AI’s Uneven Arrival, TikTok’s Potential Departure, Xiaohongshu and the Delights of Cultural Exchange

Looking to digital advertising history for clues about AI’s impact on the economy, proposed frameworks for AGI and ASI, and why AI benefits are likely to be unevenly distributed in the near term. Then: The logic and continued uncertainty surrounding a TikTok ban in the United States, the delights of Xiaohongshu mania, and a word about TikTok and conflicting principles.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:04Andrew Sharp?

  Hello and welcome back to another episode of Sharp Tech. I'm Andrew Sharp and on the other line, Ben Thompson. Ben, how you doing?

• 0:15Ben Thompson?

  I feel I'm just seeing a lot of Andrew Sharp. We recorded a day late this week. I'm already back on with you.

• 0:21Andrew Sharp?

  Do you need more time?

• 0:22Ben Thompson?

  We're apparently recording on the holiday on Monday. Yeah, I mean, geez.

• 0:27Andrew Sharp?

  That's right. Yeah. I look, I'll happily go back on vacation for 10 days and you could just kick your feet up for a little while here. But I'm excited. This half of the podcast is excited to be back in the trenches with you, the take trenches.

• 0:40Ben Thompson?

  All right. Well, let's do it then.

• 0:42Andrew Sharp?

  All right. Well, we've got a lot to wrap our arms around on this episode. So buckle up. TikTok may or may not be on the brink of a full-scale ban in the United States. But before we get there, we'll begin with AI and an article that you published on Strategery Monday morning. And it's funny because that article had me thinking back to our first show after the holidays where we got a question about AI adoption among non-tech firms and what sort of tech companies may benefit from helping those companies incorporate AI solutions into their business. And with your article on Monday, I felt like you presented a theory of the case with respect to AI's impact

• 1:24Andrew Sharp?

  on the economic landscape, at least as far as it goes in 2025. The title of that piece was AI's uneven arrival. And we can begin with your conclusion there. You wrote, "The most important AI customers will primarily be new companies. Traditional companies, meanwhile, will struggle to incorporate AI outside of whole-scale job replacement, ala the mainframe. The true AI takeover of enterprises that retain real-world differentiation will likely take years. None of this is to diminish what's coming with AI. Rather, as the saying goes, "The future may arrive but be unevenly distributed. And contrary to what you might think,

• 2:05Andrew Sharp?

  the larger and more successful a company is, the less they may benefit in the short term. Everything that makes a company work today is about harnessing people, and the entire SaaS ecosystem is predicated on monetizing this reality. The entities that will truly leverage AI, however, will not be the ones that replace them, but start without them."

• 2:27Andrew Sharp?

  So Ben, I will let you drive here. Do you want to expound on that conclusion and explain to people how you got there?

• 2:34Ben Thompson?

  Well, just one reference in there about the whole scale job replacement. That was a link to my article last year about enterprises and analogizing AI to its potential impact to the arrival of the mainframe. That sort of wiped out rear end back offices. I think to really leverage this, you need top down decision making. You need significant integration projects to sort of make this work. I'm a bit skeptical. I'm not skeptical about AI helping the individual worker. I think that's happening right now. In fact, there's a bit where the individual worker today, I think I've made this analogy on the podcast before, but the individual worker today is like

• 3:15Ben Thompson?

  the newspaper companies in the 90s. It's like, wow, we have our core business and we get all these internet customers for free too.

• 3:21Andrew Sharp?

  Just more revenue. What's the problem?

• 3:23Ben Thompson?

  Yeah. And so there's almost like this, this real arbitration opportunity that I think continues to be taken advantage of. Where if you're an employee that has the, the sort of wherewithal to go and use AI, you're tremendously more productive. And/or you can be tremendously more lazy while doing the same amount of work because AI is augmenting you. And I think that is a bit of, you know, there's a point of frustration amongst corporations to a certain extent where there are large gains being realized, but they're accruing to individual employees and not sort of to the enterprise as a whole. So that in and itself is a real motivation to sort of get this done and figure it out. But I'm skeptical of the top down, okay, everyone has an assistant now, go and use it sort of bit.

• 4:08Ben Thompson?

  And just like, you know, not everyone was going to go and use a computer, you know, the, the people that benefited from computers, even fast forwarding to the 80s, were the people that wanted computers and wanted to go and use them. And then, you know, and would have the wherewithal to figure it out and, and figure out the use cases for that. So this idea that Microsoft's gonna sell a bunch of co-pilot things, or Google just announced, which by the way, was very clever. They're taking away for Google Workspace, they're sort of like Microsoft Office equivalent. They're taking away the Gemini add-on and they're bundling it with the whole thing and then raising the price of the whole thing. That's gonna have a way more larger impact on Google's business.

• 4:50Ben Thompson?

  Like price raises that apply to everyone and you're gonna sell it as because you get this new feature, that's gonna be great for their business. And I'm skeptical that it's going to.

• 5:01Andrew Sharp?

  Be great for companies.

• 5:02Ben Thompson?

  I think, I mean, they're gonna pay more, they're locked in, they're not gonna go anywhere.

• 5:06Andrew Sharp?

  Well, right, but I think you're not gonna be transforming the productivity of a company based on Google's offerings there, I think is the thesis.

• 5:15Ben Thompson?

  Yeah, it might sort of trickle in through people using this stuff more and more and realizing what's effective and what works. But I am a little skeptical of this. We just, suddenly every company is gonna be a gazillion times more productive next year because now they have access to AI. And this bit about just the very structure of AI, even if you get to this world of agents and you can actually give a task to an AI and it will go and accomplish it. I did sort of drop my, there's always this discussion, what is AGI, what is ASI?

• 5:47Andrew Sharp?

  I like that, yeah.

• 5:49Ben Thompson?

  Yeah, I sort of arrived at AGI is when you can give the AI a task and then AI will accomplish it. And it might have to access different tools and things to do that along the way. And the exact use cases, so that's like a step up from the assistant level, right? Like where like the chatbot level, where it's directly reactive to what you do. And it's not like a multi-step sort of thing. AGI is, it's like a very conscientious, but fairly dumb employee. Where they're not gonna figure out what to do, but if you tell them what to do, they'll go do it and they'll do a good job. And by good job, it doesn't mean a perfect job, right? You give a human a job, again, to use the self-driving car analogy, self-driving cars are going to get in accidents.

• 6:33Ben Thompson?

  The question is, you have to remember, human. Get in accidents too, right? And you give a job to an employee and sometimes the employee will screw it up. And you give it a job to an AI and sometimes the AI is gonna screw it up, but it's going to reach a a good enough level that, you know, and what you'll see is this sort of bleeding of human jobs where maybe humans leave and they're not replaced because the current humans can be more productive, right? That that is a tried and true method of sort of getting productivity into the workforce is we used to have 10 employees on this team. Now we have eight and you still have the same number of responsibilities. So you're gonna have to figure out how to sort of get it done. Suddenly you reach to AI because you just have more work to do.

• 7:17Ben Thompson?

  And that is actually how it sort of gets in the organization. I think that's the way a lot of these things are going to happen. As an aside, ASI, artificial superintelligence in this framing is the AI that can decide what tasks to do in the first place.

• 7:34Andrew Sharp?

  Right. Can look at the problems you have and come up with different solutions that humans haven't devised themselves.

• 7:40Ben Thompson?

  Problems on its own and just go and fix them, right? Like that. And so, so the, and it's interesting because that, that is in some respects, like very compelling. It's also maybe a little more approachable than this idea of like this godlike oracle that is like solving the world's problems. But I do think both of these definitions have the benefit of being fairly testable, like, like, like, can it do sort of XYZ or can it not? And of course, the actual approach and achievement of them will be on a spectrum will be, you know, you know, it will be a sort of a gradient, you know, in terms of whether it achieves or not, but.

• 8:17Andrew Sharp?

  I was gonna say, because like artificial superintelligence, for instance, you can give AI like an LLM. You can give them a list of symptoms and there are cases where the LLM can identify what's wrong with a patient and a doctor can miss it. So like, I don't know whether that qualifies as artificial superintelligence.

• 8:38Ben Thompson?

  No, to me, to me, that, that, that's still just the assistant, like, like you're, it's sort of doing, it's just returning an answer. It's a. You know, I don't want to call it a glorified search engine that that diminishes what it is. It's it's but it's.

• 8:52Andrew Sharp?

  But it's processing a lot of information, just speaking in the abstract. It's processing a lot of information and and identifying what needs to be done to help a patient heal. So it's sort of like what you're describing on a micro level. But on a macro level, I understand that we're talking about sort of broader solutions and broader abilities than exist now.

• 9:11Ben Thompson?

  More of an ASI would be like it just sort of like working over all the patient data. And unilaterally goes and schedules an appointment with someone and says, you know, there's there's sort of symptoms showing up. You need to come in and then the it's like in this case, it's directing humans. It's a oh, I go do this scan on this person and then it sort of has a solution and it writes the prescription and sort of X, Y, Z. That is ASI. It's the flip. It's where the AI is starting to tell humans what to do instead of humans telling the AI what to do. And that that is sort of the line, whereas AGI and I actually I do like, I think it's been a very productive. To add ASI as opposed to AGI because these are two different things.

• 9:56Ben Thompson?

  Whereas, you know, for maybe with AGI, the doctor is telling the AI to go and do X, Y, Z. And it has to do a number of different steps to figure out the solution and do do X, Y, Z. But it's still sort of under control. The the human is still telling the AI what to do. Anyhow, all these are going to be fuzzy in implementation, but I I do like this framework as as terms of, you know, giving us. A vocabulary to sort of talk about these different steps. So right now we're in the assistant age. And that's just LLMs, you know, what we're calling AI. The next step is the agent age, which I would call AGI, where it will accomplish tasks that you tell it to do.

• 10:37Ben Thompson?

  And then ASI is it tells humans what to do because it already has it figured out that that's that's the. Both more promising and also more scary sort of a leap, you know, for our very obvious reasons.

• 10:53Andrew Sharp?

  Right. And I actually didn't realize that ASI was a recent addition to the lexicon because I saw people dropping that a couple of months ago. And I was like, what the hell is ASI? So I appreciated your digression in the article and I appreciate your digression on the pod. Take me back to your conclusion, though, about the sorts of companies that could benefit from AI in the long term.

• 11:15Ben Thompson?

  Well, there's lots of different pieces here, including the sort of this whole world of SaaS and software that is all predicated on organizing by people. Like you, like we've talked about the business model of per seat licensing and all that's a problem in a world where AI is removing jobs. But I think there's a broader principle here, which is what is a company? And this idea that we think about a company and the units of work being humans. But that's actually always been a proxy. It's a proxy for actually accomplishing a task, actually producing an economic output.

• 11:55Ben Thompson?

  And it's almost like the, this is a similar thing with when art generation, image generation models came out. I wrote an article talking about how like, for all of history, we've just sort of assumed that the ideation and the manifestation is two peas in a pod. And AI is like, what? No, actually, they're two different things. The like, the, the actual coming up with the idea and the actual implementation of the idea can be separated. Like, like you can write a prompt and then the AI can do the actual creation and sort of what it is. And you think about it like, well, yeah, that actually is true. You could go hire an artist and try to get them to make what you want.

• 12:36Ben Thompson?

  And of course, we've been doing that for a long time, but it never sort of like, you don't think about that there actually is a very clear division here. And, and I think it's a, it's a similar aspect here. We think about, when we think about things to get done, we think about the humans that do them. But those humans are just a proxy that is actually independent from getting the job done. And, and so in that world, what are we actually paying for? What's the actual goal?

• 13:05Ben Thompson?

  If you're a company, it makes a lot of sense that you pay per job completion, right? And again, this is where the art angle is also interesting. There is a bit of this with the sort of freelance world, or the upwork world, or whatever, where you hire someone to make a logo for you, and you're paying for the job. You're not necessarily paying for their work. And so it's not like this is a completely foreign concept, but it's going to become like the defining concept in terms of how you think about paying for stuff and paying for work. And that's where I came to sort of the advertising analogy. The thing with like Facebook and Meta and direct response advertising, and actually you go back to Google, really. I probably should have given Google more credit in this regard.

• 13:50Ben Thompson?

  What made Google's business model such a big deal is that until then, you paid for ads based on how many people saw them. Like, and that was a hangover from newspapers, right? Like, you paid more to put an ad in a newspaper with a lot of circulation. You paid less for one with fewer, right? Like, it's how many people are going to see this? But people seeing an ad is a proxy for the actual goal, which is people making a purchase decision, actually buying the item in question. And so what I was trying to get at with this article is it's very easy to think about this stuff from a theoretical perspective,

• 14:32Ben Thompson?

  which is, of course, it's better to pay for the actual purchase. That's the goal. You're trying to sell stuff. But it turns out there's entire ecosystems and businesses that are built around the assumption that that's not possible, that you have to focus on the proxy. And this is where the CPG analogy, I think, is super interesting. This whole CPG model. You have lots of different brands that are all the same thing. I think like I've used this analogy before, but Axe body spray and like Dove like beauty products are made by the same company. And it's pretty much the same stuff.

• 15:13Ben Thompson?

  And yet they're not thought about the same thing because that's how branding like the, the, the product managers in CPG companies are not called product managers. They're called brand managers because that's the, and actually the current, it's interesting. The current CEO of P and G is the first CEO, I think in their history that didn't come up through the marketing organization, which sort of speaks to a lot of the shifts that have happened here. But these are marketing companies. They build brands. They run commercials. They have coupon things that, and you have an affinity for a brand. So that you go into the store and it's almost, the goal is to have a subconscious selection. You see, you need deodorant, you buy like, we talked about this. You're an old style man, like, right? Which is very much a

• 15:56Andrew Sharp?

  Of course.

• 15:56Ben Thompson?

  Old Spice, old style, whatever. Yeah. I mean, like your penny loafers, like it all sort of goes together. He's being on sailboats in, in Nantucket or wherever it might be. So

• 16:04Andrew Sharp?

  That's right. My penny loafers.

• 16:10Andrew Sharp?

  But there's an entire apparatus behind that business model that wasn't suited to playing on Facebook and Google for the last 20 years.

• 16:19Ben Thompson?

  That's right. That's right. And especially you go back a decade, Facebook and Google weren't nearly as good of doing what they do as, as they sort of are now. It, it really was the case. You had to sort of be much more selective in your targeting. I'm targeting X, Y, Z. And if you paid to say, I want to reach the millennial man on the East Coast in his penny loafers. You paid a lot of money for that and you better have been pretty sure you were right. And it turned out actually, no, just running advertisements on ESPN works better. Like the actual cost to reach people is lower, even though the overall cost is, so the overall cost is high. So there's a high barrier to entry, but the cost to reach an individual consumer is actually lower. And the actual point of decision isn't when they're watching TV anyway.

• 17:03Ben Thompson?

  It's when they're in the supermarket, when they're, when they're, when they're walking down the aisle and they grab the deodorant. Like, and so this, and so there's an entire edifice that was built up around this model. And, and what was so interesting is particularly you go back like a decade, all these companies realized. Yeah, in theory, this Facebook advertising stuff's amazing. It doesn't work that well for us because we're not selling bespoke products. Like we're like, yes, we're trying to be, we have market categorization and we're trying to reach this particular demographic. But the reality is that demographic is fairly large because we operate at scale and our manufacturing is at scale.

• 17:47Ben Thompson?

  And we have to buy shelf space at scale, scale, scale, scale, scale, scale. And the fact I can reach people on an individual basis is actually not that useful for me. It just costs too much. So we should actually double down on TV. This is why TV kept making money so much longer than people thought it would. Even as the viewers are bleeding away, it's like, why are advertisers still on TV? Because they're built around TV. Their entire business is organized around this, this paradigm. Now, again, as I noted, TV has finally collapsed. The users got too small. Everyone had to adjust. P and G has had to shift their approach, all the CPG companies.

• 18:29Ben Thompson?

  And also, by the way, Facebook's gotten way better at like efficiently finding customers that you want. And also COVID drove a lot of purchases online, which tightens this loop in a way that makes these ads sort of more productive. And you can track conversions more effectively. So there's lots of factors that mean it's not, but that's interesting in its own right. It's not that digital advertising didn't end up being important to companies like P and G and Unilever. But it took a lot longer than you might have thought. And that is the analogy. I'm not saying this is a perfect one-to-one match between AI and digital advertising. Rather, you can have a product that is obviously better, that's obviously more productive.

• 19:13Ben Thompson?

  And yeah, sure, 01, 03 inference cost costs a lot. That's a lot less than paying someone $100,000 or $200,000 or whatever it might be for these, you know, white collar workers that are, that are the proxy for getting the job done. But there's an enormous amount of inertia.

• 19:33Ben Thompson?

  In the current system because there's so many systems and processes built around humans as the proxy for getting work done. And so it's right to be long term. Someone wrote like, oh, I can't believe you're optimistic about SaaS companies on Twitter. I'm like, I'm not optimistic about SaaS companies. They're clearly in trouble. This whole business model is is kind of screwed up. But just like to go back to 2015, you are right to be long term pessimistic about TV and the entire ecosystem around it. But it still took many years longer than people thought for it to sort of collapse and fall down. And you needed COVID again, I think, as a forcing function for some of this stuff is also underrated.

• 20:17Ben Thompson?

  That probably pulled forward some of the collapse for these things a fair bit. And I think it's going to be similar with with AI. Now.

• 20:26Ben Thompson?

  Sorry if I'm monologuing here.

• 20:27Andrew Sharp?

  No, no, no. Go for it. I do have a question, but I'll let you keep rolling here.

• 20:32Ben Thompson?

  The other key thing about digital advertising and the and the power of Facebook and why you could have this situation in 2020, where all those CPG companies, a bunch of other big companies boycotted them and had no impact on their business. That's because these new formats create their own customers. There's entire swaths of of companies, particularly in e-commerce and apps and all this sort of thing, that that were created in response to the Facebook product being available. And and and so Facebook basically created their own customer base. And the funny thing is you have like these CPG companies that were going to be super narrow. We're going to focus just on very specific customers because Facebook lets us do it. Guess what? If CPG or if P and G and Unilever want to pull their ads,

• 21:14Ben Thompson?

  oh, now we can buy ads on a more inexpensive basis because there's less competition and actually start hurting them, taking market share from them, which Facebook wins either way. That that that is anti fragility. Like the the sort of like the concept of anti fragile is even things that hurt you actually make you stronger. And so like CPG companies boycotting Facebook makes Facebook stronger in the long run. You saw this with Apple and the whole ATT thing proved Facebook's anti fragility. Like, yeah, it was devastating to Facebook, but it actually reinforced their overall competitive position.

• 21:48Andrew Sharp?

  Deep in their moat, yeah.

• 21:50Ben Thompson?

  Yeah, yeah. And so, so the, and so, but those were new companies and you, the whole Shopify ecosystem is downstream from Facebook ads. Like, like, so Facebook created their own market. And I think, and I think that is what you're going to see happening is AI is going to create entirely new industries. It's going to create entirely new companies that are going to be chipping away at these large companies that can't fully adjust. And that, and it's going to create its, its own ecosystem that will, in the long run, force these larger companies to cram this stuff down. Particularly once it gets better and they can figure out how to adjust. So it's not, this isn't a, this isn't a forecast about the next 50 years.

• 22:33Ben Thompson?

  That AI is not going to, not going to, you know, go into these companies and change them. It's just saying it's not going to happen in 2025. It's going to be this longer process where companies lean into it and embrace it because it's this new opportunity, I think primarily new companies. And they're going to come up from the bottom, start chipping away at the, at these existing companies. And then, you know, it, it's a sort of almost a more of a classic disruption story. And at some point, these other companies, one more point. I made this point in the context of Enterprise AI, the Enterprise AI article, but there is a generational aspect to a lot of this. I, I think that SaaS is in many respects a demographic story. You had this host of millennials coming into companies that were familiar with working online.

• 23:18Ben Thompson?

  They, it wasn't weird to them to log into a random website and sort of do your work. They'd been doing, they'd been working in Google Docs in college for ages. They were used to the sort of whole concept. And, and so that created the, a workforce that was receptive to this. It wasn't the eighties, we were saying like, go use this computer, person who's been using a pencil and paper for, or a typewriter for the last 30 years. Like, there's a generational shift that is sort of necessary. And that will be a similar thing with AI. You fast forward to 2035, you're going to have more and more portions of the workforce that have grown up with ChatGPT. They've grown up with the. Assumption of AI. It's not that the people have eight, right now, the, the arbitrage opportunity is people who have agency can go use AI

• 24:01Ben Thompson?

  and they can be more efficient than their colleagues and it's a big advantage. In 15 years, everyone will use it as a matter of default. It will change from being an advantage to being table stakes. And once it's table stakes, the, the opportunity to, to push it and increase it, it will actually start to reaccrue to the corporation as opposed to the individual employee. So, so employees, uh, enjoy it while you can. Don't think about being newspapers, uh, in 2010.

• 24:30Andrew Sharp?

  Right. Well, and as far as the way companies are built, I mean, it's not an apples to apples comparison. But when I was reading and thinking about big companies incorporating AI into their existing workflows and their existing employee bases and potentially deriving benefits, but maybe not as many benefits as people expect. I was thinking back to your piece on Tesla and Tesla's approach to self-driving technology and the bitter lesson which stuck with me. I will refresh people's memory in case they forgot the bitter lesson from the fall. But this was Rich Sutton. He wrote, "The biggest lesson that could be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective and by a large margin."

• 25:15Andrew Sharp?

  And then continuing on, he says, "Seeking an improvement that makes a difference in the shorter term, researchers seek to leverage their human knowledge of the domain, but the only thing that matters in the long run is the leveraging of computation. And the human knowledge approach tends to complicate methods in ways that make them less suited to taking advantage of general methods leveraging computation." And so, big picture stepping back, it would make sense that all the friction associated with trying to incorporate AI into human workflows becomes its own sort of gating function for some of the big incumbent companies that are trying to take advantage of this technology. And companies that get to just start with a blank slate

• 26:00Andrew Sharp?

  ultimately will be able to capitalize on all these capabilities more as we head into the future here. And that might take more like four or five years as opposed to four or five months as we all project ahead in 2025. Is that sort of what you're saying?

• 26:16Ben Thompson?

  I think, yeah, I think if you zoom out, the broad analogy is correct. I I would just would sort of distinguish that the bitter lesson is about sort of the development of the fundamental capability. But there is a separate discussion about actually productizing this, which is, there is, I don't think there's a bitter lesson for product development.

• 26:39Andrew Sharp?

  Right.

• 26:39Ben Thompson?

  Like, that's more iteration and sort of X, Y, Z. I do think, but this reminds me of another point. We did discuss a little bit on the first podcast of the year about aggregation theory and these models and things along those lines. One thing to keep in mind is there is a tendency, just in analysis generally, to jump to the new thing and say the old thing's done and gone, right? When, in reality, stuff layers on top. The old stuff continues to be relevant. And I do think that just overall L L Ms that just sort of give you an answer and they don't really think about it, they just generate it. Number one, these new models are going to make those models better because they can sort of, one of the problems in developing the sort of core models is we're running out

• 27:24Ben Thompson?

  of data. These new models can generate actually interesting and useful synthetic data more effectively that can go back into training these new models so we can get more of the data that we need. So they're going to get better. Number two, they're going to always be cheaper and they're going to always be faster. And cheap and fast still matters for things like aggregation, like doing things at scale. So I don't think aggregation is necessarily dead. When you, when you talk about Facebook and the opportunities of AI-generated content within, within the Facebook feed, or every single item on Facebook becoming an ad, right? Because you could do image, you can recognize the image, you can see the bag in the picture and you can click on it.

• 27:59Andrew Sharp?

  Sounds like an awesome future. Here we go. Yeah.

• 28:02Ben Thompson?

  The cost of mistakes there is low, right? Whatever, you mislabeled the, the, the bag, not a big deal. Like, the, the, doing it at scale and cheaply is going to be valuable. So I would actually, I would push back on aggregation theory is dead, which by the way, has only ever, that was never about business and SaaS. That's about the consumer internet by and large. And, you know, I think just the, the base L L Ms that are serial, just generate an answer are right a lot of the time, but make mistakes, are still going to have real utility and there's still a huge product overhang in leveraging them. This new capability of paying for A result to in the more you pay, the more right it is. That is going to be, that's a different category.

• 28:45Andrew Sharp?

  I was gonna say, that's just a completely different business.

• 28:48Ben Thompson?

  That's right. And this is where the other point to digital advertising, right? Paying for, you pay for results with digital advertising. You don't pay for, now there's still digital advertising, you pay for display. But you pay for results and you base your payment to Facebook, and this is why Facebook is maddening and also inescapable. They will, they'll take margin because the more you trust Facebook, the better they'll like, the better the results will be. You just give in to the AI buying algorithm and you know, they're showing enough ads to enough people they know will convert to get it. And they're showing the ads to a bunch of people that don't know and don't care and you're paying for it anyway. But you don't know who they are. You're getting customers you never would have otherwise. And so you set your price target. This is my lifetime value of a customer. I'll pay up to XYZ and Facebook will fill that.

• 29:32Ben Thompson?

  And that's why like the COVID, when COVID dropped in March, Facebook had a dip for like a week and then zoomed right back up. Because all, all these companies that need Facebook, that's their whole lifeblood. They need to be acquiring new customers all the time. Guess what? If other, if all the brand advertisers want to leave, cheaper ads for us, we'll buy more ads. And it zooms right back up to that, to that line of whatever their sort of LTV calculation is. AI, I think will be similar. You will, you will, what is the, what is the worth of this job to me to get it right? What level of accuracy do I need? Given that, what is the amount of compute necessary? What's the cost of the compute? And it's really interesting. It gets, again, this is the, this is why I wanted to make this analysis.

• 30:14Ben Thompson?

  It's right now, humans are the old advertising. Half of them work and I don't know which half, right? There's a bit about, you know, like the, when you're evaluating your workforce, it's kind of like, you just know there are some employees that seem really lazy and don't do anything and the whole company would fall apart without them. And then there's other ones that are, it's like they're really busy. They're, they're all around and they're always present. And actually they're not getting anything done.

• 30:39Andrew Sharp?

  Not doing all that much.

• 30:40Ben Thompson?

  Right. It's, it's, it's all a proxy right now. AI is going to be much more direct. You're going to know if it works or if it doesn't, and you're going to be able to price it accordingly. There's more. transparency in the pricing of the value of a job, which also is going to be hard to implement. If you're a company with its existing processes, you have no process. You have no conception about how to price a job. You know how to price an employee and what they ought to accomplish, but there's a lot of fuzziness in there. And there's going to be a level of precision necessary to price this appropriately. Which, by the way, we saw with Facebook with ATT. That the dip wasn't that the Facebook ads stopped working.

• 31:24Ben Thompson?

  It's that you couldn't know which ones were working. And so it was the uncertainty of of knowing that introduced the dip. And what they had to solve was giving you a believable number that was close enough to reality about what percentage of the ads worked and which ones didn't. So you could buy with confidence. Because if you're buying and your ads aren't working, you could boom, go out of business real quickly. And so, and so, so the, it's this level of precision and measurement that is going to be, and all this needs to be built. Like, like, and new companies are going to build it. It's a huge opportunity.

• 31:58Andrew Sharp?

  And it's easier for new companies to build it is the key point here.

• 32:02Ben Thompson?

  Well, it's easy for new companies to incorporate it. So I think there's two opportunities. Number one is new companies that do stuff existing companies do, but they do it all with AI. And so they're just, and they're going to be very disruptive from the low end. Then number two, there's the framework companies, the, the, the one, like the measurement companies, the ones that actually give you the tools to know what's working and what isn't. And those companies will benefit to some extent from the new companies. But they're the ones that will help carry existing companies over the AI finish line, which I don't think will be in 2025. But will be, you know, down the road.

• 32:37Andrew Sharp?

  Okay, um, well, I just want to clarify for the record that I do not wear penny loafers. And I will not be embracing that bit in the future on this podcast.

• 32:48Ben Thompson?

  That's, that's what you think.

• 32:50Andrew Sharp?

  I don't know where that came from, but I'm not a penny loafers guy. Uh, any final thoughts or should we move to TikTok?

• 32:56Ben Thompson?

  I don't even know penny loafers is, is an all spice sort of. Whatever they're called.

• 33:00Andrew Sharp?

  I think it is Old Spice, not all spice, not old style. This is a fun little variation on the mispronunciations here on the podcast. Well, to keep it moving, Ben, we can turn to the news of the week, which is TikTok. There are several threads to the TikTok story that are just totally unresolved at the time of this recording, including but not limited to the Supreme Court and its ruling on the case that's challenging the constitutionality of the law that would impose a ban on TikTok as of Sunday. There are several reports that PRC officials are looking into Elon Musk either as a buyer of TikTok

• 33:42Andrew Sharp?

  or someone who could potentially broker a solution with the US government. Donald Trump, the soon to be head of the US government, is reportedly considering some kind of executive order that would attempt to stay enforcement of the law's provision that bans app stores from hosting TikTok. And then TikTok itself is reportedly planning to shut down the app on Sunday, January 19th, if it receives an adverse ruling from the Supreme Court later this week.

• 34:11Ben Thompson?

  And by the way, I'm pretty sure that I don't think Trump can issue an executive order directly on doing a congressional action. So number one, he could try. There'd be a delay till a court ruled, but I think that would probably happen pretty quickly. I think people are getting too caught up in the legalese here. The law does not ban TikTok. It bans the app stores from hosting it from and from Oracle from from sort of hosting the data. What what I think could potentially happen is TikTok is trying to force the issue by saying, we're just going to end the service. They don't have to end the service. It could continue working for existing customers. And so some sort of action, even if it got struck down by the courts, could be more a function of TikTok deciding to wait.

• 34:55Ben Thompson?

  And there could be some sort of injunction in this regard, too, that lets Oracle continue hosting the data, whatever they're doing, X, Y, Z. So I would I would say with this specific point, with a lot of these things, it's easy to get hung up on specific details. When there's a lot of moving pieces and like decision making that that could be that that could be at play. So.

• 35:16Andrew Sharp?

  Yes. Well, and in lieu of bald speculation in terms of what may or may not happen over the next week on any of those fronts, we can talk in broad strokes about some of the logic here. And we got a two part question from Said. He says, with the US quote unquote ban of Tik Tok fast approaching, can Ben quickly go over the arguments for the ban and why he supports it? What do you think?

• 35:41Ben Thompson?

  Well, I mean, I made my case back in 2020 and I haven't really revisited it. I mean, it's a it. I'm sympathetic to the general idea. The US is a free market like we're not China. There is a free speech. I don't buy the free speech component from a constitutional perspective, just because you can go to other forums. And also, there is Supreme Court precedent about sort of a deference in terms of national security concerns on these sorts of issues, particularly if it's not, you're not directly muting Americans, you're, you're, you're taking one of their many platforms that they could use. I do think it's worth acknowledging, like, yes, you could tell somebody to another platform. If you have a million followers on Tik Tok,

• 36:22Ben Thompson?

  it's not the same thing. Which, by the way, goes back to our moderation discussion. I think an underappreciated bit of, oh, just started new account. Well, if you, there's real damage that comes from you getting banned and losing a huge following and having to sort of, sort of rebuild it. I mean, I have a friend of mine on Buck's Twitter, you know, got investigated by the police for, you know, being mad at the refs one time. And he's still like thousands of followers below when he had to make.

• 36:48Andrew Sharp?

  And hey, I followed his new account. I'm one of like 800 people who follow him now. Great follow. But yes, it's a good point. I mean, it's not literally an economic taking, but in effect, it sort of is because you spend a lot of time on accruing a following that has value.

• 37:09Ben Thompson?

  Taking, it's just not priced. So we kind of ignore it, right? Which, by the way, if you want to zoom out to like our overall like spreadsheet critique, what can be measured is actually a. Really compelling example, right? If you have 10,000 followers, 100,000 followers, your account gets banned. There's because it's not priced, it's underrated in the discussion, even though the value is actually exceptionally high. Like having a hundred thousand dollar, 100,000 followers is you're you have a huge opportunity in real leverage. Like that you can manifest into other things, but because it's not priced, it gets ignored. Which is a great example of how spreadsheet thinking can sort of lead you astray.

• 37:49Ben Thompson?

  Anyhow, that's a digression. Uh, to me, the TikTok thing is very straightforward. I, I, the data thing, yeah, I, I, I'm not. I'm generally less worried about data than most people in general. I, you know, okay, what are you gonna blackmail someone by showing they watch, you know, they watch a lot of, uh, you know, uh.

• 38:04Andrew Sharp?

  League Pass?

• 38:06Ben Thompson?

  Yeah.

• 38:06Andrew Sharp?

  I don't think that's where you're going.

• 38:08Ben Thompson?

  But the, the, you know, is there location tracking sort of things? Um, you know, there are concerns, I'm not dismissing them. My bear concern is it's, it's a, you're giving a foreign power that is an adversarial foreign power in multiple respects, economically, militarily, potentially, and ideologically. Uh, a direct sort of pass to the hearts and minds of the American people. To me, that's insane. We want to let the Soviet Union control a television network in, in the Cold War.

• 38:36Andrew Sharp?

  And this is a lot more powerful than a television network, which is part of the issue here.

• 38:40Ben Thompson?

  Especially with the targeting and the lack of tracking, right?

• 38:42Andrew Sharp?

  Yeah.

• 38:43Ben Thompson?

  Could China put its thumb on the scale for, uh, some little congressional race? No way to know. You would never, you would never sort of know. And I documented years ago, in the context of the Hong Kong protests, and when the whole Daryl Morey NBA thing happened. China was clearly controlling the algorithm. Well, you could search for, in my evidence in that case was you could search for every single NBA team and get NBA highlights, except for the Houston Rockets. There was zero.

• 39:09Andrew Sharp?

  Right.

• 39:09Ben Thompson?

  And like, again, maybe in the grand scheme of things, not that important of an example, but a blatant.

• 39:17Ben Thompson?

  Queer, there, there is a thumb on the scale here about something that is important to China. And it's just nuts to allow this. And, and what the, the problem is, and the frustration is, it would have been painful in 2020 to do this. It's gonna be a gazillion times more painful now as it's become larger and larger. And you're harming more and more. I'm very sympathetic to people on TikTok and the users and the creators.

• 39:40Andrew Sharp?

  I am too. I mean, it circles back to part one of the podcast because it's this new platform. And there have been businesses and careers basically built around this platform that will now cease to exist. And you're just punishing a much bigger group of people five years later.

• 39:56Ben Thompson?

  And the competition stuff really bothers me like TikTok has, has been phenomenal competition for Facebook. It's put their rear end in gear. And by the way, Facebook's much better positioned to capitalize on it because of the competition than they would have been in 2020. The likelihood if, if, if, you know, it's a bit tautological, but like China refusing to let ByteDance sell TikTok, which has tremendous economic value, does, it does kind of make the point that like, I mean, it's kind of unfair, but it does sort of make the point.

• 40:26Andrew Sharp?

  It's hard to say exactly what's happening, but it does seem like CCP officials are the ones who are now entertaining some sort of deal.

• 40:35Ben Thompson?

  That's why, that's why I don't, I don't want to say that categorically because the logical way to play this for ByteDance is to insist you're not selling it and to push it to the last minute and only sell at the, at the very last minute. So, so I, I don't want to categorically say that this proves, you know, the Chinese government uses it as a unique asset until we're like a few months down the road and it's well and truly gone.

• 40:59Andrew Sharp?

  Well, that, but also alongside that, the idea that the people who are deciding and the people who are potentially brokering some sort of deal are not ByteDance executives, but are in fact, party officials in Beijing, that would be proof if in fact that is happening. Um, or would lend credence to the concerns that people have had for several years now.

• 41:19Ben Thompson?

  I mean, what, if you want to go against the concerns, I wouldn't say that it's not that I don't believe American people could be propagandized. It's that I think that China. Chinese are you would be uniquely terrible at trying to propagandize the US, the US population. It takes Americans to propagandize Americans and and so maybe there's a bit where just there's an aspect where the concern is maybe somewhat overstated in that regard. And maybe that is manifesting in how they're playing this. ByteDance maybe sees value and says, hey, the Chinese government is saying we can't do it. Wrong play, right? We saw this when they they tried to put up that message last summer when it was being or last spring was being debated in Congress. They popped up a pop up to everyone on TikTok saying, call your representative, do XYZ. Totally the wrong way to play it.

• 42:02Andrew Sharp?

  Send Congress into a panic.

• 42:04Ben Thompson?

  That's right, that's right.

• 42:05Andrew Sharp?

  Seventeen year olds besieged both chambers.

• 42:07Ben Thompson?

  You cannot overstate the level of lack of cultural understanding between China and the US. It affects everything. Like there's, there is this, um, uh, you know, this comes up in the, the sort of, uh, little, little red. But why don't we people go write a notebook? It's literally Little Red Book, uh, Xiao Hongshu, uh, this, you know, the app that all the TikTok refugees are going to. I think the whole thing, number one is hilarious. Um, you know, let's, let's abandon TikTok by going to a literal Chinese app. But number two, you know, I, I linked to this story from, you know, Chinese state run media saying, oh, this shows the American people are opposed to their government. They don't like their policies.

• 42:47Ben Thompson?

  And you have to read between the lines and I've been on this side of the world for a long time, like, like to, to appreciate the depth of misunderstanding that undergirds that piece. The problem with these cultural misunderstandings is there's baseline assumptions that don't even occur to one side or the other. And believe me, I learn this all the time in terms of like, you know, interfacing with my family and things along those lines, right? It's just, it's a completely sort of different view of the world. And you have things like, what are the real challenges in foreign relations between China and the US? Is the Chinese are.

• 43:25Ben Thompson?

  In these sort of discussions, everything is implied and you can't believe the actual words. And, and so, you know, I've, I've, I've talked about like my favorite, one of my favorite things about the Chinese language is there's these things called a chungis, which are like groups of four characters that are like common sayings. The best way to insult someone is to use a chungie and drop one of the characters. And the character that you dropped is what you're saying they lack. So if there's like a chungie that says, oh, he's, he's handsome and trustworthy and wears penny loafers and XYZ, you drop the honest one and it sounds like you're giving a compliment and it's actually like this massive insult because you're implying that they're a very dishonest person, right?

• 44:06Ben Thompson?

  That's how like, so, so there's this, all the, that is like a stand-in for the, the communication generally. And so the US does not get that. So they actually like take the, take the Chinese at their word about different stuff and completely miss the, the subtext of what's going on. Meanwhile, the Chinese assume that the Americans are lying because why wouldn't they be? And they're saying all this stuff, oh, we care about human rights and the climate and XYZ. And they're like, we get it. That's all a lever to get your actual priority concerns. And sometimes you're just like, no, we actually do care about this. The US is very black and white. That's one of the problems with the whole Taiwan sort of thing is the Taiwan is a situation that exists in gray and the US mindset can't stand it.

• 44:45Andrew Sharp?

  Wants to make it black and white.

• 44:47Ben Thompson?

  It wants clarity. And it's not a situation that you want clear because the, there's no good outcome.

• 44:53Andrew Sharp?

  There's no clear resolution on Taiwan. There's no question about that.

• 44:56Ben Thompson?

  You push for a resolution, you're going to get a resolution good and hard. It's not going to be necessarily the one that you want. So this undergird sort of everything. So you see this, so they're like, oh, and the sort of telltale sign, the laziest media story is when you search, you go to Twitter, you search, you find someone saying something that supports your story. You're like, Twitter user XYZ said, said this, they use that as evidence of like this whole wrong thing. The Chinese state media is searching on Twitter, finding someone who's like, yeah, the US government, they think it's propaganda. We don't believe that. We want to go to China. It's like, okay. Are all these users giving a middle finger to the US government about TikTok?

• 45:34Andrew Sharp?

  Mm hmm.

• 45:35Ben Thompson?

  Yes, they are. What is hard to grok if you're not in the US is that is the US.

• 45:43Andrew Sharp?

  Freedom in action, baby.

• 45:45Ben Thompson?

  That's right.

• 45:45Andrew Sharp?

  Here we are.

• 45:46Ben Thompson?

  Our whole birthright is about giving the middle finger to the government and they can't do anything about it. This goes back to the like, the whole ban, the part of the whole context of the whole ban Trump from social media in 2020. That actually, I think even hard for Europeans to understand is this idea that in Europe, the government is always on top. And so the government determines what speech is allowed or not, and corporations operate in that context underneath the government. In the US, corporations are an equivalent institution to the government. The government can't tell them what to do. They can't, in the First Amendment context, it's not just that they can't say what they can't say. They can't say you can't moderate because it's your, it's their own platform. They can do what they want.

• 46:32Ben Thompson?

  The, the idea is that the freedom of speech is above both. And the government operates under it and the companies operate under it. And, and that can go in either direction. They can allow free speech, they can disallow free speech, and the government can't tell them to do one or the other. And it's this, it's like, where in the stack are they? In the US, they're on equivalent things. And so part of the case was, well, there is a tradition of corporations acting as one of these institutions as a power broker. As like, when you talk about the balance of powers in the US constitution between the executive branch and the judicial branch and, and the executive legislative branch. Actually, the US as a whole is a balance of powers. Like, like, like the, the, and.

• 47:14Andrew Sharp?

  Well, and look, I mean, you made the point on, on the Xiaohongshu thing. It like, I was actually jealous that I didn't think of that before Bill and I recorded Sharp China earlier this week. The surge of young people going to Xiaohongshu and crapping all over the American government is such a great testament to the American system.

• 47:32Ben Thompson?

  No, it like, it is, they're like, oh, look at these people don't listen to American propaganda.

• 47:38Andrew Sharp?

  It's all failing.

• 47:39Ben Thompson?

  It's like. You are getting, you're getting propagandized so hard right now and you don't even realize it, right? That's effective propaganda.

• 47:47Andrew Sharp?

  Well, and that's the concern.

• 47:49Ben Thompson?

  No, a bunch of US citizens. Oh, no, Xiaohongshu is screwed. Like, like, so we get like, all these citizens going online and bitching about the US government is this incredibly powerful testament to the American system that is like, it's precisely because the Chinese don't even see it is how effective it is. People going on and like you and me making it explicit, that's not effective. And everyone sees that's propaganda. This is real propaganda. It's in the water. It's not like you're, it's not a billboard. It's in the water. And then, and, and all these people going on Xiaohongshu and saying, hi, you know,

• 48:30Ben Thompson?

  nice to meet you, ni hao, blah, blah, blah. It is one of the most effective American propaganda actions in ages. It's amazing.

• 48:38Andrew Sharp?

  Right. Well, and the juxtaposition is really powerful because obviously on one hand, you have Americans who are now free to curse out our government and publicly pledge their allegiance to China and they'll suffer no consequences. But a Chinese digital media outlet earlier this week, I think it's PC Online, they were talking about the implications for Xiaohongshu and the influx, the influx of Americans, because just for people who don't know, mainland apps in China, if they are marketing abroad, they'll typically develop an entirely separate platform for international audiences. Xiaohongshu did not do that. It did not intend to, it didn't really have

• 49:17Andrew Sharp?

  ambitions to expand internationally. And so the influx of Americans was described as a Damocles sword hanging over the company. And the outlet said the risks here far outweigh the opportunities because there's just going to be immense pressure and possibly consequences from the government if they're not censoring all these Americans sufficiently.

• 49:39Ben Thompson?

  No, this is why it's going to end very soon. My prediction is within a week. Um, maybe it'll take a little bit longer because the, the risks to Xiaohongshu are astronomical. They, like, they, if they're first, they're gonna, they might try to moderate, their moderation is gonna be overwhelmed. This is an underappreciated aspect of censorship, by the way, and this actually ties back to our discussion last week. Censorship is at its most effective when people self censor. It's like that that is how you get scale from censorship. Yeah, you could have the great firewall. Yes, you can force all these social media companies to take people's accounts offline. But you add an, I don't want to be banned. I don't want to have that worry like, am I going to get trouble from the police? Or am I going to lose my thousand followers? Right? And so people self police.

• 50:23Ben Thompson?

  And that is how you actually get censorship at scale is by activating people's self preservation instinct. And you get self censorship. Guess who is not going to self censor?

• 50:35Andrew Sharp?

  Americans.

• 50:36Ben Thompson?

  The people giving the middle finger to the government by using Xiaohongshu. And so there's a bit where even if they try to have some sort of moderation apparatus, it's like it's going to go sideways. They're like, it's all, yeah, they're probably institute. They might withdraw from the US app stores. Or the thing I didn't mention, which they'll probably do is institute. You need a Chinese phone number to register and they'll force everyone to put in the phone number. And that will cut everyone off and.

• 51:00Andrew Sharp?

  Test the dedication of the TikTok refugees, you know? Maybe you find a way to get a Shanghai phone number.

• 51:07Ben Thompson?

  It's not, it's not easy. I would, I would advise against that.

• 51:13Andrew Sharp?

  Well, and to the point on Xiaohongshu. I mean, the creator of ByteDance no longer runs that company and disappeared for a while because ByteDance was censoring.

• 51:25Ben Thompson?

  No, they got called to the carpet. I wrote about this in the TikTok war. Yeah, they got called to the carpet for, and in this case, it was mostly because there are people looking at too many pictures of. What did we call it?

• 51:38Andrew Sharp?

  Scantily clad League Pass highlights, absolutely.

• 51:41Ben Thompson?

  Yeah, so.

• 51:42Andrew Sharp?

  But.

• 51:42Ben Thompson?

  I think the whole thing's very, I think the whole thing's very funny. I think, you know, I think the, this is like, you don't want to get in a propaganda war with the US. Again, because the, the problem with so much communist propaganda is it's way too literal. It, it, and US soft power is, this is US soft power. It is, it is our citizens giving the middle finger to the US government. On a Chinese app, colonizing it and do it in the process being received. Oh, it's so great. Yeah, the US government's bad, blah, blah, blah. And, and, and the entire subtext here is look at us exercising our freedoms.

• 52:24Andrew Sharp?

  Wouldn't it be nice if we in Beijing could do that? Yeah.

• 52:27Ben Thompson?

  And hey, the more exposure for US people to clean streets and, and, and functioning infrastructure, the better. So maybe it could be a two-way win, at least as long as it lasts.

• 52:37Andrew Sharp?

  No, absolutely. And I actually think it's a really cool example of cultural exchange that China has systematically prevented for the last 25 years.

• 52:46Ben Thompson?

  Well, this is the, the last thing about the TikTok thing that I didn't get to. China started this, like this is a window into what we lost with the Great Wall or the Great Firewall. Uh, I call it the Great Wall all the through. Great Firewall is obviously what I'm referring to. And by the way, there is a very strong, leave aside the persuasion issues, the data issues. They block all our consumer internet companies. We should block theirs. Like you can't have a, this is a whole problem with our whole trading regime is yeah, we're pro free trade. But you have, like, if you don't have a tit for tat retaliation system and one side blatantly violates all their parts of it, you're going to end up in a bad place.

• 53:27Ben Thompson?

  This is the part that, that, and, and so like, just from a pure sort of, uh, trading perspective. It's very, this is why it should have been done years ago. Like, like you, you just made it way more difficult by waiting until now.

• 53:40Andrew Sharp?

  Well, and speaking of borders, there was a part two to Said's email. He writes, "To the extent TikTok is considered problematic because of a security, political or cultural impact by a foreign country, large amounts of data accessible to a foreign country and a vital communication channel being owned by a foreign country. Can't these same reasons be used against US tech companies operating in foreign countries? Based on the reasons given for this ban, does the ban of US tech companies in China require reassessment?" I have some thoughts there, Ben, but do you have any reaction to that question?

• 54:16Ben Thompson?

  I mean, I don't understand the part two of the question. I think, you know, China's banning of US tech companies has been tremendously successful. I mean, number one, they limit, like, they control the discourse, they can institute the censorship sort of apparatus, maintain stability, have people self censoring, and they also developed this entire software ecosystem that rivals the US because they were, they were protected. Like, it was, it's one of them, you know, setting aside, just from a purely analytical perspective, setting aside the morality of the whole question, it's one of the smartest things that any country did. China's the only entity that stands a potential competition and opposition to the US from a tech perspective because of the Great Firewall. And every single person

• 54:59Ben Thompson?

  in the US that didn't see that back then, including myself, it should be a reminder, there's really important stuff that you can miss as it's happening, as you're so sure it's gonna fail. Bill Clinton, they're trying to nail Joe to a wall. Yeah, guess what? Totally wrong. Totally wrong.

• 55:17Andrew Sharp?

  We need to work on your Clinton impersonation going forward.

• 55:20Ben Thompson?

  Oh, I wasn't trying to impersonate at all. I can keep with it. And so, yeah, so, the answer is to, so my assessment of the Great Firewall is it was brilliant. Again, from an analytical perspective, setting aside the moral issues. Yeah. So, I'm not reassessing anything. And by extension, the fact that no one else did it to date is why, you know, is this a long-term risk that you're setting this precedent? Sure. Are any other companies going to have it in them to block US services and develop their own? No, it's too late. They missed, they missed the boat. And like, there's this, it is analogous to the chip

• 56:03Ben Thompson?

  sort of stuff, like the, you know, the- Is all the chip band sort of issues? Is there a bit where in the long run, you're really risking the industry? And not just China developing its own industry, but then selling abroad? Yes. Do I have real problems with the new controls announced this week? Absolutely. I think they go too far. It changes the paradigm from trying to stop China to instituting a permission structure on all of tech, which I think is a very, very bad and problematic shift. And is much is gonna be more destructive in the long run because now you're treating everyone as an enemy by default. I don't think that is a wise choice at all. But at the end of the day, the US does still control the entire chip industry, right?

• 56:48Ben Thompson?

  Like, and there's, I think that there's, that is the analogy in this case to US tech companies.

• 56:53Andrew Sharp?

  Well, yeah, and I also think that like a threshold issue is just the nature of the Chinese government and the difference between the US government and the Chinese Communist Party in terms of their ability and intent on controlling American tech companies. I mean, the CCP owns a 1% stake in a ByteDance subsidiary, but has a golden share on ByteDance's board.

• 57:16Ben Thompson?

  Which, by the way, this was all known and I wrote about it in 2020. Like, this, all this, that's the, whatever, this is how the US works. We wait till the last minute and like, and when it's much more difficult and costly. But like, there is an aspect of in 2020, it was still, Trump supports this, so it must be wrong. You know, that I think drove a lot of decision making.

• 57:36Andrew Sharp?

  No, but you made the case in 2020 and it was eye opening to me because I was one of the people who was like, what the hell is Trump talking about here? There was a rally that was poorly attended. Now we're banning TikTok and it was eye opening back then for me to read the case and read sort of what TikTok can do. And also, again, the CCP has voting mechanisms that allow the party to override majority stakeholders.

• 58:03Ben Thompson?

  And the voting mechanism was a cop.

• 58:04Andrew Sharp?

  They're also required by law to comply with state intelligence work. Yeah, exactly.

• 58:07Ben Thompson?

  And by the way, you could make the case, Said, that the US can just tell, at the end of the day, and this goes back to the censorship thing, right? We're all parsing. They actually force them to do XYZ. A very valid takeaway is that actually the US does tell tech companies what to do and it doesn't matter what laws are there. It's still the case that it happens. And you go back to to things like the Snowden revelations and all these sorts of pieces. That, yeah, the US has just as much control over its tech companies as China does to theirs. And my response to that is I'm a US citizen, so I'd rather we be in charge than them. Like that, I there is that you can't escape that that sort of reality.

• 58:42Andrew Sharp?

  That, but also the CCP and PLA affiliated hacker groups. They have hacked not only American companies, but also the US government itself over the past couple of years. And the hacking problem, I think, is far more extensive than the general public realizes. But the CCP has also been actively working to undermine US interests abroad for years now. And so, like, given that, it would be unbelievably naive to think that the CCP wouldn't eventually try to use TikTok to similar ends. And those concerns don't exist for a company like Meta operating in the EU. So like, I just don't think it really is an apples to apple situation as far as Said's email is concerned.

• 59:27Andrew Sharp?

  But there are certainly areas where the government has tried to exercise control. Meta is not obligated under US law to comply with those attempts.

• 59:37Ben Thompson?

  Yeah, but I would, my addition would be even if it happens in fact, at some point you have to pick sides.

• 59:45Andrew Sharp?

  So that's fair.

• 59:48Andrew Sharp?

  And that actually is a really solid place to land on all this. Because I think there's people who want to go back and forth and it's just like, well, in principle, this is a matter of national security. And sometimes that wins out at the end of the day.

• 1:00:05Ben Thompson?

  Yeah, no, I think that's right. I mean, I think this Joseph, this Joseph email actually gets to one extra point. That is a good way to wrap this up.

• 1:00:12Andrew Sharp?

  Okay, so Joseph says, "I love you guys and agree with 99% of your takes. So I feel bad writing in only to challenge points, but I can't resist. I'm a bit surprised."

• 1:00:23Ben Thompson?

  Don't feel bad. And 99% is too high. You need to lower that.

• 1:00:27Andrew Sharp?

  Yeah, and I always appreciate some feisty emails. "I am a bit surprised by Ben's consistent support of the TikTok ban. Doesn't this violate his 'you're not gonna out-China China' rule? Especially now that he's trying to be more consistently on the free speech side of things."

• 1:00:43Ben Thompson?

  Oh, that's unfair. I've been extremely consistent with that one very narrowly carved out exception. I don't think this more consistent is like I was wishy-washy to date. I was writing articles and getting a lot of flack for them, going back the entire run of Stratechery, very consistently about free speech as the top priority.

• 1:01:02Andrew Sharp?

  So it's not newfound?

• 1:01:03Ben Thompson?

  So let's not, yeah, let's not, let's not overstate, like, and if you go back and read what I wrote with the Trump off social media, it was in the context of this is pro-free speech. Corporations have free speech rights also. And so, like, I just, that's, that's a little, a bit of an unfair characterization. I'm gonna put my record forward on this point.

• 1:01:26Andrew Sharp?

  Okay, so do you have an answer for Joseph beyond needling him on his word choice there?

• 1:01:34Ben Thompson?

  All right.

• 1:01:34Andrew Sharp?

  What do you think in general?

• 1:01:36Ben Thompson?

  No, it's a, it's a, this is absolutely a fair point of pushback. I think, I think it is correct. Number, number one, I would say, I don't think this is a free speech case per se, because people can go elsewhere, to which Joseph ought to say, "Well, when people get kicked off social network, they can also go elsewhere." So like, there is a hoisting myself on my own petard on this bit. There is a, like, the reality is, everything is a trade-off. This is, it sounds like a cop-out answer, but it's true. But this whole, this, this is to support this ban in 2020. And honestly, the reason why I didn't write more about it, I'm like, look, I made my case. It's 5149, so I'm not gonna like, spend a ton of political capital going down with the ship on this.

• 1:02:20Ben Thompson?

  But it is, it is sort of what I think, it was very carefully considered.

• 1:02:23Andrew Sharp?

  5149 for you, that is. It's, it's a close call for you.

• 1:02:26Ben Thompson?

  For me, just because, yeah, like, free markets matter. And like, the, the, the free speech... Is not just a legalistic thing. It is all these people on this platform and it being a meaningful way to communicate. This is an area and maybe I, maybe you want to say you were wrong to say it was always number one. Well, no, it's not always number one. Free speech jurisprudence in general, it's not always absolute. There are exceptions that are carved out by the Supreme Court. One of those exceptions that's carved out by the Supreme Court is national security. And, and this is one where I would align with Supreme Court precedent in this regard, which is, I regret this. I don't like it. I acknowledge it's a violation of these principles.

• 1:03:08Ben Thompson?

  I just articulated last podcast, but I have looked at all sides, weighed all the issues, considered not just the issues today, but in the long run, and come down very narrowly on this. I've given it strict, this is a sort of a, a, a.

• 1:03:25Andrew Sharp?

  Strict scrutiny, here we go.

• 1:03:26Ben Thompson?

  I've given it strict scrutiny and come down on the fact that the national security concerns do trump. No pun intended. Uh, my, my principles, if you want to say, oh, you just gave this whole thing. You're not wishy washy. Well, okay, that's fine. Um, I will accept that. The, the reality is.

• 1:03:45Andrew Sharp?

  That's part of being an adult is balancing competing priorities and principles.

• 1:03:49Ben Thompson?

  Yeah. So Joseph, you child.

• 1:03:53Andrew Sharp?

  No, we love you, Joseph. Thank you for agreeing with us 99% of the time. Um, yeah, I look, here's the thing, just in broad strokes, Tik Tok is where an entire generation of Americans gets their news. And the nature of social media platforms is such that control over the algorithm and the ability to either amplify or suppress certain viewpoints is an unbelievably powerful tool.

• 1:04:16Ben Thompson?

  Right. And again, which by the way, has been manifested. I, it's not just I showed it back then. There's been studies since then that, that searched on various terms. And the reality is there is a significant thumb on the scale about anything China related right now, just by default. And that's even before we get into some sort of potential conflict or, or things along those lines.

• 1:04:32Andrew Sharp?

  Exactly. It, it's the hypothetical ability to wield this weapon that is just insane.

• 1:04:39Ben Thompson?

  Right. And by the way, well, that's why I want to emphasize it is happening now. Because there is a danger, and I'm going to like contradict myself, where we. Do policies based on hypotheticals, which is generally a very bad place to be, right? Well, you get to go back to the COVID example. You can hypothesize all potential of these bad outcomes and then make policy in response to the hypothetical, which are bad policies and you should have actually waited for more proof points and better understanding to make very strident sort of decisions and policies that you're stuck with for a very long time. So I don't like legislating against hypotheticals. That's why I do think it matters. There is evidence, there is some degree of thumb on the scale already. And then that gives more meat to the hypothetical.

• 1:05:22Ben Thompson?

  And again, it is, it is a very close call.

• 1:05:25Andrew Sharp?

  Vectors where the CCP has been actively malign to US interests across the last several years.

• 1:05:33Ben Thompson?

  There is a bit about the US needs to take China more seriously, right? Like, that's part of it. I take China very seriously and maybe you want to say I'm biased because of where I live. I acknowledge that every time I write about this because that might be the case. And you listening to it and your 99% acceptance rate should, that's why you should decrease it. Because there is an inherent sort of, I think it gives me better perspectives. And it also gives me a biased perspective, which is, which is for you to sort of figure out and me to acknowledge.

• 1:06:00Andrew Sharp?

  Yeah, well, and as far as taking China seriously, I think to Joseph's point, the impulse to be uncomfortable with this law is natural and very American, consistent with the US tradition. But the reality is there.

• 1:06:14Ben Thompson?

  Yeah, not liking ambiguity. And I, by the way, am very uncomfortable with the law. So that's why I did write.

• 1:06:18Andrew Sharp?

  Exactly. And it's also, the American system can tolerate a lot of different dissent. But you look at like with Twitter even, if you go back to COVID and the way Twitter handled some of the censorship issues there and certain things that were suppressed, like that distorted the conversation a couple of years ago. And I wonder if Elon was running Twitter a couple of years ago, whether certain policies would have been different because there just would have been more open discourse around that. And I offer that strictly as an example of where algorithmic control is really, really powerful and can have real world consequences on the democratic. Process and our policies and then obviously.

• 1:07:02Ben Thompson?

  This is a good example of like, you know, you could take the hypothetical bit and say, well, your concerns about free speech. This is, you know, people would push back on this in the, in the 2016, 2017 era. Your, your concerns about free speech are hypothetical, right? And, uh, we have, and it turned out that's why we go back to the COVID example. Because hypotheses became reality and that should influence your thinking and, and your changes. And by the way, am I, to go back to Joseph's email, am I demonstrating inconsistency? Absolutely. Like, well, you know, consistency is the hobgoblin of, of small minds or whatever it is. We're, we're to the big mind podcast here.

• 1:07:40Andrew Sharp?

  We're adults here. Yeah. Well, and there's.

• 1:07:43Ben Thompson?

  But it's fair, it's fair to call me out. It's absolutely fair to call me out. I've given Joseph our time, totally valid email, totally valid points.

• 1:07:50Andrew Sharp?

  I podcast about this every week on Sharp China. China has done a great job at taking advantage of the US freedoms and the US led system to create and exploit a variety of vulnerabilities across private industry. And banning Tik Tok will not be the last time that we have to make trade offs between pure freedom and security, pure free market principles and the general welfare of society.

• 1:08:15Ben Thompson?

  But we should keep getting called out for the inconsistency because it is, you could say people that are concerned about.

• 1:08:21Andrew Sharp?

  Should be evaluated on a case by case basis.

• 1:08:23Ben Thompson?

  Yeah. It's like, like, look, no, we're, we care about free speech. We're just, we're, we're thinking about all the details and thinking it through. And that's, that's actually totally valid. I, on that one, fall on a different spot and I've fallen in an even more extreme spot than I did even four years ago, for the reasons I articulated last time. But, uh, that's why I am respecting and I'm open to the argument because this stuff's not easy. One more bit on is not out China, China. That applies not just to the US, that applies to other countries as well. They're not going to ban the US companies because they're not going to out China, China, right? Like the, and so there is a certain amount of, of, uh,

• 1:09:01Andrew Sharp?

  You gotta want it to ban US countries.

• 1:09:04Ben Thompson?

  That's right.

• 1:09:05Andrew Sharp?

  US companies. Well, Ben, I've enjoyed the ride here and whether TikTok is around or not by next week, we will be back. We will have an episode up Monday afternoon. Getting back to regular schedules around here. Until then, enjoy the weekend and I will talk to you soon.

• 1:09:25Ben Thompson?

  Talk to you later.