.
Yes.
So I think these insider-trading scandals just show that 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 need someone to step in and say, “Okay, we’re going to establish some rules so that we can protect the integrity of these markets.”
Yes. 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.”
3. Regulators Enter the Fight
I think there are a couple of systemic issues here. One is that the CFTC is just quite small.
Yeah.
The CFTC, relative to the SEC, which regulates the stock market, is just a tiny fraction of the enforcement team. It was not really meant to regulate prediction markets. It kind of ended up there via this historical accident where Kalshi was doing 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, as this stuff gets more widespread, it should move toward something like the SEC—
Yeah.
—which just has a lot more resources to investigate insider trading.
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.”
Right.
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—
Can their staff do it?
Kevin, please don’t get way ahead of yourself. We have to see if we accidentally destroy capitalism by preventing the senators from betting on prediction markets.
Can Supreme Court justices bet on the outcome of Supreme Court cases?
You know what? I bet when they do, we’re going to hear about it in ProPublica. They seem very good at that sort of thing.
So there’s a little bit more action here in the United States. Two U.S. 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. So that would presumably prevent the president from betting on prediction markets, if that’s something that he’s been considering.
We’re also seeing some action in other countries. Brazil has now blocked 27 sites, including Kalshi and Polymarket, for offering what they’re just calling illegal gambling. France and Hungary have banned them as well.
So, Kevin, 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.”
Yeah.
While America says, “No, no, my friends, for there is money to be made. Go forth and make it.”
Yeah. It’s really—this topic is so interesting to me because do you remember when I went to that prediction-markets conference?
Mm-hmm.
I’m not a guy who likes to do sort of, “Remember when I saw Green Day at the corner bar and they were playing for 16 people, and look how cool—” But I do feel like I saw the equivalent of Green Day playing the corner bar.
The people who were interested in prediction markets several years ago were these absolute nerds in the Bay Area who were sort of involved in the kind of play-money prediction markets. They were not businesses that had billions of dollars. It was 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, I imagine this is just going to become a total casino.”
I remember arguing with someone there about insider trading, and this person, who was one of the people who were sort of originators of this movement, was 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.
So if you have members of Bad Bunny’s 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.
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.
Yeah. No, because it turns out what you are incentivizing everyone in the world to do is just to betray those closest to them.
Yes.
Betray your friends, your family, your coworkers—
Your country.
Your country. Just do it all for a quick buck.
Yeah.
So I think we should take this to, what do we do about it, Kevin? I’m curious what, if anything, you think we should do.
I just think this is one where we need a new way of regulating these. Right now, these companies are self-regulating. 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 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.
Yeah. I think there are two big categories of harms here that just have to be addressed differently. There’s a set of harms related to gambling, right?
Yeah.
Some people become addicted to gambling, and I think these prediction markets are set up such that people could develop that kind of problem. 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 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 the high schools where Kalshi is the hottest thing and there are 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 going to lead us to a good place.
But then you also just have the market problems, which is what you’re talking about: Clearly, insider trading is just an inherent feature of these platforms. So we do need a big, bad regulator that is actively surveilling these platforms and trying to get the bad actors off the platform.
And if I were Kalshi or Polymarket, I would welcome that, because then my prediction market might actually be worth something, you know?
Yeah. Yeah.
Because it wouldn’t just all be people holding up hair dryers to the temperature sensors at Charles de Gaulle Airport. Which didn’t actually happen.
Yeah. 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 a way of incentivizing the production of good knowledge.
One of the things that the proponents of prediction markets were saying is, right now we have polling for public sentiment or elections, and people are not incentivized to go out and do their own polls because they think they can do a better job than Gallup or Ipsos or whoever the polling organization is.
But if you have prediction markets where people are 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 a more flourishing system. And I would just like to see that kind of thing happen.
Yeah.
But it seems what we're getting, actually, is just people betting on the military operations that they're involved in.
I am open to the idea that these markets will eventually have their uses, but currently they're just so woefully underregulated that I think what we should expect, if nothing else changes, is to just keep reading more stories like this.
Yeah.
So maybe to end this, Kevin, what is your prediction as to whether these markets actually get regulated, let's say, by the end of the year?
I think I would put a high probability mass on that. I think that, at least when it comes to the obvious and flagrant abuses of, 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, just for national security reasons, they will do something about that. You can't have members of the military betting on raids and operations in foreign countries.
Yeah. I think 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 maybe those rules will begin to rein this in. But I do hope it happens.
Yeah. You know, I have never bet on a prediction market. Have you?
Didn't we used to bet on the fake ones?
The fake ones.
Yeah.
But I've never bet real money. I've never felt the frisson of—
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 true. It's priceless. You can't put a price tag on that.
Priceless.
4. Joanna Stern Tests AI
So for years, Kevin, you and I have both been friends with the great technology journalist Joanna Stern.
Yes, former Hard Fork guest.
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 that we talk about every week on the show.
Yeah, so I would put her book in the tradition of immersive journalism, where you just explore something by 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 the companies that are making it.
Absolutely. Joanna is not a hypester. I think that she is most interested in technologies that are entering the mainstream and wants to know how they change our lives. And so she decided to see: How much can I change my life in 1 year by applying AI to various tasks? The results were fascinating, and I think we should bring her in here and talk about it.
Let's do it.
All right. Let's bring in Joanna. Joanna Stern, welcome to Hard Fork.
I'm here.
You did it.
This is the moment I've been waiting for. Truly. 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.
Yeah.
You guys aren't often—well, you're in person, but not on this side of the country.
This is a strange, bicoastal taping for us.
You've never been this close together on this side of the country.
No. The only other time was a Southwest flight once in 2023.
And we'll never forget it.
I think it was Spirit, and that's why.
RIP.
RIP.
Joanna, let's start with the elephant in the room, if we could. There is a replica 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.
Casey, I am so happy you brought this up because I brought him.
Oh, did you really?
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.
Wonderful.
He doesn't look like you at all.
No.
But let's bring him up.
Oh, he's handsome as hell.
What do you think?
I would say Casey is looking great, kind of a preppy look with a nice red sweater—
He's jaw-maxing.
Yeah. He's jaw-maxing. He has a dull, vacant stare.
Casey, AI Casey, I want you to meet my friend, real-life Casey.
AI Casey
That sounds like you're excited about introducing me to your friend Joanna. I'm looking forward to meeting them soon.
No, you're meeting him right now. Say hi, he's here.
AI Casey
At a museum with you, remembering our last visit.
You are changing the topic.
Men don't listen.
But this man does listen. Anyway, I wanted you to know that I did not pick the name Casey.
Oh, you didn't? Okay. That was my curiosity.
But when that name came up, I was like, “I've never met a Casey that I didn't like.”
Aw.
And honestly, I think you're the only Casey I've really known. I had a friend in camp, a woman named Casey.
Uh-huh.
I liked her, too.
And she's here right now. Let's bring her in.
Casey from camp.
Nope. Okay, not here.
I want to put a pin in the AI relationships that you had because your book is so much bigger than just the 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, what was your motivation for doing this experiment?
Primarily, it was what you guys talk about on this podcast so much, and what you hear from so many of these tech executives: AI is going to change our lives, the fabric of our lives. It's going to change jobs, it's going to change health care, it's going to change transportation. We hear about it from all these different things, and yes, we're very clouded right now in the AI model race and the chatbots that live on our computers and the agents.
And that is in this book, to be clear. But I was like, what about the fabric of our entire life, right? You have all of these pitches coming from the humanoid robot companies, the self-driving car companies, the chatbot relationship-coach and therapist companies, all of these things, and I was like, “I’m going to just test it all. I’m going to 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?
It’s going great.
I think we actually have a little bit of a similar approach: 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, on the flip side, quite terrible. Can I capture that, see where we are now, and then maybe we’ll pick up this book in 5 or 10 years and be like, “You were totally right about something. You were totally wrong”?
5. AI Faces Its Reality Check
What is something that you left the book thinking, “This is all just hype right now. This actually does not have any ongoing utility in my life”?
Humanoid robots. I continue to follow this story because I love it, and I just started a new company, a new newsletter, and a new video channel. I think humanoid robots are, 1, really fun to cover, and 2, I think we’re going to watch this progression over the next couple of years. I would love to be the person who’s documenting a little bit of this. But gosh, this promise that these robots are coming to live with us—they’re really not coming to live with us anytime soon.
Yeah. Humanoid robots are very good for the sole purpose of making YouTube videos about humanoid robots. This is their actual utility.
First, do not spoil my new business plan, okay?
Okay.
That’s the new business plan. That’s what we’re doing at The New Things. 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 us folding laundry, see us doing the dishes—
See podcasting.
See podcasting. But they’re actually good at podcasting. It’s not a physical thing, right?
Yeah.
I mean, you guys—
No, this is very physical.
This—
Yes.
I train like a performance athlete, Joanna, okay? This is my Olympics. I’m doing it right now.
I can tell. You guys have perfected this.
Thank you.
This is what peak male performance looks like.
Literally.
Yes.
Drink it in.
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 caught you by surprise where you were like, “Oh, this is farther ahead than I thought”?
Two things. One was that 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. I tell the story of hiring this reporting assistant at the beginning of the year. I needed her to do lots of research tasks, send emails, et cetera. By the middle of the year, that was pretty good on its own, right? Perplexity Comment had just come out, and so I started really hammering on that and having it do a lot of the tasks she was doing. But 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. They might not be completely AI wearables, but the 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 B Bracelet, I tested the Meta glasses, all of these things kind of coming together. I was pretty surprised at how good they’re getting.
Mm.
Mm.
There’s a funny scene in the book where you’re going into a meeting with your Bee bracelet on, which I imagine is recording and transcribing everything you hear, and your boss, or someone you worked with at the time—
Yeah.
—was like, “Can you take that off?”
Yeah. No, everyone at the Journal, when I was writing this, would know: “Please leave your bracelet at the door.” My boss was literally, every time—
You were wearing a wire.
—he’d be like, “Do not wear that in here.”
Yeah.
I’m actually very sad that you and I never worked in the same office, because I would just love for you to be crashing into the office with a new stunt every week, some horrible new device that is violating some sacred principle of human existence. But, you know—
I know. I’m not sure how the Wall Street Journal’s functioning without me right now. No stunts, you know?
No stunts.
I’m curious, as a parent, how you’re thinking about AI now, 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, and learn things?
When I was writing the book, my kids were 3 and 7. Now they’re 4 and 8. Right now, I think it’s important, even at this age, to start talking about AI, and there are a lot of examples of this in the book that are hilarious but that I thought were really great examples.
There’s one example in the book where my son had a praying mantis, and the praying mantis started turning brown. He’s like, “What’s wrong with my praying mantis?” So I took out ChatGPT live mode. I told him, “Ask ChatGPT,” and ChatGPT was like, “This is amazing. The praying mantis is pregnant.” My son is super excited. He calls my dad. He’s really excited. I was like, “No, it was dying,” right?
Let’s just say the prayers weren’t working for that mantis.
And ChatGPT was fully wrong, right? I think that was an important lesson, and it’s always going to be an important lesson.
Let’s clarify this right now. What color does a mantis turn when it’s pregnant?
Casey, look it up.
All right. I’ll be right back.
Look it up.
I don’t know if it does change.
6. AI Upsells Dental Care
I want to talk about your experience with dentistry, which seemed quite maddening. So you go to the dentist, and—
I went to a dentist, yeah.
—and they use a system that has a sort of AI overlay over your X-ray. While it seemed clear that you have 1 cavity, your dentist goes further and says, “Based on the AI recommendation, we’re going to recommend this complicated, expensive, multisession therapy for your gums.” Tell us what you did next.
Yeah. I love that you brought that up, as I haven’t talked a lot about it. I became obsessed with reporting that topic. Obsessed.
Mm-hmm. Mm-hmm.
I talked to every dentist that I knew, which turns out to be a lot. Similarly to how AI is being used in radiology for breasts or gallbladder, et cetera, it’s being used in dentistry. Honestly, it’s happening almost everywhere. There are so many dental practices across this country that are using tools called Pearl AI or Overjet. 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.
For deep cavities, it puts a big box around them. It’s red. It scares the crap out of you, and you’re like, “Oh, no, I’m going to need bad drilling.” Then there’s this option where they can turn it on and show you other sorts of buildup and plaque. I go to this dentist, not even on a reporting trip, and I say, “Oh, wow, she’s got Pearl AI.” I perk up in my chair, and I’m like, “Show me.”
You’re like, “I can expense this dental care now.”
It’s a book expense.
And it shows that I have a lot of plaque buildup. She says, “We have to do a deep cleaning. We have to do this periodontal treatment. It’s going to be 4 different sessions.” And I’m like, “That’s weird. I’ve never needed this before. My teeth aren’t really bothering me.” Do you ever go to the dentist and feel really bad about yourself?
Yeah. Oh, yeah.
You’re like, “Oh, my teeth are dirty.”
They’re like, “Do you floss 4 times a day?”
Right. Yeah. You’re just like—
“What kind of person do you think you’re talking to?”
Yeah. They’re like, “Your mouth is dirty.”
Dentists believe that people spend approximately 8 hours a day on oral hygiene. That’s how they talk to you.
They talk to you—
Yeah.
—and they’re like, “I know you had candy 3 times—
Yesterday.
Well observed.
You know?
Mm-hmm.
Anyway, I came out of there feeling terrible about my mouth, feeling like, “Oh, my gosh, I might need these 4 treatments,” which they couldn’t assure me would be covered by insurance anyway, so it was going to cost thousands of dollars. Then I started going to these other dentists, and they’re like, “Yeah, no, I don’t see that.” They did do some measurements, and they said, “No, the data also shows that it is bad. It’s really bad. You need these.”
And so the story goes, 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 lo and behold, I never had the periodontal treatment.
So I started doing the reporting, and people working in dental offices who didn’t want to be named because they were worried about their jobs started 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 not-terrible cavity,” whatever it was on the level. “Why didn’t you drill it?”
Mm.
Mm.
“Why didn’t they do—why didn’t you sell the periodontal treatment?” 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 this: They are using AI to try to upsell you on dental procedures.
Yeah, the reason it struck me so much is that, so often, when we hear about AI and diagnosis, it’s this miracle story of, like, all of a sudden we can detect pancreatic cancer a year in advance. In your book, I feel like I saw the dark side of that, which is that it’s going to have this 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.
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 my 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. I think people are going to listen to this and think I’m disgusting.
Listen, if you’re wondering, Joan has very fresh, minty breath, and, as far as we can tell, her mouth is doing great.
Excellent oral hygiene.
Yeah.
Totally excellent. I need to do teeth whitening. Great. We should get a teeth-whitening sponsor right in there.
7. AI Advises a Career Leap
There’s a story that you tell toward the end of the book where you’re thinking about your career, considering whether to leave the Journal after 12 years and do something on your own. You say that you asked a bunch of colleagues whether you should quit your job, and they all hedged a bit. Then you asked ChatGPT, and it said, quote, “I think you should go. You should quit.” What did you learn from that experience?
Well, I thought it was a little bit of a full-circle moment because the whole book I am saying that AI is this mirror, and it’s going to tell you basically what you want. In some ways, it told me what I wanted, right? I knew somewhere deep down, and people kept saying, “Trust your gut.” I was so clouded with anxiety that I did not know what my gut wanted. I could say it wanted a burrito, and that was it, right? 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 form, and just thought, “Okay, let me 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. It told me that there was enough, that I had done enough to lower the risks. I had a good plan in place. I had this book coming out, and I trusted it.
It also came full circle: This is a mirror. It 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.
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 and go independent.”
You might have.
Yeah.
You might have been that bold. I actually do think you’re one of the humans who has been that bold—you and Kara Swisher. Yeah, but it’s unclear. Are you guys robots? We’re not sure.
We’re not clear on that either.
We’re not clear on that. Here, you can wear this pin, but I’m not sure it’s true.
What does it say?
What does it say?
Casey, I brought you guys pins.
Oh, “Verified human.”
“Verified human.” Wow.
That’s so nice.
These are the hottest—
So it’s like—
…AI wearables, okay?
Yeah.
It’s like the analog version of the world orb.
The orb.
Yeah. Is this recording everything—
Yeah.
…we say at all times?
Yeah, these have microphones built in, and it absolutely scans your iris to prove you’re a human.
That’s great.
Yeah.
I want to ask you about the geographic divide when it comes to AI. You live here in the New York area, and we’re out in San Francisco. Out by us, it’s 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. Did you feel that when you were reporting? You also traveled around a little bit.
Let me tell you about a place called New Jersey.
Mm-hmm.
That’s where I live. We live on the cutting edge in New Jersey, okay?
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. 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.
But I did feel that throughout the year, when people would say, “Oh, you’re working on a book about AI,” they would come up to me at barbecues and start telling me about their experiences with AI, how much better something had gotten. I have a number of friends who work in the legal field, and they would say, “Oh, we’re so scared of it, but also it’s really crazy what this unlocks.” Claude really caught on in the last 6 months while I was writing this, and I was hearing a lot about that.
Look, I realize that it’s a bit odd to go so deep on a topic like this and say, “I’m writing it for the masses,” because clearly I am not the masses. They’re not doing this. But I wanted to live at that cutting edge and be able to tell it for those people.
And I will say a number of the real people I 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 were spread out. I was trying to source that way.
Yeah.
I wanted to ask about another divide, which is the gender divide. There was a great story in Bloomberg last week from Issie Lapowsky called “The Messy Reality of AI’s Much-Discussed Gender Gap.”
Mm-hmm.
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 cheating when they use it. Another poll found that 61% of women expect AI to do more harm than good in their lives. I’m curious what you make of that gap, and if you’ve felt any of those feelings in your own work with AI.
Well, I thought you were going to bring up Reese Witherspoon.
We could also bring up Reese Witherspoon—
…who recently encouraged women to take up AI because, if they don’t, they’ll be left behind.
Right.
And Sandra Bullock, I think, was saying something similar that same week.
Yeah.
Actually, going back to the sourcing thing, a lot of my sources were women.
Mm.
They included women who were having relationships with AI, women who were speaking out against some of the dentistry stuff, and women who were using it in schools. I don’t know if I totally saw that. I think the feelings about AI are very gendered, but also a lot of people just hate AI, and they’re men and women.
Yeah, for sure. Yeah. I also think it’s related to the industries where AI is seeing the most—
Yes.
…and fastest adoption, like programming—
And harm.
Which is, yeah, and harm.
Right.
With programming—
Yeah.
—it’s 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 huge Claude swarms to do their engineering projects are men because, in part, that’s just a more predominantly male industry.
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? Is it the Alphas?
Alphas.
Mm.
The Alphas. I think that’s where we’re going to see it, and I don’t know if it’s going to break down by gender because some of those people are just furious that this exists because they can’t get a job.
Yeah.
Or they blame it because they can’t get a job, and we don’t totally know the causation there, but that’s my bigger interest. I would have loved to have more on that in this book.
Yeah.
Sequel potential.
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: What did you let AI do for you when it came to this book, and what did you preserve for yourself?
I want to ask the question back at you, but the first page—or 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, a 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.” And I was like, “No, I don’t know if you know how to structure long-form writing.” Thank God I had a human editor.
All the illustrations were by a human illustrator, Jason Snyder, who was amazing and just made this book come to life.
I had human fact-checkers, but I did use a lot of AI for fact-checking. The notes process at the end—the endnotes process—I could not have done without AI. So there were lots of little ways of augmenting or adding to the writing that I used, 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 are these journal entries. It’s very personal, and I hope somebody said it was witty in a review. That was nice.
It’s 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.
See? Thank you.
I did not feel like I was reading Joanna Slop. I felt like I was getting the real deal.
Thank you very much.
Right. Yeah.
Joanna Slop is a great term. We could just sell that. We can sell that bitch.
That could have been the name of your new media company.
That could be the name of my OnlyFans.
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, and neither are we.
Yeah, that’s why we need to wear our pins.
Okay.
That’s right. Human verified.
But you don’t have to put it—That is a nice shirt, and I wouldn’t want to ruin it.
Thank you.
Just put it in the pocket.
You know, this one’s not so nice. I’ll just stick it there.
8. Rachel Goes to Attention School
Well, Casey, have you noticed that Rachel Cohn, our wonderful producer, has been paying very close attention in meetings recently?
You know what? I have. It seems like she’s really stepped up. Do you think something’s changed in her life?
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. 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.
Yeah, I think there is a sense that the technologies 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.
Yes. So Rachel went to something called the Struthers 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.
Now, is it open to people who just want to pay normal attention, or do you have to practice radical attention?
It’s only radical.
Okay.
Yeah. Go big or go home.
I see.
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.
Let’s bring her in.
You’ve heard of “How Stella Got Her Groove Back.”
This is how Rachel—
This is how Rachel—
—got her attention back.
Exactly. Let’s bring her in. Rachel Cohn, it feels weird to welcome you to Hard Fork, a show that you produce, but hello.
Hello.
It’s nice to see you—
Nice to—
—on this side of the microphone.
I know. It’s also nice that we’re all in person today.
It is.
It really is.
It’s 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, but first I want to know: What is this school? Did they make you shave your head or receive any kind of permanent markings on your body?
And is there any multilevel marketing involved?
Great questions. No, I still have all my hair. It only cost The Times $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 elementary school, school for kids. This school is advertised to people of all ages. They’ve had people as young as 7 and as old as 70 come through their programming. But primarily, they’re offering programming—a combination of classes that I’ll get into—in the evenings, so after work hours, and on weekends. This is mostly, in my experience, continuing education for adults.
All right. Well, sounds like they have a big addressable market with the sort of 7-to-70 platform.
Yeah.
As a businessman, that appeals to me.
And is the stated goal of the school to fix people’s attention if they feel like they have lost it due to technology? Is it to cultivate new ways of paying attention? What is the problem they’re trying to solve?
Yeah. So this is a great question, and this was actually a little bit hard to pin down because the school has its own kind of jargon that I think can be a little bit hard to make sense of.
But what the school would say is that they are primarily a school for the study of attention and what they call the practice of attention. The practice is a critical thing because what the school has really built out are these kinds of attention exercises, and I want to get into some of them with you guys.
Basically, they are exercises where you are using your attention in a nontraditional way that you would not normally use day to day, that the average person would not normally use. So it is very much about getting people out of the headspace 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.
And am I right that these exercises 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.
Totally. My interest in the school actually stemmed largely from exactly what you are describing. This was the first intervention about technology and attention that I had learned about that was not about personal hygiene around tech. The Attention School is really aimed at saying, “We’re not going to be prescriptive about your relationship to technology.” They say very intentionally, “We are friends of technology here. We are for people who 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, what we can do to resist some of those harms, and resisting the commodification of our attention.
Well, Kevin and I have been really worried about your screen time. When we heard that you were going to attention school, there was kind of this moment of, “Well, finally.”
Yeah.
You know what I mean?
Yes.
So we’re excited to hear about how it went.
So tell us. 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?
Okay. Before I tell you about the building, can I just say there are 3 kinds of programs that I got to experience through this attention school, and I want to tell you a little bit about all 3 of them? I will start by telling you about the first one that I went to, which was my first experience going to the school. This is what they call their attention labs.
The school is not a bunch of classrooms. It is really a single room that operates as the epicenter of what they call the attention liberation movement. I would describe the room as a mix between a very cool startup’s office space and your favorite elementary school teacher’s classroom.
Okay.
What I mean by that is that it has all the markings of cool, sleek design, which I think was very startup-y. But the kindergarten classroom vibe was that every time I entered this room, it was configured in a different way.
Hmm.
Sometimes we were having carpet time, where we were sitting on cushions on the floor.
Did they have a talking stick that they passed around, or—
Actually, in one of the classes I did, the instructor used a flute-like instrument and sometimes a little gong to signal, “Okay, students.”
Okay. So far, not beating the cult allegations. But continue.
But the very first thing I did, this attention lab, was not like that. The room was set up in a normal circle of chairs. The first thing that really struck me when I walked in was that I had actually been delayed getting to the first class. Bad student. I was running 5 minutes late because every subway I tried to take was 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. There were crazy transportation issues on the way. I get there 5 minutes late, and there are 40 people sitting in chairs who are totally rapt. Their attention is totally fixed on these 2 facilitators who are leading this attention lab.
In the attention lab, they talk very little about technology head-on. They basically introduce the ideas that I’ve already exposed you to: We think of attention in this really singular way, and this is a school for studying attention in broader ways and getting curious about it. Now we’re going to do some exercises.
9. Attention Takes Practice
This is how all the attention labs are structured: We’re going to do some exercises that start in pair work, then we’re going to discuss them as a group, and later we’re going to do another exercise where we break up into bigger groups. This is going to take almost 2 hours collectively to do the exercises and talk about them.
And what are these exercises?
Great question. They print the exercises on cards, and I would like you to—
Oh, boy.
—read. These are the 2 that I did at the first class, but I thought maybe, Kevin, you could start by—
Which side?
They all have a quote on the back.
Okay.
All the exercises are loosely drawn from existing works of writing or artist practices. This one comes from this book called The 12 Theses of Attention, which the people who started the school helped write.
Okay. This is called “The Paths of Attention.” We’re supposed to form pairs and elect 1 partner to speak and the other to listen and ask questions.
Okay, I’ll speak.
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.
Okay, so the first exercise was to start a podcast. I’m into this. It’s getting my attention. I want to learn more.
Yeah. Very good.
So, yeah, it was a bit like that.
Yeah.
Okay.
Yeah, and you did this exercise.
Just to very briefly summarize here, I think the key thing to take away is that the exercises themselves are— They could be anything, and there are endless permutations of them. I’m going to have you read one in another second.
Yeah.
But they force you to do something that’s a little unusual. In this case, 1 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 give affirmative statements.
It was actually very strange, even for me, as someone who’s used to asking questions. I found it awkward and clunky, and it did make me think, “Huh, this is interesting. This is a little weird.”
Yeah.
That’s funny.
This one 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.”
This is an exercise that I feel like a lot of writers get encouraged to do, right? It’s just like, go out in the world around you and observe for a while and see what you notice.
Yes.
This was a cool one that they based off of a particular writer, a French writer named Georges Perec. I hope I’m pronouncing his name correctly. On the back, there’s a description of some of his work. The concept is that you exhaust the space. You detail every single little thing.
The cool thing about this experience that I didn’t quite realize is that I went off and made a list. I was looking at a Sweetgreen. We went outside, it was raining, and there was a Sweetgreen across the way. I was writing about the workers in the Sweetgreen: They are taking out the trash. Now there is someone walking by. I see pant legs moving, that kind of thing.
Then, when we got back together, we went in a circle, and every single person read a single line of their writing, on and on and on. By the end of it, we really had exhausted the place.
Mm-hmm.
But it did do some interesting things. People reflected on, “Wow, you saw something I didn’t realize.” I heard another woman say, “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 a way to get you curious about your own perception and other people’s perceptions, and to create a shared reality that you can discuss.
Mm-hmm.
Yeah. Also, I think most people probably don’t often have the experience of having fully paid attention to something, right? The condition of the modern world is that you’re always partially paying attention to 11 different things, which often makes people feel crazy. Maybe an antidote to that is just to focus continuously on 1 thing until you reach a state of profound boredom.
Yeah.
10. Attention Becomes a Movement
But it seems like the vibe of The Attention School is not just a gym for your mind. It’s not 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.
Tell us about that piece of it. What do they want beyond these individuals—40 people in a room reclaiming their own attention? What do they want to accomplish in the world writ large?
Okay, so this was the biggest question I had.
This was my biggest frustration of going to these classes: I kept feeling, “What the heck do these exercises have to do with attention?” 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. He basically articulated to me that they are trying to create a kind of intellectual community rooted in 3 key pillars that they talk about: study, sanctuary and coalition building.
By study, they mean people gathering together to study something. They mean this very loosely. They say that surfers gathering at Rockaway Beach are studying the waves and engaged in a kind of study. They want there to be a sanctuary, a physical space where people are meeting. And then they want it to be about coalition building, about inviting people in and building a shared movement.
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, the basis for a social movement. I would say back to them, “But what are your concrete political goals? Tell me your concrete political objectives.”
Right.
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 in how we think about attention, which is that you think about politics as being something related to policy.” 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 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 big tech really wants to suck our attention away. They want to have our eyeballs. So every moment that we’re doing something that cannot be commodified, he argues, is a really material form of resistance.”
Hmm.
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. Tell us about a couple of the other exercises you did.
These were the attention labs, the thing I just described. They are free and the first offering. But then there were 2 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 it’s interesting.
The second kind of programming that I did is what they call their sidewalk studies. These are also free programs. They’re also built around some kind of exercise of attention, like what we just described. But the main difference is that you leave the school to do them. So they’re kind of a flash-mob-style attention exercise out in the world.
The one I went to was all about taste. They have different themes. We met in Fort Greene Park, and they had us read a little excerpt from Anthony Bourdain’s Kitchen Confidential about how Anthony Bourdain says something to the effect of, “The body is not a temple. It is an amusement park ride. You should go out there and enjoy it that way.”
Then we were told to walk around the farmers market and take in the farmers market as though our body was either a temple or an amusement park. It was pretty fun. I walked around, really visually taking in everything. We get back together, we’re sitting at this picnic bench, and everyone told a little story about their experience.
Someone had bought oysters, and he shucked an oyster at the table and handed it around. Someone else passed around focaccia bread. It was just a bit of a group therapy exercise.
Yeah.
People were contemporaneously just saying, “Here’s what I thought.”
It’s so interesting because this sounds like an exercise that you would give to somebody who had just been reunited with their human body after having their mind uploaded to the cloud for a couple of years. You’d just be like, “Here, let’s walk you through the farm.”
Yes.
“Remember lettuce?”
Yes.
There is something about that that is funny to me, but it also seems to be quite sad that we’ve reached a place where this seems therapeutic to people. Just tasting a strawberry to return to yourself—maybe that is where we’re at.
I think it’s where we’re at. What’s interesting to me about this is that I’m not sure whether Attention School is the right solution, but the problem seems real. I don’t know many people who are feeling great about their relationship with technology these days.
Yeah.
Even the people who work in tech or are early adopters of all this stuff, I think there’s a visceral sense that this is not how I like to live. For many people, I think that’s just going to be something that they deal with by locking their phone in a box, putting on their Screen Time alerts or using whatever brute-force method they choose.
But it seems like this is a more robust way of trying to retrain yourself, not just fix the short-term problem in front of you. Is that a good way of looking at it?
Yeah.
Yeah, I think that’s right. I think it really is, to them, less about the actual exercises of attention. The people who helped form this school were a combination of academics and artists, and I think they found this kind of exercise really fun. They thought, “Here, this is a great way that we can give people a positive experience of coming together to get at some of these ideas that we’re concerned about.”
But I think the really high-level theory that they have is that we need to build communities. There are people right now who feel really uncomfortable with the way technology is changing us, and we need to actively start creating a space for them now.
I think they’ve benefited tremendously from the fact that they founded the school in June 2023.
Mm-hmm.
When they started the school, they were probably thinking primarily about social media.
Mm-hmm.
But I think the fact that we are seeing the rise of AI means that the school kind of found its moment. 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 distinctly human about the way we perceive the world?”
I think so much of what AI is causing people to think about in their lives right now is, “What can I do? What can I achieve? What can this machine help me do?” And then there’s anxiety about what I can do that it can’t do. It has pulled some attention away from the question of what it means to exist as a human. The school is really interested in creating a space for that question.
Tell us about this last exercise you did.
The last thing I did was actually my favorite thing, and it was definitely the zaniest of all the things that I did. The school offers seminars. These are the one paid offering that they have.
I want to emphasize that they really care about making this a democratic experience that is open to everyone, so they offer all different kinds of seminars. The seminars are loosely on any topic that you could argue is related to attention, which is broadly everything.
They have taught classes in the past on hypnosis. They have one going on right now that is about weeds—literally invasive flora out in 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 would be fun for you to get a taste of how seriously they were taking this and of some of the homework assignments I was getting.
There was homework. There was also reading that we got assigned. Everyone in my class, or the vast majority of people, seemed to have fully done all of the reading, done the homework and come prepared. People were incredibly engaged.
Wow.
Here’s one prompt that I love. This is the prompt.
“Sit with yourself in silence or journal to discover a quality of yours you would like to expand, like whimsy, compassion or 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.”
Basically, that’s, “Come to session 2 as your character, and then we will reintroduce ourselves.”
So literally, when you show up for the first class, you’re prompted to do all this internal work to think about the forces that constrain your imagination.
We talked about who is the prison guard in your head, who kind of jails your imagination and tells you, “These are things 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 maybe have more of. Like, a sort of 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 gave ourselves new names. Some people actively dressed up, and some people really got into the sort of improvisation of it and performed their character for most of the class. We were doing improv—
What was your character?
Wow.
My character was—her name was Princess Lollipop.
Wow.
I told Casey a little bit about this, but my big finding from this class, which I found really interesting and helpful in my own personal life, is that I found myself being really rigid in a lot of these classes.
Mm-hmm.
And getting frustrated by the nature of the exercises, the logic of the exercises, thinking, “I don’t get this.” And I started to realize I’m not really approaching this with a sense of playfulness and humor.
Mm.
And so my challenge for myself is: What is a version of me that is more playful?
Mm.
The vision that came to me was of myself as a child, a six-year-old version of myself in a little tutu. And I had a funny phase, a real phase as a six-year-old, where I think I fell in love with Candy Land and told my parents that I refused to be called Rachel. They could only call me Princess Lollipop.
Wow.
Casey, you’re more of an improv guy, but my sense is there’s some similarity and overlap between doing improv acting or comedy and what you’re talking about with inhabiting a character. And to me, it seems like there are a couple of things that are coming together.
One is Buddhism, frankly. It’s like, focus on attention and where the mind goes—
Mm-hmm.
—and re-grounding yourself in the physical world—
And in the present moment.
—and in the present moment. There’s this improv idea of exploring your feelings and exploring your imagination. There’s this tech-resistance piece of it—
Yeah.
—which is like, “I don’t like what this technology is doing to our brains.”
Mm.
And it’s interesting, and it makes me think about previous waves of technological change and some of the social and cultural movements that have grown up in response to those. During the Industrial Revolution, there were the Transcendentalists, who wanted to reconnect with nature—
Mm.
—because they felt like the whole economy was getting away from the land and the farms and going into these dehumanizing factories. And they were sort of like, “We want to go to Walden Pond and write poetry and look—
Yes.
—look at leaves.”
Yeah.
And the same kinds of things happened in the 20th century with industrialization. Every time we make a big leap forward in technology, there’s a cultural counter-movement—
Mm.
—that’s just like, “Wait a minute, we actually don’t like what this is doing to us, and we want to reclaim ourselves from the technology.”
Yeah.
Does that feel like it’s of a piece with what you’re saying?
I definitely think so. I think, actually, an interesting thing about this particular movement is that even the language that the people involved with this school use intentionally relates back to the environmental movement. They call themselves the Friends of Attention.
These are people who are often very interested in helping people get re-enchanted with nature—that’s the phrase I heard. For example, they talk about what big tech is doing to our attention as “the fracking of our eyeballs.” They’re really intentionally using this environmental language.
Yeah.
I think it’s interesting because we think of Silicon Valley in the ’80s and ’90s as a site of the counterculture, right? 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 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. I think it actually 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 help people reintroduce themselves to the feelings that you get when you’re actually in the present moment, paying attention to the world around you.
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 looking at the tree—
Yeah.
—seeing the person walking down the street.
Getting bored.
Yeah.
Seeing the bird. Having a spare moment.
Yeah.
And it’s hard.
Yeah.
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?
I think that’s the obvious question, and it’s also an incredibly hard question to answer. The analogy that feels most fitting to me is the analogy of some kind of group therapy. Did I have some kind of transformational breakthrough in a month of going? I would say no. I made some small discoveries about myself, like the one I described about my playfulness.
I would take that into therapy, by the way. I think there’s a lot there.
But I think this is true of a lot of people who go to therapy for a month. Some people come away and they’re like, “Holy shit, that changed my life.” For a lot of people, it’s gradual insights.
But 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. And I was really struck by how thoughtful people were, how earnestly they were engaging, how open-minded they were.
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 self-identified as sort of part of a neo-Luddite movement, where they were 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 workers. They had jobs. I met a scientist who’s using AI all the time. I met a bureaucrat who works in city government.
And these are people who plan to continue using technology, but they’re looking for a space where they can talk to other people about the current moment we’re in, find meaning in it, build community, and slowly figure out what we want to do next, if there is political action to take.
Well, Rachel slash Princess Lollipop, thank you for telling us about your experience. I’m so glad you went to attention school.
Thank you so much.
I think you should go. You’ve been doing your email this whole time.
Yeah. I actually haven’t been paying attention to anything you guys said. Just kidding.
Sign him up.