The Vergecast - Jaron Lanier's ideas for the future

Episode Date: April 9, 2019

Computer philosophy writer and "founding father of virtual reality," Jaron Lanier, chats with Verge editor-in-chief Nilay Patel about why he's optimistic about the future. Lanier shares his thoughts on how the "manipulation economy" has reshaped the world we live in and why we should be controlling and profiting from our own data. Vote for Vergecast in the Webby's! as well as The Verge's Why'd You Push That Button? and our wonderful YouTube channel Verge Science Learn more about your ad choices. Visit podcastchoices.com/adchoices

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dropping May 14th. Tap in with us. Hey everybody, it's Neelai from the Vergecast. I'm super excited about this week's interview episode. It's with Jaron Lanier, who is one of the early pioneers of virtual reality. I mean like really early. He's written incredible books. One of the founding documents of the Verge in my mind is a book he wrote called You Are Not a Gadget.

He lately has been working as an interdisciplinary scientist at Microsoft. But Jaron is all over the place. He's thought about everything. He's been deep in it from the beginning. and we talked about something that I think is really coming to the mainstream now, which is the idea that the data you generate as a consumer and a user of the digital world is valuable, and you should be compensated for it in various ways. And you shouldn't just give things away for free.

And I think the early part of the Internet was really about crowdsourcing, as well, sharing economy, is about people sharing everything about themselves for free. And what we've realized, and we've talked about a lot on the show, is that the platforms that enabled that sharing have gotten wildly rich, and the rest of us maybe haven't. Jaron's been writing about that forever, literally forever. He's been writing about this and talking about it. And so I caught up with him, and what really surprised me is how excited and positive he is,

that change is coming. Positive, real change is coming because we have finally started thinking about this stuff. So a big contrast to some of the other conversations I've had, and also just one of the wildest, every possible direction, conversations about tech and life that I've had in a long time. I really want you to listen to this. Let me know what you think. Jaron Lanier. Okay, we're here with Jaron Lanier.

Welcome. Thanks so much for having me on. Thank you for being here. I've got to say I'm a huge fan. This is an honor to talk to you. I've said this to you before, but when we were starting the verge in 2011, your book, You Are Not a Gadget, was deeply inspirational to us because it was, if the audience hasn't read it, you guys should stop your cars and pull over and order it right now.

It is a book about how technology makes you think and how you might think about technology. That's something I think about all the time. It's something Dieter Bone, our executive editor thinks about all the time. And it's something you have been writing about in various ways, very critically, for some time. So I want to start with where you think we are. Have we done a good job of being critical about how technology makes us think? Well, first of all, thank you so much for your kind words. And as far as where we are, I believe we're in the beginning of a process of learning how to deal with technology.

I think we're in a better place than we were a year or two ago. There's a more informed dialogue. I think the tech world has become more used to the idea of thinking through what it all really means. So I'm feeling more optimistic and energized than I have in a while. I think we're at the beginning of the beginning here. I think we're starting to really understand how computing can work in our lives and in civilization. We dived into it before with nothing but naivete and optimism. And we're growing up.

We're just, we're toddlers, but we're, but it's happening. And so I'm, I'm, I'm happy. That's, that's remarkably refreshing to hear, I have to say. I've been interviewing a lot of people on the show. And one of the reasons I wanted to talk to you in particular was so many other folks I talked to are deeply focused on problems. And they're saying, these things are problems. And it's very refreshing to hear from somebody who says,

We're at the beginning of solutions. So you've been at this for a really long time. You've been in the computing industry since it sort of burst onto the scene. Would you say there are like stages? What stage of this are we at? Well, I called us toddlers. Yeah. And the reason I'm saying that is that toddlers are growing up.

They're gaining cognitive skills. They're gaining expertise. They're gaining self-awareness. but they're also often really pissy and annoying and difficult. They're often narcissistic. They often have tantrums. And that's tech culture right now. So I choose to frame it in a positive light,

but it definitely has that quality of working through a very difficult stage of dawning self-awareness. It's not easy. One of the things that you've kind of been most critical of is sort of the nature. of collective wisdom on the internet, of crowdsourcing, of Web 2.0, of all the user-generated stuff. I think an interesting thing that I see right now is so many creators across all these platforms

are saying, hey, we're not getting paid for our work. We're making human stuff, we're making culture, and we're putting on tech platforms. The platforms are benefiting, but we feel dehumanized, and we're certainly not seeing any return. I mean, that was one of your biggest criticisms of the tech world, and you are not a gadget. It's many years later.

You've written more about it since. Do you see that tide turning or do you see that as a culmination of what you were saying? Well, it's just barely starting to turn. And I need to make one thing clear about it. When I talk about the importance of people being paid for their data, it's not so much about a narrow class of creators that we might think about today like musicians or journalists. It's more broadly about the relationship of people to technology in the far future. If we're eventually building towards a world in which there's a whole lot of automation,

a whole lot of programs that we think of as AI, what are the roles for humans? If we're going to say that supplying the data that makes the machines run isn't real work, it's not something you get paid for, it's just exhaust from you, and the way you live is from some sort of welfare scheme or something, that's incredibly dehumanizing, it's incredibly dishonest. It'll lead to a world that undervalues people and makes people feel kind of useless as if they're just dependence. And that's a terrible vision of the future, whereas the honest appraisal is that AI only runs on data, data only comes from people. So in some super advanced future world, people have to be paid for their data in order to have dignity

in an order for the system to be honest. And so these days, the examples that come up of that are often narrow groups like artists, but a lot of it's not so narrow. A lot of the data that you give over when you interact with social media or search is turning into AI algorithms that could gradually put you out of work.

And you should be paid for that. You should be acknowledged for it. You should be able to take pride in it. You should get better at providing better data because that's the future we're moving into. So to me, what it's really about is how we define the human role, how we think about the nature of human dignity, and also just whether we're creating an economy that's sustainable,

you know, will companies even have customers in the future if we enter into this world where everybody's a dependent on the state? What kind of world is that? Is that a world capable of any creativity? Or is it just some, you know, one of the dystopias that science fiction keeps on showing us in movies like The Matrix? I don't want to create that future. So the alternative is to pay people for their data. How would you, imagine that that should work. Yes, well, there's a lot of work to do. There's a lot of work to do.

One of the things my research team is working on now is trying to fill in the picture of what this future would be like. What happens when you wake up in the morning? What is the user interface like? What kind of decisions do you face? And how far in the future are we talking about? Are we talking about 50 years or 100 years? And we're trying to fill in some of the details.

I can tell you a few things. one thing I can tell you is that we have to develop a whole new class of user experiences that acknowledge that people are valuable because we're used to user experiences where we say, you know, click on one button that gives away all your data and then put yourself in our hands and we'll deliver convenience to you. And we have to shift that into this other world where we say, hey, you know, you're responsible, you're creating the world. You are a creator. We respect you. We can offer you tools. But this is, you. This is not us. I think there are some current systems that hint at what that world might be like.

The current one I like the best is called GitHub. You could imagine that expanding to cover a wider variety of things and to include more commerce in it than it does. I imagine there'll be a low parameter way of interfacing with the world, by which I mean a number of virtual knobs you can turn to adjust your position in the world. For instance, you might be able to set a bias on the price of your data, which isn't the absolute price, because that would be combined with market demand and all kinds of things. For instance, if you're young and starting out and you want to be noticed, you might make your data really cheap.

If you want a lot of privacy, you'd make it so expensive that effectively it isn't used. And most people would try to game the system and put it somewhere in the middle and maximize their returns. I think that you'll have thousands of streams of data royalties coming from thousands of different kinds of data that build up over the course of your life. So it won't be just like one or two things, but lots of things. Some of it will be live interaction where you're giving music lessons online. Some of it will be involuntary data.

I would say unwitting data taken from you. It'll be voluntary. Some of it might be biological. Some of it might be neurological. There'll be all kinds of things that come about. In order for the value of data not to go to zero, there will have to be a new kind of organization that we're calling a mid where people join together to, collectively bargain for the value of their data?

And this is a funny idea. In the history of capitalism, there's always been a necessity for some kind of a way for people to come together. So it's not a competition of each person against each other person. But because we've traditionally had this difference between what we call labor and what we call capital, we have different terminology on each side of that divide. So if you're talking about capital, then you make corporations or you might make partnerships like for a law firm. And then on the labor side, we talk about unions, labor unions.

I think in this new world, the distinction between capital and labor becomes a little harder to understand and maybe doesn't exist at all. But at any rate, something like that has to happen. We're calling it a mid, which is a mediator of individual data. And so you'll have to join mids, and probably a bunch of them, there'll be multiple ones. I'll say one more thing about mids, and then I'll let you ask another question. I love it. That's great. Okay, cool. One of the the things that the mid makes sure that you don't get paid nothing so that you're not just all every person isn't competing against every other person but the mid does another thing it solves a

really crucial problem that we have right now which is uh right now we're basing the whole world on a concept that is technically impossible that's mathematically spurious and that's the idea of global optimization uh that doesn't exist the only thing that is real is local optimization so i'm sorry to nerd out But I think you're... No, this is why I want you here. We are hearing a lot about the effects of optimization, of AI, of automation, of... We hear about the, I think, the sociological effects of them quite a bit. I interview those people on the show all the time.

I think the mathematical reality of those things is often placed at a remove. I think we spend so much time focusing on the symptoms. We rarely look at the cause. Understanding that connection is really important to me. I'm going to talk about global and local optimization. And in order to do it, I want to first talk about a legal idea that comes to us from very old common law, which is the idea of a fiducial. If there's somebody you have a business relationship with who represents you but has superior information or training or capital or something compared to you, there's a law that they have to represent your interests and not theirs or anybody else's. So, for instance, when you hire a lawyer, the lawyer has special training.

The lawyer can only represent you, not the person who opposes you. The doctor has to represent you, not somebody else, like a pharmaceutical or whatever. The same thing is true for some financial planners, et cetera. So the issue here is that we're asking the big tech platforms like your Facebooks and Googles to be fiducials for everybody globally, which is an absurdity. And the way we do that is we go to them and we keep on saying, Oh, big platform, could you please control our speech for us? Could you please get rid of the hateful people and the fraudsters?

And could you please get rid of the insiders and the harassers and the sadistic people and the blackmailers and blah, blah, blah, blah, blah. And of course, those are all horrible people. But the question is, is it functional for us to ask a global platform to become a global filter for our civilization? Where does that lead us in the long term? And the answer is it leads us to some kind of narrow authoritarian future, which is terrible. So the solution to that is found in having medium-sized organizations that can serve as filters and build up brands and followings, and they're not all identical. And this is not a new idea. This is a really old idea. And the best writers on it are somebody named Hana Arendt and somebody else named Tokville, who you might remember from the humanities courses you were forced to take when you were getting your engineering degrees. So the basic idea is that you have to be able to have people who build up brands, and the verge is a great example of this.

So the Verge has a brand. People trust you guys because you've done enough good reporting and you've demonstrated enough sanity that they think if you put something out there, it's not completely cuckoo, right? We try. We do our very best. Yeah. Hey, you know, I think you're doing better than many. Let's say that. So the thing is, if you have a multitude of those in the society and they can be universities, they can be journals, they can be unions and trade guilds, they can be all kinds of different entities. But these intermediate-sized organizations are the things that can have fiducial responsibilities to individuals. They're not all the same. They don't all have the same point of view, but people learn to trust them.

And it's those in-between places where you find the quality in a culture. Those are the in-between places where you start to have civility, where you start to have maturity, where you can have creativity and growth that isn't taken over by whoever is the biggest creep, who can get the most attention. And that's, all those intermediates are the institutions that have been weakened by the giant platforms. And that's why it's so crucial to build them back. So in this new world, you'll join those things. And those are the things that'll make sure you get paid and will help negotiate for decent rates and all of that sort of stuff. But they'll also become associated with branding and with quality.

And they might not be easy to get into. It might be hard to get into some of the better ones. But that'll be the whole point. But there'll be a multitude. So you're describing what almost sounds like a, Like in music, like a like a, like a BMI or ASCAP for your data. It's a little bit like a BMI or an ASCAP, but it's also a little bit like a label. It's more like a label than it is like an ASCAP.

The labels are barely important anymore. But the labels have a kind of a value. They kind of assert a certain sense of aesthetics and what music is for, how it fits into society. They represent typically artists who fit in some way. Like Motown or Stax, like in their heyday, they had a sound. And you're saying, in the future, you're going to have these data organizations. And you're like, I want to sign with Stacks data because I'm like a Stax data type. And they're like, you're in.

And we're going to, as you generate data moving through the world, we're going to collect that and resell it and make sure that it's good. Or we're just going to collect royalties. Like how do you see that mechanically working? Well, they'll all be different, you know. But, I mean, like today, book publishing is vulnerable. It's suffering, but it still is a real market. And part of the reason that people like me who write books still seek out traditional publishers is that it keeps us honest because the editors will force us to make readable writing. It assures readers that the book has met some sort of standard and has some sort of level of quality.

It joins into a structure in society that people already have a bit of knowledge. about, so it gets some context. Can I draw another very nerdy analogy? Yes, by all means. A society or an economy, if you like, are learning structures. There are these huge structures that we create between us that deal with uncertainty, that preserve information and lessons that we've learned generation to generation that help us cope with things. And in that sense, you can think of a society or an economy as a giant learning system as a, if you like, as a neural net. And in order to have neural nets work, you have to have intermediate layers because the whole point is that you're building up intermediate layers of representation that interact together so that the whole thing has learned

something, whereas a single layer can only be like a thermostat that responds very simply. And the mids become the intermediate layers in a civilization. And what organizations like Facebook and Google have been doing to us is they've been killing the intermediate layers. So we just have a whole society based on one level thermostats instead of on a complete machine learning system with multiple layers. And so we need to restrengthen those in between organizations. Basically we need to form various kinds of collectives to negotiate against these dominant platforms, is what you're suggesting. Well, the term collective is loaded because we associate it with Mao or something. I prefer associations or you can say confederacies.

You can say new kinds of corporations. There's all kinds of language, but it all means the same thing. All right. We're going to take a quick break, and we'll come right back. Support for the show comes from Framer. Framer is an enterprise-grade, no-code website builder, used by teams at companies like Perplexity and Muro to move faster. With real-time collaboration and a robust CMS, with everything you need for great SEO,

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targeted so that you might take some action. I just had Shoshana Zuboff on the show. She read a book called The Age of Surveillance Capitalism. Sure. Love Shoshana. She thinks this is very dangerous. She thinks that, you know, it's going to abridge free will because we will just live in a world of pervasive, extremely pervasive advertising, and we'll basically be told what to do. The outcomes will be shaped for us. And so you and I are talking about that. And you said, well, the problem is you can't mathematically tell the difference between a recommendation and a prediction. And I just want you to unpack that a little bit because I think if you talk about, okay, we're going to have meds, we're going to have some intermediary layer that collects your data that gets you paid for it, that make sure you're safe in whatever organization you are, that still suggests that we ought to collect a lot of data. And it still suggests that these other machines might still work.

And if the core problem is that we can't tell a difference between a recommendation and a prediction, well, I want to start there. But then I want to ask if we can solve that problem in a way that makes sort of healthier culture. Yeah, there is a lot to unpack there. So one of the reasons for people to be paid for their data is it removes the economic incentive of taking their data just to persuade them or just to influence them. So if there's some economic value to being able to persuade somebody and there's no cost for doing that, then you'll have a whole society based on persuasion and trickery and manipulation, which is exactly what we've been building. As soon as there's a cost to doing so on a per person basis, then the economic incentives will shift and other business models will be forced into existence because that one will become either less profitable or hopefully unprofitable. And so it's absolutely essential to undo the perverse incentive of zero cost access to data that can be used to manipulate people by putting them into behavioral modification loops. So that's perhaps the deepest reason for paying for data.

But then let's address this other question, which is this empirical problem. There are different words for this problem. In medicine, it's called iatrogenic problem, which is to say that if you have a system that's being modified, by your apparatus and then you try to measure what's happening. You can't tell what would have been there without your apparatus. And so if you have people, you know, having experiences that are guided by recommendation algorithms and automated feeds or whatever other techniques there might be, then when you measure the result, how do you tell how much of that is because of you and how much would have been the same otherwise? And there was a moment when all of this was new and you could do

A B comparisons, but by now when you have whole generations who've grown up under the influence of the algorithms, it's no longer possible to tease it apart. There are a few conclusions there. If you can change the economic incentives so that it's no longer the first and most obvious thing to do, you know, if there's a zero-cost business plan, obviously you're going to choose it. As soon as there costs, then you compare it to others. And when the others start winning, then there'll be less of the manipulation. And then I think you'll start to be to see a world that's less filled with trickery and just bizarre paranoia and irritability, which are the side effects of being manipulated all the time. I can't get into the science behind that in a second. But the other issue is just understanding the

nature of what we call AI. There's always been this weird ambiguity about whether AI is really a thing or whether it's it's just a way of manipulating people. And there's a little. And there's a lot of ways of explaining that. Like, for instance, you could say, if people are getting feedback from an algorithm that affects their behavior and it works, do we then say, oh, that algorithm was smart, or do we say, oh, well, the people were changed? And you can actually, in most cases, interpret it either way. That might sound strange to somebody. I could start with the Turing test, the original thought experiment that gave us the concept of AI. In the Turing test, you have a computer and a judge and a person. And the computer and the person are behind a curtain and they can just send messages

to the judge and the judge tries to tell them apart. So the, the Turing test can only give us a question of whether the machine and the person are distinguishable. It can't really tell us anything absolutely about whether the machine has become elevated. Because there's the equal possibility that the person has descended to the level of the machine, right? That would be another route to creating an equivalence as far as the judge is concerned, or the judge might have become an idiot and become unable to distinguish them. So there's one machine and two people in the system, so there's a two-thirds chance that somebody's become stupid to make the machine look smart, right? So the chances are that AI is, whenever you perceive an AI, there's a two-thirds chance

that you've actually perceived a reduction in human standards. Now, obviously, I'm telling that as a joke, but I think there's some truth behind it. I'll give you a few examples. When we say that AIs have become superior to people in playing things like chess, what we're really saying is, whereas chess used to be at least half about the mind game between chess players and about this whole other layer, we've just thrown out that layer and said that all it is is the moves, which was never true before. So we've actually reduced the definition of chess in order to make the AI smart. So that's a very clear example. But I would also say that when we start to accept the recommendations for who to date,

what to buy, I don't know, just all this stuff that we do these days, is it us who's getting stupider or is it the algorithm that's getting smarter? There's really not any way to tell. The one thing I can tell you is that if the business incentives change so that manipulation isn't the only business plan, then at least it'll become a more open and varied system. And I think that that's what we can hope for, because we'll never be able to really draw a clean line and say, you know, what came from the person and what came from others. You know, this is an unresolvable thing. But at the very least, we can remove the perverse incentives to reduce the incredible degree of manipulation and trickery that overwhelms our society these days. What strikes me at this is that you're making pretty classical economic arguments, right?

you're making financial and monetary incentive arguments about how to change this big behavior in a world where like politicians around the earth are saying we need to regulate the platforms to do what we want. Do you think those things are in parallel? Do you think that we can actually create a set of incentives that change our behavior this dramatically? Or do you think that we just need to tell Google to stop it? Yeah. So we're in a very interesting moment when as I see it, there are different classes of solutions being proposed, and I'm definitely an advocate for one class over another class. So the class of solutions I dislike are the ones that say, well, let's just tax the hell out of the tech companies and then redistribute that money to everybody. One reason I don't

like this kind of solution is that if you follow to its conclusion, it eventually makes everybody into a ward of the state. And that would create the sort of matrix movie like dystopia, where people are kind of just batteries sitting there and kind of useless and supposedly amusing themselves. It's just not an attractive future. And then there's another problem, which is that whenever you have a central authority that gets all the money and distributes all the money, that thing gets all the power and it becomes a really tempting target for horrible people who just want power and nothing else. So the way I usually put this with my students is you start with Bolsheviks and then you end up with Stalinists. And then when the Stalinists fall apart, you end up with this pathetic mafia.

that happened to Russia. I don't want it to happen to the whole world. I don't want it to happen to the U.S. or Europe. And it could. You know, it's really not a good thing. So there's an alternative, which is you foster multi-level, heterogeneous, interesting, varied commerce between people, between people and mids, between mids and mids. You create a complex economy with a lot of distributed influence, a lot of distributed wealth, a lot of distributed creativity and variation. And to do that, you just make people's data, valuable and open up new business plans that take advantage of that and then pull the profit out of the old business plan of pure manipulation for free data. How do you get there from here? How do you make people's data valuable? What do you have to do? You have to pass a law. I just have to write about it every day until all the tech companies just go for it. Like what's the move? Yeah, you're in a position of influence. Well, it has to come from multiple directions at once. Yeah, I think there should be laws. I think people should be encouraged to take advantage of labor law if it's powerful in whatever country they live in or whatever other body

of law might be available in order to bargain for the value of their data and be able to create mids that extract value for the benefit of the people the data comes from on their own terms. You're talking about a very powerful idea that I just want to make a literal, which is when you use a tech platform, a Google, a Facebook, Apple News, whatever. When you use a computer, you are doing labor that is valuable. It occurs to me that's the core of what you're saying right now, that when you use one of these platforms and you use the software, you're not just receiving benefit. You are actually doing some work. You're generating some data that should be valued at some level. Well, you know, the usual example I've been using, which just because it's the clearest,

is the one of language translation. So right now, people who translate between languages for a living have been seeing a reduction in their career prospects that's very similar to what's happened to recording musicians and investigative journalists and photographers and so on. What happens is where there used to be a kind of a bell curve of outcomes where the majority of people had careers at a certain level and a few people did very well and a few people just crashed out of it. We're seeing what we call a zip curve where there's just a tiny number that do well and everybody else is flattened.

And we see that in YouTube content producers and in many other systems. Language translators used to be a bell curve and they turned into a zip curve. Now, the interesting thing about this is that the natural first reaction all of us have is that language translators have turned into buggy whips. It's very sad, but this is what happens. And for those who don't know, the buggy whip is the classical example of something that's gone obsolete. They were used to motivate horses when carriages were drawn by horses, and when the internal combustion engine came along, this whole industry of buggywhips just went away. But the thing is they're not buggy whips. And the reason why is that language is alive.

Every single day there's new culture and news and memes and all this stuff. And so every single day, new examples have to be gathered to update the database that allows automatic translation to happen. The thing is, we're not paying anybody for that data, you know. And so it's a very weird situation where we're saying, hey, you're obsolete, you're buggy whip, except, except, except we still need you, but we just won't admit we need you. And that's the twist there. In the past, whenever there's been new technology, jobs have gotten better because we acknowledge that the new kinds of jobs that are needed by whatever the new technology is will turn out to be better.

Usually the new kinds of jobs are more dignified and less dangerous and filthy and awful than the old jobs. That should be the case now, but the twist is we're pretending that we don't need the people. We're pretending that the new kind of job doesn't exist. We're putting it into the same category as what used to be women's, work or slaves work or something like that. And so when you take a whole class of creativity and value and you say, hey, this isn't real, this is just nothing, this is just nothing, then of course

you're going to sort of make people feel kind of unwelcome by the future. You're going to make people feel unneeded. And it's a terrible thing to do to humanity. It's inhumane. The next idea I'm a little less confident about, but I want to share it anyway because it's been haunting me lately. I've been reading the materials of the worst people in the world, like the guy who attacked the mosque in New Zealand and other people who, quote unquote, self-radicalize, often on gaming boards or similar. And when you read what these people talk about, and it doesn't matter if they're white-skinned or if they're Islamic or whatever, they always have this bizarre. fear that they're going to be made obsolete, that they're going to be replaced. The replacement theory that the New Zealand guy was talking about was, you know, my race will be replaced by immigrants, but you find variants of it. The horrible people at the Charlottesville rally were saying,

you know, the Jews will not replace us. Or actually, they initially started, you will not replace this, and then it turned into the Jews. I've been thinking about this replacement theme. And I think what it might be is people just feeling that modernity in the future no longer really need them, no longer really want them, and that they're being replaced by where the future is going, that they're becoming obsolete. Yeah. And so in a sense, they might be responding to all of our rhetoric about AI and how everybody's just going to have to go on universal basic income.

Like if we're advertising every single day that AI can, you know, is going to surpass people in this way or that way. I think a lot of people have this feeling like, wow, this is not the world that needs me. And I think that's one of the worst things you can hear. I agree. My pushback there would be, I think, one of the obvious net benefits to social networking in these global communities is the realization for many, many people that lots of other people exist in the world, too. And then you can't just ignore them. And I think those two ideas, I think, play together.

I think I'm like a brown dude. So I see both sides of that conversation very clearly that it's not just AI and automation. It is also like there are other people in the world who feel differently and they have voices. And platforms allow them to use. So you're saying that might come as a shock. Yeah. And the combination of those two things is real. I just I would if you're saying this idea is not fully formed, what I would suggest to you is it's the combination of the things that

is even more threatening, right? Like you have this other group that is suddenly, many other groups that are suddenly in full throat because the platforms have allowed that, which is, I think, an unrecognized good when we talk about all the negative things the platforms allow. There's another idea that I actually have investigated more

for some years that I do feel confident in, which is that when you have people who use the current platforms for purposes of advocacy, often with the best of intentions and without animosity towards other groups, you'll find that the information they upload, their videos, their chats, their memes, whatever, are shopped around by the algorithms, and the algorithms are always looking for some kind of a measurable response

that can be used as feedback to increase the level of engagement and persuasion of people. And since the fighter flight responses are the most easily measured, they're not the only ones, but they're the most easily measured, when somebody inputs positive stuff, it tends to find its greatest perch with those who are annoyed or afraid of it. So the Arab Spring input a bunch of data and the algorithms introduced people who turned into ISIS using that data. In the U.S., Black Lives Matter uploaded a bunch of data, and the algorithms introduced people who became the new Ku Klux Klan, neo-Nazi online world. And so I think this keeps on happening. So I think,

this universal persuasion manipulation machine does tend to take good intentions and turn them into bad, not intentionally, but as a side effect of which human emotional responses are the most easily measurable. Yeah. Yeah. And then that creates a general feeling. Fight or flight in their diffuse forms turns into paranoia and irritability. And I think anybody who's been on a big enough comment thread has just seen this happen. Like, you know, the big YouTube story about the recommendation engine, but there's also,

just like literally any comment thread over time tends to this like negativity because that's what literally what gets upvoted is what gets responses. I want to end on an up. We're talking about some very serious things. But you have this like very clear vision of what happens next. If you're an individual listening to this, how might you participate? Because I think the people who listen to the Vergecast, they're interested in building the future. They're interested in how the future might be better. And so, you know, we are always talking about, you know, vote with your dollars, like force on competition, all this stuff. But like from your perspective, and you're obviously thinking many, many more years out, how do you as an individual begin to participate in building

that kind of future? Well, I would seek out forms of internet activity that aren't governed by manipulation economics. And they exist. A great example is podcasts. For the moment, there isn't some aggregator podcasts that's just picking out the little plums and pulling them together in order to get only the parts that get the most rise out of people. The podcast is still a medium that has an author that has a known point of view that has people taking responsibility for it. So podcasts are like mids, if you like. So instead of trying to push for a higher following count on somebody's social media platform, launch a podcast. As one example, there really are alternatives that are not in the manipulation economy at the moment, and that's a prime example.

So I would seek those out, and I think that you'll find that they both help your own career and life aspirations, and they leave you and the people you interact with in a better psychological state than when your peons competing for competition for the benefit of some platform who only makes money at all by getting people to pay to manipulate you. It's just a better way. Yeah, I think that is to find a place where you're making choices. Again, I keep coming back to the idea that you're making fundamentally economic arguments. Go to a place where you're making choices and those choices are valued.

You know, I would prefer not to be talking about economics. I always found economics to be kind of sterile. I want to be talking about how to make beautiful virtual reality systems or musical instruments or something. I want to be aesthetic. I want to be, you know, but the thing is, At the end of the day, economics is what drives events. Incentives are, you know, our incentives. It's real.

So we have no choice but to think that way. I think that is, when you say we're at the beginning of the beginning, I think that realization that we haven't built this world in isolation, that we haven't disrupted an existing order, but we've built on top of it and that order is still real and needs to be, like you said, the engineering students studying the humanities, we have to glue those things together. if that's the beginning of the beginning, then I'm actually in a hopeful spot.

Because I think that... Good. That's stuff that we've learned once before, hundreds of times before in human culture. And if we're about to build a new one, like, that's the thing I think we should take away. Good. Well, I'm glad to leave you in a hopeful spot. I'm doing my best, man. Every day, I try.

Yeah. I'm going to ask you one lightning around question at the end because I got you here. And you are a virtual reality pioneer and you brought it up. How do you think we're doing in VR? It's a funny thing because I've been doing VR for a really... really long time. So a lot of the things that people find novel are interesting now are pretty old to me. I kind of say it's just that they're cheaper now. I think a lot of the action in VR as a business is going to happen in practical things for a long time because it's kind of a little pricey to do well.

And we're probably, this idea of VR as a popular medium still has to bake a little more maybe. A long time ago in the 80s, I was privileged. to participate in building the first surgical simulator. And we did it in the first VR system from my startup back then, which was the first VR company. And I did it with a surgeon at Stanford named Joe Rosen and an engineer from my startup named Anlasco. And we did a gallbladder and a knee.

Those were the first two. And from then DARPA took it on and improved it. And it's gone through many cycles. So in the last few years, my wife's had to battle a complex cancer case. and her principal surgeon trained in VR to use a procedure that was designed in VR, and his teacher had been Joe Rosen's student. Wow. And so it all came back around, and her surgeries went great, and she's doing great,

and I'm going to knock on some wood here. So I guess the thing I want to say is that VR, for me, is not just this hypothetical thing, but it's a thing that's already saved my family, and it's something I take very seriously as something that really helps in the world. So it's no longer that's speculative for me. That's incredible. Well, that is a great story to end on. Thank you so much for all the time, all the additional time.

Like I said, I have thought about your work as we've built our coverage and thought about how to think about technology and help people think about technology. So it's been an extraordinary pleasure to talk to you. It is an honor to talk to you, and I'm very pleased that you're interested, and I wish you the very best of luck. Thank you so much, Sharon. We'll talk to you soon. All right, everybody.

That was Jerome Lanier. It's just a real honor to talk to him. It's so much fun. Let me know what you think. You can tweet you me at Reckless. We'll move back later this week on Friday with a regular Vergecast. Let me know what you want us to talk about. And then next week, Tuesday, really exciting.

Andy Hawkins, our senior transportation and I are going to interview Brad Bow, one of the founders of Lyme, and we're going to figure out what is going on with scooters. We'll see you then.