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

2026-07-31 11:00:00 • 1:06:47

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The thing about AI for business, it may not automatically fit the way your business works.

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At IBM, we've seen this firsthand.

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But by embedding AI across HR, IT, and procurement processes,

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we've reduced cost by millions, slash repetitive tasks, and free thousands of hours for strategic work.

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Deep in the work that moves the business.

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Let's create smart to business. IBM.

0:30

Well, Willie Nelson is getting involved in the fight against AI.

0:34

I saw this.

0:35

Just see this.

0:36

Yes, he has an open letter about data centers.

0:38

That's right. Apparently, there is a data center that is being planned for near where he grew up in Abbott, Texas.

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And he does not want it to be built.

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He said, quote, the last thing we need is allowed water-thieving, light polluting, data center, anywhere near our town.

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Bar or bar. You know, I think here's the issue.

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He wants whiskey for his men and beer for his horses, but he does not want water for his data center.

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So he's going to have to update that song.

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The thing about data centers, they're always on his mind, Kevin.

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That a Willie Nelson reference.

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Obviously, that's a Willie Nelson reference.

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I'm Kevin Rousseau, Ted Collins, the New York Times.

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I'm Casey Newn from Platformers.

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And this is hard for this week. Silicon Valley is standing up for open source AI, but is the troop administration listening.

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Then, author Claire Staplesden joins us to discuss her new book about what she learned leading activism inside Google.

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And finally, can it stop the slop?

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We'll talk about Substex new AI detector.

1:54

Okay, so you have ever signed an open letter?

1:56

You know, as a journalist, we're often discouraged from participating in activism.

2:01

So I usually do not.

2:03

Yeah, me neither, but apparently we are the only two because there are a lot of open letters flying around San Francisco these days.

2:09

And a lot of people are signing them.

2:11

So today, we should talk about two of these open letters that have come out in the last week.

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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.

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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.

2:37

They are open weights, but sometimes the two terms are using interchange.

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And anytime we say open source on the show, we mean open weights unless we say open source for real.

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And that is our policy going forward and you do not have to email us.

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Now continue, Kevin.

2:51

So this letter was signed by a host of big players in Silicon Valley, Microsoft, Meta, Mistral, Hugging Face, Open AI and Google.

3:02

We're not initially signatories of this letter, but they did sign on later.

3:07

The big notable missing signature on this letter, the company that did not sign was Anthropic.

3:12

And that reminds me we should do our AI disclosures.

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I work for the New York Times, which is suing open AI, Microsoft and perplexity.

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And my fiance works at Anthropic.

3:20

So this letter from Jensen Huang and the other signatories is basically all about open models and how important they are to innovation,

3:29

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.

3:40

Casey, I want to know what you made of this letter, but I first want to know why you think this is happening now.

3:45

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.

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You may remember that earlier this summer, Anthropic released Claude Fable and had to unrelease it after the Trump administration freaked out because of its cybersecurity capabilities.

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Then the release of GPT 5.6 sold by open AI was also delayed because the government had the same concerns.

4:19

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.

4:30

And the Trump administration said, give us until this coming Saturday and we are going to figure something out.

4:36

And in the meantime, Kevin, there were growing concerns that Chinese open source models were coming close to the capabilities of Fable and Soul.

4:46

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.

4:54

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 different companies are coming out in support of open models, even though some of them like open AI and Google also produce closed source models.

5:10

Sure. So, you know, maybe bracket out open AI and Google for a second for most of these companies open source is really good for that because open source lowers the cost of intelligence.

5:21

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.

5:32

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.

5:40

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.

5:53

So they have a lot of reasons to not want the Trump administration to restrict these open models.

5:58

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.

6:06

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.

6:18

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. Yes.

6:30

Classic Silicon Valley example that I love is when Google released Google Doc slides sheets. They did that for free to put pressure on Microsoft because Google and Microsoft compete in various ways.

6:43

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 and other areas. So that's a classic commoditize your compliments scenario.

6:56

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 open AI and anthropic.

7:10

And they don't want to have to end up in a future where 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.

7:27

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

7:35

Yes, they're not giving away that thing for free. Yeah, I mean, let me say because I have been cynical. I think there is at least one good principle 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.

7:54

And if they continue to improve as we assume they will, they're probably just going to spread all over the world. And like the 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?

8:08

Like that could be a mechanism for China to extend its power. And so I think there are some really sincere folks here who believe, look, it is important for there to be open source models in general, but also like American open source models that can, you know, compete geopolitically.

8:23

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.

8:32

Like I think these are actually two separate conversations about open models and then about Chinese AI sort of progress and threats.

8:41

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.

8:52

I do think it's notable that open AI and Google, which both signed this letter, like they have made open source models in the past, I think it's fair to say like they're not giving that their highest effort right now, right?

9:08

The open models that they've put out that the pace seems to have slowed the quality does not seem to be rapidly accelerating.

9:15

And the answer is because they do not want to cannibalize their own business, right? Like they have some sort of research, like, you know, public mission interest in putting these models out there, but the end of the day, you know, that it's not buttering their bread, Kevin.

9:28

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.

9:39

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 not that capable. And then they open source that.

9:55

Yeah. 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.

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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.

10:18

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 or do any names come to mind.

10:31

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 close source software products.

10:41

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 utilateral control of everything that company ever does.

10:54

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.

11:06

Yes, plus one to all of that, it is true that meta mostly has champion open source models and has this llama family of models that it made available open weights.

11:16

But it is very funny to me that Zuckerberg put these statements out like after meta pivoted to releasing new close source AI models called mu spark.

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So yeah, their tune has changed on this a bunch.

11:29

But if there's one thing I'm certain of here, it is that if meta made a frontier model, it would have a completely different story about all of this.

11:37

Yes, in general advocating for open weights models is what you do after you fall behind in the iris.

11:45

And so I think that's what we see here.

11:49

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.

11:58

I imagine there's a lot of behind the scenes lobbying and influence going on in Washington as well.

12:05

There were some reports that Jensen Huang is also meeting with some top officials in the Trump administration, including Howard Lutnik, the commerce secretary to sort of advocate for their position.

12:16

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?

12:37

It seems like that would likely cause some harm. So they want to place some restrictions on these frontier American models.

12:43

So what do you do about the open source models right now? We believe there may be 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.

13:00

And so what do we do that? Do we say, well, you the American company cannot release or sell this model, but any other American company can use the Chinese equivalent.

13:10

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.

13:16

I mean, either, 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.

13:36

I think that just becomes a very thorny challenge.

13:39

I think this is a good moment to talk about the actual frontier model cyber attack that is captivated the world's attention over the past week. We talked about it on last week show the unwitting autonomous cyber attack by open AI against the company hugging face where basically this model had been given a task to try to hit a benchmark.

13:59

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.

14:09

And then I think we should briefly mention yeah, let's talk about it. What happened? Okay, so a few things one open AI updated its blog post and said that this rogue agent use credentials.

14:19

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.

14:31

Another one of the companies that was apparently affected was called modal labs. This is a classic case of if you found one cockroach in your house.

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You do not have a one cockroach problem. That's right. That's right. There's going to be a few more floorboards.

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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.

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So this was not as simple as like password stolen log in goodbye. This was a very serious effort that unfolded over a long time.

15:09

And then finally and perhaps most interestingly, Reuters reported that at open AI, 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.

15:23

That's beautiful to me. That's solidarity among thieves.

15:28

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

15:37

And I bet it does. But I mean, this is crazy. 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.

15:47

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.

15:55

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 open AI is running.

16:06

For this model. And I just want to say to those people, no, it's not you're completely wrong. This is really happening. Yeah, wake up people. Yeah. Also what a terrible marketing campaign. Yeah, right.

16:18

We committed a crime. We committed maybe several crimes. Yeah. Would you like to buy our crime committing product for your company? We can't wait to sell it to you.

16:28

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.

16:38

This is not going to be the last time a model escapes its sandbox and breaks into another company. 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 super human.

16:57

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.

17:05

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.

17:16

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 deep seek and all these Chinese companies.

17:26

They they do appear to be helping attackers and defenders. They do appear to be conferring some benefits. They're not super obviously dangerous.

17:36

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 picture of open source may change then.

17:46

I completely agree. 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.

17:55

And I weren't a journalist. I would sign that letter. Right. Like is that seems true to me. But I think too often in the world of tech, we don't think three or four steps ahead.

18:03

But you know, hit on the hard for a program. That's a, you know, one of our core values. Well, speaking of thinking ahead, let's talk about the other big open letter that came out recently, which is called pacing the frontier.

18:16

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 is been signed by a very esteemed list of AI insiders including

18:31

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. It's like they're Willie Nelson sign it.

18:45

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

18:49

Sure. 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 paste the frontier of automated AI development.

19:13

And so, 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.

19:32

And so, we're going to 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 if there was sort of a button that we could all push together, they would just slow everyone down at the same pace.

19:47

That would be a good thing for the government to create. 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 we're going to be able to do this.

20:01

And so, we're going to be able to do this 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.

20:19

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 get out that dry erase marker and get to work.

20:30

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.

20:36

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.

20:45

But I do think it's a major statement 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.

20:57

Yeah. And this would be extremely difficult to do when I have read up on approaches to it.

21:04

The analogy that gets used the most often is nuclear monitoring, which might require building special kinds of hardware, like chips that phone to home, like back to some monitor, so that you knew where they were, or chips that refuse certain kinds of workload.

21:20

So we truly do not have the technology at this point to do any of this. We could build it, but doing so is going to require some time and time is beginning to run short.

21:31

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 this is the sort of missing piece here is like all of the US and the Western AI labs could agree to hold hands and just slow down.

21:49

For a while, but if China is still accelerating, it seems like there's not going to be much net impact on the safety of the world at large.

21:59

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're going to, you know, keep at this.

22:14

This is our approach. We think it is good for the world. And what I took from those remarks is this man, I don't even like using this term, but unfortunately this is the best one I have here. This man is not age, I pilt.

22:24

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 was using models that are three to seven months behind the frontier, right?

22:36

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.

22:49

And the same thing is going to happen to him that happened to the Trump administration, which you may recall was also all gas and outbreaks until very recently when they saw a few things and they said, we're going to need a different approach here.

22:59

So the same thing is going to happen to China. It is only a matter of time.

23:03

Well, I did see that after this open letter was signed by so many researchers, Daniel Cokatello, former hard-fork guest, author of AI 2027, updated his probability estimates of doom,

23:18

attached his scenarios where he gives slightly higher weight to better outcomes and slightly lower the likelihood of a race to ASI has declined by 10% in his estimation.

23:33

Okay. So good news.

23:36

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

23:40

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 save it in this moment.

23:48

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.

24:06

Like a lot of people are having the realization that progress is continuing that the models keep getting more capable.

24:14

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.

24:25

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.

24:35

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 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.

24:59

Yeah, but I just can't help but worry that the labs are muddling their own message because well, it's true that they are saying some of these things publicly and they are signing these open letters.

25:09

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 to the labs.

25:16

And that I imagine that if 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.

25:24

We can't just completely opt out 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.

25:43

Well, they're going public right? So it's like the the sort of rhetoric about a slow down 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 IPO.

26:00

It just really makes me glad that the Manhattan Project was conducted by the government and not a for-profit enterprise.

26:06

I think there was some wisdom in having public servants work on the hardest problems of our time.

26:11

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

26:18

I think we're all very lucky that he didn't.

26:23

When we come back, don't be evil. I say it to Kevin before every recording and it's also the title of Claire Stapleton's new book.

26:30

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

26:36

The thing about AI for business, it may not automatically fit the way your business works.

26:58

At IBM, we've seen this firsthand. But by embedding AI across HR, IT and procurement processes, we've reduced cost by millions, slash repetitive tasks and free thousands of hours for strategic work.

27:12

Now we're helping companies get smarter by putting AI where it actually pays off. Deep in the work that moves the business. Let's create smart to business, IBM.

27:22

If AI can deliver so much value, my organization's struggling to scale it because the gap between hype and ROI is wider than most would expect.

27:31

Adopting the latest technology is only the beginning. True transformation requires accessible data, scalable infrastructure, strong governance and a clear path forward.

27:40

With insight AI, you can tap into insights 35 plus years of expertise across cloud, data, AI and cybersecurity to drive real results.

27:49

That's how you go from hype to how. Learn more at insight.com slash hard fork.

27:54

Hear that? That's now crispy. I'm at crispy strips meeting creamy Caesar sauce. Sounds extra crispy.

28:04

Caesar sauce at McDonald's for limited time. Bottom up, buh buh.

28:10

Kevin, have you ever wanted to walk out on your job? No, I'm a good worker. 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.

28:22

Someone who did, however, have the courage to do it is Claire Stapleton. Yes, our guest today is Claire Stapleton, a former Google employee who is just about to publish a memoir about her time at the company.

28:35

The book is called Don't Be Evil. It's about her experience at Google where she worked from 2007 through 2019.

28:43

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.

28:55

And she is back with this book, which is a very spicy memoir. 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.

29:18

And I think left her with a lot of questions about what is possible within a company like this. 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.

29:30

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.

29:45

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 fair today as opposed to when she was organizing this walkout a few years ago.

29:57

Yeah, well, let's bring red.

30:05

Claire Stapleton, welcome to Hartford.

30:07

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

30:09

Claire, you joined Google in 2007 to work on communications and your job was to make the companies executives and internal emails sound Googley.

30:19

And I thought for our younger listeners who may have missed that sort of Googley era, what was considered Googley back in the day? And how much did you believe it when you were doing that writing?

30:30

Yeah, I wasn't questioning much. I think coming out of college, like most young people in America, Google seemed like this amazing place to work. It was on the cover of magazines. There's a lot of sort of breathless press of these sort of futuristic campuses or flush with perks.

30:48

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.

31:01

I don't think anyone would have said that. It wasn't like my manager would 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.

31:12

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 being at a company like that.

31:22

And so it was a very kind of funny place to land as a young person.

31:27

Yeah. Over the next decade, you write in the book about becoming gradually disillusioned with the company's culture.

31:34

You experience executive misconduct. You see this boys club atmosphere. This tendency at YouTube to ignore or talk past various crises on the platform.

31:46

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?

31:56

I mean, I think that that tension existed back in 2004 to 2007, 2010, you know, that early period that, you know, in which Google seemed, you know, the optimism felt like it was it could really live up to something that Google could be this different kind of company.

32:13

And now we sort of laugh and roll our eyes, you know, at that because of course, you know tech companies ended up becoming the very kind of powerful institutions that they were skeptical of to begin with.

32:24

They ended up consolidating so much money and power that, you know, the contradictions absolutely exploded.

32:29

And so, you know, I along with so many other people was just sort of struggling with the loss of that identity because we would start it at a place that promised you could do some real good with your life.

32:39

Even if you're like a junior communication staffer, you're part of the sort of world historical thing.

32:44

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.

32:57

And around the time you were working at YouTube Claire, I was doing a lot of reporting on YouTube.

33:02

I wrote many stories and did many podcasts about the problems on that platform at the time.

33:08

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.

33:14

It's not that they didn't know there was bad stuff happening on YouTube, but like they didn't see it.

33:19

It wasn't surface to them all the time. And to them, like YouTube seemed like this vehicle for progressive social change.

33:25

But describe how that felt from the inside.

33:28

Yeah, I mean, I think it's so deep in the bones 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.

33:40

And that again, another tension that was exploding, as the creator community became really problematic.

33:47

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 on a team that was essentially brand management 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.

34:10

And so, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have

34:40

people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have people like, I think it's a really good thing to have

35:10

on YouTube, basically because we'd had so many examples

35:13

of things where we had tweeted something out

35:16

that ended up sounding like a reference

35:18

to something really perverse.

35:19

Like, you know, someone's doing some crazy thing

35:21

with knife play and it's a big controversy that day,

35:23

but we missed it and then we're posting

35:25

like someone carving Halloween pumpkins with a knife

35:28

and it sounds like we're kind of, you know,

35:30

being tongue in cheek about this like really dark thing.

35:33

So we had to have this briefing to be able to steer clear

35:37

of the kind of most disgusting things on the platform,

35:39

but when you're really sitting with that for 30 minutes

35:41

at the beginning of every single day, you're like,

35:43

wait, are we the bad guys here?

35:45

This tool starts to feel way less neutral.

35:47

I think there's a really important lesson there,

35:49

particularly for our younger listeners,

35:51

which is if you're in a job where your manager

35:52

brings you a puppy at any point to sort of help you cope

35:56

with the job, you're in danger girl.

35:58

You are in danger.

36:00

You're the bad guy.

36:01

Let's talk about the walk out.

36:04

So in 2018, the New York Times reports

36:06

that former Android boss Andy Rubin had been paid

36:09

a $90 million severance package,

36:12

despite being asked to resign due to sexual misconduct

36:15

allegations as well as other executives

36:17

that had similar allegations toward them

36:19

who also received severance packages.

36:22

In the end, 20,000 Googlers walk out on their jobs

36:24

to protest.

36:25

Claire, tell us about your role in organizing the walk out

36:29

and how it came together.

36:31

Yeah, so you know, the Andy Rubin story, which was,

36:35

it was just, it was the, you know,

36:37

the match that lit the flame.

36:39

I mean, in the fire, it was right on the heels

36:41

of a huge controversy internally to Google,

36:43

which was the Demor memo,

36:45

in which kind of, you know, mid-level engineer at Google

36:50

had sent around a memo basically decrying the company's

36:55

diversity programs on the, using kind of a bunch

36:58

of different social science to say,

37:00

women really are not as well suited to being engineers.

37:02

They're way too empathetic.

37:04

They're way too relationally oriented.

37:06

This is such a logical, you know,

37:07

sort of practical job.

37:08

And it's just a huge waste of money.

37:10

Meanwhile, you know, Google's like, you know,

37:12

alienating conservatives.

37:13

You went, you know, went on in a few different things.

37:15

So the Rubin story came out.

37:17

And I was following this.

37:19

It was a mom's email group called Expecting in New Moms.

37:22

And it was a very, very active group.

37:24

A lot of female engineers just talking about parenting

37:26

or whatever related to mom life at the workplace.

37:31

The Rubin news hit that email group incredibly hard.

37:35

I think that women started,

37:38

so they started to share stories.

37:39

I was just following it.

37:41

And I was fascinated by it because you sort of had heard,

37:43

you know, hear a lot about the startup culture

37:45

and Brotopia and the kind of founding of Silicon Valley

37:48

as being sort of inherently sexist.

37:49

But I was genuinely surprised at the force and weight

37:53

of a lot of these stories where women had felt

37:57

that they had suffered, you know,

37:59

all sorts of different kind of microcrustions

38:02

and accretions, a lot of people struggling

38:04

with coming back from maternity leave.

38:05

And it was a bit like, you know,

38:07

what happened to the so-called like company of the future,

38:09

you know, progressive workplace where people feel like

38:12

they're all their projects are given away

38:13

after they're, you know, coming back from maternity leave

38:15

and that sort of thing.

38:16

So I was not at all involved in what was

38:19

an already brewing, simmering organizing community at Google,

38:23

which had formed around Maven and Dragonfly.

38:26

There's too much more kind of technology-focused issues

38:29

where people were organizing to stop Google

38:32

from in the case of Maven, a government contract

38:35

in which Google technology be used for, you know,

38:38

as weapons of war.

38:39

And I, so, but anyway, so I basically was reading these,

38:43

you know, all these women's stories and thinking like,

38:46

you know, I used to sit at the side of the stage

38:48

for TGIF every single week.

38:50

And I said, that's the weekly all hands at Google

38:53

where you would get to ask questions of the executives.

38:56

TGIF was this sort of hallmark of the culture

38:58

because it was sort of inviting tough questions and dissent.

39:02

And it was an incredibly effective vehicle

39:06

for normative control, basically,

39:08

or organizational control,

39:09

because you could kind of absorb the dissent.

39:12

And there's so much admiration and love

39:15

and, you know, generosity in workers' view of Larry and Sergey

39:18

and the other executives that, you know, nothing,

39:21

nothing really survived.

39:22

None of these controversies would really survive

39:24

past, you know, maybe one or two TGIFs.

39:26

But I just felt like, you know, okay, sure,

39:29

could bring it all to TGIF and, you know, see what happens.

39:31

And the TGIF that very day,

39:33

I think the story broke on a Thursday

39:35

and they were running TGIFs on Thursday in that time.

39:37

No, TGIF no longer exists.

39:39

But the executives gave a bunch of these really sort of flat

39:44

bland statements, not really taking accountability,

39:48

kind of talking around the Rubin stuff,

39:50

saying a lot of, you know, we really empathize with the hurt,

39:53

you know, this sort of like corporate language,

39:55

which, you know, in any other moment in my own trajectory

39:59

as a corporate comms person, you know, kind of would say,

40:02

this is the sort of thing you have to say.

40:03

But at that point, it just felt like, you know,

40:06

this is this rupture moment, you know, in America,

40:09

you know, in this company where we're talking about systemic

40:12

change to use another buzzword of that time.

40:14

And it's not gonna cut it to sort of just like deliver

40:16

the same talking points.

40:18

So, you know, that very night in the next day,

40:22

the women on the mom's group kept sort of percolating,

40:24

you know, ideas and thoughts about like how to escalate

40:27

from there.

40:28

And in my kind of naive, Tay about, you know,

40:30

the history of labor organizing and all those other things

40:32

where you're supposed to kind of move slowly

40:34

and you know, build solidarity.

40:35

I was like, let's do a walk out, you know.

40:37

Um, it's like, okay, I love that.

40:41

And the women were like, yeah, I mean, it was truly,

40:43

you know, it, for better or for worse,

40:45

it was good girls revolt because, you know,

40:47

it's like all these sort of like high achieving women

40:50

coming together around this shared purpose, Matt as hell.

40:54

And, you know, very well organized protest.

40:58

And then ultimately, fascinatingly enough

41:01

from the corporate comms perspective,

41:03

the executives got right on board.

41:05

And they were like, we're walking out too.

41:07

I remember that that was fascinating.

41:09

It was like, you had very high ranking Google executives

41:12

who you would expect to be sort of shocked and offended

41:14

by this walk out instead sort of turning it into like a,

41:17

a kind of executive sponsored event.

41:19

Yeah, so I've been trying to get your thoughts

41:21

about this Claire because like among the people

41:23

who walk out is Ruth Porot, who was then

41:26

the chief financial officer of the company

41:27

and presumably had approved all those severance packages.

41:30

So why do you think that executives responded

41:34

in the way that they did to the walk out?

41:36

Yeah, you know, Ruth had a lot of really interesting

41:38

statements around that time, which I think showed

41:40

what they were trying to do.

41:41

And then they of course quickly pivoted, you know,

41:43

to more like chilling effects after that.

41:45

But I think that they felt like they could contain

41:48

a walk out in a very similar way to the way that, you know,

41:51

TGIF existed, which is that, okay, the women

41:54

of the company are really mad.

41:55

Let's all blow off steam.

41:57

And we're gonna kind of transfer the energy of that

42:00

into something that feels non-threatening

42:02

by having the CEO send an email around saying,

42:05

we welcome people doing this.

42:07

But what she said at the time was, you know,

42:10

she went to a conference I think the next week.

42:12

And she said, this is, you know,

42:13

we have Googlers doing what Googlers do well,

42:15

which is, you know, kind of thinking big about problems.

42:18

And if we can solve self-driving cars,

42:20

like, why can't we solve this, you know,

42:22

kind of referring to sexual harassment, I guess,

42:24

which is like, okay, great.

42:25

Like, let us know.

42:26

Why can't we solve sexual harassment, then, you know,

42:28

it's like plenty of opportunity there

42:30

with your own power, institutional power.

42:34

But I think that you could do is you could not

42:38

pay $90 million to people who are incredibly

42:40

accused of sexual harassment.

42:42

And maybe in some small way, that would strike

42:44

a blow against sexual harassment.

42:46

Right.

42:47

I'm just going to be calling you over here, Kevin.

42:49

I mean, at one point, they were trying to invite

42:52

the walkout organizers into having a meeting with,

42:54

there was some sort of power center, you know,

42:56

Susan and Ruth and Jennifer's Patrick and some other people.

42:59

And they were like, we really want to,

43:01

it was before the walkout and they were trying to get,

43:04

they said they wanted, the stated purpose was that

43:06

they wanted to get the organizers feedback on, you know,

43:10

how to avoid the situation.

43:11

And I'm like, avoid what situation?

43:13

Again, you're the people who are signing off

43:14

on these obscene pay packages

43:17

and you know, you know where the rot is.

43:19

We don't even know where all the rot is.

43:22

Our feedback is not what you need here.

43:24

And of course, people like Meredith Whitaker,

43:27

who kind of had much more of their eyes open

43:30

to how fundamentally,

43:32

existentially threatening this organizing was

43:36

and would continue to be in the minds of executives.

43:39

But she was like, of course,

43:40

what they're going to try to do is defang our leadership

43:43

because you have tremendous personal power

43:46

and also institutional power being someone like that

43:48

who sits at the top ranks of a company like Google.

43:51

And how could we not be drawn in?

43:54

You know, or something by that.

43:55

So anyway, we didn't do the meeting

43:56

and they certainly weren't interested

43:58

in hearing our feedback after that.

44:00

The relationship between tech workers and their employers

44:03

has dramatically changed in the years since the walkout.

44:06

I've heard Google executives and executives

44:09

as other tech companies sort of lament those years

44:12

where workers were walking out

44:14

and expressing solidarity as sort of the time

44:17

when the inmates were running the asylum.

44:19

You know, now there is sort of this sense

44:21

that you are lucky to have a job at one of these companies

44:24

and the company does not have to care what you think anymore

44:27

with one specific exception of like Frontier AI lab employees

44:30

who we can talk about in a bit.

44:32

But I'm curious like how that shift has felt for you

44:34

as someone who I think created one of the high watermarks

44:37

of worker empowerment in Silicon Valley.

44:40

Yeah, I mean, it could never have happened

44:42

without all the Google did to create psychological safety, right?

44:48

I mean, they had these kind of interesting, you know,

44:50

data science, organizational psychology PhDs

44:52

at the company studying, you know,

44:54

what makes teams thrive, what makes people sort of, you know,

44:57

give the most, you know, their kind of creativity

44:59

and entrepreneurial spirit and stick around, all those are things.

45:02

And a lot of that was about worker voice.

45:05

And, you know, feeling like you have a stake in the company,

45:07

feeling like you can express yourself feeling free from harm

45:10

or whatever, right?

45:11

I mean, Larry Page talked about this kind of stuff all the time.

45:13

It's like why we set the company up this way

45:15

is so it will be successful.

45:17

And that's kind of shocked me the most is that this sort of like,

45:20

oh, no, we actually don't care.

45:21

Your competing, your job is could easily go to AI.

45:23

We don't care about your things at all anymore.

45:25

Our company doesn't really need you.

45:27

And so you should be, you know, grateful, deferential,

45:31

you know, I think that they're the cost of that dissolutionment

45:36

is so much bigger than what the top executives

45:38

are willing to face because they'd rather have a well-managed

45:42

kind of obedient workforce, I think.

45:43

That's, that's, you know, all the layoffs

45:46

and all those other things where people of course

45:49

aren't as willing to, you know, step out of line

45:52

and, you know, speak up and challenge authority.

45:54

This week we saw an open letter from more than 1,000 employees

45:59

of the Frontier AI Labs asking the government

46:02

to help pace AI development,

46:04

including some of the leaders of these AI labs.

46:08

I'm very curious what you made of that

46:10

because to me that felt like, oh, maybe this is a kind of

46:14

resurgence of tech worker activism or people realizing,

46:19

oh, wait, we have leverage, we're very in demand.

46:22

We are going to use that leverage to try to push through

46:26

some policy agenda that we have.

46:28

Was that a heartening for you?

46:30

Did you feel like that was kind of a nothing burger?

46:33

Like, what did you make of that letter?

46:34

No, I think anytime when people are banding together

46:37

and like putting their name on something

46:39

and feeling really passionately about it, it's great.

46:42

And I'm constant, I'm waiting, waiting by the phones.

46:44

I think that, I truly think that like, tech activism

46:46

is going to swing back around again

46:49

because you have this sort of disaffected workforce.

46:52

You have very, very challenging public opinion about AI.

46:55

The kids walking out of the, of soon-dark

46:59

Pachai's Stanford commencement speech was huge.

47:03

I mean, I think the young people and their hatred

47:06

of, sort of intrinsic, not hatred, but mistrust of AI

47:10

and the sort of the kind of broader societal consciousness

47:13

raising that, you know, whatever big tech said

47:16

it was going to be, it's become this massive consolidation

47:19

of data, power, money, resources.

47:23

And we're back to like not trusting the corporations

47:26

are going to have anyone's best interest in mind.

47:28

And, you know, I think all those conditions are very fruitful.

47:31

You know, if people feel like they're willing to risk,

47:35

that's always the hardest part is, is there people

47:37

willing to risk their jobs because, you know,

47:40

however, you know, Google was going to respond,

47:42

however any company might say they're going to respond,

47:44

companies don't like work, they don't like sharing power,

47:47

they don't like, you know, people organizing

47:49

for power, subverting, you know, their authority,

47:52

no matter how, you know, Kumbaya and open collaborative

47:55

the culture might be stated on paper.

47:57

So I think it's, you know, there's some,

48:00

there's some definitely some ripe conditions for the resurgence

48:03

of tech worker activism, but certainly the,

48:05

the, all the, the promise of that particular moment

48:09

of the walk out, I mean, way faster than I could have ever imagined,

48:13

it, it shifted drained momentum slowed to a crawl.

48:18

I wanted to ask you in the aftermath of the walk out,

48:21

what hopes you might have had about it coalescing

48:25

into something more durable?

48:27

Like what goals did you all have

48:29

and what happened to them?

48:30

It was, you know, it was a little bit the,

48:33

the kind of hubris of Google, of Googlers,

48:35

I mean, even, you know, I'm thinking of really of myself

48:37

where it's like, oh, we can just reinvent labor organizing.

48:39

No, no, no, like the canonical book, no short cuts is right,

48:43

which is that it really does have,

48:44

even if you had this kind of crazy moment in time,

48:47

you have to move lunch table to lunch table.

48:50

It's a slog, it's dangerous.

48:53

I mean, you need to have op-sec and all these things that,

48:55

you know, I think that someone like me who had,

48:58

you know, kind of, you know, a total ignorance

49:01

of how these things actually work,

49:02

that was really helpful for the walk out,

49:04

because you just have me being like,

49:05

I'm happy to be the bull in the China shop

49:06

and like, Google's never gonna fire me.

49:08

So like, guns blazing, you know, I'm sending out the emails,

49:10

I'm making the Google group internal to Google.

49:13

I mean, because everything was about numbers, not, you know,

49:15

op-sec. So, yeah, I think that that was one of the,

49:19

the kind of surprising things was that Google was,

49:21

was completely turning the wheels on,

49:25

chilling the organizing.

49:26

And I think they did some really effective things to do that,

49:28

chiefly firing everybody, who was a rabble rower,

49:32

or marking them as sort of like, dissident person,

49:34

but it was also really challenging, you know,

49:37

and you know, there's a union effort at Google,

49:39

which I think is, you know, still going,

49:42

but it's hard, hard, slow work to get people

49:45

to sign their name for that.

49:47

You know, it requires a streak of person

49:49

that has a real stake in it.

49:50

And I think that, you know, a lot of people,

49:53

you know, in a big tech company say, you know,

49:56

sure, I wish better conditions for everyone here,

49:59

including myself, but am I willing to risk it?

50:01

We live in a very kind of idealistic kind of careerist culture.

50:05

So it's, it's really hard to, to, to build that,

50:08

the number base.

50:09

As you reflect back on your time at Google,

50:13

I wonder how much of the bad conduct and culture

50:16

that you experienced, do you think was unique to Google,

50:21

as opposed to it being just sort of like,

50:22

Silicon Valley culture, or even big company culture?

50:26

I think this is what big companies are like.

50:28

And they're, I remember talking to a woman who'd,

50:30

who'd been a real upset, the Apple cart type of lady

50:35

in Wall Street in the 1980s.

50:37

And she was like, you know, tech seems worse to me

50:39

because there's this pretense that it is different.

50:41

You know, it's like, I think that that's,

50:43

that was what I think intensified this effect at Google,

50:46

which of course is true of any other company

50:48

and any other tech company, which is that Google was so invested

50:51

in the narrative that it was something different

50:53

and they hired on the back of it.

50:54

And there was so much sort of lip service to it internally

50:57

that I think that the, the kind of,

50:58

the kind of loss of innocence and the loss of that identity

51:01

was very, very hard for Googlers.

51:03

Even though as I say in the book,

51:05

it was like a really important and necessary process

51:07

for me to, to say, yeah, let's just be honest

51:11

about what a corporation can do and, you know,

51:14

and how executives can act.

51:15

And they're like, you know, highly constrained,

51:18

you know, where all the incentives are, you know,

51:20

something very different than the flourishing

51:22

of the human spirit or whatever.

51:24

So I think, you know, Google represents a moment in time

51:27

where, you know, we all kind of believed that, you know,

51:29

corporations could be something different.

51:31

And ultimately, Google is just like the ultimate corporation, right?

51:34

So the idealism that you write about in your book

51:37

that once defined Google so strongly,

51:41

I feel like now really lives at two other companies,

51:44

which are OpenAI and Anthropic.

51:46

Like you talked to the people who work there

51:48

and they are incredibly idealistic about what they are doing.

51:51

They think that they are building technology

51:53

that is going to solve the world's hardest problems

51:56

that is going to cure cancer, you know,

51:57

extend human lifespan and all of the rest.

52:00

What lessons would you share with them?

52:04

Or what maybe warnings might you give them

52:07

as their companies sort of continue down this path?

52:10

What should they be on alert for?

52:12

And are there any illusions that you might dispel for them now?

52:17

I feel like such a cynic, because I saw someone who I think is really cool

52:20

on Twitter saying it was her first week at Anthropic.

52:24

And like, wow, I'm in the future.

52:26

Like, you know, every day I'm just my mind is blown

52:28

and I'm like, fell for it again, award.

52:30

No, I mean, I think it's really important to interrogate

52:36

what is that feeling doing?

52:39

What is that rhetoric doing?

52:41

To me, as an outsider, I don't doubt that there are elements

52:44

that are really exciting or it does feel

52:46

futuristic because there's all these open questions

52:49

about sort of where we're going.

52:51

And there's like, again, we're in a period of time

52:52

where there's lots of societal transformation

52:54

and there's kind of like this competitiveness.

52:57

And Google was really invested in that too,

52:59

with social media.

53:00

We're all, you know, we're fighting for civilization here,

53:03

but much less insane.

53:04

Like, the rhetoric was less insane actually then.

53:07

And then now, it's like, you know, the singularity and all this.

53:10

But, you know, I think it's really important

53:13

to try to develop an understanding of what that power is

53:19

and what it does, how it's being deployed

53:22

and how you are being, how that rhetoric is working on you.

53:25

Because it doesn't mean that, you know,

53:27

people shouldn't feel like they're solving big problems

53:29

together or that really smart people shouldn't be working

53:33

on these things that they should.

53:35

But, you know, I think that being able to compartmentalize

53:38

your work a little bit, question authority a little bit,

53:41

you know, these things are really, really healthy

53:43

because otherwise you risk, you know, the people who are having

53:46

to like process their Google experience in therapy for the cat

53:49

of me, therapy for 10 years afterwards.

53:51

Yeah.

53:52

Yeah.

53:53

Well, Claire, thanks so much for stopping by.

53:56

The book is out next week.

53:57

It is called Don't Be Evil.

53:59

And we're very glad to have talked to you

54:01

before the gag order comes down.

54:02

God, what a pleasure.

54:05

Thanks, guys.

54:06

Thanks, Claire.

54:08

Where we come back, a Smackdown and Substackdown.

54:13

People are mad about their new AI detector.

54:15

The thing about AI for business, it may not automatically fit

54:34

the way your business works.

54:36

At IBM, we've seen this firsthand.

54:40

But by embedding AI across HR, IT, and procurement processes,

54:45

we've reduced cost by millions, slash repetitive tasks,

54:48

and free thousands of hours for strategic work.

54:51

Now we're helping companies get smarter by putting

54:53

AI where it actually pays off, deep in the work that

54:56

moves the business.

54:58

Let's create smarter business, IBM.

55:01

If AI can deliver so much value, my organization's

55:04

struggling to scale it.

55:05

Because the gap between hype and ROI

55:07

is wider than most would expect.

55:09

Adopting the latest technology is only the beginning.

55:12

True transformation requires accessible data,

55:14

scalable infrastructure, strong governance,

55:17

and a clear path forward.

55:19

With Insight AI, you can tap into Insights 35 plus years

55:23

of expertise across cloud, data, AI, and cybersecurity

55:26

to drive real results.

55:27

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55:30

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55:33

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but it's a big part of your daily routine.

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55:57

Learn more at ittakesenergy.com.

56:03

Well, Casey, it's time to talk about Slop.

56:06

Yes, it has been a big week Kevin in the fight against Slop

56:11

on Wednesday, the AI detection company Pangram,

56:15

announced it had raised $9 million

56:17

and released its first AI image detecting model.

56:21

But I think where most people probably saw Pangram

56:24

in the news was a few days earlier

56:27

when Substack announced it was going to integrate

56:29

the company's technology into its platform

56:32

so that readers can now know when you're reading an essay,

56:35

how much of it was written by AI?

56:38

Yeah, this is fascinating to me

56:39

because I have seen over the past few months

56:42

the Substacks that I subscribe to

56:44

just kind of gradually start sounding more Slopish.

56:48

They're talking about how things are landing.

56:51

They're using a lot of load bearing points.

56:52

A lot of load bearing points.

56:54

It's not X, it's Y, like that kind of thing.

56:57

And so Substack has apparently noticed this too

57:00

and is now giving readers the option

57:02

to click a little button to just run an automatic AI detector

57:07

inside whatever post, whatever Substack newsletter

57:10

they are reading.

57:11

Yes, and it is a quite expansive feature.

57:15

It includes not just posts, but comments, replies,

57:19

notes, which is their little social networking feature

57:22

that they have anything on Substack that is longer

57:25

than 100 words, you can now run the scanner on

57:29

the flip side.

57:30

If you're a creator, they've added this new

57:32

how I make this box, which is essentially an amnesty feature

57:37

where if you're a Slopster, you can say,

57:39

hey, just so you know, I write this with Slop.

57:41

Or I guess, conversely, you could say,

57:44

I would never use AI to create what I'm creating.

57:48

Yeah, I thought this was really interesting.

57:50

The CEO of Substack Chris Best posted about this.

57:53

He called this Claude Fishing.

57:54

Basically people misleading their readers

57:57

about whether they're using AI or not,

57:59

how much they're using AI to write their newsletters.

58:02

Credit where it's due, I think that is a good

58:04

and catchy phrase.

58:05

It is.

58:06

And I think that will catch on.

58:07

And the reason I think it is a good phrase

58:09

is because it is obviously a play on catfishing

58:12

and catfishing is kind of a deception, right?

58:14

It's like, I'm sending you this picture of me,

58:16

but I don't really look like this.

58:18

And Claude is saying, like, I'm making it seem

58:20

as if I wrote this when in fact,

58:22

this is the output of an LLM.

58:24

Yeah, I'm curious to hear your thoughts on this

58:26

as a professional newsletter guy and Substack critic.

58:29

What you make of this, but I should say,

58:32

like, on the face of it, I have no problem with this.

58:34

I have not done one of these Substack disclaimers,

58:36

but in my book, I have a whole preface

58:39

that sort of talks about how I did

58:42

and did not use AI writing the book.

58:44

So I didn't use it to write the words,

58:46

but I did use it for research and all kinds of other stuff.

58:50

And I thought that was important

58:51

just to sort of disclose and be transparent with readers.

58:54

And maybe it makes people less or more interested

58:57

in reading the book.

58:58

I don't care what I was trying to avoid

59:00

is a situation where people are going through

59:02

and being suspicious, oh, did this page have any AI on it?

59:05

Did that page?

59:06

And so I think this is a good practice

59:08

for writers in this day and age

59:09

to just be transparent and straightforward with their audience.

59:12

Yeah, so I'm actually going to agree with you.

59:14

I think this is a good feature

59:16

because I too get annoyed when I am reading a Substack post

59:20

and I feel like I am just reading Slop

59:23

and I kind of want to leave a comment saying,

59:26

like, did you really write this,

59:28

but now I don't have to because I'll just be able to scan it.

59:31

But while we are enthusiastic about this feature

59:34

as Substack readers,

59:35

some Substack writers seem to be quite upset about it.

59:39

404 Media had an article this week

59:41

in which they quoted at least one Substack writer

59:44

calling this a witch hunt.

59:46

Wow.

59:46

Now, do you know how you can tell

59:48

if a witch was created with AI?

59:49

Hi, six fingers.

59:51

Now, you might wonder,

59:55

why are these writers so concerned about this feature?

59:59

Well, they're worried about false positives

1:00:01

and the reputational damage that they might endure

1:00:04

if they are falsely accused of clawed fishing.

1:00:07

Yeah, I am somewhat sympathetic to this critique

1:00:09

because we've talked on this show before

1:00:11

about how none of these AI detector tools

1:00:15

really work perfectly.

1:00:17

I think PanGram is from what I understand,

1:00:19

like sort of the best of the lot,

1:00:21

but still there are false positives,

1:00:22

some independent studies have found,

1:00:24

there's some number of false positives

1:00:26

where it's accusing people of using AI.

1:00:28

And so I am worried about the accuracy of these tools

1:00:32

and I think that there will be maybe a small number,

1:00:35

but some number of writers who are falsely accused

1:00:37

of using AI because of this feature.

1:00:39

Yeah, you know, this seems like the sort of thing

1:00:42

that I should be empathetic about,

1:00:44

but I just find that I'm not.

1:00:46

And I think ultimately for most Substackers,

1:00:48

it's just not actually going to be that big of a deal

1:00:51

to be falsely accused of having used AI, right?

1:00:54

These writers by their nature,

1:00:56

like these are independent writers,

1:00:57

like these are bloggers, these are not people

1:00:59

who are at risk of losing their jobs

1:01:01

because they used AI.

1:01:03

I think, you know, the worst case scenario here is

1:01:06

they have to write a Substack post where they're like,

1:01:07

hey, I know that this essay kept getting tagged as AI,

1:01:10

but it wasn't, you know?

1:01:12

I also think that savvy writers will find ways around this.

1:01:15

I've actually heard of people running sort of like

1:01:18

an anti-pangram loop where they tell an LLM,

1:01:24

like write this essay and then run it through pangram,

1:01:27

and if it keeps coming up as AI detected, write it again,

1:01:31

and keep doing that until it doesn't come up

1:01:33

as AI detected anymore.

1:01:34

So there's sort of a cat and mouse game going on here.

1:01:37

Whenever you do something that just takes way more time

1:01:40

than actually writing it yourself,

1:01:42

I get very delighted by that.

1:01:44

So that seems like a really smart tactic.

1:01:46

You know, other people though are saying,

1:01:49

in addition to the people who are worried about the witch

1:01:51

hunt, that there was a writer named Mac Collier,

1:01:54

who wrote quote, I'm not going to apologize for using AI

1:01:57

in the creation process.

1:01:58

I wrote for 20 years without AI.

1:02:00

I could do it again if I wanted to.

1:02:02

But basically he said, look, like the only thing

1:02:05

that AI is doing for me is making my writing better

1:02:08

and why would you not want it to do that?

1:02:09

And I think the answer to that is, hey, buddy,

1:02:12

go nuts with the AI, but at least for this moment,

1:02:15

we want to know and we want to see the scan.

1:02:18

Yeah.

1:02:19

I have mixed feelings about this because I feel similarly

1:02:22

to Mac in the sense that I feel a lot of pressure

1:02:25

not to use AI in my writing.

1:02:28

And I do not use AI in my writing to be clear,

1:02:30

to write the words on the page or the words in the column,

1:02:32

I do not use AI.

1:02:34

But I feel there is a lot of pressure, social,

1:02:37

and otherwise for writers not to use AI at all

1:02:39

during any part of their process.

1:02:41

And I actually feel like journalists and other writers

1:02:44

should use the best tools that are available to them.

1:02:46

And for some writers, like maybe people who are not,

1:02:50

for whom English is not a first language,

1:02:53

people who are just starting out,

1:02:54

like I think this could be excusable to use AI

1:02:56

as a more active part of your writing process.

1:02:59

But I do think writers have an obligation for now

1:03:02

to disclose this.

1:03:03

Yeah.

1:03:04

Well, I think one reason why this is all really interesting,

1:03:07

Kevin, is trying to understand why substack felt

1:03:10

like they needed to do this, right?

1:03:14

And I think the reason is that they must believe

1:03:18

that if substack becomes seen as primarily a destination

1:03:23

for Slop, it will lower the value of the network, right?

1:03:26

Like, substack makes its money when people go

1:03:29

and buy subscriptions.

1:03:30

And I think they have rightly intuited.

1:03:32

People do not want to pay subscriptions to Slop.

1:03:35

They want to pay subscriptions for human writing.

1:03:39

So I'm curious, do you think that is the right bet?

1:03:43

Yeah, I think this is a fair bet for them to make.

1:03:45

I think what people are paying for when they pay for a substack

1:03:47

is sort of like direct access to a person's brain.

1:03:50

And if what you are getting instead

1:03:53

is something that's mostly the output of an LLM,

1:03:56

I think people will feel like they're getting a raw deal,

1:03:58

like there's some deception going on.

1:04:00

And this is an area where I think the norms are going

1:04:05

to evolve because pretty soon,

1:04:08

like AI will be integrated in every word processor

1:04:12

and content management system.

1:04:13

And it will just be kind of unfathomable

1:04:16

to like do this the old way.

1:04:18

But for now, I think there are still enough periods

1:04:20

to want 0% AI generated text in their substack newsletters

1:04:24

that I think this is a good bet for them right now.

1:04:27

I think honestly, there are all sorts of reasons

1:04:29

why they might want to do this.

1:04:31

I mean, one thing about substack is that anyone can use it for free,

1:04:34

right? And like even if you have 100,000 free subscribers,

1:04:37

they will send an email to 100,000 people for free.

1:04:39

That's costing them a lot of money.

1:04:41

And so I can admit that they're probably like

1:04:43

staring down the barrel of a future

1:04:45

where like everyone in every profession is like,

1:04:48

I'm going to start a newsletter,

1:04:49

I'm going to have a chatbot write in a chatbot

1:04:51

respond to all of my comments.

1:04:53

And all of a sudden that's going to become

1:04:54

an enormous expense for them.

1:04:57

And so they need to find a way to discourage people

1:05:00

from doing that sort of thing.

1:05:01

Yeah.

1:05:02

I'll be very curious to see how many people

1:05:04

actually use the AI detection tool.

1:05:06

Because right now, like the way it's designed,

1:05:07

you have to go out and like select this tool.

1:05:09

It does not automatically like overlay a thing on the post

1:05:12

that says this was generated by AI.

1:05:15

And my sense is like, you know,

1:05:17

there are a lot of people out there

1:05:19

who probably don't care, frankly.

1:05:21

If they can't tell that something was generated by AI,

1:05:24

what they're reacting to is just

1:05:26

how good is this thing that I'm reading?

1:05:28

It's not like, you know, like we've seen all these

1:05:30

sloped threads go viral on X and other social networks,

1:05:33

LinkedIn now is just people posting AI stuff.

1:05:37

And my impression is not that it has made LinkedIn

1:05:39

a less popular platform.

1:05:41

It probably is just people are just judging it

1:05:43

based on the quality of what they're reading.

1:05:45

Well, it's not less popular,

1:05:47

but keep in mind, LinkedIn is free to use for the most part, right?

1:05:51

Like LinkedIn isn't making you pay to read those posts.

1:05:53

Thank God.

1:05:54

But Substack is.

1:05:56

And so I just think it's different.

1:05:57

I will say when this news was announced,

1:05:59

I heard a terrible scream come out of Sandhill Road

1:06:02

down in Silicon Valley as every venture capitalist

1:06:05

realized that they could no longer outsource

1:06:08

their incessant thought leadership posts

1:06:10

about the economy to claw at any more, Kevin.

1:06:13

Well, they've been employing human ghost writers

1:06:15

for years to write their tweets and blog posts.

1:06:16

And they should do it again.

1:06:18

So we need to keep those jobs afloat.

1:06:20

Now, another interesting dimension of this,

1:06:22

and of course, this was particularly delicious to me, Kevin,

1:06:24

is somebody who dramatically left Substack a few years back

1:06:28

because of the Nazis that were on the platform

1:06:31

that the company declined to remove.

1:06:33

In this one moment, Substack has told us

1:06:36

that on some level, they find AI-generated writing

1:06:40

more offensive than Nazi content.

1:06:42

Yes, I think that is one very ungenerous way

1:06:45

of interpreting this.

1:06:46

I think it is also like a threat to their business

1:06:48

in a way that maybe Nazi content is not.

1:06:50

Yeah.

1:06:51

And turns out, no one actually cares

1:06:53

if there's Nazis on your platform.

1:06:54

Well, just you.

1:06:55

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

1:06:58

That's right.

1:07:00

And that's it.

1:07:00

But a lot of people do care if their feeds are full of slop.

1:07:03

Here's what people don't realize here in 2026.

1:07:06

Nazis used to be very controversial.

1:07:08

I would even go so far as to say they were a sort of hated group.

1:07:12

But things have changed a lot.

1:07:14

And now what we hate is AI.

1:07:16

Yeah.

1:07:17

One more point that I would just make about all of this.

1:07:19

And I think this is instructive to everyone on Substack,

1:07:23

even if you support this change.

1:07:25

This was a really great reminder, I think,

1:07:27

and wake up call that Substack is a platform.

1:07:31

And Substack is going to do the things

1:07:32

that are best for Substack.

1:07:34

And so if you like this particular change, great.

1:07:36

But if you don't like it, well, guess what?

1:07:38

You're on a platform.

1:07:39

The terms can change on you at any time

1:07:41

and they may not be in your favor.

1:07:44

Yeah.

1:07:45

Have you checked any of the Substacks

1:07:46

that you subscribe to using this new AI detection feature?

1:07:49

You know what?

1:07:50

I haven't yet.

1:07:51

I'm waiting for the next time like a VC blog post

1:07:54

starts making the rounds to see if I can bust them.

1:07:57

Let's try it now.

1:07:58

Let's try it now.

1:07:59

Yeah, what should we check?

1:08:01

I went to a blog about AI agents on Substack,

1:08:04

which I just assumed was probably generated by AI

1:08:08

and they've disabled the AI detection.

1:08:11

So that's an important thing to point out.

1:08:13

As a writer, you can disable AI detection on your blog.

1:08:18

But at that point, you might as well just put a big red banner

1:08:21

at the top of your website that reads Slop.

1:08:23

Yeah.

1:08:24

Yeah.

1:08:25

Yeah.

1:08:26

In conclusion, I hope that landed well with you.

1:08:29

It landed clearly.

1:08:30

That was a load bearing segment.

1:08:32

Loading bearing insights here on the hard work show.

1:08:56

So there's a lot of noise about AI,

1:08:58

but times too tight for more promises.

1:09:00

So let's talk about results.

1:09:02

At IBM, we work with our employees

1:09:04

to integrate technology right into the systems they need.

1:09:07

Now, a global workforce of 300,000

1:09:10

can use AI to fill their HR questions,

1:09:12

resolving 94% of common questions.

1:09:15

Not noise.

1:09:16

Proof of how we can help companies get smarter

1:09:19

by putting AI where it actually is.

1:09:21

And that's what I'm going to do.

1:09:23

Companies get smarter by putting AI where it actually pays off.

1:09:27

Deep in the work that moves the business.

1:09:29

Let's create smart to business, IBM.

1:09:32

If AI can deliver so much value,

1:09:34

my organization's struggling to scale it.

1:09:36

Because the gap between hype and ROI

1:09:38

is wider than most would expect.

1:09:40

Adopting the latest technology is only the beginning.

1:09:43

True transformation requires accessible data,

1:09:45

scalable infrastructure, strong governance,

1:09:48

and a clear path forward.

1:09:50

With insight AI, you can tap into insights

1:09:52

35 plus years of expertise across cloud, data, AI,

1:09:56

and cyber security to drive real results.

1:09:58

That's how you go from hype to how.

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Learn more at insight.com slash hard fork.

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