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Casey Newton
Founder & Editor; Co-host, Machine Gods; former Hard Fork co-host, Platformer

What Meta's $17 Billion Settlement Means for TikTok and YouTube

📅 Aug 28, 2026 Hard Fork 59 MIN 28447 VIEWS 150 SEGMENTS · 3 SPEAKERS
Meta reached a landmark settlement this week, agreeing to pay up to $17.1 billion and make major changes to Facebook and Instagram over claims it endangered children with addictive social media platforms. We discuss why Meta capitulated and what it means for the entire social media industry. Then, Princeton computer science professor Arvind Narayanan returns to offer his thoughts on why banning data centers won’t slow down A.I. progress. And finally, it’s all hats on deck for the final HatGPT. Guest: Arvind Narayanan, professor of computer science at Princeton, and co-author of the “A.I. as N...

What Casey Newton said

Written from the verified transcript and checked against it. Every figure links to the moment it was said.

Casey Newton discussed Meta's $17.1 billion multi-state settlement over child safety and addictive features, calling it the largest in Meta's history. He said the AGs had Meta 'dead to rights' on collecting data from under-13s and that Meta's addictive design was a key issue. Newton criticized Meta's full-page ad calling on TikTok and YouTube to adopt similar standards, calling it cynical. He detailed product changes: a default two-hour daily limit, a midnight-to-6 a.m. block, muted notifications from 8 a.m. to 3 p.m., hidden like counts, and disabled extreme makeup filters. He predicted TikTok and YouTube would likely adopt the standards to avoid their own settlements. Newton compared the changes to cigarette regulation, saying they'd make social media 'a little less fun' and reduce teen use. He noted Meta feared a potential $1 trillion fallout and is pivoting to AI, predicting 60% team cuts would be attempted again next year. He praised the settlement as 'democracy working.'

Key takeaways

  1. Meta's $17.1 billion settlement is the largest in its history, covering 47 states plus DC and territories.
  2. Meta will pay about $12 billion initially, with the total rising to $17 billion if TikTok and YouTube also settle.
  3. New defaults include a two-hour daily limit, a midnight-to-6 a.m. block, and muted notifications from 8 a.m. to 3 p.m.
  4. Newton predicts TikTok and YouTube will adopt Meta's standards to avoid their own $17 billion settlements.
  5. Meta feared a potential $1 trillion fallout from the case, driving the settlement.

Numbers and commitments

FigureWhat it refers toTypeAt
$17.1 billion Maximum settlement amount Meta agreed to pay commitment 0:19
$12 billion Initial payment required from Meta commitment 2:47
$10 billion Meta's expected annual ad revenue from scams metric 2:47
midnight to 6:00 a.m. Default block on app use for teens commitment 6:11
8:00 a.m. to 3:00 p.m. Push notification mute window for teens commitment 6:11
10:00 p.m. to 7:00 a.m. Expanded night mode hours if TikTok and YouTube settle commitment 8:08
60% Planned team size cuts at Meta commitment 16:36

Chapters

  1. 0:00Meta's $17.1 billion settlement
  2. 6:11Product changes for teens
  3. 8:08TikTok and YouTube hostage situation
  4. 11:46Cigarette analogy and teen mental health
  5. 14:09Meta's fear of trillion-dollar fallout
  6. 16:36Meta's AI pivot and workforce cuts
  7. 19:58Data center moratoria and AI progress
  8. 37:53Collective bargaining by data center opposition
  9. 40:09Final Hat GPT segment
  10. 55:05AGI debate and OpenAI's 80% claim

Questions asked in this interview

12
  1. 4:10Like why do we have to do the responsible thing if these other guys don't have to as well?
  2. 6:11What is Meta being forced to do or implement?
  3. 12:36... saying is, like, that this is an important symbolic step and, you know, making the apps a little less addictive will mean that sort of teens have some distance to say, like, wait a minute, do I like what this is doing to me and my friends?
  4. 14:03What does this say about Meta as a company that they are making the settlement now and that they are going to make these changes?
  5. 34:08So when I hear things like the colloquially named AI psychosis among CEOs, right?
  6. 39:15Well, and, you know, the sort of traditional form of collective bargaining has been pretty effective here, right?
  7. 43:16Do you think it's the sort of thing where there's just like an app and it's kind of like paint by numbers, you know, and it's just like poke here, prod here, a snip there, and congratulations, your tear ducts work again?
  8. 45:59Do we know what was in the package?
  9. 49:13How many group chats do you have with people with green bubbles?
  10. 50:51And are you a meat proxy?
  11. 54:56I think why are we building the machines that run faster than Usain Bolt?
  12. 55:55So I'm basically saying, yeah, that sounds about right to me. What do you think?
Kevin Roose 0:00 ↗
Well, Casey, we got some big news just before we started recording today, which is that Meta has settled its big multi-state lawsuit with all of the attorneys general.
Casey Newton 0:12 ↗
Attorneys general. Attorneys general. I always mess that up.
Kevin Roose 0:19 ↗
They have agreed to pay up to $17.1 billion and make a series of changes to their platforms. This is a big deal.
Casey Newton 0:30 ↗
It is a really big deal. This is a case that I have been following since it was filed in 2023. Initially, you can go back and read the first thing I wrote about it, which is that I didn't think the case as filed looked all that compelling. But then, Kevin, an unredacted version of the suit came out and I thought, oh, this company is in trouble. And indeed, fast forward to today, and this is the largest settlement that Meta has ever agreed to. So, one of the biggest, probably, in the history of tech.
Kevin Roose 0:59 ↗
Yeah, I think so. So, let's talk about the actual suit because there have been so many of these kind of lawsuits going around that it can be hard to keep all of them straight. This is not the New Mexico case from back in March where Meta was ordered to pay a bunch of money over various child safety violations. This is sort of the big omnibus multi-state lawsuit and investigation. 47 states plus DC and US territories. The cases are related in that they're both about child safety. And while that New Mexico case was really important, the jury there only ordered Meta to pay 375 million for child safety violations, although the judge later did tack on an additional 567 million. But this one is just orders of magnitude larger. And there were really two major things at issue here, Kevin. One was just a straightforward violation of a law that is supposed to prohibit companies like Meta from collecting information about children younger than 13 without their parents' permission. We talk all the time on the show about how we have very few privacy protections in this country, but this is one we do have. You cannot collect data about a 12-year-old without getting their parents' permission. And so what Meta did for a long time was they said, 'Well, you can't join unless you're 13.' But the thing that was in that unredacted version of the lawsuit was just tons and tons of evidence that Meta absolutely knew that millions of kids under 13 were using the platform. They were not asking for their parents' permission. And so that's what I wrote in my column. I think the AGs have Meta dead to rights here. And I think it was a major reason that this case was settled.
And this one was settled. Like, I guess Adam Mosseri, the head of Instagram, had already testified. Mark Zuckerberg was expected to testify. But before that happened, the lawyers kind of got in there and struck the deal.
Casey Newton 2:47 ↗
That's right. And that leads into the second set of issues that were under consideration here, which were just all of the things that Meta does to get you to pick up your phone and look at Facebook and Instagram as many times a day as it humanly can, right? The addictive features. Yeah. So, you know, what do we mean by that? Well, the fact that they're sending push notifications at all hours of the day or night, that they're using ranking algorithms to try to show you the absolute most enticing material. The fact that they're not enforcing any real screen time limit. So, there was just a litany of things that the company was doing to try to get teens to look at it as much as possible. The AGs came in and they said, 'Hey, this is actually just addiction that you're trying to create here.' And Meta said, 'Well, I guess we're not going to fight that one anymore.' Yeah. So, the financial settlement here is significant. Around $12 billion is what Meta will be required to pay initially. And, you know, for Meta, that's real money. It's not like all of their money. They'll be fine. They can sort of amortize that over a multi-year period. They don't have to pay right away. Not only that, Kevin, but there was reporting from Jeff Horwitz in Reuters several months ago that Meta expected that it would make about $10 billion in ads related to scams this year. So, they will unfortunately have to give up all of their scam money to pay for this settlement.
Kevin Roose 4:10 ↗
Yeah, just move the scam budget over to the settlement budget and it basically nets out. But there's this additional wrinkle, which is that the settlement dollars will go up to roughly $17 billion if TikTok and YouTube also settle and agree to penalties and changes to their products. So what is going on here? So the basic logic is like, hey, don't make us unilaterally disarm in the war for teenagers' attention, right? Like why do we have to do the responsible thing if these other guys don't have to as well? So, what we're going to do, Kevin, is we're going to hold America's teenagers hostage. And we're going to say we're not actually going to give them the safest experience possible unless these other guys do, too. And they are, of course, presenting this as industry leadership in creating a new safety standard for teenagers.
Casey Newton 4:57 ↗
Yes. I love the way they're spinning this. Have you seen the full-page ad?
Kevin Roose 5:01 ↗
No. So Meta is, according to Mike Isaac, my colleague at the Times, Meta is preparing to release a full-page ad, an open letter in the country's major newspapers this week, calling for TikTok and YouTube to, quote, 'join us in supporting teens.' It says basically, you know, we all platforms should empower parents and support teens in these ways because we know that when teens are restricted on one app, they simply move to another. So basically, they are worried that if they have to sort of unilaterally disarm and implement these new features, which we'll talk about in a second, into their apps, teenagers will just go to TikTok and YouTube instead.
Casey Newton 5:44 ↗
Yeah. And I mean, look, like, is that narrowly true? Yes. But please do not wait until truly the last possible second to do the bare minimum, effectively at gunpoint from 47 attorneys general, and then say we're excited to announce our new leadership position in teen safety. Like the depth of cynicism in this approach is breathtaking to me, even as a person who's covered this company for a really long time.
Kevin Roose 6:11 ↗
Yes. So let's talk about the product changes that are being required as part of this settlement. What is Meta being forced to do or implement? So, it is a bunch of things and I will just hit some of the highlights. A big one is that there is now a default two-hour time limit that is cumulative across both Facebook and Instagram. So, your teen will be able to spend a mere two hours a day browsing the feed. There will also be a default block on its apps between midnight and 6:00 a.m. So, your teen will not be able to, like, post to their feed or look at stories during that time when presumably they should be asleep. And also, for the first time, Kevin, they will now mute push notifications between 8:00 a.m. and 3:00 p.m. because, of course, for the past decade plus, they have been continuously interrupting children at school to try to get them to look at Instagram. But they're not going to do that anymore.
Casey Newton 7:09 ↗
How am I supposed to chat with my nasty Nancy AI chatbot during high school chemistry class?
Kevin Roose 7:14 ↗
Here's the great news, Kevin. Direct messages have been exempted from this plan. Oh, good. So, you can continue to get push notifications about all your Instagram DMs while you're trying to learn calculus.
Casey Newton 7:25 ↗
A few more changes to mention. They will finally hide the like count on Instagram posts by default. So, there has been research here that seems to show that this may have some modest mental health benefit to teenagers. They're also going to disable some what they call extreme makeup filters. I would love to know how much makeup you have to be wearing for it to be considered... like the Juggalo filters or what? How much makeup are we talking? When a teenager puts on a Juggalo makeup filter, Kevin, it gives them a sort of illusion of beauty that they may not be able to realize in real life. And that you can't unsee that.
Kevin Roose 8:08 ↗
So those are the big ones. One other unbelievable change to mention, you know, I said before that it's holding America's teenagers hostage based on what TikTok and YouTube do here. So there's another provision which is that if TikTok and YouTube will agree to Meta's terms, that Meta will reduce the daily limit for Facebook and Instagram to one hour and to expand night mode hours to 10:00 p.m. to 7:00 a.m., which would be up from midnight to 6:00 a.m. So Meta is basically saying, like, look, it would be a real shame if something happened to the children of this country, but you have a way out. Simply agree to our terms and then we will expand these hours.
Casey Newton 8:54 ↗
It's a really interesting bit of, like, game theory. Now, like, if you're TikTok or YouTube and you're looking at this, I imagine that you are saying, well, obviously we're not going to, like, join you in your, like, you know, your court-mandated or settlement-mandated changes because unlike you, we are better for kids. I can imagine especially YouTube pushing back on that. They have always insisted, like, we are not social media. We are more like TV. We are, like, we are not doing the kinds of, like, addictive and predatory things that some of these other apps are doing. There are educational uses of YouTube. A lot of, you know, a lot of schools use YouTube in the classroom. Like clearly this is a different thing than, like, Instagram or Facebook. I imagine that TikTok will have their own view on why they are different than either of these platforms too. Like, what do you think those other platforms, Meta's main competitors, will or should do in response to this sort of weird hostage situation? I actually assume that they probably will adopt these standards because we now know that if they don't, they might have to go sign their own $17 billion settlement. So I suspect that Meta believes that these things are actually coming and this will now be a talking point so that if and when TikTok and YouTube do commit to these things, Meta will go out and say we led the industry in calling for new standards and we got our peers to adopt these standards which we set. So that is sort of the next wave of cynicism that I'm expecting here, and we did it totally voluntarily with no court requiring us and no threat of, you know, many billions of dollars in penalties if we didn't. You know, I was going back to read my first column about this when the case was originally filed, and Meta had a comment that said something to the effect of, you know, we're disappointed that the state AGs didn't work with us on something more constructive and instead pursued this series of changes. I'm looking at this, I'm like, this seems pretty constructive to me. It seems like we got a lot further than we did just waiting for Meta to adopt some new standards.
Kevin Roose 10:45 ↗
I think that the product changes are a lot bigger deal than the financial piece of the settlement here. It is really like these are not sort of cosmetic tweaks around the edges. It will require, like, it will make for a much different experience for a teenage user of Instagram or Facebook. But even, you know, even that said, and I do agree with you, Kevin, I think it's important to remember that more and more democracies around the world are just banning these apps for teenagers, period. And so that is the real alternative that Meta is staring down the barrel of here, and it is willing to go, you know, pretty far by its limited standards to try to avoid the fate that it is now facing around the world. Yeah. And so do you think this actually is going to change the sort of mental health picture for teens? Like, if you had to guess, are these the kinds of changes that actually do make social media healthier for kids? Or is this just kind of a company doing the bare minimum it is required to do to at least stay out of bigger trouble?
Casey Newton 11:46 ↗
Well, at the risk of overusing an analogy, Kevin, I do think that cigarettes are relevant here in the sense that the way that we gradually got people to stop smoking was by just making it a little harder and a little worse experience over a long period of time, right? The price of those cigarettes kept going up. The number of places that you could smoke kept going down. And the amount of information about the negative health benefits just kind of continued to permeate the environment. And eventually most people said, you know what, I don't think this is for me. I think we are going to see a similar thing here where it's just going to get a little bit harder all the time for kids to use social media. They're going to continue to hear about all of the terrible outcomes that, you know, lots of teens are having on these apps, and over time they're just going to sort of move into safer and different spaces.
Kevin Roose 12:36 ↗
Yeah. They'll start vaping instead or whatever the social media... they'll be over on Kelsey turning their allowance money into less allowance money. I realize that sounds very cynical, but I do feel like there is some parallel here with the cigarette industry because they had this massive multi-state settlement back in 1998, and out of that came this sort of regime of, like, you have to put, you know, you can't advertise cigarettes in certain places. And I think what really moved the needle on smoking was not any of those things. It was like, as you said, it was sort of this cultural milieu and the, like, the fact that there just weren't smoking sections in restaurants anymore and, like, the sort of vibe shift of smoking in culture. And so I wonder if what you're saying is, like, that this is an important symbolic step and, you know, making the apps a little less addictive will mean that sort of teens have some distance to say, like, wait a minute, do I like what this is doing to me and my friends? But that it might actually be some of these cultural factors that end up making more of a difference when it comes to use of social media.
Casey Newton 13:39 ↗
That's what I think. And look, I mean, there are limits here. You know, I think that people are going to continue to watch a lot of short-form video. You know, I don't yet see an off-ramp from that particular phenomenon. But some of the, you know, other mechanisms here I do think will just make social media a little bit less fun to use. And, you know, maybe that will actually result in teens using it less.
Kevin Roose 14:03 ↗
Yeah. What does this say about Meta as a company that they are making the settlement now and that they are going to make these changes?
Casey Newton 14:09 ↗
I think they realized that the state AGs had them dead to rights on some of this stuff. This was an interesting case in that it was going to be decided by one person, which is this judge, Yvonne Gonzalez Rogers, and she has a reputation for being really tough. And I think they listened to the first few days of testimony. They were looking at all of the lawsuits that they had already lost recently on similar subjects, and they estimated that the fallout from this could be over a trillion dollars, like getting close to their total market capitalization as a company. So this case truly was too dangerous for Meta to pursue all the way to the end.
Kevin Roose 14:46 ↗
Yeah. I mean, I'm also curious if you think this will have sort of knock-on effects for them as a company. I'm thinking about, like, the Microsoft antitrust investigations of several decades ago. And one of the sort of conventional, you know, narratives that came out of that was that all of the antitrust investigations in the Justice Department and the trial and, like, all of this had an effect on Microsoft. Not because, you know, the breakup was reversed on appeal, but it was, like, so distracting and it took away so many executives' attention at a time when things were shifting under their feet and everything just became very cautious and there were lawyers in every meeting and, like, they missed the, you know, the platform shift to mobile. They missed this, they missed search because they were just so tied up in all of this expensive and distracting litigation. So, I'm curious if you think there's any parallel to Meta here and just the amount of time and energy that this company is now having to spend defending itself in these lawsuits.
Casey Newton 15:46 ↗
It's a good question. That is a story that the people at Meta know very well, and this has always been a very paranoid company. They have always assumed and have lectured their employees about how likely it is that they will get outcompeted in the marketplace. And so truly they think about this constantly, and I think you have seen them react by shifting all of the resources that they did to AI. Look at how this company talks about itself. They do not talk about a bright, bold future for Facebook and Instagram and connecting the world, right? I mean, you know, they'll make noises about creators here and there where it's useful. But when you look at what this company says it's doing, it's building superintelligence. It's releasing a Mac app that, like, plugs into your calendar to do work for you. Like, this company's public posture is that it is running away from its own products to build something completely different. That tells you a lot about what it thinks about the stuff it's already built.
Kevin Roose 16:36 ↗
Yeah. I wanted to bring up this other Meta story that came out today, which I thought was fascinating on a very different topic. Katie Paul, the great reporter over at Reuters, has a story about Meta's attempts to overhaul its workforce. Basically, Mark Zuckerberg and his lieutenants have been plotting for months now to sort of tear up the org chart at Meta and replace these sort of, like, big overstaffed teams with these small nimble AI-native pods, which could involve slashing the size of many teams across the company by as much as 60%. She reports that also this did not happen in the way that they had wanted to. Basically, it implies that Mark Zuckerberg sort of got cold feet sort of midway through this slash-and-burn reorganization and called off planning for future cuts. But to me, it seems like this is a company that realizes that it is just built for the last era and it has not made the jump to the new era. And I wonder if you think the social media addiction and harm lawsuits sort of factor in there.
Casey Newton 17:36 ↗
It's hard to say because, of course, the social media business is still so incredibly profitable for them. You know, Facebook and Instagram just print money for this company. They remain hugely popular despite everything that we have talked about. In fact, you could argue that these lawsuits are essentially targeting the fact that they are too popular. At the same time, I think this company, you know, having talked to many of their executives over the years, they got really uncomfortable with a lot of the employees they had. They thought their employees had too many ideas. They were too entitled. They wanted too many things. And I think they have frankly relished getting rid of lots of them. And so I expect that to continue. Like, here's a prediction. Those 60% cuts that they got cold feet about this year, I bet they try again next year when the AI systems are better.
Kevin Roose 18:21 ↗
Yeah. I find this totally fascinating. I think it'll be very interesting to see whether teens do actually go to sleep earlier and pay more attention in their classes or whether they just switch to some other more horrible app. Here's the thing. You cannot actually solve the teen mental health crisis at the level of app design. Like, you need more people involved and you need different solutions, but harm reduction is a very effective strategy to have in your toolkit, and I do view the changes that Meta is making today as harm reduction.
Casey Newton 18:52 ↗
I do too. I mean, I feel better raising a kid in a world with these restrictions on these platforms than I would without them. And I think there's a lot of, you know, we give a lot of guff to sort of regulators and lawmakers when it comes to technology on this show, but I think this is one instance in which they were focused and they were persistent and they got the goods on one of the most important companies in the world and they got what they wanted in the form of these stronger protections for kids. So I think this is a case of democracy working. This was a case of state attorneys general doing what Congress tried and failed to do. Right. Congress considered legislation that would have mandated some of these changes, but the state attorneys general got this over the finish line, and I am grateful that they did.
Kevin Roose 19:38 ↗
Yeah. Among other reasons, it means that I will not have to fumble my way through saying attorneys general. Imagine fighting for your constitutional right to send a 13-year-old a push notification at 3:00 a.m. saying that there was a new reel that they might be interested in. That, at some fundamental level, that is what this case has been about.
Well, Casey, we couldn't let a week go by on this show without talking about the hot topic du jour, which is data centers.
Casey Newton 20:05 ↗
Yeah, I would say it's the hot topic du jour because it seems like since January, it's almost all we hear about. Yes. And there's been so many, we've done so many segments and so many shows about the data center backlash and what's driving it and what's, you know, where it's going and what it means for the AI companies and for AI progress as a whole. But today I thought we should drill into one specific post and one specific angle that I thought was really interesting on data centers and these data center moratoria and bans. This came from Arvind Narayanan, a former Hard Fork guest, professor of computer science at Princeton and someone who is widely considered a serious critic of AI hype. He's the co-author of AI as Normal Technology, the essay we brought him on to talk about about a year and a half ago. And he has been following this data center backlash as we have and has come to a surprising conclusion.
Kevin Roose 21:00 ↗
Yeah. And that conclusion is that stopping the construction of new data centers will not meaningfully slow AI progress. Yeah. And in particular, he gives some real numbers to this argument. He says that if a typical US state enacts a one-year moratorium on new data center construction, it would only slow AI efficiency progress by 5 to 10 hours. So basically, if your concern is all this stuff seems to be moving too fast, opposing data centers in your state or your city is not an effective way to slow it down. Yeah. And there are some questions about how much opposition to data centers is really about AI progress. I think there are a lot of other factors. We'll get into it. But we did think that Arvind's point was worth dwelling on a bit because I suspect that as we move forward and more and more data centers get proposed, there are going to be a number of people who see this as a meaningful way of getting some control and agency back in the AI future.
Casey Newton 21:59 ↗
Yeah. And I've even heard it expressed by people who are generally, you know, supportive of and optimistic about AI, but are worried about some of the risks of this moving too quickly, which is like, well, maybe the data center backlash is sort of based on these, like, you know, these sort of local fears about water use and electricity. Maybe they're not quite fact-based when they're out there protesting data centers. But if the net effect is slowing down AI progress, that might be a good thing. And so I really was challenged by and provoked by Arvind's work on this subject because he is someone who's been very skeptical of the claims being made by some of the AI lab leaders, and yet here he is sort of saying, well, stopping data centers is not the way to stop AI progress. All right. Well, before we bring him in, Kevin, should we quickly do our AI disclosures? Sure. I work for The New York Times, which is suing OpenAI, Microsoft, and Perplexity. And my fiancée works at Anthropic.
Kevin Roose 23:00 ↗
Arvind Narayanan, welcome back to Hard Fork.
Arvind Narayanan 23:02 ↗
Thank you, Kevin. Thank you, Casey. Great to be here.
Kevin Roose 23:03 ↗
So, it has been nearly a year and a half since we last had you on the show to talk about your AI as Normal Technology paper, which argued that essentially there are all these bottlenecks that are going to prevent AI from being universally adopted throughout society and getting the sort of rapid takeoff that some people out here in San Francisco believe is imminent. And so it was a little surprising to me that we are having you back to talk about one sort of potential bottleneck that you don't think is going to be a big issue to continued AI progress, which is all of this backlash to and opposition to the construction of data centers. So tell us about your thesis on data centers and whether they will or won't slow down AI progress.
Arvind Narayanan 23:51 ↗
Absolutely. I think the backlash can be a real constraint to AI progress, but maybe not if it's directed toward data centers. It's a different kind of backlash if it's directed at, for instance, governments or other decision makers using AI for consequential decisions. I think that would have much more of an impact, and we're maybe seeing some of that, but most of it is directed towards data centers. And the reason I think it's, you know, it could be a good way to push back if you're concerned about noise or water or other local environmental concerns, but what if you're actually concerned about AI progress as a whole, what is this going to mean for society, for jobs, what is this going to mean for safety, and you generally want to push back on the pace at which this technology is developing, data centers to me are not the way to go.
Kevin Roose 24:42 ↗
Yeah. Well, so, let me make the naive case that not building data centers would slow down AI progress, and then you can give me your math, Arvind, and I'll pretend like I understand math for the purposes of this segment. So, I think that the naive case might go something like, well, we know that to sort of spread AI throughout society, we need to train ever bigger models. That means building more data centers that can train those models. And then we also need those data centers to serve those models. And so the fewer data centers we have, the fewer places there are where we could train these models and serve them to other people. And so for those reasons, I could imagine somebody thinking, well, maybe I'll just stop this data center from being built in my backyard and I will be doing my part to stop AI. What's wrong with that argument?
Arvind Narayanan 25:29 ↗
I think that's a good starting point to think about it, but then we have to get into the details. So you helpfully separated training and inference or serving the models. When it comes to training, most of the data centers, as I understand it, are not used for training. That requires some degree of specialization, and those are done in particular clusters, and so stopping a few data centers here and there is not going to slow down training at all. For that you need some kind of national moratorium or even global. So the real question is about inference. So is stopping a few data centers, you know, either in one's local community or a statewide moratorium or something like that, which is where the action really is, is that playing a meaningful part in decreasing the total amount of AI capacity available in the world? And so to turn that into something a little bit more concrete where we can do some math, we have to look at the total amount of capacity available at a given capability level, right? And so the reason that is important is that one way in which AI is advancing that people don't often think about is not through building new data centers and putting new GPUs into them, but by making more out of the ones that we already have. The industry is getting more efficient at building AI to do a certain kind of task at a certain capability level using less power, less machines. And then the second factor you have is that GPUs, newer GPUs are more power efficient. And those are not all going into new data centers. Those are also going into existing data centers. So it's really those first two factors, what you can do with the existing data centers, that really dominates the increased capacity from new data centers.
Kevin Roose 27:09 ↗
So you're saying that data centers are becoming efficient at a rate faster than demand is growing, or at least to the extent that demand is growing, stopping a data center here, a data center there isn't going to be enough to counteract the effects of these efficiency gains that you just described.
Arvind Narayanan 27:31 ↗
That's right. The efficiency gains both from software and from hardware are about an order of magnitude more than the capacity gains from literally new physical buildings.
Kevin Roose 27:40 ↗
I'm trying to wrap my head around this because I know that what you're saying is true. The models get more efficient to serve over time, right? That the labs keep discovering new ways of running their models more efficiently so that the query that might have, you know, eaten up a certain amount of compute last year, this year, you know, only needs a tenth of that amount. But my understanding is that those efficiency gains are the product of increased compute and having bigger models that are able to help researchers discover the efficiency tricks and the new algorithms that allow them to serve the models much more cheaply. So isn't the overall size and availability of compute important in keeping that efficiency curve going?
Arvind Narayanan 28:25 ↗
Absolutely. But again, I think we're looking at, you know, really, really marginal changes to the total capacity. We're looking at, you know, 0.1% of the national or world capacity of data centers that can be affected by the actions that one community or even one state can take. And so the way to look at it is, yes, it's true that compute is an input even for future development of AI, but whatever decrease you bring about in total capacity, you know, through stopping data centers, whether that compute is going to be used for serving models or for further AI research, that...
Same amount of progress can be made through these gradually continuing efficiency improvements. At a rate that, you know, I did the numbers on this — if one state stops new data center construction, that translates to something like 10 hours, right? That's how much it takes, aggregated, for the AI industry to catch up through efficiency improvements to the compute that has been foregone.
Casey Newton 29:29 ↗
It's just so counterintuitive because of how hard the companies are all working to build new data centers. You know, like throughout most of this year, most of the big frontier labs have been in this capacity crunch where they're basically selling as much AI as they can make. So it certainly seems like there is something very important to them about being able to build these data centers. So how do you think about that, Arvin?
Arvind Narayanan 29:53 ↗
Yeah. So that is all true, and that doesn't contradict what I said. And here is the way to square both of those things. So this progress that's happening through improved GPUs or improved software efficiency, for the most part, that is shared by all AI companies. And so that factor kind of cancels out between companies, and the competitive advantage that one company is going to have over another really comes down to how much compute they can control. And so while the total amount of compute is not a big factor in the aggregate rate of AI progress, the relative amount of compute is a surprisingly big factor in the relative competitive positions of companies. Both of those things are true at the same time.
Casey Newton 30:38 ↗
Interesting. So regardless of, you know, what moratoriums might do for overall AI progress, if you are an individual lab, it's still really important to you that you get as much compute as you can get your hands on.
Arvind Narayanan 30:49 ↗
Exactly. If only to stop your competitors from getting their hands on that.
Casey Newton 30:53 ↗
I mean, I think a lot about this in terms of the nuclear power opposition in the 1970s and 1980s, where you had this series of accidents, including Three Mile Island, and after that, like a huge chunk of the American populace, or at least the politically active American populace, decided that nuclear power was bad and dangerous and we shouldn't build it. And so there was basically a successful campaign. I mean, we didn't build nuclear power in America for like 30 years. And it didn't stop the technology, but it just sort of changed the geography of where it could be built. So instead of happening in America, it was happening in France and other places around the world that did build nuclear power. Is that what you think is the likely outcome of data center opposition in America? That it won't sort of stop the technology, but that it could change the distribution of where it's being built?
Arvind Narayanan 31:41 ↗
You're right that I don't think it'll stop the technology. I'm also very skeptical of whether it's going to meaningfully change the distribution of where it's built. State versus state, maybe. But if I understand correctly, one reason stopping a lot of nuclear plants from being built in the US was so successful was by raising the regulatory cost. And that's just a very different model from how the AI data center backlash is proceeding. It's not nationwide regulation that forces AI developers wherever they are in the nation to go through a whole lot of extra review or a whole lot of extra safety technology that is going to raise their cost tenfold and change their deployment timelines tenfold. It's rather, you know, moving it from one location to another, which locally might seem like a big win, but at a national level, I don't see it doing much.
Casey Newton 32:35 ↗
Yeah, that's interesting. I'm curious, Arvin, if stopping AI progress is not a realistic goal of the data center opposition that we're seeing right now. Like, are there other things that it could accomplish that may be constructive rather than futile?
Arvind Narayanan 32:53 ↗
Absolutely. I've looked a little bit at what is driving the anti-data center movement, and I'm certainly not claiming that this kind of slowing AI is the main goal of the movement. A lot of it is driven by local concerns. A lot of it is driven by procedural concerns, the lack of transparency, the way that local politicians enter into these deals without giving citizens a voice. But, you know, whatever the ultimate reasons are, I would say that what is happening right now is arguably a pretty rational way to go about it, because you have to have the credible threat of bans and moratoria in order to force companies to come to the negotiating table. So companies are making a lot of money. I think maybe communities can channel their opposition in a way that they can ask for direct payments, investment into local communities much more than we're seeing today from AI companies, so that local communities can benefit.
Casey Newton 33:49 ↗
What do you think does drive AI progress if it's not availability of compute? You've said algorithmic efficiency, the sort of notion that these models become cheaper to serve over time. But what else should people be — if they are interested in slowing down or stopping AI progress — like, what is the better fight to be having?
Arvind Narayanan 34:08 ↗
Yeah, I mean, there are many different dimensions of progress, right? So one can think about what is the most powerful, capable model out there, and that might matter to you a lot if what you're concerned about is some of the incidents we've seen, like the Hugging Face incident and some of the safety risks. There's another sense in which you might want to stop, you know, the rapid march of AI, which is people doing things with AI that are not really suitable for AI, delegating too much decision-making to AI. So when I hear things like the colloquially named AI psychosis among CEOs, right? CEOs, you know, using Claude Code to try to replace what an employee does. And of course, it does a first-cut version which superficially seems like it does the job, firing a bunch of people and then recognizing, oh, now when something goes wrong, there's nobody to fix the mess, hiring people back. We've heard this kind of story many times over. And of course, you know, in some cases, these models are good enough to in fact replace certain tasks that people do. But the level of premature decision-making that we've seen from CEOs has been a cause for concern. I would have hoped that these people, who frankly have a lot of money on the line, would just for rational, self-interested reasons make better decisions that take into account not just AI's potential but also its limitations, you know, here and now. So this, in my view, would be a much better target for opposition, and that's, you know, less at the community level and more at the workplace level, better aligning incentives and decision-making and information between the individual workers who, in many ways, have a much more grounded understanding of what AI can and can't do in a particular company, and management, which, you know, in many ways is forward-looking, and that can be a good thing, but can also make some misguided decisions.
Casey Newton 36:03 ↗
Yeah. At the same time, I think there are probably a lot of people out there who do want to sort of have more control and agency in a world where it seems like AI is advancing quickly, and I suspect they're not going to be satisfied with the answer of like, well, you can just rely on the inertia of your organization to slow the progress of this. So are there other things out there on the horizon that you think could give people more of that feeling of control?
Arvind Narayanan 36:34 ↗
Absolutely. I think we have a lot of control in how we ourselves use AI. So this is something I constantly confront in my own use of these tools. I mean, I am a pretty heavy user of AI tools and AI agents. And I find that by default, they do things that I'm not very happy with, in ways that I feel like I'm losing control. So if I ask an agent to, you know, find papers, materials, reports on a given topic so that I can start to analyze it, it will, without my asking for it, turn that into its own analysis, its own opinion. And so I have to put specific things in my prompts so that I can get it to do the grunt work for me, not to do my thinking for me. So that's, you know, just one simple example, but the broader point is that these tools are not only powerful, they're very, very flexible in how we can use them, and I think each of us should not just accept the way that the developer has created the tool, but configure them, personalize them in ways that meet our appropriate comfort level for what should be delegated to AI and what should be in the domain of people. That's not an answer to your broader question about AI as a kind of, you know, powerful global force and how we can slow that down. But I think at an individual level, I do want to emphasize that we have a lot of agency.
Casey Newton 37:53 ↗
The Marxist historian Eric Hobsbawm has this famous phrase about the Luddites of the Industrial Revolution, that they were conducting collective bargaining by riot. Basically, that all of the sort of opposition to machines was a form of collective bargaining, because those industries had not been unionized, and the only means of expressing their discontent that workers had was to, like, break the machines that were threatening their jobs or threatening to concentrate wealth to the owners of the factories rather than to the workers. And I've been thinking a lot about this. You know, obviously, and thankfully, we're not at the point of, like, violent riots over data centers yet, but I think there is a possibility that we end up there. And I think your point, Arvin, about this being a form of kind of collective bargaining without any formal mechanism — like, this is, to me, when I see people protesting data centers, I think this is about what's in it for these communities. You know, if the data center companies came in and said, 'We're going to build this data center, but we're also going to build you a high school and a really nice public park and improve your roads and make your everyday life better,' to me, that feels like a much better deal than they're getting now. And so I think of this sort of data center backlash as a form of kind of collective bargaining by another name.
Kevin Roose 39:15 ↗
Well, and, you know, the sort of traditional form of collective bargaining has been pretty effective here, right? We've seen workers in Korea rise up and threaten to go on strike if they didn't get a greater share of the profits, the record profits that their companies were realizing in part due to the AI bubble. So I think good old-fashioned unionization can do a lot here. We also saw it in Hollywood, right, where, you know, like the last time the big unions got together, they negotiated for a lot of protections against AI.
Arvind Narayanan 39:40 ↗
Yeah. 100% agree with the collective bargaining perspective.
Casey Newton 39:44 ↗
All right. Well, Arvin, thank you so much for coming on. We really appreciate your expertise and wisdom as always. And, yeah, we'll — I guess we won't see you out there on the picket lines for the data centers. We'll see you in the spreadsheets.
Arvind Narayanan 40:00 ↗
I'm happy with that role. Thank you. This has been really fun.
Casey Newton 40:03 ↗
Thank you.
Kevin Roose 40:09 ↗
Well, Casey, we have a bittersweet final segment of our episode today. We are doing the last ever Hat GPT.
Casey Newton 40:23 ↗
That's right, Kevin. After almost four years of slips of paper being lovingly handcrafted and fed into a variety of stylish hats, this will be our final opportunity to take a slip from the hat, discuss its contents, and then when one of us gets bored, we'll say to the other, 'Stop generating.' We've been through so many hats, at least three by my count, and so many slips, and we'll never forget them. Hats are now out of fashion, and so we are retiring it as a vehicle for podcast content creation. All right, let's do one final trip through the hat.
Kevin Roose 41:06 ↗
Wow. Sometimes I forget that we record in front of a live studio audience.
Casey Newton 41:11 ↗
That's beautiful. Our producers just hit us with the applause sound effect. And Casey, this is, I think, our longest — was this our first ever, like, segment that had its own title and gimmick?
Kevin Roose 41:23 ↗
I think it was — it's our first ever gimmick segment, and it's only fitting that we go out in a bang. My only lament is that because we're doing this segment today, we won't be able to continue with our bit of launching a new segment for every show until the end of the show. All right, Casey, let's open the hat one last time.
Casey Newton 41:46 ↗
All right, Kevin, our first item today. The Apple Vision Pro is being used in surgery. A study from UC San Diego in which the Vision Pro was used as a primary display for a tear duct procedure, which of course I know better as an endoscopic dacryocystorhinostomy. Oh my god, that's really hard.
Kevin Roose 42:08 ↗
D cryos.
Casey Newton 42:10 ↗
Keep going. You can do it.
Kevin Roose 42:13 ↗
D dacryocystorhinostomy. Let's go.
Casey Newton 42:19 ↗
Anyway, there were 32 total procedures, and key findings included that by using the Vision Pro, the operating times were 19% shorter. They had 100% functional success with no post-operative complications and a significantly lower surgeon-reported workload. Kevin, have we finally found an ideal use for the Vision Pro?
Kevin Roose 42:41 ↗
Yes. It turns out that the people most in need of the Vision Pro were the Vision Pros.
Casey Newton 42:48 ↗
And by that I mean the surgeons operating on people's eyeballs.
Kevin Roose 42:52 ↗
Stop generating.

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APA

Newton, C. (2026, August 28). What Meta's $17 Billion Settlement Means for TikTok and YouTube [Interview transcript]. Hard Fork. CEOInterviews.AI. https://ceointerviews.ai/interview/3002521/

MLA

Casey Newton. "What Meta's $17 Billion Settlement Means for TikTok and YouTube." Hard Fork, 28 Aug. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/3002521/.

BibTeX
@misc{newton2026_3002521,
  author       = {Casey Newton},
  title        = {What Meta's $17 Billion Settlement Means for TikTok and YouTube},
  howpublished = {Interview transcript, Hard Fork. CEOInterviews.AI},
  year         = {2026},
  month        = {aug},
  url          = {https://ceointerviews.ai/interview/3002521/},
  note         = {Speaker-attributed transcript with timestamps}
}