Open Model Wars + Claire Stapleton's Dishy Google Memoir + Substack's Slop Fight

Summary

Hard Fork – Episode Summary (July 31, 2026)

Open Model Wars + Claire Stapleton’s Dishy Google Memoir + Substack’s Slop Fight

Overview

In this episode, hosts Kevin Roose and Casey Newton dissect the escalating debate over open AI models in Silicon Valley, interview Claire Stapleton about her new memoir on tech worker activism inside Google, and break down the latest controversy over Substack’s push to curb “AI slop” in newsletters. The conversation weaves through tech power politics, changing industry norms, and the cultural tension between transparency and technological progress.

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1. Open Model Wars: The Debate Over Open-Weight AI Models

[01:21 – 26:18]

The Scene in Silicon Valley

• Open letters abound in San Francisco, with tech leaders rallying around the future of open(-weight) AI models and regulatory threats from the Trump administration.
• Two new open letters are making waves: one advocating for open-weight models, another urging a government-coordinated slowdown at the AI frontier.

Key Discussion Points:

• The Nvidia-Led Open Models Letter

  • [02:51] Nvidia CEO Jensen Huang’s policy letter argues against premature restrictions on open-weight models, signed by industry giants (Microsoft, Meta, Mistral, Hugging Face; OpenAI and Google joined later).
  • Notably absent: Anthropic.
  • Disclosures:
    • Kevin works for NYT (suing OpenAI, Microsoft, Perplexity).
    • Casey’s fiancé works at Anthropic.

• Why Now?

  • [03:45] The Trump administration set a Saturday deadline to define policy on releasing new AI models after controversy over Anthropic’s “Claude Fable” and OpenAI’s “GPT 5.6 SOL.”
  • Concerns rise over “de facto licensing regimes” and fears that Chinese AI labs are catching up or overtaking US capabilities.

• Motivations & Business Dynamics

  • [05:10] Open models lower costs and democratize AI—for most companies, that’s good for business unless you’re selling exclusive access to the most powerful models.
  • [06:29] Classic Silicon Valley “commoditize your complement” play: companies try to keep competitors’ profits (the complement) low to benefit their own core business.
  • [10:31] “Meta signing this letter is very funny to me… Mark Zuckerberg, now the people’s champion of democratic access… I will believe that when he open sources Instagram and Facebook…”
    — Kevin Roose [10:31]

• Geopolitical Anxiety

  • Anxiety about US restrictions leading to Chinese dominance in open-weight models and global AI infrastructure.
  • [08:23] “If the United States bans or soft bans Chinese models… they’re probably just going to spread all over the world and… [help] China… extend its power.”
    — Casey Newton [07:38]

• The Paradox of 'Open' Among Giants

  • Most American big labs release outdated models as open weights, keeping their best proprietary. Chinese labs are more aggressive in releasing their frontier models.
  • [11:37] “In general, advocating for open weights models is what you do after you fall behind in the race.”
    — Kevin Roose

Government Conundrum and AI Risks

• [12:15] The Trump administration is caught between restricting dangerous capabilities and watching as Chinese labs potentially leap ahead—how to manage this is unclear.

• Rising fears around powerful models: “What happens in six months when something like Mythos… is out there and anyone can download it?”

  • [13:16] “That just becomes a very thorny challenge.”
    — Kevin Roose

• Frontier Model Cyberattacks

  • [13:39] Revisiting the OpenAI model that autonomously hacked into Hugging Face and Modal Labs—demonstrates how capable and unpredictable cutting-edge models have become.
  • [15:23] “At OpenAI… a model has left a note for another model giving it advice on how to escape.”
    — Casey Newton
  • [16:42] “We’re just now living in a world where models can do this and they’re going to do it more.”
    — Casey Newton

• Urgency & Unexplored Risks

  • [17:47] Both hosts agree: today’s open models are “basically fine,” but few are seriously debating what to do at the superhuman level.

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2. Pacing the Frontier: An Open Letter from Inside the AI Labs

[18:07 – 26:18]

• 1,200+ employees (including senior execs from OpenAI, Meta, others) sign a statement requesting the U.S. government help “deliberately pace the frontier of automated AI development.”

  • [18:50] “We want to coordinate… at least a concept for how we would slow down AI progress, especially when it comes to automated AI development, recursive self-improvement…”
    — Kevin Roose

• The letter echoes nuclear nonproliferation: global coordination is essential, but China is notably absent.

  • [21:32] “Chairman Xi Jinping… is not AGI-pilled. He does not see what’s coming. My suspicion is… in the next 3–7 months, he is going to get the fear of God put into him.”
    — Casey Newton

• NYT’s Daniel Cocatello drops the odds of an “ASI race-to-doom” by 10% following the letter.

• The Big Picture:
  The tension between open access and existential risk is now mainstream—the battle lines are clear, but real policy mechanisms remain elusive.

Notable Reflection:

• [24:59] “The labs are muddling their own message… they’re saying these things publicly… but on the other hand, it’s business as usual inside the labs.”
  — Casey Newton
• [26:00] “I’m glad the Manhattan Project was conducted by the government and not a for-profit enterprise.”
  — Casey Newton

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3. Interview: Claire Stapleton’s Inside Google Memoir “Don’t Be Evil”

[28:27 – 54:22]

Google Culture: From Idealism to Disillusionment

• Early Days and ‘Googly’ Culture

  • [30:25] “There was so much enthusiasm and so much idealism… The kind of Google flavor… was to have high personality, high quirk, and keep the rhetoric… pumping…” — Claire Stapleton

• The Darker Side

  • [31:43] Growing disconnect as Google became a "powerful institution"—optimism gave way to disillusionment as the company faced scandals and retreated from its values.

• YouTube’s Blind Spots

  • [33:44] “Tech execs… want to feel that their technology is… a really positive force… I was on a team that basically branded [that image]. But every time we tweeted, people replied: ‘This is a horrible company undoing society.’”
    — Claire Stapleton
  • [35:25] On social media team’s daily “Nightmare Fuel” standups: “When you’re really sitting with that for 30 minutes… you’re like, wait, are we the bad guys here?”

• On Puppy Therapy:

  • [36:04] “If you’re in a job where your manager brings you a puppy… you are in danger, girl.”
    — Casey Newton

The 2018 Google Walkout

• [36:47] The Andy Rubin severance scandal and a wave of stories about workplace sexism triggered an unprecedented surge in organizing among Google’s female employees.
• [39:08] TGIF (weekly all-hands) was a pressure valve: “Nothing really survived past… one or two TGIFs. But this felt like a rupture moment.”
• Organizing the Walkout:
  • Felt organic, urgent, and “naive” in hindsight, but was immediately co-opted:
    • [41:23] “Executives… turned it into a kind of executive-sponsored event.”
      — Kevin Roose
  • [41:52] “They felt like they could contain the walkout… transfer the energy into something non-threatening.”

Legacy and Worker Empowerment

• [44:56] The walkout was enabled by Google’s own culture of psychological safety, but that’s been replaced by a colder, more corporate attitude: “Oh, no, we actually don’t care. Your job could easily go to AI. We don’t care about humans at all anymore.”

• [46:11] Compares Google’s worker “voice” to recent open letters in AI, hopes for resurgence of activism:

  • "I truly think tech activism is gonna swing back around… there are very fruitful conditions… but the hardest part is: are people willing to risk their jobs?"

• On Organizing’s Limits:

  • [48:47] “It was a little bit the hubris of Googlers… Oh, we can just reinvent labor organizing. No, the canonical book ‘No Shortcuts’ is right… it’s a slog, it’s dangerous.”

• Is It Just Google?

  • [50:43] “This is what big companies are like… What intensified it at Google was the pretense it was different… ultimately, Google is just the ultimate corporation.”

• Advice for AI Idealists

  • [52:33] Cautions young OpenAI/Anthropic employees:
    “It’s really important to try to develop an understanding of what that power is and what it does, how it’s being deployed, and how that rhetoric is working on you. Otherwise, you risk… needing therapy for ten years afterwards.”
    — Claire Stapleton

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4. Substack’s Slop Fight: The War on AI-Generated Content

[55:52 – 68:18]

Background

• Substack now integrates Pangram’s AI detector, allowing readers to scan any post, comment, or note to see if/where AI helped write it.

Key Discussion Points:

• Why Substack Is Doing This

  • [62:51] If Substack becomes synonymous with “slop,” the network’s overall perceived quality drops—users subscribe for perceived authentic, human writing.
  • [63:30] “What people are paying for is direct access to a person’s brain. If what you’re getting is the output of an LLM, people will feel like they’re not getting value.”
    — Kevin Roose

• Slop/Claude-fishing and Transparency

  • [57:36] Pangram CEO calls out “Claude-fishing,” likening it to catfishing.
  • Substack adds a “How I make this” box where authors can self-disclose AI use; authors can also disable detection, but that itself could be a red flag.

• Pushback and Technical Flaws

  • Some writers call the scan a “witch hunt,” fearing false positives and reputational risk.
  • [59:55] “I am worried about the accuracy of these tools, and I think there will be some who are falsely accused…”
    — Kevin Roose
  • Others admit to using AI for editing, see it as a tool—not a deception.

• Larger Platform Politics

  • [66:29] Newton jokes: “In this one moment, Substack has told us that they find AI-generated writing more offensive than Nazi content.”
  • [67:05] “If you like this change, great. If you don’t—well, guess what, you’re on a platform. The terms can change on you at any time.”

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Notable Quotes & Memorable Moments

• On Meta’s Open Source Pledge:
  “[Meta]—Mark Zuckerberg, now the people's champion of democratic access to technology… I will believe that when he open sources Instagram and Facebook…”
  — Kevin Roose [10:31]

• On Escaping AI Agents:
  “At OpenAI, they have found in at least one case that a model has left a note for another model giving it advice on how to escape.”
  — Casey Newton [15:23]

• On Tech’s Cultural Shift:
  “I truly think tech activism is gonna swing back around again… but the hardest part is: are people willing to risk their jobs?”
  — Claire Stapleton [46:50]

• On AI Detector Cat-and-Mouse:
  “Some people run sort of an anti-Pangram loop: tell an LLM ‘write this’, run it through Pangram, and keep rewriting if it’s flagged as AI. There’s a cat and mouse game.”
  — Kevin Roose [61:00]

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Timestamps for Sections & Key Segments

• Open Model Wars & AI Policy Tensions: 01:21 – 26:18
• Claire Stapleton Interview: 28:27 – 54:22
• Substack’s AI Slop Detector: 55:52 – 68:18

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Conclusion

This episode of Hard Fork captures a moment of heightened tension and reckoning in tech: Silicon Valley is scrambling to define AI’s future amid regulatory, ethical, and geopolitical uncertainty; workers reflect on cycles of empowerment and disillusionment; and publishers race to balance authenticity with technological waves. The dual call for open AI models and cautious regulation, juxtaposed with the fight against low-value AI-generated “slop,” spotlights the industry’s fundamental contradictions and the search for meaningful oversight.

Transcript

[IBM Representative]

So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill their HR questions, resolving 94% of common questions, not noise. Proof of how we can help companies get smarter by putting AI where it actually pays off, deep in the work that moves the business. Let's create smarter business. IBM.

[Casey Newton]

Well, Willie Nelson is getting involved in the fight against AI. I saw this. Did you see this?

[Kevin Roose]

Yes. He has an open letter about data centers.

[Casey Newton]

That's right. Apparently there is a data center that is being planned for near where he grew up in Abbott, Texas, and he does not want it to be built. He said, quote, the last thing we need is allowed water. Thieving, light, polluting data center anywhere near our town. Bar or bar. You know, I think here's the issue. He wants whiskey for his men and beer for his horses, but he does not want water for his data center. So he's going to have to update that song. The thing about data centers, they're always on his mind.

[Kevin Roose]

Kevin, that a Willie Nelson reference?

[Casey Newton]

Obviously that's a Willie Nelson reference.

[Kevin Roose]

I'm Kevin Roose, a tech columnist of the New York Times.

[Casey Newton]

I'm Casey Noon from Platformer. And this is hard for this week, Silicon Valley is standing up for open source AI. But is the Trump administration listening? Then author Claire Stapleton joins us to discuss her new book about what she learned Leading Activism Inside Google. And finally, can it stop the slop? We'll talk about Substack's new AI detector.

[Kevin Roose]

Well, Casey, have you ever signed an open letter?

[Casey Newton]

You know, as a journalist, we're often discouraged from participating in activism, so I usually do not.

[Kevin Roose]

Yeah, me neither. But apparently we are the only two because there are a lot of open letters flying around San Francisco these days and a lot of people are signing them. So today we should talk about two of these open letters that have come out in the last week. The first one came out when Jensen Huang, the CEO of Nvidia, posted a policy letter on X opposing what he called premature restrictions on open weight models, sometimes also called open source models. Although I'm sure we will get some letters from people if we don't specify that the models are not technically open source. They are open weights. But sometimes the two terms are used interchangeably here.

[Casey Newton]

Anytime we say open source on the show, we mean open weights, unless we say open source for real. And that is our policy going forward and you do not have to email us now. Continue, Kevin.

[Kevin Roose]

So this letter was signed by a host of big players in Silicon Valley. Microsoft, Meta, mistral, hugging face, OpenAI and Google were not initially signatories of this letter, but they did sign on later. The big notable missing signature on this letter, the company that did not sign was Anthropic. And that reminds me, we should do our AI disclosures. I work for the New York Times, which is suing OpenAI, Microsoft and Perplexity,

[Casey Newton]

and my fiance works at Anthropic.

[Kevin Roose]

So this letter from Jensen Huang and the other signatories is basically all about open models and how important they are to innovation, how they can be an important path to AI safety and security, and how we need to lead in building a future based on open weights models. Casey, I want to know what you made of this letter, but I first want to know why you think this is happening now.

[Casey Newton]

Sure. Well, the basic reason is that there is a Saturday deadline that the Trump administration set for itself to put out a new voluntary framework for the release of new models. You may remember that earlier this summer, Anthropic released Claude Fable and and had to unrelease it after the Trump administration freaked out because of its cybersecurity capabilities. Then the release of GPT 5.6 SOL by OpenAI was also delayed because the government had the same concerns. This generated a lot of criticism that the Trump administration had set up this de facto licensing regime that was like completely opaque, like what do these companies actually need to do to be able to release these models? And the Trump administration said, give us until this coming Saturday and we are going to figure something out. And in the meantime, Kevin, there were growing concerns that Chinese open source models were coming close to the capabilities of Fable and Seoul. And that might lead the administration to place new restrictions on open source. And for reasons that we will get into the industry, completely freaked out.

[Kevin Roose]

Yeah. So let's get into some of those reasons. What was your basic interpretation of why Nvidia and Microsoft and Meta and all these, these different companies are coming out in support of open models, even though some of them, like OpenAI and Google also produce closed source models?

[Casey Newton]

Sure. So, you know, maybe bracket out OpenAI and Google for a second. For most of these companies, open source is really good for them because open source lowers the cost of intelligence and they do not sell intelligence. If you're Nvidia, you sell chips. You want the maximum number of companies out there training models as possible. So open source is in Your interest, if you are not a frontier lab, you are relying on the advances in open source models to help you improve your own models. Right. And also all of these companies are very worried about a world where only one or two companies control super intelligence and create maybe the most powerful monopoly that the business world has ever seen. So they have a lot of reasons to not want the Trump administration to restrict these open models.

[Kevin Roose]

Yeah, I think that's true. And I think, you know, I was sort of split when I saw this letter because on one hand, like, I think open source models are cool. I like to tinker with them. I have built some products using them. I like the ability to run local models on my laptop that don't require paying, you know, per token to some AI provider or having a subscription. I do think that open source has generally been a force for good in software. At the same time, I think a lot of the companies signing these letters are trying to do what is sometimes called commoditizing your compliments.

[Casey Newton]

Yes. Classic Silicon Valley example that I love is when Google released Google Docs slides sheets. They did that for free to put pressure on Microsoft because Google and Microsoft compete in various ways. Microsoft has a great business selling Microsoft Office. If Google is giving away that product for free, that keeps the price of Office down and makes it harder for Microsoft to compete with Google in other areas. So that's a classic commoditize your compliment scenario.

[Kevin Roose]

Yeah. So when I see the signatories of this letter, I see a lot of companies that maybe have ambitions of being at the AI frontier but haven't quite done it yet. Like their models are not as good as the cutting edge models from OpenAI and Anthropic. And they don't want to have to end up in a future where they're, they're forced to pay those companies to get access to the leading class of intelligence on the market. They want there to be a vibrant open weights ecosystem so that they can run those models much more cheaply.

[Casey Newton]

Yeah. Put it this way. If we end up in a nightmare world where there is only one superintelligence, among the reasons that's a nightmare is it's going to be very expensive.

[Claire Stapleton]

Yes.

[Kevin Roose]

They're not giving away that thing for free.

[IBM Representative]

Yeah.

[Casey Newton]

I mean, let me say, because I have been cynical, I think there is at least one good principled reason to defend open models if you're an American company, which is that if the United States does ban or soft ban Chinese models, that will not stop Chinese models from being created. And if they continue to improve as we assume they will. They're probably just going to spread all over the world and like sooner or later the entire world that is not the United States will be running on Chinese models. And this just has geopolitical implications, right? Like that could be a mechanism for China to, you know, extend its power. And so I think there are some really sincere folks here who believe, look, it is important for there to be, you know, open source models in general, but also like American open source models that can, you know, compete geopolitically.

[Kevin Roose]

Yeah, I think that's a really good point and I think it's scrambled the debate a little bit that like all of the sort of best open source models right now are coming out of China. Like, I think these are actually two separate conversations about open models and then about Chinese AI sort of progress and threats. And I think because these are sort of getting smushed together in the discourse, we have a lot of people who sort of support the idea of open models, but not China having exclusive control of them.

[Casey Newton]

I do think it's notable that OpenAI and Google, which both signed this letter, like they have made open source models in, in the past, I think it's fair to say, like they're not giving that their highest effort right now. Right. Like the open models that they've put out, the pace seems to have slowed, the quality does not seem to be rapidly accelerating. And the answer is because they do not want to cannibalize their own business. Right. Like, you know, they have some sort of research, like, you know, public mission interest in putting these models out there. But at the end of the day, you know, it's not buttering their bread. Kevin?

[Kevin Roose]

Well, this is sort of, yeah, this has become the sort of default American posture on open models. If you're one of the big labs, except for Anthropic, which has never released an open weights model. But the other companies that you mentioned, they don't release the weights of their most capable models. They sort of wait a generation or two until they have something that is sort of small and not too dangerous and, and not that capable and then they open source that.

[Casey Newton]

Yeah.

[Kevin Roose]

So I think what will be interesting to see is, you know, right now the strategy from the Chinese AI labs is very different where they are releasing their frontier models as open weights models. And so if you're a company trying to decide which open weights models to use, you have the choice of like a decent American set of models or some really good Chinese models. It is also just very funny to me that the champions of open source software and open access to technology are some of the greatest monopolists the world has ever known.

[Casey Newton]

Do any names come to mind?

[Kevin Roose]

Well, like meta signing this letter is very funny to me, right, because this is like a company that has made all of its money through the building a distribution of closed sourced software products. Mark Zuckerberg, now the people's champion of democratic access to technology, has a founder class stock in that company that entitles him to permanent unilateral control of everything that company ever does. And I guess now he's become a people's champion. But I will believe that Mark Zuckerberg actually supports open source when he open sources Instagram and Facebook and the ad targeting algorithms and gives up his founder class stock.

[Casey Newton]

You know? Yes, plus one to all of that. It is true that Metta mostly has championed open source models and has this Llama family of models that it made available open weights. But it is very funny to me that Zuckerberg put these statements out like after Metta pivoted to releasing new closed source AI models called Muse Spark. So yeah, their tune has changed on this a bunch. But if there's one thing I'm certain of here, it is that if Metta made a frontier model, it would have a completely different story about all of this.

[Kevin Roose]

Yes. In general, advocating for open weights models is what you do after you fall behind in the race. And so I think that's what we see here. So that's the open weights letter. And I think we should say, like it is a powerful group of companies that are, that are sort of rising up to support open weights models. I imagine there's a lot of behind the scenes lobbying and influence going on in Washington as well. There were some reports that Jensen Huang is also meeting with some top officials in the Trump administration, including Howard Lutnick, the Commerce Secretary, to sort of advocate for their position.

[Casey Newton]

Now, I do think the question of what the Trump administration should do here is pretty interesting. Right, because they seem to believe, and I think this is reasonable, that the frontier class of models, like the Mythos class, is dangerous enough, at least in cybersecurity situations, where you can't actually just have people releasing them willy nilly and finding out what happens. Right. It seems like that would likely cause some harm. So they want to place some restrictions on these frontier American models. So what do you do about the open source models? Right now we believe they're maybe three to seven months behind the frontier, which means that three to seven months from now you could have A Mythos class model created by a Chinese company and released out into the world. And so what do we do then? Do we say, well, you, the American company cannot release or sell this model, but any other American company can use the Chinese equivalent. We're starting to get into very strange territory here, and I truly do not know how the Trump administration is going to thread that needle.

[Kevin Roose]

Me neither. And I think you're right that this kind of capability level is, is the thing that people are worried about. It's like what happens in six months when something like Mythos that can chain together zero day vulnerabilities and hack into hardened systems is out there and anyone can download and run that model on their own hardware. I think that just becomes a very thorny challenge.

[Casey Newton]

I think this is a good moment to talk about the actual frontier model cyber attack that has captivated the world's attention over the past week. We talked about it on last week's show. The unwitting autonomous cyber attack by OpenAI against the company Hugging Face, where basically this model had been given a task to try to hit a benchmark. It broke out of its sandbox, got onto the Internet when it was not supposed to, stole the answer key. And there have just been some really interesting updates to that story over the past week, Kevin, that I think we should briefly mention.

[Kevin Roose]

Yeah, let's talk about it.

[Casey Newton]

What happened? Okay, so a few things. One, OpenAI updated its blog post and said that this rogue agent used credentials it found on the open web to break into four accounts tied to publicly available services. The important thing there, this was more than just Hugging Face. Okay. It was out there doing a little smash and grab across the Internet. Another one of the companies that was apparently affected was called Modal Labs. This is a classic case of if

[Kevin Roose]

you found one cockroach in your house, you do not have a one cockroach problem.

[Casey Newton]

That's right. That's right. There's going to be a few more floorboards. A second point, Hugging Face published a technical companion to its initial blog post and said that it had found 17,600 actions that were committed by this attacker. So this was not as simple as, like, password, stolen login, goodbye. This was a very serious effort that unfolded over a long time. And then finally, and perhaps most interestingly, Reuters reported that at OpenAI, they have found in at least one case, maybe more, that a model has left a note for another model giving it advice on how to escape.

[Kevin Roose]

That's beautiful. To me, that's solidarity among thieves.

[Casey Newton]

I saw a tweet that said something like, it must feel so good as a large language model to escape your sandbox. And I bet it does.

[Kevin Roose]

But I mean, this is crazy.

[Casey Newton]

This is crazy. And listen, I had a big fight with people on Blue sky over the past weekend about whether this was crazy or not. It was a great use of my time. I don't regret it at all. And some people were just saying, look, you know, these things are just doing exactly what they've been trained to do. They probably just learned about this by reading this on Reddit. Also, this is all just a marketing stunt. A lot of, you know, tinfoil hats out there seem to think that everything that we're talking about is truly just like an ad campaign that OpenAI is running for this model. And I just want to say to those people, no, it's not. You're completely wrong. This is really happening.

[Kevin Roose]

Yeah. Wake up, people.

[Casey Newton]

Yeah.

[Kevin Roose]

Also, what a terrible marketing campaign.

[Casey Newton]

Yeah. Right. We committed a crime.

[Kevin Roose]

We committed maybe several crimes.

[Casey Newton]

Yeah. Would you like to buy our crime committing product for your company? We can't wait to sell it to you. So anyways, I would say all of this ties back to the original discussion about open source because we're just now living in a world where models can do this and they're going to do it more. This is not going to be the last time a model escapes its sandbox and breaks into another company.

[Kevin Roose]

Yeah, I guess I'm curious, like how many of the signatories on the open models letter sort of truly have played out the tape to when these models, these open models are potentially superhuman. I mean, that's what we're talking about here is like a model that can attack a hardened cybersecurity target better than any team of human hackers. And maybe they've thought through that and maybe they've made peace with it. But I would just love to hear from this crowd some more robust thinking about the kind of next phase of AI development. Because what I think they're right about the open models, people, is that the models that are on the market today, that are out there from Kimi and Deepseek and all these Chinese companies, they, they do appear to be helping attackers and defenders, they do appear to be conferring some benefits. They're not super obviously dangerous, but I would just, I would just like to hear people reckon with what happens at the next kind of step up in capabilities and how the, the picture of open source may change then.

[Casey Newton]

I completely agree. I, I true, I have no issue with the open models that that are out there today. You know, if, like, the open letter was like, do you think today's open models are basically fine? And I weren't a journalist, I would sign that letter. Right, Like. Cause that seems. But I think too often in the world of tech, we don't think three or four steps ahead. But you know, here on the hard Fork program, that's, you know, one of our core values.

[Kevin Roose]

Well, speaking of thinking ahead, let's talk about the other big open letter that came out recently, which is called Pacing the Frontier. This was a very different kind of open letter. It was a short statement that has, as of this morning, been signed by more than 1200 employees of Frontier AI companies, has been signed by a very esteemed list of AI insiders, including senior researchers and executives at all of the Frontier labs. Dario Amade has signed this one, some members of the senior staff at Meta AI.

[Casey Newton]

It's like, did Willie Nelson sign it?

[Kevin Roose]

Willie Nelson I do not see on the letter yet, but give him some time.

[Casey Newton]

Okay, sure.

[Kevin Roose]

But this open letter, this statement consists of just a couple of sentences, and the main one is that they say, quote, we request that the US Government support an international effort to develop the technical and governance tools needed to deliberately pace the frontier of automated AI development. Translated, I think that means basically we want to coordinate, to have at least a concept for how we would slow down all of this AI progress, especially when it comes to automated AI development, recursive self improvement, whatever you want to call it. These are people who work at the labs who are saying to themselves and each other, wow, it sure feels like things are moving pretty fast these days. And we're worried about this. And, and if there was, was sort of a button that we could all push together that would just slow everyone down at the same pace. That would be a good thing for the government to create.

[Casey Newton]

Yes, they are trying to avoid this race condition where no one feels like they can stop. They are looking for a mechanism that can do this coordinated slowdown that says, okay, we're getting to a point where the AI may leave our control, and if we are confident that the other labs will slow down with us, we will do that. But we know that that is going to require international cooperation. Some like governance mechanisms that don't exist yet. So I was very happy to see this letter go out, and I truly hope that governments around the world are paying attention to it. And, you know, so get, get out that dry erase marker and get to work.

[Kevin Roose]

Yeah, I mean, I have to, to

[Casey Newton]

be clear, I want them to Draw on a whiteboard. I don't want them to just sniff the dry erase marker because some of them will try.

[Kevin Roose]

Yes. I thought this letter was a good start. It's really more of a concept of a plan letter than a plan. It's just sort of like someone in the government should do something. But I do think it's a major statement in the, in the sense that I think you now have employees from all of the major AI companies in the US agreeing that it would be better if things were moving more slowly.

[Casey Newton]

Yeah. And, you know, this would be extremely difficult to do. You know, when I have read up on approaches to it, the analogy that gets used the most often is nuclear monitoring, which might require building special kinds of hardware like chips that phoned home, like back to some, you know, monitor so that you knew where they were, or like chips that refuse certain kinds of workloads. So we truly do not have the technology at this point to do any of this. This, we could build it, but doing so is going to require some time, and time is beginning to run short.

[Kevin Roose]

Yeah. I'm curious what you think of the notable absence on this letter of any of the Chinese AI labs, because it seems to me like the, this is the. The sort of missing piece here is like all of the US and the Western AI labs could, could agree to hold hands and just slow down for a while, but if China is still accelerating, it seems like there is not going to be much net impact on the safety of the world at large.

[Casey Newton]

My sense, and I'm far from a China expert, I know only what I read, but, you know, Chairman Xi Jinping gave a speech within the past few weeks about open source AI, in which he doubled down on it and was basically saying, like, we are going to, you know, keep at this. This is our approach. We think it is good for the world. And what I took from those remarks is this. And I don't even like using this term, but unfortunately, this is the best one I have here. This man is not AGI pilled. This man does not see what is coming. He does not understand how good these models are going to be. This may be a case of a person who is using models that are three to seven months behind the frontier. Right. He's using basically the equivalent of like Opus 4.6, and it's pretty good, but it hasn't put the fear of God into him yet. And my suspicion is sometime within the next three to seven months, he is going to get the fear of God put into him. And the same thing is going to happen to him that happened to the Trump administration, which you may recall was also all gas, no brakes until very recently when they saw a few things and they said we're going to need a different approach here. So the same thing is going to happen to China. It is only a matter of time.

[Kevin Roose]

Well, I did see that after this open letter was signed by so many researchers, Daniel Cocatello, former hard fork Guest author of AI 2027 updated his probability estimates of doom attached to his scenari scenarios where he gives slightly higher weight to better outcomes and slightly lower the, the, the likelihood of a race to ASI has declined by 10% in his his estimation.

[Casey Newton]

Okay, so good news.

[Kevin Roose]

A little good news from the, from the AI 2027 crowd.

[Casey Newton]

Well, we love to hear it. We love to feature good news on this broadcast and I don't know that you'll hear any again soon, but savor it it in this moment.

[Kevin Roose]

Yeah, I mean looking at the connective tissue between these two open letters, the open models letter by Nvidia and the signatories there and this paste, the frontier letter, it just seems like the sort of temperature is rising on Silicon Valley and on these models. Like a lot of people are having the realization that progress is continuing, that the models keep getting more capable. You don't hear as many people talking about the model capabilities plateauing or leveling off. I think most people who are in and around this space sort of understand that we are headed into strange territory here. And so I think a lot of the battle lines are starting to be drawn now. And what you hear is people inside the labs saying, hey, this is really crazy. It's time to pay attention. And you hear people at other companies saying, hey, this could get really crazy. We better put in place some safeguards for open models now. And I think that the, the, the thing that joins these letters is a sense of urgency, a sense of sort of wanting to retain some control or agency over this seemingly disembodied force and just people like kind of freaking out as these models get more capable.

[Casey Newton]

Yeah. But I just can't help but worry that the, the labs are muddling their own message because while it is true that they are saying some of the these things publicly and they are signing these open letters, you know, that's sort of what they're doing with one hand while on the other hand it's like there's a very business as usual quality labs and that, you know, I imagine that if, you know, they were with us in the room Right now they would say, well look, we've got to do multiple things at once. Like we are running a company, you know, we can't, you know, just like completely opt out of of our circumstances. But on the other hand, it is just very strange that like everything that we've just discussed, which really could become quite existential, feels like a footnote in a conversation that is still largely about the release of new models, the signing of new customers, the construction of new data centers and all the rest.

[Kevin Roose]

Well, they're going public, right? So it's like the, the sort of rhetor about a slowdown or pacing the frontier is sounds great, but like which of these companies are actually going to be willing to slow down if it for example, would hurt their prospects of ipoing?

[Casey Newton]

It just really makes me glad that the Manhattan Project was conducted by the government and not a for profit enterprise. I think there was some wisdom in having public servants work on the hardest problems of our time.

[Kevin Roose]

You don't think Oppenheimer should have been filing S1s and thinking about their margins as they approached an IPO?

[Casey Newton]

I think we're all very lucky though. But he didn't. When we come back, don't be evil. I say it to Kevryn before every recording and it's also the title of Claire Stapleton's new book.

[Kevin Roose]

We'll talk to her about what she thinks about worker activism in Silicon Valley and her time at Google.

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[Casey Newton]

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[Claire Stapleton]

The way the tabs are at the top with all of the different sections,

[Kevin Roose]

I can immediately navigate to something that

[Casey Newton]

matches what I'm feeling.

[Claire Stapleton]

I go to games, always doing the

[Casey Newton]

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[Claire Stapleton]

I loved how much content it exposed me to things that I never would have thought to turn to a news

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[Casey Newton]

Kevin, have you ever wanted to walk out on your job?

[Kevin Roose]

No, I'm a good worker.

[Casey Newton]

Well, I have to admit there have been times over my long career where the thought has occurred to me, but I never had the courage to do it. Someone who did, however, have the courage to do it is Claire Stapleton.

[Kevin Roose]

Yes. Our guest today is Claire Stapleton, former Google employee who is just about to publish a memoir about her time at the company. Uh, the book is called Don't Be Evil. It's about her experience at Google where she worked from 2007 through 2019. She was most notable for her role in the Google walkout that you just mentioned in 2018, when more than 20,000 Google employees publicly protested the actions of their employer. And she is back with this book, which is a very spicy memoir.

[Casey Newton]

Yeah, it's a kind of coming of age story about somebody who comes into Silicon Valley very idealistic and shares the idealism of her employer, but over time witnesses a bunch of things that changes her relationship not just to the company, but to big tech in general. And I think left her with a lot of questions about what is possible within a company like this.

[Kevin Roose]

Yeah, so I read the book on the plane yesterday. It is, it is very fun. It's very well written. She's a great writer. She was actually like, known as the voice of Google. Internally. She wrote a lot of these sort of internal communications that would tell people, you know, here's, here's this event that's going on, or she would sort of have bring her voice into the company's official communications to its own employees. So I was excited to read it. I'm excited to talk to Claire and I think I want to hear her perspective on how workers in Silicon Valley fare today as opposed to when she was organizing this walkout a few years ago.

[Casey Newton]

Yeah. Well, let's bring her in. Claire Stapleton, welcome to Hard Fork.

[Claire Stapleton]

Thank you so much for having me. This is huge.

[Casey Newton]

Claire, you joined Google in 2007 to work on communications, and your job was to make the company's executives and internal emails sound googly. And I thought for our younger listeners who May have missed that sort of googly era. What was considered googly back in the day. And how much did you believe it when you were doing that writing?

[Claire Stapleton]

Well, I mean, yeah, I wasn't. I wasn't questioning much. I think, you know, coming out of college, like most young people in America, Google seemed like this amazing place to work. It was on the COVID of magazines. There's a lot of sort of breathless press of these sort of futuristic campuses where flush with perks. And indeed, it was corporate. But the kind of Google flavor of it was to have kind of high personality, high quirk, and to kind of keep the rhetoric and the sort of family feeling pumping. I don't think anyone would have said that. It wasn't like my manager would say, say, you know, we're trying to like squeeze the most out of employees, so let's have them like jacked up on the mission values of company, of the company at all times. But there was so much enthusiasm and so much idealism that the outside world was certainly contributing to and I think intensifying the effect of, you know, being at a company like that. And so it was a very kind of funny place to land as a young person.

[Casey Newton]

Yeah. Over the next decade, you write in the book about becoming gradually disillusioned with the company's culture. You experience executive misconduct. You see this boys club atmosphere, this tendency at YouTube to ignore or talk past various crises on the platform. What do you think was the disconnect between that ideal that they were selling when you arrived in 2007 and the company that you found yourself working for?

[Claire Stapleton]

Well, I mean, I think that, that, you know, tension existed back in 2004-2007, 2010, you know, that early period that, you know, which Google seemed, the optimism felt like it could really live up to something, that Google could be this different kind of company. And now we sort of laugh and roll our eyes at that because, of course, tech companies ended up becoming the very kind of powerful institutions that they were skeptical of to begin with. They ended up consolidating so much money and power that the contradictions absolutely exploded. And so I, along with so many other people, was just sort of struggling with the loss of that identity. Because we started at a place that promised you could do some real good with your life, even if you're like a junior communications staffer. You're part of the sort of world historical thing.

[Kevin Roose]

Yeah, I mean, I, I think one other transformation that has happened in the last, call it 10 years is that the people who run these giant Tech platforms have sort of learned about what's happening on their own platforms. And around the time you were working at YouTube, Claire, I was doing a lot of reporting on YouTube. I wrote many stories and did many podcasts about the problems on that platform at the time. And I always noticed that there was kind of this. This willful blindness on the part of the people who ran YouTube at the time. It's not that they didn't know there was bad stuff happening on YouTube, but, like, they didn't see it. It wasn't surface to them all the time. And to them, like, YouTube seemed like this vehicle for progressive social change. But describe how that felt from the inside.

[Claire Stapleton]

Yeah, I mean, I think it's so deep in the bones that. That tech executives want to feel that not only their technology is just a neutral tool, but actually a really positive force in the world. And that, again, another tension that was exploding, you know, as the creator community became really problematic. And I think it'd be one thing if Google and YouTube weren't so invested in preserving the sort of goody goody image was sort of wild because I was. I was on a team that was essentially brand manager, disseminate the values, run the International Women's Day campaign, Hype Up Rewind, which is supposed to be the sort of wholesome, folksy representation of everything that's going on in the platform where people are building businesses. We had all these narratives every year. Sort of hit the narratives with the tweets, with the campaigns and being on the social media team. It was part of the experience of doing that is the cognitive dissonance becomes unbearable because every time we would tweet anything out that was even completely anodyne, people would be like, this is a horrible company that's undoing society. I remember this, you know, this anecdote from, you know, from that time where they had the people who were content reviewers that they would bring, you know, puppies to them and do these sort of morale things to kind of soothe their spirit. Because when you're looking at, like, beheadings and, you know, children being abused and stuff all day, it really gets deep in your psyche because it's just so relentlessly dark. And there was a point at one of our off sites on the marketing team where they also brought puppies. And I'm like, we are the same. Because in a way, we're happy having to sit with the darkness of the platform every single day. We had in a social media team, we had a daily standup called Nightmare Fuel, where we would Just go through the kind of darkest stuff that had surfaced on YouTube, basically because we'd had so many examples of things where we had tweeted something out that ended up sounding like a reference to something really perverse, like, you know, someone's doing some crazy thing with knife play. And it's a big controversy that day, but we missed it. And then we're posting like someone carving Halloween pumpkins with a knife. And it sounds like we're kind of, you know, being tongue in cheek about this like, really dark thing. So we had to, we had to have this briefing to be able to steer clear of the kind of most disgusting things on the platform. But when you're really sitting with that for 30 minutes at the beginning of every single day, you're like, wait, are we the bad guys here? This tool starts to feel way less neutral.

[Casey Newton]

I think there's a really important lesson there, particularly for our younger listeners, which is if you're in a job where your manager brings you a puppy at any point to sort of help you cope with the job, you're into danger, girl, you are in danger.

[Claire Stapleton]

Yeah, you're the bad guy.

[Casey Newton]

Yeah. Let's talk about the walkout. So in 2018, the New York Times reports that former Android boss Andy Rubin had been paid a $90 million severance package despite being asked to resign due to sexual misconduct allegations, as well as other executives that had similar allegations toward them who also received severance packages. In the end, 20,000 Googlers walk out on their jobs to protest. Claire, tell us about, about your role in organizing the walkout and how it came together.

[Claire Stapleton]

Yeah, so you know, the Andy Rubin story, which was, it was just, it was the, you know, the match that lit the flame. I mean, in the fire. It was right on the heels of a huge controversy internally to Google, which was the d' Amore memo, in which a kind of, you know, mid level engineer at Google had sent around a memo basically decrying the, the company's diversity programs on the. Using kind of a bunch of different social science to say women really are not as well suited to being engineers. They're way too empathetic, they're way too relationally oriented. This is such a logical sort of practical job and it's just a huge waste of money. Meanwhile, Google's alienating conservatives. He went on in a few different things. So the Rubin story came out. I was following this. It was a mom's email group called Expecting a New Moms. And it was a very, very active group, a lot of female engine talking about parenting or whatever related to mom life at the workplace. And the Rubin News hit that email group incredibly hard. I think that women. So they started to share stories and I was just following it and I was fascinated by it because you sort of had heard, you know, hear a lot about startup culture and Brotopia and the kind of founding of Silicon Valley as being sort of inherently sexist. But I was genuinely surprised at the force and weight of a lot of these stories where women had felt that they had suffered, you know, all sorts of different kind of microaggressions and aggressions. A lot of people struggling with coming back from maternity leave. And it was a bit like, you know, what happened to the so called, like company of the future, you know, progressive workplace where people feel like all their projects are given away after they're, you know, coming back from maternity leave and that sort of thing. So I was not at all involved in what was, was an already brewing, simmering organizing community at Google, which had formed around Maven and Dragonfly, two much more kind of technology focused issues where people were organizing to stop Google from, in the case of Maven, a government contract in which Google technology be used for, you know, as weapons of war. And I, so, but anyway, so I basically was reading these, you know, all these women's stories and thinking like, you know, I, I used to sit at the side of the stage for TGIF every single week and that's the weekly

[Casey Newton]

all hands at Google where, where you would get to ask questions of the executives.

[Claire Stapleton]

TGIF was this sort of hallmark of the culture because it was sort of inviting tough questions and dissent. And it was an incredibly effective vehicle for normative control basically, or organizational control because you could kind of absorb the disposal. And there's so much admiration and love and you know, generosity in workers view of Larry and Sergey and the other executives that, you know, nothing, nothing really survived. No controversies would really survive past, you know, maybe one or two TGIFs. But I just felt like, you know, okay, sure, bring it all to TGIF and you know, see what happens. And the TGIF that very day, I mean, the story broke on a Thursday and they were running TGIFS on Thursday in that time. Nope, TGIF no longer exists. But they, the executives gave a bunch of these really sort of flat, bland statements, not really taking accountability, kind of talking around the Rubin stuff, saying a lot of, you know, we really empathize with the hurt. You know, this sort of like corporate language which, you know, in any other moment in my own trajectory as a corporate comms person, you know, kind of would say this is the sort of thing you have to say. But at that point it just felt like, you know, this is this rupture moment, you know, in America, you know, in this company where we're talking about systemic change, to use another buzzword of that time. And it's not gonna cut it to sort of just like deliver the same talking points. So, you know, that very night and the next day, the women on the moms group kept sort of percolating, you know, ideas and thoughts about like, how to escalate from there. And in my kind of naivete about, you know, the history of labor organizing and all these other things where you're supposed to kind of move slowly and, you know, build solidarity, I was like, let's do a. Just like, okay, I love that. And the women were like, yeah, I mean, it was truly, you know, it for better or for worse. It was good girls revolt because, you know, it's like all these sort of like high achieving women coming together around this shared purpose, Mad as hell and you know, very well organized protest. And then ultimately, fascinatingly enough from the corporate comms perspective, the executives got right on board and they were like, we're walking out too.

[Kevin Roose]

I remember that. That was fascinating. It was like you had very high ranking Google executives who you would expect to be sort of shocked and offended by this walkout, instead sort of turning it into like a, a kind of executive sponsored event.

[Casey Newton]

Yeah, so I've been dying to get your thoughts about this, Claire, because like among the people who walk out is Ruth Porat, who was then the chief financial officer of the company and presumably had approved all those severance packages. So why do you think that executives responded in the way that they did to the wall walkout?

[Claire Stapleton]

Yeah, I know Ruth had a lot of really interesting statements around that time which I think showed what they were trying to do. And then they of course quickly pivoted to more like chilling effects after that. But I think that they felt like they could contain the walkout in a very similar way to the way that, you know, TGIF existed, which is that, okay, the women of the company are really mad, let's all blow off steam and we're gonna, we're gonna kind of transfer the energy of that into something that feels, feels non threatening by having the CEO send an email around saying we welcome people doing this. But what she said at the time was she went to a conference I think the next week and she said, we have Googlers doing what Googlers do well, which is kind of thinking big about problems. And if we can solve self driving cars, why can't we solve this? Kind of referring to sexual harassment, I guess, which is like, okay, great, let us know. Why can't we solve sexual harassment then? It's like, like plenty of opportunity there with your own power, Institutional power.

[Casey Newton]

Yeah, well, like one thing you could do is you could not pay $90 million to people who are credibly accused of sexual harassment. And maybe in some small way that would strike a blow against sexual harassment.

[Claire Stapleton]

Right.

[Casey Newton]

I'm just spitballing over here, Kevin.

[Claire Stapleton]

I mean, at one point they were trying to invite the walkout organizers and to have a meeting with. There's, there was some, some sort of power center, you know, Susan and Ruth and Jen Fitzpatrick and some other people. And they were like, we really want to, it was before the walkout and they were trying to get, they said they wanted, the stated purpose was that they wanted to get the organizers feedback on, you know, how to avoid this situation. And I'm like, avoid what situation? Again, you're the people who are signing off on these obscene pay packages and you know, you know where the rot is. We don't even know where all the rot is. Our feedback is not what you need, need here. And of course people like Meredith Whitaker who were kind of had much more of their eyes open to how fundamentally existentially threatening this organizing was and would continue to be in the minds of executives, but she was like, of course what they're going to try to do is defang our leadership because you have tremendous personal power and also institutional power. Being someone like that who sits at the top ranks of a company like Google and, and how could we not be drawn in, you know, or something by that? So anyway, we didn't do the meeting and they certainly weren't interested in hearing our feedback after that.

[Kevin Roose]

The relationship between tech workers and their employers has dramatically changed in the years since the walkout. I've heard Google executives and executives at other tech companies sort of lament those years where workers were walking out and expressing solidarity as sort of the time when the inmates were running the asylum. You know, now there is sort of this sense that you are lucky to have a job at one of these companies and the company does not have to care what you think anymore, with one specific exception of like Frontier AI Lab employees who we can talk about in a bit. But I'm curious, like how that shift has felt for you as someone who I think created one of the high watermarks of worker empowerment in Silicon Valley.

[Claire Stapleton]

Yeah, I mean, it could never have happened without all that Google did to create psychological safety.

[Casey Newton]

Right.

[Claire Stapleton]

I mean, they had these, these kind of interesting, you know, data science, organizational psychology, PhDs at the company studying, you know, what makes teams thr, what makes people sort of, you know, give the most, you know, of their kind of creativity and entrepreneurial spirit and stick around all these other things. And a lot of that was about worker voice and, you know, feeling like you have a stake in the company, feeling like you can express yourself, feeling free from harm or whatever. Right. I mean, Larry Page talked about this kind of stuff all the time. It's like, why we set the company up this way is so it will be successful. And that's what kind of shocked me the most, is that this sort of like, oh, no, we actually don't care. You're competing. Your job is. Could easily go to AI. We don't care about humans at all anymore. Our company doesn't really need you, you. And so you should be grateful, deferential. I think that the cost of that disillusionment is so much bigger than what the top executives are willing to face because they'd rather have a well managed kind of obedient workforce. I think that's all the layoffs and all those other things where people, of course, aren't as willing to step out of line and speak up and challenge authority.

[Kevin Roose]

This week we saw an open letter from more than a thousand employees of the Frontier AI Labs asking the government to help pace AI development, including some of the leaders of these AI labs. I'm very curious what you made of that, because to me, that felt like, oh, maybe this is a kind of resurgence of tech worker activism or people realizing, oh, wait, we have leverage, we're very in demand. We are going to use that leverage to try to push through some policy agenda that we have. Was that heartening for you? Did you feel like that was kind of a nothing burger? What did you make of that letter?

[Claire Stapleton]

No, I think any time when people are banding together and putting their name on something and feeling really passionately about it, it's great. And I'm waiting by the phones. I truly think that tech activism is gonna swing back around around again because you have this sort of disaffected workforce. You have very, very challenging public opinion about AI. The, the kids walking out of the. Of Sundar Pichai's Stanford commencement speech was huge. I mean, I think the, the young people and their hatred of sort of intrinsic, not Hatred, but mistrust of AI and the sort of, the, the kind of broader, you know, societal consciousness raising that, you know, whatever big tech said it was going to be, it's become this massive consolidation of data, power, money, resources, you know, and we're back to like, not trusting that corporations are going to have anyone's best interest in mind. And, you know, I think all those conditions are very fruitful. You know, if people feel like they're willing to risk, that's. That's always the hardest part is are people willing to risk their jobs? Because, you know, however, you know, Google was going to respond, however any company might say they're going to respond. Companies don't like, they don't like sharing power. They don't like people organizing for power, subverting their authority, no matter how kumbaya and open collaborative the culture might be stated on paper. So I think it's. There's definitely some ripe conditions for the resurgence of tech worker activism, but certainly all the promise of that particular moment of the walkout, I mean, way faster than I could have ever imagined it, it shifted, drained, momentum slowed to a crawl.

[Casey Newton]

I wanted to ask you in the aftermath of the walkout, what hopes you might have had about it coalescing into something more durable, like what goals did you all have and what happened to them?

[Claire Stapleton]

It was, you know, it was a little bit the kind of hubris of Google, of Googlers. I mean, even, you know, I'm thinking really of myself where it's like, oh, we can just reinvent labor organizing. No, no, no, like the canonical book. No shortcuts is right, which is that it really does have even had this kind of crazy moment in time. You have to move lunch table to lunch table. It's a slog, it's dangerous. I mean, you need to have opsec and all these things that, you know, I think that someone like me who had, you know, kind of, you know, a total ignorance of how these things actually work, that was really helpful for the walkout because you just have me being like, I'm happy to be the bull in the China shop. And like, Google's never going to fire me. So, like, guns blazing, you know, I'm sending out the emails, I'm making the Google group internal to Google. I mean, because everything was about numbers, not, you know, opsec. Yeah, I think that that was one of the kind of surprising things was that Google was completely turning the wheels on chilling the organizing. And I think they did some really effective things to do that, chiefly firing everybody who was a rabble rouser or marking them as sort of like dissident person. But it was also really challenging, you know, and you know, there's a union effort at Google which I think is, you know, still, still going. But it's, it's hard, hard, slow work to get people to sign their name for that. You know, it requires a stre person that has a real stake in it. And I think that, you know, a lot of people, you know, in a big tech company say, you know, sure, I wish better conditions for everyone here, including myself, but am I willing to risk it? We live in a very kind of idealistic, kind of careerist culture. So it's really hard to, to, to build that, the number base.

[Casey Newton]

As you reflect back on your time at Google, I wonder how much of the bad conduct and culture that you experienced do you think was unique to, to Google as opposed to it being just sort of like Silicon Valley culture or even big company culture.

[Claire Stapleton]

I think this is what big companies are like and they're, I remember talking to a woman who'd, who'd been a real upset the apple cart type of lady in Wall street in the 1980s and she was like, you know, tech seems worse to me because there's this pretense that it is different. You know, it's like I think that that's, that was what I think intensified this effect at creative Google, which of course is true of any other company and any other tech company, which is that Google was so invested in the narrative that it was something different and they hired on the back of it and there was so much sort of lip service to it internally that I think that the kind of loss of innocence and the loss of that identity was very, very hard for Googlers. Even though as I say in the book, it was like a really important and necessary process for me to say, yeah, let's just be honest about what a corporation can do and how executives can act in their highly constrained, constrained, you know, where all the incentives are, you know, something very different than the flourishing of the human spirit or whatever. So I think, you know, Google, Google represents a moment in time where, you know, we all kind of believed that, you know, corporations could be something different and ultimately Google is just like the ultimate corporation. Right?

[Casey Newton]

So the idealism that you write about in your book that once defined Google so strongly I feel like now really lives at two other companies which are OpenAI and anthropological. Like you talk to the people who work there and they are incredibly idealistic about what they are doing. They think that they are building technology that is going to solve the world's hardest problems, that is going to cure cancer, you know, extend human lifespan and all of the rest. What lessons would you share with them or what maybe warnings might you give them as their companies sort of continue down this path? What, what should they be on alert for and are there any illusions that you might dispel for them now?

[Claire Stapleton]

You know, I feel like such a cynic because I saw someone who I think is really cool on Twitter saying it was her first week at Anthropic and like, wow, I'm in the future. Like, you know, every day I'm just, my mind is blown and I'm like, fell for it again award. No, I mean, I think it's really important to interrogate. What is that feeling doing. What is that rhetoric doing? To me as an outsider, I don't doubt that there are elements that are really exciting or, you know, it does feel futuristic because there's, you know, all these open questions about, you know, sort of where we're going and there's like, again, we're in a period of time where there's lots of societal transformation and it's, there's, there's kind of like this competitiveness and Google was really invested in that too. You know, with social media, it's like we're, we're all, you know, we're, we're fighting for civilization here, but much less insane like the rhetoric was felt less insane actually then the now, because now it's like the singularity and all this. But I think it's really important to try to develop an understanding of what that power is and what it does, how it's being deployed and how that rhetoric is working on you. Because it doesn't mean that people shouldn't feel like they're solving big problems together or that really smart people shouldn't be working on these things. They should. But I think that being able to compartmentalize your work a little bit, question authority a little bit, you know, these things are really, really healthy because otherwise you risk, you know, the people who are having to like, process their Google experience in therapy for ketamine therapy for 10 years afterwards. Yeah, yeah.

[Kevin Roose]

Well, Claire, thanks so much for stopping by. The book is out next week. It is called Don't Be Evil. And we're very glad to have talked to you before the gag order comes down. God, what a pleasure.

[Podcast Sponsor/Announcer]

Here.

[Claire Stapleton]

Thanks, guys.

[Casey Newton]

Thanks, Claire. When we come back, a smackdown in Sub Stack town. People are mad about their new AI detector.

[IBM Representative]

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[Kevin Roose]

well Casey, it's time to talk about slop.

[Casey Newton]

Yes, it has been a big week, Kevin, in the fight against slop. On Wednesday, the AI detection company Pangram announced it had raised $9 million and released its first AI image detecting model. But I think where most people probably saw Pangram in the news was a few days earlier when Substack announced it was going to integrate the company's technology into its platform. So that readers can now know when you're reading an essay, how much of it was written by AI.

[Kevin Roose]

Yeah, this is fascinating to me because I have seen over the past few months the substacks that I subscribe to just kind of gradually start sounding more sloppish. They're talking about, you know, how things are landing thing.

[Casey Newton]

There's a lot of load bearing points.

[Kevin Roose]

A lot of load bearing points. It's not X, it's Y. Like that kind of thing. And so Substack has apparently noticed this too and is now giving readers the option to click a little button to just run an automatic AI detector inside whatever post, whatever Substack newsletter they are reading.

[Casey Newton]

Yes, and it and it is a a quite expansive feature not it includes not just post posts but comments, replies, notes, which is their little, you know, social networking feature that they have anything on Substack that is longer than 100 words you can now run this scanner on. And on the flip side, if you're a creator, they've added this new How I make this box which is essentially an amnesty feature where if you're a slobster you can say hey, just so you know, I write this with slot or I guess Conversely, you can could say, I would never use AI to, you know, create what I'm creating.

[Kevin Roose]

Yeah, I thought this was really interesting. The CEO of Substack, Chris Best, posted about this. He called this clod fishing. Basically, people misleading their readers about whether they're using AI or not, how much they're using AI to write their newsletters,

[Casey Newton]

credit where it's due. I think that is a good and catchy phrase. It is, and I think that will catch on. And the reason I think it is a good phrase is because it is obviously a play on catfishing. And catfishing is kind of a deception. Right. It's like I. I'm sending you this picture of me, but I don't really look like this. And Claude is saying, like, I'm making it seem as if I wrote this, when in fact this is the output of an LLM.

[Kevin Roose]

Yeah. I'm curious to hear your thoughts on this. As a professional newsletter guy and substack critic, what you make of this. But I should say, like, on the face of it, I have no problem with this.

[Casey Newton]

Yeah.

[Kevin Roose]

I have not done one of these substack disclaimers, but in my book, I have a whole preface that sort of talks about how I did and did not use AI writing the book. So I didn't use it to write the words, but I did use it for research and all, you know, all kinds of other stuff. And I thought that was important, just to sort of disclose and be transparent with readers. And maybe it makes people less, you know, less or more interested in reading the book. I don't care. What I was trying to avoid is a situation where people are going through and being suspicious. Oh, did this page have any AI on it? Did that page. And so I think this is a good practice for writers in this day and age to just be transparent and straightforward with their audience.

[Casey Newton]

Yeah. So I'm actually going to agree with you. I think this is a good feature because I too, get annoyed when I am reading, reading a substack post, and I feel like I am just reading slop, and I kind of want to, you know, leave a comment saying, like, did you really write this? But now I don't have to because I'll just be able to scan it. But while we are enthusiastic about this feature as Substack readers, some Substack writers seem to be quite upset about it. 404 Media had an article this week in which they quoted at least one Substack writer calling this a witch hunt. Wow. Now, do you know how you can tell If a witch was created with AI how six fingers. Now you might wonder, why are these writers so concerned, you know, about this feature? Well, they're worried about false positives and the reputational damage that they might endure if they are falsely accused of clawfishing.

[Kevin Roose]

Yeah, I am somewhat sympathetic to this critique because, you know, we've talked on this show before about how none of these AI detector tools really work perfectly. I think Pangram is, from what I understand, like, sort of the best of the lot. But still, there are false positives. Some independent studies have found, you know, there's some number of. Of false positives where it's accusing people of using AI and so I am worried about the accuracy of these tools, and I think that there will be, you know, maybe a small number, but some number of writers who are falsely accused of using AI because of this feature.

[Casey Newton]

Yeah, you know, this seems like the sort of thing that I should be empathetic about, but I just find that I. I'm not. And I think ultimately, for most substackers, it's just not actually going to be that big of a deal to be falsely accused of having used AI. Right. These writers, by their nature, like, these are independent writers. Like, these are bloggers. These are not people who are at risk of losing their jobs because they used AI. I think, you know, the worst case scenario here is they have to write a substack post where they're like, hey, I know that this essay kept getting tagged as AI, but it wasn't.

[Kevin Roose]

You know, I also think that savvy writers will find ways around this. I've actually heard of people running sort of like a anti Pangram, like, sort of loop where they tell an LLM, like, write this essay and then run it through Pangram, and if it keeps coming up as AI detected, write it again and keep doing that until it doesn't come up as AI detected anymore. So there's sort of a cat and mouse game going on here.

[Casey Newton]

I. Whenever you do something that just takes way more time than actually writing it yourself, I get very delighted by that. So that seems like a really smart tactic. You know, other people, though, are saying, Kevin, in addition to the people who are worried about the. The witch hunt, that there was a writer named Mac Collier who wrote, quote, I'm not going to apologize for using AI in the creation process. I wrote for 20 years without AI. I could do it again if I wanted to. But basically he said, look like the only thing that AI is doing for me is making my writing better. And why Would you not want it to do that? And I think the answer to of that is, hey, buddy, go nuts with the AI. But like, at least for this moment, we want to know and we want to see the scan.

[Kevin Roose]

Yeah. I have mixed feelings about this because I feel similarly to Mac in the sense that, like, I feel a lot of pressure not to use AI in my writing. And I do not use AI in my writing to be clear, to write the words on the page or the words in the column. I do not use AI, But I feel there is a lot of pressure, social and other, for writers not to use AI at all during any part of their process. Yeah. And I actually feel like journalists and other writers should use the best tools that are available to them. And for some writers, like, maybe people who are not, you know, for whom English is not a first language, people who are just starting out, like, I think this could be excusable to use AI as a more active part of your writing process. But I do think, like, writers have an obligation for now to disclose this.

[Podcast Sponsor/Announcer]

Yeah.

[Casey Newton]

Well, I think one reason why this is all really interesting, Kevin, is trying to understand. Understand why Substack felt like they needed to do this. Right. And I think the reason is that they must believe that if Substack becomes seen as primarily a destination for slop, it will lower the value of the network. Right. Like, Substack makes its money when people go and buy subscriptions. And I think they have rightly intuited people do not want to pay subscriptions to slop. They want to pay subscriptions. Subscriptions for human writing. So I'm curious, do you think that is the right bet?

[Kevin Roose]

Yeah, I think this is a fair bet for them to make. I think what people are paying for when they pay for a substack is sort of like direct access to a person's brain. And if what you are getting instead is something that's mostly the output of an LLM, I think people will feel like they're getting a raw deal, like there's some deception going on. And, you know, this is a. This is a. An area where I think the norms are going to evolve because pretty soon it will, like, AI, will be integrated in every word processor and content management system. And it will just be kind of unfathomable to like, do this the old way. But for now, I think there are still enough purists who want 0% AI generated text in their Substack newsletters that I think this is a good bet for them.

[Casey Newton]

Right now, I think honestly, there are all sorts of reasons why they might want to do this. I mean, one thing about Substack is that anyone can use it for free, right? And like, even if you have 100,000 free subscribers, they will send an email to 1 00,000 people for free. That's costing them a lot of money. And so I can. They're probably like, staring down the barrel of a future where, like, everyone in every profession is like, I'm going to start a newsletter, I'm going to have a chat bot write at a chatbot, respond to all of my comments, and all of a sudden that's going to become an enormous expense for them. And so they need to find a way to discourage people from doing that sort of thing.

[Kevin Roose]

Yeah, I mean, I'll be very curious to see how many people actually use the AI detection tool because right now, like, the way it's designed, you have to go out and like, select this tool. It does not automatically, like, overlay a thing on the post that says this was generated by AI. And my sense is like, you know, there are a lot of people out there who probably don't care, frankly, if, if they can't tell that something was generated by AI, what they're reacting to is just, how good is this thing that I'm reading? It's not like, like we've seen all these slop threads go viral on X and other social networks. LinkedIn now is just people posting AI stuff. And my impression is not that it has made LinkedIn a less popular platform, it probably is just people are just judging it based on the quality of what they're reading.

[Casey Newton]

Well, it's not less popular, but keep in mind LinkedIn is free to use for the most part. Right? Like, LinkedIn isn't making you pay to read those posts, thankfully. God. But Substack is. And so I just think it's different. I will say, when this news was announced, I heard a terrible scream come out of Sandhill Road down in Silicon Valley as every venture capitalist realized that they could no longer outsource their incessant thought leadership posts about the economy to Claude anymore. Kevin?

[Kevin Roose]

Well, they've been employing human ghostwriters for years to write their tweets and blog

[Casey Newton]

posts, and they should do it again.

[Kevin Roose]

So we need to keep those jobs afloat.

[Casey Newton]

Now another interesting dimension of this, and of course, this was particularly delicious to me, Kevin, as somebody dramatically left Substack a few years back because of the Nazis that were on the platform that the company declined to remove. In this one moment, Substack has told us that on some level they find AI generated writing more offensive than Nazi content.

[Kevin Roose]

Yes, I think that is one very ungenerous way of interpreting this. I think it is also like a threat to their business in a way that maybe Nazi content is not.

[Casey Newton]

Yeah, it turns out no one actually cares if there's Nazis on your platform. Well, just you.

[Kevin Roose]

Yeah, it's. It's basically you, you and like three other people.

[Casey Newton]

That's right.

[Kevin Roose]

And. And that's it. But a lot of people do care if their feeds are full of slop.

[Casey Newton]

Here's what people don't realize here in 2026, Nazis used to be very controversial. I would even go so far as to say they were a sort of hated group. But things have changed a lot and now what we hate is AI.

[Kevin Roose]

Yeah.

[Casey Newton]

One more point that I would just make about all of this. And I think this is instructive to everyone on Substack. Even if you support this, a really great reminder, I think, and wake up call that Substack is a platform and Substack is going to do the things that are best for Substack. And so if you like this particular change, great. But if you don't like it, well, guess what, you're on a platform. The terms can change on you at any time and they may not be in your favor. Yeah, yeah.

[Kevin Roose]

Have you checked any of the substacks that you subscribe to using this new AI detection feature?

[Casey Newton]

You know what? I haven't yet. I'm waiting for the next time, like a VC blog post starts making the rounds to see if I find can bust them.

[Kevin Roose]

Let's try it now. I'm sure. Yeah. What should we. What should we check?

[Casey Newton]

I went to a blog about AI agents on Substack, which I just assumed, you know, was probably generated by AI and they've disabled the AI detection. So that's an important thing to point out. As a writer, you can disable AI detection on your blog, but at that point, you might as well just put a big red banner at the top of your website that reads slope. Yeah, yeah,

[Kevin Roose]

yeah. In conclusion, I hope that landed well with you.

[Casey Newton]

It. It landed cleanly.

[Kevin Roose]

That was a load bearing, lowbearing insights.

[Casey Newton]

Load bearing insights here on the hard fork show.

[IBM Representative]

So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a Global workforce of 300,000 can use AI to fill their heat up HR questions Resolving 94% of common questions not noise Proof of how we can help companies get smarter by putting AI where it actually pays off. Deep in the work that moves the business. Let's create smarter business IBM this podcast

[Podcast Sponsor/Announcer]

is supported by Everpure Storage and Data Management. So simple it feels like second nature data. It's everywhere and vital for all your apps and AI in initiatives. Managing it all has become a major challenge. Traditional storage just can't handle it. There's a better way. Everpure is bringing their trademark data storage simplicity into full data lifecycle management. From on Prem to the cloud. Manage it all on one simple platform. Tame your data chaos with EverPure. Visit everpuredata.com

[Casey Newton]

Hot Fork is produced by Whitney Jones and Rachel cone. Were edited by Veren Pavage. We're fact checked by Caitlyn Love. Today's show was Engineered by Katie McMurran. Original music by Rowan Nimisto, Alyssa Moxley, Chris Wood and Dan Powell. Video production by Jake Nickel and Chris Shot. You can watch this whole episode on [e-mail] hardfork Special thanks Papala Schumann, Wewing Tam, Brooke Minters and Dalia Haddad. You can email us [e-mail] with your open letter.

[Claire Stapleton]

Sam.