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Speaker 1: As media.

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Speaker 2: Hello, and welcome to Better Offline. I'm your host ed

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Speaker 2: Zitron and this is the third I was about saying inaugural,

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Speaker 2: but I'm not sure that's what that word means. Episode

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Speaker 2: of Better Off Live, the live to tape radio show

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Speaker 2: that I shove in there when I'm in cities. Today,

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Speaker 2: I'm joined by two titans, Titans of the tech industry. Yes,

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Speaker 2: I've got Cory doctor Row here of course, author Cory

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Speaker 2: doctor Row and Brian Merchant, other author and journalist. And

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Speaker 2: I am so excited because today we're talking about how

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Speaker 2: we fix the entire tech industry.

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Speaker 3: Yeah, sounds like an easy order. I don't know what

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Speaker 3: we're gonna do with the excess time after we're done

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Speaker 3: with that.

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Speaker 1: Looking forward to that's probably twenty minutes, Yeah something Max, Max, Yeah,

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Speaker 1: we'll talk about our various holidays.

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Speaker 2: Brian just got back from the French rivi era. It

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Speaker 2: sounds like that's true.

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Speaker 3: Yeah, I did. We got stuck in Philadelphia, so my

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Speaker 3: brain is still.

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Speaker 2: The French revie Riviera of America, of America. Yeah, and

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Speaker 2: welcome to scholar debate, gentlemen. So the thing that I

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Speaker 2: keep thinking at the moment, the thing that really I

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Speaker 2: had too. It was like pessimism versus optimism that brought

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Speaker 2: you two together today with me and I keep coming

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Speaker 2: back to this, which is everyone's kind of depressed in

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Speaker 2: tech at the moment. It feels like everyone's very negative.

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Speaker 2: And Brian, I know you've been a ton about lat

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Speaker 2: it's obviously, and I'm wondering how we actually reverse this STrenD, Like,

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Speaker 2: how do we actually get away from the fact that

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Speaker 2: everyone feels miserable with their devices right now? Because I

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Speaker 2: love tech. I adore my gizmos, my gadgets, my apps.

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Speaker 2: I don't I care that they're messing with me, and

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Speaker 2: I write a lot about it, but I want everyone

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Speaker 2: else to enjoy it again, I just don't how do

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Speaker 2: we even begin that well.

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Speaker 3: I think that the story that the tech industry wants

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Speaker 3: to tell us is the origin of this depression, because

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Speaker 3: the tech industry wants us to think that you have

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Speaker 3: to take the bad with the good. Right that you know,

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Speaker 3: if you want to have a friend, Mark Zuckerberg has

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Speaker 3: to be your friend too. If you want to search

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Speaker 3: the internet, Sergei Brinn needs to know about it. If

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Speaker 3: you want to have a phone that works, then Tim

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Speaker 3: Apple gets to charge everyone who helps you use it

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Speaker 3: thirty percent of whatever you pay them. And their argument

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Speaker 3: is that like building a phone that works that doesn't

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Speaker 3: have this thirty percent viig is like making water that's

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Speaker 3: not wet, right, right, And that's just like patently untrue.

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Speaker 3: And so I think that, you know, to the extent

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Speaker 3: that we're like God, you know, I like being able

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Speaker 3: to talk to my friends and being able to you know,

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Speaker 3: download a movie without having to go to the video store,

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Speaker 3: and I like all of these other things. I guess

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Speaker 3: I just have to live in the apocalyptic wasteland or

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Speaker 3: I have to go and you know, live in a

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Speaker 3: shack in the woods and be the unibomber. And I'm

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Speaker 3: here to argue that there's like, you know, we could

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Speaker 3: seize the means of computation. We could decompose the prefeast

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Speaker 3: menu into an a la carde little little French content

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Speaker 3: for you then, Brian and we could have a new

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Speaker 3: good Internet that consists of the stuff we like and

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Speaker 3: throws away the stuff that's bad.

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Speaker 1: Yeah, And that's why the you know, the luddite is

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Speaker 1: such a handy epithet for them in its you know,

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Speaker 1: incorrectly deployed sort of context. That's why they use it, right,

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Speaker 1: It's not they say, oh, if you're against any one

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Speaker 1: of those things that Corey just brought up, then you

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Speaker 1: are against in fact the whole of technology. And then

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Speaker 1: we can sort of deride you, we can write you off,

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Speaker 1: we can cast you aside. And it has made for

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Speaker 1: the last twenty years or so at least kind of

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Speaker 1: you know, actual sort of substantive critiques and attempts to

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Speaker 1: reconfigure some of those systems much more difficult. You have

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Speaker 1: to clear that ball bar first, you have to say,

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Speaker 1: you have to start every argument with, well, I'm not

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Speaker 1: a lot I but I actually like technology. But I

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Speaker 1: think that and we are only now kind of reaching

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Speaker 1: a point where we have enough sort of a critical mass,

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Speaker 1: enough momentum where we don't have to sort of, you know,

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Speaker 1: dither around and sort of and make all of that,

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Speaker 1: all of that.

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Speaker 3: Sort of pretext. It's clear now, I think.

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Speaker 1: Add to your point that the Internet is such a

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Speaker 1: festering mass in so many ways that it's just self evident.

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Speaker 1: You log onto this thing and Google barely works. Everything's

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Speaker 1: tracking you, either, surveillance capitalism is at work in every

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Speaker 1: nook and cranny and it's just and anybody who uses

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Speaker 1: that besides just a few isolated apps can kind of

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Speaker 1: feel it. It makes your skin crawl these days. So

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Speaker 1: the task that we have now laid out before us

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Speaker 1: to try to fix this stuff, I think is clear

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Speaker 1: than it ever has been. And I do think, you know,

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Speaker 1: I often get criticized for being a pessimist or a

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Speaker 1: doom sayer, but I'm really not.

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Speaker 3: I'm actually quite idealistic.

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Speaker 1: I think that there's a lot that we can do

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Speaker 1: that's fairly straightforward to start sort of fixing some of

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Speaker 1: this stuff.

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Speaker 3: And I know Corey and are.

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Speaker 2: In agreement on all, but yeah, and I think that, oh,

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Speaker 2: we'll get to where you disagree later. That's where scholar

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Speaker 2: debate is. So because this is the woke Lex Friedmann show,

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Speaker 2: of course. And but the thing I keep coming back

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Speaker 2: to as well is these people who are like, I'm

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Speaker 2: a techno optimist. Not just the people the capital t

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Speaker 2: kept Low Andresen types and the fans of Nick Land,

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Speaker 2: I guess, but even the people criticizing, say tech Crunch

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Speaker 2: for being against I don't know a writer saying fuck

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Speaker 2: people who who don't like who don't like the AI,

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Speaker 2: which is bullshit. Sorry, Connie. The thing is, these people

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Speaker 2: don't seem to like tech. They seem to like business.

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Speaker 2: They don't seem to It's not like I see Bajali

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Speaker 2: sitting around digging around on his fucking iPhone playing a game.

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Speaker 2: I don't see Mark Andreson or hear Mark andries and

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Speaker 2: talk about even using technology. None of these people seem

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Speaker 2: to experience tech. They're just experiencing the ways in which

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Speaker 2: McKinsey and their various outgrowths of Sandwich. They're weigh in

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Speaker 2: between the layers of society and and it's so fucking

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Speaker 2: frustrating because I too, get called a pessimist. I have

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Speaker 2: people on the Reddit, the people who want I don't know,

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Speaker 2: actively stealing the hub caps off of cars as they

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Speaker 2: listen to the show. They're piste off, like, Oh, you

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Speaker 2: just don't like it. You're just being negative, You're just

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Speaker 2: a pessimist. No, I love this shit, and I'm tired

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Speaker 2: of not loving I'm tired of it being bad. Facebook

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Speaker 2: used to be great. I know that that company's deeply evil,

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Speaker 2: even to the early days book.

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Speaker 3: I mean, it was founded so that Mark Zarkerperg and

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Speaker 3: his friends could non consensually rate the fuck ability with

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Speaker 3: their fellow hearts. Undergraduate, it's like truly evil.

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Speaker 2: But then even then there was a good side of it,

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Speaker 2: where like I was in college in two thousand and

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Speaker 2: five and Penn's day when it was going and like there.

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Speaker 3: Was something magical. You suddenly these nights for.

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Speaker 2: Better or for worse that you might have forgotten, or

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Speaker 2: that you might have forgotten moments of these get these

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Speaker 2: shitty digital camera pictures. You have people that you'd met

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Speaker 2: in passing, that you'd never meet again except you could

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Speaker 2: now and now what over fifteen years later, Facebook actively

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Speaker 2: in vines if you try, if you're like, i'd let's

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Speaker 2: find this person, like haha, no, no, no.

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Speaker 3: So I can I draw a distinction. So I think

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Speaker 3: that you're the frame of optimism. Pessimism is not very

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Speaker 3: useful because optimism and pessimism, I think, are our beliefs

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Speaker 3: that don't leave a lot of room for human agency. Right.

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Speaker 3: Optimism is just this idea that the history is running

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Speaker 3: on rails and it's running to a good place, right,

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Speaker 3: And pessimism is the opposite belief. But neither of them

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Speaker 3: really admit of a place where where we act. And

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Speaker 3: I like hope, right, yeah, which is the idea that, like,

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Speaker 3: if you don't like your situation and you don't know

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Speaker 3: how to make it fully better, if you can find

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Speaker 3: even just one thing you can do to materially improve

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Speaker 3: that situation, you will ascend the gradient towards the future

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Speaker 3: that you want. And that as you attain that new

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Speaker 3: vantage point, you may find yourself able to see new

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Speaker 3: ways to make things better that were occulted when you

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Speaker 3: were further down the slope. And so you know, it's

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Speaker 3: not the most efficient way to get from A to Z,

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Speaker 3: but it's it's also much better than trying to treat

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Speaker 3: your activism in your life like a novel. Right. I'm

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Speaker 3: a novelist. I know how novels work. In novels, you

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Speaker 3: have a very neat dramatic arc where you do a thing,

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Speaker 3: and then you do the next thing, and you do

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Speaker 3: the next thing. You build to a climax and either

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Speaker 3: it's triumphant or it's tragic, and then that's the end.

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Speaker 3: In real life, there's a lot of backtracking, and the

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Speaker 3: fact that we can't see a novelistic way from A

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Speaker 3: to Z just tells us that we're living in the

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Speaker 3: real world and not a simulation.

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Speaker 1: So where do we find hope then, Like, really, I

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Speaker 1: think that that is it. Yeah, I mean I and

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Speaker 1: I would just also the sort of comment on that.

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Speaker 1: I do think that there is you know, there's utility

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Speaker 1: in pessimism, right, and there's utility in optimism as well.

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Speaker 1: I don't think it necessarily forecloses any futures necessarily. There's

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Speaker 1: the of course, you know that you have the pessimism

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Speaker 1: of the intellect and the you know, the optimism of

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Speaker 1: the will. I think that's endured for a reason, and

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Speaker 1: I think it's applicable here. And I think these two

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Speaker 1: sort of like brief snapshots that you just offered a

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Speaker 1: Facebook to use it as an example sort of can

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Speaker 1: can be illustrative in a sense, right, Like you you know,

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Speaker 1: it was founded for truly demonic purposes by a troll

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Speaker 1: man who continues to like wield influence over what is

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Speaker 1: now one of the most powerful platforms of all time.

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Speaker 1: And yet in that sort of interim period before it

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Speaker 1: became that from its evil origins, there was this period

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Speaker 1: where users had more power right where they were connecting

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Speaker 1: each other. I mean, some of that was somewhat illusory

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Speaker 1: because they're still subject to all of the you know restrictions. Well,

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Speaker 1: at the very least they Monk Zuckerbug was scared of

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Speaker 1: his us as being upset. Yeah, and there was a

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Speaker 1: you know, the users were dictating the growth. I mean,

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Speaker 1: we had this kind of fertile period twenty years ago

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Speaker 1: or so, especially with Web two point zero, where it

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Speaker 1: was basically the users were taking the lead.

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Speaker 3: Like Twitter was.

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Speaker 1: Like nothing before. Users said, oh what about a hashtag?

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Speaker 1: What about these features? What about you know what, how

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Speaker 1: can we sort of build this into something that's useful

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Speaker 1: for us? And you know, a couple of uh, you know,

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Speaker 1: white dudes in their in their twenties and and and

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Speaker 1: got pretty lucky because they owned some of that infrastructure

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Speaker 1: at the time, but they at least had the the

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Speaker 1: the foresight to sort of let users lead and to

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Speaker 1: see what was you know, what was what was working,

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Speaker 1: what wasn't, what was popular, what what helped. Obviously that's

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Speaker 1: imperfect as a model of genuine of sort of generalized

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Speaker 1: growth too, but it's something that is still powerful to me. Right,

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Speaker 1: we have a more democratic model of developing technology that

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Speaker 1: is not just limited to the company in Silicon Valley,

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Speaker 1: certainly not just limited to one founder, and how do

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Speaker 1: we sort of knock down some.

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Speaker 3: Of those barriers.

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Speaker 1: This is what Corey writes about a lot like especially

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Speaker 1: sort of knocking down sort of the the monopolistic and

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Speaker 1: the oligopolistic instincts and tendencies that these companies have acquired

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Speaker 1: now that they've concentrated so much wealth and power. But

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Speaker 1: we do see flashes of what can be. We still

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Speaker 1: have models of what's still good. I found myself pointing

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Speaker 1: more recently to like, Wikipedia, for all its flaws, still

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Speaker 1: a really interesting organization that still operates and creates really accurate,

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Speaker 1: good and enjoyable and useful information without you know, having

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Speaker 1: succumbed to so many of these immense like pitfalls and

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Speaker 1: become a disgusting cesspool like many of its other contemporaries.

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Speaker 3: You know, I think that what we're getting at here

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Speaker 3: when we talk about what's hopeful about the future and

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Speaker 3: when we look back on the past, is that we

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Speaker 3: see these people who were at very best imperfect I

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Speaker 3: speak as an imperfect person myself, and sometimes actually just

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Speaker 3: genuinely terrible people who nevertheless produce things that we like.

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Speaker 3: And that's a very hopeful thing because it suggests that

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Speaker 3: We don't need perfect people to make good things. We

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Speaker 3: can imperfect vessels can still hold something of value. And

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Speaker 3: so you have to ask yourself, why were they better

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Speaker 3: then and why are they worse now? And Ed, I

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Speaker 3: think you got at it right, right in the bullseye

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Speaker 3: a few minutes ago, when you said Mark Zuckerberg was

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Speaker 3: afraid of his users. Right. So I think that these

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Speaker 3: firms used to be disciplined by external forces, and by

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Speaker 3: some internal forces their workforce, and that they no longer

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Speaker 3: feel that discipline. Right. There was a time when firms

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Speaker 3: worried about competition. Hm, that's not so much a worry anymore.

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Speaker 3: We relaxed anti trust laws, and the long run effect

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Speaker 3: of forty years of relaxed anti trust laws is five

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Speaker 3: giant websites filled with screenshots of text from the other four.

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Speaker 3: In the memorable phrase of Tom Eastman, and so there's

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Speaker 3: nowhere to go, right. Lily Tomlin used to do this

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Speaker 3: bit on Saturday Night Live, where she'd play an AT

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Speaker 3: and T operator doing commercials for the Bell system. They'd

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Speaker 3: end with her turning to the camera and saying, we

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Speaker 3: don't care, we don't have to. We're the phone company.

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Speaker 3: When you have a ninety percent market share and search

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Speaker 3: when you've got twenty five billion dollars a year to

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Speaker 3: spend making sure that nobody ever sees a search engine

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Speaker 3: other than yours, because you're the default everywhere there's a search.

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Speaker 3: Why do you need to make the search good. You're

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Speaker 3: just the only game in town. You don't care, you

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Speaker 3: don't have to your Google. Right, So they didn't have

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Speaker 3: to worry about competition. They used to have to worry

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Speaker 3: about regulation, and we've seen some pretty big regulatory interventions.

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Speaker 3: You know. The real big one was Microsoft and the

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Speaker 3: DOJ for seven years over antitrust. And they don't have

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Speaker 3: to worry about that either anymore because once the sector

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Speaker 3: is really concentrated, it finds it really easy to figure

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Speaker 3: out what their lobbying position is and to stay on message.

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Speaker 3: If you remember the Napster Wars, right, there were like

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Speaker 3: one hundred little tech companies that in aggregate were still

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Speaker 3: much bigger, like orders of magnitude, bigger than seven entertainment companies.

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Speaker 3: The seven entertainment companies kick their ass, yeah, because two

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Speaker 3: hundred companies they're a raval, right, seven companies are a cartel,

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Speaker 3: and so thank you. Yeah. No, the Calltaeil. Thing is

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Speaker 3: my mite.

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Speaker 2: Phil Broughton's safety officer and a nuclear safety ex But

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Speaker 2: in general he's been telling me Calltel, Calltael, Calltel. And

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Speaker 2: I I'm really coming round to this thing that it's

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Speaker 2: not just it's not just about the monopoly. It's about

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Speaker 2: the fact that they're all sitting there shaking each other's hands.

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Speaker 2: Apple being paid at nineteen twenty billion in the year

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Speaker 2: by by by Google to not do.

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Speaker 3: So how is that Google and Facebook carving up the

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Speaker 3: search the ad market with the political collusive Jedi blue

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Speaker 3: arrangement that was revealed by the Texas AG's lawsuit against them.

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Speaker 3: So yeah, I mean, these companies they pretend that they're

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Speaker 3: you know, bitter enemies, but they're all chummy when it

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Speaker 3: comes to the stuff that matters. And you know, once

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Speaker 3: you have your regulators captured, then you also can mobilize

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Speaker 3: law against your adversary. So it's not just about flouting

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Speaker 3: the law, it's about using the law against your enemies.

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Speaker 3: And what used to happen with tech And one of

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Speaker 3: the things you asked what we love about tech? One

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Speaker 3: of the things I love about tech is how flexible

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Speaker 3: it is, right, how you can always change it so

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Speaker 3: that it does what you want. And one of the

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Speaker 3: things that we got out of the concentration in the

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Speaker 3: tech sector is a capture of regulators that led to

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Speaker 3: an expansion of IP law that has now made it

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Speaker 3: illegal to reconfigure your own stuff.

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Speaker 1: Right.

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Speaker 3: So imagine that this the three of us. We're having

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Speaker 3: a board meeting about our ad strategy for our website,

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Speaker 3: and you're chairing it at and you say, well, guys,

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Speaker 3: our KPI, here is AD revenue top line AD revenue.

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Speaker 3: I figured out we make the ads twenty percent more obnoxious,

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Speaker 3: we get two percent more top line revenue. Brian, who

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Speaker 3: may not give a damn about users, can still stick

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Speaker 3: his hand up and say, ad, has it occurred to

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Speaker 3: you that when we make the ads twenty percent more obnoxious,

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Speaker 3: forty percent of our users will type how do I

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Speaker 3: block ads? Into a search box? And then our revenue

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Speaker 3: from those users goes to zero forever because they're never

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Speaker 3: going back to type how do I start seeing ads again?

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Speaker 3: And so when you raise the price of ink, you

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Speaker 3: have to worry about third party in cartridges. When you

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Speaker 3: make MySpace terrible, you have to worry about bots that

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Speaker 3: let people leave my space, but still have their messages

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Speaker 3: imported into Facebook. You know, all these things that made

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Speaker 3: it very easy to lower the switching costs and go

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Speaker 3: where you wanted. Well, IP laws basically made that illegal.

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Speaker 3: Jay Freeman calls it felony contempt a business model where

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Speaker 3: break DRM or violating terms of services become a crime.

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Speaker 3: And so companies just put DRM in terms of service

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Speaker 3: around their stuff so that anything you do that displeases

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Speaker 3: their shareholders as a felony. And then the last thing

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Speaker 3: that used to discipline these companies, something near and Derda

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Speaker 3: Bryan's in my heart, was their workforce. Yes, because tech

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Speaker 3: workers were powerful, there weren't enough of them, and they

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Speaker 3: could get a job somewhere else. And yeah, their bosses

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Speaker 3: suckered them into working every hour that God sent by

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Speaker 3: telling them they were on a holy mission, and so

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Speaker 3: they missed their mother's funeral and their kids litteral league

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Speaker 3: game to ship the product on time. But that did

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Speaker 3: mean that they would feel profound moral injury when their

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Speaker 3: boss said let's make this shitty, and because they could

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Speaker 3: get a job somewhere else, they would tell their boss

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Speaker 3: to go fuck themselves. But two hundred and sixty thousand

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Speaker 3: tech layoffs last year one hundred thousand year to date

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Speaker 3: this year, tech workers aren't telling their bosses to go

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Speaker 3: fuck themselves. And so you have a boss who every

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Speaker 3: day went to the wall where there's a giant lever

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Speaker 3: labeled in shitification and yanked it as hard as it could.

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Speaker 3: And they couldn't get that lever to budge very far. Competition, regulation,

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Speaker 3: their own workforce, interoperable hacks, they all kept the lever

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Speaker 3: from moving freely. Now the lever just goes all the

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Speaker 3: way to one hundred, and from the boss's perspective, they're

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Speaker 3: just doing what they did every day of their lives.

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Speaker 3: They don't know why we're so angry at them.

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Speaker 1: Yeah, And I think this also circles back to, you

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Speaker 1: know that what we were talking about earlier about you know,

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Speaker 1: the need and the imperative to sort of be critical

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Speaker 1: and to sort of oppose certain aspects of how tech

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Speaker 1: and tech companies especially are unfolding. Because the current state

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Speaker 1: of play, all these things that Corey's describing that are

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Speaker 1: absolutely true that you know, they didn't just you know,

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Speaker 1: they didn't arrive prepackaged that way. I love that you

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Speaker 1: just walked us through all all those three things that

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Speaker 1: no longer happen, and it's in large part a result

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Speaker 1: because there were a lot of missed opportunities to regulate

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Speaker 1: a lot of missed opportunities to sort of constrict this

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Speaker 1: growth before it became. My favorite example is, like, I

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Speaker 1: think it was twenty thirteen when the Obama administration had

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Speaker 1: a chance to sue Google for when it became quite

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Speaker 1: clear that it was engaging in monopolistic behavior and it

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Speaker 1: was becoming sort of a monopoly of search, and they

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Speaker 1: basically just kind of let them off with the slightest

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Speaker 1: slap on the wrist possible and said go for it.

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Speaker 1: I mean, we all think about tech today and all

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Speaker 1: these people who are you.

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Speaker 3: Know what happened there?

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Speaker 1: Exactly what happened there? It was so Obama. I mean,

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Speaker 1: how far back do we want to go.

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Speaker 2: That specifically twenty thirteen era, because there's the current antitrust

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Speaker 2: lawsuit now, But what was the predecessor.

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Speaker 1: Well, it was just there was an FTC probe and

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Speaker 1: basically the Obama administration could have sort of green green

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Speaker 1: lit a more aggressive investigation, a more aggressive suit into

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Speaker 1: Google's monopoly practices. You know, this was ten years ago,

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Speaker 1: so it was before it had become so sort of

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Speaker 1: like obviously and so stultifyingly sort of the want what

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Speaker 1: does it have ninety percent of the search market, So

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Speaker 1: it's literally it's just like the textbook definition.

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Speaker 3: Of an search. So it's twenty thirteen. So that's right.

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Speaker 2: So Prabagod Ragavan at this point had joined Google. Going

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Speaker 2: back to the man who killed Google Search my favorite story,

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Speaker 2: real piece of.

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Speaker 3: Shit, motherfucker there, Probagod, come on the shell. I'll take you.

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Speaker 3: I'll take you out in the mic.

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Speaker 2: But what's interesting is that does time really interestingly with that,

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Speaker 2: so that that interrogation never happened, They never really went deep,

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Speaker 2: and just then they hired Prabagarth from Yahoo after he's

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Speaker 2: done his work destroying Yahoo's search, and that was when

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Speaker 2: Google began to sour. And it feels like that could

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Speaker 2: have been a complete that's a historic moment. That's a

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Speaker 2: moment where everything could have changed.

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Speaker 1: I mean, it was one moment of you know, a

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Speaker 1: number that they could have but yeah, and you know,

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Speaker 1: Corey has documented what's happened.

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Speaker 3: Since it's just old school.

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Speaker 1: Payola practices, right like Google has just sort of really

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Speaker 1: just kind of strangled the market, not through innovation, not

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Speaker 1: through introducing great products or ensuring that the user has

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Speaker 1: the best experience, but just by you know, sheer force of.

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Speaker 3: Paying people out.

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Speaker 1: The Apple deal is a great example, just literally just

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Speaker 1: funneling billions to another tech company to make sure that

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Speaker 1: its product shows up at the top of another tech

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Speaker 1: products you know service.

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Speaker 3: So, yeah, you know, I think that if we want

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Speaker 3: to understand why Obama took the decision he did and

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Speaker 3: what's changed, you have to understand that during the Carter administration, right,

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Speaker 3: so we have to go way back, we started to

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Speaker 3: see the rise of a crank theory of anti trust law,

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Speaker 3: and that Crank theory was that anti trust law was

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Speaker 3: being misapplied that if you saw monopoly in the wild,

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Speaker 3: what you'd actually encountered was something that was very efficient. Right,

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Speaker 3: if everyone goes and buys the same product at the

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Speaker 3: same store, uses the same search engine, it's the best.

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Speaker 3: Wouldn't it be perverse for the government to spend public

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Speaker 3: money to take the best product and make it worse, Right,

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Speaker 3: And so that was the theory that we got under Carter.

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Speaker 3: Reagan really liked it because of very monopoly friendly, and

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Speaker 3: every administration since has brought into it as did every

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Speaker 3: economic school in the country and eventually in the world.

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Speaker 3: This is a very thatchery kind of ideology, but it

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Speaker 3: also heard in the EU, thank you, and you know

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Speaker 3: that these ideas kind of raced around the world and

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Speaker 3: became orthodoxy, and they were funded by very rich people.

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Speaker 3: So there's a thing called the man seminar m a

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Speaker 3: NN that is sorry. So the man seminars are these

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Speaker 3: free junkets for federal judges where they teach them about

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Speaker 3: anti trust law and they're run by rich guys and

434
00:21:37,240 --> 00:21:40,720
Speaker 3: they fly them to luxury resorts and they explain how

435
00:21:40,760 --> 00:21:42,960
Speaker 3: anti trust law should work. And there's been quantitative work

436
00:21:42,960 --> 00:21:45,160
Speaker 3: on this where they took federal judges and they looked

437
00:21:45,160 --> 00:21:47,879
Speaker 3: at their decisions before and after going to a man seminar,

438
00:21:47,880 --> 00:21:49,760
Speaker 3: and they found that after going to a man seminar,

439
00:21:50,160 --> 00:21:52,919
Speaker 3: they weighed more heavily in favor of monopoly. And so

440
00:21:52,960 --> 00:21:57,280
Speaker 3: they built up this evidouce edifice rather of precedent and

441
00:21:57,400 --> 00:22:01,719
Speaker 3: theory and orthodoxy. And Obama's FTC said, oh, We're going

442
00:22:01,760 --> 00:22:03,840
Speaker 3: to let them walk. What they were doing was just

443
00:22:03,920 --> 00:22:10,640
Speaker 3: continuing a grand tradition of Bush one, Bush two, Reagan, Carter, Clinton,

444
00:22:10,920 --> 00:22:13,800
Speaker 3: right like this was the way that things were done.

445
00:22:13,880 --> 00:22:17,280
Speaker 3: It was an absolutely wasted opportunity. But it's more or

446
00:22:17,359 --> 00:22:20,560
Speaker 3: less what Trump did afterwards, and it's what we did

447
00:22:20,600 --> 00:22:24,560
Speaker 3: all the way up to the Biden administration, which for

448
00:22:24,680 --> 00:22:26,960
Speaker 3: reasons I think that have nothing to do with Biden's

449
00:22:26,960 --> 00:22:29,400
Speaker 3: own ideology, but have everything to do with the way

450
00:22:29,440 --> 00:22:33,160
Speaker 3: that he operates as a party powerbroker, where he wants

451
00:22:33,200 --> 00:22:36,560
Speaker 3: to give everyone a little as something. We got a

452
00:22:36,600 --> 00:22:39,280
Speaker 3: handful of appointees at the tops of some of the

453
00:22:39,359 --> 00:22:45,359
Speaker 3: most important agencies that really oriented themselves towards smashing corporate power.

454
00:22:46,040 --> 00:22:48,320
Speaker 3: Lena Kahn at the Federal Trade Commission, Jonathan Canter at

455
00:22:48,320 --> 00:22:50,840
Speaker 3: the DOJ Anti Trust Division, Tim Woho's in the White

456
00:22:50,880 --> 00:22:54,560
Speaker 3: House for several years, and so on, and these people

457
00:22:55,359 --> 00:23:00,080
Speaker 3: have really transformed things. We've seen more policy transformation in

458
00:23:00,080 --> 00:23:02,120
Speaker 3: the last four years than in the last forty. It's

459
00:23:02,200 --> 00:23:05,879
Speaker 3: it's been head spinningly great. It's wonky, it's hard to

460
00:23:05,920 --> 00:23:09,280
Speaker 3: get your head around. It's very structural, right, it's about

461
00:23:09,320 --> 00:23:11,680
Speaker 3: changing the rules of the game, which takes a while

462
00:23:11,720 --> 00:23:14,879
Speaker 3: to show up in the game. Right, But boy, oh boy,

463
00:23:15,040 --> 00:23:18,600
Speaker 3: it's pretty substantial. Do you think it could go anywhere? Though?

464
00:23:18,680 --> 00:23:21,280
Speaker 2: Do you actually we talk about hope. Should we have

465
00:23:21,359 --> 00:23:21,879
Speaker 2: hope from this?

466
00:23:22,640 --> 00:23:25,960
Speaker 1: I mean, it's it's it's very it's very tenuous. It

467
00:23:25,960 --> 00:23:29,000
Speaker 1: has been great, you know Lina con in particular. I mean,

468
00:23:29,000 --> 00:23:31,840
Speaker 1: I wish the administration would do kind of a better

469
00:23:31,960 --> 00:23:34,399
Speaker 1: job of touting its wins because all this stuff is

470
00:23:34,480 --> 00:23:38,440
Speaker 1: just so popular. What Lenakon has done in awakening sort

471
00:23:38,480 --> 00:23:42,160
Speaker 1: of the FTC from its kind of kind of coma.

472
00:23:42,359 --> 00:23:45,440
Speaker 1: Yeah it's coma, it's in decades long coma. And then

473
00:23:45,520 --> 00:23:49,359
Speaker 1: attacking some I mean, who doesn't hate Ticketmaster? Like who

474
00:23:49,400 --> 00:23:52,159
Speaker 1: doesn't you know, who who loves logging onto the Internet

475
00:23:52,200 --> 00:23:55,560
Speaker 1: as it is today? Like these are these are entities

476
00:23:55,760 --> 00:23:57,400
Speaker 1: that are popular to go.

477
00:23:57,240 --> 00:23:59,200
Speaker 3: After junk fees, non competes.

478
00:23:59,440 --> 00:24:03,000
Speaker 1: Yeah, how Amazon which has recently turned so hostile to

479
00:24:03,119 --> 00:24:06,120
Speaker 1: its own, you know, third party vendors and small businesses

480
00:24:06,160 --> 00:24:09,000
Speaker 1: that that it relies on to operate that it's strangling.

481
00:24:10,000 --> 00:24:11,920
Speaker 1: This is a perfect example of what the you know,

482
00:24:12,200 --> 00:24:14,520
Speaker 1: the Democrats and Biden are supposed to be all about

483
00:24:14,520 --> 00:24:17,080
Speaker 1: standing up for you know this, the little guy, the

484
00:24:17,080 --> 00:24:21,120
Speaker 1: small business owners, you know. And I think the problem

485
00:24:21,119 --> 00:24:23,800
Speaker 1: with all of these gains is that they're just tethered

486
00:24:23,840 --> 00:24:24,800
Speaker 1: to an administration.

487
00:24:25,000 --> 00:24:26,160
Speaker 3: Right, so if.

488
00:24:26,640 --> 00:24:28,679
Speaker 1: If Trump, I mean some some of them, you know,

489
00:24:29,640 --> 00:24:32,520
Speaker 1: some of them could could be more durable.

490
00:24:32,800 --> 00:24:34,359
Speaker 3: They could be. But I mean Lina con is not

491
00:24:34,359 --> 00:24:36,280
Speaker 3: going to be the head of the FDC if Trump wins.

492
00:24:36,320 --> 00:24:38,240
Speaker 3: They're already coming for Yeah.

493
00:24:39,119 --> 00:24:41,880
Speaker 1: Well, I mean Democratic donors are coming for her too,

494
00:24:42,000 --> 00:24:44,639
Speaker 1: because tech companies don't like Lena Khan either.

495
00:24:44,720 --> 00:24:45,920
Speaker 3: So you have guys like I think it was, is

496
00:24:45,960 --> 00:24:49,359
Speaker 3: it Reid Hoffman? Yeah? Oh god, but that company that

497
00:24:49,440 --> 00:24:51,920
Speaker 3: just turned down a thirty six billion dollar acquisition offer

498
00:24:51,920 --> 00:24:53,760
Speaker 3: from Google did so because they didn't want to go

499
00:24:53,800 --> 00:24:57,040
Speaker 3: through that wizy trust. Hell it is the security company. Yeah,

500
00:24:57,080 --> 00:24:59,920
Speaker 3: And so you know, you have had, if nothing else,

501
00:25:00,080 --> 00:25:03,800
Speaker 3: four years of companies not being acquired and instead trying

502
00:25:03,800 --> 00:25:06,359
Speaker 3: to be product led and make a thing that people

503
00:25:06,400 --> 00:25:08,359
Speaker 3: want that they can sell for more than a cost

504
00:25:08,359 --> 00:25:09,680
Speaker 3: to make them, which is you.

505
00:25:09,640 --> 00:25:12,879
Speaker 2: Know, that's an insane I don't.

506
00:25:13,520 --> 00:25:16,959
Speaker 3: I was raised by socialists, it's right, and even I

507
00:25:17,000 --> 00:25:19,840
Speaker 3: can recognize that this is what capitalism is supposed to look.

508
00:25:19,880 --> 00:25:22,720
Speaker 2: Like my dad ran apart of the NHS, like I'm

509
00:25:22,800 --> 00:25:25,119
Speaker 2: the same way. But also this is also something that

510
00:25:25,119 --> 00:25:27,399
Speaker 2: really fucking bothers me about. Take you showed me your

511
00:25:27,400 --> 00:25:30,520
Speaker 2: framework laptop beforehand, and for the listeners, the framework is

512
00:25:30,760 --> 00:25:33,080
Speaker 2: a laptop that you can actually effectively rebuild, replace the

513
00:25:33,160 --> 00:25:35,359
Speaker 2: motherboard and the screen and all these things. As a

514
00:25:35,400 --> 00:25:38,040
Speaker 2: regular user. There is still cool shit happening. But also

515
00:25:38,160 --> 00:25:40,240
Speaker 2: I assume that company makes more money than it spends

516
00:25:40,240 --> 00:25:43,600
Speaker 2: on its stuff. Take can do this, and I feel

517
00:25:43,640 --> 00:25:48,080
Speaker 2: like the Commons, there's this weird paradox at the moment,

518
00:25:48,160 --> 00:25:52,040
Speaker 2: we've got Take saying well, it's actually these companies should

519
00:25:52,040 --> 00:25:54,800
Speaker 2: be able to quote Ilia Suitskava formerly of open Ai,

520
00:25:55,200 --> 00:25:58,360
Speaker 2: we should be able to scale in peace. I by

521
00:25:58,400 --> 00:26:01,120
Speaker 2: the way, Ilia, if you some here this, you will

522
00:26:01,119 --> 00:26:02,720
Speaker 2: never have a moment of piece. As long as I

523
00:26:02,760 --> 00:26:04,520
Speaker 2: have a microphone. Now that you said that, I'm going

524
00:26:04,560 --> 00:26:06,600
Speaker 2: to be watching you, I'm going to be popping out

525
00:26:06,640 --> 00:26:09,240
Speaker 2: of the toilet like the skibberty meme that the children

526
00:26:09,280 --> 00:26:12,199
Speaker 2: look at. But the thing that frustrates me is they

527
00:26:12,200 --> 00:26:13,920
Speaker 2: want this world where they can burn as much money

528
00:26:13,920 --> 00:26:17,399
Speaker 2: as possible, but also the biggest of them can print money,

529
00:26:17,760 --> 00:26:21,520
Speaker 2: prints so much money, more money than any company should

530
00:26:21,560 --> 00:26:25,880
Speaker 2: have while also providing their services. And it's just how

531
00:26:26,000 --> 00:26:28,960
Speaker 2: is it? How do they not want to be the

532
00:26:29,000 --> 00:26:31,240
Speaker 2: company that just makes more money than they spend that

533
00:26:31,280 --> 00:26:31,879
Speaker 2: people like.

534
00:26:32,920 --> 00:26:34,560
Speaker 3: And is it just that they don't give a shit?

535
00:26:34,680 --> 00:26:36,040
Speaker 3: Is it? Is it sunned up a shy and his

536
00:26:36,119 --> 00:26:39,240
Speaker 3: ilk just don't care. Well. I think that what you're

537
00:26:39,280 --> 00:26:42,480
Speaker 3: looking for, the Fraser looking for here is what Lina

538
00:26:42,520 --> 00:26:46,200
Speaker 3: Khan calls too big to care. Right if you think

539
00:26:46,240 --> 00:26:48,760
Speaker 3: back to the moral philosophers of capitalism or you know,

540
00:26:48,960 --> 00:26:52,080
Speaker 3: writing at the time of the Light Eyed uprisings, and

541
00:26:52,119 --> 00:26:54,280
Speaker 3: they were saying, look that the thing that i'm a

542
00:26:54,400 --> 00:26:57,600
Speaker 3: profit driven economy as opposed to a rent driven economy

543
00:26:57,680 --> 00:27:02,199
Speaker 3: will get us is a world in which, instead of

544
00:27:02,240 --> 00:27:04,520
Speaker 3: the lord knowing that the peasants will have to bring

545
00:27:04,520 --> 00:27:06,879
Speaker 3: in the harvest every year because they're legally obliged to

546
00:27:06,960 --> 00:27:10,320
Speaker 3: they can't leave the land, the lord, the capitalist will

547
00:27:10,320 --> 00:27:14,080
Speaker 3: have to mobilize capital, bring free labor into contact with it,

548
00:27:14,119 --> 00:27:17,960
Speaker 3: alienate them from the surplus of that labor, and watch

549
00:27:18,000 --> 00:27:20,359
Speaker 3: over their shoulder all the time for someone who shows

550
00:27:20,440 --> 00:27:23,400
Speaker 3: up with a better machine, a better process, a better

551
00:27:23,440 --> 00:27:25,840
Speaker 3: pitch for their workers. You know, if you own the

552
00:27:25,840 --> 00:27:28,679
Speaker 3: building that a coffee shop is in, and that coffee

553
00:27:28,680 --> 00:27:30,919
Speaker 3: shop goes bankrupt because a better coffee shop is just

554
00:27:30,960 --> 00:27:34,679
Speaker 3: open across the street. You're fine. Actually you're great, because

555
00:27:34,680 --> 00:27:36,480
Speaker 3: now you have an empty storefront. You could rent on

556
00:27:36,520 --> 00:27:38,840
Speaker 3: the same block as this new hot coffee shop. Right,

557
00:27:38,960 --> 00:27:41,160
Speaker 3: if you own the coffee shop, if you're the capitalist

558
00:27:41,200 --> 00:27:44,080
Speaker 3: as opposed to the rontier, you're fucked. And so every

559
00:27:44,080 --> 00:27:47,840
Speaker 3: capitalist aspires to being a rontier. Right. They don't want

560
00:27:47,880 --> 00:27:50,720
Speaker 3: to operate in an environment in which they're like the

561
00:27:50,840 --> 00:27:53,119
Speaker 3: fastest gun in the West, who's always waiting for that

562
00:27:53,240 --> 00:27:56,280
Speaker 3: kid to show up and say draw Brian.

563
00:27:56,480 --> 00:27:59,880
Speaker 2: Actually, Bridgingenolf of that is well, I think it's time

564
00:27:59,920 --> 00:28:01,639
Speaker 2: to much the oscy just very bas what did the

565
00:28:01,720 --> 00:28:04,159
Speaker 2: Ludites actually ask for? Because I've heard people who do

566
00:28:04,160 --> 00:28:06,399
Speaker 2: not like this. They're in people who do. But explain

567
00:28:06,440 --> 00:28:09,480
Speaker 2: for the listeners because you hear this phrase Ludism mentioned

568
00:28:09,720 --> 00:28:10,320
Speaker 2: quite long.

569
00:28:10,680 --> 00:28:13,520
Speaker 1: Yeah, well, you know, so there's no there's there's no

570
00:28:14,800 --> 00:28:17,560
Speaker 1: you know, enduring lud eighte manifesto that where all the

571
00:28:17,600 --> 00:28:18,960
Speaker 1: lud Eites and the people who were out on the

572
00:28:18,960 --> 00:28:21,200
Speaker 1: streets who are part of the campaign, you know, of

573
00:28:21,240 --> 00:28:29,320
Speaker 1: the of the eighteen tens who were organizing basically against

574
00:28:29,840 --> 00:28:31,920
Speaker 1: this new sort of you know, this new this new

575
00:28:31,960 --> 00:28:35,760
Speaker 1: class of entrepreneur that was rising up to to basically

576
00:28:35,800 --> 00:28:39,840
Speaker 1: exploit their labor, to use machinery, to uh, to divide labor,

577
00:28:39,920 --> 00:28:43,400
Speaker 1: to to use children to run it, and to sort

578
00:28:43,400 --> 00:28:46,400
Speaker 1: of may force them to compete and to sort of

579
00:28:46,600 --> 00:28:49,280
Speaker 1: and to drive down their wages. So they are against

580
00:28:49,400 --> 00:28:51,760
Speaker 1: The Ludites are basically against all that they were.

581
00:28:51,760 --> 00:28:54,680
Speaker 3: Truly a They were.

582
00:28:54,520 --> 00:28:57,600
Speaker 1: In many ways, you know, a reactionary force. They had

583
00:28:57,600 --> 00:29:00,600
Speaker 1: their back against the wall. They weren't a pro active

584
00:29:00,680 --> 00:29:03,440
Speaker 1: political party or anything like that. So you can't necessarily

585
00:29:03,520 --> 00:29:06,520
Speaker 1: say every Ledite believe this or this is what they wanted.

586
00:29:06,720 --> 00:29:08,240
Speaker 3: But there are a number of things that.

587
00:29:08,200 --> 00:29:11,040
Speaker 1: Are clear about what they were that what they were seeking,

588
00:29:12,240 --> 00:29:15,360
Speaker 1: and you can really boil it down to basically a

589
00:29:15,400 --> 00:29:16,240
Speaker 1: seat at the table.

590
00:29:17,440 --> 00:29:19,320
Speaker 3: This was a profoundly.

591
00:29:18,840 --> 00:29:22,120
Speaker 1: Anti democratic way to develop and deploy technology that they

592
00:29:22,120 --> 00:29:25,800
Speaker 1: were experiencing, and they went to great lengths even before

593
00:29:25,800 --> 00:29:28,240
Speaker 1: they became Luddites to point this out. They went to

594
00:29:28,280 --> 00:29:31,880
Speaker 1: Parliament and said, these new machines are being bought up

595
00:29:31,920 --> 00:29:35,360
Speaker 1: by this new rising class of capitalists. They are being

596
00:29:35,400 --> 00:29:40,960
Speaker 1: staffed by either migrant workers or children, or precarious.

597
00:29:40,360 --> 00:29:44,720
Speaker 4: Workers Napoleonic war orphans, right exactly, they literally would pipe

598
00:29:44,720 --> 00:29:48,520
Speaker 4: in orphans from London into these factories to staff them,

599
00:29:48,720 --> 00:29:53,000
Speaker 4: and they wouldn't pay them until they turned eighteen. They

600
00:29:53,720 --> 00:29:56,600
Speaker 4: and so the Luddites or the people who became Luedites

601
00:29:56,680 --> 00:29:58,440
Speaker 4: would point this out and they would ask for some

602
00:29:58,600 --> 00:30:02,520
Speaker 4: very basic, very common sense reforms, asking for minimum wages,

603
00:30:02,680 --> 00:30:06,800
Speaker 4: protections from fraud. And that went on for ten years,

604
00:30:06,840 --> 00:30:09,200
Speaker 4: and they got laughed out of Parliament time and time

605
00:30:09,240 --> 00:30:12,200
Speaker 4: again until those any regulations that did govern the trade

606
00:30:12,240 --> 00:30:16,440
Speaker 4: were thrown up altogether. And so when the Luddites become Lutdites,

607
00:30:16,880 --> 00:30:20,600
Speaker 4: they're basically protesting all of the above, the fact that

608
00:30:20,640 --> 00:30:23,800
Speaker 4: this was a profoundly undemocratic process that they are being

609
00:30:23,880 --> 00:30:28,360
Speaker 4: forced to uh to either succumb, to either go work

610
00:30:28,400 --> 00:30:32,400
Speaker 4: in the factories or to give find it, give up,

611
00:30:32,440 --> 00:30:34,440
Speaker 4: which wasn't an option. By the way, This isn't a

612
00:30:34,440 --> 00:30:38,440
Speaker 4: diverse economy of you know that we recognize today right

613
00:30:38,520 --> 00:30:39,240
Speaker 4: exactly learned it.

614
00:30:39,280 --> 00:30:41,360
Speaker 1: You can't even learn to code. You grew up in

615
00:30:41,360 --> 00:30:45,320
Speaker 1: a weaving town. Guess what you're John's pretty limited to weaving.

616
00:30:45,400 --> 00:30:48,320
Speaker 1: So these are people who are remarkably at the at

617
00:30:48,600 --> 00:30:50,479
Speaker 1: sort of the whims of the market. And when the

618
00:30:50,480 --> 00:30:53,480
Speaker 1: market was as poor as it was, and these capitalists

619
00:30:53,520 --> 00:30:56,160
Speaker 1: were in control of it to the extent that they were.

620
00:30:57,000 --> 00:30:59,480
Speaker 1: You know, they tried, they tried to reason with a

621
00:30:59,480 --> 00:31:03,320
Speaker 1: lot of these uh, these factory owners. They tried before

622
00:31:03,520 --> 00:31:06,320
Speaker 1: it came to it came to what it came to

623
00:31:06,360 --> 00:31:09,000
Speaker 1: when they sort of organized this gorilla rebellion that was

624
00:31:09,360 --> 00:31:11,719
Speaker 1: incredibly popular that they you know, this was the new

625
00:31:11,800 --> 00:31:15,880
Speaker 1: Robin Hood movement basically, and what they wanted was, yeah,

626
00:31:15,920 --> 00:31:18,680
Speaker 1: a seat at the table. They opposed the machinery hurtful

627
00:31:18,720 --> 00:31:20,800
Speaker 1: to commonality that was align well must it.

628
00:31:20,800 --> 00:31:24,000
Speaker 2: Seems like it wasn't, because the common misunderstanding if lotism

629
00:31:24,080 --> 00:31:26,680
Speaker 2: is that they just wanted to destroy the machines because

630
00:31:26,680 --> 00:31:29,080
Speaker 2: they didn't like them. And it sounds like, I don't know,

631
00:31:29,360 --> 00:31:31,720
Speaker 2: if the market forces would have given a seat the

632
00:31:31,720 --> 00:31:34,080
Speaker 2: table for the workers, they might not fucking resent.

633
00:31:33,880 --> 00:31:35,920
Speaker 1: Under Yeah, I heard Cory, you make this make this

634
00:31:36,160 --> 00:31:38,880
Speaker 1: observation too again. If like someone had come to town

635
00:31:38,920 --> 00:31:41,240
Speaker 1: with the machine and said, all right, let's figure this out.

636
00:31:41,320 --> 00:31:43,800
Speaker 1: Let's get together, like, how can we all benefit from

637
00:31:43,800 --> 00:31:44,400
Speaker 1: this machine?

638
00:31:44,440 --> 00:31:45,240
Speaker 3: I saw it over there.

639
00:31:45,280 --> 00:31:47,800
Speaker 1: I bet the whole town could really benefit from having

640
00:31:47,880 --> 00:31:50,080
Speaker 1: access to this machine that makes our working lives a

641
00:31:50,120 --> 00:31:50,440
Speaker 1: little bit.

642
00:31:50,480 --> 00:31:52,560
Speaker 2: Maybe to make the machine better. If we talk to

643
00:31:52,560 --> 00:31:53,520
Speaker 2: the people who'd use it.

644
00:31:53,560 --> 00:31:55,400
Speaker 1: Yeah, maybe we can all make a little bit more

645
00:31:55,400 --> 00:31:58,200
Speaker 1: money together. You still have your if you're if you're

646
00:31:58,320 --> 00:32:02,080
Speaker 1: the you know, the merchant capitalist who was you know before,

647
00:32:02,200 --> 00:32:04,200
Speaker 1: was kind of the middleman in charge of distribution.

648
00:32:04,560 --> 00:32:07,239
Speaker 3: Maybe this will make you more money too. But it

649
00:32:07,240 --> 00:32:08,120
Speaker 3: didn't work like that.

650
00:32:08,520 --> 00:32:13,040
Speaker 1: It always developed where either somebody would come in from

651
00:32:13,040 --> 00:32:15,720
Speaker 1: out of town with a lot of money and be

652
00:32:15,960 --> 00:32:19,520
Speaker 1: set up something truly enormous, or a factory or owner

653
00:32:19,560 --> 00:32:25,360
Speaker 1: would recognize, or a prospective factory owner would recognize the capacity,

654
00:32:25,400 --> 00:32:28,320
Speaker 1: the productive capacity of these new machines and then try

655
00:32:28,320 --> 00:32:31,920
Speaker 1: to build them for personal gain. And this whole process

656
00:32:32,560 --> 00:32:36,640
Speaker 1: really was deeply conflicting to the vast majority of factory

657
00:32:36,680 --> 00:32:39,800
Speaker 1: owners too, because they saw a handful of people using

658
00:32:39,840 --> 00:32:42,160
Speaker 1: the machines this way in a way that then at

659
00:32:42,160 --> 00:32:46,120
Speaker 1: the time was very clearly corrosive to the social contract. Right,

660
00:32:46,120 --> 00:32:48,520
Speaker 1: if you have one person saying I'm gonna use this machine,

661
00:32:48,560 --> 00:32:50,320
Speaker 1: I'm gonna hire kids to run it, I'm gonna sort

662
00:32:50,320 --> 00:32:52,520
Speaker 1: of profit as much as I can drive prices as

663
00:32:52,560 --> 00:32:54,840
Speaker 1: low as I can to get these guys. You're fucking

664
00:32:54,920 --> 00:32:58,200
Speaker 1: up the entire town economy, You're fucking over your neighbors.

665
00:32:58,400 --> 00:33:00,760
Speaker 1: It's a disgusting thing to do. And you were hated

666
00:33:00,760 --> 00:33:02,840
Speaker 1: for it. So the people who did it were willing

667
00:33:02,880 --> 00:33:05,600
Speaker 1: to be hated. They were willing, they were they were

668
00:33:05,600 --> 00:33:08,240
Speaker 1: the ones who were willing to take that ire. And

669
00:33:08,480 --> 00:33:10,680
Speaker 1: few were. And a lot of some people walked away

670
00:33:10,680 --> 00:33:14,120
Speaker 1: from the trade rather than you know, automate their machines,

671
00:33:14,200 --> 00:33:16,760
Speaker 1: and and some you know, sided with the Ludites and

672
00:33:16,800 --> 00:33:18,840
Speaker 1: were quietly kind of like cheering, like, yeah, go smash

673
00:33:18,840 --> 00:33:22,920
Speaker 1: those guys factories. But by and large, you know who

674
00:33:22,960 --> 00:33:24,960
Speaker 1: did the state. Once the state threw its lot in

675
00:33:25,240 --> 00:33:27,680
Speaker 1: with with with with the factory and back them up

676
00:33:27,720 --> 00:33:30,520
Speaker 1: with arms and with with punitive policies, it was, you know,

677
00:33:30,560 --> 00:33:31,040
Speaker 1: pretty clear.

678
00:33:31,040 --> 00:33:32,400
Speaker 3: I was going. I want to point out two things

679
00:33:32,440 --> 00:33:35,120
Speaker 3: that I think are really important that that Brian omitted here.

680
00:33:35,160 --> 00:33:37,280
Speaker 3: The first one is that Brian wrote the definitive book

681
00:33:37,280 --> 00:33:39,760
Speaker 3: about Yes, it's called Blood in the Machine. You should

682
00:33:39,800 --> 00:33:41,920
Speaker 3: read it. It's very good. And the second one, which

683
00:33:41,960 --> 00:33:44,280
Speaker 3: I think you just you skipped over maybe too quickly,

684
00:33:44,880 --> 00:33:47,600
Speaker 3: is that they already had the legal right to a

685
00:33:47,640 --> 00:33:50,080
Speaker 3: seat at the table. They did. There were laws in

686
00:33:50,160 --> 00:33:53,720
Speaker 3: Parliament that gave them that right. The firms involved were

687
00:33:53,760 --> 00:33:57,160
Speaker 3: moving fast and breaking things, and the Luodites went to

688
00:33:57,240 --> 00:34:01,320
Speaker 3: Parliament and said, we would like the law obey right.

689
00:34:01,400 --> 00:34:03,400
Speaker 3: And this is this is an early example of of

690
00:34:03,440 --> 00:34:07,120
Speaker 3: Wellhet's law. You know that that capitalism consists of exactly

691
00:34:07,320 --> 00:34:11,000
Speaker 3: or or conservatism consists of exactly one proposition that there

692
00:34:11,000 --> 00:34:13,920
Speaker 3: should be powerful people whom the law protects but does

693
00:34:13,960 --> 00:34:16,400
Speaker 3: not bind, and everyone else whom the law binds but

694
00:34:16,440 --> 00:34:18,800
Speaker 3: does not protect right. And this is what the Luddites

695
00:34:18,840 --> 00:34:21,120
Speaker 3: were actually. You know, the thing that drove them into

696
00:34:21,120 --> 00:34:25,800
Speaker 3: the streets was they they watched these people effectively stealing

697
00:34:25,840 --> 00:34:28,440
Speaker 3: from them and Parliament going along with it, and they

698
00:34:28,440 --> 00:34:30,880
Speaker 3: were like, well, I guess we just got to do

699
00:34:30,920 --> 00:34:31,799
Speaker 3: some self defense here.

700
00:34:31,880 --> 00:34:35,240
Speaker 2: And I think you can draw a direct fucking line

701
00:34:35,239 --> 00:34:40,480
Speaker 2: from this from Luddites to people who would call someone

702
00:34:40,680 --> 00:34:44,120
Speaker 2: like me or someone better like Molly White, a cynic.

703
00:34:44,800 --> 00:34:47,560
Speaker 2: And I think it's this thing where what people like

704
00:34:47,640 --> 00:34:50,839
Speaker 2: everyone at this table, Molly White, David Garrett. When talking

705
00:34:50,880 --> 00:34:54,279
Speaker 2: about cryptocurrency these Gary Mark has been talking about AI,

706
00:34:55,080 --> 00:34:58,080
Speaker 2: Roger mcnamy, You've been talking about everything these people are

707
00:34:58,120 --> 00:35:01,040
Speaker 2: not cynics or critics. I guess they are critics if

708
00:35:01,040 --> 00:35:04,399
Speaker 2: you just frame any criticism as big critic. What they're

709
00:35:04,400 --> 00:35:07,240
Speaker 2: doing is saying, hey, can we apply very basic fucking

710
00:35:07,280 --> 00:35:10,799
Speaker 2: societal structure to this stuff that is thieving, that is

711
00:35:11,120 --> 00:35:11,840
Speaker 2: burning things?

712
00:35:11,880 --> 00:35:14,680
Speaker 3: Hey, do we want this thing that seems.

713
00:35:14,400 --> 00:35:17,320
Speaker 2: To enrich in the case of cryptocurrency a very small

714
00:35:17,320 --> 00:35:20,160
Speaker 2: and shadowy group. And the ones who want shadowy are

715
00:35:20,280 --> 00:35:25,080
Speaker 2: very annoying. And these people like the Winklevosses who lost

716
00:35:25,080 --> 00:35:28,400
Speaker 2: a billion dollars of their customers money. That's fine, But

717
00:35:28,480 --> 00:35:31,560
Speaker 2: when you talk about this stuff, well, you just don't

718
00:35:31,640 --> 00:35:35,520
Speaker 2: like technology. You just don't want progress. Motherfucker. None of

719
00:35:35,520 --> 00:35:36,560
Speaker 2: this is progress.

720
00:35:37,000 --> 00:35:39,600
Speaker 3: From the very beginning, this was the goal.

721
00:35:39,719 --> 00:35:42,800
Speaker 1: It was clear to anybody in eighteen twelve when the

722
00:35:42,840 --> 00:35:45,520
Speaker 1: Luddite movement was at its apex, that this was a

723
00:35:45,560 --> 00:35:48,760
Speaker 1: popular movement. That people were coming out in the streets

724
00:35:49,040 --> 00:35:52,400
Speaker 1: to cheer the Luddites, not the factory owners, because they

725
00:35:52,400 --> 00:35:55,000
Speaker 1: felt solidarity with them. Yeah, because they saw the shape

726
00:35:55,000 --> 00:35:57,440
Speaker 1: that industrial capitalism was taking. They knew who the winners

727
00:35:57,480 --> 00:35:59,120
Speaker 1: were going to be, they knew who the losers were

728
00:35:59,120 --> 00:36:01,319
Speaker 1: going to be, and they cheered the lued Heites on.

729
00:36:01,760 --> 00:36:04,600
Speaker 1: And so when the state comes out and it has

730
00:36:04,640 --> 00:36:06,600
Speaker 1: to sort of make its case against the Ludite, it

731
00:36:06,800 --> 00:36:10,040
Speaker 1: has to demonize the Luedites, it has to try to win,

732
00:36:10,280 --> 00:36:13,120
Speaker 1: and it does so again by making frame breaking a

733
00:36:13,160 --> 00:36:16,479
Speaker 1: capital offense. You break a machine, you can get killed,

734
00:36:16,520 --> 00:36:17,040
Speaker 1: you can get hung.

735
00:36:17,120 --> 00:36:20,759
Speaker 3: Both taking too right, oath, taking too saying that you

736
00:36:20,880 --> 00:36:23,080
Speaker 3: were a Luttite became a hang up all offense. You

737
00:36:23,120 --> 00:36:23,640
Speaker 3: could get hung.

738
00:36:23,719 --> 00:36:26,759
Speaker 1: That's why there's no real records left of sort of

739
00:36:26,800 --> 00:36:29,960
Speaker 1: their their meeting minutes or there anything or any letters

740
00:36:29,960 --> 00:36:31,720
Speaker 1: between the very few and far between.

741
00:36:32,920 --> 00:36:33,120
Speaker 3: Yeah.

742
00:36:33,200 --> 00:36:36,960
Speaker 1: Classic, and then they mobilize troops. There's more troops in

743
00:36:37,040 --> 00:36:39,280
Speaker 1: England fighting the lut Heites than they were fighting Napoleons.

744
00:36:39,280 --> 00:36:41,359
Speaker 3: They brought them back from the front, right, they brought

745
00:36:41,400 --> 00:36:43,200
Speaker 3: them back from France to fight the Lutedtite.

746
00:36:43,440 --> 00:36:45,560
Speaker 1: The tens of thousands at one point, so you could

747
00:36:45,800 --> 00:36:49,799
Speaker 1: literally see you'd see the lines drawn sort of as

748
00:36:50,080 --> 00:36:54,719
Speaker 1: industrialization was very literally almost a civil war, and the

749
00:36:54,719 --> 00:36:59,239
Speaker 1: states making the case against the Lutedites, and it's the propaganda,

750
00:36:59,400 --> 00:37:01,360
Speaker 1: you can call it. It's propaganda at the time, and

751
00:37:01,400 --> 00:37:05,279
Speaker 1: its proclamations and its declarations it's it's it's casting the

752
00:37:05,320 --> 00:37:10,080
Speaker 1: Ludites as backwards looking, as deluded, as malcontent under the

753
00:37:10,360 --> 00:37:12,920
Speaker 1: you know they must be you know, they're they're smashing

754
00:37:12,960 --> 00:37:15,920
Speaker 1: the thing that that that that you know that that's.

755
00:37:15,560 --> 00:37:16,239
Speaker 3: Part of their job.

756
00:37:16,360 --> 00:37:20,680
Speaker 1: Yeah, they're smashing, they're smashing. Probably this form of criticism

757
00:37:20,800 --> 00:37:24,080
Speaker 1: is already there. So when the Ludites do lose, when

758
00:37:24,080 --> 00:37:27,880
Speaker 1: they are hung en mass uh, that language is used

759
00:37:28,000 --> 00:37:31,360
Speaker 1: in the trial against them, and we can see why

760
00:37:31,440 --> 00:37:34,799
Speaker 1: because the state needs to have this enemy. They have

761
00:37:34,880 --> 00:37:37,280
Speaker 1: to be able to paint this portrait as anybody who's

762
00:37:37,640 --> 00:37:42,400
Speaker 1: against the shape that technological development is taking, anyone who's

763
00:37:42,600 --> 00:37:45,319
Speaker 1: criticizing any element of that, Like, wait, is are there

764
00:37:45,320 --> 00:37:49,200
Speaker 1: too many losers or winners? No, shut up, you're a luttite.

765
00:37:49,520 --> 00:37:52,120
Speaker 1: Get out, you stand down, or we will hang you.

766
00:37:52,800 --> 00:37:54,480
Speaker 2: And I think that this is a really I'm so

767
00:37:54,600 --> 00:37:57,760
Speaker 2: glad you went into this specific thing because it really

768
00:37:57,800 --> 00:37:59,719
Speaker 2: feels like now I don't know if the state is

769
00:38:00,080 --> 00:38:02,640
Speaker 2: I think the state's laziness is more or like a

770
00:38:02,760 --> 00:38:05,239
Speaker 2: lack of focus is the problem. It's not that the

771
00:38:05,600 --> 00:38:08,720
Speaker 2: administrations are being like people who don't like AI are stupid,

772
00:38:08,760 --> 00:38:10,799
Speaker 2: or people who don't like crypto. They're just like, I

773
00:38:10,840 --> 00:38:13,600
Speaker 2: don't really get this, and these people got so much money.

774
00:38:13,640 --> 00:38:16,560
Speaker 2: And I love money. I love getting paid, I love

775
00:38:16,600 --> 00:38:19,200
Speaker 2: being lobbied. This is great. So I'm gonna go with

776
00:38:19,239 --> 00:38:22,120
Speaker 2: the guys with the money versus the fact that I

777
00:38:22,200 --> 00:38:26,320
Speaker 2: think that actually the optimists I don't just mean Andresan

778
00:38:26,400 --> 00:38:29,839
Speaker 2: or Bajali, I mean the AI fantasists, all these people

779
00:38:29,880 --> 00:38:32,239
Speaker 2: who claim that if you're against AI, well you don't

780
00:38:32,280 --> 00:38:34,640
Speaker 2: care about progress. I actually have a counterpoint, which is

781
00:38:35,320 --> 00:38:38,680
Speaker 2: they are against progress. They don't want anything new to happen.

782
00:38:38,719 --> 00:38:41,719
Speaker 2: They want whatever money they want the next Google. And

783
00:38:41,760 --> 00:38:44,080
Speaker 2: when I say the next Google, I don't mean Google Search.

784
00:38:44,440 --> 00:38:47,560
Speaker 2: I mean the giant monopolistic entity that just spits like

785
00:38:47,640 --> 00:38:50,839
Speaker 2: eats people and shits out money. And I'm just gonna

786
00:38:50,840 --> 00:38:54,600
Speaker 2: put it bluntly. They they are the cynics. They are

787
00:38:54,600 --> 00:38:58,680
Speaker 2: the pessimists that like the SCALEAI guy, like all of

788
00:38:58,719 --> 00:39:00,880
Speaker 2: these people who go around, well if you if you

789
00:39:00,920 --> 00:39:02,640
Speaker 2: don't believe, we need to do this, we need to

790
00:39:02,680 --> 00:39:04,920
Speaker 2: train as much as possible. That's what the future likes. Like,

791
00:39:05,000 --> 00:39:07,160
Speaker 2: Fuck no, these people don't care about tag.

792
00:39:07,600 --> 00:39:09,600
Speaker 3: Can I can I I'll give you a little gloss

793
00:39:09,600 --> 00:39:13,200
Speaker 3: on this from Mal Sauter, who's very smart about this

794
00:39:13,320 --> 00:39:15,040
Speaker 3: and who was the first person to point this out

795
00:39:15,560 --> 00:39:19,200
Speaker 3: that that I encountered, which is that AI and indeed,

796
00:39:19,239 --> 00:39:25,440
Speaker 3: all statistical methods of prediction are intrinsically conservative because because

797
00:39:25,480 --> 00:39:29,080
Speaker 3: if what you're doing is predicting what should happen next

798
00:39:29,080 --> 00:39:31,160
Speaker 3: based on what already happened, what you're doing is you're

799
00:39:31,239 --> 00:39:33,520
Speaker 3: driving a future that looked like the past. So think

800
00:39:33,520 --> 00:39:35,120
Speaker 3: of it this way, Right, you pick up your distraction

801
00:39:35,200 --> 00:39:38,440
Speaker 3: rectangle and you type hay, and then it finishes it

802
00:39:38,480 --> 00:39:41,279
Speaker 3: with darling, because that's what you type every time. That's

803
00:39:41,280 --> 00:39:43,160
Speaker 3: what a cool mclenns you might be. You might want

804
00:39:43,160 --> 00:39:46,960
Speaker 3: to type hay, asshole, but it wants you to type hey, darling. Right,

805
00:39:47,000 --> 00:39:49,120
Speaker 3: and now, if you type something you've never type before,

806
00:39:49,800 --> 00:39:52,560
Speaker 3: it's going to pick the thing that most people say. Right,

807
00:39:52,640 --> 00:39:54,840
Speaker 3: that's that's the So you're going to get either the

808
00:39:54,880 --> 00:39:57,759
Speaker 3: statistically average version of who you used to be or

809
00:39:57,800 --> 00:40:00,919
Speaker 3: the statistically average version of who every one is. There

810
00:40:00,960 --> 00:40:06,719
Speaker 3: is something intrinsically and inseparably conservative about the project of

811
00:40:06,800 --> 00:40:10,359
Speaker 3: making the future look like the past. Now I want

812
00:40:10,400 --> 00:40:13,279
Speaker 3: to mention something that again I learned from Brian's very

813
00:40:13,280 --> 00:40:17,839
Speaker 3: excellent book Blood in the Machine, which is that Frankenstein

814
00:40:17,920 --> 00:40:20,120
Speaker 3: was a ludite novel and was widely understood as a

815
00:40:20,160 --> 00:40:22,600
Speaker 3: ludite novel. It's a cautionary tale about what happens when

816
00:40:22,600 --> 00:40:25,719
Speaker 3: an entrepreneur gets to build a machine without talking to

817
00:40:25,760 --> 00:40:28,160
Speaker 3: his neighbors about what it should do, and it was

818
00:40:28,239 --> 00:40:30,840
Speaker 3: really widely understood as this. And the irony here, and

819
00:40:30,880 --> 00:40:32,640
Speaker 3: I say this as a fully paid up member of the

820
00:40:32,640 --> 00:40:36,200
Speaker 3: Science Fiction Writers of America and science fiction novelist. The

821
00:40:36,239 --> 00:40:40,160
Speaker 3: irony here is how many of these torment nexus building

822
00:40:40,200 --> 00:40:44,760
Speaker 3: weirdos read cyberpunk as a suggestion instead of a warning,

823
00:40:45,239 --> 00:40:49,880
Speaker 3: and defend what they're doing as carrying on the visionary

824
00:40:49,920 --> 00:40:53,200
Speaker 3: tradition of science fiction. The first science fiction novel ever

825
00:40:54,040 --> 00:40:57,480
Speaker 3: was Frankenstein, and it was a novel about why you

826
00:40:57,480 --> 00:41:00,120
Speaker 3: shouldn't just build whatever goddamn machine you feel like? Bill?

827
00:41:00,400 --> 00:41:02,799
Speaker 2: What I like about The Ready Player one one? First

828
00:41:02,840 --> 00:41:04,919
Speaker 2: of all, one of the worst books ever written.

829
00:41:04,960 --> 00:41:07,759
Speaker 3: In mind, it would be nice to Ernie. I think

830
00:41:07,800 --> 00:41:11,040
Speaker 3: that book. It's very fun.

831
00:41:11,440 --> 00:41:14,480
Speaker 2: I believe it is that we are not going to

832
00:41:14,520 --> 00:41:16,360
Speaker 2: turn this into a debate on that book in so

833
00:41:16,440 --> 00:41:16,960
Speaker 2: much trouble.

834
00:41:17,239 --> 00:41:20,400
Speaker 3: But my problem. I like your book, Ernie, come on

835
00:41:20,440 --> 00:41:21,480
Speaker 3: the show, You'll kill me.

836
00:41:22,920 --> 00:41:24,799
Speaker 2: But the thing is with that is that book is

837
00:41:24,840 --> 00:41:28,799
Speaker 2: not a positive book. No, nothing about that story feels good.

838
00:41:28,800 --> 00:41:32,040
Speaker 2: But also the central plot is this shanty town this

839
00:41:32,160 --> 00:41:36,880
Speaker 2: child escapes from every day and then using his distractions

840
00:41:36,920 --> 00:41:40,600
Speaker 2: from his terrible life, he is able to decode the

841
00:41:40,640 --> 00:41:46,440
Speaker 2: thoughts of a deeply troubled, mentally unwell man as he

842
00:41:46,560 --> 00:41:49,720
Speaker 2: is chased by greedy people who don't really care about

843
00:41:49,719 --> 00:41:52,120
Speaker 2: any of it, and all of them are obsessed with

844
00:41:52,640 --> 00:41:56,319
Speaker 2: not the interest in the stuff, but the existence of

845
00:41:56,360 --> 00:42:00,320
Speaker 2: the stuff. And Mark Zucker books that's actually the single

846
00:42:00,400 --> 00:42:01,560
Speaker 2: best I'm going to build.

847
00:42:02,239 --> 00:42:04,319
Speaker 1: That's this is just what Corey was just talking about,

848
00:42:04,400 --> 00:42:07,239
Speaker 1: right is. It speaks to the conservatism of the a

849
00:42:07,280 --> 00:42:10,160
Speaker 1: lot of these the detection once they've built a company

850
00:42:10,200 --> 00:42:13,200
Speaker 1: that's big enough to where you know, you're casting around

851
00:42:13,200 --> 00:42:15,440
Speaker 1: for your next thing because you don't actually want to

852
00:42:15,480 --> 00:42:17,400
Speaker 1: do any you know, real innovating yourself.

853
00:42:17,440 --> 00:42:20,000
Speaker 3: You you you outsource it to a sci fi novel.

854
00:42:20,120 --> 00:42:25,240
Speaker 1: That's why we've seen this this sort of generation of

855
00:42:25,239 --> 00:42:29,320
Speaker 1: of sort of wish lists from cyberpunk from the metaverse.

856
00:42:29,360 --> 00:42:33,200
Speaker 1: I mean that was just Mark Zuckerberg saying, hey, uh yeah,

857
00:42:33,320 --> 00:42:35,960
Speaker 1: let's let's let my next My next thing is the metaverse.

858
00:42:36,040 --> 00:42:38,920
Speaker 3: Then that comes from your your future is being a legless, sexless,

859
00:42:38,920 --> 00:42:41,680
Speaker 3: low polygon heavily surveyed cartoon character in a virtual world.

860
00:42:41,680 --> 00:42:44,440
Speaker 3: I stole from a twenty five year old ystopian cyberpunk novel.

861
00:42:44,560 --> 00:42:47,600
Speaker 1: Exactly Elon Musk, the cyber truck that's from Blade Runner.

862
00:42:47,680 --> 00:42:49,520
Speaker 1: For some reason, it's from a blade Runner which is

863
00:42:49,520 --> 00:42:53,600
Speaker 1: Epegen based or oh now open Ai, which says, oh,

864
00:42:53,680 --> 00:42:55,879
Speaker 1: you know, it's gonna be like Her, the movie Her.

865
00:42:56,120 --> 00:42:59,240
Speaker 1: They're just saying like that, like right, like that. That's

866
00:42:59,480 --> 00:43:03,560
Speaker 1: that's sort of the extent of the imagination at work here.

867
00:43:03,800 --> 00:43:05,799
Speaker 1: And I do think that that is like an inherently

868
00:43:05,960 --> 00:43:09,839
Speaker 1: sort of conservative and restrictive way to operate, and it's,

869
00:43:10,080 --> 00:43:11,840
Speaker 1: you know, we were seeing the limits of it now.

870
00:43:11,880 --> 00:43:13,160
Speaker 1: I don't even know if they actually want to build

871
00:43:13,160 --> 00:43:14,880
Speaker 1: these products or if they just want to win a

872
00:43:14,960 --> 00:43:17,840
Speaker 1: hype cycle and sort of get it's a way that

873
00:43:17,880 --> 00:43:19,279
Speaker 1: they can get people to talk about it.

874
00:43:20,160 --> 00:43:22,879
Speaker 3: I just want to call out that ads Elon Mosk

875
00:43:23,040 --> 00:43:24,760
Speaker 3: is early similar to FW to Clark.

876
00:43:26,400 --> 00:43:30,160
Speaker 2: Well, if you're a legless fullness creature. You feel your

877
00:43:30,160 --> 00:43:32,640
Speaker 2: life's restricted, perhaps you could check out one of the

878
00:43:32,680 --> 00:43:36,439
Speaker 2: following products, and I guarantee you the following products will

879
00:43:36,480 --> 00:43:39,440
Speaker 2: not in any way embarrass me have some kind of

880
00:43:39,480 --> 00:43:43,359
Speaker 2: almost ironic connotation with what they run. So please enjoy

881
00:43:43,400 --> 00:43:55,799
Speaker 2: the following ad and we're back. So I think it's

882
00:43:55,840 --> 00:43:58,399
Speaker 2: funny you brought that up, Brian, where it's like, it's

883
00:43:58,400 --> 00:44:01,960
Speaker 2: not even obvious that they can about what they're building.

884
00:44:02,080 --> 00:44:05,000
Speaker 2: It's not even about the stuff anymore. And when I

885
00:44:05,040 --> 00:44:08,400
Speaker 2: look at a company like Google or Microsoft, what do

886
00:44:08,480 --> 00:44:11,560
Speaker 2: they do? Like if you really sit down and say

887
00:44:11,560 --> 00:44:15,279
Speaker 2: what does Google do? What does Microsoft? Or you can

888
00:44:15,320 --> 00:44:17,560
Speaker 2: look at Apple and say they make consumer electronics.

889
00:44:17,560 --> 00:44:18,640
Speaker 3: That's fairly that.

890
00:44:18,800 --> 00:44:20,760
Speaker 2: I think that that's a fair thing. They make laptops

891
00:44:20,760 --> 00:44:23,959
Speaker 2: to make phones, you use them, and sometimes they force

892
00:44:24,000 --> 00:44:26,400
Speaker 2: you into an abusive system called the app Store, But

893
00:44:26,440 --> 00:44:28,799
Speaker 2: nevertheless you can tell what they do. Google and Microsoft

894
00:44:29,400 --> 00:44:33,279
Speaker 2: are like holding companies. They're they're private equity firms that

895
00:44:33,560 --> 00:44:33,880
Speaker 2: have no.

896
00:44:34,880 --> 00:44:36,600
Speaker 3: Like formal shape.

897
00:44:36,600 --> 00:44:38,919
Speaker 2: Because this whole week I've been sitting down and reading

898
00:44:38,960 --> 00:44:41,560
Speaker 2: about something we will get to in a minute, which

899
00:44:41,560 --> 00:44:44,560
Speaker 2: is how open a I can can compete with Google Search,

900
00:44:44,560 --> 00:44:48,080
Speaker 2: and by the way, they cannot. It's impossible. It's actually impossible.

901
00:44:49,239 --> 00:44:51,560
Speaker 2: It just feels that it's not that they don't have focus,

902
00:44:51,719 --> 00:44:54,680
Speaker 2: is that they can't have focus. That there's simply nothing.

903
00:44:54,719 --> 00:44:58,040
Speaker 2: They can't make anything anymore. They can make more similar stuff,

904
00:44:58,040 --> 00:45:00,720
Speaker 2: But when was the last time Google up with something

905
00:45:01,280 --> 00:45:02,200
Speaker 2: truly innovative.

906
00:45:03,320 --> 00:45:07,080
Speaker 1: Yeah, I mean it's it's you can kind of tunnel

907
00:45:07,120 --> 00:45:10,120
Speaker 1: by the rush and it's desperation to sort of like

908
00:45:10,200 --> 00:45:13,080
Speaker 1: build some sort of an AI product that can work

909
00:45:13,200 --> 00:45:15,600
Speaker 1: or that can at least capture some attention, because it's

910
00:45:15,600 --> 00:45:17,920
Speaker 1: not I mean, it's not this this overview AI thing

911
00:45:17,960 --> 00:45:20,480
Speaker 1: that they rushed out the door and were just ruthlessly

912
00:45:20,520 --> 00:45:23,759
Speaker 1: and widely and deservedly mocked for making it. You know,

913
00:45:23,800 --> 00:45:27,640
Speaker 1: it's not even clear I think to anybody how that

914
00:45:27,960 --> 00:45:31,520
Speaker 1: serves Google's bottom line. If anything its them, it loses

915
00:45:31,560 --> 00:45:38,280
Speaker 1: the money because they have ostensibly this remarkably potent revenue

916
00:45:38,280 --> 00:45:40,560
Speaker 1: generator in terms of Google Search. I mean, that's the

917
00:45:40,680 --> 00:45:42,759
Speaker 1: only real answer to your question. I think that is

918
00:45:42,920 --> 00:45:44,719
Speaker 1: what does Google do? It runs a search engine that

919
00:45:44,760 --> 00:45:47,640
Speaker 1: it has gotten tired of running, and it's or it's

920
00:45:47,760 --> 00:45:50,880
Speaker 1: backers and partners have gotten tired of running, or people

921
00:45:51,000 --> 00:45:53,239
Speaker 1: are convinced that it's no longer the future and that

922
00:45:53,320 --> 00:45:56,319
Speaker 1: it's not going to be useful to anybody. But I mean,

923
00:45:56,400 --> 00:45:59,839
Speaker 1: to me, the search engine is still far superior to

924
00:46:00,040 --> 00:46:03,399
Speaker 1: and to using a chat, GPT or any generative AI

925
00:46:03,560 --> 00:46:06,920
Speaker 1: product that I've come across yet. And it's you know,

926
00:46:07,080 --> 00:46:10,920
Speaker 1: it's the talent as I understand it, from Google, has

927
00:46:11,320 --> 00:46:14,480
Speaker 1: has been shifted away from running the search operation, the

928
00:46:14,520 --> 00:46:18,320
Speaker 1: search department. Now it's all on on Ai, which is

929
00:46:18,360 --> 00:46:21,080
Speaker 1: the again, this nebulous form that I don't even think

930
00:46:21,320 --> 00:46:23,560
Speaker 1: it's not like Google. I mean, Google sounded that famously,

931
00:46:23,600 --> 00:46:25,960
Speaker 1: this red alert that said all hands like we got

932
00:46:25,960 --> 00:46:28,359
Speaker 1: to catch up to open aid, we gotta we gotta

933
00:46:28,360 --> 00:46:30,440
Speaker 1: figure out a way to make this happen. And we

934
00:46:30,640 --> 00:46:35,240
Speaker 1: just see this sputtering, all these little false starts and

935
00:46:35,239 --> 00:46:38,520
Speaker 1: and turds rolled off into the Internet that are that

936
00:46:38,560 --> 00:46:40,759
Speaker 1: are more mocked than us and certainly not profitable.

937
00:46:41,120 --> 00:46:42,759
Speaker 3: I want to I want to try and make the

938
00:46:42,800 --> 00:46:45,680
Speaker 3: heroic case for Google, okay, which is a tough case

939
00:46:45,719 --> 00:46:48,319
Speaker 3: to make, but I'm gonna make it so Google, I

940
00:46:48,320 --> 00:46:50,160
Speaker 3: think you said, what was the last time Google made

941
00:46:50,160 --> 00:46:52,799
Speaker 3: something truly innovative. I think it was twenty five years ago.

942
00:46:52,840 --> 00:46:55,759
Speaker 3: Google has not made a successful products in search. They've

943
00:46:55,760 --> 00:46:58,439
Speaker 3: brought a lot of successful products, right. They bought their

944
00:46:58,440 --> 00:47:00,680
Speaker 3: mobile stack, they bought their ad text, they bought video.

945
00:47:00,719 --> 00:47:04,400
Speaker 2: You could like go for example, it wasn't go fairly

946
00:47:04,440 --> 00:47:06,480
Speaker 2: recent that the coding language.

947
00:47:06,239 --> 00:47:10,200
Speaker 3: Their programming lange. Yeah, sure, I'm getting I'm getting to that. Yes,

948
00:47:10,400 --> 00:47:12,640
Speaker 3: they bought YouTube, right, yeah, they bought They bought YouTube.

949
00:47:12,640 --> 00:47:15,480
Speaker 3: They bought YouTube after Google Videos failed, so they made

950
00:47:15,520 --> 00:47:17,920
Speaker 3: a video platform that didn't work and they bought one

951
00:47:17,920 --> 00:47:20,800
Speaker 3: that did great. Right. They they bought their ad tex Stact.

952
00:47:20,800 --> 00:47:23,360
Speaker 3: They bought their customer service. They bought dogs, they bought collaboration,

953
00:47:23,440 --> 00:47:27,640
Speaker 3: they bought maps, they bought all of it, transition. Where

954
00:47:27,640 --> 00:47:29,920
Speaker 3: did they buy dogs from? Who's Who's they forget it

955
00:47:29,920 --> 00:47:30,440
Speaker 3: was that company?

956
00:47:30,920 --> 00:47:34,319
Speaker 2: That's that's something like I feel like I'm fairly well versed.

957
00:47:34,320 --> 00:47:36,080
Speaker 2: Intent was the start I thought they built.

958
00:47:36,280 --> 00:47:39,880
Speaker 3: No, No, they didn't build they so like first depending

959
00:47:39,880 --> 00:47:42,000
Speaker 3: on how on how you want to purse it, right,

960
00:47:42,000 --> 00:47:45,360
Speaker 3: because you have things like their hotmail clone, which was

961
00:47:45,480 --> 00:47:49,439
Speaker 3: very successful. Uh you know Gmail, Yeah, right, but it's

962
00:47:49,480 --> 00:47:51,759
Speaker 3: it's a they made that in house. They didn't buy

963
00:47:51,760 --> 00:47:55,160
Speaker 3: that from someone however, it's a clone of hotmail, right, sure.

964
00:47:55,640 --> 00:47:58,480
Speaker 3: And so they have these these products. But what they

965
00:47:58,480 --> 00:48:01,359
Speaker 3: did for these products, and and this is the heroic part,

966
00:48:01,400 --> 00:48:03,200
Speaker 3: the part where I'm going to be bend over backwards

967
00:48:03,200 --> 00:48:05,680
Speaker 3: to be fair to there, is they know they scaled

968
00:48:05,680 --> 00:48:10,440
Speaker 3: them and they made them reliable. Right, that's crazy. And look,

969
00:48:10,719 --> 00:48:14,040
Speaker 3: one of the things that we critique capitalism for is

970
00:48:14,040 --> 00:48:18,360
Speaker 3: that it is underinvest in maintenance, It underinvests in infrastructure,

971
00:48:18,640 --> 00:48:21,120
Speaker 3: it underinvests in what we could broadly call care work.

972
00:48:21,640 --> 00:48:24,480
Speaker 3: And at its best, what Google did was, in a

973
00:48:24,560 --> 00:48:29,080
Speaker 3: kind of patrician way, became a serial acquirer of nascent

974
00:48:29,120 --> 00:48:32,960
Speaker 3: competitors that didn't necessarily extinguish those competitors, although they did

975
00:48:32,960 --> 00:48:35,680
Speaker 3: in some cases. But what primarily they did was they

976
00:48:35,680 --> 00:48:37,920
Speaker 3: scaled them up to utility scale, and then they maintained

977
00:48:37,920 --> 00:48:40,799
Speaker 3: them to a very high degree of reliability. Now, I

978
00:48:40,840 --> 00:48:44,160
Speaker 3: think that if you want to understand Google's internal culture,

979
00:48:44,640 --> 00:48:46,279
Speaker 3: and I think you did a good job talking about

980
00:48:46,320 --> 00:48:48,240
Speaker 3: it when we wrote that the man who killed Google

981
00:48:49,640 --> 00:48:53,040
Speaker 3: is that it's a distinction between people who want to

982
00:48:53,080 --> 00:48:58,000
Speaker 3: do care work and people who want to do rent seeking, right,

983
00:48:58,800 --> 00:49:02,000
Speaker 3: And so you know, there's a version of even keyword

984
00:49:02,040 --> 00:49:04,879
Speaker 3: advertising that I think we can tell a heroic story about. Right,

985
00:49:05,160 --> 00:49:08,799
Speaker 3: if you are a novelist and you've written a science

986
00:49:08,840 --> 00:49:12,480
Speaker 3: fiction novel and it's like a novel by someone else, right,

987
00:49:12,520 --> 00:49:14,799
Speaker 3: it's a comparable to it, then you could buy the

988
00:49:14,840 --> 00:49:17,319
Speaker 3: adword and you could say, when someone searches for Neil

989
00:49:17,320 --> 00:49:21,600
Speaker 3: Stevenson launched this guy's career by saying at the top,

990
00:49:22,120 --> 00:49:24,799
Speaker 3: having one little ad slot that's like, have you read so?

991
00:49:24,840 --> 00:49:28,200
Speaker 2: And so it's the foundation of the like the good

992
00:49:28,239 --> 00:49:30,080
Speaker 2: bits of capitalism, if you can call it, like the

993
00:49:30,600 --> 00:49:33,960
Speaker 2: honest marketing, like we like this, you might you like this,

994
00:49:34,000 --> 00:49:34,680
Speaker 2: you might like this.

995
00:49:34,840 --> 00:49:37,200
Speaker 3: Yeah, yeah, it's it's and so there's a lot you know,

996
00:49:37,239 --> 00:49:39,359
Speaker 3: being able to reach into these niches. This is also

997
00:49:39,400 --> 00:49:42,359
Speaker 3: a thing that Facebook has done quite well. And and

998
00:49:42,440 --> 00:49:45,040
Speaker 3: you know when Facebook has defenders, they are often small

999
00:49:45,080 --> 00:49:48,959
Speaker 3: business people who could not address a market without fine

1000
00:49:49,000 --> 00:49:52,520
Speaker 3: grained targeting. Me right now, that fine grained targeting needn't

1001
00:49:52,520 --> 00:49:55,040
Speaker 3: be behavioral. It could be it could be content based. Right,

1002
00:49:55,080 --> 00:49:59,640
Speaker 3: you could target if you want to target plus sized cheerleaders,

1003
00:49:59,680 --> 00:50:02,000
Speaker 3: you could find the Facebook group for plus sized cheerleaders

1004
00:50:02,000 --> 00:50:03,719
Speaker 3: and sell your uniforms to them. And I'm sure that

1005
00:50:03,719 --> 00:50:05,480
Speaker 3: there are a bunch of people who are plus sized

1006
00:50:05,560 --> 00:50:08,120
Speaker 3: cheerleaders who are really pissed that the uniforms for plus

1007
00:50:08,600 --> 00:50:11,440
Speaker 3: cheerleaders suck, and who'd be really great to see those ads. Right.

1008
00:50:11,480 --> 00:50:12,640
Speaker 3: You don't have to spy on them, you don't have

1009
00:50:12,640 --> 00:50:14,040
Speaker 3: to follow them into the back. I don't need to

1010
00:50:14,040 --> 00:50:17,000
Speaker 3: know who they are. Yeah, but that's what they've done

1011
00:50:17,000 --> 00:50:20,440
Speaker 3: at their best, right, And the rent seekers just want

1012
00:50:20,520 --> 00:50:24,520
Speaker 3: to make money by providing as little to everyone else

1013
00:50:24,680 --> 00:50:28,759
Speaker 3: as they can and taking as much in as they can.

1014
00:50:28,800 --> 00:50:32,319
Speaker 3: They want to own a factor of production and they

1015
00:50:32,320 --> 00:50:34,879
Speaker 3: want to be insulated from the risk because other people

1016
00:50:34,960 --> 00:50:37,840
Speaker 3: who produce useful things will have to license or buy

1017
00:50:37,880 --> 00:50:40,480
Speaker 3: that factor of production from them in order to do

1018
00:50:40,520 --> 00:50:43,000
Speaker 3: the useful thing. But whether or not they do the

1019
00:50:43,080 --> 00:50:44,920
Speaker 3: useful thing or not, Like think of Nvidia right in

1020
00:50:45,040 --> 00:50:48,400
Speaker 3: videos selling video cards to people who are going to

1021
00:50:48,400 --> 00:50:50,600
Speaker 3: go out of business. That doesn't matter to Invidio and

1022
00:50:50,640 --> 00:50:52,919
Speaker 3: they already sold them gets a stake in Think about

1023
00:50:53,040 --> 00:50:55,880
Speaker 3: Unity right, who said, oh, we're going to take not

1024
00:50:56,040 --> 00:50:57,760
Speaker 3: We're not just going to sell you the dev tools

1025
00:50:57,800 --> 00:51:00,640
Speaker 3: to make your video game. If your video games succeeds.

1026
00:51:00,880 --> 00:51:04,560
Speaker 3: We're going to get a royalty for every game you share, right,

1027
00:51:04,680 --> 00:51:07,080
Speaker 3: And they called it shared success. Now, note that this

1028
00:51:08,200 --> 00:51:11,520
Speaker 3: rhetoric of like shared success is not the rhetoric of

1029
00:51:11,560 --> 00:51:12,160
Speaker 3: shared risk.

1030
00:51:12,360 --> 00:51:14,960
Speaker 2: Kind of like a parasite shares your success.

1031
00:51:15,440 --> 00:51:18,520
Speaker 3: Yeah, you know, shared risk, right, shared risk, shared reward

1032
00:51:18,640 --> 00:51:20,960
Speaker 3: makes a certain degree of sense. If they're saying, okay, well,

1033
00:51:20,960 --> 00:51:24,080
Speaker 3: i'll tell you what. We've got a deal where we

1034
00:51:24,200 --> 00:51:27,960
Speaker 3: will give you discounted or free tools and development money

1035
00:51:28,080 --> 00:51:31,799
Speaker 3: and whatever. We'll invest in your company, right, and as

1036
00:51:31,840 --> 00:51:34,239
Speaker 3: a form of shared success, and we will also take

1037
00:51:34,239 --> 00:51:37,480
Speaker 3: a shared risk in your failure. That's a very different matter.

1038
00:51:37,600 --> 00:51:41,160
Speaker 2: Yeah, because shared risk is inherent to actual shared success.

1039
00:51:41,200 --> 00:51:42,359
Speaker 3: We are taking a risk.

1040
00:51:42,760 --> 00:51:46,040
Speaker 2: But it's almost I think this keeps coming back to

1041
00:51:47,080 --> 00:51:51,120
Speaker 2: basic evolution Darwinism, probably two different things. Now, I said

1042
00:51:51,160 --> 00:51:52,759
Speaker 2: I did not do well in size. But nevertheless, I'll

1043
00:51:52,760 --> 00:51:55,440
Speaker 2: get round to this. There are no predators for these

1044
00:51:55,440 --> 00:51:56,560
Speaker 2: people anymore.

1045
00:51:56,400 --> 00:51:59,239
Speaker 3: There's nothing they're afraid of, no discipline, Like there's the

1046
00:51:59,320 --> 00:52:01,880
Speaker 3: cattail thing is they don't want they want everyone to

1047
00:52:01,920 --> 00:52:03,879
Speaker 3: stay the same, so they know who they're looking at

1048
00:52:03,920 --> 00:52:04,520
Speaker 3: every day.

1049
00:52:04,760 --> 00:52:07,560
Speaker 2: We can bark, bark anyone out of the area. If

1050
00:52:07,560 --> 00:52:10,440
Speaker 2: we don't like them, we can make growing difficult. We

1051
00:52:10,480 --> 00:52:14,160
Speaker 2: know the venture capitalists, we know the commercial real estate owners,

1052
00:52:14,160 --> 00:52:18,000
Speaker 2: we know the people in government office. We can make

1053
00:52:18,040 --> 00:52:20,640
Speaker 2: this really difficult and really easy for us. But also

1054
00:52:21,160 --> 00:52:23,759
Speaker 2: it feels like we need predators in the tech industry

1055
00:52:23,920 --> 00:52:26,600
Speaker 2: and not the kind who worked at Google like Andy Rubin,

1056
00:52:27,000 --> 00:52:28,680
Speaker 2: and I think the.

1057
00:52:29,280 --> 00:52:33,480
Speaker 1: Well, and as long as you have a company I mean,

1058
00:52:33,200 --> 00:52:35,800
Speaker 1: I mean that has any you know, degree of success

1059
00:52:35,880 --> 00:52:38,439
Speaker 1: or that becomes as big as Google does, I think

1060
00:52:38,560 --> 00:52:41,799
Speaker 1: just like the base logics of capitalism are going to

1061
00:52:41,840 --> 00:52:44,400
Speaker 1: mean that you do you grow the number of people

1062
00:52:44,400 --> 00:52:47,440
Speaker 1: who are the rent seekers and who are interested in

1063
00:52:47,560 --> 00:52:52,160
Speaker 1: protecting those revenue streams at any cost. And you know

1064
00:52:52,239 --> 00:52:55,320
Speaker 1: that the halo of a company like Google may dim,

1065
00:52:55,480 --> 00:52:57,320
Speaker 1: it's still kind of extent.

1066
00:52:57,400 --> 00:52:57,560
Speaker 3: You know.

1067
00:52:57,600 --> 00:53:02,000
Speaker 1: I just wrote this this art about a former Google

1068
00:53:02,080 --> 00:53:06,480
Speaker 1: privacy engineer named Tim Leibert, who was a big security

1069
00:53:06,719 --> 00:53:11,759
Speaker 1: and privacy guy in the academic field. He went to

1070
00:53:11,840 --> 00:53:14,000
Speaker 1: pen he did a time at Oxford, and he was

1071
00:53:14,000 --> 00:53:18,480
Speaker 1: a professor at Carnegie and he really, you know, was

1072
00:53:18,640 --> 00:53:21,000
Speaker 1: really a big critic of Google. And then Google hired

1073
00:53:21,040 --> 00:53:25,040
Speaker 1: him and he agreed to go because he thought this, well,

1074
00:53:25,360 --> 00:53:27,719
Speaker 1: all the things that I'm talking about, all the things

1075
00:53:27,760 --> 00:53:30,560
Speaker 1: that I want to fix, Google is the largest purveyor

1076
00:53:30,600 --> 00:53:32,640
Speaker 1: of these issues of privacy. He looks at cookies and

1077
00:53:32,640 --> 00:53:35,960
Speaker 1: the way that Google tracks your data. So he figured,

1078
00:53:36,040 --> 00:53:37,600
Speaker 1: you know, if I'm going to have a shot at

1079
00:53:37,640 --> 00:53:40,080
Speaker 1: fixing this, I'm just going to go into the mothership.

1080
00:53:40,400 --> 00:53:43,000
Speaker 1: And sure enough, the way that he describes it to

1081
00:53:43,040 --> 00:53:48,040
Speaker 1: me is his job was split between two basic tasks. One,

1082
00:53:48,120 --> 00:53:50,960
Speaker 1: he's talking to other younger hires who still kind of

1083
00:53:50,960 --> 00:53:53,920
Speaker 1: believe in the idea of a technology and a service

1084
00:53:53,960 --> 00:53:57,040
Speaker 1: that can really help and serve people, and who want

1085
00:53:57,080 --> 00:53:59,800
Speaker 1: to try to make sure that Google, you know, meets

1086
00:53:59,800 --> 00:54:02,040
Speaker 1: its privacy commitments and is in line with the law.

1087
00:54:02,440 --> 00:54:04,680
Speaker 1: And then he would go into the meetings with the

1088
00:54:04,760 --> 00:54:09,640
Speaker 1: executives and management and they would spend the most of

1089
00:54:09,680 --> 00:54:12,560
Speaker 1: the time telling him why they couldn't do all the

1090
00:54:12,600 --> 00:54:14,440
Speaker 1: things that he and all of the people who are

1091
00:54:14,440 --> 00:54:16,799
Speaker 1: actually working in the trenches at Google wanted to do.

1092
00:54:17,160 --> 00:54:20,880
Speaker 1: And it just became this two year long clash of well,

1093
00:54:20,960 --> 00:54:23,440
Speaker 1: there's this privacy law. Don't we we have the tools

1094
00:54:23,440 --> 00:54:25,440
Speaker 1: and the capabilities to fix it. Don't we want to

1095
00:54:25,440 --> 00:54:27,920
Speaker 1: do it and then butting up against management.

1096
00:54:27,920 --> 00:54:29,439
Speaker 3: Why would we do why would we do that? That would

1097
00:54:29,440 --> 00:54:30,600
Speaker 3: it's would we could?

1098
00:54:30,640 --> 00:54:32,800
Speaker 1: It would be easier just to like pay the fines

1099
00:54:32,800 --> 00:54:35,799
Speaker 1: as they come than to actually finds a price, and.

1100
00:54:35,760 --> 00:54:36,200
Speaker 3: They need to.

1101
00:54:36,320 --> 00:54:39,520
Speaker 2: I feel like they really need to change the finds

1102
00:54:39,560 --> 00:54:43,360
Speaker 2: so they scale sure or here's my other there and

1103
00:54:43,520 --> 00:54:45,920
Speaker 2: they're on a Smoglu said this as well, I'm then

1104
00:54:45,960 --> 00:54:50,680
Speaker 2: take it step well laterally put them in jail. And

1105
00:54:50,760 --> 00:54:53,880
Speaker 2: I'm only kind of kidding. I mean, if, for example,

1106
00:54:53,920 --> 00:54:56,680
Speaker 2: the CrowdStrike situation. I brought this up on the Lost

1107
00:54:56,719 --> 00:54:59,520
Speaker 2: Battle Off Live as well, such an Adella should be

1108
00:54:59,520 --> 00:55:02,560
Speaker 2: looking at potential jail time or the cuts see of

1109
00:55:02,640 --> 00:55:07,160
Speaker 2: CrowdStrike should be jail time or personal liability. If you

1110
00:55:07,239 --> 00:55:10,000
Speaker 2: work for a public company with excess revenue blah blah,

1111
00:55:10,040 --> 00:55:11,440
Speaker 2: and you make it so that they can't just do

1112
00:55:11,480 --> 00:55:13,399
Speaker 2: stock splits or some weird shit so they get away

1113
00:55:13,440 --> 00:55:18,080
Speaker 2: with him including stock revenue, you should potentially forfeit like

1114
00:55:18,400 --> 00:55:19,280
Speaker 2: tens percent.

1115
00:55:19,880 --> 00:55:21,320
Speaker 1: You know, it's funny that you say this because the

1116
00:55:21,560 --> 00:55:23,640
Speaker 1: other part of the story is, so is Tim built

1117
00:55:23,680 --> 00:55:26,759
Speaker 1: this this this system called web x ray that can

1118
00:55:26,840 --> 00:55:30,200
Speaker 1: search for every privacy violation that a company is committing

1119
00:55:30,520 --> 00:55:32,560
Speaker 1: on the web and the ideas to make it into

1120
00:55:32,680 --> 00:55:34,879
Speaker 1: like a sort of an assembly line for class action

1121
00:55:34,960 --> 00:55:38,000
Speaker 1: lawsuits and for lawsuits. So you can say, okay, you know,

1122
00:55:38,840 --> 00:55:41,839
Speaker 1: maybe Google, maybe people emailing Google and saying, hey, you're

1123
00:55:41,880 --> 00:55:44,200
Speaker 1: in violation of the Germany's new privacy law. May can

1124
00:55:44,239 --> 00:55:49,080
Speaker 1: you please address this isn't really but if you can say, okay, boom,

1125
00:55:49,080 --> 00:55:51,719
Speaker 1: here's here's a search engine can show you exactly how

1126
00:55:51,760 --> 00:55:55,520
Speaker 1: many times a minute or an hour it's violating these

1127
00:55:55,600 --> 00:55:56,840
Speaker 1: laws regularly.

1128
00:55:56,960 --> 00:55:59,759
Speaker 3: Kind of logne that have costs you know, attached to them.

1129
00:55:59,800 --> 00:56:01,520
Speaker 1: Then and maybe you can sort of so there are

1130
00:56:01,520 --> 00:56:03,359
Speaker 1: people sort of like fighting against this.

1131
00:56:03,600 --> 00:56:06,360
Speaker 3: This is maybe a good time to talk about the

1132
00:56:06,360 --> 00:56:10,399
Speaker 3: structure of regulation or what regulations work and which ones

1133
00:56:10,400 --> 00:56:13,080
Speaker 3: don't and why and so on. So one of the

1134
00:56:13,320 --> 00:56:17,800
Speaker 3: key things to understand about regulation is that a regulation

1135
00:56:17,880 --> 00:56:21,200
Speaker 3: that's hard to administer will be administered less. Right, So

1136
00:56:21,280 --> 00:56:24,680
Speaker 3: if you make a rule, for example, that says, if

1137
00:56:24,719 --> 00:56:27,480
Speaker 3: you're a platform that competes with the platform users, so

1138
00:56:27,520 --> 00:56:30,239
Speaker 3: your Amazon, you sell your own goods, but you also

1139
00:56:30,280 --> 00:56:35,400
Speaker 3: sell goods by your competitors. As a fairness requirement, you

1140
00:56:35,480 --> 00:56:38,000
Speaker 3: must put the best match for the user's search at

1141
00:56:38,040 --> 00:56:40,200
Speaker 3: the top and not just your own products. So this

1142
00:56:40,239 --> 00:56:43,080
Speaker 3: is what's called a ban on self preferencing. The problem

1143
00:56:43,200 --> 00:56:46,040
Speaker 3: is to administer that, you have to be able to

1144
00:56:46,120 --> 00:56:49,560
Speaker 3: kind of peer into the mind of the Amazon executive

1145
00:56:49,960 --> 00:56:54,200
Speaker 3: who decided to put the Amazon product at the top

1146
00:56:54,239 --> 00:56:57,120
Speaker 3: of the search, because if they believe that they made

1147
00:56:57,120 --> 00:56:59,919
Speaker 3: the best product, then they haven't violated the rule.

1148
00:57:00,000 --> 00:57:01,719
Speaker 2: And I was going to say, it feels like the

1149
00:57:01,760 --> 00:57:03,520
Speaker 2: word best is the problem then.

1150
00:57:03,480 --> 00:57:08,280
Speaker 3: Right, So it's a very difficult thing to discover. Moreover,

1151
00:57:08,400 --> 00:57:11,640
Speaker 3: if you have a sincere but incorrect belief about what's best,

1152
00:57:11,719 --> 00:57:14,319
Speaker 3: because we're really good at talking ourselves into thinking that,

1153
00:57:14,920 --> 00:57:16,840
Speaker 3: you know, with the stuff we make is good.

1154
00:57:16,600 --> 00:57:19,120
Speaker 2: And being empathetic, maybe you truly have seen more of

1155
00:57:19,160 --> 00:57:22,560
Speaker 2: this thing being built, like yeah, loss is what they'd say.

1156
00:57:22,680 --> 00:57:24,840
Speaker 3: Yeah, So you might have a good reason to do it,

1157
00:57:24,840 --> 00:57:27,640
Speaker 3: and you still might be wrong. So as an administrative matter,

1158
00:57:28,520 --> 00:57:31,080
Speaker 3: figuring out whether or not someone is self preferencing is

1159
00:57:31,080 --> 00:57:32,880
Speaker 3: really hard. Now, this isn't the first time this has

1160
00:57:32,880 --> 00:57:35,680
Speaker 3: come up. When the Sherman Act was passed in eighteen ninety,

1161
00:57:35,680 --> 00:57:37,840
Speaker 3: the first anti trust law in the United States, self

1162
00:57:37,840 --> 00:57:39,960
Speaker 3: preferencing was a huge problem because you had railroads that

1163
00:57:40,000 --> 00:57:43,680
Speaker 3: owned freight companies and they competed with the freight that

1164
00:57:43,720 --> 00:57:47,960
Speaker 3: they shipped. Right. You had banks that hadn't been split

1165
00:57:48,000 --> 00:57:50,800
Speaker 3: where you had retail and investment, so you had banks

1166
00:57:50,840 --> 00:57:53,720
Speaker 3: that loaned money to local businesses and owned local businesses

1167
00:57:53,720 --> 00:57:57,480
Speaker 3: that competed with their debtors. Right. And so we didn't

1168
00:57:57,680 --> 00:58:03,640
Speaker 3: create a rule that says, Okay, you must treat everyone fairly,

1169
00:58:03,760 --> 00:58:06,760
Speaker 3: because determining the fairness was too hard. What we said

1170
00:58:06,840 --> 00:58:11,000
Speaker 3: is you have to be structurally separated. You either are

1171
00:58:11,040 --> 00:58:14,080
Speaker 3: a bank or you're an investor, but you can't be

1172
00:58:14,120 --> 00:58:17,040
Speaker 3: in a bank that invests. You are either a railroad

1173
00:58:17,200 --> 00:58:18,760
Speaker 3: or you're a freight company, but you can't be a

1174
00:58:18,840 --> 00:58:22,360
Speaker 3: railroad that owns a freight company. This is called structural separation.

1175
00:58:22,840 --> 00:58:24,840
Speaker 3: And the thing is you do lose some efficiencies. Maybe

1176
00:58:24,880 --> 00:58:27,080
Speaker 3: there's some cool things you can do with vertical integration,

1177
00:58:27,440 --> 00:58:31,360
Speaker 3: but what you get is administratable rule. Because I can

1178
00:58:31,440 --> 00:58:35,320
Speaker 3: tell really easily whether a railroad owns a free company.

1179
00:58:35,560 --> 00:58:37,720
Speaker 3: I can't tell whether they're dealing with it fairly. But

1180
00:58:37,800 --> 00:58:40,640
Speaker 3: it's really you can from orbit. You can figure out

1181
00:58:40,680 --> 00:58:42,440
Speaker 3: whether a Railroad owns a freight company.

1182
00:58:42,640 --> 00:58:46,000
Speaker 2: So just imagine you're a dumbos look at mey you

1183
00:58:46,120 --> 00:58:49,919
Speaker 2: It's pretty easy. Yeah, just why has this not been

1184
00:58:50,760 --> 00:58:54,360
Speaker 2: done with I don't know, Microsoft and open Ai for example.

1185
00:58:54,840 --> 00:58:57,120
Speaker 3: This is very interesting. So think about the ad tech

1186
00:58:57,160 --> 00:59:01,160
Speaker 3: platforms ad tech. It's it's into three pieces. You have

1187
00:59:01,160 --> 00:59:03,720
Speaker 3: a demand side platform, a sell side platform in a marketplace.

1188
00:59:03,840 --> 00:59:06,840
Speaker 3: So the demand side platform represents advertisers, the cell side

1189
00:59:06,880 --> 00:59:10,440
Speaker 3: platform represents publishers who have places where the advertisers can place,

1190
00:59:10,480 --> 00:59:12,800
Speaker 3: and out in the marketplaces where the agents for them

1191
00:59:12,880 --> 00:59:15,080
Speaker 3: gather together to bid. And so you land on a

1192
00:59:15,080 --> 00:59:17,720
Speaker 3: web page that lag before it loads. That surveillance lag

1193
00:59:18,120 --> 00:59:20,600
Speaker 3: is all of these little auctions taking place where someone says,

1194
00:59:20,640 --> 00:59:22,000
Speaker 3: you know, I have an eighteen to thirty four year

1195
00:59:22,040 --> 00:59:26,240
Speaker 3: old manchild from Queens who has been recently searching for

1196
00:59:26,280 --> 00:59:29,360
Speaker 3: gonorrhea and owns an Xbox, who will pay to advertise

1197
00:59:29,400 --> 00:59:31,600
Speaker 3: to them? And how much will you pay? Right? Love them?

1198
00:59:33,240 --> 00:59:37,040
Speaker 3: And so there's this little thing going on in the background, right, Okay,

1199
00:59:37,120 --> 00:59:40,080
Speaker 3: So Google and Facebook each own a demand side platform,

1200
00:59:40,120 --> 00:59:43,200
Speaker 3: a sell side platform, and a marketplace. And moreover, they

1201
00:59:43,240 --> 00:59:44,960
Speaker 3: have rigged the game so that if you use one

1202
00:59:45,000 --> 00:59:46,400
Speaker 3: part of it, you pretty much have to use the

1203
00:59:46,440 --> 00:59:50,680
Speaker 3: other parts. And they're both publishers and they're both advertisers. Now,

1204
00:59:51,440 --> 00:59:56,240
Speaker 3: so fifty one percent of every advertising dollar goes into

1205
00:59:56,520 --> 01:00:01,080
Speaker 3: Google and Facebook SIG. The historic share for all intermediaries

1206
01:00:01,080 --> 01:00:04,960
Speaker 3: and advertising supported media was fifteen percent, so they've tripled

1207
01:00:04,960 --> 01:00:07,680
Speaker 3: the share for intermediaries in this. So this is like

1208
01:00:07,720 --> 01:00:10,960
Speaker 3: if you and your partner were getting divorced and you

1209
01:00:11,000 --> 01:00:12,600
Speaker 3: showed up and you realized you both had the same

1210
01:00:12,680 --> 01:00:15,280
Speaker 3: lawyer who was also the judge, who was also trying

1211
01:00:15,280 --> 01:00:17,280
Speaker 3: to match with both of you on Tinder, and then

1212
01:00:17,360 --> 01:00:20,000
Speaker 3: after the divorce was settled, you discovered that you didn't

1213
01:00:20,000 --> 01:00:21,600
Speaker 3: get the house. Your partner didn't get the house. The

1214
01:00:21,680 --> 01:00:24,560
Speaker 3: lawyer got the house. Right, This is the thing. So

1215
01:00:25,040 --> 01:00:27,120
Speaker 3: last year we had a bill introduced in Congress called

1216
01:00:27,120 --> 01:00:29,840
Speaker 3: the America Act. And one of the great tragedies of

1217
01:00:29,880 --> 01:00:33,440
Speaker 3: American politics is our brightest political science graduates go to

1218
01:00:33,480 --> 01:00:35,280
Speaker 3: work in the Senate where all they do is come

1219
01:00:35,360 --> 01:00:38,960
Speaker 3: up with acronyms for acts. So you know, the America

1220
01:00:38,960 --> 01:00:42,760
Speaker 3: accents for some of the ess A is for America, the

1221
01:00:42,840 --> 01:00:45,920
Speaker 3: country that I love. M is for motherhood, the value

1222
01:00:46,040 --> 01:00:49,160
Speaker 3: I admire. So the America Act says to the ad

1223
01:00:49,160 --> 01:00:51,200
Speaker 3: tech platforms, you have to split, you have to be

1224
01:00:51,200 --> 01:00:54,720
Speaker 3: structurally separated. You can represent sellers, you can represent buyers,

1225
01:00:54,800 --> 01:00:56,600
Speaker 3: you can be a marketplace, but you can't be all three.

1226
01:00:57,400 --> 01:00:59,919
Speaker 3: And the two main co sponsors of the America Act

1227
01:01:00,080 --> 01:01:04,200
Speaker 3: were Elizabeth Warren and Ted Cruz. Right, wow, that is

1228
01:01:04,240 --> 01:01:08,720
Speaker 3: a pretty bipartisan pill because even someone as terrible as

1229
01:01:08,720 --> 01:01:12,800
Speaker 3: Ted Cruz can look at an arrangement in which someone

1230
01:01:12,880 --> 01:01:15,400
Speaker 3: represents the buyer the seller and is the marketplace and

1231
01:01:15,560 --> 01:01:18,200
Speaker 3: is capturing three hundred percent of the traditional share for

1232
01:01:18,400 --> 01:01:22,920
Speaker 3: representatives who perform this function and say, this market cannot

1233
01:01:22,960 --> 01:01:25,880
Speaker 3: be fixed with a code of conduct. This market can

1234
01:01:25,920 --> 01:01:28,480
Speaker 3: only be fixed structurally.

1235
01:01:28,080 --> 01:01:31,280
Speaker 1: Or at least recognizes the politics of taking on big tech,

1236
01:01:31,400 --> 01:01:34,960
Speaker 1: right as something that is applicable to his constituents, Right,

1237
01:01:35,200 --> 01:01:37,400
Speaker 1: because I think, you know, I don't know that most

1238
01:01:37,400 --> 01:01:40,520
Speaker 1: of his most Texans might necessarily care about all that,

1239
01:01:40,560 --> 01:01:45,320
Speaker 1: but they do care about fairness. They do care about

1240
01:01:45,560 --> 01:01:47,440
Speaker 1: the fact that big tech has gotten so powerful.

1241
01:01:47,480 --> 01:01:49,280
Speaker 3: It is really interesting we've come to the place where

1242
01:01:49,320 --> 01:01:54,720
Speaker 3: it has been become a truly bipartisan code. Ben It's look,

1243
01:01:54,760 --> 01:01:56,520
Speaker 3: nothing moved out of the Senate last year.

1244
01:01:56,680 --> 01:02:01,520
Speaker 2: So the abyss do we move this shit forward, like

1245
01:02:01,920 --> 01:02:03,720
Speaker 2: to the to the real meat of it?

1246
01:02:04,160 --> 01:02:05,880
Speaker 3: What do we do? How do like?

1247
01:02:06,040 --> 01:02:10,080
Speaker 2: Maybe it's not us and my editor Matt Hughes, he

1248
01:02:10,480 --> 01:02:12,840
Speaker 2: suggested an idea. I can't do this because it make

1249
01:02:12,880 --> 01:02:16,480
Speaker 2: me morally corrupt. But I'm just saying American software pants, right,

1250
01:02:16,560 --> 01:02:20,960
Speaker 2: they're extremely and Matt, this is Matt's idea. You can

1251
01:02:21,080 --> 01:02:23,240
Speaker 2: there are a lot of patents you can file pants

1252
01:02:23,240 --> 01:02:23,760
Speaker 2: for anything.

1253
01:02:24,040 --> 01:02:25,280
Speaker 3: I'm not saying you do this.

1254
01:02:25,480 --> 01:02:27,400
Speaker 2: In fact, I know a lot of my listeners right

1255
01:02:27,440 --> 01:02:29,920
Speaker 2: now you're holding up a drug store, you're working on

1256
01:02:29,960 --> 01:02:33,920
Speaker 2: a new kind of tasteless poison, and you're or just

1257
01:02:34,040 --> 01:02:37,240
Speaker 2: regular stealing. It's a Friday, It's an easy day for you.

1258
01:02:37,800 --> 01:02:41,240
Speaker 2: Here's an idea. Surely someone could just anticipate the things

1259
01:02:41,280 --> 01:02:42,880
Speaker 2: the Open Eye was going to do in the future

1260
01:02:42,920 --> 01:02:46,000
Speaker 2: and just start filing patterns and then use those pans

1261
01:02:46,280 --> 01:02:51,200
Speaker 2: to mire them in endless lawsuits bullshit lawsuits. Not saying

1262
01:02:51,200 --> 01:02:53,960
Speaker 2: they should do that. But if you're not doing that,

1263
01:02:54,440 --> 01:02:57,640
Speaker 2: how do we actually break these people up? Is there

1264
01:02:57,680 --> 01:03:02,680
Speaker 2: a way for regular people to contribute towards this actual change?

1265
01:03:02,720 --> 01:03:05,360
Speaker 2: Because it feels like relying on the governments is the problem.

1266
01:03:05,400 --> 01:03:07,520
Speaker 3: Well, let me tell yes, sorry, let me tell you

1267
01:03:07,560 --> 01:03:07,880
Speaker 3: a story.

1268
01:03:07,920 --> 01:03:09,520
Speaker 2: I don't mean that in like the by the way,

1269
01:03:09,520 --> 01:03:11,680
Speaker 2: the anal kick like we can't rely on the government

1270
01:03:11,720 --> 01:03:13,440
Speaker 2: just it doesn't seem like the weapons of government.

1271
01:03:13,760 --> 01:03:16,720
Speaker 3: Let me tell a story about as yeah, yeah, about

1272
01:03:16,720 --> 01:03:18,800
Speaker 3: a man who was in the wilderness, a man who

1273
01:03:18,840 --> 01:03:21,680
Speaker 3: had ideas that everybody thought were crazy, a man called

1274
01:03:21,720 --> 01:03:25,640
Speaker 3: Milton Friedman, right, oh, Christ. In the nineteen sixties, Milton

1275
01:03:25,640 --> 01:03:28,160
Speaker 3: Friedman had this idea that all of the gains of

1276
01:03:28,200 --> 01:03:30,680
Speaker 3: the Great Society and the New Deal should be rolled back.

1277
01:03:30,720 --> 01:03:32,400
Speaker 3: So there are problems with the New Deal in the

1278
01:03:32,400 --> 01:03:34,720
Speaker 3: Great Society. They excluded black people, they excluded gay people,

1279
01:03:34,720 --> 01:03:36,560
Speaker 3: they excluded women to a large extent, and so on.

1280
01:03:36,840 --> 01:03:40,040
Speaker 3: That wasn't Milton Friedman's problem with it. Problem with it

1281
01:03:40,080 --> 01:03:42,560
Speaker 3: was who had included, not who had excluded. And he

1282
01:03:42,680 --> 01:03:45,720
Speaker 3: was like, we need more forelock tugging plubs, right, like,

1283
01:03:45,880 --> 01:03:48,840
Speaker 3: you shouldn't expect to have a dignified retirement. You shouldn't

1284
01:03:48,840 --> 01:03:50,840
Speaker 3: expect that your children will go to school for free,

1285
01:03:50,880 --> 01:03:54,080
Speaker 3: and so on. And people would say, Milton, people like that, shit,

1286
01:03:54,760 --> 01:03:56,400
Speaker 3: how are you going to make that shit happen. And

1287
01:03:56,440 --> 01:04:00,240
Speaker 3: he would say that in times of crisis, ideas can

1288
01:04:00,240 --> 01:04:02,840
Speaker 3: move from the periphery to the center. So our job

1289
01:04:03,240 --> 01:04:05,920
Speaker 3: is to keep ideas lying around so that when the

1290
01:04:05,960 --> 01:04:08,920
Speaker 3: crisis arises, we can move them into the center. And

1291
01:04:08,920 --> 01:04:11,360
Speaker 3: that crisis was the oil crisis of the nineteen seventies.

1292
01:04:11,760 --> 01:04:13,920
Speaker 3: So I like to quote Milton Friedman because I like

1293
01:04:13,920 --> 01:04:16,640
Speaker 3: to imagine that he looks up from that spit that's

1294
01:04:16,640 --> 01:04:20,200
Speaker 3: protruding from his mouth and gargles a curse as he

1295
01:04:20,200 --> 01:04:23,320
Speaker 3: hears his words. Him and Jack Welch, and you know,

1296
01:04:23,360 --> 01:04:25,760
Speaker 3: the demons laugh and they throw more molten shit on

1297
01:04:25,800 --> 01:04:29,880
Speaker 3: his naked body. But you know, if there's one thing

1298
01:04:29,880 --> 01:04:32,720
Speaker 3: that Milton Friedman has bequeathed us besides this theory change,

1299
01:04:32,720 --> 01:04:37,360
Speaker 3: it's an abundance of crises. Right. We have so many

1300
01:04:37,480 --> 01:04:41,720
Speaker 3: foreseeable crises on our horizon, crises of technology, climate crises,

1301
01:04:41,760 --> 01:04:45,720
Speaker 3: economic crises, legitimacy crises for the Supreme Court, and so on,

1302
01:04:46,440 --> 01:04:50,800
Speaker 3: and having these ideas lying around like being part of

1303
01:04:51,680 --> 01:04:54,280
Speaker 3: a group of people who say, look, right now, this

1304
01:04:54,400 --> 01:04:57,040
Speaker 3: is impossible, but this is like just because it's just

1305
01:04:57,080 --> 01:04:59,240
Speaker 3: because it's hard, it doesn't mean that we should do

1306
01:04:59,280 --> 01:05:01,200
Speaker 3: something easier. If it won't work, you don't look for

1307
01:05:01,240 --> 01:05:03,480
Speaker 3: your keys under the lamp post. I get it. If

1308
01:05:03,480 --> 01:05:05,400
Speaker 3: you wanted to get there, I wouldn't start from here.

1309
01:05:05,800 --> 01:05:07,400
Speaker 3: But this is the thing we have to do. And

1310
01:05:07,400 --> 01:05:09,760
Speaker 3: if we keep talking about the thing we have to do,

1311
01:05:10,200 --> 01:05:12,439
Speaker 3: then when the crisis comes and someone says, Jesus Christ,

1312
01:05:12,480 --> 01:05:15,120
Speaker 3: we've got to do something here, we can say, here's

1313
01:05:15,160 --> 01:05:15,920
Speaker 3: the thing we have to do.

1314
01:05:16,000 --> 01:05:18,520
Speaker 1: So it starts with breaking them up, then, I mean,

1315
01:05:18,520 --> 01:05:20,919
Speaker 1: I think that that's well, you know, I think both

1316
01:05:21,000 --> 01:05:23,000
Speaker 1: Corey and I would probably agree that that's pretty high

1317
01:05:23,000 --> 01:05:25,680
Speaker 1: on the priority list. It makes a lot of things easier,

1318
01:05:25,680 --> 01:05:27,480
Speaker 1: and it would make a lot of things better. And

1319
01:05:27,560 --> 01:05:29,920
Speaker 1: it's something that's also within sort of the realm of

1320
01:05:30,360 --> 01:05:32,600
Speaker 1: possibility for a lot of reasons. Again, that's sort of

1321
01:05:33,000 --> 01:05:35,680
Speaker 1: that you know, it might be a flimsy bipartisanship right now,

1322
01:05:35,680 --> 01:05:39,600
Speaker 1: but it is a bipartisanship nominally, and so it's it's

1323
01:05:39,640 --> 01:05:42,520
Speaker 1: it's something that's actually sort of more imaginable than a

1324
01:05:42,520 --> 01:05:47,080
Speaker 1: lot of other happen It's happened before Bell systems. Yeah,

1325
01:05:47,160 --> 01:05:48,480
Speaker 1: and you know, I think there's a lot that you

1326
01:05:48,480 --> 01:05:52,200
Speaker 1: can do. I think there's you know, as we've seen

1327
01:05:52,240 --> 01:05:54,840
Speaker 1: the tech industry sort of you know, it is wealth

1328
01:05:54,920 --> 01:05:57,919
Speaker 1: concentrate and it's sort of calcify, and each of those

1329
01:05:57,920 --> 01:06:02,240
Speaker 1: things that that Corey mentioned earlier on gets sealed off

1330
01:06:02,320 --> 01:06:05,080
Speaker 1: to most people. Well, you see more anger, and you

1331
01:06:05,120 --> 01:06:07,520
Speaker 1: see an industry that doesn't historically have a lot of

1332
01:06:07,520 --> 01:06:11,880
Speaker 1: interesting in organizing or in sort of activism becoming much

1333
01:06:11,920 --> 01:06:16,080
Speaker 1: more so. So I think that is another area that's

1334
01:06:16,200 --> 01:06:18,520
Speaker 1: ripe for action. You probably have a lot of listeners

1335
01:06:18,560 --> 01:06:20,640
Speaker 1: who are in the tech industry or related to the

1336
01:06:20,680 --> 01:06:26,680
Speaker 1: tech industry, and startingly underneath cause outside Google, that's the mechanics,

1337
01:06:26,720 --> 01:06:30,080
Speaker 1: might all might might be the mechanics, right, Yeah, they

1338
01:06:30,120 --> 01:06:31,640
Speaker 1: might already be unionized, but they should.

1339
01:06:31,720 --> 01:06:33,360
Speaker 3: But organizing, I think is a.

1340
01:06:33,280 --> 01:06:38,120
Speaker 1: Really really ripe area where you can really start to

1341
01:06:38,160 --> 01:06:39,240
Speaker 1: move the needle and how.

1342
01:06:39,320 --> 01:06:43,160
Speaker 2: Software developers actually unionize, Yeah they can.

1343
01:06:43,320 --> 01:06:45,560
Speaker 1: So when I one of my organizing efforts, I was

1344
01:06:45,600 --> 01:06:49,479
Speaker 1: at Medium and I and and Medium was at the time.

1345
01:06:49,640 --> 01:06:52,880
Speaker 3: They've since jettisoned all of their editorial employees.

1346
01:06:52,560 --> 01:06:54,720
Speaker 1: Like me, So there's no none, none of those like

1347
01:06:54,760 --> 01:06:57,560
Speaker 1: three times as well, yeah, I was I think the last.

1348
01:06:57,360 --> 01:07:01,919
Speaker 3: Time the third wave Choral bleaching. Yeah, they just launch

1349
01:07:02,000 --> 01:07:03,720
Speaker 3: them out of a cannon everything once in a while.

1350
01:07:04,400 --> 01:07:06,880
Speaker 1: But it was it was half editorial and half tech,

1351
01:07:06,920 --> 01:07:11,240
Speaker 1: and there was genuine and uh you know, really sort

1352
01:07:11,240 --> 01:07:15,400
Speaker 1: of animated interest in organizing, and we got so close,

1353
01:07:15,440 --> 01:07:18,640
Speaker 1: we got within one one vote, and it wasn't you know,

1354
01:07:18,760 --> 01:07:22,560
Speaker 1: for them, it wasn't about you know, I'm sure they

1355
01:07:22,560 --> 01:07:25,280
Speaker 1: wanted their their salaries to be a little bit higher

1356
01:07:25,360 --> 01:07:29,400
Speaker 1: or whatever, but that wasn't the driving, uh, motivating factor.

1357
01:07:29,960 --> 01:07:32,680
Speaker 1: It was they didn't like a lot of the direction

1358
01:07:33,000 --> 01:07:34,840
Speaker 1: that medium was going. They didn't like a lot of

1359
01:07:34,840 --> 01:07:37,320
Speaker 1: the policies that medium had, they didn't like a lot

1360
01:07:37,360 --> 01:07:39,960
Speaker 1: of uh, you know what the founder the power of

1361
01:07:40,000 --> 01:07:42,560
Speaker 1: the that the founder had to wield over the entire platform,

1362
01:07:43,360 --> 01:07:46,640
Speaker 1: and organizing is one way to sort of claw back

1363
01:07:46,720 --> 01:07:49,240
Speaker 1: some of that power. I mean, in some cases, it's

1364
01:07:49,280 --> 01:07:52,080
Speaker 1: almost like when you have a weird situation like Meta

1365
01:07:52,160 --> 01:07:55,000
Speaker 1: with Zuckerberg at top, as like the boy king who

1366
01:07:55,240 --> 01:07:57,720
Speaker 1: is just going to rule that forever barring.

1367
01:07:57,400 --> 01:07:59,160
Speaker 3: Some fireable right exactly.

1368
01:07:59,680 --> 01:08:01,640
Speaker 1: But well, most tech companies are not like that, and

1369
01:08:01,880 --> 01:08:04,560
Speaker 1: you can begin to you know, sort of wield more

1370
01:08:04,640 --> 01:08:07,240
Speaker 1: influence internally if you join some of those efforts. There's

1371
01:08:07,240 --> 01:08:10,760
Speaker 1: a lot of great unions and organizers working in that

1372
01:08:10,800 --> 01:08:12,800
Speaker 1: space right now. So that's just one thing that you

1373
01:08:12,840 --> 01:08:15,760
Speaker 1: can that you can start to get involved in.

1374
01:08:15,800 --> 01:08:17,880
Speaker 3: You yeah, let me say, you know, you said can

1375
01:08:17,920 --> 01:08:19,320
Speaker 3: we do this? And you said we have to break

1376
01:08:19,320 --> 01:08:20,960
Speaker 3: them up. Well, like the thing that stops us from

1377
01:08:21,040 --> 01:08:22,760
Speaker 3: unionizing is also the thing that stops us from breaking

1378
01:08:22,760 --> 01:08:24,840
Speaker 3: them up, which is that they're powerful. Right, And so

1379
01:08:24,880 --> 01:08:27,599
Speaker 3: the reason that we practiced anti trust law the way

1380
01:08:27,600 --> 01:08:30,400
Speaker 3: we did until the Carter administration was not just because

1381
01:08:30,400 --> 01:08:32,920
Speaker 3: we wanted to preserve choice or competition. It was because

1382
01:08:32,920 --> 01:08:35,479
Speaker 3: when companies get too big to fail, they become too

1383
01:08:35,479 --> 01:08:37,479
Speaker 3: big to jail. Right. Once a company's more powerful than

1384
01:08:37,520 --> 01:08:40,840
Speaker 3: the government. IBM, you know, was suit for anti trust

1385
01:08:40,920 --> 01:08:43,519
Speaker 3: violations from nineteen seventy to nineteen eighty two, and every

1386
01:08:43,560 --> 01:08:46,080
Speaker 3: year for twelve consecutive years, they spent more on lawyers

1387
01:08:46,120 --> 01:08:48,240
Speaker 3: to fight the DOJ Anti Trust Division than all of

1388
01:08:48,280 --> 01:08:51,600
Speaker 3: the lawyers at the DOJ Anti Trust Division costs combined

1389
01:08:51,920 --> 01:08:55,439
Speaker 3: for all anti trust cases in America for twelve consecutive years.

1390
01:08:55,439 --> 01:08:57,840
Speaker 2: There's no way to limit their ability to fight back

1391
01:08:57,880 --> 01:08:59,200
Speaker 2: as well, because that'd be undemocrats.

1392
01:08:59,240 --> 01:09:01,880
Speaker 3: So once they're once they're a monopoly, right then you know,

1393
01:09:01,920 --> 01:09:04,760
Speaker 3: like the best time to stall monopoly forming is is

1394
01:09:05,040 --> 01:09:08,360
Speaker 3: But look, before there is a law, there must be

1395
01:09:08,439 --> 01:09:11,000
Speaker 3: a crime, you know. Lenny Bruce points out that if

1396
01:09:11,040 --> 01:09:13,000
Speaker 3: we have a law against fucking chicken, someone must have

1397
01:09:13,040 --> 01:09:15,680
Speaker 3: fucked a chicken at some point. Right. So before we

1398
01:09:15,760 --> 01:09:21,040
Speaker 3: had antis, before we had anti trust law, we had

1399
01:09:21,080 --> 01:09:24,000
Speaker 3: monopolists right right, that's where we got the anti trust

1400
01:09:24,040 --> 01:09:27,880
Speaker 3: law from. And specifically we had monopolists like John D. Rockefeller,

1401
01:09:27,920 --> 01:09:30,000
Speaker 3: who is still the richest man that ever lived, the

1402
01:09:30,040 --> 01:09:33,960
Speaker 3: most powerful, the most ruthless, terrible piece of shit, and

1403
01:09:34,360 --> 01:09:36,640
Speaker 3: we brought him low. And like the way that we

1404
01:09:36,720 --> 01:09:39,160
Speaker 3: did it, it happened in living memories, like nineteen twelve.

1405
01:09:39,200 --> 01:09:41,519
Speaker 3: So there's people alive today who were mentored by the

1406
01:09:41,560 --> 01:09:43,960
Speaker 3: people who did it right, and then there's people alive

1407
01:09:43,960 --> 01:09:46,280
Speaker 3: today who are those people's mentors, who are still working

1408
01:09:46,680 --> 01:09:49,959
Speaker 3: and still on the job. Right, it's not like embalming pharaohs.

1409
01:09:49,960 --> 01:09:52,559
Speaker 3: It's not a lost art from a fallen civilization. The

1410
01:09:52,600 --> 01:09:53,519
Speaker 3: thing we know how to do.

1411
01:09:53,680 --> 01:09:56,959
Speaker 2: And yeah, like breaking up for me, bring him low though.

1412
01:09:57,120 --> 01:10:00,120
Speaker 3: It's a great story. So woman called Ida Tarbell was

1413
01:10:00,160 --> 01:10:02,599
Speaker 3: the first woman in America get an undergraduate science degree.

1414
01:10:02,640 --> 01:10:04,720
Speaker 3: She was trained as a biologist sick. She was the

1415
01:10:04,840 --> 01:10:07,439
Speaker 3: daughter of a Pennsylvania oil man who was destroyed by

1416
01:10:07,479 --> 01:10:10,519
Speaker 3: the Standard Oil Trust Wow, and she went to work

1417
01:10:10,560 --> 01:10:14,160
Speaker 3: for Colliers, which was the biggest magazine in America at

1418
01:10:14,160 --> 01:10:16,800
Speaker 3: the time. Were one of the biggest, and she serialized

1419
01:10:16,840 --> 01:10:22,000
Speaker 3: a two volume muckraking history that pitilessly laid out exactly

1420
01:10:22,400 --> 01:10:25,080
Speaker 3: how the John D. Rockefeller scam worked. It had a

1421
01:10:25,160 --> 01:10:27,040
Speaker 3: very good title, she called it the History of the

1422
01:10:27,040 --> 01:10:30,639
Speaker 3: Standard Oil Company, Volumes one and two. It was super viral,

1423
01:10:30,960 --> 01:10:33,679
Speaker 3: and at the end of it, the Incoe political will

1424
01:10:33,720 --> 01:10:36,040
Speaker 3: that we'd had that said, like something is really wrong

1425
01:10:36,560 --> 01:10:39,400
Speaker 3: turned into a very sharp political will that said, we

1426
01:10:39,479 --> 01:10:41,639
Speaker 3: know how the scam works, and we demand that something

1427
01:10:41,640 --> 01:10:43,280
Speaker 3: to be done about it. And the Sherman Act, which

1428
01:10:43,280 --> 01:10:46,000
Speaker 3: had been hanging around for twenty years, finally was taken

1429
01:10:46,040 --> 01:10:48,920
Speaker 3: off the shelf and mobilized against John D. Rockefeller, and

1430
01:10:48,960 --> 01:10:49,639
Speaker 3: we brought him low.

1431
01:10:49,920 --> 01:10:51,600
Speaker 2: So this is I'm so glad you brought up the

1432
01:10:51,600 --> 01:10:54,920
Speaker 2: story which I just learned. First of all, I'm gonna

1433
01:10:54,920 --> 01:10:57,360
Speaker 2: look at cool people who did cool stuff. If Maggie's

1434
01:10:57,360 --> 01:10:59,080
Speaker 2: not done that, she needs to hear this, that is.

1435
01:10:59,120 --> 01:11:02,160
Speaker 3: And she then became a leading suffragist and was one

1436
01:11:02,160 --> 01:11:04,000
Speaker 3: of the greatest orators of American history.

1437
01:11:04,680 --> 01:11:08,840
Speaker 2: Just first of all, go eu to Tarbell original poster. Yeah,

1438
01:11:08,960 --> 01:11:13,360
Speaker 2: like the like, genuinely like amazing. But also I think

1439
01:11:13,439 --> 01:11:16,559
Speaker 2: this speaks to something. I'm speaking to anyone who is

1440
01:11:16,640 --> 01:11:19,439
Speaker 2: a reporter, who's listening to this right now, there is

1441
01:11:19,479 --> 01:11:22,280
Speaker 2: this common sense that why are we doing this, Why

1442
01:11:22,320 --> 01:11:24,439
Speaker 2: are we cataloging this? They're still gonna do these things?

1443
01:11:24,520 --> 01:11:29,040
Speaker 2: Why bother? And the answer is that fucking story Hindenberg Research.

1444
01:11:29,479 --> 01:11:32,040
Speaker 2: I don't know if I agree with all their methods,

1445
01:11:32,320 --> 01:11:34,680
Speaker 2: but the fact is we need more people out there.

1446
01:11:34,720 --> 01:11:35,880
Speaker 3: And I do this too. Well.

1447
01:11:35,880 --> 01:11:39,240
Speaker 2: You don't necessarily write these fuckers are bad, they are right?

1448
01:11:39,360 --> 01:11:43,440
Speaker 2: Why and write in detail because it sounds like historically

1449
01:11:43,479 --> 01:11:45,200
Speaker 2: that actually eventually works.

1450
01:11:45,280 --> 01:11:46,920
Speaker 3: You know, there is a there's a phrase out of

1451
01:11:46,920 --> 01:11:49,280
Speaker 3: the finance sector called migo. It stands from my eyes

1452
01:11:49,360 --> 01:11:51,280
Speaker 3: glaze over, And it's the idea that if you make

1453
01:11:51,320 --> 01:11:53,559
Speaker 3: the prospectus thick enough, people will just assume that it's

1454
01:11:53,600 --> 01:11:55,840
Speaker 3: good because they can't possibly read it like the pile

1455
01:11:57,000 --> 01:12:03,160
Speaker 3: pony under it right, un unraveling migo, whether that's you know, Marco,

1456
01:12:03,240 --> 01:12:06,639
Speaker 3: Robbie and a Bathtub explaining synthetic collateralized at obligations, or

1457
01:12:07,080 --> 01:12:09,439
Speaker 3: you know, my last couple of novels, the Bazil and

1458
01:12:09,479 --> 01:12:12,799
Speaker 3: Red Team Blues are about explaining how real world private

1459
01:12:12,800 --> 01:12:15,599
Speaker 3: equity scams, cryptocurrency hustles and so on, how they work.

1460
01:12:17,360 --> 01:12:20,040
Speaker 3: Is I think the first step on the path to

1461
01:12:20,080 --> 01:12:23,080
Speaker 3: making people feel like they can see where the weak

1462
01:12:23,120 --> 01:12:26,479
Speaker 3: points are in this in this very large but very

1463
01:12:26,520 --> 01:12:29,080
Speaker 3: brittle edifice, and they can start go kicking at the

1464
01:12:29,080 --> 01:12:29,519
Speaker 3: week point.

1465
01:12:29,560 --> 01:12:32,880
Speaker 2: Because I think that something Google is very powerful. They

1466
01:12:32,920 --> 01:12:35,479
Speaker 2: have tens of billions of dollars in like sixteen billion

1467
01:12:35,520 --> 01:12:39,519
Speaker 2: dollars a profit every quarter. They are unbreakable by traditional means. However,

1468
01:12:40,200 --> 01:12:43,760
Speaker 2: they are also culturally weak. They are a patchwork of

1469
01:12:43,760 --> 01:12:46,639
Speaker 2: people who've been there two minutes and twenty years. They

1470
01:12:46,840 --> 01:12:49,599
Speaker 2: don't fire some Ben Gomes, the gouy around Google search

1471
01:12:49,600 --> 01:12:51,400
Speaker 2: Board provate God took over. They put them in the

1472
01:12:51,439 --> 01:12:55,080
Speaker 2: corner in SVP of education because they know if Ben left,

1473
01:12:55,920 --> 01:12:59,440
Speaker 2: he could very easily at least raise money to completely

1474
01:12:59,680 --> 01:13:04,360
Speaker 2: a real Google competitor. But the thing is, the asshole

1475
01:13:04,400 --> 01:13:07,400
Speaker 2: doesn't talk to the mouth or the elbow. Nothing, there

1476
01:13:07,439 --> 01:13:10,080
Speaker 2: is no form. But as they get bigger, they are

1477
01:13:10,160 --> 01:13:12,760
Speaker 2: weaker on some levels. And I think it's just something

1478
01:13:12,800 --> 01:13:14,479
Speaker 2: I'm doing with the show. And actually both of you

1479
01:13:14,520 --> 01:13:17,920
Speaker 2: had done amazingly with your work is breaking down these

1480
01:13:17,920 --> 01:13:20,120
Speaker 2: weak points, these pain points. Brian, you did the great

1481
01:13:20,120 --> 01:13:23,080
Speaker 2: thing about the mechanical turk for example, how it's very

1482
01:13:23,120 --> 01:13:26,920
Speaker 2: similar to how generative AI works. And it's just I

1483
01:13:26,960 --> 01:13:29,439
Speaker 2: think it's strange. I've heard and I won't name names,

1484
01:13:29,439 --> 01:13:31,800
Speaker 2: but I've heard people kind of make the suggestion that well,

1485
01:13:32,120 --> 01:13:33,960
Speaker 2: why why should we bother?

1486
01:13:34,040 --> 01:13:35,200
Speaker 3: Why, Well, they're so.

1487
01:13:35,240 --> 01:13:38,880
Speaker 2: Powerful, And the answer is they're actually terrified of this.

1488
01:13:38,960 --> 01:13:41,880
Speaker 2: They do not want this. This is scary. Do it

1489
01:13:42,040 --> 01:13:42,719
Speaker 2: every day?

1490
01:13:43,200 --> 01:13:43,439
Speaker 3: Yeah?

1491
01:13:43,520 --> 01:13:45,519
Speaker 1: Look at I mean again, we mentioned this earlier, but

1492
01:13:45,520 --> 01:13:50,800
Speaker 1: look look how Google reacted when a single credible.

1493
01:13:50,640 --> 01:13:51,880
Speaker 3: Competitor entered the field.

1494
01:13:51,960 --> 01:13:55,160
Speaker 1: Oh but they ran around like chickens with their heads

1495
01:13:55,200 --> 01:13:58,160
Speaker 1: cut off and they scrambled to find a product.

1496
01:13:58,200 --> 01:13:59,600
Speaker 3: It was internal turmoil.

1497
01:13:59,680 --> 01:14:04,040
Speaker 1: It is. If anything, it wasn't the reaction of a

1498
01:14:04,080 --> 01:14:09,360
Speaker 1: company that is convinced of the power and security of

1499
01:14:09,400 --> 01:14:12,400
Speaker 1: its products and its placement in the marketplace.

1500
01:14:12,960 --> 01:14:13,439
Speaker 3: This was.

1501
01:14:13,640 --> 01:14:16,280
Speaker 1: This was a company that is like, as you were saying,

1502
01:14:16,280 --> 01:14:21,040
Speaker 1: pretty profoundly insecure and reliant on all these deals in

1503
01:14:21,120 --> 01:14:24,479
Speaker 1: order to maintain its position where it's paying out a

1504
01:14:24,520 --> 01:14:25,280
Speaker 1: great deal of money.

1505
01:14:25,280 --> 01:14:28,200
Speaker 3: I mean this, it's it seems to me more.

1506
01:14:28,120 --> 01:14:30,120
Speaker 1: Like a house of cards that that could collapse if

1507
01:14:30,160 --> 01:14:33,639
Speaker 1: the right one is pulled out. And to to add

1508
01:14:33,720 --> 01:14:37,759
Speaker 1: on too, what Corey was saying, Uh, you know another

1509
01:14:38,080 --> 01:14:40,160
Speaker 1: work that that I that that I read while I

1510
01:14:40,160 --> 01:14:42,000
Speaker 1: was researching the Luddite Book, which was one of the

1511
01:14:42,040 --> 01:14:45,639
Speaker 1: first efforts to sort of quote rescue the Lutdites from

1512
01:14:45,840 --> 01:14:49,040
Speaker 1: from from condescension, was E. P. Thompson's The Making of

1513
01:14:49,080 --> 01:14:51,519
Speaker 1: the English Working Class, and it tries to tell the

1514
01:14:51,600 --> 01:14:53,720
Speaker 1: story of like, how did the how did we get

1515
01:14:53,720 --> 01:14:57,360
Speaker 1: to the point where workers came together and said, wait

1516
01:14:57,400 --> 01:15:00,280
Speaker 1: a minute, we have enough power to actually I have

1517
01:15:00,320 --> 01:15:01,000
Speaker 1: some change.

1518
01:15:01,400 --> 01:15:02,000
Speaker 3: How did that?

1519
01:15:02,120 --> 01:15:04,400
Speaker 1: How did it because it didn't exist before? How did

1520
01:15:04,439 --> 01:15:07,320
Speaker 1: workers start to see themselves as part of a class

1521
01:15:07,439 --> 01:15:11,440
Speaker 1: or have solidarity? And it's just filled with all these examples,

1522
01:15:12,280 --> 01:15:15,559
Speaker 1: you know, of little fights that you know have otherwise

1523
01:15:15,560 --> 01:15:18,479
Speaker 1: been completely lost to history, where people stood up for

1524
01:15:18,560 --> 01:15:22,759
Speaker 1: something and you know, were crushed and then everybody forgot

1525
01:15:22,760 --> 01:15:23,120
Speaker 1: about it.

1526
01:15:23,160 --> 01:15:23,960
Speaker 3: By and large.

1527
01:15:24,400 --> 01:15:28,000
Speaker 1: But the neighbors didn't forget, the local newspaper men didn't forget,

1528
01:15:28,680 --> 01:15:32,000
Speaker 1: the families didn't forget. They're recorded in oral histories. They

1529
01:15:32,040 --> 01:15:35,559
Speaker 1: formed this tapestry. So I feel like it's it's always

1530
01:15:35,560 --> 01:15:37,920
Speaker 1: a bad idea to feel like nothing that we're doing

1531
01:15:38,360 --> 01:15:42,080
Speaker 1: matters or registers, because it is, and it can reverberate,

1532
01:15:42,120 --> 01:15:43,920
Speaker 1: and it can echo, and it can coalesce, and it

1533
01:15:43,920 --> 01:15:45,200
Speaker 1: can snowball really quickly.

1534
01:15:46,240 --> 01:15:48,880
Speaker 2: And if things aren't really working out for you right now,

1535
01:15:48,920 --> 01:15:52,320
Speaker 2: if the crowball won't get the ATM open, if even

1536
01:15:52,439 --> 01:15:54,320
Speaker 2: driving a car doesn't get into it, but you still

1537
01:15:54,360 --> 01:15:56,519
Speaker 2: have some left open money, perhaps you could check out

1538
01:15:56,520 --> 01:15:58,880
Speaker 2: one of the following products. I think that this will

1539
01:15:58,960 --> 01:16:01,360
Speaker 2: solve probably every problem you've ever had.

1540
01:16:01,680 --> 01:16:17,160
Speaker 3: I hope it's SCRIPTO. So I want to bring up

1541
01:16:17,200 --> 01:16:19,719
Speaker 3: one way in which Google is unexpectedly weak, in which

1542
01:16:19,720 --> 01:16:22,920
Speaker 3: its strength strength is a weakness. And this is a

1543
01:16:23,120 --> 01:16:25,040
Speaker 3: characteristic of all the big tech companies, which is that

1544
01:16:25,080 --> 01:16:28,280
Speaker 3: they do the same shitty thing everywhere, which means that

1545
01:16:28,360 --> 01:16:30,720
Speaker 3: if there's a case built against a tech company by

1546
01:16:30,720 --> 01:16:33,240
Speaker 3: a regulator, and are a big, powerful country like the

1547
01:16:33,320 --> 01:16:36,960
Speaker 3: United States, all of those facts will be almost identical

1548
01:16:37,400 --> 01:16:40,160
Speaker 3: in much smaller countries like South Korea. We've actually seen

1549
01:16:40,200 --> 01:16:44,320
Speaker 3: this where cases against Apple for antitrust have been effectively

1550
01:16:45,080 --> 01:16:50,280
Speaker 3: recycled in South Korea Japan and successfully so. Right, so,

1551
01:16:50,920 --> 01:16:54,920
Speaker 3: all of the world's governments are facing the same adversary.

1552
01:16:55,000 --> 01:16:57,439
Speaker 3: So even if these companies are bigger than most countries,

1553
01:16:57,439 --> 01:16:58,639
Speaker 3: they're not bigger than all many countries.

1554
01:16:58,640 --> 01:17:00,800
Speaker 2: When you say a shitty thing, what do you mean, Oh,

1555
01:17:01,040 --> 01:17:02,280
Speaker 2: you know, like specific Apple.

1556
01:17:02,320 --> 01:17:05,559
Speaker 3: Apple has this Danegeld system where they take thirty cents

1557
01:17:05,560 --> 01:17:07,400
Speaker 3: out of every dollar you spend on an app, and

1558
01:17:07,400 --> 01:17:09,439
Speaker 3: it's super anti competitive, and they have all these ways

1559
01:17:09,439 --> 01:17:12,479
Speaker 3: that they block people from trying to circumvent it, and

1560
01:17:12,520 --> 01:17:16,320
Speaker 3: it lets them control certain markets, and it's just it's

1561
01:17:17,280 --> 01:17:20,719
Speaker 3: it's illegal under most countries systems of law. Here's here's

1562
01:17:20,720 --> 01:17:22,479
Speaker 3: a fun fact for you. After World War Two, the

1563
01:17:22,520 --> 01:17:25,200
Speaker 3: American technocrats who went around and rebuilt the legal systems

1564
01:17:25,200 --> 01:17:29,960
Speaker 3: of Europe and Japan just basically copypasted American anti trust laws.

1565
01:17:29,960 --> 01:17:33,559
Speaker 3: Oh yeah, so, and here's another funny thing. They were

1566
01:17:33,640 --> 01:17:36,880
Speaker 3: keenly aware of how important monopolies were to the rise

1567
01:17:36,880 --> 01:17:39,479
Speaker 3: of fascism and the access powers, and so one of

1568
01:17:39,479 --> 01:17:41,280
Speaker 3: the things they did when they got to Germany and

1569
01:17:41,360 --> 01:17:45,960
Speaker 3: Japan and Italy was smashed their monopolies because they said

1570
01:17:46,120 --> 01:17:48,280
Speaker 3: monopolies lead to fascism.

1571
01:17:48,720 --> 01:17:52,080
Speaker 2: But the thing is as well is monopolies are bad

1572
01:17:52,120 --> 01:17:52,759
Speaker 2: for everyone.

1573
01:17:52,840 --> 01:17:54,519
Speaker 3: It is a bipartisan issue.

1574
01:17:54,600 --> 01:17:57,240
Speaker 2: Roger mcnammey, who I mentioned Elie Facebook and bested though, Yeah,

1575
01:17:57,320 --> 01:17:58,040
Speaker 2: really good friend mine.

1576
01:17:58,080 --> 01:17:58,719
Speaker 3: He's wonderful.

1577
01:17:59,120 --> 01:18:01,120
Speaker 2: He really was, Like I was talking to about something

1578
01:18:01,120 --> 01:18:04,960
Speaker 2: I was writing, and I within shitification. I did the

1579
01:18:05,040 --> 01:18:07,439
Speaker 2: raw economy, which is very similar, but I know my

1580
01:18:07,479 --> 01:18:09,840
Speaker 2: central failing in it. And it was these monopolies. And

1581
01:18:10,560 --> 01:18:13,000
Speaker 2: it's just this sense where you get these Sam Wulton

1582
01:18:13,040 --> 01:18:15,120
Speaker 2: types who want the monopolies. You get these and recent

1583
01:18:15,160 --> 01:18:17,880
Speaker 2: types want to invest in monopolies for the money, but

1584
01:18:18,600 --> 01:18:22,640
Speaker 2: they're shitty businesses. Monopolies are like Google is probably is

1585
01:18:22,640 --> 01:18:27,160
Speaker 2: an incredible business, but inevitably must die, like it's going

1586
01:18:27,200 --> 01:18:31,360
Speaker 2: to die eventually, and fast or slow it must because

1587
01:18:32,280 --> 01:18:33,719
Speaker 2: eventually you run out of humans.

1588
01:18:34,520 --> 01:18:37,160
Speaker 3: Well, this is the problem Amazon is facing, right. They

1589
01:18:37,240 --> 01:18:39,360
Speaker 3: keep looking at the rate at which they're burning out

1590
01:18:40,000 --> 01:18:43,759
Speaker 3: warehouse workers and saying, well, all available semi skilled workers

1591
01:18:43,800 --> 01:18:46,040
Speaker 3: will have worked at an Amazon warehouse and no longer

1592
01:18:46,080 --> 01:18:49,599
Speaker 3: want to do so or have been permanently maimed by whatever.

1593
01:18:49,680 --> 01:18:52,000
Speaker 3: Originally it was twenty twenty four was their initial projection.

1594
01:18:52,160 --> 01:18:55,040
Speaker 3: That was their clarion call that made them start investing

1595
01:18:55,040 --> 01:18:57,400
Speaker 3: more heavily in automation. Not in treating work I bake,

1596
01:18:57,600 --> 01:19:00,000
Speaker 3: not in making it better to work there. Yeah no, no, no,

1597
01:19:00,120 --> 01:19:03,000
Speaker 3: not not in the slightest no, just in in adding

1598
01:19:03,040 --> 01:19:05,200
Speaker 3: more of that. Now. I have a lot of lefty

1599
01:19:06,000 --> 01:19:10,439
Speaker 3: comrades who are skeptical of this anti monopoly stuff, and

1600
01:19:10,479 --> 01:19:13,040
Speaker 3: they say, look, I don't want a million choices. I

1601
01:19:13,080 --> 01:19:14,920
Speaker 3: don't want to go to Amazon looking for a light

1602
01:19:14,920 --> 01:19:18,439
Speaker 3: bulb and find ten million light bulbs. You already do right, well,

1603
01:19:18,479 --> 01:19:21,519
Speaker 3: you do right, exactly right. I want to go and like,

1604
01:19:21,560 --> 01:19:23,920
Speaker 3: I want to live in an orderly regulated world where

1605
01:19:23,960 --> 01:19:25,920
Speaker 3: I don't have to use the magic of the market

1606
01:19:26,000 --> 01:19:28,160
Speaker 3: to make sure that like my water isn't poison or

1607
01:19:28,160 --> 01:19:30,120
Speaker 3: that things aren't bad and so on. And there's something

1608
01:19:30,160 --> 01:19:33,160
Speaker 3: to that. I don't know. Everything has to be. We

1609
01:19:33,160 --> 01:19:36,000
Speaker 3: can have regulated monopolies, we can have state we can

1610
01:19:36,040 --> 01:19:36,519
Speaker 3: have state.

1611
01:19:36,560 --> 01:19:40,840
Speaker 2: Things like healthcare. Ye competition, but the.

1612
01:19:40,880 --> 01:19:45,240
Speaker 3: Thing that that competition gets you is not merely choice.

1613
01:19:45,760 --> 01:19:50,240
Speaker 3: It's a weak corporate sector. People really fail to understand

1614
01:19:50,240 --> 01:19:54,800
Speaker 3: this at their peril because although these companies appear to

1615
01:19:54,840 --> 01:19:57,759
Speaker 3: be at one another's throats, when you look more closely

1616
01:19:57,800 --> 01:20:00,760
Speaker 3: at it, they're really quite chummy. We've surface around us

1617
01:20:00,800 --> 01:20:04,000
Speaker 3: several times. Yeah, so you know, Apple says, oh, we're

1618
01:20:04,040 --> 01:20:07,400
Speaker 3: the non surveilling company, and Google and Facebook are the

1619
01:20:07,439 --> 01:20:10,040
Speaker 3: bad ones. They surveil and we're so different from them.

1620
01:20:10,400 --> 01:20:13,679
Speaker 3: But Apple like puts a surveillance tap in the pocket

1621
01:20:13,680 --> 01:20:16,679
Speaker 3: of every iPhone owner by defaulting to Google. I mean,

1622
01:20:16,960 --> 01:20:20,120
Speaker 3: Apple wants to block surveillance unless they're getting paid for it,

1623
01:20:20,120 --> 01:20:21,040
Speaker 3: so they block Faceto and.

1624
01:20:21,040 --> 01:20:24,320
Speaker 2: They don't do unless it's their and they.

1625
01:20:24,040 --> 01:20:28,040
Speaker 3: Do their own surveillance. Right. Google and Facebook allegedly are

1626
01:20:28,120 --> 01:20:30,559
Speaker 3: our great adversaries in the ad tech sector, except they

1627
01:20:30,600 --> 01:20:33,160
Speaker 3: have this illegal collusive arrangement where they divided up ad

1628
01:20:33,200 --> 01:20:35,360
Speaker 3: tech like the pope dividing up the new world called

1629
01:20:35,439 --> 01:20:40,679
Speaker 3: Jedi Blue. Right, you have Cheryl Sandberg moving from one

1630
01:20:41,439 --> 01:20:43,240
Speaker 3: firm to the other. Right, she was a Googler before

1631
01:20:43,280 --> 01:20:44,360
Speaker 3: she was at Facebook, and.

1632
01:20:44,320 --> 01:20:47,120
Speaker 2: Before that Mackenzine before that Larry Summ's Department's treasury.

1633
01:20:47,280 --> 01:20:50,160
Speaker 3: Yeah, and Facebook is stuffed with ex Apple people, and

1634
01:20:50,160 --> 01:20:52,720
Speaker 3: Apple is stuff with x Facebook people. That the way

1635
01:20:52,760 --> 01:20:56,640
Speaker 3: that you ascend through the ranks of a highly concentrated

1636
01:20:56,680 --> 01:21:00,879
Speaker 3: sector is through lateral moves because we within the firms,

1637
01:21:01,040 --> 01:21:03,160
Speaker 3: there are no boxes on the org chart for you

1638
01:21:03,280 --> 01:21:04,960
Speaker 3: to rise up to. Either someone has to die or

1639
01:21:05,000 --> 01:21:08,679
Speaker 3: become disgraced, right, and so it's only when a firm

1640
01:21:08,920 --> 01:21:12,360
Speaker 3: seeks someone from outside that you can actually jump up

1641
01:21:12,360 --> 01:21:14,439
Speaker 3: the rank, which is why you see, for example, people

1642
01:21:14,439 --> 01:21:17,719
Speaker 3: from Disney jumping to Universal and people from Universal jumping

1643
01:21:17,720 --> 01:21:18,880
Speaker 3: from Disney to ascend the right.

1644
01:21:18,960 --> 01:21:20,840
Speaker 2: Just to push back a little bit, isn't some of

1645
01:21:20,880 --> 01:21:22,519
Speaker 2: this just domain expertise though.

1646
01:21:23,320 --> 01:21:25,639
Speaker 3: In the sense that that's why they're doing it. Sure,

1647
01:21:26,000 --> 01:21:28,200
Speaker 3: But and you know, this is another problem with regulation,

1648
01:21:28,439 --> 01:21:31,160
Speaker 3: is that when a sector becomes highly concentrated, the domain

1649
01:21:31,200 --> 01:21:34,599
Speaker 3: expertise is siloed within the firms that you're hoping to regulate.

1650
01:21:34,880 --> 01:21:38,280
Speaker 3: And you know, there's a there's a not wrong point

1651
01:21:38,320 --> 01:21:40,840
Speaker 3: that people make about the revolving door, which is that

1652
01:21:41,240 --> 01:21:43,439
Speaker 3: if a sector consists of five companies, then everyone who

1653
01:21:43,520 --> 01:21:45,880
Speaker 3: understands those companies works for one of them. So where

1654
01:21:45,880 --> 01:21:47,920
Speaker 3: else are you going to get a regulator? Right? Of course,

1655
01:21:47,960 --> 01:21:49,600
Speaker 3: they hire ex Googlers.

1656
01:21:49,200 --> 01:21:51,719
Speaker 2: And at this point you have people where you only

1657
01:21:51,760 --> 01:21:54,200
Speaker 2: really hire if they've worked at a big tech firm. Sure,

1658
01:21:54,320 --> 01:21:56,240
Speaker 2: that's the only way you will know how to work

1659
01:21:56,439 --> 01:21:57,280
Speaker 2: very similar machines.

1660
01:21:57,280 --> 01:21:59,720
Speaker 3: Although I'm speaking of regulators, so sorry. The reason the

1661
01:21:59,840 --> 01:22:03,000
Speaker 3: f SEE is hiring x Comcast people, supposedly is that, like,

1662
01:22:03,120 --> 01:22:05,880
Speaker 3: who understands how the cable networks work except for people

1663
01:22:05,880 --> 01:22:07,120
Speaker 3: who work for one of the two or three big

1664
01:22:07,160 --> 01:22:10,920
Speaker 3: cable operators. Right, So there's a grain of truth to this.

1665
01:22:11,040 --> 01:22:13,080
Speaker 3: It's not entirely true, but there's a grain of truth

1666
01:22:13,120 --> 01:22:16,880
Speaker 3: to it. And the fix for it is not to

1667
01:22:17,000 --> 01:22:19,880
Speaker 3: let cable companies mark their own homework by parachuting their

1668
01:22:19,880 --> 01:22:22,639
Speaker 3: own people into the regulators. The fix is to make

1669
01:22:22,640 --> 01:22:27,120
Speaker 3: them small enough to be comprehensible, right, to make them

1670
01:22:27,280 --> 01:22:30,880
Speaker 3: small enough that outside parties can see what they're doing.

1671
01:22:30,640 --> 01:22:33,599
Speaker 2: But also a marketplace with tons of choices. It makes

1672
01:22:33,640 --> 01:22:37,000
Speaker 2: for a weaker corporate sector, but stronger companies, I would argue,

1673
01:22:37,040 --> 01:22:39,800
Speaker 2: because if you make a good fucking product, you can

1674
01:22:39,840 --> 01:22:42,320
Speaker 2: win a market. And I realize that this is not

1675
01:22:42,400 --> 01:22:44,960
Speaker 2: a perfect system at all, and that doesn't always happen,

1676
01:22:45,360 --> 01:22:49,040
Speaker 2: but at least to some extent, Apple has dominated because

1677
01:22:49,080 --> 01:22:52,400
Speaker 2: they aren't imperfect. And I know, listeners, I know you

1678
01:22:52,479 --> 01:22:54,880
Speaker 2: always am not hard enough about Apple. I'm doing an

1679
01:22:54,880 --> 01:22:56,760
Speaker 2: app Store episode. It's so hard to write, you want

1680
01:22:56,760 --> 01:22:59,559
Speaker 2: to write five thousand words. Jesus fucking But the things

1681
01:22:59,600 --> 01:23:03,559
Speaker 2: of Apple, they've done pretty well because they make good phone, phone,

1682
01:23:03,600 --> 01:23:06,880
Speaker 2: good laptop great, Like the laptops are great. These are

1683
01:23:06,920 --> 01:23:09,200
Speaker 2: good pieces of tech that do the job well. And

1684
01:23:09,320 --> 01:23:11,639
Speaker 2: yes they use monopolistic forces to keep where they are,

1685
01:23:12,960 --> 01:23:15,240
Speaker 2: but it also feels like a Google's phone division. They're like,

1686
01:23:15,280 --> 01:23:17,120
Speaker 2: why does this never work? And it's because it kind

1687
01:23:17,160 --> 01:23:20,840
Speaker 2: of like Android phones are good, but they've really why

1688
01:23:20,840 --> 01:23:23,360
Speaker 2: doesn't Google try and pay for my message? Well they shouldn't.

1689
01:23:23,400 --> 01:23:25,960
Speaker 2: They should actually really push our cs much harder. But

1690
01:23:25,960 --> 01:23:28,519
Speaker 2: they don't push it that hard. They could put a

1691
01:23:28,560 --> 01:23:31,200
Speaker 2: lot of more money behind our ces, or try and

1692
01:23:31,240 --> 01:23:33,120
Speaker 2: find a way to work without I know it's coming in,

1693
01:23:33,479 --> 01:23:35,960
Speaker 2: but it's like, like, doesn't really give a shit about

1694
01:23:36,000 --> 01:23:37,040
Speaker 2: Android doing super well.

1695
01:23:37,080 --> 01:23:37,880
Speaker 3: They just don't want.

1696
01:23:37,760 --> 01:23:40,559
Speaker 2: Apple to have everything. I guess it's so strange.

1697
01:23:40,560 --> 01:23:43,799
Speaker 3: It's hard to play criminology here, but I want to

1698
01:23:43,840 --> 01:23:47,559
Speaker 3: say that while competition is obviously imperfect, yes that in

1699
01:23:47,600 --> 01:23:50,320
Speaker 3: tech we do have a kind of secret power. And

1700
01:23:50,360 --> 01:23:52,719
Speaker 3: you ask. You started this conversation by asking what excites

1701
01:23:52,800 --> 01:23:54,880
Speaker 3: us about tech. One of the things that excites me

1702
01:23:54,920 --> 01:23:58,080
Speaker 3: about tech is a kind of nerdy principle, which is

1703
01:23:58,120 --> 01:24:01,360
Speaker 3: that all computers are We're in complete universal of onon

1704
01:24:01,439 --> 01:24:04,719
Speaker 3: noion machines. They can all run every program, which means

1705
01:24:04,720 --> 01:24:06,920
Speaker 3: that any program running on a computer that you have,

1706
01:24:07,000 --> 01:24:09,720
Speaker 3: whether it's your pocket Destruction rectangle, your laptop, or your

1707
01:24:09,760 --> 01:24:12,880
Speaker 3: game console, another program can run that modifies how it

1708
01:24:12,920 --> 01:24:14,800
Speaker 3: works so that it works for you and not someone else.

1709
01:24:15,200 --> 01:24:18,040
Speaker 3: Your printer can always take someone else's inc your car

1710
01:24:18,080 --> 01:24:21,760
Speaker 3: can always have its surveillance technology disabled, and so on.

1711
01:24:22,160 --> 01:24:24,240
Speaker 3: And what that does is it means that with tech

1712
01:24:24,800 --> 01:24:29,280
Speaker 3: you have this separate competitive capacity, which is the ability

1713
01:24:29,320 --> 01:24:34,439
Speaker 3: to compete by modifying existing technology. Right Like Lexmark used

1714
01:24:34,479 --> 01:24:38,240
Speaker 3: to be IBM's printer division, right, and they made laser printers.

1715
01:24:38,600 --> 01:24:43,320
Speaker 3: And there was a company out of not Malaysia, Taiwan

1716
01:24:43,600 --> 01:24:47,360
Speaker 3: that made refill kits for their toner cartridges, and the

1717
01:24:47,360 --> 01:24:49,840
Speaker 3: toner cartridge had a little crude microchip in it. This

1718
01:24:49,880 --> 01:24:52,000
Speaker 3: is in the early two thousands, is when embedded systems

1719
01:24:52,000 --> 01:24:55,000
Speaker 3: were expensive and very primitive. It had a sixty four

1720
01:24:55,040 --> 01:24:57,519
Speaker 3: byte program and when you used up all the toner

1721
01:24:57,520 --> 01:25:00,559
Speaker 3: and the cartridge, the sixty four by program would toggle

1722
01:25:00,560 --> 01:25:02,640
Speaker 3: a switch that said, I'm now an empty cartridge, and

1723
01:25:02,680 --> 01:25:05,519
Speaker 3: if you put more carbon powder in the cartridge, it

1724
01:25:05,520 --> 01:25:08,000
Speaker 3: wouldn't work because the cartridge told the printer it was empty.

1725
01:25:08,360 --> 01:25:11,160
Speaker 3: So Static reverse engineered this sixty four by program not

1726
01:25:11,320 --> 01:25:15,280
Speaker 3: very challenging. They made another chip and it reset it

1727
01:25:15,320 --> 01:25:19,960
Speaker 3: to one. Right, I am a full cartridge. And when

1728
01:25:20,000 --> 01:25:25,759
Speaker 3: that happened, Lexmark sued them, and they sued them, arguing

1729
01:25:25,960 --> 01:25:29,000
Speaker 3: that they had violated their copyright, that they bypassed an

1730
01:25:29,040 --> 01:25:31,679
Speaker 3: access control for a copyrighted work, which is prohibited under

1731
01:25:31,680 --> 01:25:34,080
Speaker 3: the Digital Mining of Copyright Act. And the judge at

1732
01:25:34,120 --> 01:25:37,160
Speaker 3: the time said, like, where is the copyrighted work. It's

1733
01:25:37,200 --> 01:25:39,800
Speaker 3: not the carbon in the printer cartridge. They said, no,

1734
01:25:39,840 --> 01:25:42,400
Speaker 3: it's the sixty four by program. They said, well, you know,

1735
01:25:42,680 --> 01:25:46,080
Speaker 3: like sixty four by programs software is like copyrightable, but

1736
01:25:46,080 --> 01:25:48,519
Speaker 3: a sixty four by program isn't. It's not even a

1737
01:25:48,560 --> 01:25:51,040
Speaker 3: high coup right, Like, it doesn't rise to the level

1738
01:25:51,080 --> 01:25:53,559
Speaker 3: of complexity that attracts a new copyright. And so they

1739
01:25:53,560 --> 01:25:57,000
Speaker 3: threw the case out punchline. Today, Lexmark is a division

1740
01:25:57,000 --> 01:26:00,679
Speaker 3: of static controls, right, because they went for I'm refilling

1741
01:26:00,680 --> 01:26:05,960
Speaker 3: the cartridges to buying the business. Ah. Right. So today,

1742
01:26:06,080 --> 01:26:07,960
Speaker 3: if you were to try and make that argument about HP,

1743
01:26:08,080 --> 01:26:11,360
Speaker 3: which has this disgusting habit of pushing at fake security

1744
01:26:11,400 --> 01:26:14,639
Speaker 3: updates that break your printer's ability to use their party Inc.

1745
01:26:14,720 --> 01:26:18,160
Speaker 3: It breaks on its own. Sorry that too. But if

1746
01:26:18,200 --> 01:26:19,439
Speaker 3: you were to do this and you were to go

1747
01:26:19,479 --> 01:26:22,160
Speaker 3: back to court and say the program in the chip

1748
01:26:22,360 --> 01:26:24,559
Speaker 3: in the chip in the cartridge that stops you from

1749
01:26:24,640 --> 01:26:27,080
Speaker 3: using third party Inc. Doesn't rise to love a copyright ability.

1750
01:26:27,280 --> 01:26:29,040
Speaker 3: That's like a twenty six cent system on a chip

1751
01:26:29,040 --> 01:26:31,800
Speaker 3: that's running a full Linux stack with like busy box

1752
01:26:31,840 --> 01:26:33,839
Speaker 3: and a network stack. You could probably attach a monitor

1753
01:26:33,880 --> 01:26:36,040
Speaker 3: to it if you want it to write, and like,

1754
01:26:36,080 --> 01:26:40,679
Speaker 3: there's just no argument that that's not copyrightable. Now, with tech,

1755
01:26:40,760 --> 01:26:43,200
Speaker 3: if we could clear some of these rules that have

1756
01:26:43,280 --> 01:26:46,200
Speaker 3: been mobilized by big tech to block new market entry,

1757
01:26:46,520 --> 01:26:49,200
Speaker 3: to block reverse engineering, to block all this other stuff,

1758
01:26:49,439 --> 01:26:51,439
Speaker 3: we could do lots of things to compete, Like the

1759
01:26:51,479 --> 01:26:54,040
Speaker 3: iPhone is a great platform for someone else to make

1760
01:26:54,080 --> 01:26:55,599
Speaker 3: an app store, right.

1761
01:26:55,600 --> 01:26:58,120
Speaker 2: Vidia I was one of the like I was really

1762
01:26:58,160 --> 01:27:00,800
Speaker 2: into the homebrew community and iPhone. Yeah, and you know what,

1763
01:27:00,920 --> 01:27:03,000
Speaker 2: some of it was broken as shit, but you could

1764
01:27:03,000 --> 01:27:06,839
Speaker 2: do so many There were weird little things that connected

1765
01:27:06,920 --> 01:27:10,680
Speaker 2: the systems, probably in ways that were extremely leaky, but

1766
01:27:10,720 --> 01:27:14,600
Speaker 2: they were drowned in the water. Now geohot makes weird

1767
01:27:15,000 --> 01:27:16,760
Speaker 2: autonomous car things that kind of work.

1768
01:27:17,240 --> 01:27:19,560
Speaker 3: It's just yeah. But you know, if you remember in

1769
01:27:19,600 --> 01:27:23,439
Speaker 3: the early two thousands, Apple was dying because Microsoft wouldn't

1770
01:27:23,439 --> 01:27:25,800
Speaker 3: make a functional version of Microsoft Office right. And the

1771
01:27:25,800 --> 01:27:29,080
Speaker 3: way Steve Jobs resolved that was not by begging Bill

1772
01:27:29,080 --> 01:27:32,639
Speaker 3: Gates to fix Office. He just had technologists at Apple

1773
01:27:32,720 --> 01:27:35,400
Speaker 3: reverse engineer Microsoft Office and make iWork pages, numbers, and

1774
01:27:35,479 --> 01:27:39,320
Speaker 3: keynote that perfectly run word, Excel and PowerPoint. Now. It

1775
01:27:39,360 --> 01:27:42,799
Speaker 3: was janki at first, because Microsoft kept cycling the file formats, yes,

1776
01:27:42,920 --> 01:27:45,720
Speaker 3: in order to break compatibility. But that hurt Microsoft more

1777
01:27:45,800 --> 01:27:48,320
Speaker 3: than it hurt Apple because Apple had their own internal

1778
01:27:48,360 --> 01:27:50,439
Speaker 3: file formats. Microsoft just had these file formats, and they

1779
01:27:50,520 --> 01:27:53,000
Speaker 3: kept making them more obfuscated and complex, and then they

1780
01:27:53,080 --> 01:27:55,360
Speaker 3: had to support them all. So eventually Microsoft sued for

1781
01:27:55,400 --> 01:27:58,040
Speaker 3: peace and they standardized those file formats. That's where we

1782
01:27:58,080 --> 01:28:01,200
Speaker 3: get doc x PPT x xls X. Those are the

1783
01:28:01,280 --> 01:28:03,720
Speaker 3: XML versions. And the reason you can copy and past

1784
01:28:03,760 --> 01:28:06,479
Speaker 3: style text into a browser and then into libre office,

1785
01:28:06,520 --> 01:28:08,560
Speaker 3: and then into iWork and then back into office is

1786
01:28:08,600 --> 01:28:12,960
Speaker 3: because they're all using this standard. If Apple could not

1787
01:28:13,200 --> 01:28:16,400
Speaker 3: use the courts to shut down something like Sidia, uh

1788
01:28:16,439 --> 01:28:19,000
Speaker 3: and if they were required to just have hand to

1789
01:28:19,040 --> 01:28:24,559
Speaker 3: hand guerrilla warfare with Jay Freeman and his engineers, they

1790
01:28:24,560 --> 01:28:29,160
Speaker 3: would eventually sueer piece because they they are fighting an

1791
01:28:29,200 --> 01:28:33,280
Speaker 3: asymmetric battle where they have to make no mistakes in

1792
01:28:33,320 --> 01:28:36,800
Speaker 3: the iPhone, and Jay and Johatt just have to find

1793
01:28:36,800 --> 01:28:39,400
Speaker 3: one mistake they've made, and every time they do that,

1794
01:28:39,400 --> 01:28:40,840
Speaker 3: they have to go back to the drum. Alright.

1795
01:28:40,960 --> 01:28:43,720
Speaker 2: Talking to Margaret Thatcha, you need we only need to

1796
01:28:43,760 --> 01:28:44,439
Speaker 2: be lucky ones.

1797
01:28:44,680 --> 01:28:47,360
Speaker 1: Yeah, And and you should be pointed out that I

1798
01:28:47,360 --> 01:28:50,519
Speaker 1: think that Apple's in house design were watching what they

1799
01:28:50,520 --> 01:28:53,120
Speaker 1: were doing in the in those jail broken sists, and

1800
01:28:53,200 --> 01:28:55,559
Speaker 1: they were, and they a lot of the things that

1801
01:28:55,680 --> 01:28:59,240
Speaker 1: were really popular. They poured it into the into iOS

1802
01:28:59,240 --> 01:29:03,320
Speaker 1: and future design. You know, obviously not the interoperability or

1803
01:29:03,360 --> 01:29:05,840
Speaker 1: the things that would be more radical, but just like

1804
01:29:05,880 --> 01:29:09,000
Speaker 1: design flourishes and features, like they were watching that community

1805
01:29:09,040 --> 01:29:09,920
Speaker 1: and taking notes from it.

1806
01:29:09,960 --> 01:29:12,679
Speaker 3: Every good designer starts by paving the desire path.

1807
01:29:12,640 --> 01:29:14,360
Speaker 2: And I mean one of my favorite examples of this

1808
01:29:14,439 --> 01:29:16,080
Speaker 2: where yeah, the courts would I don't know how the

1809
01:29:16,120 --> 01:29:17,759
Speaker 2: courts would have gone in because this is video games,

1810
01:29:17,800 --> 01:29:21,400
Speaker 2: but the originals of the World of Warcraft were from

1811
01:29:22,000 --> 01:29:24,559
Speaker 2: numerous forums, from numerous guilds. In EverQuest, there's a big

1812
01:29:24,560 --> 01:29:27,200
Speaker 2: thing with the plane of time, with the shadows lukelan expansion.

1813
01:29:27,400 --> 01:29:29,720
Speaker 2: Anyone who knows this story, by the way, email me.

1814
01:29:29,880 --> 01:29:32,200
Speaker 2: I love you, easy Better off line dot com. But

1815
01:29:32,320 --> 01:29:34,880
Speaker 2: long story short, there was a massive bug with the

1816
01:29:34,880 --> 01:29:37,120
Speaker 2: final rate, and a bunch of people, for all being

1817
01:29:37,120 --> 01:29:39,040
Speaker 2: one of them said I'm fucking done with this game.

1818
01:29:39,080 --> 01:29:40,920
Speaker 2: This company doesn't give a shit. They can't even finish

1819
01:29:41,000 --> 01:29:45,160
Speaker 2: their goddamn work. It's disgusting. And Blizzard, who are now

1820
01:29:45,280 --> 01:29:47,800
Speaker 2: kind of horrible thanks to Activision, Kotic and all them,

1821
01:29:48,280 --> 01:29:51,360
Speaker 2: said huh, well, if we just got all these high

1822
01:29:51,439 --> 01:29:55,679
Speaker 2: level players and ask them, how would you like EverQuest

1823
01:29:55,680 --> 01:29:57,800
Speaker 2: to be better? What would a better MMO look like?

1824
01:29:57,920 --> 01:30:01,680
Speaker 2: World of Warcraft was an amazing m I genuinely love

1825
01:30:01,760 --> 01:30:03,680
Speaker 2: Wow at the beginning, and to this day, I'm sure

1826
01:30:03,720 --> 01:30:06,400
Speaker 2: ever picked up. And it does that because this crazy

1827
01:30:06,439 --> 01:30:08,960
Speaker 2: idea of we could really compete with pretty much the

1828
01:30:08,960 --> 01:30:13,760
Speaker 2: only successful Western MMO with some exceptions, by taking the

1829
01:30:13,760 --> 01:30:16,480
Speaker 2: things they like and doing better at them, by iterating

1830
01:30:16,520 --> 01:30:19,200
Speaker 2: on their work and doing great things. If we could

1831
01:30:19,200 --> 01:30:22,200
Speaker 2: do that in tech. Even the small examples we have

1832
01:30:22,240 --> 01:30:25,240
Speaker 2: in tech of that working are so good. I mean

1833
01:30:26,280 --> 01:30:29,479
Speaker 2: Anchor being my favorite one, Like they have gallium nitrie.

1834
01:30:29,479 --> 01:30:31,679
Speaker 2: They've managed to make shit really powerful and really small,

1835
01:30:32,040 --> 01:30:34,800
Speaker 2: and yeah, it's made every other battery manufacturer have to

1836
01:30:34,800 --> 01:30:37,320
Speaker 2: fucking compete. I'm sure they didn't do it first, but

1837
01:30:37,400 --> 01:30:40,040
Speaker 2: Anchor has made a successful business out of seeing other

1838
01:30:40,080 --> 01:30:43,600
Speaker 2: people shit and going, what if this was good?

1839
01:30:44,360 --> 01:30:48,280
Speaker 3: Let me make one more point about why user adaptability

1840
01:30:48,360 --> 01:30:51,400
Speaker 3: is good. It's not merely because it lets firms discover

1841
01:30:51,520 --> 01:30:55,519
Speaker 3: a new way so pleasing us, or because it lets

1842
01:30:55,600 --> 01:30:59,920
Speaker 3: us make our lives easier. It's because when our technology

1843
01:31:00,000 --> 01:31:02,520
Speaker 3: doesn't work for us, it is often because the circumstances

1844
01:31:02,520 --> 01:31:04,680
Speaker 3: that we're in have changed for the worse. Okay, right,

1845
01:31:04,760 --> 01:31:06,880
Speaker 3: your printer, you need to get one more page out

1846
01:31:06,880 --> 01:31:08,719
Speaker 3: of your printer, and it's really desperate and it won't

1847
01:31:08,720 --> 01:31:11,160
Speaker 3: print because it doesn't have any magenta in it, even

1848
01:31:11,200 --> 01:31:12,720
Speaker 3: though you're printing a black and white document, and the

1849
01:31:12,760 --> 01:31:14,559
Speaker 3: black and white document you're printing is the thing that

1850
01:31:14,600 --> 01:31:16,840
Speaker 3: you need to bring to the bail bondsmen because your

1851
01:31:16,880 --> 01:31:20,519
Speaker 3: kid's just been arrested. Right The people who are finness

1852
01:31:20,560 --> 01:31:24,160
Speaker 3: this again, the people who make the technology can never

1853
01:31:24,240 --> 01:31:26,600
Speaker 3: anticipate all the ways that the people who use the

1854
01:31:26,600 --> 01:31:28,720
Speaker 3: technology are going to need to use it, not just

1855
01:31:28,800 --> 01:31:31,519
Speaker 3: in the immediate future, but in the decades that will

1856
01:31:31,600 --> 01:31:34,960
Speaker 3: come afterwards, because this technology lives in our stack forever

1857
01:31:35,040 --> 01:31:37,599
Speaker 3: and ever. If you want to read an amazing document

1858
01:31:37,640 --> 01:31:40,720
Speaker 3: about how technology ac creates, the British Librari's postmortem on

1859
01:31:40,840 --> 01:31:43,240
Speaker 3: their ransomware attack, where they talk about how they were

1860
01:31:43,280 --> 01:31:45,599
Speaker 3: early adopters and then they because they could never shut

1861
01:31:45,680 --> 01:31:47,880
Speaker 3: down the system, they just put more and more layers

1862
01:31:47,920 --> 01:31:49,559
Speaker 3: on top of it. Each layer was a seam that

1863
01:31:49,560 --> 01:31:51,439
Speaker 3: could be exploited by ransomware creeps. It's one of the

1864
01:31:51,479 --> 01:31:55,240
Speaker 3: most important tech documents I've ever read. So you know

1865
01:31:55,280 --> 01:31:58,720
Speaker 3: when things are broken, when people in the future are

1866
01:31:58,720 --> 01:32:01,479
Speaker 3: trying to maintain or adapt the things that you've made.

1867
01:32:02,160 --> 01:32:04,720
Speaker 3: When the climate emergency hits and the power goes out,

1868
01:32:04,800 --> 01:32:07,760
Speaker 3: or the internet is not available or not available continuously,

1869
01:32:07,840 --> 01:32:09,720
Speaker 3: or a website that's supposed to be checked every time

1870
01:32:09,720 --> 01:32:12,439
Speaker 3: you launch for a license key goes down because there's

1871
01:32:12,520 --> 01:32:15,639
Speaker 3: been a big cyber attack or because CrowdStrike has gone down.

1872
01:32:16,240 --> 01:32:18,920
Speaker 3: That is the moment where being able to change how

1873
01:32:18,960 --> 01:32:22,479
Speaker 3: your technology works is going to be the difference between

1874
01:32:23,040 --> 01:32:25,320
Speaker 3: success and failure, a good life and a bad life,

1875
01:32:25,320 --> 01:32:29,600
Speaker 3: sometimes life and death by it. And the hubris of

1876
01:32:29,640 --> 01:32:32,400
Speaker 3: thinking that you can anticipate all the ways that people

1877
01:32:32,400 --> 01:32:34,280
Speaker 3: are going to use it, all the bodies they'll be in,

1878
01:32:34,560 --> 01:32:40,160
Speaker 3: all the circumstances they'll live through, is so monumentally arrogant

1879
01:32:40,240 --> 01:32:45,120
Speaker 3: and reckless, and ultimately, although you may not always make

1880
01:32:45,120 --> 01:32:47,880
Speaker 3: the best decision about how the technology around you should work,

1881
01:32:48,479 --> 01:32:50,800
Speaker 3: that decision should still always vest with you.

1882
01:32:51,760 --> 01:32:54,360
Speaker 2: So as we wrap up here, I want to finish

1883
01:32:54,400 --> 01:32:59,439
Speaker 2: around the generative a Brian, do you see any value?

1884
01:32:59,680 --> 01:33:02,160
Speaker 2: This is such an aweshole question to end on. I

1885
01:33:02,240 --> 01:33:04,960
Speaker 2: realized we've got like tim but like, do you see

1886
01:33:04,960 --> 01:33:06,479
Speaker 2: any value in this? I think this is a good

1887
01:33:06,479 --> 01:33:07,480
Speaker 2: thing to wrap.

1888
01:33:08,760 --> 01:33:10,479
Speaker 1: I think like a lot of the technologies that have

1889
01:33:10,560 --> 01:33:13,679
Speaker 1: kind of surfaced or have become fixations of Silicon Valley

1890
01:33:13,680 --> 01:33:16,559
Speaker 1: over the last five years, as it's sort of cycled

1891
01:33:16,760 --> 01:33:21,280
Speaker 1: through the latest next big thing, as it's investors are

1892
01:33:21,320 --> 01:33:26,320
Speaker 1: desperate to find said big thing because it hasn't really had.

1893
01:33:26,200 --> 01:33:26,960
Speaker 3: One in a while.

1894
01:33:28,040 --> 01:33:31,439
Speaker 1: I think, you know, Jennert of AI has found a

1895
01:33:31,439 --> 01:33:33,080
Speaker 1: few more use cases.

1896
01:33:32,960 --> 01:33:35,720
Speaker 3: Than whatever the metaverse or web.

1897
01:33:35,479 --> 01:33:40,719
Speaker 1: Three or crypto, So therefore it's been a little bit stickier.

1898
01:33:41,280 --> 01:33:45,160
Speaker 1: And you know, as a technology it's itself, is there

1899
01:33:45,240 --> 01:33:46,439
Speaker 1: is there something interesting there?

1900
01:33:47,400 --> 01:33:50,600
Speaker 3: You know? Yeah, like I think that there's there.

1901
01:33:50,360 --> 01:33:56,120
Speaker 1: We should be having researchers and developers looking into into

1902
01:33:56,200 --> 01:33:58,640
Speaker 1: large language models and how to make them better and

1903
01:33:58,680 --> 01:34:00,559
Speaker 1: how to make them more interesting. Scene they can and

1904
01:34:00,640 --> 01:34:04,360
Speaker 1: can't do by kicking the tires? Do we need every

1905
01:34:04,720 --> 01:34:09,200
Speaker 1: major tech company running massive data farms doing basically the

1906
01:34:09,240 --> 01:34:13,000
Speaker 1: same thing as the cost of energy and compute skyrockets

1907
01:34:13,040 --> 01:34:15,280
Speaker 1: and a game that and a company that made video

1908
01:34:15,320 --> 01:34:17,920
Speaker 1: game chips as of two or three years ago is

1909
01:34:17,960 --> 01:34:22,400
Speaker 1: now suddenly more valuable than Apple and the entire GDP

1910
01:34:22,680 --> 01:34:25,880
Speaker 1: of or like the London Stock Exchange, I think I saw.

1911
01:34:26,080 --> 01:34:26,840
Speaker 3: Something like that.

1912
01:34:26,920 --> 01:34:30,120
Speaker 1: Yeah, then you have then you have an issue. And

1913
01:34:30,200 --> 01:34:33,160
Speaker 1: this is the problem with our current mode of technological development.

1914
01:34:33,240 --> 01:34:36,920
Speaker 3: It's not just is technology? Is this technology and question good?

1915
01:34:37,600 --> 01:34:41,280
Speaker 1: Is Is this in any way a sensible way to

1916
01:34:41,360 --> 01:34:43,040
Speaker 1: go about seeing how it's.

1917
01:34:42,920 --> 01:34:45,160
Speaker 3: Useful or who it could be useful for, or what

1918
01:34:45,320 --> 01:34:48,640
Speaker 3: use cases it might have? And I think absolutely not.

1919
01:34:48,800 --> 01:34:50,520
Speaker 3: I think it's so hard.

1920
01:34:50,560 --> 01:34:55,000
Speaker 1: To distinguish that question right now because it's gone from

1921
01:34:55,479 --> 01:34:58,320
Speaker 1: zero to one hundred and twenty and it's spinning out

1922
01:34:58,320 --> 01:35:02,160
Speaker 1: in all directions, and it's so many bad decisions have

1923
01:35:02,200 --> 01:35:06,800
Speaker 1: been made in its rollout. It's it's been deeply non

1924
01:35:06,840 --> 01:35:10,080
Speaker 1: consensual to a lot of the parties whose work has

1925
01:35:10,120 --> 01:35:12,559
Speaker 1: been harvested into this thing. So you have a bunch

1926
01:35:12,600 --> 01:35:14,920
Speaker 1: of people who are furious at the way that the

1927
01:35:14,920 --> 01:35:16,599
Speaker 1: models were trained in the first place.

1928
01:35:17,000 --> 01:35:21,080
Speaker 3: It's being set against creative markets where people.

1929
01:35:20,800 --> 01:35:23,880
Speaker 1: Are now worried about their jobs, so you have them angry.

1930
01:35:23,920 --> 01:35:26,200
Speaker 1: On the other side, you have ordinary people who are

1931
01:35:26,200 --> 01:35:28,519
Speaker 1: just worried about is this going to automate my job?

1932
01:35:28,520 --> 01:35:30,760
Speaker 1: How's it going to affect me? And so you have

1933
01:35:30,800 --> 01:35:36,120
Speaker 1: this immense climate of not just fear but also of anger,

1934
01:35:36,560 --> 01:35:38,960
Speaker 1: and it's really hard to pull out. You know, like, well,

1935
01:35:39,080 --> 01:35:42,880
Speaker 1: is generative AI like a good technology in terms of

1936
01:35:42,960 --> 01:35:45,800
Speaker 1: the use cases to which it is being put right now,

1937
01:35:45,840 --> 01:35:47,600
Speaker 1: I would say absolutely not.

1938
01:35:48,280 --> 01:35:48,479
Speaker 3: Yeah.

1939
01:35:48,560 --> 01:35:52,400
Speaker 2: It feels almost like the most egregious example of everything

1940
01:35:52,400 --> 01:35:55,520
Speaker 2: we've been talking about. When these companies have no natural predators,

1941
01:35:55,640 --> 01:35:58,000
Speaker 2: when they have no one to go shit, you can't

1942
01:35:58,040 --> 01:36:02,720
Speaker 2: do that. Customers will be mad because otherwise they'd say, so,

1943
01:36:02,800 --> 01:36:05,600
Speaker 2: what is chet GPT exact? Why are we doing this

1944
01:36:05,760 --> 01:36:07,280
Speaker 2: that just not more most stuff?

1945
01:36:07,560 --> 01:36:09,439
Speaker 1: Well, again, I would say I would push back on

1946
01:36:09,479 --> 01:36:12,640
Speaker 1: that a little bit because it did rack up organically,

1947
01:36:12,960 --> 01:36:14,960
Speaker 1: you know, one hundred million users or whatever. So there

1948
01:36:14,960 --> 01:36:16,760
Speaker 1: were some people who are like, this is a fun

1949
01:36:16,800 --> 01:36:19,840
Speaker 1: toy to play with, okay, but actually okay, well, but

1950
01:36:19,960 --> 01:36:22,639
Speaker 1: but then we transition to like, well, that's not really

1951
01:36:22,680 --> 01:36:25,160
Speaker 1: gonna make us any money, so how do we get

1952
01:36:25,200 --> 01:36:26,720
Speaker 1: it to make any money? And then all of a

1953
01:36:26,720 --> 01:36:28,919
Speaker 1: sudden it's like, oh, maybe we can just like automate

1954
01:36:29,000 --> 01:36:31,880
Speaker 1: some stuff. And it becomes an enterprise software that it's

1955
01:36:31,920 --> 01:36:35,640
Speaker 1: selling that it's being sold you know, to to consultancies,

1956
01:36:35,760 --> 01:36:39,719
Speaker 1: to uh fintech firms, to anyone who any any anyone,

1957
01:36:39,880 --> 01:36:42,360
Speaker 1: anyone who will who will listen to a to an

1958
01:36:42,360 --> 01:36:45,120
Speaker 1: open AI salesman's pitch, and that's how we wind up

1959
01:36:45,120 --> 01:36:48,280
Speaker 1: where we are today. Where you have hundreds of thousands

1960
01:36:48,320 --> 01:36:52,480
Speaker 1: of these enterprise seats sold to a dubiously useful technology.

1961
01:36:52,960 --> 01:36:53,200
Speaker 3: Uh.

1962
01:36:53,240 --> 01:36:57,240
Speaker 1: People are are rightfully concerned that it's that it's you know,

1963
01:36:57,280 --> 01:37:01,599
Speaker 1: that it's threatening their uh, their their, their livelihoods. Even

1964
01:37:01,640 --> 01:37:02,840
Speaker 1: though it doesn't do a good job.

1965
01:37:02,880 --> 01:37:03,360
Speaker 3: It sucks.

1966
01:37:03,360 --> 01:37:05,200
Speaker 1: This is a point that Coreya makes a lot, is

1967
01:37:05,200 --> 01:37:09,400
Speaker 1: that it doesn't actually often create a superior product. It

1968
01:37:09,439 --> 01:37:12,680
Speaker 1: almost never does. Yeah, it's just it's good enough for

1969
01:37:12,720 --> 01:37:14,320
Speaker 1: a manager to say, all right, we'll take it.

1970
01:37:14,320 --> 01:37:15,599
Speaker 3: It's cheaper. But I wanted to.

1971
01:37:15,560 --> 01:37:17,360
Speaker 2: Push back on one thing. And I don't necessarily know

1972
01:37:17,400 --> 01:37:20,360
Speaker 2: if you've disagree, But yeah, I don't know if chat

1973
01:37:20,439 --> 01:37:23,360
Speaker 2: GPT grew organically. The reason I say that is this

1974
01:37:24,000 --> 01:37:26,000
Speaker 2: when you have no hypergrowth markets, when you have no

1975
01:37:26,120 --> 01:37:29,160
Speaker 2: big new thing, and you have what I would argue

1976
01:37:29,200 --> 01:37:34,200
Speaker 2: is members of the media willfully engaging in a marketing campaign. Yeah,

1977
01:37:34,280 --> 01:37:36,720
Speaker 2: run by and I would. By the way, like all

1978
01:37:36,720 --> 01:37:39,360
Speaker 2: evil systems, I don't know how much of this was conscious.

1979
01:37:39,800 --> 01:37:42,280
Speaker 2: I don't think people sat around and now we shall

1980
01:37:42,280 --> 01:37:44,240
Speaker 2: all agree to write about chat GEPT.

1981
01:37:44,520 --> 01:37:44,600
Speaker 3: No.

1982
01:37:44,760 --> 01:37:48,479
Speaker 2: I think that just a desperation in the media for

1983
01:37:48,520 --> 01:37:51,120
Speaker 2: something new to write about, connected with the desperation in

1984
01:37:51,200 --> 01:37:53,719
Speaker 2: venture capital, which connected with the desperation in the market.

1985
01:37:53,960 --> 01:37:54,479
Speaker 3: Boom yeah.

1986
01:37:54,520 --> 01:37:57,519
Speaker 1: And then into the vacuum comes this new apparently viable

1987
01:37:57,600 --> 01:38:01,000
Speaker 1: product about which any number of narratives can.

1988
01:38:00,960 --> 01:38:04,280
Speaker 2: Unfold exactly, and you can probabilis telling me to leave

1989
01:38:04,320 --> 01:38:07,120
Speaker 2: my wife. Wow, you know, like Kevin Rose, the goat

1990
01:38:07,120 --> 01:38:08,400
Speaker 2: of freaking out about the computer.

1991
01:38:08,720 --> 01:38:12,680
Speaker 3: But you really, you really, you know whether or not.

1992
01:38:12,800 --> 01:38:14,880
Speaker 1: The one thing that I would say in its corner

1993
01:38:15,000 --> 01:38:18,479
Speaker 1: that that maybe some of that was is that is

1994
01:38:18,520 --> 01:38:22,559
Speaker 1: that it hasn't claimed that user growth has increased much

1995
01:38:22,600 --> 01:38:25,240
Speaker 1: since then We're like a year later, they're still saying.

1996
01:38:25,040 --> 01:38:26,880
Speaker 3: Like, well, we still got one hundred million years.

1997
01:38:27,439 --> 01:38:29,759
Speaker 1: So you'd think that if they were inflating that figure,

1998
01:38:29,760 --> 01:38:32,120
Speaker 1: they would at least they would find some you know,

1999
01:38:32,240 --> 01:38:34,880
Speaker 1: metric to put together active paine. Now we've got two

2000
01:38:34,960 --> 01:38:38,639
Speaker 1: hundred yeah, exactly, some muskie and you know, minutes viewed

2001
01:38:38,760 --> 01:38:40,799
Speaker 1: per syllable generally.

2002
01:38:41,400 --> 01:38:44,960
Speaker 3: Yeah. So I think that, you know, maybe a useful

2003
01:38:44,960 --> 01:38:48,760
Speaker 3: analogy here, although not a perfect one, is gamification. Right. So,

2004
01:38:49,160 --> 01:38:51,639
Speaker 3: if you've read Jane mcgonagle's old work on this stuff,

2005
01:38:51,680 --> 01:38:53,800
Speaker 3: you know, Jane was doing this incredible stuff where she

2006
01:38:54,240 --> 01:38:56,719
Speaker 3: On the one hand, she she'd suffered a neurological industry

2007
01:38:57,000 --> 01:39:00,080
Speaker 3: injury rather and she needed to do a lot of

2008
01:39:00,400 --> 01:39:05,000
Speaker 3: very repetitive and difficult and generally low compliance rehabilitation for it.

2009
01:39:05,040 --> 01:39:07,200
Speaker 3: People don't recover from those injuries because it's so hard

2010
01:39:07,240 --> 01:39:09,200
Speaker 3: to do. And she made a game out of it, right,

2011
01:39:09,240 --> 01:39:11,439
Speaker 3: and it really worked, and she started she's a game developer.

2012
01:39:11,479 --> 01:39:13,479
Speaker 3: She started figuring out how to bring these out. So

2013
01:39:13,560 --> 01:39:17,200
Speaker 3: there are some marketing crossings. I don't remember where she was,

2014
01:39:17,240 --> 01:39:19,360
Speaker 3: but she you know, she she worked on I Love Bees,

2015
01:39:19,400 --> 01:39:22,800
Speaker 3: which was the AI movie, and she worked on a

2016
01:39:22,800 --> 01:39:26,160
Speaker 3: bunch of other like really Texas Hold Them, Texas, Tombstone

2017
01:39:26,160 --> 01:39:28,200
Speaker 3: Hold Them or whatever it was called Tombstone Hold Them.

2018
01:39:28,320 --> 01:39:31,720
Speaker 3: People got married playing these games like they were really fun, right,

2019
01:39:32,160 --> 01:39:34,280
Speaker 3: And then a bunch of people said, oh, well, we

2020
01:39:34,280 --> 01:39:38,439
Speaker 3: could use these to get Amazon warehouse workers to uh

2021
01:39:39,200 --> 01:39:41,920
Speaker 3: gamify how long they can go without urinating so that

2022
01:39:41,960 --> 01:39:45,080
Speaker 3: they can meet quota. Right. And we look at that

2023
01:39:45,120 --> 01:39:47,400
Speaker 3: and we go, oh, this is horrific, But playing games

2024
01:39:47,479 --> 01:39:51,120
Speaker 3: is not horrific, right, right, And I've been following people

2025
01:39:51,160 --> 01:39:53,439
Speaker 3: doing weird, playful things with stuff we would now call

2026
01:39:53,479 --> 01:39:55,479
Speaker 3: generative AI. For a really long time. This guy called

2027
01:39:55,520 --> 01:39:58,679
Speaker 3: Shardcore is like a digital artist who's making weird videos

2028
01:39:58,680 --> 01:40:02,400
Speaker 3: and stills forever, really cool fun stuff. You know, literally

2029
01:40:02,400 --> 01:40:05,799
Speaker 3: a decade of this, which lends it self generative. Yeah,

2030
01:40:05,840 --> 01:40:07,720
Speaker 3: and you know, today I look around and I see

2031
01:40:07,760 --> 01:40:10,080
Speaker 3: people who like play a D and D game, and

2032
01:40:10,120 --> 01:40:13,960
Speaker 3: then at the end, the LM has generated a transcript

2033
01:40:14,000 --> 01:40:18,120
Speaker 3: of the game. It generates a precie of the transcript,

2034
01:40:18,200 --> 01:40:21,080
Speaker 3: It illustrates it with fun epic moments from it. It

2035
01:40:21,080 --> 01:40:23,920
Speaker 3: doesn't matter if the ORC has six fingers, right, And

2036
01:40:23,960 --> 01:40:26,040
Speaker 3: everybody looks at that and they go, hahaha, that's great,

2037
01:40:26,360 --> 01:40:31,920
Speaker 3: and then they fire the customer service reps for your insulin.

2038
01:40:32,320 --> 01:40:34,720
Speaker 2: For the company that runs the thing that generates the

2039
01:40:34,800 --> 01:40:35,400
Speaker 2: ORC pictures.

2040
01:40:35,800 --> 01:40:38,160
Speaker 3: You know, No that for the people who supply you

2041
01:40:38,360 --> 01:40:42,400
Speaker 3: with dialysis you sell, or who determine whether or not

2042
01:40:42,439 --> 01:40:45,120
Speaker 3: you can legally get insulin on your insurance. And you

2043
01:40:45,160 --> 01:40:47,960
Speaker 3: find yourself arguing with a chatbot about whether you're going

2044
01:40:48,040 --> 01:40:50,679
Speaker 3: to get dialysis? Who live? And then you die? Right,

2045
01:40:50,760 --> 01:40:55,040
Speaker 3: And that's not a problem with the existence of tools

2046
01:40:55,040 --> 01:40:58,720
Speaker 3: that do weird shit, right, that is a problem. And

2047
01:40:58,800 --> 01:41:03,160
Speaker 3: now the thing is that total addressable market of epic

2048
01:41:03,439 --> 01:41:08,479
Speaker 3: illustrations from last night's D and D game is very small. Yes,

2049
01:41:09,320 --> 01:41:12,800
Speaker 3: and it may be that some of the productive residue

2050
01:41:12,800 --> 01:41:16,400
Speaker 3: of this bubble will be standalone models that run on

2051
01:41:16,560 --> 01:41:20,680
Speaker 3: commodity hard Yeah. And in the same way that, like

2052
01:41:20,720 --> 01:41:23,479
Speaker 3: the productive residue of the world Coom bubble was a

2053
01:41:23,520 --> 01:41:25,040
Speaker 3: lot of dark fiber in the ground that's being lit

2054
01:41:25,120 --> 01:41:27,640
Speaker 3: up now. The productive residue the dot com bubble was

2055
01:41:27,760 --> 01:41:30,559
Speaker 3: a couple hundred million humanities undergrads who are coerced into

2056
01:41:30,640 --> 01:41:33,720
Speaker 3: dropping out learning Python, Pearl and HTML and went on

2057
01:41:33,760 --> 01:41:35,639
Speaker 3: to create a bunch of really playful things that turned

2058
01:41:35,640 --> 01:41:37,960
Speaker 3: into Web two point zero. That might be a productive resue,

2059
01:41:37,960 --> 01:41:39,720
Speaker 3: doesn't make the bubble good. Bubbles are always bad. They

2060
01:41:39,800 --> 01:41:43,200
Speaker 3: steal from retail investors mom pops and leave them eating

2061
01:41:43,200 --> 01:41:45,679
Speaker 3: dog food into their retirement or sleeping a cardboard box.

2062
01:41:45,680 --> 01:41:48,719
Speaker 3: They're very bad, right. But en Ron was a bubble

2063
01:41:48,720 --> 01:41:52,439
Speaker 3: that left nothing behind, right, NFTs left nothing behind, But

2064
01:41:52,560 --> 01:41:55,479
Speaker 3: like shitty JPEGs and worse Austrian ex customs, the tank

2065
01:41:55,640 --> 01:41:57,920
Speaker 3: was bad. Yeah, but this case, in this case, maybe

2066
01:41:57,920 --> 01:41:58,880
Speaker 3: something good comes of it.

2067
01:41:58,960 --> 01:41:59,080
Speaker 1: Right.

2068
01:41:59,120 --> 01:42:01,439
Speaker 3: It doesn't make the thing good, but maybe something good

2069
01:42:01,479 --> 01:42:04,280
Speaker 3: comes up it maybe there's a productive residue, maybe not.

2070
01:42:04,520 --> 01:42:06,000
Speaker 3: I think it's so yeah.

2071
01:42:06,000 --> 01:42:08,559
Speaker 1: I mean you've probably been watching the Olympics or at

2072
01:42:08,600 --> 01:42:10,320
Speaker 1: least read about like the I think one of the

2073
01:42:10,360 --> 01:42:13,280
Speaker 1: really telling you. One of the telling things here is

2074
01:42:13,320 --> 01:42:15,799
Speaker 1: you can look at how these companies are like trying

2075
01:42:15,840 --> 01:42:21,200
Speaker 1: to advertise generative AI service. So when the first like Google,

2076
01:42:21,520 --> 01:42:23,760
Speaker 1: you know, Gemini or I forget what it was called it,

2077
01:42:23,800 --> 01:42:25,320
Speaker 1: then maybe it was already overview, but it was like,

2078
01:42:25,600 --> 01:42:27,559
Speaker 1: you know, embrace this techno and then you can you

2079
01:42:27,600 --> 01:42:30,200
Speaker 1: can use it to scan all your photos and I'll

2080
01:42:30,200 --> 01:42:33,640
Speaker 1: tell you our new AI will tell you what your license.

2081
01:42:33,280 --> 01:42:36,240
Speaker 3: Plate number is. Is this a problem anybody has? You

2082
01:42:36,240 --> 01:42:37,479
Speaker 3: can't just go outside and.

2083
01:42:37,439 --> 01:42:40,760
Speaker 2: Look at the So that one is the useful one.

2084
01:42:40,800 --> 01:42:42,559
Speaker 2: But also I don't know if it's generally if AI,

2085
01:42:42,880 --> 01:42:46,200
Speaker 2: because it's just that's not they've now started wrapping these

2086
01:42:46,240 --> 01:42:48,040
Speaker 2: things in to try and sell the dog shit.

2087
01:42:48,000 --> 01:42:48,680
Speaker 3: Or look at this one.

2088
01:42:48,880 --> 01:42:50,879
Speaker 1: Did you see the did you see the ad for

2089
01:42:50,880 --> 01:42:53,639
Speaker 1: for Meta's AI where it's like they're like walking through

2090
01:42:53,840 --> 01:42:58,880
Speaker 1: a little Italy and going and and she's like she's like, Grandpa,

2091
01:42:59,040 --> 01:43:01,599
Speaker 1: weren't you here when it was you know the beginning

2092
01:43:01,640 --> 01:43:05,120
Speaker 1: of little Italy and she's like, meta, tell me what

2093
01:43:05,360 --> 01:43:07,479
Speaker 1: you know, tell me what little Italy looks like. Now

2094
01:43:07,479 --> 01:43:09,519
Speaker 1: we can see it, and it like produces like a

2095
01:43:09,560 --> 01:43:13,160
Speaker 1: slop picture of like a pretend little little when it's

2096
01:43:13,200 --> 01:43:15,880
Speaker 1: just like there are photos of little Italy.

2097
01:43:16,040 --> 01:43:18,000
Speaker 3: Could you could like, yeah, you could? That are in

2098
01:43:18,080 --> 01:43:20,360
Speaker 3: a public aren't they also look up woods.

2099
01:43:20,360 --> 01:43:23,000
Speaker 1: Or the Google one where they were like, oh you

2100
01:43:23,040 --> 01:43:25,160
Speaker 1: can have your Does your daughter want to write a

2101
01:43:25,240 --> 01:43:26,960
Speaker 1: letter to an Olympic athlete?

2102
01:43:26,960 --> 01:43:28,120
Speaker 3: Did you see this one? Yes?

2103
01:43:28,240 --> 01:43:33,599
Speaker 1: And it was like, have Google Gemini generate and use

2104
01:43:33,720 --> 01:43:37,600
Speaker 1: generative AI to write the letter. And it's like, obviously

2105
01:43:37,640 --> 01:43:41,200
Speaker 1: this has been roasted because it's the whole point of

2106
01:43:41,240 --> 01:43:43,880
Speaker 1: an activity like that is you get to you, you

2107
01:43:43,920 --> 01:43:46,880
Speaker 1: introduce your child to this, you know, to this this

2108
01:43:47,080 --> 01:43:50,880
Speaker 1: art of writing something down and engaging with this dream

2109
01:43:51,120 --> 01:43:54,040
Speaker 1: of of you know, and you actually participating in an

2110
01:43:54,080 --> 01:43:56,520
Speaker 1: activity not just like a fuck it hit a button.

2111
01:43:56,280 --> 01:43:57,640
Speaker 3: And you can imagine what it would be like to

2112
01:43:57,640 --> 01:44:00,800
Speaker 3: be the athlete. After that video rounds, that's twenty million

2113
01:44:00,840 --> 01:44:04,600
Speaker 3: AI slot letter. Where do I begin? So I have

2114
01:44:04,640 --> 01:44:08,960
Speaker 3: a friend who's a professor who tells me that now

2115
01:44:09,200 --> 01:44:10,439
Speaker 3: it used to be that if someone asked you to

2116
01:44:10,439 --> 01:44:13,360
Speaker 3: write a letter of recommendation for a grand student, you'd

2117
01:44:13,400 --> 01:44:16,320
Speaker 3: be very selective because you wouldn't want to just say

2118
01:44:16,400 --> 01:44:18,240
Speaker 3: yes to everybody because it's a lot of work. And

2119
01:44:18,240 --> 01:44:20,160
Speaker 3: then the people who got those letters really valued them

2120
01:44:20,200 --> 01:44:22,320
Speaker 3: because they knew that you were very selective. But now

2121
01:44:23,040 --> 01:44:26,040
Speaker 3: you take three bullet points about anyone who asks, and

2122
01:44:26,080 --> 01:44:29,120
Speaker 3: it expands it into an AI slot recommendation letter, which

2123
01:44:29,200 --> 01:44:31,600
Speaker 3: means that they're now getting so many recommendation letters that

2124
01:44:31,640 --> 01:44:34,960
Speaker 3: they ask AI to summarize them back into three different

2125
01:44:34,960 --> 01:44:38,120
Speaker 3: bullet points, three extremely losty bullet points, and the entire

2126
01:44:38,160 --> 01:44:39,160
Speaker 3: system is broken down.

2127
01:44:39,280 --> 01:44:43,360
Speaker 2: Hosting the ass hose in the mouth, it's it's my favorite.

2128
01:44:43,360 --> 01:44:45,479
Speaker 2: One of these commercials, by the way, was the co

2129
01:44:45,640 --> 01:44:49,040
Speaker 2: pilot ad for Microsoft on the Super Bowl where one

2130
01:44:49,040 --> 01:44:52,439
Speaker 2: of the things eagle in listeners will hear this and say,

2131
01:44:52,920 --> 01:44:55,120
Speaker 2: I just smashed the window, but I know this bit.

2132
01:44:56,479 --> 01:44:58,519
Speaker 2: It said, there's a bit what you type and say

2133
01:44:58,720 --> 01:45:00,360
Speaker 2: write the code for my three D game.

2134
01:45:00,880 --> 01:45:03,120
Speaker 3: Yeah, it doesn't do it. I did it.

2135
01:45:03,120 --> 01:45:05,040
Speaker 2: It creates a document telling you how to make a

2136
01:45:05,040 --> 01:45:07,680
Speaker 2: three D game. And I think that the point I'm

2137
01:45:07,680 --> 01:45:10,000
Speaker 2: coming towards him glad you'd brought this up both you

2138
01:45:10,160 --> 01:45:14,679
Speaker 2: is GPT really isn't the problem. Transformer based architecture cannot

2139
01:45:14,680 --> 01:45:16,280
Speaker 2: do the things the saying it, But it isn't the problem.

2140
01:45:16,320 --> 01:45:20,559
Speaker 2: The problem is the people building generative AI are actually

2141
01:45:20,600 --> 01:45:24,200
Speaker 2: deeply uncreative because gory up, you're the person you cited

2142
01:45:24,240 --> 01:45:26,760
Speaker 2: who makes the cool art. That's someone who's effectively like,

2143
01:45:26,800 --> 01:45:28,400
Speaker 2: I don't know, this is a very messy way of

2144
01:45:28,439 --> 01:45:30,800
Speaker 2: describing it, but getting a robot with sixty arms and

2145
01:45:30,840 --> 01:45:33,160
Speaker 2: throwing pain to the wall to make something random, sure

2146
01:45:33,200 --> 01:45:36,479
Speaker 2: that is art because you are operating the machine. But

2147
01:45:36,560 --> 01:45:40,040
Speaker 2: generat ive AI, the way it's being pedled is depriving

2148
01:45:40,040 --> 01:45:43,920
Speaker 2: people of actual operational expertise or any kind of domain

2149
01:45:43,960 --> 01:45:45,960
Speaker 2: ex police. It's you're not writing a letter that you

2150
01:45:46,000 --> 01:45:47,719
Speaker 2: care about because you're not writing the letter.

2151
01:45:47,960 --> 01:45:49,320
Speaker 3: Yeah, yeah, I.

2152
01:45:49,280 --> 01:45:52,519
Speaker 1: Mean that's I just I wrote a whole newsletter about

2153
01:45:52,560 --> 01:45:54,719
Speaker 1: this because it was bothering me so much. How many

2154
01:45:54,720 --> 01:46:00,200
Speaker 1: times they've heard it said, mostly by vcs and you

2155
01:46:00,200 --> 01:46:06,120
Speaker 1: know AI advocates saying well, it democratizes creativity. I mean

2156
01:46:06,200 --> 01:46:08,800
Speaker 1: in in what in what what is art? What is

2157
01:46:08,840 --> 01:46:13,240
Speaker 1: more democratic than just producing art? Already? This is not

2158
01:46:13,360 --> 01:46:16,320
Speaker 1: something that needs to be further democratized.

2159
01:46:16,760 --> 01:46:21,599
Speaker 2: Actually democratizes creativity, access to the ants. It's time and

2160
01:46:21,680 --> 01:46:25,080
Speaker 2: space to access the arts and contributing. The best way

2161
01:46:25,120 --> 01:46:28,080
Speaker 2: I got better at writing was writing but also reading,

2162
01:46:28,280 --> 01:46:30,840
Speaker 2: which was my privilege of my parents being able to

2163
01:46:30,880 --> 01:46:34,320
Speaker 2: afford the internet, afford books. These are the actual ways.

2164
01:46:34,320 --> 01:46:36,080
Speaker 2: But none of these people are creative to how the

2165
01:46:36,080 --> 01:46:36,800
Speaker 2: fuck would that this is?

2166
01:46:36,880 --> 01:46:38,720
Speaker 1: And this is my whole point is, if anything, it's

2167
01:46:38,760 --> 01:46:42,440
Speaker 1: doing the exact opposite. It's it's it's creating an automated

2168
01:46:42,439 --> 01:46:44,679
Speaker 1: process by which you can pump out as much shit

2169
01:46:44,760 --> 01:46:48,920
Speaker 1: as possible, thereby pitting people who create art for a

2170
01:46:48,960 --> 01:46:50,680
Speaker 1: living and hope to make a living off of it

2171
01:46:51,120 --> 01:46:54,320
Speaker 1: against a machine that can generate as much slop as

2172
01:46:54,400 --> 01:46:57,040
Speaker 1: as as as the client can handle. And it's just

2173
01:46:57,080 --> 01:47:00,559
Speaker 1: pushing down wages. It's making it harder for art to

2174
01:47:00,640 --> 01:47:04,520
Speaker 1: make a living. It's it's it's doing anything but but democratizing.

2175
01:47:04,600 --> 01:47:09,000
Speaker 1: And it's making extant relationships between like a publisher and

2176
01:47:09,040 --> 01:47:12,120
Speaker 1: an art and an artist, or a writer and a

2177
01:47:12,200 --> 01:47:16,679
Speaker 1: and and somebody who's commissioning work much more important, thereby

2178
01:47:16,720 --> 01:47:18,120
Speaker 1: depriving people who are new to.

2179
01:47:18,080 --> 01:47:20,880
Speaker 3: The field of opportunities. Uh, you know.

2180
01:47:20,920 --> 01:47:24,200
Speaker 1: Ted Chang makes makes this point in his Great New

2181
01:47:24,280 --> 01:47:27,960
Speaker 1: Yorker essays about AI that it's just it's it's depriving.

2182
01:47:28,040 --> 01:47:29,639
Speaker 3: It's it's kicking down that ladder.

2183
01:47:29,800 --> 01:47:33,000
Speaker 1: Basically, it's like people who practice a craft by doing

2184
01:47:33,040 --> 01:47:36,920
Speaker 1: stuff that's less than you know, authoring a novel that

2185
01:47:36,960 --> 01:47:39,000
Speaker 1: you know you're going to get a full, full rate for,

2186
01:47:39,439 --> 01:47:42,360
Speaker 1: or it's you might still just be learning to apply

2187
01:47:42,439 --> 01:47:45,719
Speaker 1: the trade by writing a you know, marketing copy. Well,

2188
01:47:45,760 --> 01:47:47,680
Speaker 1: the generative AI is going to vacuum up all of

2189
01:47:47,720 --> 01:47:51,080
Speaker 1: those jobs and those opportunities. It's it's it's the anti

2190
01:47:51,640 --> 01:47:52,800
Speaker 1: democratizing force.

2191
01:47:52,880 --> 01:47:54,479
Speaker 3: Really, I was just trying to look up a book,

2192
01:47:54,520 --> 01:48:00,639
Speaker 3: but I failed. There's a wonderful artist, cartoonist, and novelist

2193
01:48:00,680 --> 01:48:05,040
Speaker 3: named Linda Barry, and I co taught a workshop writing

2194
01:48:05,040 --> 01:48:08,080
Speaker 3: workshop that she was also teaching at. And Barry is

2195
01:48:08,120 --> 01:48:11,080
Speaker 3: a great believer in the idea that you can anyone

2196
01:48:11,120 --> 01:48:14,760
Speaker 3: can draw, and that drawing is itself a gateway to

2197
01:48:14,800 --> 01:48:18,320
Speaker 3: a kind of creative understanding of yourself in the world

2198
01:48:18,760 --> 01:48:23,040
Speaker 3: that is uniquely powerful. And as someone who doesn't draw,

2199
01:48:23,560 --> 01:48:25,760
Speaker 3: I was skeptical of this claim. She's written a couple

2200
01:48:25,760 --> 01:48:27,920
Speaker 3: of very good books about this, and she's also won

2201
01:48:27,920 --> 01:48:30,960
Speaker 3: a MacArthur Prize. And I came in and I looked

2202
01:48:30,960 --> 01:48:33,160
Speaker 3: at what my writing students had done after spending a

2203
01:48:33,160 --> 01:48:36,479
Speaker 3: week drawing with Linda Barry. They were not there to

2204
01:48:36,560 --> 01:48:38,120
Speaker 3: learn to draw. They were there to learn to write,

2205
01:48:38,720 --> 01:48:42,120
Speaker 3: and they were remarkably like they had a free and

2206
01:48:42,200 --> 01:48:45,360
Speaker 3: loose arm and in a way that you know a

2207
01:48:45,360 --> 01:48:47,599
Speaker 3: lot of writers. This is a very intensive writing workshop

2208
01:48:47,600 --> 01:48:50,000
Speaker 3: called the Clarion Workshop. It's for science fiction writers at

2209
01:48:50,160 --> 01:48:52,760
Speaker 3: UCSD and I'm a graduate of it and a board

2210
01:48:52,760 --> 01:48:57,759
Speaker 3: member of it and in instructor. And it's often characterized

2211
01:48:57,760 --> 01:48:59,840
Speaker 3: as a kind of boot camp, and usually you get

2212
01:48:59,840 --> 01:49:01,479
Speaker 3: an it's a six week workshop, and I think I

2213
01:49:01,479 --> 01:49:03,000
Speaker 3: was teaching week four and by week four of these

2214
01:49:03,080 --> 01:49:05,760
Speaker 3: kids are zombies. These kids were not zombies, right, They

2215
01:49:05,760 --> 01:49:11,559
Speaker 3: were really open and free and really thinking expansively. So,

2216
01:49:12,160 --> 01:49:15,280
Speaker 3: you know, I think that like giving everyone a week

2217
01:49:15,280 --> 01:49:18,200
Speaker 3: with Linda Berry democratize his art. And I think there's

2218
01:49:18,320 --> 01:49:22,800
Speaker 3: you know, look, I think like typing prompts into an

2219
01:49:22,920 --> 01:49:28,599
Speaker 3: LM is in its own way like being Jackson Pollock

2220
01:49:28,640 --> 01:49:30,960
Speaker 3: and throwing pain at the wall. If that's why and

2221
01:49:31,000 --> 01:49:34,200
Speaker 3: how you're doing it right, Like if you're fooling around, right,

2222
01:49:34,280 --> 01:49:38,120
Speaker 3: if you're fooling around, you can you can get to

2223
01:49:38,200 --> 01:49:40,000
Speaker 3: somewhere that you can't get to if you're trying to

2224
01:49:40,000 --> 01:49:43,519
Speaker 3: get their own purpose. And I just don't think that

2225
01:49:43,560 --> 01:49:46,040
Speaker 3: we're being invited to fool around. Yeah, I think that

2226
01:49:46,040 --> 01:49:46,720
Speaker 3: that's the whole thing.

2227
01:49:46,760 --> 01:49:50,160
Speaker 1: I think artists would not give a shit about jenerative

2228
01:49:50,160 --> 01:49:53,680
Speaker 1: AI if it wasn't being put in opposition to their livelihoods,

2229
01:49:53,680 --> 01:49:55,120
Speaker 1: as if it wasn't threatening.

2230
01:49:54,760 --> 01:49:56,440
Speaker 3: Their economics security.

2231
01:49:56,280 --> 01:49:58,880
Speaker 1: The people that are many people as they want can

2232
01:49:58,920 --> 01:50:01,519
Speaker 1: go play around at home and and do and make

2233
01:50:01,600 --> 01:50:04,599
Speaker 1: different variations and for their own personal enjoyment. I don't

2234
01:50:04,600 --> 01:50:08,400
Speaker 1: think anybody would would would begrudge them that if that

2235
01:50:08,640 --> 01:50:12,560
Speaker 1: wasn't simultaneously being used as a justification as a promotional

2236
01:50:12,600 --> 01:50:16,680
Speaker 1: material essentially by these companies who are then going to

2237
01:50:16,760 --> 01:50:18,240
Speaker 1: go sell other firms.

2238
01:50:18,240 --> 01:50:19,800
Speaker 3: And I know you're gagging to go to an abit.

2239
01:50:19,800 --> 01:50:21,960
Speaker 3: I want to say one last thing. We've got to

2240
01:50:22,040 --> 01:50:23,720
Speaker 3: rouse this bad bloup. So I want to say one

2241
01:50:23,760 --> 01:50:26,080
Speaker 3: last thing here, which is that if you pouparize every

2242
01:50:26,080 --> 01:50:31,000
Speaker 3: single commercial illustrator in the world without open AI, you

2243
01:50:31,080 --> 01:50:33,960
Speaker 3: will pay the kombucha bill for fifteen minutes for their

2244
01:50:34,040 --> 01:50:37,200
Speaker 3: senior engineers. That the only reason they're doing this, This

2245
01:50:37,280 --> 01:50:39,400
Speaker 3: is a great tragedy. The reason they're doing this is

2246
01:50:39,439 --> 01:50:42,520
Speaker 3: not because there is a huge market opportunity in popularizing

2247
01:50:42,520 --> 01:50:47,360
Speaker 3: commercial illustrators. It's that it is an exemplary opportunity. It's

2248
01:50:47,360 --> 01:50:49,280
Speaker 3: not that there's a it's not that the market will

2249
01:50:49,320 --> 01:50:51,840
Speaker 3: then return their investment. It's that it will be a

2250
01:50:51,960 --> 01:50:55,280
Speaker 3: very visible example of what you can do with open AI.

2251
01:50:55,479 --> 01:50:56,360
Speaker 3: It's a convincer.

2252
01:50:56,640 --> 01:50:59,439
Speaker 1: They are effected one of the few that actually works, Yes,

2253
01:51:00,160 --> 01:51:03,240
Speaker 1: that can be dependably relied on to produce results that

2254
01:51:03,280 --> 01:51:04,639
Speaker 1: you can point to and say, hey, look.

2255
01:51:04,640 --> 01:51:05,840
Speaker 3: That kind of works. Yeah.

2256
01:51:05,960 --> 01:51:09,280
Speaker 2: Yeah, So guys, it's been so wonderful having you. I

2257
01:51:09,280 --> 01:51:12,200
Speaker 2: could go another three hours, but that's just me Corey.

2258
01:51:12,240 --> 01:51:13,200
Speaker 2: Where can people find you?

2259
01:51:13,400 --> 01:51:13,479
Speaker 4: So?

2260
01:51:13,720 --> 01:51:17,080
Speaker 3: I'm at pluralistic dot net and as I've mentioned a

2261
01:51:17,080 --> 01:51:19,599
Speaker 3: few times, I write science fiction novels and other kinds

2262
01:51:19,600 --> 01:51:23,080
Speaker 3: of books, mostly published by tor Books at McMillan. You

2263
01:51:23,080 --> 01:51:24,920
Speaker 3: can get them wherever you get books.

2264
01:51:26,520 --> 01:51:30,920
Speaker 1: Brian, Yeah, I write a newsletter called Blood in the Machine.

2265
01:51:31,280 --> 01:51:34,679
Speaker 1: It's also the name of the book of the similar theme.

2266
01:51:34,960 --> 01:51:36,320
Speaker 1: You can check either out.

2267
01:51:36,479 --> 01:51:39,000
Speaker 3: Yeah blood inthemachine dot com.

2268
01:51:39,400 --> 01:51:42,840
Speaker 2: Yeahs so you and also hopefully I'll put all of

2269
01:51:42,880 --> 01:51:44,120
Speaker 2: the links to this stuff in there.

2270
01:51:44,120 --> 01:51:45,960
Speaker 3: But it's always good to hear out loud. Guys.

2271
01:51:46,000 --> 01:51:48,200
Speaker 2: Thank you so much for joining me and listeners, thank

2272
01:51:48,240 --> 01:51:51,280
Speaker 2: you so much for listening. When you get out of

2273
01:51:51,840 --> 01:51:54,160
Speaker 2: the clink, you can email me at easy at Better

2274
01:51:54,200 --> 01:51:56,840
Speaker 2: Offline dot com and net for my Canadian and UK

2275
01:51:57,080 --> 01:51:59,080
Speaker 2: just that out Canadians say z as well.

2276
01:51:59,080 --> 01:52:01,880
Speaker 3: Ez off line, You're like serial killers where everyone we

2277
01:52:01,920 --> 01:52:03,600
Speaker 3: look just like everyone else and we say Z.

2278
01:52:04,120 --> 01:52:07,120
Speaker 2: That's right, bellow Canadian, I've I just learned, I've met

2279
01:52:07,120 --> 01:52:07,800
Speaker 2: a Canadians.

2280
01:52:07,840 --> 01:52:08,280
Speaker 3: Wonderful.

2281
01:52:08,320 --> 01:52:10,360
Speaker 2: All right, thank you so much for listening, and Corey Brian,

2282
01:52:10,479 --> 01:52:11,600
Speaker 2: thank you so much for joining me.

2283
01:52:11,760 --> 01:52:22,200
Speaker 3: Thank you, thank you, thank you for listening to Better Offline.

2284
01:52:22,320 --> 01:52:24,760
Speaker 2: The editor and composer of the Better Offline theme song

2285
01:52:24,840 --> 01:52:27,479
Speaker 2: is Matasowski. You can check out more of his music

2286
01:52:27,479 --> 01:52:31,160
Speaker 2: and audio projects at Mattasowski dot com, M A T

2287
01:52:31,160 --> 01:52:35,600
Speaker 2: T O. S O W s KI dot com. You

2288
01:52:35,640 --> 01:52:38,160
Speaker 2: can email me at easy at Better Offline dot com

2289
01:52:38,240 --> 01:52:40,519
Speaker 2: or visit Better Offline dot com to find more podcast

2290
01:52:40,600 --> 01:52:43,920
Speaker 2: links and of course, my newsletter. I also really recommend

2291
01:52:43,960 --> 01:52:45,840
Speaker 2: you go to chat dot Where's your ed dot at

2292
01:52:45,840 --> 01:52:48,280
Speaker 2: to visit the discord, and go to our slash Better

2293
01:52:48,320 --> 01:52:49,880
Speaker 2: Offline to check out our reddit.

2294
01:52:50,680 --> 01:52:53,920
Speaker 3: Thank you so much for listening. Better Offline is a

2295
01:52:53,960 --> 01:52:57,040
Speaker 3: production of cool Zone Media. For more from cool Zone Media,

2296
01:52:57,160 --> 01:53:00,479
Speaker 3: visit our website cool zonemedia dot com. Check us out

2297
01:53:00,560 --> 01:53:03,519
Speaker 3: on the iHeartRadio app, Apple Podcasts, or wherever you get

2298
01:53:03,520 --> 01:53:17,680
Speaker 3: your podcasts.