Speaker 1: Also media.
Speaker 2: Hello and welcome to Better Offline. I'm your host ed Zeitron.
Speaker 2: Back in March of this year, MIT economist, their own
Speaker 2: some Oglu and MIT Sloan Simon Johnson published a paper
Speaker 2: called the Urgent Need to Tax Digital Advertising, where digital
Speaker 2: advertisers will be levied with a flat tax of fifty
Speaker 2: percent on all revenue above five hundred million dollars. And
Speaker 2: today I'm joined by Drone to walk through it. Daron,
Speaker 2: thank you for coming on.
Speaker 1: Thank you, Thanks Ed.
Speaker 2: It's my pleasure, so walk me through the idea. It
Speaker 2: seems pretty simple, but maybe there's more nuance to it.
Speaker 1: Well, it's very simple to implement, it's very simple to explain.
Speaker 1: The question is why, you know, why do something like this?
Speaker 1: You know, after all, who doesn't love something free? And
Speaker 1: we're getting a lot of free things because the entire
Speaker 1: our online ecosystem is monetized via digital ads. The issue is,
Speaker 1: I think this ecosystem creates a number of problems which
Speaker 1: are set to get worse.
Speaker 3: With AI right.
Speaker 1: The most obvious of those is something that's been discussed
Speaker 1: quite a bit over the last few years, which is
Speaker 1: that monetizing via digital ads means that you are going
Speaker 1: to encourage platforms to collect more and more data about people,
Speaker 1: and this creates a much more intrusive, lower privacy, and
Speaker 1: potentially distorted sort of system.
Speaker 3: Right.
Speaker 1: The second, perhaps corollary or separate thing which has started
Speaker 1: Reach receiving more attention, is that this also means you
Speaker 1: want to make sure that the eyeballs are glued to
Speaker 1: the screen, which your large screen, small screen, and that
Speaker 1: itself might generate a lot of other problems, including perhaps
Speaker 1: mental health problems, because you try to get people to
Speaker 1: stay on the platform by inducing strong emotions envy, jealousy, anger, outrage,
Speaker 1: and so on and sort of it creates a very
Speaker 1: different type of social environment than we are used to,
Speaker 1: with widespread negative consequences. But I think the one that
Speaker 1: I'm most worried about is that this reduces competition. It
Speaker 1: is impossible today for any service by a newcomer to
Speaker 1: come in and say, Okay, you're going to get this
Speaker 1: from Google, Facebook, Instagram for free, and I'm going to
Speaker 1: provide higher quality content for which you have to pay
Speaker 1: a subscription fee or something else. Especially difficult because newcomers
Speaker 1: are not going to have the network. There's going to
Speaker 1: be uncertainty about their quality. So it really cements the
Speaker 1: system where everything is going to be monetized via digital ads,
Speaker 1: and that's going to discourage the entry of new products,
Speaker 1: new services, and especially new technologies. For example, everybody worries
Speaker 1: about what social media and other online platforms and AI
Speaker 1: implies will imply for democracy. Well, something that actually creates
Speaker 1: more pro democratic conversations, higher quality content, that's going to
Speaker 1: be very difficult to get off the ground today.
Speaker 2: Right, So how does this tax actually change the incentive though?
Speaker 1: Well, I think the main way in which it changes
Speaker 1: the incentives is that it makes it possibly more likely
Speaker 1: that both existing platforms and new platforms will now say,
Speaker 1: let me experiment with new products that are higher quality
Speaker 1: for which I can build a clientele via subscription fees
Speaker 1: or other things. Because if I get one hundred million
Speaker 1: dollars via digital ads, half of it is gonna go away.
Speaker 1: If I can get that money for I have subscription fees,
Speaker 1: that's good. It's no longer so inferior to doing it
Speaker 1: via digital ads.
Speaker 2: But I think one of the things that concerns me
Speaker 2: with it, or maybe it's less of a concern and
Speaker 2: more just the after effect will be is the people
Speaker 2: are used to not paying for social media.
Speaker 1: That's why this needs to be high. You know, if
Speaker 1: this was a ten percent tax, it wouldn't make so
Speaker 1: much of a difference. So in some sense, when I
Speaker 1: mentioned ecosystem, I was intending to imply by that both
Speaker 1: what the offering side the platforms are doing and what
Speaker 1: the consumers are expecting. So there's a synergistic relationship between users, consumers,
Speaker 1: and the firms, and you want to change that relationship. Again,
Speaker 1: you wouldn't want to do it if the market system
Speaker 1: was working perfectly and everything was hanky dory, but I
Speaker 1: think there's a lot of evidence that's not the case
Speaker 1: at the moment.
Speaker 2: So and the incentives would be that they just can't
Speaker 2: make that much money off of digital ads, so they
Speaker 2: will have to find new business lines. But could this
Speaker 2: not potentially kill off the idea of the free social network.
Speaker 1: Well, first of all, I think that idea has become excessive.
Speaker 1: If we scale it back, it wouldn't be so bad.
Speaker 1: And in some sense, I think the purpose is to
Speaker 1: scale it back because once everybody expects everything for free,
Speaker 1: that does create a race to the bottom in terms
Speaker 1: of quality, in terms of data protection, in terms of
Speaker 1: you know, new technologies that you know, will actually change
Speaker 1: the face of the kinds of offerings that we get right.
Speaker 2: And it's I remember in the past, we've had companies
Speaker 2: try paid social networks and it just hasn't worked.
Speaker 1: Well. It didn't work because they were up against free
Speaker 1: social networks digitized so it monetized via digital ads, especially
Speaker 1: at a time when people didn't understand what the costs
Speaker 1: of these things were. You know, I think even today
Speaker 1: there are consumers who do not fully recognize the amount
Speaker 1: of data that's being collected about them. So if you
Speaker 1: go back ten years ago, I think both the sort
Speaker 1: of addictive or quasi addictive nature of social media, the
Speaker 1: extensive data collection, and how that data can be used
Speaker 1: both you know, to guide you towards certain products, perhaps
Speaker 1: to behaviorally manipulate you, or perhaps to charge you higher prices.
Speaker 1: All of these things were not completely understood.
Speaker 3: And I think I gain what you mean.
Speaker 2: It's like the latest stage model of Instagram and Facebook
Speaker 2: is so different because when everything's free, you don't really
Speaker 2: have a mechanism to control the customer other than just
Speaker 2: tricking them just continually.
Speaker 1: I mean, I'm not gonna trick is probably wrong. There
Speaker 1: is tricking. There is tricking, it's not everything. So you know,
Speaker 1: when you get an AD, it's useful, you're finding out
Speaker 1: about products. But what is the trade off between how
Speaker 1: much of your private data you want other people to
Speaker 1: have access to versus getting some of those products? And second,
Speaker 1: once people wants platforms have access to that data, what
Speaker 1: is there to stop them from offering some of the
Speaker 1: manipulative products as well as some of the useful products.
Speaker 2: So perhaps the biggest thing, because I just while prepping
Speaker 2: for this episode, I went and did some math, and
Speaker 2: what you're suggesting would kill Meta. Now I'm not saying
Speaker 2: that you should. You're suggesting you should kill Meta. I'm
Speaker 2: just saying that metas for the last four quarters their
Speaker 2: net income was fifty one point three five billion, offer
Speaker 2: one hundred and thirty billion dollars worth of revenue. So
Speaker 2: this would make their business model untenable.
Speaker 3: Is that well?
Speaker 1: First of all, no, I mean, you know, instead of
Speaker 1: fifty five billion, if they make you know, thirty billion,
Speaker 1: it's not the end of the world. I would be
Speaker 1: happy to have a company that is worth thirty billion.
Speaker 3: As would I.
Speaker 1: But the hope is that they would also then offer
Speaker 1: products and services that are higher quality, that are subscription based.
Speaker 1: You know, we know people still you know, pay for
Speaker 1: certain things, although less like Netflix. Netflix is also now
Speaker 1: being sort of being forced to move more in that direction.
Speaker 1: You know, is there a world in which higher quality
Speaker 1: Netflix for which some people pay is viable, where whereas
Speaker 1: you know, some lower quality one financed via you know,
Speaker 1: monetized via ads also coexists. I think those are questions,
Speaker 1: and I think it sort of opens up the market
Speaker 1: system to different, different sort of forces. So if there
Speaker 1: is a paid What's Up that has better security features
Speaker 1: and you don't get these completely unexpected annoying things that
Speaker 1: have started popping up in What's Up, perhaps that's attractive
Speaker 1: and some people will be happy to pay ten dollars
Speaker 1: a year for that.
Speaker 2: Kind of feels like the advertising model is a lazy
Speaker 2: man's business as well, because it doesn't incentivize you to
Speaker 2: make a better product. To exactly, a device is a monopoly, right.
Speaker 1: And why, you know, how did I arrive to this idea?
Speaker 1: My stick for the last you know, two decades at least,
Speaker 1: and especially with regards to AI and the digital technologies,
Speaker 1: is these technologies are extremely malleable. We can develop them
Speaker 1: in different ways. We can have higher quality technologies that
Speaker 1: increase worker productivity, or we can have rot automation lazy automation.
Speaker 1: You can have addictive social media that makes you go
Speaker 1: into your cocoon and you become uninterested in forming bridges
Speaker 1: and engaging in democratic citizenry. Or we can have platforms
Speaker 1: that actually encourage different types of communications and the active
Speaker 1: citizenry that democracy requires. Which ones of those will be?
Speaker 1: And I think since we have gone more and more
Speaker 1: in the automation way and the lay in the sort
Speaker 1: of toxic environment of social media, a change requires new products,
Speaker 1: new technologies, and that means a more open system. So
Speaker 1: the way that I sort of started sort of coming
Speaker 1: towards this idea was, well, what's the barrier to this? Well,
Speaker 1: the fact that there are a few big tech companies
Speaker 1: that can acquire competitors as a barrier, but the fact
Speaker 1: that even if they don't acquire you, they pigeonhole you
Speaker 1: into the same ecosystem in which they exist. And I
Speaker 1: think that's a big problem.
Speaker 2: How do you mean they pigeonhole you even if they
Speaker 2: haven't acquired you as a user, Because.
Speaker 1: To compete against them, you need to also offer your
Speaker 1: products for free, which means the only thing you can
Speaker 1: do is for digital advertising. If you need quality data,
Speaker 1: you can't afford it, You're not going to have an
Speaker 1: incentive to get it. If you need high quality, niche products,
Speaker 1: you know nobody's going to buy them because everybody is
Speaker 1: used to this free free v's and.
Speaker 3: Everything, right, So it creates a kind of h yeah,
Speaker 3: RaSE the bottom. But also just there's no way to
Speaker 3: there's no reason they would have.
Speaker 2: To compete, like you couldn't compete as they We haven't
Speaker 2: really seen any new social networks in years other than
Speaker 2: Blue Sky and Threads. And Threads is a part of
Speaker 2: a part of the Facebook machine.
Speaker 1: And we have seen talk about TikTok is just a
Speaker 1: amplification of the same business model, same monetization system, same
Speaker 1: sort of weaknesses being exploited as Instagram, Facebook.
Speaker 2: And they burned, and they burned billions and billions of
Speaker 2: dollars to get there. It wasn't like that. People try
Speaker 2: and I don't know why people would possibly think this,
Speaker 2: but they frame Byte Dance some plucky upstart versus just
Speaker 2: a massively funded Chinese juggernaut.
Speaker 1: Actually much is why I actually use the word ecosystem
Speaker 1: because this model itself is highly synergistic with companies growing
Speaker 1: very fast. And why do they grow very fast Because
Speaker 1: they want market share, they want to dominate the market.
Speaker 1: But I also want data and how is that possible?
Speaker 1: How can you grow so fast? Well, you get venture
Speaker 1: capital or Microsoft to bankroll you, as in the case
Speaker 1: of open ai, So you burn through a lot of
Speaker 1: cash early on in order to get data dominance and
Speaker 1: market dominance. And again it's not a pro competitive picture
Speaker 1: that's emerging here.
Speaker 2: I feel like General VII is something separate because with
Speaker 2: that they well they don't have a business model yet,
Speaker 2: they do not.
Speaker 1: Have a business model. But you know what that does,
Speaker 1: It makes it even more likely that we're gonna just
Speaker 1: repeat the same sins of earlier social media. Look at
Speaker 1: what is open ai doing. It's burning through a lot
Speaker 1: of cash in order to acquire market share and data.
Speaker 1: It's not monetizing through anything. And I think the most
Speaker 1: likely cash cow ideas that are coming up we're going
Speaker 1: to use generative AI for Internet search and we're gonna
Speaker 1: take over the digital ad revenues. Well, that's more of
Speaker 1: the same.
Speaker 3: And I don't different conversation.
Speaker 2: I don't think that'll work, but it's Nevertheless, I can
Speaker 2: see the idea.
Speaker 3: It's funny, these incentives really have it.
Speaker 2: I've never really thought about it before this conversation, but
Speaker 2: it feels like digital advertising really did harm the tech
Speaker 2: industry in that they found something very profitable that got
Speaker 2: more profit ple without making the user's life better at all.
Speaker 1: Well, Larry Page and say Gay Brinn, when they first
Speaker 1: formed their company, said we don't want ads. That's not
Speaker 1: like a good model.
Speaker 3: Yeah, it's empathetical to a search problem.
Speaker 1: At the moment, somebody came and gave them venture capital
Speaker 1: money and said, but we do it so that you
Speaker 1: can actually the lads.
Speaker 3: Yes, what if you were super rich.
Speaker 2: But it doesn't sound like this would kill the digital
Speaker 2: ads industry, because if.
Speaker 1: I don't think we should kill it either. I mean
Speaker 1: I think again, if we created a monolith, a monoculture,
Speaker 1: that wouldn't be good. If everything was on online, everything
Speaker 1: was based on subscription, that wouldn't be a good model either.
Speaker 2: So you want a variety, but so well is more
Speaker 2: operational level. I'm guessing that this would also have to
Speaker 2: have some way of cutting through things like if people
Speaker 2: set up subsidiaries to try and pass off the tax
Speaker 2: as well. You would have to make sure that there
Speaker 2: was a way around.
Speaker 1: You know. That's why this is not a sort of
Speaker 1: a graduated tax that is easier to gain. But if
Speaker 1: you know five hundred million, you know it's like a
Speaker 1: very small amount of money. So you just set a
Speaker 1: minimum like that, perhaps a little bit more so that
Speaker 1: the really small companies are not burdened by it. We
Speaker 1: know one problem, for example, with the European GDPR is
Speaker 1: that once you put a regulation like that, the burden
Speaker 1: is heavier on smaller companies, and so it actually it's
Speaker 1: a competitive advantage for the large platforms that you don't
Speaker 1: want to do that.
Speaker 2: But I think five hundred million would actually that would
Speaker 2: make a very healthy market for smaller companies.
Speaker 1: Which is great. We want more smaller companies as well.
Speaker 2: But wouldn't I think that this would help with the
Speaker 2: problem a great deal. But don't we also need something
Speaker 2: to do with the algorithms themselves. Because I feel you
Speaker 2: could do this and it would solve some problems. It
Speaker 2: would begin incentivizing them in the right direction. Theoretically, yeah,
Speaker 2: but you still have this problem of they wouldn't stop algorithm.
Speaker 2: In fact, this might encourage them to be more algorithmically.
Speaker 1: Absolutely, and that's why I don't think this is a
Speaker 1: silver bullet, you know it. You need a range of policies.
Speaker 1: But the hope is that at least such a policy
Speaker 1: would create some push towards some platforms and products to
Speaker 1: have better quality algorithms that don't trap you like that.
Speaker 1: But for example, if we're talking about social media, we
Speaker 1: should also be talking about repeal or relaxation of Section
Speaker 1: two thirty of the Digital Acts, so that you know,
Speaker 1: companies that algorithmically boost content cannot then say, well, you know,
Speaker 1: this is not our speech, this is somebody else's thing
Speaker 1: that we have nothing to do with it. So there
Speaker 1: are some details there that we have to think about.
Speaker 1: And I think Section two thirty, which was written in
Speaker 1: a different age in the nineteen nineties, is definitely not
Speaker 1: up for dealing with issues algorithmic boosty.
Speaker 2: And debating Section two thirty a side, because that is
Speaker 2: also a separate conversation. It does feel like we have
Speaker 2: just kind of not given tech companies much responsibility for
Speaker 2: what they're doing.
Speaker 1: No exactly, just that's the main reason why I want
Speaker 1: to have a conversation about Section two thirty because it
Speaker 1: can't be optimal that that corporations that are arguably the
Speaker 1: largest and the most powerful humanity has ever seen can
Speaker 1: then wash off their hands and say we're not responsible
Speaker 1: for anything that happens on our platforms.
Speaker 2: Yeah, it feels with two thirty and I am not
Speaker 2: as well read as I should be about it, but
Speaker 2: it feels as if that responsibility side is the real
Speaker 2: niggling issue but also the most thorny because on some
Speaker 2: level it makes sense with social media platforms that they
Speaker 2: should be able to say we're not responsible for all
Speaker 2: the posts, and if they had to be, they will.
Speaker 1: Absolutely And look, I think free speeches of major issue.
Speaker 1: I am worried about erosion of free speech, but you know,
Speaker 1: I'm also not like a one hundred percent free speech absolutist.
Speaker 1: I think we have to balance it, and the way
Speaker 1: that I would suggest as is again, so now we're
Speaker 1: changing topic a little bit. Second two thirty is, you know,
Speaker 1: subject to whatever legal requirements there are on you know,
Speaker 1: abusive content, et cetera. If you post something on Instagram
Speaker 1: or Facebook and the company doesn't algorithmically promote it, then.
Speaker 3: It's completely right.
Speaker 1: It's there. It's my speech. If my friends find out
Speaker 1: about it, they can go and look at it. If
Speaker 1: somebody stumbles on it, that's fine. But algorithmic boosting is
Speaker 1: like New York Times putting you on their front page.
Speaker 1: We can't say New York Times is putting you on
Speaker 1: your front page, and you can say all sorts of
Speaker 1: lies and crazy things, and that's just freedom of wealth.
Speaker 3: Yeah, okay, yeah, now I know what you mean.
Speaker 1: Though, if you have a more more preferred newspaper that example.
Speaker 2: No, no, no, but I know what you mean. It almost,
Speaker 2: and it seems like the problem is that you're saying
Speaker 2: is it isn't two thirty itself. It's the fact that
Speaker 2: the algorithms boost yeah, these particular things.
Speaker 1: Thirty was fine for the age it was written where
Speaker 1: nobody could could have understood the onslaught of algorithmic boosting
Speaker 1: promotion and manipulation that would come.
Speaker 2: And it feels like it's an incentive problem that we
Speaker 2: just it's almost that platforms should either move away from
Speaker 2: the algorithm model, because if you because the amendments section
Speaker 2: two thirty that just says it should go away kind
Speaker 2: of doesn't sit right with me. I don't think you should.
Speaker 2: It would make platforms like WordPress impossible to use, or
Speaker 2: like blogging platforms, but the idea of what they promote
Speaker 2: being more intentional.
Speaker 1: Absolutely that I actually reallyze this rule that I suggested
Speaker 1: completely protects WordPress. WordPress doesn't promote, right, So this sort
Speaker 1: of reformed two thirty is completely fine in that respect.
Speaker 2: So as far as this fifty percent tax, do we
Speaker 2: have any kind of historical press to something like this
Speaker 2: being done?
Speaker 1: And that's why, you know, am I sure fifty percent
Speaker 1: is the right level? Absolutely not per thirty.
Speaker 3: But I think fifty is great.
Speaker 1: Thank you.
Speaker 2: Well, Because the thing is, the way I look at
Speaker 2: it is these companies are so adept to avoiding responsibility,
Speaker 2: and they're so unwilling to change their ways and so
Speaker 2: unwilling to be responsible with what they're doing, that it
Speaker 2: needs to be like this. And I'm sure that if
Speaker 2: this actually got anywhere near a government, they would have
Speaker 2: the world's biggest tantrum.
Speaker 3: But I feel like we need stuff.
Speaker 1: It needs to be a shock to the system, absolutely.
Speaker 2: And I think that well, actually maybe that's the question.
Speaker 2: How practical would this be to actually implement?
Speaker 1: Well, Well, it depends on what you mean by that.
Speaker 2: Well, I mean, how how hard would it be to
Speaker 2: get to get this actually into existence with the government
Speaker 2: able to levy that tax.
Speaker 1: It would be extremely hard because of the lobbying, as
Speaker 1: you pointed out, But if there was agreement, if the
Speaker 1: Chinese government wanted to do it right, they could do
Speaker 1: it overnight. It's it's all out there. The digital ad
Speaker 1: revenue is there, it's measured, you know all. And the
Speaker 1: flat tax is very easy to implement. You could do
Speaker 1: it at source when you know advertisers, companies pay for advertising.
Speaker 1: You could do it in many different ways, so it's
Speaker 1: very easy, you know. We it's a version of variety
Speaker 1: of VAT like at volume taxes. We have them in
Speaker 1: under much more complicated situations when there is much lower
Speaker 1: quality data about what's going on. You know, many middle
Speaker 1: income countries have a very complex sales tax or a
Speaker 1: VAT tax.
Speaker 2: Yeah, and it almost feels that you could have a
Speaker 2: little fun with it as well. Maybe you could do
Speaker 2: this fifty percent tax and freed it directly into some
Speaker 2: sort of national venture fund. It would end up funding
Speaker 2: the feure. It feels as if the as go like
Speaker 2: on a larger scale, it feels like governments are just
Speaker 2: twenty years behind technology. Not even putting aside even Section
Speaker 2: two thirty. It feels like we should have an EPA
Speaker 2: or an FDA for data. It feels like we should
Speaker 2: have ways of Actually we don't know how these algorithms work,
Speaker 2: and it just feels a little crazy to me.
Speaker 1: Yeah. Absolutely, But the way I would say it is,
Speaker 1: I'm not sure that I would say they are twenty
Speaker 1: years behind in terms of knowledge.
Speaker 3: I actually, oh, not knowledge, just legislation.
Speaker 1: Legislation. Yeah. So, like a completely different but related topic
Speaker 1: is we actually need an infrastructure for data markets, right,
Speaker 1: so you know, I think everybody says data is going
Speaker 1: to be one of the most important factors of production
Speaker 1: for the future, more important than land. Imagine that I
Speaker 1: told you that today land that is still pretty relevant
Speaker 1: for many businesses. It's up for grabs. You can just
Speaker 1: go and get whatever piece of land you want and
Speaker 1: you don't have to pay for it. You know, that
Speaker 1: tragedy of the commons is well understood from history. It
Speaker 1: will be disastrous.
Speaker 3: Yeah, it's just the wild West.
Speaker 1: Yeah, it's wild West. Nobody produces high quality data, Nobody
Speaker 1: gets compensated for the data that they have, and it
Speaker 1: encourages you know, the monetization that model that we talked
Speaker 1: about where you actually sweep people's data without their permission
Speaker 1: or without their understanding, and you try to monetize it
Speaker 1: by digital app So a complementary thing is we think
Speaker 1: about how how is it that we can have a
Speaker 1: system where data producers are encouraged to produce higher quality
Speaker 1: data so that perhaps, you know, next version of a
Speaker 1: large language model learns not from Reddit, but learns from
Speaker 1: high quality, dominant the domain relevant expertise.
Speaker 3: I think in that case, Hey, I think in that case.
Speaker 2: I'm not sure I agree, just because large language models
Speaker 2: getting higher quality data is a pro like how you
Speaker 2: build them, would like it? Just higher quality data would
Speaker 2: just be they still need more. But I get what
Speaker 2: you mean that if these companies were incentivized to actually
Speaker 2: have good data and provide good services with the data,
Speaker 2: that would be better. Because that's the thing I'm not.
Speaker 2: I don't love digital targeting. I don't love any of it.
Speaker 2: But man, if they have all this data, why are
Speaker 2: all their services so impersonal? They don't feel like they're
Speaker 2: for us?
Speaker 1: And why does Microsoft word always crash? Yes?
Speaker 2: I know that, but that one, that one's it doesn't matter.
Speaker 2: They have the dot doc and dot doc x model.
Speaker 2: They have a tiny little kind of monopoly now though
Speaker 2: they were various sense trust actions have to change.
Speaker 1: Let me actually, let me actually talk push back a
Speaker 1: little bit on generative AI. Okay, because I think your
Speaker 1: statement makes sense. If you buy in that generative AI
Speaker 1: is most productively developed in the form of general purpose
Speaker 1: human like chatbots, they will need like huge amount of
Speaker 1: data because next word prediction is very very inefficient and
Speaker 1: you need to imitate humans and variety of circumstances. But
Speaker 1: imagine that we use generative to AI in a very
Speaker 1: domain specific way. You know, I want to know what
Speaker 1: drug creates, what side effects in conjunction with other drugs, right, Well,
Speaker 1: for that, I don't need my generative AI tool to
Speaker 1: communicate with me in you know, human like fashion or
Speaker 1: write Shakespearean sonnets. I just need some very specific domain expertise.
Speaker 1: But that high quality data is actually not out.
Speaker 3: There, and I fully agree with that.
Speaker 2: And smaller language models focus language moddles does make sense.
Speaker 2: But I think we are actually agreeing because this is
Speaker 2: an incentive problem. The reason open AI isn't really focused
Speaker 2: on that is because it doesn't make that much money.
Speaker 1: Well, open AI itself is not making a lot of money.
Speaker 1: They're not liking No, I think I think they are
Speaker 1: not focused on that because A, if you want to
Speaker 1: get big, very very fast and collect a lot of data,
Speaker 1: domain specific models are not going to work. So creating
Speaker 1: hype around something that sounds very intelligent is a much
Speaker 1: better tool for doing that. And second, I think in
Speaker 1: the industry is still in an unhealthy way, in my opinion,
Speaker 1: preoccupied with artificial general intelligence right, human like intelligent, even
Speaker 1: if that's not what we need, even if that's not
Speaker 1: what's feasible, even if that's got a lot of downsides.
Speaker 1: So that's why they don't, in my opinion, pay sufficient
Speaker 1: attention to these domain specific expertise models.
Speaker 2: So if for you, I actually agree, But also then
Speaker 2: and that is an economics problem, that is a these
Speaker 2: companies are incentivized to grow at all costs, to get
Speaker 2: as big as possible. Is what you're suggesting that they
Speaker 2: shouldn't it is.
Speaker 1: It is not just an economics problem, but it has
Speaker 1: an important economic leg If we did not have venture
Speaker 1: capital be so important, this model would not have gotten
Speaker 1: off the ground.
Speaker 2: So how do we push back on the VC model?
Speaker 2: How do we actually make technology work without that model,
Speaker 2: because I agree it's the growth of all costs. Build
Speaker 2: as big as possible, then IPO and everyone gets rich
Speaker 2: other than the user.
Speaker 3: Well, what are the alternatives?
Speaker 1: I don't know. I mean, I am not so much
Speaker 1: of an interventionist that I'm going to say, you know,
Speaker 1: you should tax VC as well. But I think one
Speaker 1: thing that encourages the VC grow at all cost model
Speaker 1: is that we don't have any anti trust right there
Speaker 1: was very strong anti trust and implementation. Then becoming so
Speaker 1: big wouldn't be so attractive, and you wouldn't be able
Speaker 1: to acquire all your competitors in the process as well,
Speaker 1: which is a very important part of this get very big,
Speaker 1: very quick. So I think our big failure of you know,
Speaker 1: upholding existing antitrust laws and introducing new anti trust laws
Speaker 1: appropriate for the digital age, I think has contributed to
Speaker 1: this problem.
Speaker 2: Is there a way of incentivizing vcs? So actually this
Speaker 2: is how we are. This is the final question, because
Speaker 2: you might actually have an answer here. How do we
Speaker 2: incentivize venture capital and the startup industry to start investing
Speaker 2: at the earlier stage because a big fund just gave
Speaker 2: back a chunk of their fund because they were not
Speaker 2: finding as many opportunities in the late stage, and it
Speaker 2: like most of the money goes into that late stage.
Speaker 2: How do we incentivize that.
Speaker 1: That's a much harder problem, because even well qualified vcs
Speaker 1: are not going to have an easy time recognizing a
Speaker 1: very promising product when it's in the garage stage. Right.
Speaker 1: But and this brings another, you know, set of issues.
Speaker 1: The fact that we tax capital so lightly contributes to this. Again,
Speaker 1: we're subsidizing vcs because if you make your money via
Speaker 1: vcs as sort of investment on your capital, you pay
Speaker 1: very little tax. You know, if you are you know,
Speaker 1: a tech billionaire, I want name names, you don't even
Speaker 1: pay yourself a salary. You keep on borrowing money from
Speaker 1: venture capitals or other specialized financial vehicles, and you pay
Speaker 1: yourself out of that. Everything is capital income. You pay
Speaker 1: minimal taxes. So our tax system, already a big contributor
Speaker 1: to inequality, actually also distorts the digital landscape. So one
Speaker 1: simple thing, again, which is probably even less likely to
Speaker 1: be implemented in our current polarized environment, is let's tax
Speaker 1: capital and labor at a flat rate the same or
Speaker 1: you know, you can act whether a progressity you want,
Speaker 1: but you do not distinguish capital and labor income. If
Speaker 1: you're going to tax labor income at thirty percent tax
Speaker 1: capital at thirty percent.
Speaker 3: I agree on that one.
Speaker 2: It just feels like it would be great if there
Speaker 2: was a way of just almost because you're talking a
Speaker 2: lot about taxation such and I agree that we need
Speaker 2: those controls, But is there a way to incentivize them
Speaker 2: to put more money earlier make more risky bets. I'm
Speaker 2: not saying a deduction, because that would be crazy, but
Speaker 2: it feels like that would also solve, in part in
Speaker 2: concert with these taxes, a way of getting that money
Speaker 2: into the early ecosystem.
Speaker 1: There may be, but I don't know exactly. We should
Speaker 1: think more about it, but there is an alternative solution
Speaker 1: yet another policy proposal, as we fund a federal agency
Speaker 1: on AI which is tasked both by communicating and developing
Speaker 1: best standards on things like privacy data you know AI standards,
Speaker 1: security safety, but also has deep enough pockets that it
Speaker 1: can play that incubator role for especially for technologies that
Speaker 1: are deemed to be socially beneficial. So if we have
Speaker 1: technologies that actually protect in users of privacy and enable
Speaker 1: users to make better decisions. That's the kind of thing
Speaker 1: that the government should put money in early on. Some
Speaker 1: of it will go to waste, some of it will
Speaker 1: go bankrupt. But if a few of them are successful,
Speaker 1: that's great. And if the alternative is that the vcs
Speaker 1: are going to develop the technologies that are most manipulative,
Speaker 1: there is even more reason for putting this money.
Speaker 2: Thorne, thank you so much for joining me again. It's
Speaker 2: been such a pleasure.
Speaker 1: Of course, this was my pleasure. Thank you for being
Speaker 1: interested in these issues and such by having such a
Speaker 1: great conversation.
Speaker 3: Thanks so much. Thank you for listening to Better Offline.
Speaker 2: The editor and composer of the Better Offline theme song
Speaker 2: is Mattersowski. You can check out more of his music
Speaker 2: and audio projects at Matasowski dot com, M A T
Speaker 2: T O s O W s ki dot com. You
Speaker 2: can email me at easy at Better Offline dot com,
Speaker 2: or visit Better Offline dot com to find more podcast
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Speaker 3: Better Offline to check out our reddit. Thank you so
Speaker 3: much for.
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