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Speaker 1: Hi everyone, I'm Kitty Kuric and this is next question.

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Speaker 1: Fair warning everyone. I love Kara Swisher. I mean, how

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Speaker 1: can you not. She's been one of the hardest hitting

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Speaker 1: journalists covering the tech industry since the tech industry started.

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Speaker 1: Kara knew early on that the Internet was going to

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Speaker 1: irreversibly change the world. Now, that might sound like a

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Speaker 1: given now, but it wasn't at the beginning of Kara's

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Speaker 1: career three decades ago. And who can forget when I

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Speaker 1: asked Alison, what is internet? Yeah, let's try to forget that.

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Speaker 1: Kara's decision to make tech her beat and really stick

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Speaker 1: to that role as chief watchdog and rabble rouser in

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Speaker 1: an industry that often seemed to view its leaders as

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Speaker 1: God's has been a true public service. Kara has a

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Speaker 1: new memoir. It's called burn Book, a Tech Love Story,

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Speaker 1: and it's out today. And by the way, the blurbs

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Speaker 1: on the back of the book under praise for Kara Swisher,

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Speaker 1: well they are classic Kara Like quote not a single

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Speaker 1: more vitriolic voice in the tech ecosystem David sachs Loquacious

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Speaker 1: podcast guy, or Mark Andresen's quote she would sit on

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Speaker 1: instant messenger all day and harass the shit out of people.

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Speaker 1: Sally Quinn said, she has an incredible bullshit detector, which

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Speaker 1: is always helpful in Washington. You're an asshole. That was

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Speaker 1: Elon Musk quote, so you get the drift. Along with

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Speaker 1: being a fascinating look at how a great journalist gets made,

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Speaker 1: it's a history of how the tech industry burrowed itself

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Speaker 1: into every aspect of our lives. Kara uses history as

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Speaker 1: her guide. In fact, no surprise when you hear what

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Speaker 1: she studied in college to examine how new technologies like

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Speaker 1: AI could change our lives profoundly. Again, I'm really grateful

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Speaker 1: to have Kara's insight and her irrev doggie, keen and

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Speaker 1: incisive point of view to keep the tech industries feet

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Speaker 1: to the fire, and to have her as my guest today.

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Speaker 1: She's also a great person and a really good friend.

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Speaker 1: Here's my conversation with the one and only Kara Swisher.

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Speaker 1: First of all, Kara, are you sick of talking about

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Speaker 1: your book yet? Or you're nice?

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Speaker 2: This is the first day? Well no, I did a

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Speaker 2: bunch last week, but yes, this is the first big day.

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Speaker 1: Well, I'm very excited because everyone, I mean, I love Kara,

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Speaker 1: and she's got a new book out called burn Book,

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Speaker 1: a tech love story, and honestly, reading it, I felt

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Speaker 1: like I was just having a really long, fun, extended

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Speaker 1: dinner with you, caring about really tech for the last

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Speaker 1: thirty plus years, and you've had a front row seat.

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Speaker 1: I love the book. It's so fun and funny but

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Speaker 1: also incredibly substantive, just like you.

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Speaker 2: Thank you. Well, you know, thirty years, Katie. Don't try

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Speaker 2: to age me. I know you try to age me

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Speaker 2: all the time. Thirty exactly thirty years.

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Speaker 1: And I found the book to be funny, smart, cheeky,

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Speaker 1: and insightful. So here's the quick question. Was it fun

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Speaker 1: writing this?

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Speaker 2: Kara? Well, you know I'm two and a half years late, actually,

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Speaker 2: so no. I didn't really want to do that. And

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Speaker 2: one of the things that was hard is getting to

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Speaker 2: do it, as you know, from writing your memoir right,

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Speaker 2: getting yourself psyched. But you're like a harder worker than

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Speaker 2: I am, Like I was sort of hones not that is,

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Speaker 2: I'm hard on the things I like. How's that? And

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Speaker 2: I didn't want to write a book at all. You know,

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Speaker 2: I had avoided books for a long time. I had

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Speaker 2: been offered you know whenever there was a Twitter book

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Speaker 2: or what happened to Katie Kirk at Yahoo book.

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Speaker 1: Well you did write ah, we'll discuss that later, but

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Speaker 1: you did write a book really early on in your

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Speaker 1: career about age by the way, I did.

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Speaker 2: Then it was too That was when I was in

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Speaker 2: you know, really young, and.

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Speaker 1: I was and you needed to make some cabbage.

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Speaker 2: Cabbage, and not just cabbage, but reputation, right, And I

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Speaker 2: really did think this internet thing was going to be

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Speaker 2: a big deal. And nobody at that time when that

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Speaker 2: book came out in nineteen ninety seven, very few people

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Speaker 2: were figuring this out. And so that was a different thing.

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Speaker 2: Is I was there in Washington sitting by myself and

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Speaker 2: going this is this is a big revolution and people

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Speaker 2: need to pay attention. So I had been the editor

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Speaker 2: on that was John carp who now runs Simon and Schuster.

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Speaker 2: He was a young guy too, We were both at

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Speaker 2: the beginning of our careers and he's the one that

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Speaker 2: got me to write it, which was interesting the first

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Speaker 2: book and I he said, this is these people are

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Speaker 2: going to change the world care you need to write

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Speaker 2: a book about them. And I was like, okay. And

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Speaker 2: then in that book, I have Yahoo people, Amazon people.

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Speaker 2: There's all jeff Is in that. And so he kept

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Speaker 2: bugging me over the years, like do you want to

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Speaker 2: do this? I was like, no, I don't want to

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Speaker 2: do with Google book or Twitter book or whatever. But

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Speaker 2: then he came to me and said, would you write

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Speaker 2: a fictional book? And I said, oh, what do you mean,

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Speaker 2: like make it up? And he goes, yeah, I'll get

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Speaker 2: you a fiction writer this and that, and I said, oh,

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Speaker 2: I could kill someone then, right, but you know, like

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Speaker 2: I could make it a murder mious and you know

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Speaker 2: that murderer doesn't get solved essentially. And then I was like,

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Speaker 2: I can't do that, It's not really me. And then

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Speaker 2: he Walt Mosburg was supposed to write a memoir of

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Speaker 2: his time in tech, and I wanted him to do that,

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Speaker 2: and he just decided not to abandon it for his

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Speaker 2: own reasons. And I said, someone's got to say what

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Speaker 2: happened here, right, someone who knew, who has notes, who

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Speaker 2: has pictures, who you know, and especially not just that.

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Speaker 2: It was more like we are at a cusp of

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Speaker 2: another huge change. And I thought a artificial general intelligence

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Speaker 2: AGI was a line another line and like just like

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Speaker 2: mobile was or the internet itself was, and I thought

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Speaker 2: I could end it there, like we're on the cusp.

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Speaker 2: Let me tell you what happened the first time, because

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Speaker 2: we're in for like a world of trouble if we don't,

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Speaker 2: And that's why I did it.

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Speaker 1: I think one of the great things about the book

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Speaker 1: is how precient you were, Karen, how you read the

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Speaker 1: tea leaves, unlike really anyone else. That sounds like Jonathan

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Speaker 1: Carr did as well, by the way.

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Speaker 2: But yeah he did.

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Speaker 1: But before we talk about sort of the business writ large,

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Speaker 1: I want to talk a little bit about you personally,

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Speaker 1: because I found some of the stuff about your family

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Speaker 1: so moving. You lost your dad to a complications from

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Speaker 1: a brain aneurysm when you were just five years old,

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Speaker 1: remembering that morning, I think it was a sunny Saturday,

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Speaker 1: I think you described it that way, and your brother

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Speaker 1: knocking on his door and how traumatizing that was, and

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Speaker 1: also about your stepfather, and I'm curious in retrospect, and

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Speaker 1: you write a little bit about this in the book,

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Speaker 1: and I want people to buy the book, so we

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Speaker 1: don't want to tell everything that's in the book, But

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Speaker 1: how were you shaped by the father? You really didn't

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Speaker 1: know very well. I think you knew better posthumously.

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Speaker 2: Yeah, because here's the deal. You know, I have a

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Speaker 2: lot of kids. You have a lot of kids. When

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Speaker 2: my son, who's twenty one now, turn five, I was

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Speaker 2: over five years old when my father got sick. When

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Speaker 2: it was a couple months older. My son knew me

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Speaker 2: so well. At five. My daughter who's four, and I

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Speaker 2: chitchat all the time, my two year old at I

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Speaker 2: chit chat. I realized the devastation then, like, oh my god,

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Speaker 2: I did know him really well, right, And so I

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Speaker 2: just don't remember it. That's very different than I didn't.

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Speaker 2: And so I had thought that because I was so

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Speaker 2: young and didn't remember, it didn't have an impact. But

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Speaker 2: the minute I had kids it was. And I actually

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Speaker 2: had a stroke very close to when my older kids

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Speaker 2: were that age, right, and.

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Speaker 1: I thought so scary it was.

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Speaker 2: But I think it really was a formative experience. And

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Speaker 2: think that was another thing I didn't want to write about.

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Speaker 2: I mean, you wrote your memoir it was a lot

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Speaker 2: about work and stuff like that, but I had a

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Speaker 2: very hard time. I don't in my case, I don't

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Speaker 2: think I was as interesting as the people I was

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Speaker 2: writing about, And so I was very reticent to write

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Speaker 2: about my personal life, very I never had done it,

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Speaker 2: and he for asked me to do that, to add

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Speaker 2: it in. And then I realized, you know, this is

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Speaker 2: a journey story. This is I'm Nick in the Great Gatsby.

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Speaker 2: That's who I am.

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Speaker 1: And I love to use that quote too, by the

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Speaker 1: day at the beginning of the book.

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Speaker 2: Yeah, yeah, it's it's a tell for me. But I'm

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Speaker 2: that character, and you need to know a little bit

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Speaker 2: about Nick and where he came from, so you understand

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Speaker 2: my journey essentially.

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Speaker 1: Well, I also think your understanding of this brave new

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Speaker 1: world you have to understand sort of the person who's

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Speaker 1: telling the story, and obviously that's you. And your dad

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Speaker 1: sounded like such a gem of a person, a doctor, right, yes,

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Speaker 1: and just sounds like an incredible man. And then your

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Speaker 1: mom goes and marries a stepfather. And I think you

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Speaker 1: used alliteration casually cruel. Didn't you use a cascade of

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Speaker 1: casual cruelties?

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Speaker 2: Like cascade of casual cruelties? Yeah, exactly.

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Speaker 1: Yeah, Well, let me go back to my original question.

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Speaker 1: How did both men in retrospect shape you and the

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Speaker 1: person you became?

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Speaker 2: Well, you know, my dad was. You know every look,

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Speaker 2: when people die, young people get to make them to heroes, right,

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Speaker 2: That's true. You know, no matter how you do, the

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Speaker 2: memories sort of get much more burnished. And you had

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Speaker 2: a tragic your husband died, but we know who they were.

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Speaker 2: But my dad, I have to say everyday. I wrote

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Speaker 2: a story about I moved his body from where it

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Speaker 2: was buried in New York a long time. I wrote

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Speaker 2: a story in The Washington Post about it to West

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Speaker 2: Virginia after my grandmother, who was devastated by his death,

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Speaker 2: asked me to. She was dying of leukemia, and she

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Speaker 2: asked me to move him, and I did this. I

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Speaker 2: wrote a story about it. And after we wrote it

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Speaker 2: when I was a young young I was in my

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Speaker 2: mid twenties, I guess when I wrote it, and I

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Speaker 2: got so many letters people who knew him, which was

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Speaker 2: really something like it was really something and including like

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Speaker 2: I got a young doctor who he had trained, he

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Speaker 2: tutored her. I didn't know this. I got an email

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Speaker 2: from a Jewish doctor. He said he's the only one

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Speaker 2: who was said cut the anti Semitic bullshit, which was

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Speaker 2: really I was sort of like, what good guy, this

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Speaker 2: guy's gay couple. He's the only people. He treated us

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Speaker 2: like we were a real couple. This was way back

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Speaker 2: in the you know, in the sixties, and I was

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Speaker 2: like and friends of his and ex girl front of his,

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Speaker 2: you know, all this stuff, and it was really fascinating

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Speaker 2: to learn about him.

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Speaker 1: That's a wonderful gift for your kids, by the way,

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Speaker 1: it is.

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Speaker 2: One hundred percent. And one of the things that it

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Speaker 2: did teach me is that you really don't you have

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Speaker 2: to understand impact of people on your life, even if

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Speaker 2: they're not The absence of my father was as important

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Speaker 2: as his presence, right, you know, in terms of losing him,

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Speaker 2: and then my mom didn't marry someone who was not nice,

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Speaker 2: and I was sort of It wasn't Cinderella. I'm not

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Speaker 2: in the you know, an episode, but it was to

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Speaker 2: think about losing someone so precious and then having to

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Speaker 2: deal with a very tough person afterwards. And your mom

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Speaker 2: is part of it, right, and so you know she

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Speaker 2: had a reasons, young woman with three kids, like, I

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Speaker 2: get it, I get it. But he was just I'll

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Speaker 2: tell you, he did teach me about strategy. He was

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Speaker 2: brilliant and.

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Speaker 1: Sought again really good.

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Speaker 2: I won't play it anymore because I get really mean

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Speaker 2: my plan it. It's really funny. I learned how to

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Speaker 2: be tough, you know, in that regard, and you had

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Speaker 2: to be when you're left with almost raising yourself in

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Speaker 2: a weird way in an expensive environment. It's not like

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Speaker 2: I was like I had a scrabble eat food. It

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Speaker 2: was a very I mean, I grew up in a

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Speaker 2: very lovely environment. But doesn't make it any less lonely

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Speaker 2: or sad.

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Speaker 1: You know, it sounds like your dad gave you though,

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Speaker 1: maybe the ability or this instinct you have to stand

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Speaker 1: up for what's right from those letters you got.

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Speaker 2: Yes, I think so absolutely. And so my grandmother played

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Speaker 2: My mom's mom played a big role in my life.

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Speaker 2: Was very supportive and loving, and I later got much

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Speaker 2: closer to my father's mom. All kinds of reasons. We

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Speaker 2: didn't spend as much time with him, but you know,

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Speaker 2: I had a lot of support from family. We have

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Speaker 2: a big Italian family. So there was that.

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Speaker 1: You didn't talk about your mom that much in the book.

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Speaker 2: I didn't. That's the next book, Katie. Why not.

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Speaker 1: It's complicated, a tough relationship.

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Speaker 2: It's complicated, you know, I think how funny you're pressing

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Speaker 2: exactly what you shouldn't. But that's okay, that's Katie Kurk.

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Speaker 2: I have a complex relationship with her, continue to this day,

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Speaker 2: and I think there's a lot of me that doesn't

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Speaker 2: forgive her for him. I guess, you know, I think

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Speaker 2: there's probably that element to it. She's you know, we've

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Speaker 2: had a very up and down relationship, including me being gay,

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Speaker 2: and she's come around well, but at the initially she

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Speaker 2: was terrible. And so that was another thing. I knew

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Speaker 2: I was gay at four or five years old, Like

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Speaker 2: I knew it?

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Speaker 1: And how did you know it?

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Speaker 2: Just did? I don't know what to tell you. I

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Speaker 2: just was like, ah huh, that's what I am. I

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Speaker 2: was kind of proud of it. It was weird except

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Speaker 2: for all the messages you were getting from media at

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Speaker 2: the time, which, as you know, you know, predatory lesbians

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Speaker 2: all drong, blah blah blah, that kind of stuff and

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Speaker 2: gay people bad. You know, that was during my era

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Speaker 2: pre aids.

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Speaker 1: Right and mine too, mine too. And one of the

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Speaker 1: things I marvel at always is I think sometimes people

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Speaker 1: don't not that we don't have miles to go before

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Speaker 1: we sleep, but people don't recognize how different. It is

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Speaker 1: not perfect for gay people in this country. And you know,

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Speaker 1: I was thinking about, you know, you're a little younger

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Speaker 1: than I am, Kara, maybe a lot younger than I am.

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Speaker 1: And I was thinking about how you wanted to go

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Speaker 1: into the CIA, and back then the military would have

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Speaker 1: been the eighties, right when you graduated. Right that, you know,

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Speaker 1: people forget about don't ask, don't tell. They don't forget

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Speaker 1: about the fact that Obama actually initially didn't support gay marriage.

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Speaker 2: They don't remember Clinton.

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Speaker 1: Clinton's were exactly how no, no, no, I know, I

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Speaker 1: know for the military, but then Obama it's just sort

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Speaker 1: of shocking to see that he had to evolve, and

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Speaker 1: thank goodness he did during his presidency. But you couldn't

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Speaker 1: be in the CIA or the military, which is what

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Speaker 1: you wanted to do, Which would have you would have

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Speaker 1: been so great.

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Speaker 2: I would have been a kick ass admirl you would

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Speaker 2: have you would I would have been tell me why

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Speaker 2: what stopped you? I didn't want to lie. I didn't

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Speaker 2: it was. And then before don As Hotel, which is

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Speaker 2: already offensive enough, right like, first of all, I ask

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Speaker 2: and I tell, like, so that's kind of hard, which

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Speaker 2: I can't even believe they passed that. I just when

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Speaker 2: you think about it today, you're like, are you kidding me?

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Speaker 1: Talk about why that's so offensive for people who might

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Speaker 1: not remember.

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Speaker 2: Well, because it's like they don't get to ask, and

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Speaker 2: you don't say, because if you say, you have to leave.

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Speaker 2: So you have to lie. Everybody's lying, and it's just

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Speaker 2: it creates talk. You want to create, you know, community

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Speaker 2: within the military. You want to create collegiality and the

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Speaker 2: kind of things you need to have a strong military.

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Speaker 2: And you're all lying to each other. It's like, I

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Speaker 2: might as well be with my family, right, you know,

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Speaker 2: the kind of thing and the furtiveness is what is

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Speaker 2: bad about it. And before don't ask, don't tell. I

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Speaker 2: think a lot of straight up people thought, well, we're

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Speaker 2: being nice. We're not going to ask now or hold

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Speaker 2: it against them. But asking you to lie is just like,

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Speaker 2: this is who I am, and I have to tell

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Speaker 2: you I'm not or pretend I'm not. It was just

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Speaker 2: so ridiculous, And they thought that was nice compared to

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Speaker 2: putting you in jail for it or throwing you out

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Speaker 2: of the military with a dishonorable discharge. What happened, and

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Speaker 2: so the whole but It wasn't just in the military,

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Speaker 2: was everywhere you had to be furtive. It was I

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Speaker 2: can't you know, today is a full on assault of

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Speaker 2: gay people, and that's where they're headed gay marriage. But

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Speaker 2: they're doing it in plain sight. Now they're saying they

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Speaker 2: don't like gay people, they don't like trans people, they

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Speaker 2: don't like algy they're not even hiding their their kind

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Speaker 2: of thing. Before it was it was very furtive the

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Speaker 2: way you were. You know, if you're gay, then you

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Speaker 2: know people knew to keep quiet or else kind of thing.

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Speaker 2: And I just I couldn't do it. I couldn't do it.

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Speaker 2: I just I'm not that person. So then I did

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Speaker 2: another job.

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Speaker 1: After a quick break, Kara talks about her early career

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Speaker 1: and dishes out some excellent professional advice. If you want

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Speaker 1: to get smarter every morning with a breakdown of the

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Speaker 1: news and fascinating takes on health and wellness and pop culture,

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Speaker 1: sign up for our daily newsletter wake Up Call like

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Speaker 1: going to Katiecuric dot com. And we're back with Kara Swisher.

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Speaker 1: So you decided to go into journalism. You went to Georgetown,

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Speaker 1: you didn't love it. You wanted to go to Stanford,

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Speaker 1: where your brother went, but you did love your history courses,

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Speaker 1: you write. My focus was on propaganda and how groups

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Speaker 1: like the Nazis used media and communications tools to twist facts,

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Speaker 1: radicalize their populace, and demonize the targeted population. Obviously, Hitler

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Speaker 1: and his henchmen had conducted a masterclass an evil. But

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Speaker 1: what struck me was how easily people could be manipulated

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Speaker 1: by fear and rage, and how facts could be destroyed

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Speaker 1: without repercussions. Did you ever imagine your major would come

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Speaker 1: in so handy? I mean, that's so scary.

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Speaker 2: You know, yes, Because when I saw the Internet for

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Speaker 2: the first time, I was like, that was one of

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Speaker 2: my first thoughts besides cool, right, whoa, this is really interesting,

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Speaker 2: especially the Worldwide Web, the hyperlinks. I was like, oh,

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Speaker 2: look at that was the ability to manipulate it. You know,

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Speaker 2: you saw it. It was right, You couldn't miss what

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Speaker 2: you could do with it from a negative point. I'm

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Speaker 2: one of those people, and I think that was one

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Speaker 2: of the things I write about in the book, which

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Speaker 2: is I anticipate consequences. I'm good at that, right, If

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Speaker 2: this then that and that was what I wanted to

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Speaker 2: do in the military. Intelligence is sort of be like

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Speaker 2: you know, Homeland, but you know, one hundred percent less

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Speaker 2: mentally challenge. But I like that, like, what's going to

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Speaker 2: happen here if I know this input? And you know

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Speaker 2: that in reporting you do that. You sit there and

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Speaker 2: you're like, when you're doing an interview, you're like, strategize

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Speaker 2: it right, right, if I say this, they might say this,

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Speaker 2: then I'll say this. You know, you do things like that,

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Speaker 2: and so I really liked that. I was really attracted

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Speaker 2: to that, and so I think reporting is like that,

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Speaker 2: very much like that, and so it was really easy

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Speaker 2: for me to move to understand what the Internet would

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Speaker 2: be when I saw it, because I was like, oh,

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Speaker 2: this is a really good propaganda tool.

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Speaker 1: And that was when you were on a fellowship at

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Speaker 1: Duke and you have this aha moment. I think you

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Speaker 1: were in the library and this idea that you could

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Speaker 1: just digitize the world, right.

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Speaker 2: You could, Yeah, a book. In this case, it was

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Speaker 2: a book, but it could have been anything. And I

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Speaker 2: think I did see that, and I had already been

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Speaker 2: attracted to like the mobile phone that they had at

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Speaker 2: the post.

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Speaker 1: The big clunky one that was like the size of

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Speaker 1: a shoe box.

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Speaker 2: Yeah, yeah, there was one in a suitcase, and then

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Speaker 2: there was a shoe box one, then there was the

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Speaker 2: Gordon Geecko one, and then it got small part. But

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Speaker 2: I was attracted to it. I was like mobile communications.

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Speaker 2: I like it, like you know what I mean, Like,

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Speaker 2: why wouldn't we have these? Everybody have them as a reporter.

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Speaker 2: Why be in the newsroom? And so I was super

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Speaker 2: attracted to that. I was always obsessed. I know it

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Speaker 2: sounds crazy with that teletype machine. Did you ever visit

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Speaker 2: the Post back in the day.

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Speaker 1: You might have no, but I mean, honey, I had teleton.

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Speaker 2: Yeah.

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Speaker 1: Right. My job was changing the purple ribbon. And they

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Speaker 1: even have little white gloves so you wouldn't stain your fingers.

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Speaker 1: I mean, this is how old I am.

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Speaker 2: Yes, me too. I delivered the page proofs down to

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Speaker 2: the printers at the Washington Post. I was a newsgg

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Speaker 2: and but that teletype machine. I hated it. I was like,

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Speaker 2: why is it here? Why it's going to be on

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Speaker 2: the intern the internet? But it can go on the computer.

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Speaker 2: I kept like. And even when I was at Columbia,

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Speaker 2: they were teaching us to type on a typewriter. I'm like,

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Speaker 2: why are we on a typewriter? There's a computer like,

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Speaker 2: there's no need to put anything on paper, And it

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Speaker 2: wasn't because I like trees so much, although that's a benefit,

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Speaker 2: added benefit, but it was so onerous, like and then

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Speaker 2: you use your red pen and I was like, you.

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Speaker 1: Don't need to wipe out and the white out I

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Speaker 1: remember you could do a reverse thing. And the by

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Speaker 1: the way, a little known fact, Michael Nessmith, one of

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Speaker 1: the Monkeys, his inventor, invented white out. But then remember

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Speaker 1: you had a backspace thing that you could wipe it

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Speaker 1: out on years later.

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Speaker 2: That was a big innovation. That was yeah, like we're

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Speaker 2: going down old Lady Highway.

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Speaker 1: But you saw technology, the existing technology, and you always

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Speaker 1: thought there's got to be a better way. And then

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Speaker 1: the Internet comes up right and you're like, holy shit,

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Speaker 1: this is the better way.

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Speaker 2: But but I did see the negatives. I was like, wow,

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Speaker 2: if Hitler had this, that would be pretty that would

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Speaker 2: be scary, right, and bad people. I always was thinking

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Speaker 2: what would bad people do to this?

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Speaker 1: Well, I think that benefited from your major, from what

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Speaker 1: you studied in college, you know, I think you applied that.

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Speaker 1: I want to talk more about the Internet in a moment,

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Speaker 1: but I want to ask you about I had so

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Speaker 1: much fun reading about as you describe yourself as a nuisance.

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Speaker 1: I think probably people have other choice words, Karen to

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Speaker 1: describe you in your early early days and to now

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Speaker 1: and even now. But I loved how you worked your way.

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Speaker 1: You know, how you got a job at the Washington

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Speaker 1: Post by complaining about how an article was written. I

432
00:20:43,240 --> 00:20:46,879
Speaker 1: love the fact that when you told John McLaughlin, the

433
00:20:46,960 --> 00:20:52,560
Speaker 1: infamous Molton hard blowhard of the Magawklan group, that he

434
00:20:52,600 --> 00:20:54,400
Speaker 1: was going to lose power because he was getting old,

435
00:20:54,400 --> 00:20:56,600
Speaker 1: that you said in a much more eloquent, funny way.

436
00:20:57,000 --> 00:20:59,720
Speaker 1: The way you kind of interacted with Don Graham the

437
00:20:59,720 --> 00:21:01,080
Speaker 1: public sure, the pose.

438
00:21:00,880 --> 00:21:01,960
Speaker 2: To lovely guy.

439
00:21:02,160 --> 00:21:06,640
Speaker 1: Yeah, lovely, but almost unnecessarily humble, I think is sort

440
00:21:06,640 --> 00:21:09,160
Speaker 1: of the ways.

441
00:21:08,680 --> 00:21:11,440
Speaker 2: You're unnecessarily humble speak a little more arrogant, Tom.

442
00:21:11,600 --> 00:21:14,920
Speaker 1: But you know to suggesting to marketers of major newspapers

443
00:21:14,960 --> 00:21:16,879
Speaker 1: that the best way to get younger readers was to

444
00:21:17,000 --> 00:21:20,359
Speaker 1: quote tape a joint between every single page. And it

445
00:21:20,440 --> 00:21:23,400
Speaker 1: struck me how did you have such confidence at such

446
00:21:23,400 --> 00:21:25,200
Speaker 1: an early age. I mean, we talked about your dad

447
00:21:25,280 --> 00:21:27,160
Speaker 1: standing up for what it was right, but you were

448
00:21:27,240 --> 00:21:30,639
Speaker 1: such a baller even in your twenties, Kara, And I

449
00:21:30,680 --> 00:21:33,199
Speaker 1: mean you called out bullshit and it was risky.

450
00:21:33,280 --> 00:21:33,439
Speaker 2: You know.

451
00:21:33,520 --> 00:21:35,440
Speaker 1: I know that you thought John McLaughlan was going to

452
00:21:35,480 --> 00:21:38,159
Speaker 1: fire you when you gave him a piece of your mind, yeah,

453
00:21:38,200 --> 00:21:41,800
Speaker 1: which was so funny. Yeah, but he didn't. He laughed.

454
00:21:42,080 --> 00:21:44,960
Speaker 1: But where does that come from? Because honestly, I want

455
00:21:44,960 --> 00:21:46,119
Speaker 1: to slice of that part.

456
00:21:46,000 --> 00:21:48,600
Speaker 2: Of me thinks it's lesbian. I think it's a lesbian thing.

457
00:21:48,640 --> 00:21:51,400
Speaker 2: I think you did. You're an honorary lesbian. Thank you,

458
00:21:51,680 --> 00:21:53,919
Speaker 2: as you know what I told you that, But you

459
00:21:53,920 --> 00:21:55,679
Speaker 2: have elements of it. And I'm not going to ask

460
00:21:55,720 --> 00:21:57,520
Speaker 2: any personal questions Katie. It's up to you what you

461
00:21:57,520 --> 00:22:01,119
Speaker 2: want to do. But I I just have a little

462
00:22:01,160 --> 00:22:03,160
Speaker 2: to do with it. Like I didn't have to seek

463
00:22:03,200 --> 00:22:05,560
Speaker 2: the approval of men. And there's an old joke like

464
00:22:05,640 --> 00:22:07,280
Speaker 2: I don't know why they think lesbian's hate men. They

465
00:22:07,320 --> 00:22:09,359
Speaker 2: don't have to sleep with them, right, you know, Like

466
00:22:09,560 --> 00:22:11,879
Speaker 2: why would I? And I had great brothers and I

467
00:22:11,920 --> 00:22:14,080
Speaker 2: had a lot of really good experiences with men, and

468
00:22:14,480 --> 00:22:17,639
Speaker 2: so I just think I was I was like that

469
00:22:17,680 --> 00:22:19,760
Speaker 2: from a young age. I was like, this is stupid.

470
00:22:19,960 --> 00:22:21,960
Speaker 2: You know, I don't understand it, and I would I

471
00:22:21,960 --> 00:22:24,119
Speaker 2: wouldn't be able to not say it. And I don't know.

472
00:22:24,160 --> 00:22:26,320
Speaker 1: Maybe that's not no filter, I guess, right.

473
00:22:26,200 --> 00:22:28,280
Speaker 2: I don't, Well, I have a filter I have, I don't.

474
00:22:28,359 --> 00:22:31,800
Speaker 2: I don't. I'm not unnecessarily cruel to I don't have

475
00:22:31,840 --> 00:22:35,000
Speaker 2: a filter of people above me. Like I find myself

476
00:22:35,080 --> 00:22:39,640
Speaker 2: constantly saying, what's everybody's thinking? Right, very quickly, and I think,

477
00:22:40,240 --> 00:22:42,439
Speaker 2: I don't know. And as I've gotten older, I'm like,

478
00:22:42,960 --> 00:22:45,160
Speaker 2: I sort of moved to a cranky old lady very

479
00:22:45,160 --> 00:22:48,399
Speaker 2: early in my life, right like what ha ha or

480
00:22:48,480 --> 00:22:51,480
Speaker 2: Larry David or that kind of thing. And I don't

481
00:22:51,520 --> 00:22:54,080
Speaker 2: know what why that was, but I was like that,

482
00:22:54,400 --> 00:22:56,840
Speaker 2: and especially when there was like it didn't make any

483
00:22:56,920 --> 00:22:59,600
Speaker 2: sense to me when they were like, and it's such

484
00:22:59,600 --> 00:23:01,439
Speaker 2: a thing, meant they're confidence because I've had a lot

485
00:23:01,480 --> 00:23:04,320
Speaker 2: of excerence. Why are you so confident? Why aren't other

486
00:23:04,320 --> 00:23:06,760
Speaker 2: people confident? Like it's never that question, it's that as

487
00:23:06,800 --> 00:23:09,920
Speaker 2: we have to all be not confident, especially women. I

488
00:23:10,040 --> 00:23:12,440
Speaker 2: did never understood that I was like I never said

489
00:23:12,480 --> 00:23:14,800
Speaker 2: I was great at things I wasn't great at. But

490
00:23:14,880 --> 00:23:17,720
Speaker 2: I also never said I wasn't great at things I

491
00:23:17,800 --> 00:23:20,320
Speaker 2: was great at, Right, Like I didn't like. I didn't go,

492
00:23:20,400 --> 00:23:22,480
Speaker 2: I'm so good at basketball, but if I was good

493
00:23:22,480 --> 00:23:25,919
Speaker 2: at writing, which I was, i'd say it. And a

494
00:23:25,920 --> 00:23:28,439
Speaker 2: lot of people, especially men, I'm sorry to say, this

495
00:23:28,480 --> 00:23:31,280
Speaker 2: is what happens, but women do it too. They were like, well,

496
00:23:31,280 --> 00:23:34,679
Speaker 2: you shouldn't be so confident. I'm like why what precisely?

497
00:23:35,160 --> 00:23:38,960
Speaker 2: Why not? Well, because people will think you're you're too confident.

498
00:23:39,040 --> 00:23:41,880
Speaker 2: I'm like, what is too? It's like saying people will

499
00:23:42,000 --> 00:23:45,200
Speaker 2: think you're too stunning, or people will think you're too smart,

500
00:23:45,400 --> 00:23:48,040
Speaker 2: Like why do that? And it was just irritating. I

501
00:23:48,080 --> 00:23:51,840
Speaker 2: found it irritating on every level, and I especially you don't.

502
00:23:51,960 --> 00:23:54,240
Speaker 2: I think women really get the brunt of that. And

503
00:23:54,320 --> 00:23:56,280
Speaker 2: I didn't care, like if they said I was bossy

504
00:23:56,280 --> 00:23:58,639
Speaker 2: because I wasn't gonna marry any of them, Like, okay,

505
00:23:59,400 --> 00:24:03,160
Speaker 2: well we're not getting married and five of those. That's

506
00:24:03,200 --> 00:24:06,520
Speaker 2: a great tool for a reporter. You know you're challenging people.

507
00:24:06,560 --> 00:24:08,800
Speaker 2: I know you don't like the term speaking truth to power,

508
00:24:08,800 --> 00:24:12,240
Speaker 2: and I think it's sort of overused because and it's

509
00:24:12,280 --> 00:24:14,959
Speaker 2: insinuating as you write that all power is bad and

510
00:24:15,000 --> 00:24:19,000
Speaker 2: it isn't necessarily but it comes in handy and I

511
00:24:19,040 --> 00:24:21,639
Speaker 2: think early on we were talking about your understanding of

512
00:24:21,680 --> 00:24:25,320
Speaker 2: the Internet. You saw very clearly the Washington Post was

513
00:24:25,359 --> 00:24:28,000
Speaker 2: in deep doo doo, as they say, because of the

514
00:24:28,040 --> 00:24:31,639
Speaker 2: classified ads, and not just that. I covered retail before

515
00:24:32,480 --> 00:24:39,240
Speaker 2: and garfing girls gar had lunch, probably had lunch, and

516
00:24:39,240 --> 00:24:40,080
Speaker 2: the rotunda.

517
00:24:40,200 --> 00:24:42,200
Speaker 1: We were not the ladies who lunch crowd.

518
00:24:42,320 --> 00:24:42,520
Speaker 2: You know.

519
00:24:42,600 --> 00:24:45,399
Speaker 1: I had a very pretty pretty modest upbringing, but my

520
00:24:45,480 --> 00:24:47,840
Speaker 1: mom once in a while would go to Garfing Gels

521
00:24:47,880 --> 00:24:50,160
Speaker 1: and we would shop there. And I love that store.

522
00:24:50,200 --> 00:24:52,080
Speaker 1: And you write about it closing.

523
00:24:51,840 --> 00:24:53,400
Speaker 2: Explain what it was. It was an elegance.

524
00:24:53,520 --> 00:24:56,720
Speaker 1: Yeah, I think there were only two, weren't there Weren't

525
00:24:56,760 --> 00:24:58,960
Speaker 1: they just in DC? Because there was one downtown.

526
00:24:59,119 --> 00:25:02,240
Speaker 2: It was a local tailor. Same thing with hex Hexcal.

527
00:25:03,200 --> 00:25:04,879
Speaker 1: I bought my first broad hecks.

528
00:25:05,160 --> 00:25:09,240
Speaker 2: Oh, how nice to know, Katie, So hex Garfinkel's. There's

529
00:25:09,359 --> 00:25:10,680
Speaker 2: giant food heckingers.

530
00:25:11,080 --> 00:25:11,359
Speaker 1: Right.

531
00:25:11,400 --> 00:25:14,159
Speaker 2: There was a bunch of local retailers, and I covered

532
00:25:14,200 --> 00:25:16,280
Speaker 2: the decline of all of them for the Post. That

533
00:25:16,400 --> 00:25:18,400
Speaker 2: was my beat because I covered the Half family, who

534
00:25:18,440 --> 00:25:22,960
Speaker 2: you also knew crowded track exactly, Bobby and Bobby Half

535
00:25:23,560 --> 00:25:26,400
Speaker 2: and so I really did cover that and I could

536
00:25:26,440 --> 00:25:29,440
Speaker 2: see and at the time, the culprit was Walmart. It

537
00:25:29,560 --> 00:25:31,800
Speaker 2: came in all the big box retailers, and Walmart was

538
00:25:31,840 --> 00:25:34,760
Speaker 2: the most prominent, and we're putting those companies out of business.

539
00:25:34,840 --> 00:25:37,720
Speaker 2: And they were highly technical by the way, Walmart was,

540
00:25:38,200 --> 00:25:40,239
Speaker 2: and I was paying a lot of attention to their

541
00:25:40,320 --> 00:25:43,000
Speaker 2: use of technology. But then I thought, well, if display

542
00:25:43,000 --> 00:25:47,640
Speaker 2: advertising goes and then I saw the classifieds, I was like, Oh,

543
00:25:47,680 --> 00:25:49,880
Speaker 2: that's Craigslist is going to put this out of business.

544
00:25:50,080 --> 00:25:53,280
Speaker 2: And then third, when the internet really started seeing news,

545
00:25:53,359 --> 00:25:55,679
Speaker 2: I was like, oh, news is free. A lot of

546
00:25:55,720 --> 00:25:57,960
Speaker 2: it is a lot of what's in the Washington Post

547
00:25:58,000 --> 00:26:02,119
Speaker 2: is free. I was like, that's every single economic underpinning

548
00:26:02,119 --> 00:26:04,920
Speaker 2: of this place. And therefore their costs are too high.

549
00:26:05,000 --> 00:26:08,080
Speaker 2: Immediately their revenue will drop out and then curtains.

550
00:26:08,359 --> 00:26:10,760
Speaker 1: So why do you think so many people were in

551
00:26:10,960 --> 00:26:14,280
Speaker 1: You know, I had some foresight, not as much as

552
00:26:14,320 --> 00:26:16,240
Speaker 1: you did. I wish you'd telly you and I had

553
00:26:16,320 --> 00:26:21,560
Speaker 1: talked more about the business side of journalism. But why

554
00:26:21,560 --> 00:26:23,879
Speaker 1: do you think there were so many people in the

555
00:26:24,040 --> 00:26:28,000
Speaker 1: industry who didn't want to see the writing on the wall?

556
00:26:28,119 --> 00:26:30,359
Speaker 1: Is it because they wanted to protect their business model

557
00:26:30,359 --> 00:26:32,679
Speaker 1: at all costs? That they were older, they were just

558
00:26:32,720 --> 00:26:36,040
Speaker 1: trying to reach retirement. What was it? Because I remember

559
00:26:36,040 --> 00:26:39,520
Speaker 1: being at CBS Kara and saying to the digital people, Hey,

560
00:26:39,560 --> 00:26:42,200
Speaker 1: we really have to lean in Nsie Smith, Yeah, Quincy.

561
00:26:42,400 --> 00:26:45,520
Speaker 1: But also there was sort of a team at CBS

562
00:26:45,560 --> 00:26:47,840
Speaker 1: News like, we really have to lean into this. I

563
00:26:47,920 --> 00:26:52,080
Speaker 1: want to do online interviews. Let's stay covering the conventions

564
00:26:52,320 --> 00:26:56,160
Speaker 1: longer online and direct people to go online to watch

565
00:26:56,160 --> 00:26:59,159
Speaker 1: our conversations. And so I feel like I was a

566
00:26:59,200 --> 00:27:01,439
Speaker 1: bit ahead of the but people looked at me like

567
00:27:01,480 --> 00:27:02,439
Speaker 1: I had three heads.

568
00:27:02,760 --> 00:27:05,480
Speaker 2: They did. They did because they couldn't understand. You know,

569
00:27:05,520 --> 00:27:08,320
Speaker 2: everything was sort of handed you. It wasn't just in media,

570
00:27:08,359 --> 00:27:12,040
Speaker 2: it was also record companies like here's an album. What

571
00:27:12,119 --> 00:27:14,800
Speaker 2: if you just want a song, you know, it's sort

572
00:27:14,840 --> 00:27:17,520
Speaker 2: of like coaxing. Sixty four ounce bottle is all you'll

573
00:27:17,520 --> 00:27:19,640
Speaker 2: be getting. And if you don't want that, you don't

574
00:27:19,640 --> 00:27:21,680
Speaker 2: have a glass or screwed. Essentially, we're not going to

575
00:27:21,720 --> 00:27:25,360
Speaker 2: sell it in cans. No other product was sold at

576
00:27:25,400 --> 00:27:28,720
Speaker 2: the convenience of the seller as much as media. Right,

577
00:27:29,119 --> 00:27:32,480
Speaker 2: whatever system they wanted, they would do.

578
00:27:32,560 --> 00:27:34,920
Speaker 1: And they controlled it back then, right, that's right.

579
00:27:35,040 --> 00:27:37,120
Speaker 2: Yeah, because they felt like it because they I used

580
00:27:37,119 --> 00:27:39,879
Speaker 2: to get arguments over the five o'clock deadline? Why is

581
00:27:39,920 --> 00:27:43,760
Speaker 2: it five? That's me being irritating care I was like,

582
00:27:44,160 --> 00:27:46,080
Speaker 2: why shouldn't it be seven, or why shouldn't it be

583
00:27:46,119 --> 00:27:48,040
Speaker 2: all the time, or why not when it just happens?

584
00:27:48,040 --> 00:27:49,840
Speaker 2: Why not just if it's a two, let's put it

585
00:27:49,880 --> 00:27:52,720
Speaker 2: up at two, right And they're like, we're not the

586
00:27:52,760 --> 00:27:55,680
Speaker 2: AP and I'm like no, but people are going to

587
00:27:55,720 --> 00:27:57,680
Speaker 2: get their news right then, and therefore you're going to

588
00:27:57,720 --> 00:28:00,600
Speaker 2: be late if you're not like the IP or why

589
00:28:00,640 --> 00:28:02,760
Speaker 2: don't you do more? There's all of these behind the

590
00:28:02,800 --> 00:28:06,520
Speaker 2: scenes things, and I just it seemed like an opportunity

591
00:28:06,560 --> 00:28:08,800
Speaker 2: to mean more than a negative, and they resisted. It

592
00:28:08,840 --> 00:28:11,960
Speaker 2: was such vehemence. That was something to say to watch the.

593
00:28:11,960 --> 00:28:15,879
Speaker 1: Resistance and frustrating and hard to know. But I think

594
00:28:16,040 --> 00:28:20,240
Speaker 1: it's risky to jump to a different business model and

595
00:28:20,400 --> 00:28:23,800
Speaker 1: potentially cannibalize the product you're putting out, you know.

596
00:28:23,920 --> 00:28:26,200
Speaker 2: So I think there were some well guess what happened.

597
00:28:26,240 --> 00:28:29,280
Speaker 2: They got pushed and they were too late to get technical,

598
00:28:29,680 --> 00:28:31,800
Speaker 2: to get cockecting os paches and guess who owns digital

599
00:28:31,800 --> 00:28:34,639
Speaker 2: advertising now, which is really the only advertising except for

600
00:28:34,680 --> 00:28:38,520
Speaker 2: some some display advertising, but for the most part, most

601
00:28:38,520 --> 00:28:40,600
Speaker 2: of the money has shifted. One of the things I

602
00:28:40,720 --> 00:28:43,800
Speaker 2: saw in Scott Gallier Mining is today. I remember when

603
00:28:43,960 --> 00:28:47,360
Speaker 2: a TV usage was seven percent of the attention and

604
00:28:47,440 --> 00:28:51,719
Speaker 2: thirty percent of the advertising, and Internet was thirty percent

605
00:28:51,800 --> 00:28:54,560
Speaker 2: of the usage and seven percent of the And I thought,

606
00:28:55,040 --> 00:28:57,520
Speaker 2: that doesn't make any sense. And of course it's gone

607
00:28:57,640 --> 00:29:01,640
Speaker 2: like this, right, Why should the thing people are on

608
00:29:01,760 --> 00:29:04,560
Speaker 2: not get the bulk of the advertising? Right? And I

609
00:29:04,640 --> 00:29:07,360
Speaker 2: think the I don't know what numbers they were looking at,

610
00:29:07,440 --> 00:29:09,880
Speaker 2: but anybody could have seen it coming. It's not like

611
00:29:10,000 --> 00:29:11,840
Speaker 2: that was some genius in any way.

612
00:29:12,160 --> 00:29:15,160
Speaker 1: I remember Jeff Sucker used to talk about analog dollars

613
00:29:15,200 --> 00:29:18,480
Speaker 1: in digital dimes, and it just didn't seem like the

614
00:29:18,520 --> 00:29:20,760
Speaker 1: money would be there. But if you read the you know,

615
00:29:20,880 --> 00:29:23,400
Speaker 1: if you have any foresight, you know that it's going

616
00:29:23,440 --> 00:29:25,640
Speaker 1: to do. You think the big mistake was that people

617
00:29:25,800 --> 00:29:28,840
Speaker 1: media organizations gave their content away for free.

618
00:29:29,080 --> 00:29:32,080
Speaker 2: Was that no, they they just had to. Their economics

619
00:29:32,080 --> 00:29:34,920
Speaker 2: were out of out of line with where the business

620
00:29:35,000 --> 00:29:37,360
Speaker 2: was going. Yes, they would be digital dimes, but someday

621
00:29:37,400 --> 00:29:40,600
Speaker 2: they would be a lot of digital dimes, right, But

622
00:29:40,840 --> 00:29:44,560
Speaker 2: until then, you had costs. You all made so much money,

623
00:29:44,760 --> 00:29:48,080
Speaker 2: like your contracts were crazy, and I think.

624
00:29:47,920 --> 00:29:50,120
Speaker 1: You those days are over by the Those days.

625
00:29:49,960 --> 00:29:52,520
Speaker 2: Are over by the way. You might have been valuable,

626
00:29:52,520 --> 00:29:55,280
Speaker 2: But were the other twelve people valuable? You know what

627
00:29:55,320 --> 00:29:57,360
Speaker 2: I mean? Like should they have gotten millions of dollars?

628
00:29:57,400 --> 00:29:59,720
Speaker 2: Probably not. Like one of the things I tried to

629
00:29:59,760 --> 00:30:02,200
Speaker 2: do early on because one I was irritating and two

630
00:30:02,280 --> 00:30:06,200
Speaker 2: I was irritated, and so I always matched myself with

631
00:30:06,240 --> 00:30:08,880
Speaker 2: my revenues. I was very aware of what my revenues

632
00:30:08,920 --> 00:30:11,360
Speaker 2: were and my profits, not just my revenues, my profits.

633
00:30:11,600 --> 00:30:14,720
Speaker 2: Because then if they're like, we want to we want

634
00:30:14,760 --> 00:30:16,240
Speaker 2: you to do this, I'm like, no, I'm making money

635
00:30:16,280 --> 00:30:18,960
Speaker 2: over here. Leave me alone. Like if I'm making money,

636
00:30:19,000 --> 00:30:22,080
Speaker 2: you cannot bother me, essentially, And so if you were

637
00:30:22,120 --> 00:30:24,719
Speaker 2: aware of your actual contribution, and I know a lot

638
00:30:24,760 --> 00:30:27,920
Speaker 2: of journalists are like, you shouldn't put a number on it,

639
00:30:27,960 --> 00:30:30,800
Speaker 2: Well guess what someone's putting a number on it somewhere,

640
00:30:30,880 --> 00:30:33,360
Speaker 2: so it might as well be you. Once I knew

641
00:30:33,440 --> 00:30:35,640
Speaker 2: what my value was, and I know I sound like

642
00:30:35,680 --> 00:30:37,920
Speaker 2: Mika Berzinski there, but you know, if you don't know

643
00:30:38,000 --> 00:30:41,080
Speaker 2: your value, you don't know what you can do or

644
00:30:41,120 --> 00:30:41,800
Speaker 2: what you can't do.

645
00:30:42,080 --> 00:30:45,160
Speaker 1: That's good professional advice. I think for anyone to kind

646
00:30:45,200 --> 00:30:48,640
Speaker 1: of have a really keen understanding of not only what

647
00:30:48,680 --> 00:30:51,720
Speaker 1: they're making, but what they're making the other people as well.

648
00:30:51,800 --> 00:30:55,160
Speaker 2: Right, regular people have to do it every day, hourly workers.

649
00:30:55,200 --> 00:30:57,080
Speaker 2: If they're not keeping up, they don't get the money.

650
00:30:57,120 --> 00:30:57,239
Speaker 1: Like.

651
00:30:57,400 --> 00:30:59,880
Speaker 2: That's the problem is that a lot of it was

652
00:31:00,040 --> 00:31:03,480
Speaker 2: supported by other things that no one ever saw or

653
00:31:03,520 --> 00:31:07,560
Speaker 2: thought of, and the minute digital, which it's hitting obviously

654
00:31:07,840 --> 00:31:11,600
Speaker 2: the blue collar workers. A lot of the manufacturing innovation

655
00:31:11,800 --> 00:31:14,760
Speaker 2: happened or farming it started to hit white collar workers.

656
00:31:14,800 --> 00:31:17,680
Speaker 2: That's now everybody's screaming like, oh, can you believe this?

657
00:31:17,720 --> 00:31:20,160
Speaker 2: I'm like, yeah, I can, because it makes sense for

658
00:31:20,240 --> 00:31:22,719
Speaker 2: it to move up the food chain in that regard.

659
00:31:23,040 --> 00:31:26,080
Speaker 1: Let's talk about you going to San Francisco. One media

660
00:31:26,200 --> 00:31:29,360
Speaker 1: reporter who you refused to name in the book made

661
00:31:29,400 --> 00:31:31,120
Speaker 1: fun of you, mocked you said, what are you going

662
00:31:31,160 --> 00:31:33,320
Speaker 1: to be covering? Cbe radios? By the way, who is

663
00:31:33,360 --> 00:31:34,120
Speaker 1: that person cares?

664
00:31:34,200 --> 00:31:38,040
Speaker 2: I'm telling you, come on, why not because it's not

665
00:31:38,240 --> 00:31:40,520
Speaker 2: someone well known. If it was someone well known, it

666
00:31:40,640 --> 00:31:42,640
Speaker 2: was Katie Crook, I would say, so, thank you he

667
00:31:42,680 --> 00:31:46,160
Speaker 2: works for an online everybody I know, I know, I know,

668
00:31:46,400 --> 00:31:48,320
Speaker 2: all right, Well it's not someone well known enough. But

669
00:31:48,360 --> 00:31:51,040
Speaker 2: if it was like Jeff Zucker, I'd say it was Jeffson.

670
00:31:51,120 --> 00:31:52,760
Speaker 2: I might have to get you drunk so you can

671
00:31:52,800 --> 00:31:55,240
Speaker 2: tell me. All right, I'm telling So you go to

672
00:31:55,240 --> 00:31:57,600
Speaker 2: San Francisco and the way was very typical. He was

673
00:31:57,680 --> 00:32:00,880
Speaker 2: very typical of the attitude at the time that tech

674
00:32:00,960 --> 00:32:04,520
Speaker 2: didn't deserve its own that wasn't a legitimate beat for

675
00:32:04,600 --> 00:32:07,920
Speaker 2: a journalists right right when you got to the West coast.

676
00:32:08,200 --> 00:32:11,680
Speaker 2: The way you described these startup, big tech companies. You

677
00:32:11,800 --> 00:32:16,680
Speaker 2: talk about being like kindergarteners and playgrounds and pre stuff

678
00:32:16,720 --> 00:32:18,960
Speaker 2: and ping pong tables, which made me laugh because that

679
00:32:19,080 --> 00:32:20,880
Speaker 2: was sort of when I went to Yahoo.

680
00:32:20,920 --> 00:32:23,320
Speaker 1: I was like, this is such a weird vibe and

681
00:32:23,480 --> 00:32:27,640
Speaker 1: such a weird environment. Can you talk about that? The

682
00:32:27,800 --> 00:32:29,000
Speaker 1: vibe of these early.

683
00:32:28,880 --> 00:32:31,760
Speaker 2: Starts, I'm curious, did they make you do fun things?

684
00:32:31,840 --> 00:32:34,719
Speaker 2: Force fun? Did they force fun upon you? Really? They

685
00:32:34,760 --> 00:32:35,120
Speaker 2: have that.

686
00:32:35,440 --> 00:32:38,240
Speaker 1: They had the yodeling thing, which I just wouldn't do.

687
00:32:38,440 --> 00:32:41,560
Speaker 1: And as you said, that irritating exclamation.

688
00:32:41,240 --> 00:32:43,920
Speaker 2: Point, what is with the X stop of it? Did

689
00:32:43,920 --> 00:32:45,959
Speaker 2: they make you yodel. They tried to get you to yodel.

690
00:32:46,120 --> 00:32:49,840
Speaker 1: I didn't yodel. I just honestly coming there was just

691
00:32:49,920 --> 00:32:52,160
Speaker 1: such a culture shock for me, Caro. I just could

692
00:32:52,200 --> 00:32:55,200
Speaker 1: not really like, I didn't bleed purple as a lot

693
00:32:55,200 --> 00:32:57,280
Speaker 1: of folks that Yahoo did. And good good on them

694
00:32:57,320 --> 00:33:00,640
Speaker 1: if that's what they wanted. But why was it so juvenile?

695
00:33:00,720 --> 00:33:03,040
Speaker 1: And so many of these startups you talk about, Mark

696
00:33:03,120 --> 00:33:06,240
Speaker 1: intreeson and all these other places tell me about that.

697
00:33:06,720 --> 00:33:08,680
Speaker 2: Well, it was interesting because I think one of them

698
00:33:08,800 --> 00:33:10,960
Speaker 2: started doing it, which was Google, was the one that

699
00:33:11,080 --> 00:33:14,880
Speaker 2: really pioneered, like the multi the primary colors. If you

700
00:33:14,920 --> 00:33:17,720
Speaker 2: notice it, it's very juvenile. A lot of their parties

701
00:33:17,800 --> 00:33:21,520
Speaker 2: had slipping slides and bouncy houses and things like that,

702
00:33:21,560 --> 00:33:24,120
Speaker 2: and I was like, and it's sort of I gave

703
00:33:24,160 --> 00:33:25,920
Speaker 2: the example on the book is when I went to Excite,

704
00:33:25,920 --> 00:33:27,960
Speaker 2: which is now gone, but it was one of the.

705
00:33:27,960 --> 00:33:30,200
Speaker 1: Search when they had the red slide, the red slide.

706
00:33:30,240 --> 00:33:31,360
Speaker 2: Did you go down the red slide?

707
00:33:31,400 --> 00:33:33,120
Speaker 1: You might all, Hell, no, I didn't go down the

708
00:33:33,160 --> 00:33:35,000
Speaker 1: rest slide. I just remember it from the book.

709
00:33:35,120 --> 00:33:38,400
Speaker 2: Yeah. Yeah, So there was a red slide and it

710
00:33:38,440 --> 00:33:40,160
Speaker 2: was between the second and first of all, they had

711
00:33:40,200 --> 00:33:43,640
Speaker 2: a fake garage door so they could performatively be a garage,

712
00:33:43,720 --> 00:33:46,320
Speaker 2: and I was like, this isn't this is an office.

713
00:33:46,360 --> 00:33:48,880
Speaker 2: Why are we having a garage because it shows us?

714
00:33:49,640 --> 00:33:52,200
Speaker 2: Or I'm like, but it's not the actual garage door, right,

715
00:33:52,320 --> 00:33:55,400
Speaker 2: Like that was me. I was like I don't, okay, sure.

716
00:33:56,200 --> 00:33:58,240
Speaker 2: And they had the slide that they wanted between the

717
00:33:58,280 --> 00:34:00,760
Speaker 2: floors and they're like, you know, everyone gets on the slide.

718
00:34:00,800 --> 00:34:04,400
Speaker 2: I'm like, I hated slides at five years old. I'm not.

719
00:34:04,640 --> 00:34:06,960
Speaker 2: I'm like by this time, I'm in my late thirties.

720
00:34:07,000 --> 00:34:09,840
Speaker 2: I was like, I'm not getting on your brig and slide,

721
00:34:10,080 --> 00:34:12,640
Speaker 2: like forget it. And they were It was you know,

722
00:34:12,719 --> 00:34:15,719
Speaker 2: it's kind of forced fun. There was forced fun, like

723
00:34:15,960 --> 00:34:16,880
Speaker 2: forced joviality.

724
00:34:16,960 --> 00:34:18,000
Speaker 1: Why is that you think?

725
00:34:18,120 --> 00:34:20,200
Speaker 2: I think a lot of them didn't have social lives.

726
00:34:20,360 --> 00:34:22,239
Speaker 2: I didn't have real social lives. A lot of them.

727
00:34:22,400 --> 00:34:24,279
Speaker 2: You know a lot of the nerds really were like

728
00:34:25,320 --> 00:34:27,520
Speaker 2: nerding it out during high school. And I was like,

729
00:34:27,520 --> 00:34:29,680
Speaker 2: that was fun in sixth grade.

730
00:34:29,840 --> 00:34:31,719
Speaker 1: But I also think they were trying to show they

731
00:34:31,719 --> 00:34:35,520
Speaker 1: were so anti corporate or anti establishment, right, yes, yeah.

732
00:34:35,400 --> 00:34:37,800
Speaker 2: That was part. It was the clothing, you know, the clothing,

733
00:34:37,960 --> 00:34:41,680
Speaker 2: the soft clothing, the soft everything soft. All the chairs

734
00:34:41,680 --> 00:34:42,680
Speaker 2: were soft.

735
00:34:42,440 --> 00:34:46,040
Speaker 1: All the bad chairs. In fact, I laughed, and I

736
00:34:46,080 --> 00:34:48,880
Speaker 1: felt like you were channeling your own version of Jennifer

737
00:34:48,920 --> 00:34:51,880
Speaker 1: Melfie and the Sopranos. Do you write quote? Tech is

738
00:34:51,960 --> 00:34:55,200
Speaker 1: littered with men whose parents, typically fathers were either cruel

739
00:34:55,280 --> 00:34:57,400
Speaker 1: or absent. By the time they grew to be adults,

740
00:34:57,400 --> 00:35:00,680
Speaker 1: many were unhappy and often had some disc brontal tail

741
00:35:00,760 --> 00:35:04,720
Speaker 1: of being misunderstood before they were proved triumphantly right. Most

742
00:35:04,760 --> 00:35:08,359
Speaker 1: of all the damaged one shared one sat attribute. They

743
00:35:08,440 --> 00:35:12,440
Speaker 1: all seemed achingly lonely. More please, I agree.

744
00:35:12,480 --> 00:35:15,680
Speaker 2: Yeah, well, I'll never forget. I was at two things.

745
00:35:15,719 --> 00:35:17,920
Speaker 2: When I was at one of those vanity fair oscar

746
00:35:17,960 --> 00:35:20,279
Speaker 2: parties here, and there was a year they let all

747
00:35:20,320 --> 00:35:23,799
Speaker 2: the techies in Marissa was there. Was there a whole

748
00:35:23,840 --> 00:35:26,560
Speaker 2: bunch of them, and I was there to see the celebrities,

749
00:35:26,640 --> 00:35:28,960
Speaker 2: like I got invited. I'm like, yay, get to look

750
00:35:28,960 --> 00:35:32,240
Speaker 2: at celebrities. Fantastic. I'm going over to look at Daniel

751
00:35:32,280 --> 00:35:34,600
Speaker 2: day Lewis. I'm headed over that way. And they were

752
00:35:34,600 --> 00:35:36,520
Speaker 2: all like, Kara, hey, come talk to us. I'm like, no,

753
00:35:36,600 --> 00:35:38,040
Speaker 2: get the fuck away from me. I'm like, I don't

754
00:35:38,040 --> 00:35:39,640
Speaker 2: want to talk to you. I know, you like, I'm

755
00:35:39,680 --> 00:35:41,920
Speaker 2: not going to the celebrity people. Oh look it's Robert

756
00:35:41,960 --> 00:35:44,359
Speaker 2: de Niro. I'm going over to Robert de Niro. And

757
00:35:45,320 --> 00:35:49,000
Speaker 2: was wearing a set of Google glass remember they had

758
00:35:49,000 --> 00:35:49,799
Speaker 2: the first.

759
00:35:49,600 --> 00:35:53,000
Speaker 1: Oh yeah, brand who the founder of one.

760
00:35:52,840 --> 00:35:55,760
Speaker 2: Of the founders, right, there's two co founders. Larry Page

761
00:35:55,800 --> 00:35:57,719
Speaker 2: is the other one. And he was wearing it at

762
00:35:57,719 --> 00:36:01,480
Speaker 2: the party. And he's like, no one's talking to me.

763
00:36:01,920 --> 00:36:04,360
Speaker 2: To me, and I go, well, take that off your face.

764
00:36:04,400 --> 00:36:07,000
Speaker 2: They don't like pictures that they don't know are being taken.

765
00:36:07,080 --> 00:36:11,000
Speaker 2: It's not cool here among these people. Like it's cool elsewhere,

766
00:36:11,000 --> 00:36:13,840
Speaker 2: but it's not cool here. And he's like, well should

767
00:36:13,880 --> 00:36:15,480
Speaker 2: I talk to him about And I said, tell them

768
00:36:15,480 --> 00:36:18,160
Speaker 2: you're a billionaire. They do like money, they do these

769
00:36:18,200 --> 00:36:20,800
Speaker 2: people seem to like and maybe you'll pay for a movie.

770
00:36:20,920 --> 00:36:22,799
Speaker 2: I don't know that'll work. I'm sure one of these

771
00:36:22,840 --> 00:36:23,560
Speaker 2: people will talk.

772
00:36:23,440 --> 00:36:25,680
Speaker 1: To you for They're just very socially awkward.

773
00:36:25,560 --> 00:36:27,799
Speaker 2: Right awkward, And so that was part of it. And

774
00:36:27,840 --> 00:36:33,680
Speaker 2: then there was always like it was they seemed, you know,

775
00:36:34,040 --> 00:36:35,839
Speaker 2: not all of them had bad parents, by the way,

776
00:36:35,920 --> 00:36:37,840
Speaker 2: not all of them. But it's interesting. Steve, you know,

777
00:36:37,840 --> 00:36:41,400
Speaker 2: Steve Jobs was adopted, I was fostered, and then his

778
00:36:41,520 --> 00:36:43,920
Speaker 2: parents went on to have another kid and didn't come

779
00:36:43,960 --> 00:36:47,560
Speaker 2: back and get him. Larry Ellison, same thing, you know,

780
00:36:47,600 --> 00:36:50,280
Speaker 2: Elon's obviously, that's the famous story of the bad Dad.

781
00:36:50,840 --> 00:36:54,359
Speaker 2: And you know, they all had kind of social awkward

782
00:36:54,560 --> 00:36:58,440
Speaker 2: issues kind of thing, and so you'd feel like they

783
00:36:58,880 --> 00:37:01,600
Speaker 2: didn't know quite how to talk to people, some of them,

784
00:37:01,600 --> 00:37:03,839
Speaker 2: and that was lots of reasons. Some of them are

785
00:37:03,840 --> 00:37:06,320
Speaker 2: on the spectrum. Obviously it's a famous thing in tech,

786
00:37:07,160 --> 00:37:10,080
Speaker 2: but they also seemed to I don't know, it just

787
00:37:10,120 --> 00:37:11,760
Speaker 2: felt like I felt like I was in a constant

788
00:37:11,800 --> 00:37:15,680
Speaker 2: janis Ian song, like they got picked lastic basketball or something,

789
00:37:16,239 --> 00:37:19,600
Speaker 2: you know, and it was it was interesting to watch, No,

790
00:37:19,719 --> 00:37:21,800
Speaker 2: not all of them. Some of them, you know, Brian

791
00:37:21,840 --> 00:37:24,760
Speaker 2: Chesky from there maybe is quite witty and funny.

792
00:37:24,480 --> 00:37:26,760
Speaker 1: And I think had, I mean, from what I understand,

793
00:37:26,760 --> 00:37:29,680
Speaker 1: a wonderful upbringing, close to his family.

794
00:37:29,360 --> 00:37:32,040
Speaker 2: Family and wonderful. Let me just say, best parents of

795
00:37:32,080 --> 00:37:35,680
Speaker 2: the Internet are Brian Chesky's parents. And one of the

796
00:37:35,800 --> 00:37:37,440
Speaker 2: things that they also had is if they had an

797
00:37:37,440 --> 00:37:41,040
Speaker 2: interest outside of tech. Some of them were just totally

798
00:37:41,080 --> 00:37:44,880
Speaker 2: tech focused, so say, see jobs, he loved design, he

799
00:37:44,920 --> 00:37:48,680
Speaker 2: loved fonts, he was very well read. He had cultural

800
00:37:48,719 --> 00:37:52,520
Speaker 2: references while others didn't, and so that was nice. But

801
00:37:52,560 --> 00:37:55,560
Speaker 2: then others didn't check. That's all they could talk about

802
00:37:55,600 --> 00:37:58,040
Speaker 2: twenty four to seven was tech right, and they didn't

803
00:37:58,040 --> 00:38:01,600
Speaker 2: have other interests or their interests were just awkward. I

804
00:38:01,600 --> 00:38:02,480
Speaker 2: don't you know what I mean.

805
00:38:02,640 --> 00:38:04,400
Speaker 1: I'm not going to make you tell the story of

806
00:38:04,440 --> 00:38:07,239
Speaker 1: the baby shower, but folks, the book is worth it

807
00:38:07,400 --> 00:38:10,759
Speaker 1: just to read about the baby shower and what the

808
00:38:10,880 --> 00:38:14,759
Speaker 1: host expected their guests to wear. And thankfully that was

809
00:38:14,800 --> 00:38:16,399
Speaker 1: almost the first chapter of the book.

810
00:38:16,440 --> 00:38:17,920
Speaker 2: But I decided to go more serious.

811
00:38:18,000 --> 00:38:21,560
Speaker 1: That was so funny that pint. It's such a picture

812
00:38:21,600 --> 00:38:23,120
Speaker 1: for me, and I love the fact that you and

813
00:38:23,160 --> 00:38:27,520
Speaker 1: Gavin Newsom refused to go along with the costume idea.

814
00:38:28,200 --> 00:38:29,120
Speaker 2: But you get a nice suit on.

815
00:38:29,520 --> 00:38:30,920
Speaker 1: Yeah, yeah, do you like?

816
00:38:31,960 --> 00:38:34,080
Speaker 2: I do very much. So I think he's I thought

817
00:38:34,080 --> 00:38:36,240
Speaker 2: he was terrific this weekend on Meet the Press.

818
00:38:36,280 --> 00:38:37,560
Speaker 1: Do you think he'd be a good president?

819
00:38:37,680 --> 00:38:39,560
Speaker 2: I do. I do. I think he would. He's very

820
00:38:39,640 --> 00:38:41,640
Speaker 2: you know, he's a he's got a lot, you know,

821
00:38:41,760 --> 00:38:44,520
Speaker 2: like he's a man who's been through difficult times and

822
00:38:44,680 --> 00:38:47,919
Speaker 2: understands them. I think he's I think he suffers from

823
00:38:48,000 --> 00:38:51,160
Speaker 2: he's so handsome and smooth that people don't trust him.

824
00:38:51,200 --> 00:38:53,560
Speaker 2: I think that's I do. I think. Look, here's why

825
00:38:53,600 --> 00:38:56,000
Speaker 2: I like. The main reason like Gavin is among many

826
00:38:56,040 --> 00:38:59,440
Speaker 2: because he's really intelligent and smart and sharp, is because

827
00:38:59,760 --> 00:39:02,000
Speaker 2: when he passed the gay marriage thing when he was

828
00:39:02,600 --> 00:39:05,640
Speaker 2: in San Francisco. I have to tell you, he did

829
00:39:05,640 --> 00:39:07,839
Speaker 2: not have to do that right, and it really hurt.

830
00:39:07,920 --> 00:39:09,920
Speaker 2: He was on the way up on the political thing.

831
00:39:09,960 --> 00:39:14,600
Speaker 2: He was sort of riding high and he was laid

832
00:39:14,640 --> 00:39:17,719
Speaker 2: low by doing that. And I don't think there's been

833
00:39:17,760 --> 00:39:20,880
Speaker 2: another politician who took a risk like that on something

834
00:39:20,920 --> 00:39:24,239
Speaker 2: that wasn't and that I really appreciated that. I nearly

835
00:39:24,280 --> 00:39:26,080
Speaker 2: the name one of my kids Gavin, because I was like,

836
00:39:26,239 --> 00:39:28,920
Speaker 2: nobody did that, Like no stray guy who was on

837
00:39:28,960 --> 00:39:32,120
Speaker 2: his way to the top floor of the political spectrum

838
00:39:32,120 --> 00:39:35,120
Speaker 2: did that, and he suffered for many, many years for

839
00:39:35,200 --> 00:39:35,600
Speaker 2: doing so.

840
00:39:39,239 --> 00:39:41,360
Speaker 1: We have to take a quick break. But after we do,

841
00:39:42,000 --> 00:39:45,759
Speaker 1: why so few tech moguls saw the harmful effects of

842
00:39:45,840 --> 00:40:00,839
Speaker 1: what they were creating. We're back with Kara Swisher. You know,

843
00:40:01,280 --> 00:40:04,359
Speaker 1: you'd write about a lot of these fascinating figures who

844
00:40:04,360 --> 00:40:07,520
Speaker 1: have become, in a way, the rock stars of modern

845
00:40:07,600 --> 00:40:09,640
Speaker 1: life in terms of the business world.

846
00:40:09,680 --> 00:40:10,600
Speaker 2: Carpet rock stars.

847
00:40:10,800 --> 00:40:15,640
Speaker 1: Yeah, and you knew early on the unintended consequences of

848
00:40:15,680 --> 00:40:20,160
Speaker 1: this huge transition into the digital age. But I'm curious,

849
00:40:20,200 --> 00:40:22,680
Speaker 1: do you think that some of these other folks, like

850
00:40:22,800 --> 00:40:26,200
Speaker 1: Mark Zuckerberg, they just didn't think about it. I mean,

851
00:40:26,320 --> 00:40:29,600
Speaker 1: I know that their motto has moved fast and break things,

852
00:40:29,680 --> 00:40:31,600
Speaker 1: or was and you write a lot about it that

853
00:40:32,440 --> 00:40:37,080
Speaker 1: was it arrogance or willful ignorance that they never contemplated that,

854
00:40:37,480 --> 00:40:39,879
Speaker 1: or was it just like we're just going to make

855
00:40:40,000 --> 00:40:41,360
Speaker 1: more and more and more money.

856
00:40:41,960 --> 00:40:43,799
Speaker 2: Well, I think it was the reason the first line

857
00:40:43,840 --> 00:40:46,040
Speaker 2: of the book is it was capitalism after all, is

858
00:40:46,080 --> 00:40:47,839
Speaker 2: because that's the first line of the book. I want

859
00:40:47,880 --> 00:40:50,279
Speaker 2: to point out this was about nothing but money, Like,

860
00:40:50,360 --> 00:40:52,759
Speaker 2: let's be clear. And I think they would have liked

861
00:40:52,760 --> 00:40:55,799
Speaker 2: they had a very again performative nature of the many

862
00:40:55,840 --> 00:40:58,759
Speaker 2: performative nature things was we're in it for everybody, We're

863
00:40:58,760 --> 00:41:02,480
Speaker 2: here to save humanity. And initially it's very attractive and

864
00:41:02,520 --> 00:41:05,000
Speaker 2: then it's like, wait, that is so narcissistic. You know,

865
00:41:05,080 --> 00:41:07,040
Speaker 2: I think it sort of reached his height when I

866
00:41:07,080 --> 00:41:10,560
Speaker 2: was interviewing Elon Musk and he said, this was twenty

867
00:41:10,960 --> 00:41:13,840
Speaker 2: eighteen maybe, and I was at headquarters of Tesla, and

868
00:41:13,840 --> 00:41:16,000
Speaker 2: he had just gone through a very difficult period for Tesla.

869
00:41:16,000 --> 00:41:18,520
Speaker 2: It almost closed down, and he'd gotten a government loan

870
00:41:18,640 --> 00:41:21,000
Speaker 2: and they had pushed their way through, as many even

871
00:41:21,080 --> 00:41:23,600
Speaker 2: makers are doing. Now there's a valley of death there.

872
00:41:24,239 --> 00:41:26,239
Speaker 2: And he had, you know, he had at some emotional

873
00:41:26,280 --> 00:41:28,359
Speaker 2: times that There was a very famous interview he did

874
00:41:28,360 --> 00:41:29,719
Speaker 2: with the New York Times where he seemed like he

875
00:41:29,760 --> 00:41:32,000
Speaker 2: was crying. He denies he was crying, but seemed like

876
00:41:32,040 --> 00:41:34,759
Speaker 2: he was crying. I could see it. And he said

877
00:41:34,760 --> 00:41:37,239
Speaker 2: to me in this interviews something along the lines of

878
00:41:37,320 --> 00:41:39,560
Speaker 2: if Tesla. I thought, I said, why are you so

879
00:41:39,640 --> 00:41:41,799
Speaker 2: emotional about this? And indeed the whole I'm sleeping on

880
00:41:41,800 --> 00:41:45,080
Speaker 2: the factory floor, which is like such a drama queen, like,

881
00:41:45,160 --> 00:41:46,960
Speaker 2: come on, there's you can be in a bed. It

882
00:41:46,960 --> 00:41:48,960
Speaker 2: doesn't take that long to get to a bed like

883
00:41:49,040 --> 00:41:51,040
Speaker 2: he has to be. If he's not there, the entire

884
00:41:51,120 --> 00:41:54,600
Speaker 2: thing falls upod. Oh my god. And I remember thinking

885
00:41:54,600 --> 00:41:56,080
Speaker 2: that at the time, and I just let him talk

886
00:41:56,160 --> 00:41:59,680
Speaker 2: and he goes, if I thought, if Tesla didn't make it,

887
00:42:00,080 --> 00:42:03,240
Speaker 2: humanity was doomed. That's literally what he said, Like essentially,

888
00:42:03,360 --> 00:42:05,239
Speaker 2: I forget the cold quote, but it was like that,

889
00:42:05,280 --> 00:42:08,160
Speaker 2: and I was like, what they really I don't know.

890
00:42:08,600 --> 00:42:11,520
Speaker 2: Seems like if you go, it doesn't really matter, like

891
00:42:11,640 --> 00:42:15,080
Speaker 2: you're not the lynchman. And it wasn't until just recently

892
00:42:15,440 --> 00:42:18,160
Speaker 2: when I was interviewing Ben Mezrich, who did social network.

893
00:42:18,160 --> 00:42:20,520
Speaker 2: He just wrote a book about Twitter, where I kept thinking,

894
00:42:20,640 --> 00:42:23,680
Speaker 2: is he just a giant narcissist? And now I'm a

895
00:42:23,760 --> 00:42:27,560
Speaker 2: levolent narcissist? And Ben said he thinks everything is a

896
00:42:27,640 --> 00:42:30,360
Speaker 2: video game. And he has talked to me about simulation.

897
00:42:30,560 --> 00:42:33,160
Speaker 2: You know. Elon has this whole theory like a lot

898
00:42:33,200 --> 00:42:35,000
Speaker 2: of them, about we're in a simulation and none of

899
00:42:35,080 --> 00:42:40,480
Speaker 2: us is real, and he is the main player. He's

900
00:42:40,520 --> 00:42:43,000
Speaker 2: the it's called ready Player one or whatever. And I

901
00:42:43,000 --> 00:42:46,520
Speaker 2: don't play video games, but it makes perfect sense. Oh,

902
00:42:46,680 --> 00:42:48,560
Speaker 2: so the rest of us are fungible. That's why he

903
00:42:48,600 --> 00:42:52,320
Speaker 2: can say nasty things to everybody because he's the main player,

904
00:42:52,360 --> 00:42:54,439
Speaker 2: and so he can shoot anyone he wants. He can,

905
00:42:54,680 --> 00:42:59,440
Speaker 2: like his version of this rime. And I don't play them,

906
00:42:59,440 --> 00:43:01,799
Speaker 2: but I know enough about them, but that everybody is,

907
00:43:01,960 --> 00:43:03,960
Speaker 2: you know, when my kids, there was that one game

908
00:43:04,000 --> 00:43:06,320
Speaker 2: that was I can't remember one of them, one of

909
00:43:06,360 --> 00:43:07,960
Speaker 2: the shoot them up games. I wouldn't let my kids

910
00:43:08,000 --> 00:43:10,440
Speaker 2: call up duty or something. One of them. No, it

911
00:43:10,520 --> 00:43:12,480
Speaker 2: was the city one, the one in the city anyway,

912
00:43:12,520 --> 00:43:14,200
Speaker 2: I don't know, I don't play them. And there was

913
00:43:14,239 --> 00:43:17,319
Speaker 2: a point where they were shooting women. It was, you know,

914
00:43:17,920 --> 00:43:19,759
Speaker 2: they were shooting women or they could shoot women or

915
00:43:19,800 --> 00:43:21,400
Speaker 2: something like that, which I was like, I don't like

916
00:43:21,440 --> 00:43:23,640
Speaker 2: them shooting anybody, but I guess it's a shooting game.

917
00:43:24,080 --> 00:43:25,799
Speaker 2: And they were like, well, you know, mom, you can't

918
00:43:25,800 --> 00:43:28,200
Speaker 2: shoot people without guns, and I was like, but you

919
00:43:28,239 --> 00:43:30,880
Speaker 2: can shoot them. It was just like this ridiculous argument

920
00:43:31,000 --> 00:43:33,560
Speaker 2: about it, and what it created in a lot of

921
00:43:33,680 --> 00:43:36,160
Speaker 2: particularly men, was this idea that they're the hero of

922
00:43:36,160 --> 00:43:39,680
Speaker 2: the story, right, except the story is pretty ugly. Right.

923
00:43:39,760 --> 00:43:41,960
Speaker 2: What if you're not the hero, you're the villain of

924
00:43:42,000 --> 00:43:42,520
Speaker 2: the story.

925
00:43:43,080 --> 00:43:45,880
Speaker 1: Is that why they cloaked everything in this notion that

926
00:43:45,920 --> 00:43:47,759
Speaker 1: they're saving humanity.

927
00:43:47,560 --> 00:43:49,880
Speaker 2: Saving humanity? I was like, we don't need you to

928
00:43:49,960 --> 00:43:52,520
Speaker 2: save us, thank you like that. I don't know why

929
00:43:52,560 --> 00:43:55,520
Speaker 2: they needed to say that, you know instead of can

930
00:43:55,560 --> 00:43:58,200
Speaker 2: you imagine, like I don't know, Like you know, an

931
00:43:58,200 --> 00:44:01,600
Speaker 2: insurance company, you go to save humanity by giving you

932
00:44:02,760 --> 00:44:06,040
Speaker 2: a policy, like will they'd be laughed out of the room,

933
00:44:06,120 --> 00:44:07,880
Speaker 2: right or a Walstree person. I'm here to save you

934
00:44:07,920 --> 00:44:09,920
Speaker 2: humanity by giving you a checking account. And if you

935
00:44:09,920 --> 00:44:12,520
Speaker 2: don't get a checking account, all of commerce will stop.

936
00:44:12,880 --> 00:44:16,359
Speaker 2: Like that's kind of technically true. But like you're making

937
00:44:16,400 --> 00:44:19,359
Speaker 2: a car right right, You're making a dating service, you're

938
00:44:19,400 --> 00:44:23,280
Speaker 2: making a you know, You're just you're just making something

939
00:44:23,400 --> 00:44:26,200
Speaker 2: and for some reason they have to make it more

940
00:44:26,280 --> 00:44:28,239
Speaker 2: vaunted than that, and that has to do with their

941
00:44:28,280 --> 00:44:31,240
Speaker 2: own personal traumas. I think in a lot of ways.

942
00:44:31,400 --> 00:44:33,279
Speaker 1: Who do you think is going to be upset with

943
00:44:33,320 --> 00:44:36,080
Speaker 1: this book? I mean, you write about Jeff Bezos, you

944
00:44:36,080 --> 00:44:39,640
Speaker 1: write about obviously Mark Zuckerberg. You say, from the moment

945
00:44:39,719 --> 00:44:41,800
Speaker 1: we met, Mark seemed to think of me and maybe

946
00:44:41,840 --> 00:44:43,399
Speaker 1: all the press as an adversary.

947
00:44:43,880 --> 00:44:44,279
Speaker 2: He did.

948
00:44:44,480 --> 00:44:46,439
Speaker 1: The first thing he said to you was I heard

949
00:44:46,520 --> 00:44:47,600
Speaker 1: you think I'm an asshole.

950
00:44:48,080 --> 00:44:51,080
Speaker 2: He did say that to me. Yes, I mean he

951
00:44:51,200 --> 00:44:53,319
Speaker 2: was insecure, and yeah I could see it he was.

952
00:44:53,400 --> 00:44:55,919
Speaker 2: He had a kind of a jerky reputation. I happen

953
00:44:56,000 --> 00:44:58,400
Speaker 2: to like Mark in that compared to many of the

954
00:44:58,400 --> 00:45:01,120
Speaker 2: people I covered, he's actually try It's just that he

955
00:45:01,160 --> 00:45:04,320
Speaker 2: shouldn't have this much responsibility, and he's made a series

956
00:45:04,360 --> 00:45:07,359
Speaker 2: of mistakes that at some point he really needs to stop, right,

957
00:45:07,520 --> 00:45:09,880
Speaker 2: Like he's gotten so many at bats, and he keeps

958
00:45:10,120 --> 00:45:11,080
Speaker 2: what do you.

959
00:45:11,000 --> 00:45:12,840
Speaker 1: Think it's the biggest mistake he's made.

960
00:45:13,560 --> 00:45:16,320
Speaker 2: He doesn't have a sense that he perhaps has designed

961
00:45:16,320 --> 00:45:18,920
Speaker 2: it in a way that's damaging. Like, I get the

962
00:45:18,920 --> 00:45:22,800
Speaker 2: pluses of it. I get. I'm not averse to saying

963
00:45:22,840 --> 00:45:25,359
Speaker 2: a lot of it is really cool. What I am

964
00:45:25,400 --> 00:45:28,440
Speaker 2: averse to saying is, you know, there's been a rise

965
00:45:28,560 --> 00:45:32,239
Speaker 2: in the self esteem issues around teenage girls at the

966
00:45:32,280 --> 00:45:34,640
Speaker 2: same time as the rise of social media. Do you

967
00:45:34,640 --> 00:45:38,160
Speaker 2: think it's Oh, you can't prove it. I'm like, you

968
00:45:38,160 --> 00:45:41,160
Speaker 2: know what, everyone suddenly got fat after Twinkies. I can't

969
00:45:41,200 --> 00:45:43,480
Speaker 2: prove it, but I believe it's because of Twinkies, like

970
00:45:43,520 --> 00:45:46,239
Speaker 2: you know what I mean, or processed foods, or there's

971
00:45:46,239 --> 00:45:49,239
Speaker 2: been a sudden rising cancer here because and you're like,

972
00:45:49,920 --> 00:45:52,880
Speaker 2: I can make you can make some very what the

973
00:45:52,880 --> 00:45:55,200
Speaker 2: internet has done to us the way they've designed it

974
00:45:55,280 --> 00:45:59,759
Speaker 2: as a casino has made us addicted, and it's made

975
00:45:59,800 --> 00:46:02,400
Speaker 2: us made it necessary, so we can't live without it.

976
00:46:02,440 --> 00:46:05,000
Speaker 2: And the COVID pushed this through really quickly, like that

977
00:46:05,040 --> 00:46:08,400
Speaker 2: we needed it. So you can't live without it, because

978
00:46:08,400 --> 00:46:12,680
Speaker 2: you really can't because of work or whatever, communications everything else.

979
00:46:13,400 --> 00:46:16,719
Speaker 2: You also can't get it, can't stop looking at it.

980
00:46:16,719 --> 00:46:19,480
Speaker 2: It's really Andris Don Harris, who I think you've interviewed,

981
00:46:19,840 --> 00:46:22,160
Speaker 2: has done a lot of things on this. He was

982
00:46:22,680 --> 00:46:24,600
Speaker 2: a Google product manager.

983
00:46:24,480 --> 00:46:26,560
Speaker 1: I know, Tristan, Yeah, yeah, he did.

984
00:46:26,680 --> 00:46:28,520
Speaker 2: You know, he was a product manager. He knew what

985
00:46:28,520 --> 00:46:31,839
Speaker 2: he was making. He was making a casino. And yes,

986
00:46:32,000 --> 00:46:34,720
Speaker 2: push that button. Push you want to push that button?

987
00:46:34,800 --> 00:46:40,040
Speaker 2: And anyone with even five seconds on TikTok gets it.

988
00:46:40,160 --> 00:46:42,840
Speaker 2: You can't get out. It's really hard to look away.

989
00:46:43,239 --> 00:46:46,880
Speaker 1: Not only addicted Cara, but also obviously more more and

990
00:46:46,960 --> 00:46:50,879
Speaker 1: more tribal and the country so polarized. And you know,

991
00:46:51,000 --> 00:46:54,200
Speaker 1: getting back to your original calling as a journalist, and

992
00:46:54,280 --> 00:46:57,799
Speaker 1: something that I've done for many years is it is

993
00:46:59,080 --> 00:47:04,040
Speaker 1: it is very diff difficult to convince people of the

994
00:47:04,120 --> 00:47:10,080
Speaker 1: facts or to even yeah, even have them open their

995
00:47:10,160 --> 00:47:12,080
Speaker 1: eyes to other issues.

996
00:47:12,400 --> 00:47:13,440
Speaker 2: Well that's propaganda.

997
00:47:13,560 --> 00:47:16,000
Speaker 1: Yeah, Well I did an interview with Mike McFall, you know,

998
00:47:16,040 --> 00:47:19,600
Speaker 1: the former ambassador to Rush, all about navalny and about

999
00:47:19,800 --> 00:47:24,400
Speaker 1: a to Ukraine. The comments were, so, you know, why

1000
00:47:24,400 --> 00:47:26,720
Speaker 1: aren't you talking about the border? Why aren't you talking

1001
00:47:26,719 --> 00:47:29,160
Speaker 1: about the border? And you know that that's what people

1002
00:47:29,520 --> 00:47:32,479
Speaker 1: are reading about hearing on Fox News twenty four to seven.

1003
00:47:32,520 --> 00:47:35,080
Speaker 1: I know your mom's a big if Fox News aficionado,

1004
00:47:35,880 --> 00:47:42,279
Speaker 1: but this constant flow of information is basically altering their

1005
00:47:42,320 --> 00:47:43,680
Speaker 1: brain chemistry, right.

1006
00:47:43,760 --> 00:47:44,400
Speaker 2: I would agree.

1007
00:47:44,760 --> 00:47:47,520
Speaker 1: And you call an engagement through enragement. I use that

1008
00:47:47,600 --> 00:47:48,160
Speaker 1: all the time.

1009
00:47:48,440 --> 00:47:50,160
Speaker 2: Thank you good. It's a really good one. One of

1010
00:47:50,200 --> 00:47:51,880
Speaker 2: the things that joins me crazy. I mean, I'll use

1011
00:47:51,880 --> 00:47:53,359
Speaker 2: my mom as an example. I think I've told you

1012
00:47:53,400 --> 00:47:55,880
Speaker 2: this is I did an interview with Hillary Clinton. I've

1013
00:47:55,920 --> 00:48:00,319
Speaker 2: done several of them. You have done many. And my

1014
00:48:00,360 --> 00:48:02,160
Speaker 2: mom called me the next day and she goes, oh,

1015
00:48:02,320 --> 00:48:04,640
Speaker 2: now this was Fox News. Well she's not an online peruse.

1016
00:48:04,680 --> 00:48:07,160
Speaker 2: It doesn't matter. It's the same. It's a repetitive nature

1017
00:48:07,200 --> 00:48:11,719
Speaker 2: of addictive things media. And she said, oh, I can't

1018
00:48:11,760 --> 00:48:14,040
Speaker 2: believe but Hillary said about people like me. And I

1019
00:48:14,120 --> 00:48:15,080
Speaker 2: was like, what did she say?

1020
00:48:15,280 --> 00:48:16,600
Speaker 1: The deplorables thing? No?

1021
00:48:16,760 --> 00:48:18,440
Speaker 2: I thought it was something else. I had just done

1022
00:48:18,440 --> 00:48:21,920
Speaker 2: an interview. It had dropped. I thought she had tweeted something.

1023
00:48:22,040 --> 00:48:24,400
Speaker 2: I don't know. She sometimes she's very clever on the twitter,

1024
00:48:24,520 --> 00:48:26,680
Speaker 2: and so I said, oh, what did she say? And

1025
00:48:26,680 --> 00:48:28,440
Speaker 2: my mom started repeating it back to me, and I

1026
00:48:28,480 --> 00:48:31,400
Speaker 2: was like, that sounds familiar, but not right. It's like

1027
00:48:31,680 --> 00:48:34,560
Speaker 2: it's a twisted version of my interview. And I realized

1028
00:48:34,560 --> 00:48:37,440
Speaker 2: they had taken my interview and restated it in an

1029
00:48:37,239 --> 00:48:41,000
Speaker 2: inaccurate way, but they used pieces of it to create

1030
00:48:41,040 --> 00:48:44,439
Speaker 2: a building that wasn't what I built, right, And I said, Mom,

1031
00:48:44,480 --> 00:48:47,200
Speaker 2: that was my interview. She didn't say that. She goes, oh,

1032
00:48:47,560 --> 00:48:52,080
Speaker 2: she did, and I was like, no, she didn't. I

1033
00:48:52,120 --> 00:48:55,120
Speaker 2: did the interview. I'm your daughter, and I'm telling you

1034
00:48:55,840 --> 00:48:58,680
Speaker 2: she didn't. And she's like, oh, you're wrong. She did.

1035
00:48:58,719 --> 00:49:00,600
Speaker 2: And I'm like, all right, this is what we're gonna do.

1036
00:49:00,719 --> 00:49:03,880
Speaker 2: You're gonna go listen to it and then you're gonna

1037
00:49:03,880 --> 00:49:06,799
Speaker 2: call me back. And she went to listen to it.

1038
00:49:06,800 --> 00:49:11,080
Speaker 2: She called me back. She goes, Okay, she didn't say it,

1039
00:49:11,160 --> 00:49:14,000
Speaker 2: but you know her emails. And I literally was like,

1040
00:49:14,280 --> 00:49:17,560
Speaker 2: oh right then, and you know, Jimmy Kimmel did it

1041
00:49:17,560 --> 00:49:20,360
Speaker 2: the other day where they said something Trump said and

1042
00:49:20,400 --> 00:49:23,320
Speaker 2: said it was Biden and then the people were like, yes, yes,

1043
00:49:23,400 --> 00:49:26,000
Speaker 2: that is a terrible bleach. Are you kidding? What an idiot?

1044
00:49:26,360 --> 00:49:28,200
Speaker 2: And then they goes, oh, I'm sorry that was Trump

1045
00:49:28,280 --> 00:49:30,319
Speaker 2: said that, and they're like, well the man has the

1046
00:49:30,360 --> 00:49:35,279
Speaker 2: point like second a second later, and he did this

1047
00:49:35,320 --> 00:49:37,520
Speaker 2: with like ten different things, and You're sitting there like,

1048
00:49:39,040 --> 00:49:41,759
Speaker 2: what's And I don't think these people had any They

1049
00:49:41,800 --> 00:49:44,520
Speaker 2: weren't trying to be tricky. They just they their brain

1050
00:49:44,920 --> 00:49:47,640
Speaker 2: chemistry was they couldn't do it. And you know, it

1051
00:49:47,760 --> 00:49:51,520
Speaker 2: was really I just was. I'm always astonished by it

1052
00:49:51,600 --> 00:49:54,040
Speaker 2: how well or something it works because it's an online medium,

1053
00:49:54,080 --> 00:49:57,040
Speaker 2: is an addictive it's like, you know, Mark Benioff called

1054
00:49:57,040 --> 00:49:59,399
Speaker 2: it cigarettes. I think when he did it at the time,

1055
00:49:59,440 --> 00:50:01,360
Speaker 2: people were losing their minds when you told me that.

1056
00:50:01,520 --> 00:50:04,200
Speaker 2: But I'm like, yeah, you're pretty pretty much right.

1057
00:50:04,360 --> 00:50:08,759
Speaker 1: So what so what? Yeah? What is the solution a

1058
00:50:09,120 --> 00:50:16,000
Speaker 1: for polarization and media diets that really convince people of

1059
00:50:16,080 --> 00:50:20,560
Speaker 1: things that aren't true or make them hold fast to

1060
00:50:20,600 --> 00:50:24,360
Speaker 1: these certain positions like your mom did, And what do

1061
00:50:24,400 --> 00:50:26,839
Speaker 1: we do about the future of media. Let's start with

1062
00:50:26,960 --> 00:50:30,080
Speaker 1: the first question. I mean, what can be done. I

1063
00:50:30,160 --> 00:50:32,759
Speaker 1: was on the Aspen Commission for Disinformation. We made all

1064
00:50:32,800 --> 00:50:37,120
Speaker 1: these recommendations. We asked for more transparency, you know, for

1065
00:50:37,400 --> 00:50:42,040
Speaker 1: Facebook and algorithm transparency. Yeah, exactly. Well actually, you know,

1066
00:50:42,320 --> 00:50:45,840
Speaker 1: not even algorithm transparency, Kara, just like the inner working.

1067
00:50:45,960 --> 00:50:51,400
Speaker 1: So researchers could really study the phenomenon that we're talking about,

1068
00:50:51,760 --> 00:50:54,880
Speaker 1: or how these places work and how they distribute and

1069
00:50:54,960 --> 00:51:00,960
Speaker 1: amplify certain information. But it seems like nothing has been done.

1070
00:51:01,200 --> 00:51:03,319
Speaker 2: Why should they why? Because are you know at this

1071
00:51:03,400 --> 00:51:07,960
Speaker 2: point these companies are money making, shareholder focused companies. Let's

1072
00:51:08,000 --> 00:51:09,839
Speaker 2: just be honest about it. That's what they're doing. And

1073
00:51:09,880 --> 00:51:12,919
Speaker 2: they control everything. By the way, they're the richest they've

1074
00:51:12,960 --> 00:51:14,960
Speaker 2: net looked in videos now at two trillion dollars a

1075
00:51:15,000 --> 00:51:18,760
Speaker 2: mixed ships it's like two trillion dollars Apples trillions of dollars.

1076
00:51:18,800 --> 00:51:22,759
Speaker 2: Microsoft they own AI because it's so expensive where we're

1077
00:51:22,800 --> 00:51:26,400
Speaker 2: going next. So they have unlimited funds and no consequences

1078
00:51:26,640 --> 00:51:29,000
Speaker 2: for anything they do, and we have we have left.

1079
00:51:29,080 --> 00:51:32,040
Speaker 2: We have that that now to me, they're like, aren't

1080
00:51:32,080 --> 00:51:33,480
Speaker 2: you mad at the tech companies? I'm like, you know

1081
00:51:33,560 --> 00:51:35,719
Speaker 2: what they're doing? What they do? Like this is how

1082
00:51:35,719 --> 00:51:38,960
Speaker 2: they they're sharks, Sharks are sharks, gonna make shark you

1083
00:51:38,960 --> 00:51:41,319
Speaker 2: know kind of thing. At this point, we need to

1084
00:51:41,360 --> 00:51:43,600
Speaker 2: do something about the sharks, or you put them in

1085
00:51:43,600 --> 00:51:45,919
Speaker 2: a pen, or figure out a way to have shark

1086
00:51:45,960 --> 00:51:49,360
Speaker 2: repellent or something. But it's up to our elected officials

1087
00:51:49,400 --> 00:51:51,920
Speaker 2: now to do something when they happen. They just haven't,

1088
00:51:52,360 --> 00:51:53,120
Speaker 2: will they ever?

1089
00:51:53,480 --> 00:51:54,960
Speaker 1: And if not? Why?

1090
00:51:55,600 --> 00:51:59,719
Speaker 2: Money? Money, the deleterious effects of money on politics. Who

1091
00:51:59,800 --> 00:52:02,480
Speaker 2: has the most money? Tech companies? Right? That's one. Two

1092
00:52:02,640 --> 00:52:06,719
Speaker 2: is the partisanship that was created by these these tech companies,

1093
00:52:06,760 --> 00:52:09,680
Speaker 2: I think, in part not completely has now been so

1094
00:52:09,719 --> 00:52:12,000
Speaker 2: they can't agree on anything. They Instead they want to

1095
00:52:12,000 --> 00:52:13,759
Speaker 2: go dunk on Twitter. You think you're gonna get any

1096
00:52:13,760 --> 00:52:16,759
Speaker 2: cooperation chat Marjorie Taylor Green, I'm sorry, good luck. Talk

1097
00:52:16,760 --> 00:52:19,440
Speaker 2: about someone who's been totally addled by the internet and

1098
00:52:19,440 --> 00:52:22,680
Speaker 2: the attention, you know, talk about I'm a malignant narcissist,

1099
00:52:22,760 --> 00:52:25,600
Speaker 2: and who is who is hopped up on the social media?

1100
00:52:25,719 --> 00:52:28,040
Speaker 2: There you go, there she is there, Welcome to our

1101
00:52:28,080 --> 00:52:31,840
Speaker 2: next public official. Meanwhile, you have people like Mike Gallagher

1102
00:52:31,880 --> 00:52:34,040
Speaker 2: who listen. I don't agree with Mike Galla on a

1103
00:52:34,080 --> 00:52:36,160
Speaker 2: lot of stuff. I think it scant. His gay stuff

1104
00:52:36,200 --> 00:52:39,480
Speaker 2: is really problematic and troubling. But at the same time,

1105
00:52:39,560 --> 00:52:42,760
Speaker 2: what a smart legislator about all kinds of issues. He's leaving.

1106
00:52:43,120 --> 00:52:44,400
Speaker 1: I know he's terrific.

1107
00:52:44,480 --> 00:52:46,360
Speaker 2: I did a great interview with her. He's so smart.

1108
00:52:46,560 --> 00:52:47,759
Speaker 2: I don't agree with him, but I can have a

1109
00:52:47,760 --> 00:52:50,719
Speaker 2: good discussion with him about things to be on. He's

1110
00:52:50,800 --> 00:52:53,040
Speaker 2: throwing his hands up, like not going to do this,

1111
00:52:53,200 --> 00:52:56,239
Speaker 2: and he's an important figure. Ken Buck another person who's

1112
00:52:56,280 --> 00:53:00,319
Speaker 2: push talk about conservative I gotta tell you fight in

1113
00:53:00,320 --> 00:53:02,320
Speaker 2: the good fight, like this is a lie, This was

1114
00:53:02,360 --> 00:53:04,520
Speaker 2: a lie. This is like he's he learned it. He

1115
00:53:04,680 --> 00:53:08,080
Speaker 2: learned about the internet. With Dave Cicelini, you can put

1116
00:53:08,080 --> 00:53:12,480
Speaker 2: together two more and you know, David this gay, blue

1117
00:53:12,480 --> 00:53:16,960
Speaker 2: blue blue Democrat and Ken Buck this red red, red coloradens.

1118
00:53:17,000 --> 00:53:21,120
Speaker 2: But they both cared about the truth. Right. Well, he's leaving,

1119
00:53:21,280 --> 00:53:24,320
Speaker 2: David Cezelini left, you know, and so what we're left

1120
00:53:24,320 --> 00:53:26,759
Speaker 2: with is a lot of people. You know, It's just

1121
00:53:27,400 --> 00:53:32,160
Speaker 2: I often the Yates poem of slouching towards Bethlehem, waiting

1122
00:53:32,160 --> 00:53:34,880
Speaker 2: to be born, that's what we have. I think the

1123
00:53:34,960 --> 00:53:36,880
Speaker 2: moment in the book that I like the best is

1124
00:53:36,920 --> 00:53:39,960
Speaker 2: when when Google tried to take over Yahoo Search. As

1125
00:53:40,000 --> 00:53:43,279
Speaker 2: you recall, I was writing a lot of no and

1126
00:53:43,360 --> 00:53:46,840
Speaker 2: during the during the Obama administration, which bear hugged these people.

1127
00:53:46,880 --> 00:53:48,920
Speaker 2: By the way, I'm not this is not a Republican

1128
00:53:48,960 --> 00:53:52,799
Speaker 2: Democrat thing. And they all bear hugged them, especially definitely

1129
00:53:53,040 --> 00:53:57,280
Speaker 2: the Obama people, right, And they were trying to basically

1130
00:53:57,320 --> 00:53:59,600
Speaker 2: control Yahoo. They couldn't buy it, but they could have

1131
00:53:59,719 --> 00:54:01,959
Speaker 2: done the business. It was just ridiculous. They were gonna

1132
00:54:01,960 --> 00:54:04,640
Speaker 2: have ninety nine point nine percent of the search market.

1133
00:54:04,680 --> 00:54:07,160
Speaker 2: It was crazy. I've never agreed with Microsoft on anything,

1134
00:54:07,200 --> 00:54:10,040
Speaker 2: and I was like, they are correct, sir, they cannot

1135
00:54:10,040 --> 00:54:12,400
Speaker 2: have this much. At that time, it was the biggest

1136
00:54:12,560 --> 00:54:15,760
Speaker 2: income generator of the Internet what they were doing in search.

1137
00:54:16,400 --> 00:54:18,560
Speaker 2: And I wrote a piece and I used a Doctor

1138
00:54:18,640 --> 00:54:21,960
Speaker 2: Seuss thing and I as a joke, and then I

1139
00:54:22,040 --> 00:54:25,080
Speaker 2: said a line where I said, at least Microsoft knew

1140
00:54:25,120 --> 00:54:27,440
Speaker 2: they were thugs. And this was referring to their previous

1141
00:54:27,480 --> 00:54:30,960
Speaker 2: attempts to control the software platform through Windows, which I

1142
00:54:31,000 --> 00:54:33,600
Speaker 2: had written about at the Washington Post. And one of

1143
00:54:33,640 --> 00:54:36,000
Speaker 2: the founders called me up and I literally can't write.

1144
00:54:36,080 --> 00:54:37,959
Speaker 2: Probably was Larry because he was the one who talked

1145
00:54:38,000 --> 00:54:41,080
Speaker 2: the most about serious issues like this, and he said,

1146
00:54:41,200 --> 00:54:45,440
Speaker 2: you know us, you know we're not bad people, right,

1147
00:54:45,960 --> 00:54:48,799
Speaker 2: you know, we're not bad people. We would handle it well.

1148
00:54:48,880 --> 00:54:51,759
Speaker 2: I'm like, you know what, here's the problem. Because you

1149
00:54:51,920 --> 00:54:55,280
Speaker 2: didn't go to school enough, you didn't take history classes.

1150
00:54:55,640 --> 00:54:59,000
Speaker 2: I'm not worried about you. I'm worried about the next person.

1151
00:55:00,040 --> 00:55:03,759
Speaker 2: And I quoted Yates where I said some rough beast

1152
00:55:03,840 --> 00:55:06,719
Speaker 2: is sloushing towards Bethlehem, whiting to be born. This is Bethlehem.

1153
00:55:07,160 --> 00:55:09,920
Speaker 2: There's a beast coming, and that we'll be here. And

1154
00:55:10,000 --> 00:55:12,319
Speaker 2: they were like, what are you talking about. I'm like, oh,

1155
00:55:12,360 --> 00:55:18,879
Speaker 2: forget it, like, forget it. I'm always quoting like poetry terrible. Yeah, right,

1156
00:55:19,320 --> 00:55:21,880
Speaker 2: And so I said this, and I said and they

1157
00:55:21,880 --> 00:55:24,120
Speaker 2: had the don't be evil thing remember in there as

1158
00:55:24,160 --> 00:55:26,640
Speaker 2: their motto. And when they went public and I said,

1159
00:55:27,760 --> 00:55:30,560
Speaker 2: I don't think you're evil, but there is evil coming,

1160
00:55:30,760 --> 00:55:34,240
Speaker 2: like and you know, welcome, welcome. Donald Trump, who used

1161
00:55:34,239 --> 00:55:38,560
Speaker 2: this medium for his advantage. There was always it didn't

1162
00:55:38,560 --> 00:55:41,960
Speaker 2: matter if it was Donald Trump, someone the Chinese, the Iranians,

1163
00:55:43,000 --> 00:55:47,000
Speaker 2: white nationalists. They were coming for this because it was perfect.

1164
00:55:47,040 --> 00:55:50,239
Speaker 2: It was a perfect way to finally crawl out from

1165
00:55:50,320 --> 00:55:53,640
Speaker 2: under rocks and take over people's minds. Finally they had

1166
00:55:53,640 --> 00:55:54,160
Speaker 2: a vehicle.

1167
00:55:54,440 --> 00:55:56,520
Speaker 1: It sounds like you think the genie is out of

1168
00:55:56,560 --> 00:55:58,920
Speaker 1: the bottle and there's no no.

1169
00:55:59,200 --> 00:56:04,080
Speaker 2: Because look, look remember Standard Oil ran everything, corrupted, everything

1170
00:56:04,960 --> 00:56:09,120
Speaker 2: decided everything from one person at and t Standard Oil,

1171
00:56:09,320 --> 00:56:14,760
Speaker 2: the train monopoly. We've always been subject to power consolidating

1172
00:56:14,760 --> 00:56:17,840
Speaker 2: and trying to manipulate everybody's lives. And there's huge damage

1173
00:56:17,840 --> 00:56:20,200
Speaker 2: that was done by each of those monopolies, each of

1174
00:56:20,239 --> 00:56:23,520
Speaker 2: them in their own way, whether they mutated cities or

1175
00:56:24,000 --> 00:56:27,719
Speaker 2: people worked in terrible conditions. We don't have to put

1176
00:56:27,800 --> 00:56:31,040
Speaker 2: up with this. We don't and we just need elected officials.

1177
00:56:31,080 --> 00:56:32,919
Speaker 1: So who's going to fix it if all these people

1178
00:56:33,000 --> 00:56:36,239
Speaker 1: are leaving and other people are thriving as on the

1179
00:56:36,239 --> 00:56:37,440
Speaker 1: way things are.

1180
00:56:37,160 --> 00:56:40,440
Speaker 2: Someone I don't know, that's the problem. Like they have

1181
00:56:40,520 --> 00:56:42,759
Speaker 2: all these bills that they could pass. Look right now,

1182
00:56:42,800 --> 00:56:45,080
Speaker 2: one of the biggest issues right now, a run free

1183
00:56:45,120 --> 00:56:46,920
Speaker 2: speech is right in front of the Supreme Court today

1184
00:56:47,680 --> 00:56:51,880
Speaker 2: on these laws that these ridiculous attorney generals from Florida

1185
00:56:51,880 --> 00:56:53,440
Speaker 2: and Texas are trying. I can't believe I'm on the

1186
00:56:53,480 --> 00:56:56,000
Speaker 2: tech people's side, but they want to control. They want

1187
00:56:56,080 --> 00:56:59,239
Speaker 2: the government to control political speech. And you know, as

1188
00:56:59,239 --> 00:57:03,200
Speaker 2: I read the First Amendment, Google can control political speech.

1189
00:57:04,040 --> 00:57:07,280
Speaker 2: The State of Florida cannot even to tell them they can't.

1190
00:57:07,760 --> 00:57:10,560
Speaker 2: And they throw around words like censorship, and they abuse

1191
00:57:10,640 --> 00:57:13,600
Speaker 2: the First Amendment in ways that are Both sides do that,

1192
00:57:13,719 --> 00:57:16,160
Speaker 2: by the way, But it seems to me that we

1193
00:57:16,240 --> 00:57:19,400
Speaker 2: need to put in place a range of things. Privacy laws,

1194
00:57:19,800 --> 00:57:26,000
Speaker 2: redo the antitrust bills, encourage government research in government investment

1195
00:57:26,080 --> 00:57:29,560
Speaker 2: in all kinds of innovation, allow new companies to come.

1196
00:57:29,640 --> 00:57:32,960
Speaker 2: That's our strength. Our strength isn't seven large companies that

1197
00:57:32,960 --> 00:57:36,440
Speaker 2: are called the Magnificent Seven. Now, it's that's not our strength.

1198
00:57:37,080 --> 00:57:40,440
Speaker 2: They're not our strength. Our strength a small little group

1199
00:57:40,480 --> 00:57:42,760
Speaker 2: of people coming up with a great idea and a garage.

1200
00:57:42,800 --> 00:57:45,080
Speaker 2: And I'm not romantic about this stuff, but it is.

1201
00:57:45,160 --> 00:57:48,320
Speaker 2: That's what makes America different. That's why we led the

1202
00:57:48,360 --> 00:57:52,240
Speaker 2: Internet age, not because we have the biggest national heroes.

1203
00:57:52,520 --> 00:57:55,280
Speaker 2: You know. So I'm hoping at some point, you know,

1204
00:57:55,320 --> 00:57:58,760
Speaker 2: I thought this this stuff around girls and kids and

1205
00:57:58,800 --> 00:58:02,320
Speaker 2: pornography work. I thought the self esteem would work. I

1206
00:58:02,480 --> 00:58:06,520
Speaker 2: thought Francis Hogan would work. At some point, regular people

1207
00:58:06,520 --> 00:58:09,480
Speaker 2: are going to be. Isn't this is enough? We're all

1208
00:58:09,720 --> 00:58:13,040
Speaker 2: hopped up on this crap and we and there's all

1209
00:58:13,080 --> 00:58:14,840
Speaker 2: sorts of good things that could come of it, like

1210
00:58:14,960 --> 00:58:19,240
Speaker 2: start to lean into cancer research and healthcare and climate

1211
00:58:19,320 --> 00:58:21,520
Speaker 2: change tech and things like that. Why do we have

1212
00:58:21,600 --> 00:58:23,800
Speaker 2: to why do we have to have all the bad

1213
00:58:23,880 --> 00:58:25,160
Speaker 2: things that it brings.

1214
00:58:25,480 --> 00:58:27,840
Speaker 1: I was talking to my friend Kevin Goldman, who was

1215
00:58:27,840 --> 00:58:29,760
Speaker 1: a media writer for The Wall Street Journal. I don't

1216
00:58:29,760 --> 00:58:31,800
Speaker 1: know if you know Kevin, but he's like, ask Kara

1217
00:58:31,880 --> 00:58:34,439
Speaker 1: about the future of newspapers. I was going to say,

1218
00:58:34,480 --> 00:58:36,600
Speaker 1: I'm going to ask care about the future of media.

1219
00:58:36,800 --> 00:58:39,960
Speaker 1: We see the fragmentation of the media landscape. We see,

1220
00:58:40,680 --> 00:58:45,880
Speaker 1: you know, traditional journalism imploding. We see lots of actual

1221
00:58:46,000 --> 00:58:49,440
Speaker 1: fake news, not just what Donald Trump calls it, crawling

1222
00:58:49,480 --> 00:58:53,280
Speaker 1: all over the internet. When you look out on the horizon, Kara,

1223
00:58:53,360 --> 00:58:55,440
Speaker 1: since you're so good at looking at the big picture

1224
00:58:55,480 --> 00:58:58,920
Speaker 1: and identifying trends, what is the future of media in

1225
00:58:58,960 --> 00:58:59,439
Speaker 1: your view?

1226
00:59:00,000 --> 00:59:01,720
Speaker 2: It's just gonna be different. I think it. You know,

1227
00:59:01,880 --> 00:59:05,200
Speaker 2: I sound much tougher on media, but it's the news business.

1228
00:59:05,360 --> 00:59:07,280
Speaker 2: It needs to be a business. You can't not be

1229
00:59:07,360 --> 00:59:09,919
Speaker 2: a business. And so look what you've done. You've built

1230
00:59:09,920 --> 00:59:12,400
Speaker 2: a little media company, haven't you. You're doing good. You're

1231
00:59:12,480 --> 00:59:16,080
Speaker 2: pulling people, you're running influenced you. Your costs are in

1232
00:59:16,160 --> 00:59:20,160
Speaker 2: line with your output, like your revenues and costs are

1233
00:59:20,160 --> 00:59:22,320
Speaker 2: in line, or else you'd be out of business. Right,

1234
00:59:22,320 --> 00:59:24,360
Speaker 2: You're not gonna No one's gonna like fund Katie Kuric

1235
00:59:24,480 --> 00:59:27,800
Speaker 2: to negative numbers. It's not gonna happen for a while.

1236
00:59:28,160 --> 00:59:30,280
Speaker 2: So they just have to be different the way they

1237
00:59:30,320 --> 00:59:33,440
Speaker 2: did things before every business changes. There used to be

1238
00:59:33,480 --> 00:59:38,680
Speaker 2: a very thriving stagecoach business. There used to be telegrams. Well,

1239
00:59:38,720 --> 00:59:41,040
Speaker 2: guess what, they don't exist. I have a I don't

1240
00:59:41,040 --> 00:59:43,120
Speaker 2: think I put this in the book, but my kids

1241
00:59:43,120 --> 00:59:44,680
Speaker 2: we were walking on the street in a light, which

1242
00:59:44,680 --> 00:59:46,560
Speaker 2: is unusual in and of itself, and there was a

1243
00:59:46,600 --> 00:59:48,640
Speaker 2: payphone there. It was an old payphone and it was all,

1244
00:59:48,720 --> 00:59:51,360
Speaker 2: you know, hanging, The thing was hanging down, didn't work.

1245
00:59:51,800 --> 00:59:53,320
Speaker 2: And one of my kids, he was at the time,

1246
00:59:53,400 --> 00:59:55,520
Speaker 2: he was six or seven, he's like, what's that? And

1247
00:59:55,560 --> 00:59:58,040
Speaker 2: I said, oh, it's a pig. It's a payphone. And

1248
00:59:58,400 --> 00:59:59,720
Speaker 2: I hadn't thought of it. I hadn't used one of

1249
00:59:59,720 --> 01:00:00,240
Speaker 2: along time.

1250
01:00:00,320 --> 01:00:04,800
Speaker 1: I saw on a show recently and I was like, wow.

1251
01:00:03,920 --> 01:00:06,680
Speaker 2: Right right, And I said, well, he goes, what did

1252
01:00:06,720 --> 01:00:09,400
Speaker 2: you do? And I said, well, you stood there and

1253
01:00:09,440 --> 01:00:12,880
Speaker 2: you put money in our credit cards sometimes that was later,

1254
01:00:13,400 --> 01:00:16,400
Speaker 2: and then you called people and that's where if you

1255
01:00:16,400 --> 01:00:18,240
Speaker 2: were out, that's where you had to call people. But

1256
01:00:18,320 --> 01:00:20,520
Speaker 2: otherwise people couldn't reach you if you were out of

1257
01:00:20,560 --> 01:00:23,000
Speaker 2: your house. And he looked at me and he goes,

1258
01:00:23,040 --> 01:00:26,600
Speaker 2: that's filthy, and I said yes, like that was his

1259
01:00:26,640 --> 01:00:29,640
Speaker 2: first reaction, and I was like and then I started thinking,

1260
01:00:29,960 --> 01:00:31,680
Speaker 2: and I was talking to them, I go what happened

1261
01:00:31,720 --> 01:00:33,400
Speaker 2: to all the people that used to service these What

1262
01:00:33,440 --> 01:00:36,400
Speaker 2: about the people that made these? What about? Like there

1263
01:00:36,440 --> 01:00:39,480
Speaker 2: was a whole infrastructure and business. It's the same thing

1264
01:00:39,480 --> 01:00:41,320
Speaker 2: with news. You're just going to have to change and

1265
01:00:41,320 --> 01:00:44,160
Speaker 2: make products that where the costs are in line with

1266
01:00:44,240 --> 01:00:48,080
Speaker 2: the revenues. Unfortunately, a lot of the big media companies

1267
01:00:48,120 --> 01:00:51,440
Speaker 2: because Facebook and Google have eaten up all digital revenues

1268
01:00:51,920 --> 01:00:55,120
Speaker 2: and you didn't get tech enough soon enough, fast enough.

1269
01:00:55,880 --> 01:00:58,840
Speaker 2: You need to, I'm sorry. You have to change the

1270
01:00:58,880 --> 01:01:01,640
Speaker 2: cost structure and or makes something that people will pay

1271
01:01:01,640 --> 01:01:03,560
Speaker 2: for so you can have the cost structure you have.

1272
01:01:04,160 --> 01:01:08,360
Speaker 2: That is really hard for reporters to do you have

1273
01:01:08,440 --> 01:01:11,000
Speaker 2: to embrace some AI stuff that makes it more efficient.

1274
01:01:11,040 --> 01:01:12,600
Speaker 2: You just do that. Some of it is going to

1275
01:01:12,680 --> 01:01:16,960
Speaker 2: help make things more efficient. But I'm very heartened by

1276
01:01:17,160 --> 01:01:20,360
Speaker 2: me people like me and like you, and like Platformer

1277
01:01:20,400 --> 01:01:23,800
Speaker 2: with Casey Newton, all kinds of things. Casey has enormous influence.

1278
01:01:23,840 --> 01:01:27,680
Speaker 2: He has two people and he's doing great. Right, Well,

1279
01:01:27,720 --> 01:01:31,440
Speaker 2: that's small, but it's not nothing that's I see that,

1280
01:01:31,560 --> 01:01:33,880
Speaker 2: or else you're gonna have a couple of big paces

1281
01:01:33,960 --> 01:01:37,880
Speaker 2: like that'll consolidate, like the New York Times, you know,

1282
01:01:37,960 --> 01:01:40,520
Speaker 2: which sort of has become its own news monopoly. At

1283
01:01:40,520 --> 01:01:42,919
Speaker 2: the same time, it's not that big. It's not that big.

1284
01:01:42,960 --> 01:01:45,360
Speaker 2: It's just a smaller business, Katie, That's all it is.

1285
01:01:45,560 --> 01:01:47,640
Speaker 1: I always think that, And this gets back to the

1286
01:01:47,680 --> 01:01:51,480
Speaker 1: polarization issue, that mass media is an oxymoron, this notion

1287
01:01:51,560 --> 01:01:59,520
Speaker 1: of monoculture, of a shared experience that actually contributes to polarization.

1288
01:01:59,640 --> 01:02:03,960
Speaker 1: Though because everyone does creating their own media ecosystem.

1289
01:02:03,600 --> 01:02:06,200
Speaker 2: They are. But at the same time, let's just be honest.

1290
01:02:06,280 --> 01:02:08,000
Speaker 2: Like you worked for the networks for years. You came

1291
01:02:08,080 --> 01:02:10,880
Speaker 2: up networks I was arguing about that people were going

1292
01:02:10,960 --> 01:02:12,680
Speaker 2: to make years ago I was saying, there's could be

1293
01:02:12,680 --> 01:02:14,640
Speaker 2: all kinds of media from all kinds of people, because

1294
01:02:14,640 --> 01:02:17,120
Speaker 2: everyone suddenly has tools and there's all this creativity out

1295
01:02:17,120 --> 01:02:19,440
Speaker 2: there that you that has to go through your gateways.

1296
01:02:19,520 --> 01:02:22,800
Speaker 1: No, and I love that. That's a positive, definitely.

1297
01:02:22,400 --> 01:02:24,160
Speaker 2: And they're like, well, it's going to be very different

1298
01:02:24,160 --> 01:02:25,960
Speaker 2: because the gatekeepers is I said, you know what, the

1299
01:02:25,960 --> 01:02:28,680
Speaker 2: gatekeepers used to be twelve white men on the Upper

1300
01:02:28,800 --> 01:02:31,320
Speaker 2: East Side of Manhattan. Do we really want to take

1301
01:02:31,320 --> 01:02:34,520
Speaker 2: our cues from them. We don't. That's that wasn't the

1302
01:02:34,600 --> 01:02:36,600
Speaker 2: right thing either. It just happened to work for the

1303
01:02:36,640 --> 01:02:37,360
Speaker 2: time it was in.

1304
01:02:37,520 --> 01:02:40,520
Speaker 1: So No, I agree that people who were the gatekeepers

1305
01:02:40,640 --> 01:02:44,479
Speaker 1: were not ideal, but I still believe in the need

1306
01:02:44,640 --> 01:02:48,040
Speaker 1: for gatekeeping that is true, you know, for editing, for

1307
01:02:48,160 --> 01:02:52,720
Speaker 1: ascertaining what's actually accurate and truthful. And I think, you know,

1308
01:02:52,760 --> 01:02:55,920
Speaker 1: it's the wild wild West now anybody can say something,

1309
01:02:56,000 --> 01:02:59,080
Speaker 1: and unfortunately too many people are willing to believe.

1310
01:02:58,800 --> 01:03:02,120
Speaker 2: It right, except that I think I am of the

1311
01:03:02,200 --> 01:03:05,240
Speaker 2: opposite belief. I think especially young people and you have

1312
01:03:05,360 --> 01:03:09,240
Speaker 2: you have young adults. You know, your children are young adults.

1313
01:03:09,280 --> 01:03:12,440
Speaker 2: My older sons are young adults. I think they're very savvy.

1314
01:03:12,720 --> 01:03:14,720
Speaker 2: I think they know a lot about stuff. I think

1315
01:03:14,760 --> 01:03:17,800
Speaker 2: they do can't ascertain the differences. I don't think they're

1316
01:03:17,800 --> 01:03:19,520
Speaker 2: tricked easily. And I have a lot of faith in

1317
01:03:19,560 --> 01:03:21,800
Speaker 2: young people in that regard. And one of the things,

1318
01:03:21,840 --> 01:03:23,800
Speaker 2: do you remember when we were growing up when they

1319
01:03:23,840 --> 01:03:27,120
Speaker 2: said the TV was the boob tube? Oh yeah, of course, right,

1320
01:03:27,520 --> 01:03:31,440
Speaker 2: your mind is going to turn to the mushube. You're

1321
01:03:31,480 --> 01:03:34,160
Speaker 2: going to turn to mush Did you turn to mush Katie? No?

1322
01:03:34,360 --> 01:03:37,320
Speaker 2: And also TV's pretty good now, right, Look at music.

1323
01:03:37,680 --> 01:03:40,560
Speaker 2: Music was under siege by digital and they figured it out.

1324
01:03:40,680 --> 01:03:44,200
Speaker 2: Now it's a pretty thriving industry. Well we'll figure it out.

1325
01:03:44,320 --> 01:03:46,960
Speaker 2: That's what we're going to do. And to every reporter,

1326
01:03:47,080 --> 01:03:50,200
Speaker 2: I say, I'm so sorry, but this is This happened

1327
01:03:50,240 --> 01:03:53,600
Speaker 2: to the farming people. This happened in manufacturing people, and

1328
01:03:53,800 --> 01:03:55,400
Speaker 2: it doesn't hurt any less.

1329
01:03:55,560 --> 01:03:57,960
Speaker 1: This happened to the people who operated and made the

1330
01:03:58,000 --> 01:03:59,080
Speaker 1: teletype machines.

1331
01:03:59,280 --> 01:04:03,320
Speaker 2: That's right. So guess what it's time to change. And unfortunately,

1332
01:04:03,360 --> 01:04:05,840
Speaker 2: because we live, you know, or we just have the

1333
01:04:05,840 --> 01:04:08,120
Speaker 2: government pay for everything. That's the other way to go, right,

1334
01:04:08,240 --> 01:04:10,920
Speaker 2: have the government pay for media. That's not happening in

1335
01:04:10,920 --> 01:04:14,400
Speaker 2: this country anytime soon at a massive level because the

1336
01:04:14,520 --> 01:04:18,440
Speaker 2: polarization and it just probably shouldn't right, So I don't know,

1337
01:04:18,520 --> 01:04:20,680
Speaker 2: you just make a business and start to grow. It

1338
01:04:20,720 --> 01:04:22,960
Speaker 2: is the is the only way to stay ahead. That

1339
01:04:23,120 --> 01:04:25,480
Speaker 2: is the only way to do it and continue to

1340
01:04:25,760 --> 01:04:28,120
Speaker 2: like I believe, and I think you do. I believe

1341
01:04:28,160 --> 01:04:31,520
Speaker 2: in substantive media, and I think there's a market for it.

1342
01:04:31,680 --> 01:04:34,720
Speaker 2: I really really do. And I'm not going to hit everybody,

1343
01:04:34,720 --> 01:04:36,480
Speaker 2: but I'm going to make a business out of it,

1344
01:04:36,600 --> 01:04:39,520
Speaker 2: and and and then you know, that's how business is,

1345
01:04:39,600 --> 01:04:42,800
Speaker 2: That's how that's what's great about this country. It's about innovation.

1346
01:04:43,000 --> 01:04:46,640
Speaker 2: There's no place on Earth like the United States around innovation.

1347
01:04:47,040 --> 01:04:49,560
Speaker 2: There isn't. There just isn't. I've been all over the globe.

1348
01:04:49,600 --> 01:04:53,080
Speaker 2: I've seen all the places, and there's there's an innovative

1349
01:04:53,120 --> 01:04:55,880
Speaker 2: spirit in this country that exists. So let's find it

1350
01:04:56,000 --> 01:04:59,200
Speaker 2: everywhere it is and encourage it so that we don't

1351
01:04:59,240 --> 01:05:02,240
Speaker 2: have to have top down you know, our world is

1352
01:05:02,240 --> 01:05:05,280
Speaker 2: in shape. By Mark Zuckerberg, I know he's look great,

1353
01:05:05,600 --> 01:05:08,800
Speaker 2: really nice, but honestly, it shouldn't take him two years

1354
01:05:08,840 --> 01:05:13,040
Speaker 2: to figure out anti Semitism is a problem. Unchecked right,

1355
01:05:13,160 --> 01:05:15,760
Speaker 2: that's right. How long it took him? So let's get

1356
01:05:15,840 --> 01:05:17,840
Speaker 2: lots of voices happening. Let's get a lot of people.

1357
01:05:17,840 --> 01:05:19,520
Speaker 2: And I do think, I don't know. I have a

1358
01:05:19,560 --> 01:05:21,600
Speaker 2: confidence that journalists will be just fine.

1359
01:05:22,040 --> 01:05:24,920
Speaker 1: I hope so, because they're so important. They are, and

1360
01:05:24,960 --> 01:05:28,640
Speaker 1: your voice is so important too, Kara, to make sure

1361
01:05:28,720 --> 01:05:31,720
Speaker 1: that people really know what's going on. The book is

1362
01:05:31,720 --> 01:05:33,960
Speaker 1: called burn Book, a Tech Love Story. Kara, thank you.

1363
01:05:34,040 --> 01:05:36,160
Speaker 1: This was so fun. I could talk to you for hours,

1364
01:05:36,200 --> 01:05:45,400
Speaker 1: but well you might. Thanks for listening. Everyone. If you

1365
01:05:45,520 --> 01:05:48,120
Speaker 1: have a question for me, a subject you want us

1366
01:05:48,160 --> 01:05:50,800
Speaker 1: to cover, or you want to share your thoughts about

1367
01:05:50,840 --> 01:05:54,360
Speaker 1: how you navigate this crazy world, reach out. You can

1368
01:05:54,440 --> 01:05:57,360
Speaker 1: leave a short message at six oh nine five one

1369
01:05:57,480 --> 01:06:00,360
Speaker 1: two five to five oh five, or you can send

1370
01:06:00,400 --> 01:06:03,000
Speaker 1: me a DM on Instagram. I would love to hear

1371
01:06:03,080 --> 01:06:06,880
Speaker 1: from you. Next Question is a production of iHeartMedia and

1372
01:06:07,000 --> 01:06:11,120
Speaker 1: Katie Couric Media. The executive producers are Me, Katie Kuric,

1373
01:06:11,240 --> 01:06:15,800
Speaker 1: and Courtney Ltz. Our supervising producer is Ryan Martz, and

1374
01:06:15,880 --> 01:06:21,040
Speaker 1: our producers are Adriana Fazzio and Meredith Barnes. Julian Weller

1375
01:06:21,160 --> 01:06:25,800
Speaker 1: composed our theme music. For more information about today's episode,

1376
01:06:25,960 --> 01:06:28,360
Speaker 1: or to sign up for my newsletter wake Up Call,

1377
01:06:28,800 --> 01:06:31,720
Speaker 1: go to the description in the podcast app, or visit

1378
01:06:31,800 --> 01:06:35,000
Speaker 1: us at Katiecuric dot com. You can also find me

1379
01:06:35,080 --> 01:06:38,800
Speaker 1: on Instagram and all my social media channels. For more

1380
01:06:38,840 --> 01:06:44,160
Speaker 1: podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, or

1381
01:06:44,200 --> 01:06:47,760
Speaker 1: wherever you listen to your favorite shows.