WEBVTT - Big Tech’s Most Valuable Product Isn’t AI. It’s the Belief that AI is Inevitable - The Story

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<v Speaker 1>Welcome to tech Stuff. I'm Os Voloshen. If you've been

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<v Speaker 1>listening to this podcast, or if you spend any time

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<v Speaker 1>on the Internet, you won't be able to miss the

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<v Speaker 1>word in shitification. And our guest today is the man

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<v Speaker 1>who coined it, Corey doctor Ol. He's a science fiction author,

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<v Speaker 1>a technology activist, and a journalist. His new book is

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<v Speaker 1>called The Reverse Centaur's Guide to Life After AI, How

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<v Speaker 1>to Think about Artificial Intelligence before It's too late. Corey,

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<v Speaker 1>Welcome to text Stuff.

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<v Speaker 2>Thanks as it's a pleasure to be on.

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<v Speaker 1>For anyone who did miss it. What is in ghentification?

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<v Speaker 2>Well, I've worked for the Electronic Frontier Foundation, which is

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<v Speaker 2>an NGO, for twenty five years on the question digital rights,

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<v Speaker 2>and getting people to engage with that question is very

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<v Speaker 2>hard because digital rights questions are abstract and technical and

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<v Speaker 2>relate to things that are going to happen in the future,

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<v Speaker 2>and for very good reasons, people mostly care about concrete

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<v Speaker 2>things happening right now. And what I have done over

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<v Speaker 2>the years has come up with different framing devices and

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<v Speaker 2>similes and metaphors and narratives too. I'm a science fiction novelist,

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<v Speaker 2>but it turned out that a dirty word initification was

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<v Speaker 2>the way to get people to engage in it, and

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<v Speaker 2>so more specifically in sitification is this theory and description.

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<v Speaker 2>It describes how the platforms that we rely on have

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<v Speaker 2>turned into piles of shit, where first they are good

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<v Speaker 2>to their end users but lock them in, and then

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<v Speaker 2>having locked in the end users and made it difficult

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<v Speaker 2>for them to leave, they make it worse for them

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<v Speaker 2>to make it tempting for businesses. And then when the

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<v Speaker 2>businesses are also locked in, they also extract everything they

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<v Speaker 2>can from those businesses and line their own pockets and

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<v Speaker 2>turn into a pile of shit. But the more interesting

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<v Speaker 2>part of it is why they're doing it, And this

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<v Speaker 2>maybe relates to the conversation we're having today, which is

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<v Speaker 2>about the economics and political economy of monopoly, that when

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<v Speaker 2>you let firms get too big to fail, they become

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<v Speaker 2>too big to jail, and then that makes them too

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<v Speaker 2>big to care, and they destroy our lives for the

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<v Speaker 2>same reason your dog looks its balls because they can

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<v Speaker 2>and no one makes them start.

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<v Speaker 1>I want to get into all of that with you,

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<v Speaker 1>but I've read the acknowledgments of your book, not just

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<v Speaker 1>the acknowledgements. If I'm always interesting acknowledgments, and you had

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<v Speaker 1>the same editor for this book, this new book, the

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<v Speaker 1>Reverse Centaur's Guide, as you did for last year's in

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<v Speaker 1>Certification book, and you kind of credit him with helping you,

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<v Speaker 1>not just with in Certification argument, but with this argument.

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<v Speaker 1>And I'm curious, like, where does the reverse central sit

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<v Speaker 1>in the lineage of inertifications? What is it a development

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<v Speaker 1>of the same argument or is it totally new argument?

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<v Speaker 1>Because in Certification was essentially about the tech platforms of

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<v Speaker 1>the Internet, and this is about the experience of AI.

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<v Speaker 2>The common lineage between in Certification and my critique of

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<v Speaker 2>AI is grounded in the dysfunctions and pathologies of firms

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<v Speaker 2>that conquer their markets of saturate their markets. Monopolies, cartels doopolies.

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<v Speaker 2>And one of the consequences of having monopoly is that

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<v Speaker 2>you become ungovernable in the worst sense, not in the

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<v Speaker 2>cool sense of like a raccoon, but in the bad

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<v Speaker 2>sense of like Donald Trump. And you are so liberated

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<v Speaker 2>from consequence that you can do unlimited bad things to

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<v Speaker 2>lots of people, including people you would think would have

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<v Speaker 2>some power in the economy, and just get away with it.

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<v Speaker 2>And really the worst ideas of the worst people become

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<v Speaker 2>the most profitable way of doing business. So that's like

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<v Speaker 2>in shitification at its theoretical core. But reverse centaur is

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<v Speaker 2>about another epiphenomenon, another thing that a consequence of monopoly,

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<v Speaker 2>which is that if your firm that has saturated its

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<v Speaker 2>market right Google has a ninety percent market share, then

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<v Speaker 2>you can't grow anymore. And you know, there's this saying

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<v Speaker 2>among leftists and crunchy granola types that endless growth is

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<v Speaker 2>the ideology of a tumor, and that grounds it in

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<v Speaker 2>this idea that the reason firms want to continue growing

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<v Speaker 2>as ideological and not practical or concrete. And while there

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<v Speaker 2>is some ideology at work there in the way that

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<v Speaker 2>we think about our economy and in the environmental consequences

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<v Speaker 2>of that, there are very practical, material reasons that companies

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<v Speaker 2>want to be perceived as growing and not as mature

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<v Speaker 2>and at the end of their growth cycle. And that

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<v Speaker 2>is because the share price of a company that is

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<v Speaker 2>growing is much higher based on the total economic turnover

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<v Speaker 2>of that company than the share price of affirm with

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<v Speaker 2>the same turnover. But that is static, and that's not irrational.

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<v Speaker 2>A share and affirm is a claim on its future earnings.

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<v Speaker 2>Firms that are growing have more future earnings to return

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<v Speaker 2>to you than firms that are not growing. And the

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<v Speaker 2>corollary of this is that when your firm stops growing,

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<v Speaker 2>it becomes overvalued because the future earnings have contracted when

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<v Speaker 2>you reach the top of your game and you stop growing,

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<v Speaker 2>and that provokes these mass sell offs by investors.

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<v Speaker 1>You mentioned, I think you mentioned that you know the

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<v Speaker 1>Invidia cell of when the deep Seak moment happened. Obviously, Yeah,

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<v Speaker 1>in video rebounded from that, but it raised the it

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<v Speaker 1>raised a specter that growth may not be unlimited.

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<v Speaker 2>Yeah, the video sell off was the largest decapitalization in

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<v Speaker 2>twenty four hours of any firm. And when your firm

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<v Speaker 2>becomes illiquid, right when it's not, when it's not traded

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<v Speaker 2>at this high multiple and so liquid, you can't grow

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<v Speaker 2>by buying other firms by offering them stock. You have

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<v Speaker 2>to give them money. And money is an exogenous substance

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<v Speaker 2>that's produced outside the firm, and shares are things that

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<v Speaker 2>are produced inside the firm by typing zeros and to

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<v Speaker 2>a spreadsheet. And so it's always preferable to be able

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<v Speaker 2>to acquire firms and talent using shares. This endogenous substance

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<v Speaker 2>you can produce on demand, and you can only do

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<v Speaker 2>that while you're growing. So this is another kind of

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<v Speaker 2>growth paradox, right, which is that it's easy to keep

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<v Speaker 2>growing when you're growing because you can buy other companies,

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<v Speaker 2>but it's hard when you stop growing to start growing again,

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<v Speaker 2>not least because all those key employees that have been

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<v Speaker 2>paid in shares suddenly see their net worthfall off a

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<v Speaker 2>cliff when you when your share price declines, and they

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<v Speaker 2>might go look for work elsewhere, which means they're not

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<v Speaker 2>going to help you start the firm up again. They're

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<v Speaker 2>not going to help you get a back on a

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<v Speaker 2>growth trajectory.

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<v Speaker 1>So that the central argument of the book is that

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<v Speaker 1>a lot of technology companies order the practice order. The

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<v Speaker 1>technology companies have an extraordinary incentive to persuade the white

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<v Speaker 1>world that in a AI is inevitable, and that that

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<v Speaker 1>kind of mythology is of the essence to protecting their

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<v Speaker 1>value and therefore keeping their employees and their ability to

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<v Speaker 1>keep growing by buying other companies with their stock.

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<v Speaker 2>Yes, So what I would say is that the book

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<v Speaker 2>is exploring why tech bubbles exist at all. And this

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<v Speaker 2>is not the first one we've had, you know, metaverse

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<v Speaker 2>and cryptocurrency and web three, all those other things.

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<v Speaker 1>But they were all palpably confections, right, those those were

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<v Speaker 1>not things that people use, whereas, like all you do

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<v Speaker 1>is any conversation you over hear in the subway, in

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<v Speaker 1>a restaurant, whatever, is people telling each other how they

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<v Speaker 1>use AI. So that arguably is a big difference.

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<v Speaker 2>So it's just so those bubbles were smaller. Why is

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<v Speaker 2>the a bubble larger? And some of it is because

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<v Speaker 2>AI is realer than those things. So I'm a fake

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<v Speaker 2>computer scientist. I have an honorary doctor in computer science

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<v Speaker 2>from the Open University, and in my capacity as a

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<v Speaker 2>fake computer scientist, I can tell you that AI is

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<v Speaker 2>pretty interesting.

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<v Speaker 1>And from a user point of view, I would argue

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<v Speaker 1>a feeling of technology magic for the first time in

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<v Speaker 1>a long time.

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<v Speaker 2>Sure, yeah, no, very impressive, although I would also say

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<v Speaker 2>that that feeling regresses to the mean pretty quickly. Right

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<v Speaker 2>that if there was a place where there was like

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<v Speaker 2>some kind of weird localized gravity storm, and you took

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<v Speaker 2>a big pile of leaves and you threw it in

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<v Speaker 2>the air and it fell down, in a sentence, we

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<v Speaker 2>would all go throw leaves in the air and look

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<v Speaker 2>at the sentences they made for a while, and then

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<v Speaker 2>we'd be like, they're just not good sentences.

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<v Speaker 1>Going back to the Internet bubble, obviously Internet bubble crash,

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<v Speaker 1>but then very shortly afterwards, Facebook and Google and Amazon emerged.

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<v Speaker 1>So even if there is like a big froth cycle

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<v Speaker 1>around some of the valuations and companies and new billionaires

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<v Speaker 1>who are emerging, I mean, if it's a bubble like

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<v Speaker 1>the web, it maybe a short term financial bubble that

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<v Speaker 1>will burst, but a fundamental platform shift in terms of

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<v Speaker 1>how we interact with technology in the world, Like do

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<v Speaker 1>you believe that will be true of AI or didn't

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<v Speaker 1>the AI in more similar to web three or to

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<v Speaker 1>the metaverse?

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<v Speaker 2>Yeah? Sure, I think AI has some similarities to the

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<v Speaker 2>Web bubble as compared to other bubbles of the day.

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<v Speaker 2>So you know, a bubble that was roughly concurrent with

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<v Speaker 2>the Web bubble was the Enron bubble, right, the energy

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<v Speaker 2>trading bubble, and that was just accounting fraud, and when

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<v Speaker 2>it was over there was nothing but like indictments and

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<v Speaker 2>a language corpus because they couldn't be arked to pay

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<v Speaker 2>a lawyer to redact their emails before they submitted them

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<v Speaker 2>for discovery, whereas the Web left behind like a couple

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<v Speaker 2>million humanities undergraduates who'd been inveigled to drop out and

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<v Speaker 2>become Pearl and python in HTML jocks, and so you know,

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<v Speaker 2>you say that what succeeded the dot com bubble was

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<v Speaker 2>Amazon and Google and Facebook and so on, but there

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<v Speaker 2>was an intermediate step there, and the intermediate step was

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<v Speaker 2>Web too. It was a ton of little amazing startups

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<v Speaker 2>that were what you got when skill practitioners were liberated

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<v Speaker 2>from the need to indulge the foolish fantasies of their

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<v Speaker 2>bosses who were very good at getting capital and very

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<v Speaker 2>bad at coming up with products. So that was pretty amazing.

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<v Speaker 2>Although we shoul it's say that the Enron bubble, the

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<v Speaker 2>Web bubble, and the AI bubble foundationally are not about

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<v Speaker 2>what they produce. They're about separating suckers from their money,

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<v Speaker 2>right that like the point of a bubble is to

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<v Speaker 2>get insiders to cash out and leave ordinary investors holding

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<v Speaker 2>the bag. So no bubble is good, but some bubbles

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<v Speaker 2>have productive residues. So in that sense, AI, I think

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<v Speaker 2>is like the Web in that we're going to have

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<v Speaker 2>a lot of GPUs at ten cents on the dollar,

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<v Speaker 2>a lot of skilled practitioners looking for work and maybe

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<v Speaker 2>hiring each other. And also these open source models that

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<v Speaker 2>will continue to function whether or not there's a company

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<v Speaker 2>that produce them, because open source software continues to exist

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<v Speaker 2>for as long as it exists. But there's a big difference,

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<v Speaker 2>actually two. So the first is the vibe. So if

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<v Speaker 2>you go back and you read like Harvard Business Review

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<v Speaker 2>articles or NBER reports on the workforce in the era

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<v Speaker 2>of the web, what you see are all these articles

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<v Speaker 2>about like bosses who have to be dragkicking and screaming

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<v Speaker 2>into allowing their workers to use a technology that they

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<v Speaker 2>see as transformative. And when you look at comparable reports today,

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<v Speaker 2>it's full of bosses threatening to fire workers if they

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<v Speaker 2>don't use AI. Right. This is now getting to the

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<v Speaker 2>material way in which the web is different from AI.

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<v Speaker 2>The unit economics of the web were very good. Every

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<v Speaker 2>new user of the web made the web more profitable.

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<v Speaker 2>Every new use of the web made the web more profitable,

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<v Speaker 2>and every generation of the web was more profitable than

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<v Speaker 2>the previous generation. That's the opposite of AI. Right, So

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<v Speaker 2>AI companies are selling hundred dollars bills for a dollar apiece.

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<v Speaker 2>So if you become an AI customer, they start to

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<v Speaker 2>lose money. If you continue to be an AI customer,

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<v Speaker 2>they lose more money. And the next generation of AI

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<v Speaker 2>is going to be selling two one hundred dollars bills

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<v Speaker 2>for a dollar apiece, and so it's going to be worse.

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<v Speaker 2>And so that makes it a qualitatively and quantitatively different

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<v Speaker 2>kind of bubble to the web bubble.

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<v Speaker 1>So what's your role in all of this? And I

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<v Speaker 1>think you mentioned the book or in your speech that

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<v Speaker 1>you gave Washington that you know, as a science fiction

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<v Speaker 1>right to people always want to ask you if your

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<v Speaker 1>opinion on AI because I guess so many of the

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<v Speaker 1>AI overlords talk about how science fiction governs their thoughts

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<v Speaker 1>about what they're building. You know, you've said as well,

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<v Speaker 1>science fiction is anti inevitableist literature, as it was a

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<v Speaker 1>great phrase. I mean, what is what is your role

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<v Speaker 1>in this? What do you what do you want people

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<v Speaker 1>to understand to do differently?

0:12:25.520 --> 0:12:28.880
<v Speaker 2>Yeah, I think that the people who run a bubble,

0:12:30.040 --> 0:12:32.240
<v Speaker 2>whether or not it has a productive residue, you always

0:12:32.280 --> 0:12:35.000
<v Speaker 2>want to style themselves as avatars of the great forces

0:12:35.040 --> 0:12:38.160
<v Speaker 2>of history and the iron laws of economics. Right, they're

0:12:38.240 --> 0:12:43.280
<v Speaker 2>not imposing a technology on you. Rather, they are just

0:12:43.400 --> 0:12:46.040
<v Speaker 2>doing what the circumstances demand. And if it wasn't them,

0:12:46.040 --> 0:12:48.040
<v Speaker 2>it'd be someone else, although it has to be them

0:12:48.080 --> 0:12:50.800
<v Speaker 2>because they're extraordinary. But but you know, this is the

0:12:50.800 --> 0:12:52.680
<v Speaker 2>moment at which we are going to get AI and

0:12:52.679 --> 0:12:54.040
<v Speaker 2>we're all going to use AI, and there is no

0:12:54.120 --> 0:12:56.200
<v Speaker 2>future without AI, and the only II that we're going

0:12:56.200 --> 0:12:57.960
<v Speaker 2>to have in the future is the AI they're making,

0:12:59.000 --> 0:13:03.280
<v Speaker 2>and everybody else just shut up. And I call this

0:13:03.600 --> 0:13:08.080
<v Speaker 2>a kind of species of vulgar Thatcherism, because you know

0:13:08.160 --> 0:13:11.240
<v Speaker 2>Margaret Thatcher, she had this aphorism, there is no alternative,

0:13:11.640 --> 0:13:15.360
<v Speaker 2>and this is the mother of all thoughts stopping cliches,

0:13:15.920 --> 0:13:18.400
<v Speaker 2>because what she meant by there is no alternative is

0:13:18.400 --> 0:13:21.120
<v Speaker 2>don't you dare try and think of an alternative? Right.

0:13:21.200 --> 0:13:24.280
<v Speaker 2>Another way of saying there is no alternative is resistance

0:13:24.360 --> 0:13:29.520
<v Speaker 2>is futile, but there is no alternative implies Also, if

0:13:29.559 --> 0:13:32.840
<v Speaker 2>you're unhappy with this, don't get mad at me. Get

0:13:32.880 --> 0:13:34.960
<v Speaker 2>mad at the iron laws of economics and the great

0:13:35.000 --> 0:13:37.280
<v Speaker 2>forces of history, because it could be no other way,

0:13:38.040 --> 0:13:42.160
<v Speaker 2>and science fiction is entirely concerned with all the other

0:13:42.200 --> 0:13:48.080
<v Speaker 2>ways things could be right and in challenging the idea

0:13:48.600 --> 0:13:51.559
<v Speaker 2>that everything is inevitable and nothing is contingent.

0:13:52.160 --> 0:13:55.480
<v Speaker 1>So what's the alternative vision you're laying out for what

0:13:55.520 --> 0:13:58.080
<v Speaker 1>the future may be? I mean, right now it looks like,

0:13:58.880 --> 0:14:04.360
<v Speaker 1>you know, three trillion dollar IPOs, this year's basic exentropic

0:14:05.040 --> 0:14:09.840
<v Speaker 1>open AI. You know, new trillionaires and billionaires and multimillionaires,

0:14:11.360 --> 0:14:15.240
<v Speaker 1>all of whom will then have the capital. Well, the

0:14:15.640 --> 0:14:18.920
<v Speaker 1>share evaluation is to quiem more companies the cash money

0:14:18.960 --> 0:14:25.880
<v Speaker 1>to support politicians and packs like. What might disrupt the

0:14:25.920 --> 0:14:27.720
<v Speaker 1>futures is currently emerging.

0:14:27.720 --> 0:14:31.400
<v Speaker 2>So I can't predict when the bubble will pop. But

0:14:31.640 --> 0:14:34.840
<v Speaker 2>firms that are making tens of billions of dollars a

0:14:34.960 --> 0:14:37.360
<v Speaker 2>year and spending hundreds of billions of dollars a year

0:14:37.400 --> 0:14:39.600
<v Speaker 2>and that are telling us they need to spend more

0:14:39.640 --> 0:14:42.040
<v Speaker 2>hundreds of billions of dollars a year, but whenever they

0:14:42.040 --> 0:14:44.240
<v Speaker 2>try to raise prices. I mean, Anthropic just tried to

0:14:44.280 --> 0:14:46.360
<v Speaker 2>clean up its balance sheet a little by saying we're

0:14:46.360 --> 0:14:48.600
<v Speaker 2>not selling hundred dollar bills for a dollar apiece anymore.

0:14:48.640 --> 0:14:50.760
<v Speaker 2>They're going to be five dollars apiece, and all their

0:14:50.760 --> 0:14:52.840
<v Speaker 2>best customers are like, I guess we can't use AI

0:14:52.960 --> 0:14:55.640
<v Speaker 2>anymore because at five dollars, these hundred dollar bills are

0:14:55.640 --> 0:15:00.000
<v Speaker 2>not worth it. So when they run out of peace,

0:15:00.000 --> 0:15:04.520
<v Speaker 2>people who will give the money. Because listed are privately held,

0:15:05.080 --> 0:15:07.240
<v Speaker 2>you can't spend more than your taking in unless you

0:15:07.280 --> 0:15:10.280
<v Speaker 2>have a creditor. Right, it doesn't matter how big your

0:15:10.320 --> 0:15:15.200
<v Speaker 2>IPO was, Right, you have operating expenses. I mean, I

0:15:15.240 --> 0:15:18.320
<v Speaker 2>guess you could just like loan the company money from

0:15:18.400 --> 0:15:20.520
<v Speaker 2>your own shares, but you know this kicks off the

0:15:21.440 --> 0:15:25.480
<v Speaker 2>crunch where you flog your shares to get operating capital

0:15:25.520 --> 0:15:28.160
<v Speaker 2>for the company. The supply of shares goes up, the

0:15:28.200 --> 0:15:29.840
<v Speaker 2>value of the shares goes down, and you're in a

0:15:29.880 --> 0:15:32.560
<v Speaker 2>death spiral. So you know, I don't know what's going

0:15:32.600 --> 0:15:37.560
<v Speaker 2>to shatter this fragile system we're in. Maybe it's like

0:15:37.960 --> 0:15:41.800
<v Speaker 2>Golf States say, sorry, Dario, I know you told us

0:15:41.800 --> 0:15:43.960
<v Speaker 2>that we were going to make God here, but we've

0:15:44.000 --> 0:15:47.640
<v Speaker 2>decided that we need to have LNG terminals because Donald

0:15:47.640 --> 0:15:50.920
<v Speaker 2>Trump keeps getting the Iranians to blow ours up, and

0:15:51.040 --> 0:15:53.520
<v Speaker 2>we don't think we have a future without LNG terminals,

0:15:53.560 --> 0:15:56.600
<v Speaker 2>even if we are going to own eight percent of God,

0:15:56.840 --> 0:16:00.560
<v Speaker 2>and then, like without the golf, you lose the the

0:16:00.560 --> 0:16:03.240
<v Speaker 2>rest of the financing collapses. Who knows, right, it could

0:16:03.280 --> 0:16:05.760
<v Speaker 2>be any or all of the above, but anything that

0:16:05.760 --> 0:16:07.440
<v Speaker 2>can't go on forever eventually stops.

0:16:08.000 --> 0:16:10.720
<v Speaker 1>I think, I think, I guess that the pushback would

0:16:10.720 --> 0:16:14.240
<v Speaker 1>be to say, well, maybe right, but you know, if

0:16:14.280 --> 0:16:18.000
<v Speaker 1>there's there are other companies like Google, for example, who

0:16:18.080 --> 0:16:21.200
<v Speaker 1>can continue to fund their plans which are very similar

0:16:21.200 --> 0:16:23.520
<v Speaker 1>to Anthropic and opening eyes into SpaceX is because of

0:16:23.600 --> 0:16:27.480
<v Speaker 1>their you know, they're they're they're profitably if they're operating

0:16:27.600 --> 0:16:31.480
<v Speaker 1>operating business, and that like somebody may they all Elon

0:16:31.560 --> 0:16:33.960
<v Speaker 1>may be able to convince the public and public markets

0:16:34.000 --> 0:16:36.560
<v Speaker 1>believing for long enough that he can bring together space

0:16:36.640 --> 0:16:40.080
<v Speaker 1>and robotics and data centers and all these types of things.

0:16:40.080 --> 0:16:42.080
<v Speaker 1>I mean, I guess like the proof will being the

0:16:42.120 --> 0:16:46.120
<v Speaker 1>pulling is it's just unknowable, but certainly that is what

0:16:46.360 --> 0:16:51.240
<v Speaker 1>is clear is that the it's a historical disconnect between

0:16:51.280 --> 0:16:53.800
<v Speaker 1>the financial performance of these companies and the evaluation and

0:16:54.000 --> 0:17:11.200
<v Speaker 1>and and I mean, that's that's unarguable. After the break,

0:17:11.680 --> 0:17:14.480
<v Speaker 1>what if a computer program decided whether or not you

0:17:14.600 --> 0:17:23.320
<v Speaker 1>deserve a job stay with us. We sort of spent

0:17:23.400 --> 0:17:26.160
<v Speaker 1>quite a lot of time I think setting the stakes,

0:17:26.240 --> 0:17:28.360
<v Speaker 1>the backdrop. There's two more things I want to talk

0:17:28.400 --> 0:17:32.480
<v Speaker 1>about while we're together. One is people and the other

0:17:32.600 --> 0:17:35.280
<v Speaker 1>is politics. But we've had too much fun to define

0:17:35.359 --> 0:17:36.480
<v Speaker 1>what a reverse centaur is.

0:17:38.240 --> 0:17:42.280
<v Speaker 2>Yeah, well, I think that in a long history of automation,

0:17:43.040 --> 0:17:45.639
<v Speaker 2>where automation is driven by workers, it tends to be

0:17:46.119 --> 0:17:50.680
<v Speaker 2>about improving quality, whereas capital driven automation is tilted towards

0:17:50.720 --> 0:17:55.320
<v Speaker 2>improving throughput. Not because bosses are mustache twirling villains, but

0:17:55.480 --> 0:17:57.840
<v Speaker 2>because when you have an asset that's depreciating, you want

0:17:57.880 --> 0:17:59.000
<v Speaker 2>to get as much use out of it as you

0:17:59.080 --> 0:18:02.400
<v Speaker 2>can before it falls off balance sheet. Another aspect that's

0:18:02.440 --> 0:18:06.280
<v Speaker 2>closely related in automation theory is the idea of a centaur,

0:18:07.000 --> 0:18:10.120
<v Speaker 2>which is a person assisted by a machine. So that's

0:18:10.760 --> 0:18:13.480
<v Speaker 2>you on a bicycle, you with a spell checker, you

0:18:13.600 --> 0:18:16.399
<v Speaker 2>with an ide right, Like when I started programming, we

0:18:16.480 --> 0:18:19.200
<v Speaker 2>didn't have debuggers, right, So like that makes you a

0:18:19.280 --> 0:18:24.639
<v Speaker 2>centaur too, whereas a reverse centaur is a person conscripted

0:18:24.840 --> 0:18:27.760
<v Speaker 2>to serve as a peripheral for a machine, and because

0:18:27.800 --> 0:18:32.920
<v Speaker 2>of those dynamics of how capital views its investments, that

0:18:33.359 --> 0:18:36.879
<v Speaker 2>person is usually the bottleneck in the machine's performance. Right.

0:18:37.000 --> 0:18:39.600
<v Speaker 2>People generally can't work as long or as fast as

0:18:39.600 --> 0:18:42.600
<v Speaker 2>a machine, and that person is now worked at the

0:18:42.800 --> 0:18:46.200
<v Speaker 2>edge of their capability and to the edge of their endurance,

0:18:47.000 --> 0:18:49.800
<v Speaker 2>because that's how you maximize the return on the hard

0:18:49.840 --> 0:18:53.320
<v Speaker 2>asset that they are assisting. And again this is not

0:18:53.440 --> 0:18:55.680
<v Speaker 2>a new idea, Like there's a reason that you know,

0:18:55.760 --> 0:18:58.159
<v Speaker 2>whether you're looking at Charlie Chaplin in Modern Times or

0:18:58.520 --> 0:19:00.959
<v Speaker 2>Lucille Ball in that episode where she and Ethel are

0:19:01.000 --> 0:19:03.560
<v Speaker 2>putting chocolates in the chocolate box on the conveyor belt,

0:19:03.880 --> 0:19:08.760
<v Speaker 2>that the motif of automation is the speed up, right,

0:19:08.920 --> 0:19:12.160
<v Speaker 2>and it's it's the worker being used up by the machine.

0:19:13.000 --> 0:19:15.639
<v Speaker 2>And you know, the warehouses that are most automated in

0:19:15.720 --> 0:19:18.800
<v Speaker 2>America are Amazon's warehouses, and they're also the warehouses with

0:19:18.840 --> 0:19:21.879
<v Speaker 2>the highest rate of significant injury. Those aren't coincidences. Those

0:19:21.920 --> 0:19:24.600
<v Speaker 2>are like those are co determined, right, because if you're

0:19:24.600 --> 0:19:26.680
<v Speaker 2>going to put seven figures into warehouse automation, you want

0:19:26.680 --> 0:19:28.520
<v Speaker 2>to work the warehouse automation as quickly as you can.

0:19:29.080 --> 0:19:32.960
<v Speaker 2>So an Amazon driver is there because even if you

0:19:33.000 --> 0:19:35.600
<v Speaker 2>could get the van to drive itself in urban traffic, well,

0:19:36.320 --> 0:19:39.120
<v Speaker 2>it couldn't get the parcel onto your porch or onto

0:19:39.200 --> 0:19:42.960
<v Speaker 2>your mailbox or you know, into your office building, and

0:19:43.280 --> 0:19:45.639
<v Speaker 2>so it needs to have a driver there, and so

0:19:45.800 --> 0:19:48.280
<v Speaker 2>you work that driver at the outer limit of their

0:19:48.400 --> 0:19:52.480
<v Speaker 2>ability and their endurance. And the reason people pee in

0:19:52.520 --> 0:19:55.760
<v Speaker 2>the vans is because you cannot make the quota unless

0:19:55.840 --> 0:19:59.000
<v Speaker 2>you operate at a speed that requires that you not

0:19:59.160 --> 0:19:59.800
<v Speaker 2>have kidneys.

0:20:00.200 --> 0:20:01.640
<v Speaker 1>I mean you said in the book that you get

0:20:01.720 --> 0:20:05.439
<v Speaker 1>penalized for swerving even if you're avoiding Yeah, a danger.

0:20:05.600 --> 0:20:06.680
<v Speaker 1>I mean that does that really true?

0:20:07.080 --> 0:20:10.120
<v Speaker 2>Yeah? So Katie Wells just published a good ethnography. She's

0:20:10.119 --> 0:20:12.000
<v Speaker 2>done a lot of work on Amazon drivers and on

0:20:12.080 --> 0:20:16.280
<v Speaker 2>algorithmic wage discrimination and algorithmic management. She just published some

0:20:16.440 --> 0:20:20.000
<v Speaker 2>ethnographies where she worked with another Amazon a former Amazon driver,

0:20:20.560 --> 0:20:22.880
<v Speaker 2>to interview a bunch of current and past Amazon drivers,

0:20:22.920 --> 0:20:26.720
<v Speaker 2>including one who was fired for swerving when a big

0:20:26.880 --> 0:20:29.800
<v Speaker 2>rig crossed the medium because the driver had fallen asleep

0:20:29.920 --> 0:20:32.520
<v Speaker 2>and was headed for a head on collision. And they

0:20:32.560 --> 0:20:34.960
<v Speaker 2>were fired for making a dangerous maneuver, which is to say,

0:20:35.040 --> 0:20:37.480
<v Speaker 2>swerving out of the way of a truck that would

0:20:37.480 --> 0:20:40.600
<v Speaker 2>have killed them. And there's lots of petty examples too, though, right,

0:20:40.640 --> 0:20:43.720
<v Speaker 2>you can get dinged on your performance if the camera

0:20:43.840 --> 0:20:46.080
<v Speaker 2>thinks that your mouth has opened too much, because singing

0:20:46.200 --> 0:20:50.480
<v Speaker 2>is considered distracted driving. You know, it's something of a

0:20:50.560 --> 0:20:56.120
<v Speaker 2>paradox that these heavily surveilled workers who you would think

0:20:56.280 --> 0:20:59.440
<v Speaker 2>those cameras might be used to vindicate them, find that

0:20:59.480 --> 0:21:02.160
<v Speaker 2>those cameras are only an ever used to penalize them.

0:21:02.680 --> 0:21:04.960
<v Speaker 2>Right that if you've got a million cameras on your truck,

0:21:05.080 --> 0:21:08.200
<v Speaker 2>that's when you show your boss, hey, look I got

0:21:08.359 --> 0:21:11.119
<v Speaker 2>I swerve because the truck was coming straight at me.

0:21:11.840 --> 0:21:15.199
<v Speaker 2>But that's never in the field. In fact, you never

0:21:15.240 --> 0:21:17.120
<v Speaker 2>get to talk to the person who fires you, because

0:21:17.119 --> 0:21:19.359
<v Speaker 2>the way that it works with the DSPs is that

0:21:19.680 --> 0:21:23.040
<v Speaker 2>they don't they're not Amazon, they're they are themselves so

0:21:23.240 --> 0:21:26.840
<v Speaker 2>called independent businesses that hire you. And then the app

0:21:27.040 --> 0:21:30.280
<v Speaker 2>tells your boss to fire you. And then you can

0:21:30.320 --> 0:21:32.919
<v Speaker 2>tell your boss all day long, I swerve to avoid

0:21:32.960 --> 0:21:35.240
<v Speaker 2>a truck, But your boss doesn't get to keep you

0:21:36.040 --> 0:21:39.359
<v Speaker 2>on the payroll if Amazon says that they're not allowed

0:21:39.400 --> 0:21:42.240
<v Speaker 2>to and Amazon makes that determination based on their own

0:21:42.280 --> 0:21:43.040
<v Speaker 2>internal logic.

0:21:44.040 --> 0:21:48.080
<v Speaker 1>Unpack this idea of Amazon telling the DSP to fire

0:21:48.119 --> 0:21:49.600
<v Speaker 1>the driver, and the driver is say, why don't you

0:21:49.600 --> 0:21:52.399
<v Speaker 1>review the well, you know, the video footage and the

0:21:52.480 --> 0:21:55.200
<v Speaker 1>DSP saying, well, even if we could do that, it

0:21:55.200 --> 0:21:59.120
<v Speaker 1>wouldn't change our decision. I mean, how is this being exactive?

0:21:59.160 --> 0:22:03.479
<v Speaker 1>Because the Amazon worker ethnography stuff is haunting, but has

0:22:03.600 --> 0:22:09.160
<v Speaker 1>been preceded for sure the AI error? Right, Like, what's

0:22:09.320 --> 0:22:12.760
<v Speaker 1>what's being accelerated by AI? In what you're describing here?

0:22:13.320 --> 0:22:14.560
<v Speaker 2>You know you've hit on one of the points that

0:22:14.600 --> 0:22:16.400
<v Speaker 2>I wanted to make, which is that we can understand

0:22:16.560 --> 0:22:19.920
<v Speaker 2>the problems of AI and also the potential of AI,

0:22:20.359 --> 0:22:22.879
<v Speaker 2>both as being in a lineage and not being with

0:22:23.040 --> 0:22:25.760
<v Speaker 2>earlier phenomena. I'm firmly the belief that AI is a

0:22:25.800 --> 0:22:31.000
<v Speaker 2>normal technology and not extraordinary, neither extraordinarily evil nor extraordinarily amazing.

0:22:31.080 --> 0:22:34.480
<v Speaker 2>It's just a new technology, and it has all the

0:22:34.520 --> 0:22:37.639
<v Speaker 2>potential and all the problems that technologies have. The bubble

0:22:37.720 --> 0:22:42.200
<v Speaker 2>is extraordinary only because of its scale. And so there

0:22:42.280 --> 0:22:46.200
<v Speaker 2>has been so much well publicized conduct by firms that

0:22:46.320 --> 0:22:49.800
<v Speaker 2>have made workers redundant or limited how workers worked and

0:22:49.920 --> 0:22:54.159
<v Speaker 2>insisted that they work alongside of output from bots with

0:22:54.480 --> 0:22:58.400
<v Speaker 2>predictably disastrous results, right like, so not like it. It's

0:22:59.320 --> 0:23:01.280
<v Speaker 2>the only way you could be surprised is if you

0:23:01.359 --> 0:23:04.000
<v Speaker 2>were deliberately not listening to people who are warning you

0:23:04.080 --> 0:23:07.600
<v Speaker 2>why you shouldn't do it. And that is a feature

0:23:07.600 --> 0:23:09.399
<v Speaker 2>of the bubble, right, That's a feature first of all

0:23:09.720 --> 0:23:13.800
<v Speaker 2>of leaders themselves just being gripped by FOMO and being insecure,

0:23:14.160 --> 0:23:17.160
<v Speaker 2>but also the fact that investors are quite excited by

0:23:18.080 --> 0:23:23.160
<v Speaker 2>news that a firm has added AI to its operations,

0:23:23.760 --> 0:23:27.760
<v Speaker 2>and so there's maybe even a rational basis for harming

0:23:27.840 --> 0:23:30.840
<v Speaker 2>the firm's outputs in order to produce a narrative that's

0:23:30.920 --> 0:23:34.160
<v Speaker 2>friendly to investors. And it's one of those things where

0:23:34.600 --> 0:23:37.720
<v Speaker 2>we were told that if only we made top executives

0:23:37.760 --> 0:23:40.480
<v Speaker 2>shareholders of the firm, they would be incentivized to do

0:23:40.600 --> 0:23:42.960
<v Speaker 2>what's best for the firm. It actually turns out that

0:23:43.040 --> 0:23:45.200
<v Speaker 2>what's best for the firm might involve some short term

0:23:45.280 --> 0:23:47.840
<v Speaker 2>pain to the share price. But if your net worth

0:23:47.920 --> 0:23:49.800
<v Speaker 2>is tied up and shares in the firm you work for,

0:23:50.160 --> 0:23:55.200
<v Speaker 2>then you become as short term as the most nimble,

0:23:55.280 --> 0:23:57.840
<v Speaker 2>footloose hedge fund guy who has taken a position for

0:23:57.960 --> 0:24:00.200
<v Speaker 2>three weeks and is going to be out again and

0:24:00.320 --> 0:24:01.600
<v Speaker 2>on the road and never look back.

0:24:02.440 --> 0:24:06.480
<v Speaker 1>You also talk about sort of how the harm of

0:24:06.640 --> 0:24:11.120
<v Speaker 1>technology percolates. You said you have to find people without

0:24:11.160 --> 0:24:14.320
<v Speaker 1>social power and you grind down the rough edges on

0:24:14.400 --> 0:24:18.160
<v Speaker 1>their bodies, which is haunting phrase, But then it goes

0:24:18.240 --> 0:24:22.880
<v Speaker 1>to you in the end that metastasizes. And you've also

0:24:22.960 --> 0:24:25.000
<v Speaker 1>said for AI to be valuable, it has to replace

0:24:25.680 --> 0:24:28.240
<v Speaker 1>high wage workers. Talk about both of those ideas.

0:24:28.880 --> 0:24:31.480
<v Speaker 2>Yeah, so you're describing something I call the shitty technology

0:24:31.520 --> 0:24:34.320
<v Speaker 2>adoption curve, which is basically, when you've got it, when

0:24:34.359 --> 0:24:36.359
<v Speaker 2>you've got something you want to do that's terrible and

0:24:36.520 --> 0:24:39.480
<v Speaker 2>hurts the people who use it. If you make me

0:24:39.680 --> 0:24:42.640
<v Speaker 2>the first person who uses it, unlike a mouthy, affluent

0:24:42.720 --> 0:24:44.800
<v Speaker 2>white guy who speaks English as a native language and

0:24:44.920 --> 0:24:48.080
<v Speaker 2>has a giant platform, and it will be hard for

0:24:48.200 --> 0:24:50.720
<v Speaker 2>you to deploy it. But if you start with people

0:24:50.800 --> 0:24:54.600
<v Speaker 2>who don't have social capital, who no one listens to,

0:24:54.840 --> 0:24:58.320
<v Speaker 2>and who can't say no, you can both normalize the

0:24:58.400 --> 0:25:02.640
<v Speaker 2>technology but also sand down the things that people find

0:25:02.680 --> 0:25:05.480
<v Speaker 2>most odious about it. And so you know, if you

0:25:05.600 --> 0:25:07.560
<v Speaker 2>think about an example, here would be the way that

0:25:07.640 --> 0:25:12.639
<v Speaker 2>algorithmic wage discrimination works. So the first really widespread use

0:25:12.640 --> 0:25:16.400
<v Speaker 2>of algorithm wage discrimination was at uber, where they were

0:25:16.680 --> 0:25:20.080
<v Speaker 2>making inferences about the economic desperation of drivers based on

0:25:20.359 --> 0:25:22.440
<v Speaker 2>whether or not they signed on to take rides that

0:25:22.680 --> 0:25:26.200
<v Speaker 2>were bad deals, right, whether they poorly compensated, and then

0:25:26.600 --> 0:25:30.320
<v Speaker 2>the drivers who took poorly compensated rides were offered progressively

0:25:30.359 --> 0:25:33.919
<v Speaker 2>lower compensation. Right, the algorithm is seeking the floor at

0:25:33.960 --> 0:25:37.040
<v Speaker 2>which they'll pay. And so you know uber drivers, we

0:25:37.160 --> 0:25:39.880
<v Speaker 2>call them unskilled. I don't think that's fair, but they're

0:25:39.920 --> 0:25:45.440
<v Speaker 2>certainly not professionally certified workers. But Katie Wells, again the

0:25:45.840 --> 0:25:48.320
<v Speaker 2>woman who's done all this work on algorithmic wage discrimination

0:25:48.560 --> 0:25:53.320
<v Speaker 2>and algorithm management, has written about how nurses are now

0:25:53.880 --> 0:25:57.879
<v Speaker 2>experiencing this. So you know, hospitals in the US preferentially

0:25:57.920 --> 0:26:01.480
<v Speaker 2>higher nurses as contractors because that allows them to do

0:26:01.680 --> 0:26:04.000
<v Speaker 2>union avoidance. And it used to be that you would

0:26:04.080 --> 0:26:06.240
<v Speaker 2>hire a contract nurse through a body shop, through a

0:26:06.280 --> 0:26:08.720
<v Speaker 2>staffing agency in town, and there'd be three or four

0:26:08.920 --> 0:26:12.159
<v Speaker 2>or maybe one or two. And now there's just four apps,

0:26:12.480 --> 0:26:15.800
<v Speaker 2>and they operate nationally, and they all advertise themselves as

0:26:15.800 --> 0:26:18.960
<v Speaker 2>an uber for nursing, and at least two of them,

0:26:19.280 --> 0:26:21.960
<v Speaker 2>if not all of them, before they offer a shift

0:26:22.040 --> 0:26:26.040
<v Speaker 2>to a nurse, look up the nurse's credit history and

0:26:26.240 --> 0:26:29.240
<v Speaker 2>they make inferences about the economic desperation about the nurse

0:26:29.240 --> 0:26:31.040
<v Speaker 2>based on how much credit card debt they're carrying and

0:26:31.080 --> 0:26:34.440
<v Speaker 2>whether it's delinquent, and they offer a lower wage based

0:26:34.480 --> 0:26:38.320
<v Speaker 2>on that. So they extract a desperation premium from nurses

0:26:38.400 --> 0:26:40.880
<v Speaker 2>before they're offered a shift. And so you can see

0:26:40.880 --> 0:26:44.080
<v Speaker 2>how this starts with Uber drivers, who, if they're not

0:26:44.200 --> 0:26:46.240
<v Speaker 2>unskilled at least don't require anything more than a car

0:26:46.320 --> 0:26:49.520
<v Speaker 2>and a driving license to get started with Uber, and

0:26:49.640 --> 0:26:51.760
<v Speaker 2>goes to nurses who are trained for several years and

0:26:51.840 --> 0:26:54.920
<v Speaker 2>have to maintain professional licensure in order to do their job.

0:26:55.080 --> 0:26:56.680
<v Speaker 2>And you could imagine that that's going to come for

0:26:56.760 --> 0:27:01.359
<v Speaker 2>other kinds of workers too. And so, you know, if

0:27:01.440 --> 0:27:04.080
<v Speaker 2>you want to know what the future looks like, I'm

0:27:04.080 --> 0:27:05.560
<v Speaker 2>a science fiction writer. I don't know that I can

0:27:05.640 --> 0:27:06.840
<v Speaker 2>predict it. But if you want to know what it's

0:27:06.920 --> 0:27:11.320
<v Speaker 2>leading indicators are, look to the terrible things that are

0:27:11.359 --> 0:27:13.800
<v Speaker 2>being done to people with less social capital as you.

0:27:14.200 --> 0:27:16.200
<v Speaker 2>Because if they're profitable to do to people with less

0:27:16.200 --> 0:27:18.360
<v Speaker 2>social capitalis you, They'll be even more profitable if they're

0:27:18.400 --> 0:27:20.280
<v Speaker 2>done to you. And someone is going to get the

0:27:20.320 --> 0:27:21.680
<v Speaker 2>idea of trying to do it now, whether or not

0:27:21.720 --> 0:27:25.440
<v Speaker 2>they're successful is something that's socially determined, not inevitable, but

0:27:25.600 --> 0:27:28.080
<v Speaker 2>you should imagine that it's going to happen, you know.

0:27:28.320 --> 0:27:30.119
<v Speaker 2>William Gibson said, the future is here is just not

0:27:30.240 --> 0:27:32.399
<v Speaker 2>evenly distributed. If you want to find out where the

0:27:32.440 --> 0:27:34.960
<v Speaker 2>worst aspects of the future are pulling up very thick

0:27:35.040 --> 0:27:37.760
<v Speaker 2>and on the ground, look at Amazon warehouse workers and

0:27:37.880 --> 0:27:42.040
<v Speaker 2>Uber drivers and immigrants and people in ice detention and

0:27:42.960 --> 0:27:45.200
<v Speaker 2>kids and so on. That's where it's all headed.

0:27:45.440 --> 0:27:47.480
<v Speaker 1>And Gibson also said, as I learned from reading the

0:27:47.520 --> 0:27:50.000
<v Speaker 1>introduction to a book, the street finds its own use

0:27:50.119 --> 0:27:53.840
<v Speaker 1>for things. Yeah, I talk about the anti inevitable. Is

0:27:54.080 --> 0:27:55.879
<v Speaker 1>this where politics comes in. I might listen to you

0:27:56.040 --> 0:28:00.240
<v Speaker 1>and as recline with Tim Woo and getting into you know,

0:28:00.359 --> 0:28:04.760
<v Speaker 1>some some fairly detailed policy discussions or policy solutions. But

0:28:05.040 --> 0:28:07.359
<v Speaker 1>is policy and regulation the antidote to all of this?

0:28:08.160 --> 0:28:11.560
<v Speaker 2>Well, the regulation sets the contours on which markets operate.

0:28:12.320 --> 0:28:14.440
<v Speaker 2>I will confess that I don't think markets are the

0:28:14.520 --> 0:28:17.840
<v Speaker 2>only or necessarily the best way to solve our allocation problems.

0:28:17.880 --> 0:28:21.480
<v Speaker 2>But you know, the term free market, as first coined

0:28:21.640 --> 0:28:23.959
<v Speaker 2>or popularized at least by David Ricardo, did not mean

0:28:24.000 --> 0:28:27.040
<v Speaker 2>a market free from regulation. I meant a market free

0:28:27.080 --> 0:28:29.920
<v Speaker 2>from rents, right, A meant a market where factors of

0:28:30.000 --> 0:28:33.920
<v Speaker 2>production were freely traded and not owned by financiers. And

0:28:34.040 --> 0:28:35.600
<v Speaker 2>so if you wanted to make something, you didn't have

0:28:35.680 --> 0:28:37.240
<v Speaker 2>to go rent it. You could just acquire it on

0:28:37.320 --> 0:28:40.120
<v Speaker 2>the market or buy it, or another firm would sell

0:28:40.160 --> 0:28:42.240
<v Speaker 2>it to you that was doing something productive with it.

0:28:42.880 --> 0:28:45.080
<v Speaker 2>So it's basically the end of landlords. That's that's what

0:28:45.160 --> 0:28:47.440
<v Speaker 2>a free market was, whether that was landlords for ideas

0:28:47.480 --> 0:28:50.280
<v Speaker 2>in the form of patents or landlords for property or

0:28:50.400 --> 0:28:52.640
<v Speaker 2>what have you. So that's the origin of the idea

0:28:52.640 --> 0:28:57.160
<v Speaker 2>of a free market. And so every market, whether it's

0:28:57.200 --> 0:28:59.440
<v Speaker 2>the markets that we call heavily regulator to the markets

0:28:59.480 --> 0:29:03.080
<v Speaker 2>that we call regulated, is determined by regulation, by what

0:29:03.200 --> 0:29:05.920
<v Speaker 2>we allow firms to do, by what we prohibit from firms,

0:29:06.520 --> 0:29:10.640
<v Speaker 2>and by the extent to which firm's conduct can be

0:29:11.280 --> 0:29:14.960
<v Speaker 2>practically speaking policed. You know, it's very hard for the

0:29:15.040 --> 0:29:17.719
<v Speaker 2>referee to ensure a fair game if the players are

0:29:17.760 --> 0:29:20.480
<v Speaker 2>more powerful than the ref What do you do with that?

0:29:20.640 --> 0:29:24.280
<v Speaker 1>I guess because like it's tempting to ground these conversations

0:29:24.400 --> 0:29:28.080
<v Speaker 1>in like AI and technology and big technology, but they

0:29:28.160 --> 0:29:30.960
<v Speaker 1>sort of the set of problems you describe and we're

0:29:31.000 --> 0:29:35.600
<v Speaker 1>talking about are problems of how society is organized by

0:29:35.640 --> 0:29:39.240
<v Speaker 1>government and what role government plays as power broken between

0:29:39.480 --> 0:29:41.960
<v Speaker 1>citizens and organizations.

0:29:42.040 --> 0:29:44.800
<v Speaker 2>Right, it really depends on which aspect of AI we're

0:29:44.840 --> 0:29:46.840
<v Speaker 2>talking about, Like if we're talking about the question of

0:29:46.880 --> 0:29:49.720
<v Speaker 2>AI and creative labor, I don't think copyright solves this.

0:29:50.480 --> 0:29:53.360
<v Speaker 2>We keep expanding copyright and then we discover that in

0:29:53.440 --> 0:29:56.040
<v Speaker 2>a market where all creative workers have to sell their

0:29:56.040 --> 0:29:58.360
<v Speaker 2>work through a handful of firms, you know, five publishers

0:29:58.400 --> 0:30:00.920
<v Speaker 2>and four studios and three labels, two companies that do

0:30:01.040 --> 0:30:03.840
<v Speaker 2>the apps, and one company does the ebooks and audiobooks,

0:30:03.880 --> 0:30:05.560
<v Speaker 2>it doesn't matter how many rights we have, we just

0:30:05.640 --> 0:30:08.160
<v Speaker 2>bargain them away. Right. It's like giving bulliked school kids

0:30:08.200 --> 0:30:10.120
<v Speaker 2>extra lunch money. It just doesn't matter how much you

0:30:10.160 --> 0:30:12.360
<v Speaker 2>give them. They don't get lunch. But we do have

0:30:12.720 --> 0:30:16.120
<v Speaker 2>answers to this right that, we've seen successful gambits by

0:30:16.160 --> 0:30:20.000
<v Speaker 2>creative workers to resist using AI to erode their wages

0:30:20.040 --> 0:30:22.760
<v Speaker 2>and working conditions. The one group of workers who did

0:30:22.800 --> 0:30:26.160
<v Speaker 2>it most successfully was the screenwriters. And the big difference

0:30:26.200 --> 0:30:28.960
<v Speaker 2>between the screenwriters and every other kind of worker except

0:30:29.000 --> 0:30:32.120
<v Speaker 2>for other Hollywood workers is that they are allowed to

0:30:32.200 --> 0:30:35.400
<v Speaker 2>do sectoral bargaining, which was outlawed in the Taft Hartley

0:30:35.400 --> 0:30:38.440
<v Speaker 2>Act of nineteen forty seven. Which sectoral bargaining is when

0:30:38.520 --> 0:30:41.320
<v Speaker 2>all the workers in a sector, like everyone who works

0:30:41.320 --> 0:30:43.720
<v Speaker 2>at a fast food restaurant, is organized under a union,

0:30:43.760 --> 0:30:46.440
<v Speaker 2>and every fast food owner is bound by the contract

0:30:46.560 --> 0:30:51.120
<v Speaker 2>with those workers. So, you know, if you see creative

0:30:51.120 --> 0:30:54.560
<v Speaker 2>workers kind of at a crossroads, and on one fork

0:30:54.960 --> 0:30:56.880
<v Speaker 2>they can argue for more copyright, which is the thing

0:30:56.920 --> 0:30:59.200
<v Speaker 2>their bosses want and no other work in America gives

0:30:59.200 --> 0:31:02.000
<v Speaker 2>a shit about. And on the other fork is sectoral bargaining.

0:31:02.040 --> 0:31:03.960
<v Speaker 2>I think their bosses would hate and every other worker

0:31:04.000 --> 0:31:06.120
<v Speaker 2>in America would benefit from. It seems to me like

0:31:06.200 --> 0:31:08.400
<v Speaker 2>that it's just you could just do basy and reasoning

0:31:08.520 --> 0:31:11.560
<v Speaker 2>without knowing a single thing about the specifics of these policies.

0:31:12.000 --> 0:31:14.160
<v Speaker 2>You know, broadly speaking, you're on the right side of

0:31:14.280 --> 0:31:16.240
<v Speaker 2>history when you're on the same side as all the

0:31:16.320 --> 0:31:19.080
<v Speaker 2>workers and the opposite side is your boss if you

0:31:19.200 --> 0:31:21.840
<v Speaker 2>care about labor rights. When we're talking about data centers,

0:31:21.920 --> 0:31:26.080
<v Speaker 2>I mean, I think it's not hard to imagine a

0:31:26.120 --> 0:31:28.560
<v Speaker 2>regulatory regime that would make data centers better, like, we

0:31:28.640 --> 0:31:31.560
<v Speaker 2>could have rules about the carbon emissions of them. We

0:31:31.640 --> 0:31:35.200
<v Speaker 2>could have democratic determination about their water usage and their

0:31:35.360 --> 0:31:38.280
<v Speaker 2>energy usage and the noise that they create. We could

0:31:38.440 --> 0:31:41.920
<v Speaker 2>have very very strict limits or possibly a total prohibition

0:31:42.520 --> 0:31:45.480
<v Speaker 2>on the use of eminent domain to expropriate farmers and

0:31:45.560 --> 0:31:47.480
<v Speaker 2>other people who have large tracks of land to build

0:31:47.560 --> 0:31:49.440
<v Speaker 2>data centers. I mean, all of those things are like,

0:31:49.520 --> 0:31:52.200
<v Speaker 2>none of them are new, they're just like again back

0:31:52.240 --> 0:31:55.120
<v Speaker 2>to AI as a normal technology. This does not require

0:31:55.320 --> 0:31:59.520
<v Speaker 2>extraordinary new regulations to stop people from you know, polluting

0:31:59.640 --> 0:32:04.920
<v Speaker 2>and just uptive job sites near your home in ways

0:32:05.000 --> 0:32:07.320
<v Speaker 2>that make your quality of life worse, and that also

0:32:07.440 --> 0:32:09.640
<v Speaker 2>sometimes results in your home being stolen from you through

0:32:09.680 --> 0:32:12.280
<v Speaker 2>an eminent domain. And if we're worried about the way

0:32:12.360 --> 0:32:14.960
<v Speaker 2>that local councils are being uveiled into doing this, we

0:32:15.000 --> 0:32:18.280
<v Speaker 2>could also have rules about like taking bribes, which is

0:32:18.360 --> 0:32:21.960
<v Speaker 2>basically how they're getting these regulatory things through. It doesn't

0:32:22.000 --> 0:32:26.360
<v Speaker 2>require anything extraordinary to make that happen. In terms of

0:32:26.800 --> 0:32:30.360
<v Speaker 2>the decision outcomes right where we're using AI to decide

0:32:30.400 --> 0:32:33.400
<v Speaker 2>who gets parole or who gets bond in Gaza, or

0:32:33.960 --> 0:32:37.560
<v Speaker 2>which people DOGE is going to fire or which people

0:32:37.640 --> 0:32:39.440
<v Speaker 2>ice are going to round up or shoot in the

0:32:39.480 --> 0:32:42.000
<v Speaker 2>face or send to a concentration camp in El Salvador.

0:32:42.400 --> 0:32:44.400
<v Speaker 2>I mean, we can just say those things should be illegal,

0:32:44.920 --> 0:32:46.760
<v Speaker 2>and we can say that if someone needs to be fired,

0:32:46.960 --> 0:32:49.040
<v Speaker 2>that there should be a normal procedure for firing them,

0:32:49.040 --> 0:32:50.760
<v Speaker 2>and that you should have to show evidence and so on,

0:32:50.920 --> 0:32:53.160
<v Speaker 2>you have to fire them for cause, and we could

0:32:53.200 --> 0:32:56.840
<v Speaker 2>honor the existing union contracts that federal workers have. Again, like,

0:32:56.920 --> 0:32:59.200
<v Speaker 2>it doesn't require anything new. It just requires that we

0:32:59.760 --> 0:33:02.560
<v Speaker 2>not treat AI as an extraordinary technology that when it

0:33:02.600 --> 0:33:04.960
<v Speaker 2>says fire someone, we get to ignore all the rules

0:33:05.400 --> 0:33:06.840
<v Speaker 2>about when you can fire someone.

0:33:07.720 --> 0:33:12.440
<v Speaker 1>I mean, I guess the one politician who has put

0:33:12.640 --> 0:33:15.240
<v Speaker 1>forth the kind of national platform of you know, the

0:33:15.320 --> 0:33:19.120
<v Speaker 1>relationship between government technology is Bernie Sanders with his AI

0:33:19.320 --> 0:33:22.480
<v Speaker 1>sovereign Wealth fund, which interesting he Trump is also a

0:33:22.640 --> 0:33:25.880
<v Speaker 1>fan of of, as is Simultman. So there's something something

0:33:25.920 --> 0:33:27.960
<v Speaker 1>there which maybe should tasty.

0:33:28.080 --> 0:33:30.600
<v Speaker 2>But I mean, look, if AI were profitable, it would

0:33:30.600 --> 0:33:32.600
<v Speaker 2>be a great target for a sovereign wealth fund. I

0:33:32.720 --> 0:33:34.760
<v Speaker 2>don't know why we would want the money losing this

0:33:34.920 --> 0:33:37.240
<v Speaker 2>thing in the world to be in public ownership unless

0:33:37.360 --> 0:33:39.360
<v Speaker 2>we thought it was a public good, in which case

0:33:39.400 --> 0:33:40.840
<v Speaker 2>it might make sense. I mean, there's a sense in

0:33:40.840 --> 0:33:43.040
<v Speaker 2>which schools don't make money. It would be weird if

0:33:43.080 --> 0:33:46.960
<v Speaker 2>schools made money, you know, elementary schools, public schools. But

0:33:47.320 --> 0:33:49.640
<v Speaker 2>I don't think that's what Bernie means. I think he means,

0:33:49.760 --> 0:33:51.800
<v Speaker 2>I think these are going to throw off extraordinary amounts

0:33:51.800 --> 0:33:54.200
<v Speaker 2>of profit. I just think he's wrong. I think he's mistaken.

0:33:54.640 --> 0:33:57.080
<v Speaker 2>And that's getting back to being a better AI critic.

0:33:57.160 --> 0:33:59.400
<v Speaker 2>I think being a better AI critic means not accepting

0:33:59.600 --> 0:34:03.400
<v Speaker 2>the facially the claims that AI is very valuable and

0:34:03.480 --> 0:34:07.640
<v Speaker 2>profitable or will be shortly and requiring at least ordinary

0:34:07.720 --> 0:34:10.520
<v Speaker 2>evidence for such an extraordinary claim, for a way that

0:34:10.600 --> 0:34:13.279
<v Speaker 2>a company that can't raise the price of its one

0:34:13.320 --> 0:34:15.960
<v Speaker 2>hundred dollar bills from one dollars to five dollars without

0:34:15.960 --> 0:34:19.000
<v Speaker 2>losing most of its customers will someday be profitable.

0:34:19.520 --> 0:34:22.319
<v Speaker 1>You close the book with this line. The future can

0:34:22.440 --> 0:34:25.319
<v Speaker 1>be ours if we never stop remembering that the most

0:34:25.400 --> 0:34:28.879
<v Speaker 1>important fact about technology isn't what it does, it's who

0:34:28.920 --> 0:34:31.000
<v Speaker 1>it does it for and who it does it to.

0:34:32.000 --> 0:34:34.000
<v Speaker 1>What do we do with that? What should our listeners?

0:34:34.600 --> 0:34:38.440
<v Speaker 1>What should they do this afternoon tomorrow? Having heard this conversation,

0:34:39.560 --> 0:34:40.680
<v Speaker 1>you have to join a polity.

0:34:40.880 --> 0:34:44.279
<v Speaker 2>I wish, because hell truly is other people. I wish

0:34:44.360 --> 0:34:46.359
<v Speaker 2>we could all be as solive cystic as the AI

0:34:46.480 --> 0:34:48.279
<v Speaker 2>bros want us to be, and we could just solve

0:34:48.360 --> 0:34:51.040
<v Speaker 2>things with our individual action. We could just go like

0:34:51.160 --> 0:34:53.600
<v Speaker 2>shop our way out of a monopoly and recycle our

0:34:53.640 --> 0:34:56.759
<v Speaker 2>way out of the wildfires and so on. Alas that

0:34:56.880 --> 0:35:01.000
<v Speaker 2>is not possible. Systemic problems require system solutions, and the

0:35:01.080 --> 0:35:03.160
<v Speaker 2>way that you make systemic solutions is being part of

0:35:03.200 --> 0:35:06.480
<v Speaker 2>a polity. And that would mean joining the Electronic Frontier Foundation,

0:35:06.600 --> 0:35:10.520
<v Speaker 2>getting involved in local politics, getting involved with unions and

0:35:10.640 --> 0:35:12.680
<v Speaker 2>your job site. And if there isn't one and you

0:35:12.800 --> 0:35:15.839
<v Speaker 2>work in tech, look up Tech Solidarity and the Tech

0:35:15.880 --> 0:35:19.840
<v Speaker 2>Workers Coalition. You know, that's that's how you make a difference,

0:35:19.920 --> 0:35:22.960
<v Speaker 2>right as being part of a group. And I'm not

0:35:23.040 --> 0:35:25.200
<v Speaker 2>saying that because I think it's easier fun to work

0:35:25.200 --> 0:35:28.000
<v Speaker 2>in groups. It can be, but like it is just

0:35:28.560 --> 0:35:31.680
<v Speaker 2>outrageous how hard it is to convince other people that

0:35:31.800 --> 0:35:34.719
<v Speaker 2>you are right. You know, I mean, as much as

0:35:34.760 --> 0:35:37.080
<v Speaker 2>I insist on it it as an Agelino, people just

0:35:37.200 --> 0:35:38.680
<v Speaker 2>will not listen to me when I say when I

0:35:38.800 --> 0:35:40.719
<v Speaker 2>need to get on the five. That's when everyone else

0:35:40.719 --> 0:35:43.239
<v Speaker 2>should get the hell off the five. But you know

0:35:43.840 --> 0:35:46.400
<v Speaker 2>the fact is that anytime you want to do something superhuman,

0:35:46.520 --> 0:35:49.480
<v Speaker 2>something that exceeds the capability of one person, you need

0:35:49.560 --> 0:35:51.000
<v Speaker 2>to find a way to work with someone else to

0:35:51.040 --> 0:35:53.239
<v Speaker 2>do something that two or more people can do. And

0:35:53.360 --> 0:35:54.680
<v Speaker 2>the only way to do that is to be part

0:35:54.680 --> 0:36:00.399
<v Speaker 2>of a polity ry. Doctor.

0:36:00.400 --> 0:36:13.400
<v Speaker 1>Oh, thank you, thank you for tech Stuff. I'm oz Veloscian.

0:36:13.440 --> 0:36:16.320
<v Speaker 1>This episode was produced by Eliza Dennis and Melissa Slaughter.

0:36:16.760 --> 0:36:19.640
<v Speaker 1>It was executive produced by me Julian Nutter and Kate

0:36:19.680 --> 0:36:24.239
<v Speaker 1>Osborne for Kaleidoscope and Katrin Norvel for iHeart Podcasts. Jack

0:36:24.320 --> 0:36:27.160
<v Speaker 1>Insley mixed this episode and Kyle Murdoch wrote out theme song.

0:36:27.960 --> 0:36:30.080
<v Speaker 1>Please do rate and review the show where ever you listen,

0:36:30.480 --> 0:36:33.000
<v Speaker 1>and reach out to us at tech Stuff podcast at

0:36:33.040 --> 0:36:33.759
<v Speaker 1>gmail dot com.