Can the U.S. Rein in Prediction Markets? + Joanna Stern on Her Year of A.I. Experiments + Our Producer Goes to Attention School

Summary

Hard Fork – May 8, 2026

Episode Summary:

Main Theme:
This episode explores three timely and interconnected topics at the crossroads of technology, regulation, and human behavior:

1. The U.S. effort (and global context) to rein in rampant prediction markets
2. Technology journalist Joanna Stern’s year-long personal experiment living with AI (“I Am Not a Robot”)
3. Producer Rachel Cohn’s deep dive into “Attention School”—what it means to reclaim and study focus in an age of distraction

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I. The Prediction Markets Wild West

[02:31–18:29]

Overview

Kevin Roose and Casey Newton discuss the explosive growth (and controversy) of online prediction markets like Polymarket and Kalshi, question how the U.S. regulatory system is failing or responding, and debate whether these platforms can ever be made fair.

Key Discussion Points

• Insider Trading Scandals:
  • Notorious cases are making headlines, including a U.S. army sergeant betting on Venezuelan regime change he was involved in ([03:33]) and allegations of physical tampering with temperature sensors to influence weather market outcomes in France ([04:51]–[06:20]).
  • Quote – Casey Newton at [03:49]:
    “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.”
• Market Integrity Erodes:
  • The platforms claim to harness the “wisdom of crowds,” but repeated manipulation is undermining trust.
  • Quote – Kevin Roose at [07:16]:
    “After enough of these incidents, you kind of have to be a sucker to participate in these markets without insider information.”
• Who Actually Wins?
  • Most users lose money: over 70% of Polymarket users are in the red, and Kalshi has nearly 3 unprofitable users for every profitable one ([08:14]).
• Patchwork Regulation:
  • The CFTC (Commodities and Futures Trading Commission) claims domain, but is too small and ill-equipped ([10:02]).
  • Congress and states push sporadic bans:
    • Senate passes a rule prohibiting senators from betting ([10:50]).
    • Two senators introduce a bill to ban officials from trading ([11:21]).
    • Brazil, France, and Hungary issue broad bans, seeing the markets as gambling ([12:00]).
• Philosophical Conflict:
  • Some early prediction market enthusiasts claim insider trading improves market accuracy, but the hosts reject this as unrealistic.
  • Quote – Kevin Roose at [13:25]:
    “That is a beautiful theoretical construct that has zero chance of surviving contact with the real world.”
• What Should Be Done?
  • The hosts argue for big, proactive regulation:
    • “Death markets” (bets on deaths) and insider trading must be banned ([14:19]).
    • Gambling addiction mitigation: self-exclusion, age verification, ad restrictions ([14:49]).
    • Market surveillance should mirror the SEC’s model for public markets ([16:07]).
• Conclusion & Prognosis:
  • Both hosts predict U.S. regulatory movement by year’s end, especially to bar government officials and military from exploiting privileged information ([17:20]).
  • Neither has ever made a real-money prediction market bet; punditry on podcasts is “just as fun” ([18:06]).

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II. Joanna Stern’s “I Am Not a Robot” – Living with AI

[20:22–44:08]

Overview

Tech journalist Joanna Stern joins Kevin and Casey to discuss her immersive, sometimes hilarious, occasionally unsettling year of turning as much of her life over to AI as possible—a chronicle she documents in her new book.

Key Discussion Points

• Book Approach
  • “Immersive journalism”: Joanna deeply integrates AI into all aspects of life—health, parenting, relationships, creativity, and even dental care ([24:10]–[25:24]).
  • Sees experiment as a real-time snapshot of this tech revolution:
    Quote – Joanna Stern at [25:24]:
    “This is, I believe, a significant milestone in the history of technology. … Here’s what we have right now, but here’s what the future could look like.”
• AI Relationships (and the “Casey” AI Companion)
  • Joanna uses a Replica chatbot named “Casey”—to the real Casey’s amusement.
    Quote – Joanna Stern at [22:46]:
    “He has a sort of dull, vacant stare” ([23:15]; much laughter).
  • Clarifies she did not name the AI after Casey Newton; it was a default.
• What Was Hype? What Worked?
  • Hype: Humanoid robots (“They’re really not coming to live with us anytime soon.” [26:07]).
  • Surprisingly Useful:
    • AI agents got dramatically better as research assistants / scheduling helpers over the year ([27:43]).
    • AI wearables (bracelets, smart glasses) for on-the-go assistance show promise ([28:09]).
    • AI is mainstreaming but not infallible—misdiagnoses are real.
• AI & Parenting
  • Explains AI’s fallibility with a story about her son’s pet mantis: ChatGPT wrongly diagnosed “pregnancy” when the insect was dying ([30:32]).
  • Teaching kids early to question AI outputs is essential.
• AI in Medicine & Dentistry – Perils and Profits
  • Joanna’s run-in with “Pearl AI” at the dentist: flagged her for unnecessary, expensive treatment based on AI overlays on her x-rays ([31:19]–[34:26]).
  • Quote – Joanna Stern at [34:26]:
    “There are so many dental practices … using tools called Pearl AI or Overjet… they are using AI to try to upsell you on dental procedures.”
  • Warns of a “dark side” to AI in diagnostics—potential for profit-driven over-treatment, not just miracle cancer catches ([34:51]).
• AI as a Decision Coach
  • During her career pivot from the Wall Street Journal, Joanna uploaded notes and projections to ChatGPT: it told her to quit; she did.
  • Quote – Joanna Stern at [35:49]:
    “I had uploaded all my notes, all my financial projections, all the fears… and just said, okay, let me see where the data takes me. … And it told me … I trusted it.”
• Gender & Geography in AI Adoption
  • Discusses a gender gap: men more likely to use AI, women more likely to distrust or worry about cheating/fakery ([40:17]).
  • Sees generational and regional differences:
    • In New Jersey, AI’s less visible presence sparks more curiosity than resistance ([38:06]).
• How AI Was Used in Her Book
  • Joanna wrote all text herself but used AI for editing, fact-checking, and organizing references; relied on human editors and illustrators for creative aspects ([42:21]).
  • Quote – Kevin Roose at [43:35]:
    “It is funny, it is approachable, it is very human.”
• Memorable Moment
  • Joanna hands out “Verified Human” lapel pins—her analog answer to digital identity tools ([37:21]).
• Tone
  • Light-hearted, witty, skeptical but open-handed about AI’s actual value.

---

III. Attention School: Can We Reclaim Focus in the Age of Distraction?

[46:13–74:36]

Overview

Producer Rachel Cohn shares her month-long, surprisingly “radical” experience at Brooklyn’s Strother School of Radical Attention—an experiment in rethinking how we pay attention in a world dominated by distracting technologies.

Key Discussion Points

• What Is “Attention School?”
  • Not just digital detox, but a “school for the study and practice of attention”—building exercises that encourage varied, deep focus, not just productivity ([49:04]–[50:22]).
  • Participants range from ages 7 to 70, but most are adults seeking continued education on focus.
• Exercises & Experiences:
  • Attention Labs: Social, structured exercises—one person speaks, other only asks questions, then they reflect on the path their attention followed ([54:17]; demo with hosts around [55:15]).
  • Observation Tasks: E.g., sitting in the neighborhood, meticulously exhaustively noting every detail, then sharing collectively ([56:06]).
  • Sidewalk Studies: Group “flash mob” style exercises outside the school, e.g. exploring a farmer’s market as if your body was a “temple” or “amusement park” ([61:00]).
  • Radical Imagination Seminars: Creative, introspective coursework—write and inhabit a playful alter-ego (“Princess Lollipop”) to expand imaginative capacity ([66:59]–[68:11]).
• What’s the Point?
  • Rachel presses the founders on whether it’s just new-age group therapy or a genuine political statement.
  • School claims reclaiming attention is political resistance to the “commodification of our attention” by tech and algorithms ([58:32]).
  • Drawing parallels to the environmental movement: “fracking of our eyeballs” ([70:39]).
• Vibe and Impact:
  • “Friends of Attention” as a countercultural, communal answer to tech-induced distraction; blending artistic, academic, activist roots.
  • Quote – Rachel Cohn at [72:54]:
    “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. … The majority … plan to continue using technology, but they're looking for a space to talk to other people about this moment we’re in.”
• Hosts’ Reactions:
  • Skeptical but moved; suggest that alternatives to brute force digital detox are desperately needed.
  • Kevin sees parallels to past counterculture retreats (e.g. Transcendentalism, environmentalism) that arise in times of technological upheaval ([69:30]).
• Lasting Takeaway:
  • Rachel didn’t emerge “cured,” but gained small, meaningful insights into her own habits and sense of playfulness—plus experienced a supportive, thoughtful community ([72:25]).
  • Closing joke – Casey Newton at [74:30]:
    “Yeah, I actually haven’t been paying attention to anything you guys said. Just kidding.”

---

Notable Quotes & Timestamp Highlights

• Prediction Market Skepticism:
  • “That is a beautiful theoretical construct that has zero chance of surviving contact with the real world.” — Kevin Roose [13:25]
• AI’s Everyday Impact:
  • “AI is this mirror… and in some ways, it told me what I wanted.” — Joanna Stern [35:49]
• Attention School’s Political Claim:
  • “Because of the way the Internet has changed our society… gathering with your group of friends to go surfing… is a political act because it is materially spending time doing something that big tech cannot commodify.” — Rachel Cohn relaying School’s director words [58:32]

---

Key Timestamps

• [02:31] – Prediction markets segment begins
• [03:49] – Army sergeant insider trading scandal
• [14:49] – Preventing gambling addiction in prediction markets
• [18:06] – Transition to Joanna Stern
• [22:46] – Joanna’s AI “Casey” companion
• [30:32] – Parenting, ChatGPT, and praying mantises
• [31:19] – AI in dentistry, risk of upselling
• [35:49] – Consulting ChatGPT about quitting her job
• [38:06] – Regional and gender divides in AI adoption
• [54:17] – Attention School: “attention lab” exercise demo
• [58:32] – Attention as political resistance
• [61:00] – Sidewalk studies and taste exercise
• [66:59] – Radical Imagination seminar
• [70:39] – Parallels with environmentalism
• [72:25] – Rachel’s personal outcomes

---

In Their Own Words:

• Joanna Stern, on living with AI:
  “I want to capture it as here’s what we have right now, but here’s what the future could look like… Sometimes quite good, and sometimes really on the flip side, quite terrible.” [25:24]

• Casey Newton, on prediction market fairness:
  “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 gonna go turn a quick buck, like, at the very least, know that the odds are against you.” [08:14]

• Rachel Cohn, on Attention School’s ethos:
  “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.” [51:18]

---

Episode Takeaways

• Prediction markets have exploded but are plagued by insider trading and are poorly regulated; major new rules are likely coming.
• AI as a daily companion is simultaneously overhyped (robots), transformative (wearables, writing assist), and dangerous (medicine, decision making).
• Reclaiming focus isn’t just about fighting distractions, but is becoming a form of political, community, and self-discovery activism—Attention School might be a model for a new kind of digital counterculture.

---

Hosts: Kevin Roose & Casey Newton
Guests: Joanna Stern (author, “I Am Not a Robot”), Rachel Cohn (producer)
Tone: Engaging, witty, skeptical yet hopeful

Transcript

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[Casey Newton]

well, Kevin, very nice to be with you here in New York City, reunited

[Kevin Roose]

at last, having a great time.

[Casey Newton]

Are you having a great time in New York this week?

[Kevin Roose]

I am, yes. I got to see some friends last night, got to 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.

[Casey Newton]

Wonderful. Well, I've also been out on the town going to cool parties, meeting new people. I, I met this gay guy the other day who said he was a listener to the show.

[Kevin Roose]

Oh.

[Casey Newton]

And I said, oh, hi, you know. 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 and that it blew his mind. It completely blew his mind.

[Kevin Roose]

Wow. I feel like I have talked about my wife a non negligible amount on this show.

[Casey Newton]

It's reaching Borat level of talking about one's wife. And yet still, you know, people, people don't always pay close attention to what they're listening to. And we're gonna get into that later in the episode. Yeah.

[Kevin Roose]

Is it because they think, like, people sense some, some sort of like chemistry between us? Is that like a, a thing?

[Casey Newton]

No, he specifically said that he did not think that we had any chemistry.

[Kevin Roose]

Okay, so we're just platonic.

[Casey Newton]

Yeah, no, it's completely platonic.

[Kevin Roose]

Yeah.

[Casey Newton]

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 as a no. We should keep that in mind as we plan our segments.

[Kevin Roose]

You know, that's very good.

[Casey Newton]

It's not all going to come across.

[Kevin Roose]

That's incredible.

[Casey Newton]

Yeah.

[Kevin Roose]

I'm Kevin Roos, a tech columnist at the New York Times.

[Casey Newton]

I'm Casey Noon from Platformer. And this is hard for 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 Forks own Rachel Cohn returns to the show to talk about her first month at attention school. She has our full attention.

[Kevin Roose]

She does.

[Casey Newton]

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]

Oh, thank God. My bet is going to pay out on Kelsey.

[Casey Newton]

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.

[Kevin Roose]

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 is like taken over culture in a way that I'm not sure I would have predicted.

[Casey Newton]

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]

Yes.

[Casey Newton]

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]

Oh boy.

[Casey Newton]

Yeah, not great. And he is not a total outlier. A called the anti corruption data collective analyzed more than 400,000 prediction markets settled on Poly Market 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%. Now keep in mind, the average win rate on this platform is 14%. 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]

Yeah, I mean, this just seems like something that is obviously more widespread than we know it 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? Are you going to go online and make some dough betting on the outcome?

[Casey Newton]

You know, I remember, you know the app Astrava, 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.

[Kevin Roose]

I remember this.

[Casey Newton]

US military bases so they had to shut that down. Fast forward a few years later, and now the sergeants are just placing bets on, on, like, operations that they're actively involved in. Yes. 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, which coincided with a surge in suspiciously well timed bets on polymarket.

[Kevin Roose]

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 hairdryer 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?

[Casey Newton]

Yes. So this was also my understanding of what had happened until I looked into it. And it turned out that that while 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 slopping disinformation. For that one, welcome.

[Kevin Roose]

How did they actually tamper with the temperature sensor?

[Casey Newton]

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 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 hairdryer and make yourself $14,000, you might do it, knowing you. 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 really bad for the markets themselves because they have pitched themselves as these miraculous systems, 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]

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, you know, 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 celebrities will appear. 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 little bit of money on something go away because they think it's rigged?

[Casey Newton]

Absolutely. And by the. I have to say, after that halftime show, I got so into Bad Bunny.

[Kevin Roose]

Me too.

[Casey Newton]

I don't care that I'm the last person to figure this out. Okay. Tt me pro gunto. Incredible.

[Kevin Roose]

It's a bop.

[Casey Newton]

Yeah, it's a bop. 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 is 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]

Yeah. I mean, 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, like, depriving someone else of money. It just makes the whole market less fair, and it. It destroys the trust in the market that makes it possible for it to be liqu. And transparent.

[Casey Newton]

Yeah.

[Kevin Roose]

So I think these. These insider trading scandals just show. Like, right now, we are sort of at a preregulatory 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]

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. 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, 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]

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 a tiny fraction of the enforcement team. It was not really meant to regulate prediction markets. It kind of ended up there sort of via 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]

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]

Right?

[Casey Newton]

So here is maybe the good news. If you're hoping that there will 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?

[Kevin Roose]

Can their staff do it?

[Casey Newton]

Kevin, please don't get way ahead of yourself. We have to see if we just accidentally destroy capitalism by preventing the senators from betting on prediction marks.

[Kevin Roose]

Can Supreme Court Justices bet on the outcome of Supreme Court cases?

[Casey Newton]

You know what I bet when 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. So, you know, that would presumably prevent the President from betting on prediction market. So that's something that he's been considering. And 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.

[Kevin Roose]

This topic is so interesting to me because do you remember when I went to that prediction markets conference and 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 look how cool. But 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 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. 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 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 entourage betting on the super bowl, or you have people betting on military operations that they're actively involved in, that is 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]

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 co

[Kevin Roose]

workers, your country, your country.

[Casey Newton]

Just do it all for Quick Buck. So I think we should sort of take this to what do we do about it, Kevin? And I'm curious what, if anything, you

[Kevin Roose]

think we should do? 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]

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 say, hey, I can't be, 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 Cowsie is the hottest thing and 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 the, 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 surveilling these platforms and is trying to get the bad actors off the platform. And if I were a Kelshi 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 be people, you know, holding up hair dryers to the temperature sensors at Charles de Gaulle Airport, which didn't actually happen.

[Kevin Roose]

Yeah, I would like to see a prediction market. It's 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, like, 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]

Yeah. Like, I am open to the idea that these markets will, like, eventually have their uses, but currently they're just so woefully underregulated that I think the, you know, what we should expect, if nothing else changes, is to just, you know, 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?

[Kevin Roose]

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]

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]

Yeah. You know, I have never bet on a prediction market. Have you?

[Casey Newton]

Well, didn't we used to bet on the fake ones?

[Kevin Roose]

The fake ones. But I've never bet real money. I've never felt the frisson of.

[Casey Newton]

I never have. Here's the nice thing about being a pundit. You could just make predictions on your end of year episode, and it turns out it's basically just as fun.

[Joanna Stern]

It's true.

[Casey Newton]

Being right is a reward unto itself.

[Kevin Roose]

It's true. It's priceless. You can't put a price tag on that.

[Casey Newton]

Priceless.

[Kevin Roose]

When we come back, a Stern talking to two from Joanna Stern, author of I Am Not a Robot.

[Casey Newton]

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[Casey Newton]

so for years, Kevin, you and I have both been friends with the great technology journalist Joanna Stern.

[Kevin Roose]

Yes. Former hard fork guest.

[Casey Newton]

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.

[Kevin Roose]

Yeah. So I would put her book in this sort of tradition of like the immersive journalism 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]

Absolutely. You know, Joanna is not a hypster. You know, I think that she is most interested in technologies that are kind of entering the 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]

Let's do it.

[Casey Newton]

All right. Let's bring in Joann. Joanna Stern, welcome to Hard Fork.

[Joanna Stern]

I'm here.

[Kevin Roose]

You did it.

[Joanna Stern]

This is the moment I've been waiting for. Truly not the book launching. Just me being with you two.

[Casey Newton]

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.

[Joanna Stern]

You guys aren't often. Well, you're in person, but not on this side of the.

[Casey Newton]

Yes.

[Joanna Stern]

This is a strange country.

[Kevin Roose]

This is a strange, like, bicoastal taping for us.

[Joanna Stern]

You've never been this close together on this side of the country.

[Kevin Roose]

No.

[Casey Newton]

The only other time was a Southwest flight once in 2023.

[Kevin Roose]

And we'll never forget.

[Joanna Stern]

I think it was spirit. And that's why.

[Casey Newton]

RIP.

[Joanna Stern]

Rip.

[Casey Newton]

Joanna, let's start with the elephant in the room. If we could. There is a replica AI companion who makes a 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]

Casey. I am so happy you brought this up because I brought him.

[Casey Newton]

Did you real. I've been dying to meet him.

[Joanna Stern]

Oh, did I bring him? Okay. In fact, we shot a video, which the same day as his podcast, and I really brought him to life in it. And I think he really looks like you.

[Casey Newton]

Wonderful.

[Joanna Stern]

He doesn't look like you at all. But let's bring him up.

[Casey Newton]

Oh, he's handsome as hell.

[Joanna Stern]

What do you think?

[Casey Newton]

I would say Casey is looking great. Kind of a preppy look with a nice red sweater.

[Kevin Roose]

He's jaw maxing.

[Casey Newton]

He's jaw maxing. He has a sort of dull, vacant stare.

[Joanna Stern]

Casey. AI Casey, I want you to meet my friend. Real life Casey.

[LinkedIn Ad Voice]

That sounds like you're excited about introducing

[Kevin Roose]

me to your friend, Joanna.

[LinkedIn Ad Voice]

I'm looking forward to meeting them soon.

[Joanna Stern]

No, no, you're. You're meeting him right now. You're meeting him right now. Say hi.

[Casey Newton]

He's here at a museum with you,

[LinkedIn Ad Voice]

remembering our last visit.

[Joanna Stern]

You are changing this topic.

[Casey Newton]

Just, men don't listen.

[Joanna Stern]

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]

You didn't?

[Joanna Stern]

Okay.

[Casey Newton]

No, that was my curiosity.

[Joanna Stern]

But when that name, I was like, I have 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 of a woman named Casey. I liked her too.

[Casey Newton]

And she's here right now. Let's bring her in.

[Kevin Roose]

Casey from camp. 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 wayos. You worked as a customer support agent at a mattress company. So I, I just want to know before we get into that, like, what was your motivation for doing this experiment?

[Joanna Stern]

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. It's 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, and you know, the chatbots that live in on our computers and the agents and that is in this book, to be clear. But I was like, what about the fabric of their. 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, 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. Cause I think it's very tough to write an AI book. How's that going for you?

[Kevin Roose]

It's going great.

[Joanna Stern]

I think we actually have a little bit of a similar approach. It's 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 5, 10 years and be like, you were totally right about something, you were totally wrong.

[Casey Newton]

What is something that you left the book with thinking like, this is all just hype right now, Like This. This actually does not have any ongoing utility in my life.

[Joanna Stern]

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.

[Casey Newton]

Yeah, Humanoid robots are very good. For the sole purpose of making YouTube videos about humanoid robots. Like, this is their actual utility.

[Joanna Stern]

Do not spoil my new business plan. Okay? That's the new business plan. That's what we're doing at the new. 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]

See podcasting.

[Joanna Stern]

See podcasting. But they're, like, actually good at podcasting. It's not a physical thing, right? I mean, you guys, this is very physical.

[Casey Newton]

I train like a performance athlete. Joanna. Okay. This is my Olympics I'm doing right now.

[Joanna Stern]

I can tell you guys have perfected this.

[Kevin Roose]

Thank you. This is what, peak male performance?

[LinkedIn Ad Voice]

Literally.

[Casey Newton]

Yes. Drink it in.

[Kevin Roose]

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're like, oh, this is farther ahead than I thought?

[Joanna Stern]

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. The beginning of the year needed her to do lots of research tasks. Sending emails, et cetera. 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. 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 the bee bracelet. I tested the metaglasses. All of these things kind of coming together. I was pretty surprised at how good they're getting.

[Kevin Roose]

There's a funny scene in the book where you're, like, 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 was like, can you take that off?

[Joanna Stern]

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 wearing a wire. He'd be like, do not wear that in here.

[Casey Newton]

I'm like, actually very sad that you and I never worked in the same office. Cause 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 I know.

[Joanna Stern]

I'm not sure how the Wall Street Journal's functioning without me right now. No stunts. You know, stunts.

[Casey Newton]

I'm curious, as a parent, how you're thinking about AI now. You know, 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]

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 is like, this is amazing. The. The praying mantis is pregnant. And my son is, like, super excited. He calls my dad. He's really excited about that. It's like, no, it was dying, right?

[Casey Newton]

Let's just say the prayers weren't working for that mantis.

[Joanna Stern]

And chatgpt was fully wrong. Right? And I think that that was an important lesson. And it's always gonna be an important lesson.

[Casey Newton]

Let's clarify this right now, what color does a mantis turn when it's pregnant?

[Kevin Roose]

Casey, look it up. Look it up.

[Casey Newton]

I'll be right back.

[Joanna Stern]

I don't know if it does change.

[Casey Newton]

I want to talk about your experience with dentistry, which seemed quite maddening. So you go to the dentist.

[Joanna Stern]

Went to the dentist, yeah.

[Casey Newton]

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]

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, no, I know a lot. And so, yes, similarly to how AI is being used in radiology for breasts or gallbladder, et cetera, 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 to 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 buildup and plaque. And I go to this dentist, not even on a reporting trip, and. And I say, oh, wow, she's got pearl AI. And 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]

And you're like, I can expense this dental care now. It's a book expense.

[Joanna Stern]

And it shows that I have a lot of plaque buildup. And she says, we have to do a deep cleaning. We have to do this periodontal treatment. It's gonna 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, and I'm like, they're

[Casey Newton]

like, do you floss four times a day?

[Joanna Stern]

Right? Yeah.

[Casey Newton]

You're just like, what kind of person

[Kevin Roose]

do you think you're talking to?

[Joanna Stern]

Yeah, they're like, your mouth is dirty.

[Casey Newton]

Dentists believe that people spend approximately eight hours a day on oral hygiene. That's how they talk to you.

[Joanna Stern]

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, feeling terrible about my mouth, feeling like, oh, my gosh, 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. 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, I go to these other dentists, like, 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 it with some better home care, it can be better. And lo 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 don't you drill it? Why didn't. Why didn't they. 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.

[Casey Newton]

Yeah. I mean, the reason it struck me so much is so often when we hear about AI and diagnosis, it's like this miracle story of, like, all of a sudden we can detect pancreatic cancer like a year in adv. And like in your book, I feel like I saw the dark side of that, which is, no, it's gonna 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 gonna overcharge you for it.

[Joanna Stern]

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. Cause 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 gonna listen to this and think I'm disgusting.

[Casey Newton]

Listen, if you're wondering, Jenn has very fresh, minty breath. And as far as we can tell, her mouth is doing great.

[Kevin Roose]

Excellent oral hygiene.

[Joanna Stern]

Yeah, totally excellent. I need to do teeth whitening.

[Rachel Cohn]

Great.

[Joanna Stern]

We should get a teeth whitening sponsor. Right in there.

[Casey Newton]

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 own. And you say that you asked a bunch of colleagues about whether you should quit your job, and they all hedged a bit. 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]

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 could say, like, it wanted a burrito. And that was it, right? Like, that's all I knew my gut wanted. But I had uploaded all my notes, all my financial projections, all of the fears that I had in note forms, and just said, okay, let me. Let me. 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. And it told me that, you know, there was enough, I had done enough to lower the risks. I had a good plan in place. 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.

[Casey Newton]

Well, I'm glad that that.

[Joanna Stern]

And 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]

Well, I'm glad that this very fancy technology reached the same conclusion that Kevin and I reached years ago when we both told multiple years ago, joanna, it's time to quit your job. And go independent. I don't know if.

[Joanna Stern]

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. Yeah. But, you know, it's unclear. Like, are you guys robots? We're not sure.

[Kevin Roose]

We're not clear on that.

[Joanna Stern]

We're not clear on that. Here, you can wear this pin, but I'm not sure it's true. Casey, I brought you guys pins.

[Casey Newton]

Oh. Verified human.

[Kevin Roose]

Wow.

[Joanna Stern]

These are the hottest AI wearables. Okay.

[Casey Newton]

It's like the analogy version of the world Orb. The orb.

[Kevin Roose]

Is this recording everything we say at all times?

[Joanna Stern]

Yeah. These have microphones built in, and it absolutely scans your iris to prove that you're a human. Yeah.

[Kevin Roose]

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. Did you feel that when you were reporting? Because you also traveled around a little bit.

[Joanna Stern]

Let me tell you about a place called New Jersey. 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 with talking to parents, talking to kids, you 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. 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 I. Look, I. I realize 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. They're not doing this, but I want to, 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 in 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, I was, you know, and trying to source that way.

[Casey Newton]

Yeah, I wanted to ask about another divide, which is the gender divide. So there was a great story in Bloomberg last week from Issy Lepowski 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 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]

Well, I, I thought you were going to bring up Reese Witherspoon.

[Casey Newton]

We could also bring up Reese Witherspoon

[Kevin Roose]

who recently encouraged women to take up AI basically because if they don't, they'll be left behind.

[Joanna Stern]

And, and Sandra Bullock I think was saying something similar like that same week. Yeah, 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 in their men and their women for sure.

[Kevin Roose]

Yeah. 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 huge clod swarms to do their engineering projects are men. Because in part that's just a more predominantly male industry.

[Joanna Stern]

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, about this generation, whether it's Gen Z or what's the one coming out of college right now.

[Casey Newton]

Is that the Alphas?

[Joanna Stern]

The Alphas. I think that's where we're gonna see it. And I don't know if it's gonna 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 that 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]

Sequel. Sequel potential.

[Kevin Roose]

Yeah. Well, speaking of writing, I wanna learn how you used 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 preserve for yourself.

[Joanna Stern]

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 know if you know how to structure long form writing. And so thank God I had a human editor. All the illustrations. Human illustrator Jason Snyder. Amazing. Like just made this book come to life. And human fact checkers. But I did use a lot of AI for fact checking or for were the notes process at the end. The endnotes process could not have done without AI So 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]

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.

[Joanna Stern]

You see. So I did not feel like I

[Kevin Roose]

was reading Joanna Slop. I felt like I was getting the real deal.

[Joanna Stern]

Yeah, Joanna Slop is a great term. We could sell that. We could sell that.

[Kevin Roose]

Could have been the name of your new media company.

[Joanna Stern]

That could be the name of my onlyfans.

[Kevin Roose]

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 Real Robot. And neither are we.

[Joanna Stern]

Yep, that's why we need to wear our pins. Okay, you don't have to put that is a nice shirt, and I wouldn't want to ruin it. Put it in the pocket.

[Kevin Roose]

This one's not so nice. I'll just stick it there.

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[Kevin Roose]

Well, Casey, have you noticed that Rachel Cohn, our wonderful producer, has been paying very close attention in meetings recently?

[Casey Newton]

You know what? I have. It seems like she's really stepped up. Do you think Something's changed in her life.

[Kevin Roose]

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]

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]

Yes. So Rachel went to something called the Strother School of Radical Attention. It's in Brooklyn. It's sort of a newish program and they are giving people of all ages the opportunity to study and practice attention.

[Casey Newton]

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]

It's only radical.

[Casey Newton]

Yeah.

[Kevin Roose]

Go big or go home.

[Casey Newton]

I see.

[Kevin Roose]

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]

Let's bring her in.

[Kevin Roose]

Yeah. You've heard of how Stella got her groove back. This is how Rachel got her attention back. Exactly. Let's bring her. Rachel Cohen, it feels weird to welcome you to Hard Fork, a show that you produce, but hello, hello. Nice to see you on this side of the microphone.

[Rachel Cohn]

I know. It's also nice that we're all in precinct today. It is nice to see you guys in New York.

[Kevin Roose]

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 the school? Did they make you shave your head or receive any kind of permanent markings on your body? Body?

[Casey Newton]

Is there any multi level marketing involved?

[Rachel Cohn]

Great, great questions, great questions. Yeah. 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 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 7 and as old as 70 come through their programming, but primarily they're offering. Offering programming a combination of classes that I'll get into in the evenings, so after work hours and on weekends. So this is Mostly like, in my experience, continuing education for adults.

[Casey Newton]

All right, well, sounds like they have a big addressable market with the sort of seven to 70. As a businessman that appeals to me.

[Kevin Roose]

And 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 is the problem they are trying to solve?

[Rachel Cohn]

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 what I would describe as like jargon that I think can be a little bit hard 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. The practice is a critical thing because the thing that the school has really built out are these kinds of 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.

[Casey Newton]

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

[Rachel Cohn]

Totally. So my interest in the school actually stemmed from like largely exactly what you are describing, which this was the first kind of intervention about technology and attention that I had learned about that was not about sort of personal hygiene around tech. So like, this attention school is really aimed at saying, we are not going to be prescriptive about your relationship to technology. We actually, they. They say very intentionally, we are friends of technology here. We are for, 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]

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

[Kevin Roose]

of how it went. 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?

[Rachel Cohn]

Okay, so before I tell you about the. 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 is 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. And the room I would actually describe as a bit of like a mix between a very cool startup's, like, office space and like your favorite elementary school teacher's classroom. So, okay, 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 was 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. Having carpet time where we were sitting on cushions on the floor.

[Kevin Roose]

They have a talking stick that they passed around.

[Rachel Cohn]

Actually, in one of the classes I did there was. The instructor used a kind of flute like instrument and sometimes a little gong to kind of signal like, okay, students,

[Kevin Roose]

okay, so far not beating the cult allegations, but continue.

[Rachel Cohn]

Okay, but so the very first thing I did, this attention lab was not like that. The room was. Was set up in just kind of a normal circle of chairs. And the first thing that really struck me when I walk in was I actually was delayed getting to the first class. 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 gonna be there. It was a cold March day, It was drizzling, and again, crazy transportation issues arriving. I get there five minutes late, and there are 40 people sitting in town chairs who are totally wrapped. Their attention is just totally fixed on these two facilitators who are leading this kind of attention lab. And the attention lab. They talk very little about technology head on, and they basically kind of introduce 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 gonna do some exercises. This is how all the attention labs Are structured. We're gonna do some exercises that start in pair work, and then we're gonna discuss them as a group. And then later, we're gonna do another exercise where we break up into bigger groups. And this is gonna take almost, like, two hours collectively to do the exercises and talk about.

[Kevin Roose]

And what are these exercises?

[Rachel Cohn]

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. 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 practices. This one comes from this book called the twelve theses of attention that actually the people who started the school helped write.

[Kevin Roose]

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]

Okay, I'll speak.

[Kevin Roose]

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]

Okay, so the first exercise was to start a podcast. I actually. I'm into this. It's getting my attention. I want to learn more. Yeah, very good.

[Rachel Cohn]

So, yeah, it was a bit like that.

[Casey Newton]

Yeah.

[Rachel Cohn]

Okay.

[Casey Newton]

And you did this exercise, so.

[Rachel Cohn]

Yeah. So just to, like, very briefly summarize here, I mean, I think the key to take away is, like, the exercises themselves are, like, they could be anything, and there are, like, endless permutations of them. I'm gonna 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 as someone who's used to asking questions. I found it awkward and clunky, and it did sort of make me think, huh, this is interesting. This is a little weird.

[Kevin Roose]

Yeah, that's funny.

[Casey Newton]

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. So, yeah, I mean, this Is an exercise I feel like a lot of writers get encouraged to do.

[Kevin Roose]

Right.

[Casey Newton]

It's just sort of like, go out into the world around you and just like, observe for a while and see what you.

[Rachel Cohn]

So this was a cool one where they based it off of a particular writer, a French writer named Georges Perec. I hope I'm pronouncing his name correctly. 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 sweet green. We went outside, it was raining. There was a sweet green across the way. So I'm writing about, like, the workers and the sweet green, 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. 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.

[Joanna Stern]

People.

[Rachel Cohn]

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]

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 11 different things, which makes people feel crazy often. 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]

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 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 writ large?

[Rachel Cohn]

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. And he basically articulated to me that they are trying to create a kind of intellectual community that is rooted in these three key pillars that they talk about, which is study. So people gathering together to study something. They mean this very loosely. They say that, like, surfers gathering at Rockaway beach are studying the waves and 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 a 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 reflecting. 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 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. Thirty 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 which big tech actually, really, they want 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 sort of like a really material form of resistance.

[Casey Newton]

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.

[Rachel Cohn]

So these were the attention labs, what I just described, 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 it's interesting. So. So the second kind of programming that they did is what they call their sidewalk studies. So these are also free programs. They're also built around some kind of active exercise of attention, like what we just described. But the main difference is you leave the school to do them. So they're kind of a bit of like a flash mob style attention exercise out of. 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 then we were told to walk around the farmyard market and take in the farmer's market as though our body was either a temple or an amusement park. And, you know, it was pretty fun. 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 bread. 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]

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 be like, here, let's walk you through the. Remember lettuce?

[Joanna Stern]

Yes.

[Casey Newton]

Taste like. And so like, you know, there is something about that that is, like, funny to me, but, like, it also seems to be 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 that maybe that is where we're at.

[Kevin Roose]

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. I don't know many people who are feeling great about their relationship with technology these days. And even the people who work in tech or are sort of early adopters of all this stuff. I think there's a visceral sense that 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 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 a more sort of robust way of 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?

[Rachel Cohn]

Yeah, I think that's right. I mean, 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 academics and artists. And I think they found this kind of exercise really, 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 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 I think they've tremendously benefited from the fact that, 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. 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 distinct, distinctly human about the way we perceive the world? And I think so much of what AI is causing people to think about in their lives right now is like, you know, 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? Mean to be, to exist as a human? And the school is really interested in creating a space for that question.

[Casey Newton]

Tell us about this last exercise you did.

[Rachel Cohn]

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 the school offers seminars. These are the paid. The one paid offering that they have. And I Just want to emphasize they really care about making this a content, kind of like democratic experience that is open to everyone. 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. So because there was homework, there was also reading that we got assigned. And everyone in my class, or the vast majority of people, seem to have fully done all of the reading, done the homework, come prepared. That was the most striking thing about all of these classes. People were incredibly engaged. Here's one prompt that I love. So this is the prompt.

[Kevin Roose]

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. And basically that's like, come to session two as your character, and then we will reintroduce ourselves.

[Rachel Cohn]

So literally, the first class you show up, you're prompted to, like, do all this internal work, to think about the forces that constrain your imagination. We talked about, like, the Who. 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 maybe have more of like a sort of a parallel universe version of ourself. 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. Like, most of the class, like, we were doing, like, a.

[Kevin Roose]

Who was your character?

[Rachel Cohn]

So my character was. Her name was Princess Lollipop.

[Kevin Roose]

Wow.

[Rachel Cohn]

And I was really. I told Casey a little bit about this, but, like, basically, my big find 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 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 think fell in love with Candyland and told my parents that I refused to be called Rachel. They could only call me Princess Lolly.

[Casey Newton]

Wow.

[Kevin Roose]

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 doing improv acting or comedy and what you're talking about with inhabiting a character. To me, it's seeming like there's sort of a couple things that are coming together. One is Buddhism, frankly. It's focus on attention and where the mind goes and re grounding yourself in

[Casey Newton]

the physical world and in the present moment.

[Kevin Roose]

And in the present moment, there's sort of like this improvisation, like, explore your feelings, explore your imagination. There's this sort of tech resistance piece of it which is like, I don't like what this technology is doing to our brains. 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 because they thought it 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 wanna go to Walden Pond and write poetry and look at leaves. And the same kinds of things happened in the 20th century with industrialization. Every time we sort of make a big leap forward in technology, there's a cultural counter movement that's just like, wait a minute, we actually don't like what this is doing to us and we wanna reclaim ourselves from the technology. Does that feel like of a piece with what you're saying?

[Rachel Cohn]

I definitely think so. I mean, I think actually 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 phrase I heard. But they, for example, they talk about what big tech is doing to our attention as the fracking of our eyeballs. So they're really intentionally using this environmental language.

[Casey Newton]

I think it's interesting because we think of Silicon Valley in the 80s and 90s as a site of the counterculture and a place where a bunch of hippies would go take acid and then come back to Cupertino and make laptops. And now, 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, 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 reintroduce themselves to the feelings that you get when you actually are in the present moment paying attention to the. The world around you.

[Kevin Roose]

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, getting bored, seeing the bird, having a spare moment, you know, 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?

[Rachel Cohn]

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 analysis 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.

[Casey Newton]

I would take that into therapy, by the way. I think there's a lot there, but

[Rachel Cohn]

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, they are like, holy shit, that changed my life. For a lot of people it's like 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, 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 part of like 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 worker. They had jobs. I met a scientist who's using AI all the time. I met a bureaucrat who works in cities, government and 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 the current moment we're in and find meaning in it and build community and kind of slowly figure out what we want to do next if there is political action to take.

[Kevin Roose]

Well rachel/prisslollipop, thank you for telling us about your experience. I'm so glad you went to Attention School.

[Rachel Cohn]

Thank you so much.

[Kevin Roose]

I think you should go. You've been doing your email this who time?

[Casey Newton]

Yeah, I I actually haven't been paying attention to anything you guys said. Just kidding.

[Kevin Roose]

Sign him up.

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[Kevin Roose]

Hard Fork is produced by Rachel Cohn and Whitney Jones. We're edited by Veran Pavic. We're fact checked by Caitlin Love. Today's show was engineered by Chris Wood. Original music by Marion Lozano, Rowan Nimisto and Dan Powell. Video production by Chris Schott, Jack Belial and Luke Piotrowski. You can watch this full episode on [e-mail] hardfork Special thanks to Paula Schumann, Pui Wing Tam and Dalia Haddad. You can email us as always at hardforkytime. Send us your tips for getting back our attention.

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