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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. This week on the

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Speaker 1: podcast a special bonus episode. Corey Doctorow has a new

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Speaker 1: book out entitled Ingentification, all about the decay of digital platforms.

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Speaker 1: I've been reading Corey for a long time, both at

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Speaker 1: Boing Buying and elsewhere. I'm a big fan of his

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Speaker 1: takes on technology. I thought this conversation was really intriguing,

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Speaker 1: and I think you will also with no further ado,

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Speaker 1: my conversation with technology author Corey doctor Corey doctor O,

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Speaker 1: Welcome to Bloomberg.

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Speaker 2: Thank you very much. Berry. It's a great pleasure to

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Speaker 2: be here.

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Speaker 1: It's a pleasure to have you. So you Before we

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Speaker 1: get into the book, I have to just go into

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Speaker 1: a little bit about your background. I think of you

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Speaker 1: as a writer first, but you have such a multifaceted career.

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Speaker 1: How do you describe what you do?

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Speaker 2: Well?

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Speaker 3: You know, it's funny, before I became a British citizen,

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Speaker 3: when I was living in London, every time I landed,

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Speaker 3: I had to fill in a landing card with my

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Speaker 3: occupation and just had this little like three quarter inch

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Speaker 3: blank and I would eventually just write in writer. But

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Speaker 3: you know, trying to explain to my grandmother when she

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Speaker 3: was alive. What I did for a living was always challenging.

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Speaker 3: I'm a writer, I'm an activist. I've worked for the

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Speaker 3: Electronic Frontier Foundation for nearly a quarter of a century.

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Speaker 2: Now.

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Speaker 3: It's a digital rights group that tries to make sure

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Speaker 3: that your human rights apply online and offline in these days,

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Speaker 3: that the Internet isn't taking away your human rights. Offline,

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Speaker 3: I write science fiction novels. I've written a couple of

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Speaker 3: dozen of those, won a bunch of awards, had New

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Speaker 3: York Times bestsellers.

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Speaker 2: And I'm a blogger.

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Speaker 3: As you say, I edited Boing Boing for nineteen years

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Speaker 3: and these days I have my own blog, Pluralistic dot net,

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Speaker 3: and I write about tech, policy, culture, science fiction, all

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Speaker 3: kinds of stuff.

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Speaker 1: So let's start with tech culture and EFF. What was

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Speaker 1: the first issue that got you interested in exploring digital

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Speaker 1: rights and just protecting user rights on the Internet.

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Speaker 3: Well, like a lot of EFF supporters, you know, I

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Speaker 3: got started reading about the stuff EFF was doing long

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Speaker 3: before I got involved with them.

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Speaker 2: So, you know, one of the big.

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Speaker 3: Cases that we got involved with very early almost and

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Speaker 3: then called Bernstein. So the NSA had classed encryption as

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Speaker 3: a munition and they said that civilians should not be

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Speaker 3: able to access working encryption. They had a kind of

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Speaker 3: weak form of encryption they called DEZ fifty. It was

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Speaker 3: the defense encryption standard with fifty bits of key, and

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Speaker 3: they said DEZ fifty is good enough for anyone.

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Speaker 2: The mafia won't.

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Speaker 3: Break it, our foreign adversaries won't break it. But you know,

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Speaker 3: the NSA can break it if they need to. And

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Speaker 3: we tried all kinds of things to say this was

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Speaker 3: a bad idea. One of our founders, John Gilmour, actually

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Speaker 3: built a computer called deep crack that could brute force

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Speaker 3: all of DEAs fifty and two and a half hours.

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Speaker 3: It cost a quarter of a million bucks and it's

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Speaker 3: actually in my office now because John got tired of

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Speaker 3: having it in his garage and no one cared. But

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Speaker 3: then we went to court representing a cryptographer grad student

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Speaker 3: at Berkeley called Daniel J. Bernstein, who had made an

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Speaker 3: encryption program that was stronger than des fifty, that was

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Speaker 3: as strong as modern encryption these days. You know, when

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Speaker 3: you take your distraction rectangle out of your pocket and

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Speaker 3: click it. In the instant it takes for that file

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Speaker 3: to land on the mass storage, it's encrypted, so well

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Speaker 3: that if every hydrogen atom in the universe were a

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Speaker 3: computer and it did nothing until the end of the universe,

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Speaker 3: but try and guess the key, you would run out

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Speaker 3: of universe before you ran into keys. So he makes

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Speaker 3: a working encryption, this kind of miraculous modern thing, the

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Speaker 3: thing that protects your bank transactions and the firmware updates

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Speaker 3: for your anti lock breaks, and you're a pacemaker and

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Speaker 3: all that other stuff that we want to keep secret

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Speaker 3: and secure. And we argued that he had a First

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Speaker 3: Amendment right to publish his source code, that source code

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Speaker 3: was a form of expressive speed each under the First Amendment.

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Speaker 3: We won in the district, we won at the appellate

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Speaker 3: division in the ninth Circuit. The NSA didn't want to

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Speaker 3: take their chances with the Supreme Court. And ever since then,

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Speaker 3: code has been speech and we have had the tools

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Speaker 3: to have secure communications.

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Speaker 1: So I recall you being very involved with Digital Rights

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Speaker 1: Management and Napster and Grockster, and there was a video

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Speaker 1: version of that.

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Speaker 2: There was a broadcast flag, right.

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Speaker 1: That's that's when I first realized, Oh, he's more than

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Speaker 1: just a curator, he's really very much an activist. You

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Speaker 1: started writing about surveillance and monopolies and information asymmetries. I

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Speaker 1: don't know, is it twenty twenty five years ago? Tell

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Speaker 1: us a little bit about that.

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Speaker 3: Well, I'm partly it's because I'm a science fiction writer,

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Speaker 3: and so as a science fiction writer, the thing that

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Speaker 3: I'm most preoccupied with is not what the gadgets do,

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Speaker 3: but who to gadgets.

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Speaker 2: Do them for?

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Speaker 3: And who to gadgets do them too. I think of

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Speaker 3: science fiction as a kind of inverse of this kind

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Speaker 3: of vulgar thing aturism that says there is no alternative.

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Speaker 3: You know, Margaret Thatcher used to say there is no alternative,

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Speaker 3: so often they called her Tina there is no alternative.

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Speaker 3: What she met was like, stop trying to think of

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Speaker 3: an alternative, right, And and you know, when you are

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Speaker 3: a technologist, and that's my background as a software developer,

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Speaker 3: and when you have that kind of science fiction imagination,

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Speaker 3: you look at the things that you're using, You're thinking,

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Speaker 3: why do we have to take the bad with the good?

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Speaker 2: Right?

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Speaker 3: Why is the product designer here delivering me a prefeast

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Speaker 3: menu that's full of a bunch of stuff that no

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Speaker 3: one would ever want to eat instead of just the

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Speaker 3: a la carte that has the things that I want.

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Speaker 3: And so I started to wonder why we couldn't, you know,

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Speaker 3: seize the means of computation, take the things that we

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Speaker 3: were using, and you know, make them work for us,

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Speaker 3: not for someone else. They sell you a printer that

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Speaker 3: only takes our third party inc. You modify the printer

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Speaker 3: so it takes generic ink. They sell you a phone

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Speaker 3: that only uses their apps. Store you modified so it

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Speaker 3: uses anyone's apps. They put you on the web and

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Speaker 3: they start spying on you. Well, you put a privacy blocker.

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Speaker 3: You know, more than half of all Internet users have

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Speaker 3: installed an ad blocker.

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Speaker 2: It's the largest consumer boycott in history.

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Speaker 1: Wow.

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Speaker 3: And it means that whenever a product manager sits down

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Speaker 3: to think about, like how invasive and obnoxious should our

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Speaker 3: ads be, they kind of have to contend with this

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Speaker 3: possibility that users will take it upon themselves to correct

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Speaker 3: the situation, to make a counter offer.

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Speaker 2: Right, my offer is I'm.

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Speaker 3: Going to show you this web page, but I'm going

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Speaker 3: to spy on you and bombard you with ads.

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Speaker 2: Your counter offer might be how about no? Right?

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Speaker 3: And so you know that's dangerous because if like making

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Speaker 3: your ads twenty percent more obnoxious makes forty percent of

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Speaker 3: your users put in an ad blocker. You don't get

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Speaker 3: money from them anymore, and no one ever goes back

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Speaker 3: to the search engine and types how do I start

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Speaker 3: seeing ads again? So that's that's a permanent thing. And

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Speaker 3: you know, one of the big changes and one of

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Speaker 3: the things that I've tracked over these these this quarter

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Speaker 3: century is the rise and rise of IP rules that

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Speaker 3: prohibit that kind of modification. So the biggest one being

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Speaker 3: something called anti circumvention law, which is law that just

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Speaker 3: says you can't modify something that's designed not to be modified.

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Speaker 2: In other words, of the.

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Speaker 1: Programmer, despite the fact that you paid for it and.

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Speaker 3: It's yours, you want to do something legal with it.

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Speaker 3: So if the programmer, basically when they're writing the code,

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Speaker 3: does equivalent of drawing a chalk dotted line around some

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Speaker 3: of the code and says like don't look in here

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Speaker 3: or change this, under laws like the Digital Millennium Copyright

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Speaker 3: Act of nineteen ninety eight, it becomes a felony to

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Speaker 3: change it, even for a lawful purpose. And so you know,

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Speaker 3: an app, it's just the web, but it has these

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Speaker 3: these these technical protection measures that make reverse engineering illegal.

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Speaker 3: So an app is just a website, you know, skinned

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Speaker 3: to the right eyep to make it a felony to

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Speaker 3: defend your privacy.

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Speaker 2: When you use it.

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Speaker 3: This is why you know, bosses are so horny to

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Speaker 3: make you use their apps and not their websites.

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Speaker 1: Right, right, So it's interesting because you lived in Europe,

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Speaker 1: and in particular in London for so long, it seems

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Speaker 1: like the Europeans have a much more user friendly perspective

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Speaker 1: on privacy rights and digital rights. How how far away

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Speaker 1: is the United States from if not the platonic ideal

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Speaker 1: just the way Europe does it? Or am I giving

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Speaker 1: them too much credit?

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Speaker 2: Well?

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Speaker 3: Look, I don't think it's necessarily because the Europeans are

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Speaker 3: better at regulation than the Americans. I think it has

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Speaker 3: a lot to do with the fact that the companies

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Speaker 3: that abuse us on the Internet are not called Nokia, Olivetti,

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Speaker 3: ericson Deutsche Telecom. Right, It's a lot easier to get

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Speaker 3: the political space to do evidence based policy when your

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Speaker 3: economy isn't so focused and controlled by a small number

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Speaker 3: of very dominant firms. That's just a rale politique here.

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Speaker 3: I think though, that something is changing in Europe, and

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Speaker 3: it has changed over the last few years, and it's

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Speaker 3: about to accelerate quite a lot, I believe.

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Speaker 2: So.

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Speaker 3: For a long time, the European approach to tech was

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Speaker 3: to try and make them behave themselves.

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Speaker 2: Right.

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Speaker 3: So, you know, Mark Zuckerberg has a platform with a

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Speaker 3: lot of abuse and hate speech and harassment. They say,

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Speaker 3: Mark Zuckerberg, you have to prevent that.

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Speaker 2: Right.

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Speaker 3: What they're saying to him is the problem isn't that

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Speaker 3: you have the power. The problem is how you wield

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Speaker 3: the power. We would like you to wield your power

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Speaker 3: more responsibly, and in fact, if you need more power

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Speaker 3: to do that, right, Because if you're going to stamp

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Speaker 3: out harassment on a platform, you have to know whatevery

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Speaker 3: user is doing and have the power to stop them.

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Speaker 3: So even if you need to arrogate more power to

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Speaker 3: yourself over your users, that's okay.

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Speaker 2: Just use the power in the way that we want.

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Speaker 3: It's kind of a constitutional monarchy, right, he is the

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Speaker 3: absolute ruler, but he suffers himself to be draped and

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Speaker 3: like gilded chains held by his courtiers.

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Speaker 2: Right.

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Speaker 3: In the last few years, the European Union has started

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Speaker 3: to regulate as though the problem was the power itself,

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Speaker 3: not that Mark Zuckerberg was bad at being the social

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Speaker 3: medias are for four billion people unelected with an office

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Speaker 3: for life, but rather that that office shouldn't exist, And

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Speaker 3: so they've started to impose things like interoperability requirements that

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Speaker 3: make it so that if you leave a social media

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Speaker 3: platform when you get somewhere else, Blue Sky masked it

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Speaker 3: on something that doesn't exist, because why would you capitalize

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Speaker 3: something when everyone's locked into Facebook or Twitter.

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Speaker 2: When you get there, you.

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Speaker 3: Should be able to see the messages posted by the

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Speaker 3: people you left behind. You should be able to have

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Speaker 3: discourse with them, be part of those communities in the

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Speaker 3: same way that like when you switch from you know,

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Speaker 3: Vota phone to T Mobile, you do some administrative work

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Speaker 3: and a few seconds later your phone number cuts over.

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Speaker 1: No, one doesn't seem to work that way. You used

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Speaker 1: to be able to drag your either the people you

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Speaker 1: were following or your own followers. Sure from Twitter to

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Speaker 1: Blue Sky that that those ais got.

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Speaker 2: Yeah, they made it a lot harder.

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Speaker 3: So it wasn't that you could drag them over, you

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Speaker 3: could find them, right And this was all cutting off

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Speaker 3: the This is what musted when he cut off the

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Speaker 3: API is he made it much harder to build those

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Speaker 3: migration tools, and so you know, the EU is like

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Speaker 3: focusing on those migration tools, and they're about to become

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Speaker 3: a lot more focused because of Trump's foreign policy. So

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Speaker 3: for more than twenty years, I have gone around the

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Speaker 3: world more than thirty countries on behalf of the FF

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Speaker 3: and talk to policy makers about what would make a

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Speaker 3: better Internet policy, things like improved interoperability rules, the right

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Speaker 3: to reverse engineer, modified bet are privacy rules. And what

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Speaker 3: they've said at every time is that, well, we'd love

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Speaker 3: to do that. It sounds very sensible, but the US

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Speaker 3: Trade Representative has made it very clear that if we

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Speaker 3: don't have policies that protect the rent extraction of American firms,

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Speaker 3: they're going to hit us with tariffs. Well, you know,

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Speaker 3: a happy liberation day, right if the guy.

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Speaker 1: Says this trade thing is two sided? Yeah, suggesting.

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Speaker 3: So if the guy says, do what I tell you're

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Speaker 3: going to burn your host down, you do what he

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Speaker 3: tells you, and he burns your host down.

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Speaker 2: Anyways, you're kind of a sucker if he keep doing

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Speaker 2: what he tells you to do.

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Speaker 3: And not only that, but Trump has made it so

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Speaker 3: clear that what we used to call American trading partners

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Speaker 3: are now America's rivals, right, and that that rivalry will

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Speaker 3: be pursued through the American tech giants.

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Speaker 2: You know, this is what we were told Huawei was

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Speaker 2: going to do to us.

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Speaker 3: Every accusation is a confession rights.

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Speaker 1: That's exactly right.

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Speaker 3: You know, when the International Criminal Court swore out a

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Speaker 3: complaining against Benjamin and Yahoo for genocide, Trump denounced this

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Speaker 3: and then Microsoft terminated his online accounts.

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Speaker 2: He lost his e email, he lost his.

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Speaker 3: Address book, he lost his calendar, and he lost the

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Speaker 3: working files of the International Criminal Court.

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Speaker 2: Well, this has lit a fire under Europe. Right.

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Speaker 3: They are now pursuing this thing they call Eurostack. There's

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Speaker 3: a lot of money for it, and they want to

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Speaker 3: replicate American tech stacks. They want to replicate the data centers,

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Speaker 3: they want to replicate the applications Google Docs and so

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Speaker 3: on and so on. The problem is, no one is

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Speaker 3: ever going to copy and paste a million documents from

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Speaker 3: their government ministry, one at a time, out of g

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Speaker 3: Docs and into a eurostack.

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Speaker 1: This sounds very much like Europe has a TikTok problem

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Speaker 1: the way the United States does. Only the issue is

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Speaker 1: American tech companies, not a Chinese social media network.

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Speaker 3: And Honestly, I don't think TikTok is doing what they

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Speaker 3: say they're doing, and if they are, the best way

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Speaker 3: to solve that is to just update American privacy law

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Speaker 3: because that's the problem. You know, the last time we

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Speaker 3: got a new privacy law in America, you may know this,

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Speaker 3: it was nineteen eighty eight. It was when Ronald Reagan

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Speaker 3: signed the Video Privacy Protection Act. It makes it a

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Speaker 3: crime for video store clerks to disclose your VHS rentals.

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Speaker 3: Everything else is fair game, right, Why is TikTok spying

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Speaker 3: on you? That's why I ticked it because we let

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Speaker 3: them right. But you know, in Europe, when they reach

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Speaker 3: this point where they're not gonna be able to migrate

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Speaker 3: from these old American services to these new European services,

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Speaker 3: they're going to have to start reinvigorating their reverse engineering

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Speaker 3: game and make it so that you can run headless

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Speaker 3: phones and the cloud that impersonate users and iterate through

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Speaker 3: the documents and move them over and do scraping or

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Speaker 3: all clients on device bridging, all this stuff that we

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Speaker 3: used to do.

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Speaker 2: All the time. Right, That was like ross Perot's.

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Speaker 3: Business, right, it was helping people move data between systems

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Speaker 3: that we used to do all the time. As they

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Speaker 3: would say in the Star Wars universe, this elegant weapon

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Speaker 3: from a more civilized age. They're gonna have to revive

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Speaker 3: it because right now it's like they've observed a giant

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Speaker 3: housing crisis in East Berlin, and so they built a

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Speaker 3: bunch of houses in West Berlin, and they're not thinking.

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Speaker 2: About how the people are going to move in.

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Speaker 3: They're gonna have to tear down the wall, right, And

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Speaker 3: so this is in some ways one of the most

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Speaker 3: amazing things to happen in digital rights in my whole career.

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Speaker 3: It's sort of analogous to what happened when Putin invaded Ukraine.

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Speaker 3: You know, there used to be all these structural reasons

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Speaker 3: that couldn't solarize Europe, right planning, permission, electrical and safety

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Speaker 3: codes and so on. All of a sudden, when you're

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Speaker 3: shivering in the dark, that stuff isn't so important. And

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Speaker 3: now Europe is ten years ahead of their solar transition plan, right.

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Speaker 3: I think that we're about to get this on a

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Speaker 3: global scale, not least because economically it makes so much sense.

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Speaker 3: You think about the extraction from these locked platforms right

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Speaker 3: in jet inc In jet ink is the most expensive

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Speaker 3: fluid you can buy as a civilian without taking a

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Speaker 3: special license. It would be cheaper to print your grocery

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Speaker 3: list with this semen of a Kentucky derby winning Stylly.

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Speaker 1: That's unbelievable.

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Speaker 3: And you know the only reason we don't have generic

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Speaker 3: ink in our printers is because it's against the law

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Speaker 3: to like make modifications to printer firmware so it doesn't

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Speaker 3: check for generic ink.

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Speaker 1: But you can buy your don't work.

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Speaker 3: Reliably, right, and the printer companies push non consensual updates

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Speaker 3: to your printer that shuts this down. And they've done

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Speaker 3: all kinds of sleazy things, like HP pushed an update

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Speaker 3: in March that was a security update that was like

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Speaker 3: a Manchurian candidate, a sleeper agent. It sat there until September,

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Speaker 3: didn't do anything, waited for all the parents to go

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Speaker 3: to Costco and buy back to school kits of generic inc.

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Speaker 3: And then it detonated and all that ink was useless. Right,

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Speaker 3: So they're trying to like send a message to America's parents,

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Speaker 3: don't buy generic inc. Ever, you never know when it's

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Speaker 3: going to stop working. They were like maximizing the pain.

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Speaker 1: Here unbelievable, absolutely unbelievable. So literally had to have a

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Speaker 1: conversation with the powers that be to figure out how

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Speaker 1: to say the title of your book, which ironically has

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Speaker 1: been named the word of the year in two separate

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Speaker 1: major three three I found two in.

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Speaker 2: My two dictionaries, but three countries, three countries.

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Speaker 1: Yeah, so let's talk about in shitification. How do you

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Speaker 1: define it sure in a way that we can broadcast

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Speaker 1: without running a foul of the of.

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Speaker 3: Course, well, you know, working for the Electronic Frontier Foundation,

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Speaker 3: as I have for so long, my job has really

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Speaker 3: been about trying to raise the salience and the urgency

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Speaker 3: of these digital issues that are very abstract, very technical.

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Speaker 3: You know, they eventually become very concrete, but it's when

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Speaker 3: your house is on fire. You kind of want people

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Speaker 3: to get active before then. And so that's a game

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Speaker 3: of coming up with similesm metaphors and framing devices, funny words,

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Speaker 3: parables and so on. And the latest of these is

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Speaker 3: this one in shitification. And in shitification is both observation

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Speaker 3: about how things go bad and also a theory about

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Speaker 3: why they're going bad. And so the observation is quite straightforward,

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Speaker 3: and in the first phase you have firms that are

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Speaker 3: good to their end users, but find a way to

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Speaker 3: lock those users in. In the second phase, they make

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Speaker 3: things worse for those end users, and they rely on

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Speaker 3: the lock in to stop those end users from departing,

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Speaker 3: and they make things good for business customers. In the

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Speaker 3: third phase, they lock in those business customers and extract

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Speaker 3: all of their surplus as well. They leave behind the

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Speaker 3: kind of meanest homeopathic residue needed to keep users locked

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Speaker 3: to the platform, businesses locked to the users, and they

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Speaker 3: extract everything for themselves and they turn into a palocrap.

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Speaker 3: That's the kind of observational end of it. But the

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Speaker 3: question I want to interrogate is why is it happening now?

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Speaker 2: Right? Because we didn't invent greed in the middle of

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Speaker 2: the last decade.

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Speaker 3: The people running these companies are often the same people

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Speaker 3: around them from day one. You know, Mark Zuckerberg was

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Speaker 3: running Facebook from his Harvard dorm to today, and he

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Speaker 3: owns the majority of the voting shares. Google actually got

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Speaker 3: worse when Sergey Brin came back in terms of its

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Speaker 3: path to platform decay. So what is it that made

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Speaker 3: these companies bad now? And I think really the way

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Speaker 3: to understand that is to ask the inverse, which is

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Speaker 3: why weren't they worse before? Because obviously firms would like

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Speaker 3: to charge more, deliver less, pay less to their suppliers,

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Speaker 3: pay less to their employees, seek more beneficial terms of themselves.

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Speaker 3: And when you freeze it that way, you know why

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Speaker 3: firms don't do it. Because if you charged infinity and

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Speaker 3: paid nothing, well, maybe you'd be running a scholarly journal.

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Speaker 3: But if you're not running a scholarly journal, no one

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Speaker 3: would do it right. You would lose your employees, you'd

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Speaker 3: lose your customers. You have to labor under the discipline

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Speaker 3: of competition of regulators, and if you're in tech, you

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Speaker 3: had other sources of discipline, like interoperability, the ability to

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Speaker 3: make two programs work with each other. So maybe if

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Speaker 3: you had a rent extraction scheme, some would alienate your

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Speaker 3: users from you by coming up with a plugin that

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Speaker 3: made it possible for them to avoid that rent extraction scheme,

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Speaker 3: and those customers would then discover that there was a

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Speaker 3: better firm out there, and they might switch to becoming

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Speaker 3: the customers of them. And you had to worry about

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Speaker 3: your workers because tech workers were so powerful and they

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Speaker 3: often really fought hard for their users. They cared about

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Speaker 3: their jobs. And so my thesis is that when we

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Speaker 3: dismantled these sources of discipline, we created what you could

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Speaker 3: call the eshridogenic policy environment, right, the environment that rewards

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Speaker 3: the firms that do the worst, that rewards the factions

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Speaker 3: and the firms that advocate for the worst, that rewards

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Speaker 3: the impulses and CEOs that are tempted to do the worst,

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Speaker 3: and then the worst happened.

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Speaker 1: So let's talk about some of these firms, because I imagine

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Speaker 1: everybody has experienced the title of your book. Platform decay

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Speaker 1: is the phrase I like to use. I mean, in

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Speaker 1: my experience, and I'm a few years older than you.

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Speaker 1: It began with Microsoft, probably the Suez generis first company

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Speaker 1: that figured out how to lock people in and then

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Speaker 1: abuse the monopoly position they had. That was followed by

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Speaker 1: let's go through the list eBay, Google, Amazon, I would

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Speaker 1: be biased if I didn't include Apple. I think I

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Speaker 1: can also include Starbucks and other entities like that. I

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Speaker 1: have a peeve with them because they basically threatened users

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Speaker 1: with their Starbucks points during the pandemic. I thought that

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Speaker 1: was very misguided and okay, SIA, that was an easy

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Speaker 1: platform to Wait, there was an article in the Wall

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Speaker 1: Street Journal that the Starbucks app, you would load it.

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Speaker 2: Up with a credit card?

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Speaker 1: Wait, why don't I have to give you fifty dollars?

429
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Speaker 1: Just hit my credit card right, and it turned out

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Speaker 1: it was a three or four billion dollar interest free

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Speaker 1: loan there, giving free cash flow. So that was a

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Speaker 1: little bit of a oh and you want to take

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Speaker 1: my points? All right, I'm done with you not boycotting

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Speaker 1: them just they just kind of fell off my first choice.

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Speaker 1: But let's I'm curious.

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Speaker 2: They overcook their beings too, right, Well.

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Speaker 1: If you like strong coffee and don't mind a little

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Speaker 1: bit of bitterness, sure for sure. But I'm curious what

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Speaker 1: were your experiences that led to the book. What was

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Speaker 1: the first platforms that you watched decay?

441
00:20:45,920 --> 00:20:49,040
Speaker 3: Well, let me be clarify a little here, because there

442
00:20:49,119 --> 00:20:51,240
Speaker 3: is there have been lots of platforms that have decayed,

443
00:20:51,280 --> 00:20:54,119
Speaker 3: but they didn't shamble on, right. I think that's one

444
00:20:54,119 --> 00:20:55,760
Speaker 3: of the mysteries that I'm trying to plumb here.

445
00:20:55,840 --> 00:20:59,159
Speaker 1: Well, there's a difference between a company like MySpace that

446
00:20:59,359 --> 00:21:02,800
Speaker 1: just loses out to a superior technology or a better

447
00:21:02,840 --> 00:21:09,560
Speaker 1: interface or whatever, versus something where the entire platform follows

448
00:21:09,640 --> 00:21:11,680
Speaker 1: the pattern that you've outlined.

449
00:21:11,280 --> 00:21:14,000
Speaker 3: And they but but and then they stay in business. Right,

450
00:21:14,040 --> 00:21:15,120
Speaker 3: that's the thing that I want to.

451
00:21:15,040 --> 00:21:17,240
Speaker 2: Interrogate profitably wildly profitable.

452
00:21:17,320 --> 00:21:20,960
Speaker 3: Yeah, so you know, uh, let's think about a few

453
00:21:21,080 --> 00:21:25,159
Speaker 3: examples that you just raised and what happened when they hitified?

454
00:21:25,359 --> 00:21:25,520
Speaker 2: Right?

455
00:21:25,560 --> 00:21:28,840
Speaker 3: So Microsoft, I was you mentioned Apple and you said

456
00:21:28,840 --> 00:21:30,320
Speaker 3: you'd be biased if you didn't mention Apple.

457
00:21:30,640 --> 00:21:31,760
Speaker 2: I was a kind of.

458
00:21:31,720 --> 00:21:34,480
Speaker 3: Cio for hire in the early two thousands, and every

459
00:21:34,520 --> 00:21:35,080
Speaker 3: shop that I.

460
00:21:35,080 --> 00:21:37,960
Speaker 1: Would a chief info or chief chief info chief.

461
00:21:37,800 --> 00:21:40,720
Speaker 3: Info yeah, never chief investor. I invested all my dot

462
00:21:40,720 --> 00:21:42,920
Speaker 3: com money wisely in laptops. I'm sure they're going to

463
00:21:42,960 --> 00:21:43,920
Speaker 3: appreciate someday.

464
00:21:44,960 --> 00:21:45,720
Speaker 2: No, I was.

465
00:21:45,840 --> 00:21:48,399
Speaker 3: I was going around helping little SMEs get online. I

466
00:21:48,440 --> 00:21:50,719
Speaker 3: put up their land, I get the file server everything.

467
00:21:50,800 --> 00:21:52,600
Speaker 3: And they all had a problem, which is that they'd

468
00:21:52,600 --> 00:21:55,240
Speaker 3: have a couple of Macs in the shop and they

469
00:21:55,240 --> 00:21:58,560
Speaker 3: couldn't read or reliably read or write Microsoft Office files.

470
00:21:58,320 --> 00:22:00,960
Speaker 2: Because Microsoftice Microsoft Off. Yeah.

471
00:22:01,119 --> 00:22:04,200
Speaker 3: Microsoft Office for the Mac was the most cursed piece

472
00:22:04,240 --> 00:22:06,200
Speaker 3: of software to come out of redmand and just wave

473
00:22:06,280 --> 00:22:08,960
Speaker 3: the floppy disk around the office and files with spontaneously

474
00:22:09,000 --> 00:22:11,600
Speaker 3: go corrupt. And so Eventually you'd go to the designer

475
00:22:11,640 --> 00:22:13,399
Speaker 3: and maybe the CEO would have a power Book, and

476
00:22:13,400 --> 00:22:16,320
Speaker 3: you put a PC on their desk that was just

477
00:22:16,440 --> 00:22:20,240
Speaker 3: for like Excel, Word and PowerPoint, and then that was

478
00:22:20,320 --> 00:22:22,400
Speaker 3: kind of unwieldy, so then you put a big graphics

479
00:22:22,400 --> 00:22:25,440
Speaker 3: card in there. You'd buy Windows versions of all the

480
00:22:26,320 --> 00:22:28,800
Speaker 3: programs the graphic designer used, and you throw away the Mac.

481
00:22:29,359 --> 00:22:31,399
Speaker 3: And so Steve Jobs knew that this was a problem.

482
00:22:31,520 --> 00:22:34,760
Speaker 3: He didn't just beg Bill Gates to fix Office for

483
00:22:34,800 --> 00:22:38,720
Speaker 3: the Mac. He reverse engineered Office for the Mac. He

484
00:22:38,800 --> 00:22:41,959
Speaker 3: reverse engineered the Office file formats, and he made iWork

485
00:22:42,040 --> 00:22:44,960
Speaker 3: pages numbers in Keynote, which can perfectly read and write

486
00:22:44,960 --> 00:22:47,639
Speaker 3: the Microsoft Office file format. So what he did in

487
00:22:47,720 --> 00:22:51,600
Speaker 3: economics terms is he reduced the switching costs to zero

488
00:22:51,960 --> 00:22:53,600
Speaker 3: because you didn't have to leave any of your files

489
00:22:53,640 --> 00:22:55,280
Speaker 3: behind when you went from Windows.

490
00:22:54,920 --> 00:22:55,400
Speaker 2: To a Mac.

491
00:22:56,200 --> 00:22:59,280
Speaker 3: And he solved the collective action problem of convincing everyone

492
00:22:59,520 --> 00:23:01,399
Speaker 3: to move to a Mac because you didn't have to.

493
00:23:01,800 --> 00:23:03,360
Speaker 3: You could go to the Mac and other people could

494
00:23:03,440 --> 00:23:05,600
Speaker 3: join you when they were ready. This saved apples.

495
00:23:05,600 --> 00:23:09,600
Speaker 1: Bacon I recall the famous prey cover of Wired in

496
00:23:09,680 --> 00:23:13,600
Speaker 1: nineteen ninety eight and My pet theory, or it's not

497
00:23:13,680 --> 00:23:17,400
Speaker 1: even mine, is that Microsoft cut a deal in order

498
00:23:18,000 --> 00:23:20,960
Speaker 1: there was already the antitrust doublings. So hey, we have

499
00:23:21,000 --> 00:23:23,320
Speaker 1: to keep a legitimate operating system.

500
00:23:23,560 --> 00:23:25,760
Speaker 2: Run otherwise controlled opposition. That's right.

501
00:23:25,800 --> 00:23:29,560
Speaker 3: Well, yeah, and they ran these switch ads if you'll recall,

502
00:23:29,640 --> 00:23:32,159
Speaker 3: oh very much, how easy it us to switch So

503
00:23:32,280 --> 00:23:34,800
Speaker 3: this was this incredible moment. Now what would happen if

504
00:23:34,840 --> 00:23:36,600
Speaker 3: you did this to Apple? Right, we have people locked

505
00:23:36,600 --> 00:23:39,280
Speaker 3: into the iPhone today. Their apps are there, their data

506
00:23:39,320 --> 00:23:41,639
Speaker 3: is there, and so on. It's not hard to make

507
00:23:41,680 --> 00:23:45,320
Speaker 3: an iPhone emulator that runs on another computer, including like

508
00:23:45,840 --> 00:23:48,000
Speaker 3: on an Android device, right, and so you could run

509
00:23:48,040 --> 00:23:50,320
Speaker 3: all those apps, you could access all that data if

510
00:23:50,359 --> 00:23:52,560
Speaker 3: you did that to Apple today. If you did onto

511
00:23:52,560 --> 00:23:55,760
Speaker 3: Apple as Apple had done unto Microsoft, first, they'd hit

512
00:23:55,840 --> 00:23:57,760
Speaker 3: you with Section twelve to one of the Digital monam

513
00:23:57,840 --> 00:24:00,280
Speaker 3: Copyright Act for circumvention. That's a five h thousand dollar

514
00:24:00,320 --> 00:24:02,520
Speaker 3: fine in a five year prison sentence for a first offense.

515
00:24:03,040 --> 00:24:05,080
Speaker 3: Then they would call you a tortious interferer with their

516
00:24:05,119 --> 00:24:07,200
Speaker 3: contract for violating their terms of service, and they might

517
00:24:07,280 --> 00:24:09,680
Speaker 3: hit you with criminal terms of service violation under the

518
00:24:09,680 --> 00:24:11,840
Speaker 3: Computer fraud and Abuse Act. They would call you a

519
00:24:11,880 --> 00:24:14,880
Speaker 3: copyright violator, they call you a trademark violator, a patent violator.

520
00:24:15,960 --> 00:24:18,280
Speaker 3: Maybe if you hired some ex employees, they'd say that

521
00:24:18,320 --> 00:24:20,800
Speaker 3: you're going after their trade secrets, and maybe there are

522
00:24:20,800 --> 00:24:26,280
Speaker 3: ex employees non disclosures. They would basically nuqu till you glowed, right.

523
00:24:26,440 --> 00:24:30,440
Speaker 3: And so it's true platforms went bad all through history,

524
00:24:30,640 --> 00:24:32,399
Speaker 3: but they had counter maneuvers.

525
00:24:32,680 --> 00:24:32,919
Speaker 2: You know.

526
00:24:33,000 --> 00:24:36,879
Speaker 3: It wasn't just that MySpace was outcompeted by Facebook. It

527
00:24:36,920 --> 00:24:39,800
Speaker 3: was that when Facebook was trying to lure users over

528
00:24:39,880 --> 00:24:43,240
Speaker 3: from MySpace, it gave them a bot, and you gave

529
00:24:43,240 --> 00:24:45,040
Speaker 3: that bought your login and password, and it would go

530
00:24:45,080 --> 00:24:47,760
Speaker 3: to MySpace several times a day. It would grab everything

531
00:24:47,800 --> 00:24:49,760
Speaker 3: in your MySpace feed and put it in your Facebook

532
00:24:49,760 --> 00:24:51,480
Speaker 3: feed so you could apply to it and it would

533
00:24:51,480 --> 00:24:53,600
Speaker 3: push it back out again. So again you didn't have

534
00:24:53,600 --> 00:24:56,600
Speaker 3: to choose between the people that you loved on MySpace

535
00:24:56,840 --> 00:25:00,000
Speaker 3: and the superior application that was Facebook. Because Facebook's pay

536
00:25:00,000 --> 00:25:02,080
Speaker 3: which at the time was don't use my Space. It's

537
00:25:02,080 --> 00:25:03,719
Speaker 3: owned by an evil billionaire. No one wants to use

538
00:25:03,760 --> 00:25:05,960
Speaker 3: social media owned by an evil billionaire. Plus, did you

539
00:25:06,000 --> 00:25:07,960
Speaker 3: know they spy on you? We're never going to spy

540
00:25:08,080 --> 00:25:10,400
Speaker 3: on you at Facebook, right, But you know, no one

541
00:25:10,600 --> 00:25:12,919
Speaker 3: is going to just smugly read the superior terms of

542
00:25:12,960 --> 00:25:14,720
Speaker 3: service while they wait for their dumb friends to join

543
00:25:14,720 --> 00:25:15,480
Speaker 3: them on Facebook.

544
00:25:15,520 --> 00:25:16,919
Speaker 2: They're going to be where their friends are. So they

545
00:25:17,000 --> 00:25:18,959
Speaker 2: just solved that problem for them. Now.

546
00:25:18,960 --> 00:25:20,800
Speaker 3: In the book, I tell the story of an app

547
00:25:20,840 --> 00:25:23,280
Speaker 3: called og app was created last year by a couple

548
00:25:23,320 --> 00:25:26,520
Speaker 3: of teenagers. They just reverse engineered Instagram. And so you

549
00:25:26,560 --> 00:25:29,040
Speaker 3: would give Instagram, you give the app your Instagram logging

550
00:25:29,080 --> 00:25:31,359
Speaker 3: and password. It would go to Instagram, pretend to be

551
00:25:31,400 --> 00:25:33,960
Speaker 3: You would grab everything in the queue waiting to be

552
00:25:34,000 --> 00:25:35,840
Speaker 3: shown to you, and it would throw away the ads,

553
00:25:35,960 --> 00:25:37,719
Speaker 3: it would throw away the recommendation, so it would throw

554
00:25:37,760 --> 00:25:39,720
Speaker 3: away the boost of content, would throway everything and been

555
00:25:39,760 --> 00:25:42,879
Speaker 3: like surfaced from three months ago because it was getting clickbait,

556
00:25:43,200 --> 00:25:44,720
Speaker 3: and it would just show you the things that the

557
00:25:44,720 --> 00:25:47,240
Speaker 3: people you followed had posted in reverse chronological order.

558
00:25:47,400 --> 00:25:48,840
Speaker 2: It was the og app.

559
00:25:49,080 --> 00:25:53,480
Speaker 1: It's what Facebook did to MySpace in take they're doing

560
00:25:53,560 --> 00:25:55,000
Speaker 1: to a Facebook owned property.

561
00:25:55,080 --> 00:25:58,159
Speaker 3: And so within twenty four hours it was in the

562
00:25:58,160 --> 00:26:00,879
Speaker 3: top ten on both app stores. Wow, And then that

563
00:26:01,080 --> 00:26:03,760
Speaker 3: night Apple and Google shut it down at Meta's request.

564
00:26:04,040 --> 00:26:06,679
Speaker 3: No kidding, because now we have these choke points, and

565
00:26:06,720 --> 00:26:09,760
Speaker 3: it turns out that there is honor among thieves. Right,

566
00:26:09,840 --> 00:26:13,160
Speaker 3: they will all defend to the death one another's ability

567
00:26:13,200 --> 00:26:17,840
Speaker 3: to structure whole markets and decide which products can reach audiences,

568
00:26:18,280 --> 00:26:20,640
Speaker 3: how profitable those products can be, what they can charge,

569
00:26:21,280 --> 00:26:23,760
Speaker 3: whether or not you can even use them. Right, all

570
00:26:23,800 --> 00:26:28,680
Speaker 3: of those things are now being privately regulated by entities

571
00:26:29,080 --> 00:26:32,159
Speaker 3: that are not winning their markets alone, but rather are

572
00:26:32,280 --> 00:26:36,480
Speaker 3: enlisting the state to win their markets. So people have

573
00:26:36,480 --> 00:26:39,040
Speaker 3: different views about how much industrial policy we should have

574
00:26:39,040 --> 00:26:42,040
Speaker 3: and so on, but nobody I think that I know

575
00:26:42,160 --> 00:26:44,520
Speaker 3: of is like, we should have industrial policy, but the

576
00:26:44,520 --> 00:26:46,800
Speaker 3: way that it should work is that the government should

577
00:26:46,840 --> 00:26:49,760
Speaker 3: find some monopolists, pay no attention to what they're doing,

578
00:26:49,800 --> 00:26:52,359
Speaker 3: except when the monopolists get angry and then destroy anyone

579
00:26:52,359 --> 00:26:55,359
Speaker 3: they're angry at. That is like the weirdest form of

580
00:26:55,440 --> 00:26:57,240
Speaker 3: industrial policy I've ever heard of.

581
00:26:57,520 --> 00:26:59,679
Speaker 1: And that seems to be the sort of policy we have.

582
00:27:00,280 --> 00:27:04,400
Speaker 1: Let's talk a little bit about the crapification of Amazon. Sure,

583
00:27:05,119 --> 00:27:09,600
Speaker 1: which the Great revealed to me was during the pandemic

584
00:27:09,760 --> 00:27:12,840
Speaker 1: when they would frequently run out of stuff, and then

585
00:27:13,080 --> 00:27:15,320
Speaker 1: sometimes it would be at Walmart, sometimes it would be

586
00:27:15,440 --> 00:27:21,000
Speaker 1: at Target, sometimes it would be on Instacart. And the

587
00:27:21,040 --> 00:27:25,520
Speaker 1: shock of the pandemic to me was, these guys have

588
00:27:25,800 --> 00:27:28,720
Speaker 1: been I've had an Amazon account since I got a

589
00:27:28,800 --> 00:27:30,720
Speaker 1: gift from a college roommate. I want to say it

590
00:27:30,720 --> 00:27:33,560
Speaker 1: was ninety eight something like that, so a long time.

591
00:27:33,680 --> 00:27:38,919
Speaker 1: The same with eBay, and suddenly you discovered that Amazon

592
00:27:39,119 --> 00:27:43,199
Speaker 1: wasn't the low cost provider. And then the free overnight shipping.

593
00:27:43,240 --> 00:27:46,000
Speaker 1: It's like, hey, your shipping day is Wednesday. We'll send

594
00:27:46,040 --> 00:27:47,760
Speaker 1: it to you on Wednesday. We'll give it to you

595
00:27:47,800 --> 00:27:51,040
Speaker 1: tomorrow for three ninety nine. Wait, this isn't next day

596
00:27:51,040 --> 00:27:53,920
Speaker 1: shipping or even two day shipping. And then the last

597
00:27:54,119 --> 00:27:58,119
Speaker 1: insults was the advertisement. I was searching, you know, the

598
00:27:58,119 --> 00:28:03,360
Speaker 1: little lithium batteries for kifire, Like they're very specific. Durcel

599
00:28:03,520 --> 00:28:06,320
Speaker 1: fifty three seventy four. You put that in the search

600
00:28:06,359 --> 00:28:08,560
Speaker 1: bar and the first thing that pops up it's a

601
00:28:08,640 --> 00:28:10,840
Speaker 1: Dura cell. You click it, you send it, you open

602
00:28:10,920 --> 00:28:13,800
Speaker 1: up the package. Wait, this isn't a fifty three seventy

603
00:28:13,800 --> 00:28:18,760
Speaker 1: four right, Why you I'm advertising for this exact size

604
00:28:18,840 --> 00:28:22,000
Speaker 1: voltage whatever? Why on earth would you show me something else?

605
00:28:22,440 --> 00:28:25,719
Speaker 1: And I'm enough of a jerk that I make them

606
00:28:25,920 --> 00:28:27,920
Speaker 1: pay me the two dollars and eighty nine cents for it,

607
00:28:28,240 --> 00:28:29,240
Speaker 1: and I send it back.

608
00:28:29,520 --> 00:28:32,639
Speaker 3: So you remember Lily Tomlin's bits on SNL where she

609
00:28:32,680 --> 00:28:35,080
Speaker 3: would pretend to be Ernestine the phone operator doing these.

610
00:28:34,920 --> 00:28:35,879
Speaker 2: Commercials for effort.

611
00:28:35,960 --> 00:28:37,920
Speaker 3: Well, start on a laughing and she took to been

612
00:28:37,920 --> 00:28:40,960
Speaker 3: corrected by so many panantic people, but she started on laughing.

613
00:28:41,080 --> 00:28:42,960
Speaker 3: She did it on SNL. She did more segments on

614
00:28:43,080 --> 00:28:44,960
Speaker 3: SNL though yes that's it.

615
00:28:45,160 --> 00:28:48,880
Speaker 2: Yeah, so it's but yes, I but both.

616
00:28:49,280 --> 00:28:50,960
Speaker 3: And she would at the end of these ads for

617
00:28:51,000 --> 00:28:53,320
Speaker 3: the Bell system, she would turn to the camera and

618
00:28:53,360 --> 00:28:54,640
Speaker 3: she'd say, we don't care.

619
00:28:55,040 --> 00:28:58,120
Speaker 2: We don't have to. We're in the phone company. Right.

620
00:28:58,280 --> 00:29:00,640
Speaker 3: One of the insights I think that Lena had when

621
00:29:00,680 --> 00:29:03,640
Speaker 3: she was in office that really landed was that companies

622
00:29:03,720 --> 00:29:05,560
Speaker 3: don't just become too big to fail. They don't just

623
00:29:05,600 --> 00:29:07,360
Speaker 3: become too big to jail. They become too big to

624
00:29:07,440 --> 00:29:11,200
Speaker 3: care that when they're insulated from consequence, they do this. Now,

625
00:29:11,520 --> 00:29:15,320
Speaker 3: what's striking about Amazon is the growth that they've experienced

626
00:29:15,320 --> 00:29:18,600
Speaker 3: from rent, right, not from products, but from rent. So

627
00:29:18,640 --> 00:29:21,480
Speaker 3: you mentioned the advertisements when I wrote this book. They're

628
00:29:21,520 --> 00:29:24,000
Speaker 3: so called ad market, which is the payola market. It's

629
00:29:24,080 --> 00:29:27,840
Speaker 3: the payment for placement and a search result. That was

630
00:29:27,880 --> 00:29:30,600
Speaker 3: like a thirty two billion dollar business, it's now a

631
00:29:30,680 --> 00:29:35,120
Speaker 3: fifty something billion dollar business. This is remarkable growth. And

632
00:29:35,520 --> 00:29:38,240
Speaker 3: that's the reason that the first item in your Amazon

633
00:29:38,280 --> 00:29:41,040
Speaker 3: search result is on average twenty nine percent more expensive

634
00:29:41,080 --> 00:29:42,480
Speaker 3: than the best match for your search.

635
00:29:42,400 --> 00:29:43,440
Speaker 1: Or just the ruling item.

636
00:29:43,480 --> 00:29:46,440
Speaker 3: It's amazing, sure, and then the top bar twenty five percent,

637
00:29:46,560 --> 00:29:49,719
Speaker 3: and then you get down to position number seventeen or so,

638
00:29:49,720 --> 00:29:51,680
Speaker 3: and that's where you find the good result. And of

639
00:29:51,680 --> 00:29:56,040
Speaker 3: course the companies spending more to advertise have less surplus

640
00:29:56,080 --> 00:29:59,640
Speaker 3: to allocate to product quality, and so they're just dominating

641
00:29:59,680 --> 00:30:02,440
Speaker 3: these search results, and they're they're shipping bad things to you.

642
00:30:03,040 --> 00:30:06,800
Speaker 3: By the same token, every merchant on Amazon is paying

643
00:30:06,880 --> 00:30:09,520
Speaker 3: junk fees to list on Amazon, and most of these

644
00:30:09,560 --> 00:30:11,840
Speaker 3: fees are listed as option we'll practically speaking, if you

645
00:30:11,840 --> 00:30:13,880
Speaker 3: don't pay them, you won't get there. So you have

646
00:30:13,920 --> 00:30:15,640
Speaker 3: to do fulfillment by Amazon. You have to pay for prime,

647
00:30:15,640 --> 00:30:18,000
Speaker 3: you have to pay for advertising. When I wrote the book,

648
00:30:18,560 --> 00:30:20,760
Speaker 3: it was, depending on the estimate, forty five to fifty

649
00:30:20,800 --> 00:30:23,760
Speaker 3: one percent in junk fees, and now today in the

650
00:30:23,760 --> 00:30:27,040
Speaker 3: New York Times, Tim wu sites fifty to sixty percent.

651
00:30:27,120 --> 00:30:29,280
Speaker 3: That's on and I've been through New York Times fact checking.

652
00:30:29,360 --> 00:30:31,960
Speaker 3: I think he wouldn't make that. And I've known Tim

653
00:30:32,000 --> 00:30:35,600
Speaker 3: since we were in elementary school together fifty years Columbia Professor,

654
00:30:35,760 --> 00:30:38,240
Speaker 3: Columbia Professor. We both grew up in Toronto, like all

655
00:30:38,240 --> 00:30:39,920
Speaker 3: the best Americans were Canadians.

656
00:30:40,120 --> 00:30:44,120
Speaker 1: So in the book, it's funny because I'm assuming the

657
00:30:44,440 --> 00:30:49,960
Speaker 1: advertising on Amazon yields a result. In the book, you

658
00:30:50,080 --> 00:30:53,680
Speaker 1: talk about how the process of decay got worse and

659
00:30:53,720 --> 00:30:57,040
Speaker 1: worse at Facebook and what was it twenty eighteen Procter

660
00:30:57,080 --> 00:30:59,200
Speaker 1: and Gamble said we're just going to cut twenty seventeen

661
00:30:59,320 --> 00:31:02,520
Speaker 1: two hundred billion dollars in advertising and they source zero

662
00:31:02,640 --> 00:31:03,520
Speaker 1: decrease in sales.

663
00:31:03,640 --> 00:31:03,880
Speaker 2: Yeah.

664
00:31:03,920 --> 00:31:06,520
Speaker 3: So one of the things that Facebook did early on

665
00:31:06,840 --> 00:31:10,000
Speaker 3: was allocate a lot of resources to anti fraud because

666
00:31:10,040 --> 00:31:11,040
Speaker 3: ad fraud is very easy.

667
00:31:11,080 --> 00:31:11,800
Speaker 2: You think about how the.

668
00:31:11,720 --> 00:31:14,200
Speaker 3: Ad market works, it's very complicated, and you know, if

669
00:31:14,200 --> 00:31:16,560
Speaker 3: you're a publisher and you're getting paid by the click,

670
00:31:16,640 --> 00:31:19,000
Speaker 3: you can just fire fake clicks.

671
00:31:18,440 --> 00:31:20,760
Speaker 1: On ads, right boy, farms and everything else.

672
00:31:20,840 --> 00:31:23,600
Speaker 3: Yeah, yeah, or you know, just websites that don't even

673
00:31:23,640 --> 00:31:26,520
Speaker 3: exist that are just loading like they just they only

674
00:31:26,560 --> 00:31:29,440
Speaker 3: exist like as a series of API calls that are

675
00:31:29,480 --> 00:31:32,600
Speaker 3: then generating click responses.

676
00:31:32,000 --> 00:31:32,719
Speaker 2: And so on.

677
00:31:32,760 --> 00:31:35,800
Speaker 3: You know, it can be very lucrative, and so they

678
00:31:35,800 --> 00:31:37,640
Speaker 3: put a lot of money into policing this, and then

679
00:31:37,640 --> 00:31:41,560
Speaker 3: they just drew down that spend because it's expensive, right,

680
00:31:41,600 --> 00:31:42,280
Speaker 3: and so you just.

681
00:31:42,280 --> 00:31:45,720
Speaker 1: Like, providing a quality product and service is expensive.

682
00:31:45,320 --> 00:31:48,040
Speaker 3: And so a million dollars disappeared down the fraud hole. Right,

683
00:31:48,040 --> 00:31:51,160
Speaker 3: that's someone else's problem, right, it's not Facebook's problem. I'm

684
00:31:51,160 --> 00:31:54,160
Speaker 3: sure Facebook would prefer a fraud free marketplace, but why

685
00:31:54,200 --> 00:31:57,520
Speaker 3: bother you know, gold plating their anti fraud.

686
00:31:57,360 --> 00:32:00,480
Speaker 1: When one of the biggest advertisers in the purchase the

687
00:32:00,520 --> 00:32:03,920
Speaker 1: country says, cutting this out because your ads are garbage,

688
00:32:04,400 --> 00:32:05,000
Speaker 1: that's why.

689
00:32:05,160 --> 00:32:07,920
Speaker 3: Well they're back now though, Oh they reinstituted it, and

690
00:32:07,960 --> 00:32:09,880
Speaker 3: they just have more anti fraud on their own ends.

691
00:32:09,880 --> 00:32:12,840
Speaker 3: So they're internalizing those costs. They're doing more auditing on

692
00:32:12,880 --> 00:32:13,280
Speaker 3: their end.

693
00:32:13,520 --> 00:32:17,720
Speaker 1: Unbelievable. So we talked about Facebook, we talked about Amazon,

694
00:32:18,360 --> 00:32:21,680
Speaker 1: got to ask about Uber, which has all sorts of

695
00:32:21,840 --> 00:32:26,200
Speaker 1: interesting platform issues. The big one was when the vcs

696
00:32:26,240 --> 00:32:30,360
Speaker 1: first realized, hey, we have to stop subsidizing these millennials

697
00:32:30,640 --> 00:32:34,680
Speaker 1: and allow the prices to float freely. The one I've

698
00:32:34,680 --> 00:32:37,840
Speaker 1: noticed over the past year or two is there's time

699
00:32:38,040 --> 00:32:41,080
Speaker 1: as it exists in the universe, and then there's time

700
00:32:41,160 --> 00:32:44,160
Speaker 1: on the Uber app waiting for a car that seems

701
00:32:44,200 --> 00:32:48,560
Speaker 1: to have no correlation to the actual time. What's going

702
00:32:48,600 --> 00:32:50,880
Speaker 1: on with Uber in terms of what they pay people,

703
00:32:51,440 --> 00:32:57,040
Speaker 1: surge pricing, and their wonky perspective on time.

704
00:32:57,320 --> 00:33:00,560
Speaker 2: So when Uber kicked off, they tapped the cow market.

705
00:33:00,600 --> 00:33:04,200
Speaker 3: Specifically, they got Masioshi's son, Star of Stage and Screen,

706
00:33:04,240 --> 00:33:06,920
Speaker 3: the man who gave us Yahoo, buying and destroying every

707
00:33:06,920 --> 00:33:10,120
Speaker 3: promising web two point zero company, and we work and

708
00:33:10,440 --> 00:33:13,760
Speaker 3: these days open aiyes latest round, and he went to

709
00:33:13,880 --> 00:33:16,840
Speaker 3: his favorite suckers, the Saudi royal family, and he got

710
00:33:16,960 --> 00:33:19,200
Speaker 3: thirty one billion dollars out of them. And then they

711
00:33:19,200 --> 00:33:21,200
Speaker 3: lost forty one cents on every dollar for the next

712
00:33:21,200 --> 00:33:24,520
Speaker 3: thirteen years and just lit it on fire. But that

713
00:33:24,680 --> 00:33:27,400
Speaker 3: did have some salutary effects from their business perspective. It

714
00:33:27,440 --> 00:33:30,120
Speaker 3: provoked a lost decade in transit investment all over the world,

715
00:33:30,640 --> 00:33:33,440
Speaker 3: because why invest in transit when it's so cheap. They

716
00:33:33,520 --> 00:33:36,880
Speaker 3: put medallion cabs out of business everywhere, and they used

717
00:33:36,880 --> 00:33:40,960
Speaker 3: predatory pricing to freeze out all but one also ran

718
00:33:41,400 --> 00:33:45,280
Speaker 3: ride hail company, which is lyft and then having effectively

719
00:33:45,280 --> 00:33:47,480
Speaker 3: cornered a market and spent a lot of money on

720
00:33:47,520 --> 00:33:50,200
Speaker 3: policy adventurism. Think about the two hundred and twenty five

721
00:33:50,240 --> 00:33:52,440
Speaker 3: million dollars that was spent in California on Prop. Twenty

722
00:33:52,440 --> 00:33:55,880
Speaker 3: two to formalize the Workermer's classification allowed them to you

723
00:33:56,160 --> 00:33:58,080
Speaker 3: only pay the drivers when they had a passenger in

724
00:33:58,120 --> 00:34:00,360
Speaker 3: the car, and they not when they were cruising around,

725
00:34:00,360 --> 00:34:02,440
Speaker 3: giving free labor and wear and tear on their cars

726
00:34:02,440 --> 00:34:05,880
Speaker 3: to the company. They were able to raise prices and

727
00:34:05,920 --> 00:34:08,360
Speaker 3: they were able to lower wages, and to do both

728
00:34:08,440 --> 00:34:15,160
Speaker 3: they tap both private data and algorithmic fluidity. So the

729
00:34:15,400 --> 00:34:18,600
Speaker 3: labor or the lawyer rather the labor lawyer viena do

730
00:34:18,800 --> 00:34:23,799
Speaker 3: ball coin. This term algorithmic wage discrimination. It's when two

731
00:34:23,800 --> 00:34:27,440
Speaker 3: workers are offered a different wage based on the algorithm's

732
00:34:27,880 --> 00:34:31,280
Speaker 3: estimation of their desperation. And so in the case of Uber,

733
00:34:31,360 --> 00:34:33,880
Speaker 3: the way that this works is if you take a

734
00:34:33,920 --> 00:34:35,839
Speaker 3: low ball offer, and when you get an offer as

735
00:34:35,840 --> 00:34:38,160
Speaker 3: an Uber driver, just a few seconds to say yes

736
00:34:38,239 --> 00:34:40,600
Speaker 3: or no, and you've got to figure out like mileage,

737
00:34:40,680 --> 00:34:43,400
Speaker 3: minutes and so on. When if you take that offer

738
00:34:43,520 --> 00:34:46,560
Speaker 3: and it's lower than your historic rate, then that becomes

739
00:34:46,560 --> 00:34:49,279
Speaker 3: a new ceiling and they start to nudge you down

740
00:34:49,400 --> 00:34:50,080
Speaker 3: lower and lower.

741
00:34:50,239 --> 00:34:51,560
Speaker 1: Really, and that's unbelievable.

742
00:34:51,640 --> 00:34:54,880
Speaker 3: Yeah, So drivers they bucket themselves into pickers and ants,

743
00:34:55,160 --> 00:34:57,440
Speaker 3: and the pickers are picky, and the ants take everything,

744
00:34:57,800 --> 00:35:00,520
Speaker 3: and ants have their wages go down and down and down.

745
00:35:00,520 --> 00:35:02,720
Speaker 3: And the idea is to turn every picker into an ant,

746
00:35:02,880 --> 00:35:05,560
Speaker 3: because an ant is subsidizing the company.

747
00:35:05,960 --> 00:35:06,520
Speaker 2: Right, they're just.

748
00:35:06,520 --> 00:35:08,759
Speaker 3: Driving around and around. They're on the road, no matter

749
00:35:08,760 --> 00:35:12,120
Speaker 3: how garbage the fares are. It's great for the company.

750
00:35:12,120 --> 00:35:13,799
Speaker 3: And of course if you can take a low ball

751
00:35:13,840 --> 00:35:16,520
Speaker 3: offer and you can find a passenger who will take

752
00:35:16,680 --> 00:35:20,239
Speaker 3: a price gouging offer, then the differences to companies to

753
00:35:20,840 --> 00:35:23,360
Speaker 3: sock up. And so we on the passenger side we

754
00:35:23,440 --> 00:35:25,640
Speaker 3: have our own version of this where they are doing

755
00:35:25,640 --> 00:35:28,040
Speaker 3: all kinds of calculations in the back end to calculate

756
00:35:28,080 --> 00:35:30,440
Speaker 3: how desperate we are get to take the ride. Now,

757
00:35:30,440 --> 00:35:31,759
Speaker 3: it used to be that they had this whole thing

758
00:35:31,800 --> 00:35:33,719
Speaker 3: about how we're going to match supply with demand using

759
00:35:33,760 --> 00:35:36,960
Speaker 3: price signals. We'll have surge pricing when everyone gets out

760
00:35:37,000 --> 00:35:39,160
Speaker 3: of a dodger's game, we'll crank.

761
00:35:38,960 --> 00:35:41,880
Speaker 2: Up the price and that'll drive drivers out.

762
00:35:41,920 --> 00:35:44,080
Speaker 3: That's not what they do anymore, right, they do have

763
00:35:44,160 --> 00:35:48,160
Speaker 3: surge pricing. They just keep the searge right unless the

764
00:35:48,239 --> 00:35:51,760
Speaker 3: drivers won't take it. Now again, if it were lawful

765
00:35:51,840 --> 00:35:55,399
Speaker 3: to do reverse engineering modification, you could imagine drivers doing

766
00:35:55,400 --> 00:35:58,080
Speaker 3: what they're already doing in other countries, like in Indonesia,

767
00:35:58,480 --> 00:36:01,719
Speaker 3: gig riders, because they don't cars. They ride motorbikes there,

768
00:36:01,719 --> 00:36:03,880
Speaker 3: and those are the taxis and delivery vehicles and so on.

769
00:36:04,080 --> 00:36:06,719
Speaker 3: Those gig riders, they started these little clubhouses because you

770
00:36:06,760 --> 00:36:08,279
Speaker 3: need somewhere to pee and to have a cup of

771
00:36:08,280 --> 00:36:09,439
Speaker 3: tea and you know.

772
00:36:09,400 --> 00:36:10,080
Speaker 2: Working your bike.

773
00:36:10,360 --> 00:36:12,120
Speaker 3: And those clubhouses turned into co ops, and the co

774
00:36:12,160 --> 00:36:15,680
Speaker 3: ops started commissioning software, and the commissioned software to modify

775
00:36:15,719 --> 00:36:16,720
Speaker 3: their dispatch apps.

776
00:36:16,880 --> 00:36:18,040
Speaker 2: And it started pretty modest.

777
00:36:18,080 --> 00:36:22,080
Speaker 3: It started with the well understood tendency of graphic designers

778
00:36:22,080 --> 00:36:24,279
Speaker 3: to torment the rest of us by making all their

779
00:36:24,320 --> 00:36:27,040
Speaker 3: type eight point great type on white, right, and all

780
00:36:27,040 --> 00:36:29,080
Speaker 3: the older riders are like, I cannot see my goddamn

781
00:36:29,080 --> 00:36:29,960
Speaker 3: phone and I'm in traffic.

782
00:36:30,040 --> 00:36:31,240
Speaker 2: Make the type bigger and black.

783
00:36:31,520 --> 00:36:33,840
Speaker 3: But these days it's stuff like an app that allows

784
00:36:33,880 --> 00:36:36,359
Speaker 3: all the riders to say, none of us will take

785
00:36:36,360 --> 00:36:36,800
Speaker 3: a ride.

786
00:36:36,960 --> 00:36:38,040
Speaker 2: That's a low ball offer.

787
00:36:38,280 --> 00:36:41,600
Speaker 3: So automatically calculate the mileage and the per minute when

788
00:36:41,640 --> 00:36:43,719
Speaker 3: you get the offer over the air, and just turn

789
00:36:43,760 --> 00:36:46,440
Speaker 3: it down automatically so that you can force the algorithm

790
00:36:46,480 --> 00:36:50,040
Speaker 3: to force the wage up right. Drivers here can't do that,

791
00:36:50,120 --> 00:36:52,600
Speaker 3: not because it's technically impossible, because it's unlawful.

792
00:36:52,840 --> 00:36:54,640
Speaker 2: You know the posse would that be unlawful.

793
00:36:54,840 --> 00:36:56,120
Speaker 1: It's like a union.

794
00:36:55,840 --> 00:36:59,600
Speaker 3: Because you're bypassing the technical protections in the app and

795
00:36:59,680 --> 00:37:02,319
Speaker 3: unders section twelve one of the Digital One Name Copyright Act.

796
00:37:02,560 --> 00:37:05,280
Speaker 3: That's illegal, even if you're doing so for a lawful purpose.

797
00:37:05,800 --> 00:37:09,239
Speaker 3: So the mere presence of what's called an effective means

798
00:37:09,280 --> 00:37:13,520
Speaker 3: of access control in the statute creates a zone where

799
00:37:13,560 --> 00:37:17,120
Speaker 3: you cannot enter, irrespective of the legitimacy of the reason

800
00:37:17,160 --> 00:37:17,840
Speaker 3: for your entry.

801
00:37:18,480 --> 00:37:21,279
Speaker 1: That's unbelievable. You would think they could create a very

802
00:37:21,320 --> 00:37:25,040
Speaker 1: simple client app where the server is the one that's

803
00:37:25,080 --> 00:37:27,480
Speaker 1: doing all of that. It's not, and just do the

804
00:37:27,520 --> 00:37:28,760
Speaker 1: calculation and say.

805
00:37:28,520 --> 00:37:31,960
Speaker 3: No, yeah, but scraping, So scraping the number right when

806
00:37:31,960 --> 00:37:33,640
Speaker 3: it comes in is illegal.

807
00:37:33,680 --> 00:37:36,239
Speaker 1: You're not even scraping it. You're just you're seeing it.

808
00:37:36,280 --> 00:37:38,040
Speaker 1: You don't have to go to their site and see no.

809
00:37:38,160 --> 00:37:41,359
Speaker 2: No, but it's on your device, but on your device. Right,

810
00:37:41,640 --> 00:37:42,920
Speaker 2: they're blocking.

811
00:37:42,560 --> 00:37:45,719
Speaker 3: Other apps, but they're blocking other apps from reading what

812
00:37:46,080 --> 00:37:48,399
Speaker 3: one app. One app by design, one app can't see

813
00:37:48,440 --> 00:37:50,279
Speaker 3: what the other app is doing, which is good. You

814
00:37:50,360 --> 00:37:52,200
Speaker 3: kind of want that, right, you don't want you don't

815
00:37:52,200 --> 00:37:54,760
Speaker 3: want like the malware and your browser seeing your prodcasts.

816
00:37:55,239 --> 00:37:55,920
Speaker 1: Right, that's fair.

817
00:37:56,000 --> 00:37:59,160
Speaker 3: But you, as the owner of the device could certainly say, well,

818
00:37:59,160 --> 00:38:03,400
Speaker 3: I give permission for this, right, But for someone to

819
00:38:03,480 --> 00:38:06,680
Speaker 3: write the app that bypasses that control, even with permission

820
00:38:06,680 --> 00:38:10,040
Speaker 3: from the owner, is unlawful because that control itself has

821
00:38:10,080 --> 00:38:12,920
Speaker 3: its own zone of protection that is not in the

822
00:38:12,920 --> 00:38:15,160
Speaker 3: control of the owner of the device. It's in control

823
00:38:15,160 --> 00:38:17,279
Speaker 3: of the author of the software. I'll give you a

824
00:38:17,320 --> 00:38:17,759
Speaker 3: quick exam.

825
00:38:17,880 --> 00:38:18,719
Speaker 1: It's unbelievable.

826
00:38:18,719 --> 00:38:21,279
Speaker 3: All the audio books on Audible are sold with these

827
00:38:21,320 --> 00:38:22,520
Speaker 3: technical protection measures.

828
00:38:23,160 --> 00:38:23,359
Speaker 2: Play.

829
00:38:23,520 --> 00:38:26,560
Speaker 3: Yeah, they only play on Amazon's approved apps. They're ninety

830
00:38:26,560 --> 00:38:28,839
Speaker 3: percent of the market. That means every time I sell

831
00:38:28,840 --> 00:38:31,160
Speaker 3: you an audiobook, I create a switching cost for you.

832
00:38:31,680 --> 00:38:34,080
Speaker 3: And so if Amazon screws me and I leave to

833
00:38:34,640 --> 00:38:36,520
Speaker 3: you I have to guess whether you're willing to throw

834
00:38:36,560 --> 00:38:37,840
Speaker 3: all your audiobooks to follow me.

835
00:38:38,000 --> 00:38:41,040
Speaker 1: No. Well, I mean, how many people listen to the

836
00:38:41,040 --> 00:38:42,200
Speaker 1: same audiobook twice?

837
00:38:42,400 --> 00:38:44,359
Speaker 3: Lots of people big library. Yeah, lots of people are

838
00:38:44,360 --> 00:38:47,080
Speaker 3: big library. So here's the thing. If I give you

839
00:38:47,120 --> 00:38:50,479
Speaker 3: a tool to move your audiobook library from one app

840
00:38:50,480 --> 00:38:53,359
Speaker 3: to another, I the author of the book, and in

841
00:38:53,360 --> 00:38:55,760
Speaker 3: this case, I read the book aloud myself in a studio.

842
00:38:55,920 --> 00:38:58,799
Speaker 3: I finance the production, I paid the director, I paid

843
00:38:58,800 --> 00:39:02,280
Speaker 3: the engineer. This is my copyright from top to bottom.

844
00:39:02,320 --> 00:39:03,520
Speaker 2: This is not a lot to do that.

845
00:39:04,200 --> 00:39:07,400
Speaker 3: Not only do I commit a crime, but I commit

846
00:39:07,480 --> 00:39:09,800
Speaker 3: a more serious crime than you would if you pirated

847
00:39:09,840 --> 00:39:13,360
Speaker 3: the audiobook. I face a worse sentence than if you

848
00:39:13,480 --> 00:39:16,360
Speaker 3: shoplifted the audiobook on CD at a truck stop. And

849
00:39:16,400 --> 00:39:19,440
Speaker 3: we would probably get the same sentence if you and I.

850
00:39:19,440 --> 00:39:20,840
Speaker 3: If I were to provide you with a tool to

851
00:39:20,840 --> 00:39:22,400
Speaker 3: take the audiobook out of the app, and if you

852
00:39:22,480 --> 00:39:24,160
Speaker 3: were to stick up the driver of the truck that

853
00:39:24,200 --> 00:39:25,000
Speaker 3: delivered the CD.

854
00:39:24,880 --> 00:39:27,960
Speaker 1: Set, that's unbelievable. I have to ask you about general

855
00:39:28,000 --> 00:39:31,640
Speaker 1: of AI, the impact on artists and writers, and what

856
00:39:31,680 --> 00:39:33,080
Speaker 1: it means in terms of.

857
00:39:33,200 --> 00:39:35,000
Speaker 2: Oh We're never going to get this in two minutes,

858
00:39:35,040 --> 00:39:35,680
Speaker 2: but let me try.

859
00:39:35,840 --> 00:39:36,240
Speaker 1: Go ahead.

860
00:39:36,320 --> 00:39:39,600
Speaker 3: So look, the only your boss is insatiable horney for

861
00:39:39,640 --> 00:39:41,799
Speaker 3: firing you and replacing you with an algorithm. That has

862
00:39:41,840 --> 00:39:45,080
Speaker 3: been true since the time of the Luddites. Bosses don't

863
00:39:45,120 --> 00:39:47,080
Speaker 3: like to pay workers, and they're looking for a way

864
00:39:47,120 --> 00:39:50,200
Speaker 3: to erode the rights of workers. If we were to

865
00:39:50,239 --> 00:39:53,560
Speaker 3: give to creative workers a new right to control AI training,

866
00:39:54,000 --> 00:39:56,480
Speaker 3: those workers would still have to sell their labor into

867
00:39:56,520 --> 00:39:59,160
Speaker 3: a market of five publishers for studios, three labels, two

868
00:39:59,200 --> 00:40:02,880
Speaker 3: companies that control all the apps, and one ebook audiobook company,

869
00:40:03,080 --> 00:40:06,480
Speaker 3: and those companies would negotiate change their terms of contract

870
00:40:06,520 --> 00:40:09,360
Speaker 3: to non negotiably acquire that training right. They would license

871
00:40:09,400 --> 00:40:12,560
Speaker 3: our data to the AI companies, and then they would

872
00:40:12,640 --> 00:40:14,839
Speaker 3: buy back the resulting algorithm and try and put us.

873
00:40:14,800 --> 00:40:15,400
Speaker 2: Out of business.

874
00:40:15,680 --> 00:40:18,759
Speaker 3: However, we do have some remedies to us. So the

875
00:40:18,800 --> 00:40:21,400
Speaker 3: first important one is that the US Copyright Office has

876
00:40:21,440 --> 00:40:25,279
Speaker 3: said correctly that copyright is only for works of human creativity,

877
00:40:25,480 --> 00:40:28,520
Speaker 3: so anything out by a bot excuse my language, is

878
00:40:28,560 --> 00:40:30,560
Speaker 3: not eligible for a copyright. And the only thing our

879
00:40:30,560 --> 00:40:32,920
Speaker 3: bosses hate more than paying us is having people take

880
00:40:32,960 --> 00:40:37,160
Speaker 3: the stuff we make for them and using it without

881
00:40:37,200 --> 00:40:39,439
Speaker 3: paying them without their permission. So that's the first thing,

882
00:40:39,760 --> 00:40:41,879
Speaker 3: and the second thing is what the Writers Guild taught us,

883
00:40:42,200 --> 00:40:46,080
Speaker 3: which is that you can't solve AI with a copyright,

884
00:40:46,239 --> 00:40:47,920
Speaker 3: but you can solve it with a union that has

885
00:40:47,920 --> 00:40:50,600
Speaker 3: the right for sectoral bargaining right to bargain with all

886
00:40:50,600 --> 00:40:53,960
Speaker 3: the studios. And if creative workers are going to advocate

887
00:40:54,000 --> 00:40:56,520
Speaker 3: for a new law, let's not make it a law

888
00:40:56,560 --> 00:40:58,799
Speaker 3: that our bosses want, which is a new copyright law.

889
00:40:58,960 --> 00:41:01,080
Speaker 2: Let's make it a law that our boss's hate.

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Speaker 3: Which is a sectoral bargaining right for all creative workers

891
00:41:04,360 --> 00:41:07,319
Speaker 3: to bargain with all employers in their sector. Because that

892
00:41:07,600 --> 00:41:08,640
Speaker 3: actually worked.

893
00:41:10,640 --> 00:41:13,640
Speaker 1: That was my conversation with Cory doctor O, author of

894
00:41:13,640 --> 00:41:17,360
Speaker 1: the new book in Citification. If you enjoy this conversation,

895
00:41:17,640 --> 00:41:19,920
Speaker 1: well be sure and check out any of our previous

896
00:41:20,280 --> 00:41:23,600
Speaker 1: six hundred we've done over prior twelve years. You can

897
00:41:23,640 --> 00:41:28,200
Speaker 1: find those at iTunes, Spotify, YouTube, Bloomberg, wherever you get

898
00:41:28,239 --> 00:41:29,640
Speaker 1: your favorite podcasts.

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00:41:30,160 --> 00:41:30,680
Speaker 2: I would be.

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00:41:30,640 --> 00:41:32,960
Speaker 1: Remiss if iden thank our crack staff who helps us

901
00:41:33,000 --> 00:41:37,120
Speaker 1: put these conversations together each week. Alexis Noriega is my

902
00:41:37,280 --> 00:41:42,480
Speaker 1: video producer Sean Russo is my researcher. Anna Luke is

903
00:41:42,520 --> 00:41:46,680
Speaker 1: my producer. I'm Barry Rittolts. You've been listening to Masters

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Speaker 1: in Business on Bloomberg Radio.