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Speaker 1: Hi Brian, Hi Katie, and hello listeners. You know, when

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Speaker 1: you think about the news these days, Brian, you think

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Speaker 1: about the two arenas that are dominating the headlines day

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Speaker 1: in and day out, minute by minute, and those two

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Speaker 1: arenas are probably politics and technology. And you know who

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Speaker 1: understands tech better than almost anyone, including the two of us.

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Speaker 1: Could it be our next guest, Kara Swisher? Wow, that's

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Speaker 1: so convenient it could. Yes, this week's wonder Woman. Kara

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Speaker 1: Swisher has been covering the industry for more than twenty

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Speaker 1: years and is one of the most incisive and well

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Speaker 1: connected players in Silicon Valley. She's such a pit bowl, Brian,

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Speaker 1: but she's actually a very nice pit bowl. She started

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Speaker 1: working a long time ago, actually at the Washington Post.

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Speaker 1: She apparently chewed out an editor for an article that

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Speaker 1: had been written about an event at Georgetown where she

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Speaker 1: was a student. She ultimately got a job there. She

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Speaker 1: went to the Wall Street Journal, and then she wrote

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Speaker 1: a couple of books about a O Well, she started

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Speaker 1: this huge tech site. I think really she was on

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Speaker 1: the front lines of tech journalism back in the day, Brian,

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Speaker 1: when she started All Things D with her partner Walt

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Speaker 1: Mossburg and she's an entrepreneur herself. She left the Journal

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Speaker 1: and all things d to start Recode and I like this.

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Speaker 1: A few years back in New York Magazine described Kara

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Speaker 1: as Silicon Valley's most feared and well liked journalist, which

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Speaker 1: is quite a rare combo, that's for sure. Fo schizl,

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Speaker 1: as the kids might say. Brian. By the way, this

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Speaker 1: is a crossover episode with Kara's podcast, Recode Decode, which

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Speaker 1: means a version of this conversation will dropping Kara's podcast

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Speaker 1: feed as well. But sadly for you, Brian, I'm flying

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Speaker 1: solo this time and I'm missing you. Yeah. I don't

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Speaker 1: want to get in the way of the two alpha women.

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Speaker 1: So you have your conversation. Keep me out of trouble, please,

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Speaker 1: and I'm gonna be excited to listen. Thanks Brian. Karen

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Speaker 1: and I covered a lot of ground from how she

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Speaker 1: got into the business of journalism in college using her

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Speaker 1: trademark Hutzpah Hutzpah Hotspa. We also talked about our respective

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Speaker 1: careers and we kick things off by talking about Snapchat,

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Speaker 1: of all things. Well, let me ask you about Snapchat

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Speaker 1: because I want to not only talk to you about

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Speaker 1: some of these big media companies and get the latest

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Speaker 1: skinny on it. But I also want to talk about you, Kac.

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Speaker 1: But first, you know, so, I know Evan Spiegel had

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Speaker 1: a good quarter. I know that investors were a little heartened,

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Speaker 1: but it seems like Instagram really took the wind out

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Speaker 1: of his sales with Insta Stories, which I'm totally obsessed with,

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Speaker 1: which is actually a sickness which will will discuss later.

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Speaker 1: But UM, tell me what's going on with Snapchat. I

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Speaker 1: know they did a redesign and people were sad about

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Speaker 1: it when the latest on that my son texted me

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Speaker 1: is like, nobody likes this redesign. I mean, I think

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Speaker 1: these companies redesigned continually. They're always shifting and changing, and

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Speaker 1: you know, Facebook had twenty ones that people didn't like,

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Speaker 1: so I think that I think they just have to

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Speaker 1: go with the way they want to do it and

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Speaker 1: then the best and people will. Yeah, I don't. I

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Speaker 1: don't obsess on redesigns unless they're just truly awful, like

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Speaker 1: a new coke, like new you know, something really doesn't work, um,

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Speaker 1: and people get people get used to the way they're

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Speaker 1: using these things, So I don't over index on that

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Speaker 1: UM that said, you know, they've got to be very

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Speaker 1: careful because what happened is years ago Facebook tried to

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Speaker 1: copies try to buy Snapchat. First of all, Facebook is

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Speaker 1: essentially they're mortal, not their mortal enemy. They're they're killer really,

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Speaker 1: They're they're trying to kill off Snapchat. UM, and they

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Speaker 1: bought they try to buy Snapchat, and he put it off.

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Speaker 1: He's a really interesting and visionary entrepreneur, Evan Spiel. I

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Speaker 1: think every time I talked to him, always fascinated, and

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Speaker 1: that's I can't say that with everybody I talked to UM.

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Speaker 1: And he's he's got a big sense of where things

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Speaker 1: are going. And they really do have an advantage in

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Speaker 1: that it's not a twitchy medium at all, even though

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Speaker 1: I don't use it that much and I do know

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Speaker 1: how to use it, UM, but it's a much it's

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Speaker 1: a different it's a communications meeting a lot more like

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Speaker 1: we chat in China, UM if you if you ever

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Speaker 1: used that one. But Facebook had just decided to try

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Speaker 1: to kill it, and so they try something I think

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Speaker 1: it was called poke or something like that, which is

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Speaker 1: just an awful name for a medium. UM. Based on

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Speaker 1: the pokes on Facebook essentially UM, and that didn't work

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Speaker 1: and didn't catch on UM. And then they did it,

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Speaker 1: used Instagram to do this, to do Instagram stories UM.

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Speaker 1: And I had Kevin H. Sistram, who was the founder

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Speaker 1: of Instagram, on my podcast and he you know, most

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Speaker 1: the people complained about it. They basically thought it was

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Speaker 1: shoplifting or plagiarism, you know, in terms of how they

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Speaker 1: borrowed what Snapchat was doing. And he said, look, we

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Speaker 1: are doing exactly the same thing they're doing. But someone

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Speaker 1: invented the car radio. Should we not make better car radios?

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Speaker 1: You know what I mean? That's that was his argument.

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Speaker 1: We're making a better car radio, and good for them

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Speaker 1: for inventing the car radio, but too bad. And I

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Speaker 1: think he was talking about the itera of nature of

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Speaker 1: technologies that people build on, just like jobs and Gates stole.

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Speaker 1: They borrowed the stuff from xerox park, the graphical user interface,

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Speaker 1: it happens, it happens again. And I think the problem

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Speaker 1: for Snapchat is that Facebook can just roll eventually will

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Speaker 1: get it right, just like Microsoft did a million times

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Speaker 1: on a bunch of other tech companies. So what does

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Speaker 1: that mean for Evan Spiegel and Snapchat. How does Instagram compare, Well,

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Speaker 1: he's so creative. I so it is Kevin's Sistram by

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Speaker 1: the way, who runs Instagram. Um, but I think it's hard.

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Speaker 1: I think it's super hard to compete. I mean, the

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Speaker 1: ear of big tech companies now is really here. Um.

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Speaker 1: It was talking to someone the other day of a

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Speaker 1: venture capitalist named Sarah Tavil, and she said, it's really

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Speaker 1: hard to do innovative companies anymore because and there will

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Speaker 1: be innovative companies, it's not going to never stop. But

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Speaker 1: the powerful companies Apple, Google, Facebook, Um, Amazon and Amazon

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Speaker 1: are just it just creates a like a really difficult

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Speaker 1: and they're buying up companies and they're they're being innovative

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Speaker 1: and iterative themselves, and so it makes it super hard

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Speaker 1: for smaller companies to break in. Facebook has gotten a

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Speaker 1: lot of bad press lately Russia and about all kinds

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Speaker 1: of things. So give me can you just catch me

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Speaker 1: up on what's happening in Facebook? And what do you

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Speaker 1: think the outcome is going to be of a lot

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Speaker 1: of this criticism. Well, you know it's interesting. I was

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Speaker 1: on you don't follow Twitter that carefully, but I had

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Speaker 1: a debate with Facebook executives this weekend on Twitter. I'm

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Speaker 1: gonna have to go back. They lost, they lost. It's gone,

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Speaker 1: o Katie. Yeah. No, Here's what they did is they're

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Speaker 1: they're very sensitive. First of all, they did a very

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Speaker 1: slow roll about the uses of their platform by Russia. UM,

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Speaker 1: in terms of initially last year, Mark Zuckerberg said there

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Speaker 1: was no impact whatsoever. They said that again even recently, right,

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Speaker 1: they did say the election, which is the unknowable thing. Yes,

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Speaker 1: well they wanted to. You know, they just keep saying it,

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Speaker 1: and they maybe it's like Trump, right, they just keep saying,

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Speaker 1: the crowds are bigger, the crowds are bigger than crowds

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Speaker 1: were here. UM. I think one of the things is

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Speaker 1: they're very you know, they're very technical and mathematical people,

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Speaker 1: and so they're being very accurate about certain things they're

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Speaker 1: saying and and focusing in on and missing the forest

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Speaker 1: through the trees. You know, a lot of this stuff unquantifiable.

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Speaker 1: Some of it is, some of it is. But I

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Speaker 1: think the overall issue is that they're they're they're technically

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Speaker 1: saying these ads were not run. Until these ads were,

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Speaker 1: they weren't talking about the content on the platform. It's

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Speaker 1: so much larger and bigger than they're discussing. But technically

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Speaker 1: their ads were bought at various times, and so their

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Speaker 1: their whole premise around this is that these ads didn't

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Speaker 1: sway the election, and everyone else is like, well, there's

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Speaker 1: an indictment by Robert Mueller that shows how they used

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Speaker 1: primarily Facebook and Instagram to invade the system and take

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Speaker 1: advantage of the system. And I liken it to I mean,

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Speaker 1: if you think about it, what if Russia had bought

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Speaker 1: all the advertisements on a network or run the content

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Speaker 1: of a network during a presidential election and swayed it.

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Speaker 1: And they don't. They're not, they're not. They don't want

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Speaker 1: to take responsibility for the fact that their platform was

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Speaker 1: used by a malevolent power to create discord in our

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Speaker 1: country and that doesn't seem to bother them as much

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Speaker 1: as technically our ads weren't bought into here, the platforms

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Speaker 1: were used and abused, because you know, it's sort of

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Speaker 1: like why would you rob a bank. That's where the

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Speaker 1: money is, that's where the people are. So these platforms,

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Speaker 1: and Facebook being the biggest one, have been much abused

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Speaker 1: by malevolent powers. So what's going to happen like when

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Speaker 1: you think about Facebook, Karen, you think about say, YouTube,

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Speaker 1: which has also had a lot of problems with I

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Speaker 1: just intornography and inappropriate content, and advertisers are now shying

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Speaker 1: away from that. I mean, what what is the solution

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Speaker 1: for these companies with they you know, the genies out

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Speaker 1: of the bottle? Well, I just had a long interview

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Speaker 1: with Susan Wijiski at one of our events earlier this week. Actually,

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Speaker 1: who's the CEO? Very thoughtful person. I just had her

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Speaker 1: on an NBC MSNBC show. I did. I really like her.

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Speaker 1: She's great, She's great. But I mean they're trying very

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Speaker 1: hard because they know that these platforms are massive. I

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Speaker 1: mean the they I think it's a trillion hours a

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Speaker 1: week or some it's some enormous number that's being uploaded

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Speaker 1: to YouTube and all these social media platforms, and so

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Speaker 1: the ability of them to monitor it is enormous. They don't.

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Speaker 1: There's obviously people can't do it. It's not it's not

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Speaker 1: feasible for people to do it's not scalable. And then secondly,

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Speaker 1: the technology around AI and other machine learning in order

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Speaker 1: to to maybe control this better is still in its

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Speaker 1: infancy and very problematic. And so they they're trying to

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Speaker 1: figure out how to maintain order, I guess, and at

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Speaker 1: the same time pretend they're not media companies. And so

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Speaker 1: when I interview them, I do a lot of well

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Speaker 1: are you immediate? No, we're not where I think Susan

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Speaker 1: was like where a technology platform whose end result is

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Speaker 1: media or something. It was something like really convoluted ways.

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Speaker 1: Do you think they're so reticent to be you know,

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Speaker 1: because it requires responsibility, because it requires responsibility there. That

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Speaker 1: means they're responsible. Like the New York Times cares if

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Speaker 1: it's wrong, right, you know, whatever people think of the

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Speaker 1: New York Times or whatever liberal media or whatever. You know,

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Speaker 1: working at any of these institutions, we care when we're wrong.

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Speaker 1: We say we're wrong. We like correct and it matters.

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Speaker 1: There's a great deal of heaviness to the responsibility. Well,

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Speaker 1: they're like I think they say they're the pipes. They're not.

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Speaker 1: That goes through it, right, even as they ruin the

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Speaker 1: business plans of every publisher, you know what I mean,

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Speaker 1: it's really they have to take it's a different kind

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Speaker 1: of media company. But they're a media company. But the

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Speaker 1: minute they admit their a media company, it means they

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Speaker 1: have responsibility for what's on their platform, and and there's

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Speaker 1: lots of laws why they don't want that to happen

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Speaker 1: to like they don't they want to just say they're

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Speaker 1: at the nine platform essentially. Do you think that's ever

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Speaker 1: going to change? I mean, what, how do you see

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Speaker 1: this all? You know? No, I don't think that there

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Speaker 1: would be any regulation. There's there's always talk about it.

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Speaker 1: And obviously I'm interviewing Corey Booker and others. The Democrats

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Speaker 1: are suddenly which were the friend of internet, are now

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Speaker 1: turning on the Internet, which is really interesting. Um and

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Speaker 1: so we'll see if the Democrats get in power, if

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Speaker 1: there's more regulation. But so far the US and where

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Speaker 1: most of this is taking place, has been toothless. Europe,

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Speaker 1: on the other hand, there's a woman named Marguerite Vestiger

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Speaker 1: who's been very tough on all the big media companies

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Speaker 1: in Europe. She's a she's a commissioner at the EU.

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Speaker 1: I think it's for competition. I forget her long title,

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Speaker 1: but she's vanta. I did a great podcast an interview

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Speaker 1: with her. She's she's really an interesting force and she's

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Speaker 1: the one that's levied all these fines on these companies

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Speaker 1: and and really has the teeth to really bother them

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Speaker 1: in these countries. And I think the European Union and

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Speaker 1: Europe has a very different point of view on privacy,

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Speaker 1: on abuse, on all kinds of things that that is

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Speaker 1: problematic for tech US tech companies. But in the US,

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Speaker 1: you know, they roll over. Everybody rolls over. And obviously

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Speaker 1: our Twitter in chief, our troll in chiefs Donald Trump

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Speaker 1: is using the medium to his own advantage. It's time

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Speaker 1: to take a quick break. We'll have more of my

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Speaker 1: conversation with Kara Swisher right after this. And now back

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Speaker 1: to my conversation with Kara Swisher. You know, nobody knows this,

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Speaker 1: but we like each other, Katie character, don't we We like? Yes,

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Speaker 1: I admire you. I like you. I think you're really smart,

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Speaker 1: really funny, and really good at what you do. So,

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Speaker 1: speaking of that, how did you get into this crazy business?

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Speaker 1: I know you went to Georgetown, you started writing for

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Speaker 1: your school newspaper. You could call the Washington Post to

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Speaker 1: bitch them out about an artist, which made me laugh

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Speaker 1: because you thought that they did a big bad job

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Speaker 1: covering something at Georgetown. Yeah I did, I did. I

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Speaker 1: was mad at them for a piece and if you

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Speaker 1: outdate myself, Roberto Dabizon, remember him from Nicaragua, the awful

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Speaker 1: killer of women and children at Nicaragua, he led the

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Speaker 1: desk squads, and so I thought it was irresponsible they

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Speaker 1: didn't do a good job covering him. So, you know

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Speaker 1: what I thought was really interesting about that story, Kara,

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Speaker 1: though you called, and I don't remember the editor to

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Speaker 1: whom you spoke, it's what's Larry Kramer. So Larry Kramer,

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Speaker 1: which I really thought was cool, said come in and

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Speaker 1: talk to me about it. Now. If he hadn't done that,

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Speaker 1: do you think you would have gotten into journalism anyway?

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Speaker 1: That's a good question. Yes, I was. I was already

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Speaker 1: really writing a lot. Yes, percent. I think getting that

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Speaker 1: break to go to the Washington Post was a big deal. Um.

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Speaker 1: And it was a big deal too because it you know,

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Speaker 1: you know how it elevates you when you go where

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Speaker 1: did you start? You started out like a small I

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Speaker 1: started at ABC News in Washington, getting Frank frendin tam

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Speaker 1: Sandwich is, making coffee and passing out xeroxes of the Rundown.

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Speaker 1: Guess what I did? Delivered mail? You know that? And

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Speaker 1: you know what was really interesting about working from the beginning,

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Speaker 1: as I was in the mail room and I did

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Speaker 1: night news aid and things like that at the Washington

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Speaker 1: Post when I was younger, when I was in college,

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Speaker 1: was that you understand the dynamics of politics of a

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Speaker 1: newsroom much better from a lower wrong. I don't know

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Speaker 1: if you did. I learned that really talented people weren't

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Speaker 1: quite as difficult as the less talented people. Yeah, I

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Speaker 1: don't know if I learned that, but I did learn

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Speaker 1: through osmosis, just kind of how a newsroom worked. I

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Speaker 1: think it's sort of feeds your curiosity. You watch people

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Speaker 1: who you admire, who you think are good, who are tough,

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Speaker 1: um and um. I also think it makes you think, hey,

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Speaker 1: if they can do it, I can do it, because

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Speaker 1: they're not that great, right exactly. And I think I

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Speaker 1: took I think you probably did the same thing. I

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Speaker 1: took every opportunity I got, every time someone handed me

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Speaker 1: a chance, I took it. And like, oh, someone go

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Speaker 1: to the Smithsonian to write about this dumb like rock

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Speaker 1: collection story, and I just said, I'll do it, you

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Speaker 1: know what I mean, I'll do it. Was my definitely

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Speaker 1: right say yes to everything, everything. And I think that

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Speaker 1: is a really important, you know, and a valuable piece

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Speaker 1: of advice for people starting out, don't you, Kara, Yeah,

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Speaker 1: I do absolutely think one of the things it was

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Speaker 1: more than yes, I just I didn't just say yes,

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Speaker 1: I just I literally would do whatever kind of thing.

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Speaker 1: And I think I you know, one of the things

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Speaker 1: I was talking to some of the other day, they

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Speaker 1: were like, what do you regret? And I'm like, I

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Speaker 1: didn't really travel. I went right to work like I worked.

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Speaker 1: I think you'd probably did the same thing. Is I

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Speaker 1: didn't like take time off. I didn't like go and

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Speaker 1: find myself in you know, Thailand. I know for me,

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Speaker 1: work is like oxygen. You know, I have to work.

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Speaker 1: I and and I know you feel the same way.

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Speaker 1: And I'm wondering I didn't realize. I feel like I

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Speaker 1: know a lot about you, but I don't think I

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Speaker 1: knew that your dad died when you were just five

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Speaker 1: years old. Um, and and he had a cerebral hemorrhage

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Speaker 1: and you know it. Yeah, And he was how old, Kara,

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Speaker 1: thirty four years old, which is so heartbreaking. And you

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Speaker 1: know that was the age Ellie was when Jay died,

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Speaker 1: my my late husband. And do you remember for your dad?

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Speaker 1: You know. It's funny. I do in bits and pieces,

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Speaker 1: and I don't know how much she does. You should.

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Speaker 1: You know, a lot of people whose parents died a

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Speaker 1: young age or or something called highly functional because they

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Speaker 1: become like half their life goes away. Really, if you

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Speaker 1: think about it, if you're five, you don't have much

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Speaker 1: reference to other friends and family and things that you

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Speaker 1: reference your parents pretty much, and so you get highly

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Speaker 1: functional because the worst thing in the world happened to

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Speaker 1: you and you survived. And I think a lot of

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Speaker 1: people kids whose parents died a young age, but they

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Speaker 1: just move faster because they realize, you know, the ephemorality

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Speaker 1: of life. And then at the same time, um, they

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Speaker 1: can deal with things. Things don't bother them that much,

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Speaker 1: like both negative and positive. You want to be bothered

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Speaker 1: by certain things in life, but you definitely roll on through.

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Speaker 1: Is your mom still living? Yes she is? Oh, yes,

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Speaker 1: you do. You find me worried about her a lot

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Speaker 1: because the one thing that I've noticed, and I had

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Speaker 1: talked with Carrie, my younger daughter, about this because Ellie

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Speaker 1: was at such a formative age. Carrie was just two

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Speaker 1: and Ellie had just turned I guess was six. It

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Speaker 1: had turned six, and she gets a lot of anxiety

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Speaker 1: about me because I think she doesn't you know, I'm

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Speaker 1: her only parent and do you feel that way about

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Speaker 1: your mom? No? And I'm sorry. We're an Italian family,

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Speaker 1: so no, I do not worry about it sometimes, like

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Speaker 1: she loves her Fox News. Let me just say so,

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Speaker 1: that's been a great interesting you guys not talk about

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Speaker 1: politics at the thanks table. Shut up. I had to

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Speaker 1: throw out of Thanksgiving one because she voted for Rink Santorum.

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Speaker 1: But that's in a long story. She said she wouldn't

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Speaker 1: because he was for anti gay stuff, and I said,

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Speaker 1: you can't vote for him and continue to have Thanksgiving

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Speaker 1: in New York City and she everywhere. She's in Mexico

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Speaker 1: City right now. It's interesting that she's quite a she's

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Speaker 1: like an anti name kind of person. Uh yeah, Fox

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Speaker 1: his his poison her brain completely. But but she's okay.

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Speaker 1: She's pretty funny. Um, you like girl, you'd like her, Katie,

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Speaker 1: she's fun. Oh yeah, she sounds fun. We'll have to

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Speaker 1: take a little lunch or something and just not talk

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Speaker 1: about politics too. But she doesn't like Trump so much.

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Speaker 1: But she you know, she loves Fox News. Oddly, she does.

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Speaker 1: She again't stand Trump. So listen after wait, I just

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Speaker 1: want to do a little more of your career stuff.

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Speaker 1: So after the Washington Post. Um, I mean, you are

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Speaker 1: such a force, Kara, and you're sort of the most

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Speaker 1: well liked and feared. I've read that a million places

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Speaker 1: journalists covering in Silicon Valley. And and how did you

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Speaker 1: get so interested in covering technology? I covered Steve Case

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Speaker 1: to Mayo. Well, Um, I was here in Washington at

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Speaker 1: the Washington Post, and I covered the Internet early early on, um,

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Speaker 1: when there was a tant interchange and all this other stuff.

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Speaker 1: And so I was super struck by the Internet from

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Speaker 1: a very early age. I had the Washington Post, had

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Speaker 1: a phone. I used a big, old, heavy one. It

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Speaker 1: was in a suitcase. Um, I was. I was riveted

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Speaker 1: to the idea that there was going to be a

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Speaker 1: mobile phone for some reason. Did you have one of

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Speaker 1: those like Maxwell smart car phones that looked like a

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Speaker 1: shoe box. I was not in my car, but it

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Speaker 1: was a suitcase that I brought in my car. That was.

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Speaker 1: And then I bought one of the you know, And

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Speaker 1: then I had one of the other phones that looked

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Speaker 1: like those big ones. And I had I've had early.

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Speaker 1: I've had phones forever. I one time was on a

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Speaker 1: vacation with someone I was going out with and I

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Speaker 1: was in the middle of a bay in Provincetown. It

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Speaker 1: was low tide and so I could walk out pretty

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Speaker 1: far and it's like it works out here, and I

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Speaker 1: think they broke up with me, right that. Yeah, No,

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Speaker 1: I just went on a vacation of Mexico with the

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Speaker 1: Nelly and who was supposed to be without any internet

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Speaker 1: or anything else, and of course I managed to find

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Speaker 1: a cellular connection somewhere, managed to find the one square

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Speaker 1: foot where would come in. I did hike up the

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Speaker 1: giant hill to get there. But whatever, it's details, Well,

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Speaker 1: do you worry, Donny, Do you worry about tech addiction,

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Speaker 1: because that's something that actually I am worried about, not

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Speaker 1: only for myself but for people in general, because I

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Speaker 1: see my daughters. One of the hours I'm doing for

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Speaker 1: Nacio shameless Plug is talking about this technology making us

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Speaker 1: lose our humanity because it really is changing, dramatically, changing

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Speaker 1: the nature nature of our relationships. And one thing I

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Speaker 1: heard Kara from an internet expert. In an addiction expert

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Speaker 1: out in California, I interviewed Larry Rosen. He said that

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Speaker 1: kids are actually developing plaque in their brain because phones

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Speaker 1: and screen time is actually interrupting the mel a tonent

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Speaker 1: in their brain and increasing cortisol. And they're very, very

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Speaker 1: worried about early dementia among these addicted kids. Which wasn't

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Speaker 1: enough to freak me out. Oh my goodness, yeah, Katie,

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Speaker 1: that's terrible. I'm sorry to make the news to you,

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Speaker 1: but so I'm completely demented right now. Then I think, uh,

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Speaker 1: you know, it's not to joke about it. I agree.

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Speaker 1: I think it's going to be a big topic this year.

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Speaker 1: I think, uh, you know, people talk about this and

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Speaker 1: again this is the next wave of hit hits. The

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Speaker 1: companies like Facebook definitely and sing you hear more more

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Speaker 1: people making noise. One of the guys I interviewed, Tristan Tris,

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Speaker 1: who I just think is I love him, Kara. He's

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Speaker 1: such a remarkable young man. He's thirty three years old.

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Speaker 1: He quick Google right because he said was it Google

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Speaker 1: or Google? Because he felt like these tech companies are

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Speaker 1: manipulating us so much and they're making us addicted by

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Speaker 1: and I see it taking same theme, not taking responsibility

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Speaker 1: for what they're doing. And so one of the things,

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Speaker 1: you know, people are liking him. I'm media companies are

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Speaker 1: like him to dissigarette companies. I think that's probably taking

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Speaker 1: it slightly too far. But there is uh there there

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Speaker 1: is a question of how much warning people should have,

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Speaker 1: how much knowing about how much science needs to happen.

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Speaker 1: That's one of the reasons I wanted to do this hour.

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Speaker 1: You know, we're operating and it's like minute by minute,

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Speaker 1: and nobody I think in the media culture takes a

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Speaker 1: step back and says, wait a second, let's take a

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Speaker 1: look at some of these big issues. Because I think

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Speaker 1: this is such an incredibly transformational time in almost every arena,

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Speaker 1: but nobody is sort of debating it or talking about it.

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Speaker 1: They don't want to. These internet companies don't want to

424
00:20:35,000 --> 00:20:36,680
Speaker 1: do that because I think what they've been doing is

425
00:20:36,720 --> 00:20:38,720
Speaker 1: growing at a breaknext speed. And one of the things

426
00:20:38,800 --> 00:20:40,600
Speaker 1: I started to do last year, right when they went

427
00:20:40,640 --> 00:20:42,720
Speaker 1: to visit Trump, Remember they all trooped up to Trump

428
00:20:42,760 --> 00:20:45,399
Speaker 1: Tower and and didn't say anything about immigration, And I

429
00:20:45,440 --> 00:20:48,360
Speaker 1: had I wrote one of these skull the Scullly columns

430
00:20:48,359 --> 00:20:50,680
Speaker 1: about it, talking about how dare you do this without

431
00:20:50,680 --> 00:20:55,199
Speaker 1: discussing immigration? This guy has been so anti immigrant, you know,

432
00:20:55,240 --> 00:20:58,840
Speaker 1: which has been the fuel for Silicon Valley. Essentially all

433
00:20:58,840 --> 00:21:03,520
Speaker 1: the major companies founded by immers Elon Musk, Sergei Brand, Saton, Adela,

434
00:21:03,680 --> 00:21:07,439
Speaker 1: uh Seve Jobs parents father was an immigrant, um and

435
00:21:07,520 --> 00:21:10,320
Speaker 1: so in eight of them, you know, Susan Wachsky's parents

436
00:21:10,320 --> 00:21:14,119
Speaker 1: are from father's from country. UM. So I was I

437
00:21:14,160 --> 00:21:16,320
Speaker 1: was really angry at them for doing that by walking

438
00:21:16,400 --> 00:21:17,760
Speaker 1: up there, and they were all like, oh, you know,

439
00:21:17,840 --> 00:21:19,600
Speaker 1: we'll get to it. He's not he doesn't mean what

440
00:21:19,640 --> 00:21:21,520
Speaker 1: he says. I'm like, he means what he says, you know,

441
00:21:21,600 --> 00:21:23,600
Speaker 1: around this topic, as he said it so many times

442
00:21:23,600 --> 00:21:27,120
Speaker 1: and was one of his basic promises to his constituency.

443
00:21:27,240 --> 00:21:29,240
Speaker 1: And so I think what they want to do is

444
00:21:29,359 --> 00:21:32,000
Speaker 1: act as if they are the saviors of humanity and

445
00:21:32,040 --> 00:21:35,520
Speaker 1: not take the responsibility for what their inventions create. Um.

446
00:21:35,560 --> 00:21:37,520
Speaker 1: And that and tech addiction is just one of the many.

447
00:21:37,560 --> 00:21:39,360
Speaker 1: And I think, you know, you at some point you do,

448
00:21:39,840 --> 00:21:41,680
Speaker 1: like I get, I get a lot of push back

449
00:21:41,720 --> 00:21:44,119
Speaker 1: this past year like you're such a skull, and I'm like, no,

450
00:21:44,440 --> 00:21:47,119
Speaker 1: you need to grow up and start to understand not

451
00:21:47,200 --> 00:21:50,119
Speaker 1: just tech addiction, but job displacement, Like what's going to

452
00:21:50,160 --> 00:21:52,760
Speaker 1: happen around AI and automation. Well, let's can we talk

453
00:21:52,800 --> 00:21:55,640
Speaker 1: about that too, because that's that's something that that I

454
00:21:55,680 --> 00:22:00,359
Speaker 1: addressed in this hour of jobs are suscept doble to

455
00:22:00,400 --> 00:22:04,239
Speaker 1: automation eliminating them by the early twenty thirties. I know

456
00:22:04,320 --> 00:22:07,920
Speaker 1: you did a town hall series with MSNBC about that

457
00:22:08,000 --> 00:22:09,879
Speaker 1: and with jobs in the future. This is something that

458
00:22:09,960 --> 00:22:13,400
Speaker 1: I've been really interested in because you know, it's a job.

459
00:22:13,480 --> 00:22:16,040
Speaker 1: These jobs are not being lost to globalization, they're being

460
00:22:16,040 --> 00:22:21,160
Speaker 1: lost to automation and and so so I mean, it's

461
00:22:21,240 --> 00:22:23,959
Speaker 1: a huge dilemma and I think it's actually part of

462
00:22:24,000 --> 00:22:27,760
Speaker 1: what's feeding white working class frustration. Another hour I'm doing

463
00:22:27,800 --> 00:22:30,600
Speaker 1: on that GEO. So what what is the solution here?

464
00:22:30,640 --> 00:22:33,440
Speaker 1: I mean, I don't know, because you know, I got

465
00:22:33,440 --> 00:22:36,040
Speaker 1: the inspiration from doing that series eMac from Mark Andres

466
00:22:36,080 --> 00:22:38,679
Speaker 1: and I who've been arguing for decades. How he and

467
00:22:38,720 --> 00:22:40,560
Speaker 1: I argue about all kinds of things, But one of

468
00:22:40,560 --> 00:22:42,080
Speaker 1: the things he was telling about was that it's like

469
00:22:42,119 --> 00:22:47,280
Speaker 1: the farming to manufacturing. Definitely, And look except except that

470
00:22:47,280 --> 00:22:50,600
Speaker 1: that happened over seventy some years and it was a

471
00:22:50,720 --> 00:22:53,480
Speaker 1: very and it was huge political uprising because of it,

472
00:22:53,600 --> 00:22:56,080
Speaker 1: and now in this age of social media and also

473
00:22:56,440 --> 00:23:01,800
Speaker 1: constant and repeated media everywhere, people's feeling, you know, so

474
00:23:02,359 --> 00:23:04,760
Speaker 1: apart from each other, and so part is in it's

475
00:23:04,800 --> 00:23:06,399
Speaker 1: a it's a powder keke as far as I can,

476
00:23:06,600 --> 00:23:08,639
Speaker 1: you know, I mean, you really create agree, you know.

477
00:23:08,680 --> 00:23:10,760
Speaker 1: Steve Case has talked about this. J. D. Vance is

478
00:23:10,760 --> 00:23:14,560
Speaker 1: great book, Killabilly Elegy. There is a massive transition about

479
00:23:14,600 --> 00:23:17,639
Speaker 1: to happen around jobs that people are not paying attention to,

480
00:23:17,760 --> 00:23:19,440
Speaker 1: and I don't want to be one of them. Wrote

481
00:23:19,440 --> 00:23:22,359
Speaker 1: a great book based on a Harvard Business Review article

482
00:23:22,440 --> 00:23:25,440
Speaker 1: called just called White Working Class, which talks a lot

483
00:23:25,480 --> 00:23:29,440
Speaker 1: about class cluelessness and cultural condescension and all just highly

484
00:23:29,520 --> 00:23:32,040
Speaker 1: recommend it's such as why it say what? Who is

485
00:23:32,080 --> 00:23:34,160
Speaker 1: thinking of it? That's I don't want to like say, Okay,

486
00:23:34,200 --> 00:23:36,000
Speaker 1: there's not gonna be better jobs in the future that

487
00:23:36,359 --> 00:23:37,919
Speaker 1: but who what are we gonna do about it? One

488
00:23:37,960 --> 00:23:41,160
Speaker 1: of the things that Nellie just interviewed Robert rich who

489
00:23:41,200 --> 00:23:43,800
Speaker 1: was the former Labor Secretary Beery, and one of the

490
00:23:43,800 --> 00:23:45,439
Speaker 1: things he said in this interview, they did a New

491
00:23:45,520 --> 00:23:48,399
Speaker 1: York Times thing on ei AI. It was an event

492
00:23:48,680 --> 00:23:50,040
Speaker 1: and one of the things that I thought was the

493
00:23:50,040 --> 00:23:51,959
Speaker 1: best quote that came out of it was you were

494
00:23:51,960 --> 00:23:54,760
Speaker 1: either this is universal. She was asked a universal basic income,

495
00:23:54,800 --> 00:23:57,400
Speaker 1: which is you pay people essentially when jobs get lost.

496
00:23:57,440 --> 00:23:59,480
Speaker 1: And it's you know a lot of it's very controversial.

497
00:23:59,480 --> 00:24:01,159
Speaker 1: It feels like communism a little bit, you know what

498
00:24:01,200 --> 00:24:02,600
Speaker 1: I mean. It's a question, but it's one of the

499
00:24:02,640 --> 00:24:06,120
Speaker 1: ideas of how to deal with this joblessness and uh

500
00:24:06,160 --> 00:24:10,560
Speaker 1: and eventual joblessness. Um. He said, you either are gonna

501
00:24:10,600 --> 00:24:14,000
Speaker 1: pay pay then these numbers to pay people to not

502
00:24:14,119 --> 00:24:17,919
Speaker 1: work essentially, or you're gonna pay to bulletproof you're tesla

503
00:24:18,680 --> 00:24:21,240
Speaker 1: like And I was like, oh wow, that's because people

504
00:24:21,280 --> 00:24:23,199
Speaker 1: are gonn You're gonna create this sort of Brazil like

505
00:24:23,359 --> 00:24:26,840
Speaker 1: situation where there's very war and very rich. Um. And

506
00:24:26,840 --> 00:24:28,560
Speaker 1: and that's going to be We've got to really my

507
00:24:28,720 --> 00:24:31,960
Speaker 1: question is who's thinking about it? Who among our Is

508
00:24:32,000 --> 00:24:34,679
Speaker 1: it the tech companies whose responsibilities that the tech companies

509
00:24:34,680 --> 00:24:37,159
Speaker 1: is a government? Is it's citizens? I think, yeah, I

510
00:24:37,160 --> 00:24:39,240
Speaker 1: think it's all the above. But you're right, it's very

511
00:24:39,280 --> 00:24:42,160
Speaker 1: frustrating that people are just kind of have their head

512
00:24:42,160 --> 00:24:45,399
Speaker 1: in the sands about sand about this. Zoe Baird is

513
00:24:45,440 --> 00:24:49,320
Speaker 1: working very hard on this thing called skillful and she's

514
00:24:49,359 --> 00:24:52,080
Speaker 1: working with Governor hick and Looper in Colorado to try

515
00:24:52,119 --> 00:24:56,200
Speaker 1: to come up with a way to retrain and uh,

516
00:24:56,240 --> 00:24:59,400
Speaker 1: you know, especially displaced workers. But I think our whole

517
00:24:59,520 --> 00:25:03,480
Speaker 1: education system needs to be reevaluated. I went to Johnstown, Pennsylvania,

518
00:25:03,680 --> 00:25:06,320
Speaker 1: where they're of the high school students are involved in

519
00:25:06,400 --> 00:25:10,439
Speaker 1: vocational training, and I just think that this we just

520
00:25:10,480 --> 00:25:13,600
Speaker 1: have to really kind of everybody has to put their

521
00:25:13,680 --> 00:25:16,359
Speaker 1: their thinking where it's going and where it's going because

522
00:25:16,400 --> 00:25:17,879
Speaker 1: some of these jobs you don't even I mean some

523
00:25:17,920 --> 00:25:19,040
Speaker 1: of the jobs. There was a great story in The

524
00:25:19,160 --> 00:25:22,439
Speaker 1: York Times recently about Sweden that they were doing robots

525
00:25:22,480 --> 00:25:25,399
Speaker 1: are doing mining essentially right, and all kinds of like

526
00:25:25,800 --> 00:25:28,280
Speaker 1: why should people like this whole thing about Kentucky going

527
00:25:28,320 --> 00:25:31,480
Speaker 1: back to coal mining. People probably shouldn't coal mine like this.

528
00:25:31,720 --> 00:25:35,320
Speaker 1: It's very dangerous. It's you know, there's certain jobs, wrote

529
00:25:35,440 --> 00:25:38,280
Speaker 1: jobs that maybe people shouldn't do anymore, and it wasn't

530
00:25:38,320 --> 00:25:40,520
Speaker 1: good for people in the first place, So why just

531
00:25:40,720 --> 00:25:44,720
Speaker 1: have them there when robots can do it better? What's hard? Karras,

532
00:25:44,760 --> 00:25:48,800
Speaker 1: You know, these are generational, traditional jobs that have been

533
00:25:48,880 --> 00:25:52,680
Speaker 1: passed on. It is part of certain people's DNA. So

534
00:25:52,760 --> 00:25:57,440
Speaker 1: we have to rethink education, rethink all the different possibilities

535
00:25:57,520 --> 00:26:01,160
Speaker 1: and how from the get go, from pre k on

536
00:26:01,720 --> 00:26:05,000
Speaker 1: we start orienting people towards the jobs of the future.

537
00:26:05,359 --> 00:26:07,359
Speaker 1: Thank you who knows, who knows? Thank you, Thank you

538
00:26:07,440 --> 00:26:10,520
Speaker 1: President correct Um. But but but the thing is, uh,

539
00:26:11,119 --> 00:26:12,840
Speaker 1: we can't. They can't even decide in lunch. They can't

540
00:26:12,840 --> 00:26:15,240
Speaker 1: pass a dreamer's Act. And this is like, for example,

541
00:26:15,240 --> 00:26:17,400
Speaker 1: the Dreamer's Act thing is just driving me crazy because

542
00:26:17,400 --> 00:26:19,720
Speaker 1: it's literally an advertisement to the rest of the world

543
00:26:19,960 --> 00:26:22,520
Speaker 1: that we don't like innovation, we don't like innovative people,

544
00:26:22,560 --> 00:26:25,000
Speaker 1: we don't like people who work harder. It is such

545
00:26:25,000 --> 00:26:27,560
Speaker 1: a message to the rest of the world, which again

546
00:26:27,680 --> 00:26:30,800
Speaker 1: we have. The technology and innovation in this country has

547
00:26:30,840 --> 00:26:33,760
Speaker 1: been fueled by immigrants, no matter how you slice of

548
00:26:33,840 --> 00:26:37,560
Speaker 1: people coming in, fresh ideas, fresh thinking, and and the

549
00:26:37,640 --> 00:26:41,440
Speaker 1: and so hard king you know exactly the people all

550
00:26:41,720 --> 00:26:44,359
Speaker 1: you know, the scrappy people who have something to prove

551
00:26:44,520 --> 00:26:47,320
Speaker 1: who I mean, those are the people who change the world,

552
00:26:47,400 --> 00:26:50,080
Speaker 1: not people who you know, pardon the expression, are born

553
00:26:50,119 --> 00:26:51,800
Speaker 1: with the silver spoon in their mouth. Right. And the

554
00:26:51,840 --> 00:26:53,720
Speaker 1: problem is, I think one of the things you know,

555
00:26:53,800 --> 00:26:56,119
Speaker 1: we can get a diversity in the next section. But

556
00:26:56,160 --> 00:26:57,679
Speaker 1: I do need to talk to you about Yahoo. I

557
00:26:57,680 --> 00:27:01,320
Speaker 1: need to. And then when I talked to you about

558
00:27:01,359 --> 00:27:03,280
Speaker 1: like how you're able to get so many people to

559
00:27:03,359 --> 00:27:06,840
Speaker 1: talk to you, and how you stay in the business

560
00:27:06,880 --> 00:27:09,320
Speaker 1: without pissing so many people off, they never talk to

561
00:27:09,400 --> 00:27:11,560
Speaker 1: you again. Well, I'm about to piss everyone off. I

562
00:27:11,600 --> 00:27:12,840
Speaker 1: think at the end of my career is gonna be

563
00:27:12,880 --> 00:27:19,159
Speaker 1: one big disaster. No, You're just like a Roman candle Kadie.

564
00:27:19,200 --> 00:27:22,720
Speaker 1: I'm going out big and ugly. Um. So the finish

565
00:27:22,800 --> 00:27:24,240
Speaker 1: of this section, one of the things I think is

566
00:27:24,400 --> 00:27:26,240
Speaker 1: what I think about when I think about these ideas

567
00:27:26,240 --> 00:27:29,960
Speaker 1: around not accepting people in this country and around and

568
00:27:30,040 --> 00:27:32,199
Speaker 1: keeping in an open borders and things like that in

569
00:27:32,280 --> 00:27:34,760
Speaker 1: order to do this um is that there is a

570
00:27:35,240 --> 00:27:38,240
Speaker 1: like including around the issues of diversity, to like not

571
00:27:38,400 --> 00:27:42,119
Speaker 1: bringing not thinking bigger. There is a I have this

572
00:27:42,440 --> 00:27:45,720
Speaker 1: vision in my head of a small girl in Afghanistan

573
00:27:46,119 --> 00:27:48,439
Speaker 1: who knows how to solve cancer. It's in her brain,

574
00:27:48,600 --> 00:27:50,160
Speaker 1: like who is going to be the one that doesn't?

575
00:27:50,280 --> 00:27:52,840
Speaker 1: Who will never get there because of all kinds of

576
00:27:52,880 --> 00:27:56,720
Speaker 1: issues either immigration or discrimination or whatever there there are.

577
00:27:56,760 --> 00:27:59,720
Speaker 1: We don't know who hasn't been able to invent things

578
00:27:59,800 --> 00:28:03,480
Speaker 1: because of the barriers we put in people's way that

579
00:28:03,560 --> 00:28:05,960
Speaker 1: we could remove and create a better place. And I

580
00:28:05,960 --> 00:28:07,920
Speaker 1: know it sounds like sort of pie in the sky,

581
00:28:08,040 --> 00:28:11,160
Speaker 1: but the more barriers we put in front of people

582
00:28:11,240 --> 00:28:15,080
Speaker 1: to be innovative, the less humanity benefits. I agree with you,

583
00:28:16,160 --> 00:28:20,040
Speaker 1: and I think the Internet is helping remove some of

584
00:28:20,080 --> 00:28:23,159
Speaker 1: those barriers in terms of giving people a pathway to

585
00:28:23,320 --> 00:28:28,359
Speaker 1: education and exposing them to, you know, ideas that they'd

586
00:28:28,359 --> 00:28:31,240
Speaker 1: never be exposed to otherwise. Well, we're gonna talk about

587
00:28:31,240 --> 00:28:32,520
Speaker 1: that more because we get you talked to James to

588
00:28:32,600 --> 00:28:35,120
Speaker 1: Moore and others for your one of your that I

589
00:28:35,160 --> 00:28:38,800
Speaker 1: was talking on Yahoo. Yeah, Katie, what happened? Well, I

590
00:28:38,840 --> 00:28:43,240
Speaker 1: think it was a really interesting experience. I think that, Um,

591
00:28:43,280 --> 00:28:45,520
Speaker 1: you know, I think the real issue is many of

592
00:28:45,560 --> 00:28:47,600
Speaker 1: these tech companies. I mean, it's what we were talking

593
00:28:47,640 --> 00:28:50,960
Speaker 1: about earlier. They are not media companies. They do not

594
00:28:51,440 --> 00:28:57,680
Speaker 1: care deeply about stories about content, about true connection. I

595
00:28:57,720 --> 00:29:01,200
Speaker 1: think they care about widgets and djets and how to

596
00:29:01,520 --> 00:29:05,680
Speaker 1: and delivery systems, but they aren't really super interested in

597
00:29:06,360 --> 00:29:09,840
Speaker 1: you know, the vegetable soup that's running through the pipes,

598
00:29:10,440 --> 00:29:12,880
Speaker 1: and um, and I think for me it was just

599
00:29:12,960 --> 00:29:17,400
Speaker 1: a bit of a culture clash. I think that the problems,

600
00:29:17,440 --> 00:29:21,480
Speaker 1: the challenges of making sure people got good content was

601
00:29:21,560 --> 00:29:24,440
Speaker 1: just not high on their priority list, right, So what

602
00:29:24,520 --> 00:29:26,400
Speaker 1: do you do? When you went in, you were thinking

603
00:29:26,440 --> 00:29:32,440
Speaker 1: what a Yeah. I saw the world changing. I saw people,

604
00:29:33,400 --> 00:29:37,960
Speaker 1: uh consuming information. I saw this pipeline, whether you know

605
00:29:38,680 --> 00:29:44,760
Speaker 1: direct discernment, dis disintermedia or you know, using these pipes

606
00:29:44,840 --> 00:29:49,000
Speaker 1: to reach people as something that was incredibly promising. And

607
00:29:49,080 --> 00:29:52,240
Speaker 1: I thought Yahoo, I said to marissamr I said, do

608
00:29:52,280 --> 00:29:54,960
Speaker 1: you want to be known as the company that serves

609
00:29:55,040 --> 00:29:57,360
Speaker 1: up stories about the boy who lived on Ramen noodles

610
00:29:57,400 --> 00:30:00,120
Speaker 1: for thirteen years? Or do you want to kind of

611
00:30:00,200 --> 00:30:04,040
Speaker 1: have really important, interesting, substantive interviews. Do you want to

612
00:30:04,160 --> 00:30:07,400
Speaker 1: educate and enlighten people? Do you want to raise the bar?

613
00:30:07,840 --> 00:30:09,600
Speaker 1: And you know, it doesn't mean you can't have the

614
00:30:09,680 --> 00:30:11,920
Speaker 1: Roman noodle story, but you could do maybe a high

615
00:30:11,960 --> 00:30:14,400
Speaker 1: low thing like they do in fashion. You know, you

616
00:30:14,400 --> 00:30:16,920
Speaker 1: were a sweater from burn Doors and jeans from Jay

617
00:30:17,000 --> 00:30:20,360
Speaker 1: Crew whatever. So she seemed to be open, but I

618
00:30:20,360 --> 00:30:23,840
Speaker 1: don't think she was ever sort of understood the commitment

619
00:30:23,920 --> 00:30:26,000
Speaker 1: that would take. And I just think she had a

620
00:30:26,000 --> 00:30:28,760
Speaker 1: lot of other things on her plate and fairness, and

621
00:30:28,840 --> 00:30:32,480
Speaker 1: so you know I wouldn't because they were a huge company. Marriage,

622
00:30:32,520 --> 00:30:35,520
Speaker 1: but it was certainly not very fulfilling for me because

623
00:30:35,840 --> 00:30:39,120
Speaker 1: I had all this great content. I was getting big interviews,

624
00:30:39,200 --> 00:30:40,960
Speaker 1: and it's sort of like a tree falling in the

625
00:30:41,000 --> 00:30:43,200
Speaker 1: forest because no one because they didn't put it on

626
00:30:43,200 --> 00:30:44,680
Speaker 1: the front page. Well they didn't put it on the

627
00:30:44,720 --> 00:30:47,000
Speaker 1: front page, or they didn't really know how to. I mean,

628
00:30:47,040 --> 00:30:50,840
Speaker 1: even now, they really don't have very good distributions, you know,

629
00:30:51,080 --> 00:30:53,800
Speaker 1: they don't. They didn't really know how to market things properly.

630
00:30:53,960 --> 00:30:58,920
Speaker 1: They didn't know how to take quality and make it scalable.

631
00:30:59,080 --> 00:31:01,120
Speaker 1: And at one point, you were paying for Facebook ads?

632
00:31:01,160 --> 00:31:04,000
Speaker 1: Is that correct or yourself? I did bring someone in.

633
00:31:04,240 --> 00:31:06,880
Speaker 1: I wasn't no, no, no, I wasn't paying. I did

634
00:31:06,880 --> 00:31:10,080
Speaker 1: bring someone in who was really an expert on micro targeting,

635
00:31:10,680 --> 00:31:13,440
Speaker 1: because you know, I would say to him, how can

636
00:31:13,600 --> 00:31:16,280
Speaker 1: how can my stuff get seen more? And I would,

637
00:31:16,400 --> 00:31:18,480
Speaker 1: you know, say to the Yahoo folks, can we please

638
00:31:18,520 --> 00:31:22,040
Speaker 1: do a newsletter. I'll totally push out everybody's content. I'll

639
00:31:22,040 --> 00:31:24,720
Speaker 1: make sure everyone sees Matt Buy's column, or I'll make

640
00:31:24,720 --> 00:31:28,040
Speaker 1: sure that people see Josie's fashion thing. You know people

641
00:31:28,040 --> 00:31:29,960
Speaker 1: they hired you need to be Yeah, they hired some

642
00:31:30,000 --> 00:31:31,880
Speaker 1: big names and yet you know, they were in the

643
00:31:31,920 --> 00:31:34,760
Speaker 1: witness protection program. So I said, let me help you,

644
00:31:34,880 --> 00:31:38,400
Speaker 1: help them, help us, help everybody. But they just I

645
00:31:38,400 --> 00:31:41,200
Speaker 1: don't know. Maybe it's because they were kind of at

646
00:31:41,240 --> 00:31:45,320
Speaker 1: that that time and are a legacy tech company that

647
00:31:45,400 --> 00:31:48,280
Speaker 1: they had kind of an attitude show to innovate. I think,

648
00:31:48,680 --> 00:31:51,400
Speaker 1: you know, it's a it's an attitude throughout tech. The

649
00:31:51,720 --> 00:31:56,880
Speaker 1: content doesn't matter. They have for content. It's not even

650
00:31:56,920 --> 00:32:00,360
Speaker 1: no respect. It's it's as if it's disdaining. Don't even

651
00:32:00,360 --> 00:32:02,400
Speaker 1: that it's really weird. It's like, oh, it's just another

652
00:32:02,440 --> 00:32:05,440
Speaker 1: thing they're pushing through the system. Essentially, it doesn't matter.

653
00:32:05,560 --> 00:32:08,600
Speaker 1: That's why I like. I think the Secret Sauce are

654
00:32:08,760 --> 00:32:13,960
Speaker 1: people who are technologically savvy but also respect and care

655
00:32:14,000 --> 00:32:18,040
Speaker 1: about storytelling. And the company that I think combines those

656
00:32:18,080 --> 00:32:21,400
Speaker 1: two things is going to be It's gonna win the day.

657
00:32:21,480 --> 00:32:24,120
Speaker 1: And I haven't really found it yet, have you guess?

658
00:32:24,440 --> 00:32:27,320
Speaker 1: By the way Box Doyes, we we tried to, but

659
00:32:27,360 --> 00:32:28,760
Speaker 1: we don't own the pipes, you know what I mean.

660
00:32:28,760 --> 00:32:31,280
Speaker 1: I do think sometimes when I talked to Evan Spiegel.

661
00:32:31,320 --> 00:32:33,840
Speaker 1: I do think, well, at least he gets the concepts

662
00:32:33,880 --> 00:32:37,600
Speaker 1: around it, like the idea that you differentiate or you curate,

663
00:32:37,680 --> 00:32:40,720
Speaker 1: and I think that's the that's the question, is the curation.

664
00:32:40,800 --> 00:32:42,160
Speaker 1: And I think that doesn't matter. I think one of

665
00:32:42,200 --> 00:32:45,080
Speaker 1: the things that I found fascinating from your tenure, besides

666
00:32:45,080 --> 00:32:47,240
Speaker 1: all the other things I was writing about there um,

667
00:32:47,520 --> 00:32:50,960
Speaker 1: was the they made this enormously high profile higher and

668
00:32:51,000 --> 00:32:52,960
Speaker 1: you are you know it was. It was a big

669
00:32:53,040 --> 00:32:56,320
Speaker 1: giant higher that they made and then they literally hit

670
00:32:56,360 --> 00:33:00,360
Speaker 1: you anywhere. That was so weird, right, It was just

671
00:33:00,920 --> 00:33:03,760
Speaker 1: just it's a business proposition. It's not like I'm all

672
00:33:03,800 --> 00:33:05,760
Speaker 1: that and a bag of ships. But like, if you

673
00:33:05,840 --> 00:33:08,960
Speaker 1: are going to invest in somebody like me who has

674
00:33:09,520 --> 00:33:11,760
Speaker 1: a quote unquote brand, which I hate that, but you know,

675
00:33:11,800 --> 00:33:15,960
Speaker 1: who is recognizable and has a connection with people, why

676
00:33:16,000 --> 00:33:19,280
Speaker 1: not leverage that. It was bizarre. I don't think they

677
00:33:19,320 --> 00:33:21,880
Speaker 1: meant it in the first place. I think it was no, no, no,

678
00:33:22,200 --> 00:33:24,840
Speaker 1: I think the very they never intended to do it,

679
00:33:24,880 --> 00:33:26,760
Speaker 1: but it wasn't e they It sounded good, it was

680
00:33:26,840 --> 00:33:28,920
Speaker 1: like a good press release, but it was sort of

681
00:33:28,960 --> 00:33:30,800
Speaker 1: They hired a lot of people so it was more

682
00:33:30,840 --> 00:33:32,360
Speaker 1: than a press It was something, you know what I mean,

683
00:33:32,400 --> 00:33:34,760
Speaker 1: Like that was what was interesting the whole I just

684
00:33:34,880 --> 00:33:36,920
Speaker 1: was it was sort of a sidelight and I don't

685
00:33:36,920 --> 00:33:38,840
Speaker 1: think it was even as cynical as just a press release.

686
00:33:38,880 --> 00:33:40,840
Speaker 1: I think they thought they want no I think you're right.

687
00:33:40,960 --> 00:33:44,200
Speaker 1: I think they just didn't understand what it required. And

688
00:33:44,560 --> 00:33:46,400
Speaker 1: I would try to say, hey, let me bring this

689
00:33:46,480 --> 00:33:49,960
Speaker 1: person in to run media who really gets it, and

690
00:33:50,560 --> 00:33:53,400
Speaker 1: you know, and they just I don't know. It was

691
00:33:53,680 --> 00:33:56,520
Speaker 1: it was strange. So you left because why because it

692
00:33:56,600 --> 00:33:59,040
Speaker 1: then it had changed. Merris was because I just didn't

693
00:33:59,040 --> 00:34:03,040
Speaker 1: see them shifting their attitudes. And you know, at some point,

694
00:34:03,560 --> 00:34:07,320
Speaker 1: even under Oath, I just had to interview too. I

695
00:34:07,360 --> 00:34:10,080
Speaker 1: liked him. I think he's great. I told him I

696
00:34:10,120 --> 00:34:12,440
Speaker 1: thought the new name of the company should be rise

697
00:34:12,600 --> 00:34:15,120
Speaker 1: Are I z E. Because it's sort of like Verizon

698
00:34:15,239 --> 00:34:19,799
Speaker 1: and it's aspirational and positive. But you know, I think

699
00:34:19,840 --> 00:34:21,440
Speaker 1: they've paid a lot of money to come up with

700
00:34:21,520 --> 00:34:24,560
Speaker 1: Oath whatever. But anyway, so I think that, you know,

701
00:34:24,680 --> 00:34:28,480
Speaker 1: I think these companies are are Maybe they'll wake up

702
00:34:28,520 --> 00:34:31,719
Speaker 1: and smell the coffee, but I think they're just very

703
00:34:31,840 --> 00:34:36,839
Speaker 1: lumbering and slow and so at some point ironically right,

704
00:34:36,920 --> 00:34:39,400
Speaker 1: but at some point you want to do quality work

705
00:34:39,880 --> 00:34:42,879
Speaker 1: and make sure that someone values what you do and

706
00:34:42,960 --> 00:34:45,640
Speaker 1: make sure that they hopefully want to get it out

707
00:34:45,640 --> 00:34:48,439
Speaker 1: into the world, which is increasingly fragmented by the way.

708
00:34:48,640 --> 00:34:53,400
Speaker 1: Two questions of Netflix just paid Ryan Murphy a millionaire,

709
00:34:53,840 --> 00:34:57,000
Speaker 1: you know, and then Shanna Rhymes as a similar Obviously

710
00:34:57,040 --> 00:35:01,319
Speaker 1: Apple is just invested in a Reese Withers. When things expensive, Um,

711
00:35:01,560 --> 00:35:04,600
Speaker 1: you know, you some morning television, right exactly, It's all

712
00:35:04,640 --> 00:35:08,480
Speaker 1: about you. It's not about me, I don't think, but

713
00:35:08,400 --> 00:35:10,239
Speaker 1: but you could consult for sure. You seem to know

714
00:35:10,280 --> 00:35:12,960
Speaker 1: what a thing or two about that, um when you

715
00:35:13,520 --> 00:35:15,640
Speaker 1: when you look at all that though they are, they

716
00:35:15,680 --> 00:35:18,440
Speaker 1: are moving rather heavily, they are. You know, I think

717
00:35:18,640 --> 00:35:22,400
Speaker 1: right now, I think that they are not super jazzed

718
00:35:22,400 --> 00:35:26,799
Speaker 1: about moving into a more news space. But maybe ultimately

719
00:35:26,960 --> 00:35:29,120
Speaker 1: they will be. But right now, I think they're really

720
00:35:29,120 --> 00:35:33,719
Speaker 1: focused on scripted content and you know, super kind of impactful,

721
00:35:34,360 --> 00:35:37,520
Speaker 1: buzzy stuff. And you know, I think in a news

722
00:35:37,600 --> 00:35:40,799
Speaker 1: landscape where there is so much content everywhere, I don't

723
00:35:40,800 --> 00:35:42,560
Speaker 1: know about you care, but I can. I mean, I

724
00:35:42,680 --> 00:35:44,920
Speaker 1: read so many articles on my phone and I'm like,

725
00:35:45,080 --> 00:35:47,040
Speaker 1: where did I read that? What was that? How did

726
00:35:47,080 --> 00:35:51,160
Speaker 1: I know that? And it's disconnected. It feels very confusing.

727
00:35:51,280 --> 00:35:54,160
Speaker 1: But but you're right, I think I think the landscape

728
00:35:54,239 --> 00:35:58,880
Speaker 1: is continually changing and iterating, as they say, and uh,

729
00:35:59,040 --> 00:36:01,279
Speaker 1: you know, it will be interesting to see. But the

730
00:36:01,520 --> 00:36:04,080
Speaker 1: most important thing is, you know, how are we going

731
00:36:04,120 --> 00:36:07,359
Speaker 1: to keep people informed and engaged in the world around them.

732
00:36:07,400 --> 00:36:10,680
Speaker 1: I do think, you know from what I said earlier,

733
00:36:10,719 --> 00:36:13,600
Speaker 1: that a lot of young people gen z whatever you

734
00:36:13,640 --> 00:36:18,239
Speaker 1: call it, millennials really do are engaged. But we have

735
00:36:18,320 --> 00:36:21,640
Speaker 1: to continue to think about how we'll continue to keep

736
00:36:21,680 --> 00:36:25,719
Speaker 1: people engaged, you know, because it's so democracy. I know,

737
00:36:25,800 --> 00:36:27,560
Speaker 1: what would you do right now if you were young?

738
00:36:27,600 --> 00:36:29,440
Speaker 1: I mean you already if I want to be let

739
00:36:29,480 --> 00:36:32,880
Speaker 1: me say everybody. Katie kirk is the hardest woman working woman.

740
00:36:32,920 --> 00:36:35,000
Speaker 1: And we were having dinner and literally she was getting

741
00:36:35,200 --> 00:36:36,880
Speaker 1: on You were getting on a knife, like where were

742
00:36:36,920 --> 00:36:39,240
Speaker 1: you going? You were going to, like Alabama or somewhere.

743
00:36:39,280 --> 00:36:42,120
Speaker 1: We're like, Katie Kurrt can rest. I know, I just

744
00:36:42,320 --> 00:36:44,919
Speaker 1: love to work. I don't know why. My husband thinks

745
00:36:44,920 --> 00:36:49,719
Speaker 1: I'm insane and I think you're insane. I know, I

746
00:36:49,800 --> 00:36:52,040
Speaker 1: have to figure out I do feel like I have

747
00:36:52,200 --> 00:36:54,920
Speaker 1: to find a better balance. But what would I do

748
00:36:54,960 --> 00:36:57,839
Speaker 1: if I were starting out in the I just felt

749
00:36:57,920 --> 00:36:59,920
Speaker 1: like like at one point, I'm like, you did that,

750
00:37:00,040 --> 00:37:03,000
Speaker 1: Sarah Paliner if you can retire now, I know, but don't.

751
00:37:03,080 --> 00:37:05,320
Speaker 1: I mean, I'd like to be engaged in the world.

752
00:37:05,360 --> 00:37:08,239
Speaker 1: I like to be talking to interesting people. And what

753
00:37:08,239 --> 00:37:09,640
Speaker 1: would you do if you're young? What would you what?

754
00:37:09,680 --> 00:37:13,400
Speaker 1: Are you interested now? And interested in now? Yeah? What

755
00:37:13,440 --> 00:37:15,760
Speaker 1: do you mean? Because look, broadcast is sort of shifting

756
00:37:15,880 --> 00:37:19,080
Speaker 1: so dramatically, and you know, you tried the Yahoo thing,

757
00:37:19,080 --> 00:37:21,399
Speaker 1: although it doesn't mean that that didn't work. But are

758
00:37:21,440 --> 00:37:23,600
Speaker 1: you where would you where? Where are you looked at?

759
00:37:23,680 --> 00:37:25,680
Speaker 1: Or where would you go? I mean, I think that

760
00:37:25,920 --> 00:37:29,680
Speaker 1: I'd like to try something more entrepreneurial because I think

761
00:37:29,760 --> 00:37:32,480
Speaker 1: there's never been a better time. I mean, if you

762
00:37:32,560 --> 00:37:36,359
Speaker 1: talk about disintermediation, I mean I've I do a lot

763
00:37:36,400 --> 00:37:40,120
Speaker 1: on Instagram because I feel a real connection with people

764
00:37:40,120 --> 00:37:43,360
Speaker 1: who follow me on Instagram. It feels a little less

765
00:37:43,440 --> 00:37:48,640
Speaker 1: kind of uh, sort of cosmic than Twitter. I feel

766
00:37:48,760 --> 00:37:52,640
Speaker 1: it's more community based, and I think that that's a

767
00:37:52,680 --> 00:37:56,680
Speaker 1: really interesting outlet to experiment in and try different things.

768
00:37:56,920 --> 00:38:00,360
Speaker 1: And you know, I'd like to do something that really,

769
00:38:00,680 --> 00:38:02,719
Speaker 1: you know, at this point in my career, shines the

770
00:38:02,840 --> 00:38:06,719
Speaker 1: light on other young up and coming especially female journalists,

771
00:38:06,719 --> 00:38:10,600
Speaker 1: diverse journalists, people who represent all different points of view.

772
00:38:10,640 --> 00:38:14,680
Speaker 1: Because the one thing we've seen Kara so clearly is

773
00:38:15,000 --> 00:38:18,880
Speaker 1: certainly in broadcasts, that it is still a male bastion.

774
00:38:19,040 --> 00:38:23,480
Speaker 1: It's still all the decision makers are are primarily white men,

775
00:38:24,239 --> 00:38:26,319
Speaker 1: and we have to start changing that. And how do

776
00:38:26,360 --> 00:38:29,279
Speaker 1: you change it while you give women an opportunity and

777
00:38:29,360 --> 00:38:33,120
Speaker 1: experience and a chance to shine. How did you take

778
00:38:33,200 --> 00:38:35,480
Speaker 1: I mean, obviously media has been the focus of a

779
00:38:35,520 --> 00:38:37,360
Speaker 1: lot of me too stuff, more than any I was

780
00:38:37,400 --> 00:38:39,040
Speaker 1: talking about so the other day. There's there's a lot

781
00:38:39,040 --> 00:38:40,760
Speaker 1: of it in tech, but it really has been focused

782
00:38:40,760 --> 00:38:43,359
Speaker 1: on media and including places you've worked. I mean, how

783
00:38:43,360 --> 00:38:46,480
Speaker 1: do you look at when you when you see that happening?

784
00:38:46,760 --> 00:38:48,920
Speaker 1: Did you just become a nerd to it like this

785
00:38:49,000 --> 00:38:50,719
Speaker 1: is the way it is? I mean, I have to

786
00:38:50,760 --> 00:38:53,799
Speaker 1: say personally, I did not deal with a lot of that.

787
00:38:54,000 --> 00:38:57,320
Speaker 1: I don't know whether, uh, you know, I'm just imminently

788
00:38:57,480 --> 00:39:02,680
Speaker 1: in harassable, but you know I'm harassable, not harassable, But

789
00:39:03,160 --> 00:39:06,000
Speaker 1: you know, I was very lucky. I you know, every

790
00:39:06,040 --> 00:39:09,279
Speaker 1: now and then, um, you know, someone would make a

791
00:39:09,320 --> 00:39:11,840
Speaker 1: comment or it would be a little fratty, but I

792
00:39:11,840 --> 00:39:14,000
Speaker 1: would just I think, I'm kind of like you. I

793
00:39:14,000 --> 00:39:17,080
Speaker 1: would roll my eyes or give it right back. And

794
00:39:17,200 --> 00:39:22,320
Speaker 1: so I think culturally it's just been such a shift

795
00:39:22,600 --> 00:39:26,760
Speaker 1: in what is acceptable and what is unacceptable. But having

796
00:39:26,800 --> 00:39:30,000
Speaker 1: said that, you know, I've been the beneficiary of having

797
00:39:30,040 --> 00:39:34,000
Speaker 1: a pretty powerful job, and I would try to set

798
00:39:34,280 --> 00:39:37,759
Speaker 1: the right tone in a work environment. Having said that,

799
00:39:37,840 --> 00:39:40,960
Speaker 1: I think I'm sure it was you know, jocularity bordered

800
00:39:41,000 --> 00:39:44,920
Speaker 1: on too much kind of uh, you know, boy's humor.

801
00:39:45,120 --> 00:39:47,000
Speaker 1: But yeah, I think I think about what I did

802
00:39:47,000 --> 00:39:49,080
Speaker 1: I allow that I shouldn't have. Yeah, well, you know,

803
00:39:50,000 --> 00:39:52,719
Speaker 1: and I don't I don't really feel that way. I

804
00:39:52,760 --> 00:39:55,200
Speaker 1: think that some people have said, well, how did you

805
00:39:55,280 --> 00:39:57,960
Speaker 1: not know what was going on? I think there was

806
00:39:58,000 --> 00:40:03,279
Speaker 1: also this feeling of privacy, you know, and people do

807
00:40:03,520 --> 00:40:08,320
Speaker 1: things and you're not monitoring behavior, uh, in people's spare time,

808
00:40:08,480 --> 00:40:11,760
Speaker 1: you don't know about it. And so I think that,

809
00:40:12,480 --> 00:40:16,000
Speaker 1: you know, I feel I have a totally clear and

810
00:40:16,239 --> 00:40:22,239
Speaker 1: clean conscience about the way I comported myself, and you know,

811
00:40:22,320 --> 00:40:26,279
Speaker 1: any responsibility that I bear for people's bad behavior. Yeah,

812
00:40:26,480 --> 00:40:28,880
Speaker 1: that's hard because I think what's what happens is one

813
00:40:28,920 --> 00:40:30,720
Speaker 1: of the things I've noticed, at least in Silicon Valley

814
00:40:30,920 --> 00:40:33,200
Speaker 1: and talking to people is that people let things go.

815
00:40:33,520 --> 00:40:36,759
Speaker 1: Like you know, I think about like how how you

816
00:40:36,880 --> 00:40:39,359
Speaker 1: just you become again a nerd to it, like you

817
00:40:39,360 --> 00:40:41,360
Speaker 1: you get you get this stuff all the time and

818
00:40:41,360 --> 00:40:44,000
Speaker 1: then you live in the environment and stime. It is

819
00:40:44,040 --> 00:40:48,120
Speaker 1: so subtle, Kara. You know something aggressive things that hasn't

820
00:40:48,120 --> 00:40:53,280
Speaker 1: gotten a lot of attention is sort of very subtle sexism.

821
00:40:53,320 --> 00:41:02,200
Speaker 1: That's that's marginalizing and dismissive and undervalues people's accomplishments and

822
00:41:02,280 --> 00:41:07,439
Speaker 1: intelligence and and um ability to contribute. And it's it's

823
00:41:07,440 --> 00:41:11,200
Speaker 1: this very subtle thing that you can't go to necessarily

824
00:41:11,400 --> 00:41:15,680
Speaker 1: hr about it, but you feel it intensely. And I

825
00:41:15,760 --> 00:41:18,719
Speaker 1: hadn't experienced that. Yeah, it's really interesting. When I just

826
00:41:18,760 --> 00:41:22,480
Speaker 1: finished the Tina Brown book about her tenure, which I

827
00:41:22,480 --> 00:41:25,719
Speaker 1: thought was fantastic and one of the things you got rated.

828
00:41:25,719 --> 00:41:28,160
Speaker 1: It's hysterical. It's hysterical and beautifully written in very funny

829
00:41:28,200 --> 00:41:31,520
Speaker 1: and very rob but brilliant, brilliant. But I was just

830
00:41:31,560 --> 00:41:34,400
Speaker 1: thinking people have a vision of her that's really not

831
00:41:34,560 --> 00:41:37,560
Speaker 1: very nice, like tough, you know, ball busting lady editor

832
00:41:37,640 --> 00:41:40,839
Speaker 1: Cain and like, I'm so over that. I am over

833
00:41:41,040 --> 00:41:44,839
Speaker 1: and I was. I was like she she changed magazines

834
00:41:44,960 --> 00:41:47,200
Speaker 1: and to not one but two, and she had some

835
00:41:47,360 --> 00:41:49,759
Speaker 1: like Rocky, Our Times, a Daily Beast and Talk and

836
00:41:49,760 --> 00:41:53,360
Speaker 1: stuff like that. But her accomplishments were massive when you

837
00:41:53,400 --> 00:41:56,680
Speaker 1: start to realize it. The impact on magazines definitely. The

838
00:41:56,800 --> 00:41:59,640
Speaker 1: kind of image she has is so like everyone any

839
00:41:59,760 --> 00:42:02,240
Speaker 1: man only did that. I just was made me furious

840
00:42:02,239 --> 00:42:04,720
Speaker 1: when I was reading. I was thinking, this person still

841
00:42:04,800 --> 00:42:08,480
Speaker 1: has sort of a reputation among some which is like,

842
00:42:08,520 --> 00:42:10,640
Speaker 1: oh what a what a tough bit. She is that

843
00:42:10,719 --> 00:42:13,160
Speaker 1: kind of thing, and I'm like, whoa wait, wait a minute,

844
00:42:13,160 --> 00:42:15,560
Speaker 1: she did a lot and why is she why is

845
00:42:15,600 --> 00:42:17,759
Speaker 1: that her image? Well, you know, I think that's why

846
00:42:17,760 --> 00:42:20,239
Speaker 1: it's so important to have women in leadership positions. When

847
00:42:20,280 --> 00:42:22,960
Speaker 1: I anchored the CBS Evening News, like I would call

848
00:42:23,040 --> 00:42:25,480
Speaker 1: writers out and say, why are you describing Hillary Clinton

849
00:42:25,520 --> 00:42:28,040
Speaker 1: that way? Would you describe a male candidate that way?

850
00:42:28,160 --> 00:42:30,120
Speaker 1: Or just why can't we do a story on X,

851
00:42:30,280 --> 00:42:33,520
Speaker 1: Y and Z things that that my male counterparts would

852
00:42:33,560 --> 00:42:36,760
Speaker 1: never in a million years imagine. And but Why should

853
00:42:36,760 --> 00:42:39,120
Speaker 1: it be you that does it? Why does it have

854
00:42:39,200 --> 00:42:41,439
Speaker 1: to be someone I was just I did the same

855
00:42:41,440 --> 00:42:43,840
Speaker 1: thing when I interviewed Hillary Clinton last year at code

856
00:42:43,960 --> 00:42:45,920
Speaker 1: um So. One of the anchors I was telling you

857
00:42:46,000 --> 00:42:48,160
Speaker 1: was like, she was strident, and I'm like, what did

858
00:42:48,160 --> 00:42:49,840
Speaker 1: you just use? And this was on the air, and

859
00:42:49,840 --> 00:42:51,839
Speaker 1: they're like, I said strident as a word you only

860
00:42:51,920 --> 00:42:54,000
Speaker 1: used for hysterically true? And how that I was like,

861
00:42:54,040 --> 00:42:57,040
Speaker 1: she was top of that being struck? You know, taken

862
00:42:57,080 --> 00:42:59,759
Speaker 1: out of our vocabulary? Do you ever, hey? And how

863
00:42:59,760 --> 00:43:03,319
Speaker 1: about perky? You know, like I was called and I

864
00:43:03,320 --> 00:43:06,359
Speaker 1: am very outgoing and I'm friendly and I'm very like,

865
00:43:06,880 --> 00:43:10,880
Speaker 1: I'm very upbeat, but you know, our men ever called perky? No,

866
00:43:11,080 --> 00:43:15,840
Speaker 1: I feel like it's a demeaning, marginalizing description of somebody.

867
00:43:15,920 --> 00:43:18,120
Speaker 1: And I am like, when you shifted, like I think

868
00:43:18,120 --> 00:43:20,200
Speaker 1: you did shift though, and you'r you were not You

869
00:43:20,239 --> 00:43:23,120
Speaker 1: were a much more complex person than you know what

870
00:43:23,160 --> 00:43:25,600
Speaker 1: I mean. People people didn't like it. Well, people don't

871
00:43:25,680 --> 00:43:28,759
Speaker 1: like they don't want to acknowledge people are multidimensional. They

872
00:43:28,800 --> 00:43:31,239
Speaker 1: want to, you know, put them in a box and

873
00:43:31,320 --> 00:43:33,680
Speaker 1: say their X, Y and Z. And you know, I

874
00:43:33,719 --> 00:43:37,440
Speaker 1: think that nuance has been lost in our current discourse

875
00:43:37,480 --> 00:43:40,600
Speaker 1: and hasn't really existed for a very long time. And

876
00:43:40,680 --> 00:43:44,160
Speaker 1: it's just very easy to stereotype people or else you

877
00:43:44,680 --> 00:43:47,080
Speaker 1: I think about you. I remember when we were Fanny

878
00:43:47,120 --> 00:43:49,200
Speaker 1: Fair and you yelled. I was talking about your salary

879
00:43:49,200 --> 00:43:50,760
Speaker 1: and I was thrilled that you got the big salary.

880
00:43:50,800 --> 00:43:52,759
Speaker 1: You did it. Yeah. Who Someone was sort of saying, oh,

881
00:43:52,760 --> 00:43:54,200
Speaker 1: that's a lot of money. I'm like, who cares? You

882
00:43:54,239 --> 00:43:56,360
Speaker 1: got the money like that? And you yelled from the

883
00:43:56,400 --> 00:43:59,840
Speaker 1: onon that's right, switcher or something like that, but in

884
00:44:00,120 --> 00:44:02,799
Speaker 1: sort of growl, and it was fantastic, and everyone's like,

885
00:44:02,920 --> 00:44:04,840
Speaker 1: is that Katie Karrek, And I was like, yes, that

886
00:44:04,960 --> 00:44:08,239
Speaker 1: is Katie k I think women, especially, I mean, think

887
00:44:08,239 --> 00:44:11,000
Speaker 1: about it morning television. You have to be nice and

888
00:44:11,040 --> 00:44:14,560
Speaker 1: you know, I think luckily I am. I think of

889
00:44:14,640 --> 00:44:17,560
Speaker 1: myself as a nice person. But you have to fulfill

890
00:44:17,640 --> 00:44:21,560
Speaker 1: these expectations and roles, and you know, it's very hard

891
00:44:21,600 --> 00:44:24,080
Speaker 1: to navigate as a woman this kind of you know,

892
00:44:24,239 --> 00:44:27,560
Speaker 1: being tough but not too tough, you know, being challenging

893
00:44:27,640 --> 00:44:31,359
Speaker 1: but not too challenging, not having an opinion, being you know,

894
00:44:31,520 --> 00:44:35,080
Speaker 1: being palatable and pleasant in the morning. You know, you

895
00:44:35,120 --> 00:44:38,600
Speaker 1: have to be like the breakfast smoothie, and so it's hard,

896
00:44:38,800 --> 00:44:41,759
Speaker 1: It's really hard. I like the breakfast smooth I think

897
00:44:41,760 --> 00:44:45,719
Speaker 1: I stole that first. Who described that as that? Once? Yeah?

898
00:44:45,719 --> 00:44:49,200
Speaker 1: What not anymore? What smoothie would you be? Like? Oh,

899
00:44:49,239 --> 00:44:51,839
Speaker 1: my goodness, you'd be an interesting smoothie. But it's true.

900
00:44:51,840 --> 00:44:54,040
Speaker 1: But it's it's I think that that's what's interesting is

901
00:44:54,040 --> 00:44:56,480
Speaker 1: that if you don't fulfill their expectations of you. I

902
00:44:56,480 --> 00:44:58,560
Speaker 1: think there's so much you know, one of the hours

903
00:44:58,600 --> 00:45:00,880
Speaker 1: I'm doing for Natchie and again, I'm I've been thinking

904
00:45:00,880 --> 00:45:02,719
Speaker 1: about all these and the only reason I bring it

905
00:45:02,800 --> 00:45:05,759
Speaker 1: up is because you're in this hour and you're fantastic.

906
00:45:05,840 --> 00:45:09,920
Speaker 1: It's about gender inequality in Hollywood and Silicon Valley, and

907
00:45:10,200 --> 00:45:13,160
Speaker 1: I talked to a woman at Harvard who studies implicit bias,

908
00:45:13,400 --> 00:45:15,640
Speaker 1: and we you and I talked about this, Kara. You know,

909
00:45:15,640 --> 00:45:18,799
Speaker 1: because I don't think that consider themselves a meritocracy, are

910
00:45:18,840 --> 00:45:22,560
Speaker 1: the least meritocratic of anyone, because they don't acknowledge their

911
00:45:22,600 --> 00:45:26,319
Speaker 1: in eight biases. And I think we are so programmed

912
00:45:26,360 --> 00:45:29,160
Speaker 1: to see men and women in a certain way that

913
00:45:29,320 --> 00:45:32,440
Speaker 1: is actually, you know, reinforced by all the messaging we

914
00:45:32,560 --> 00:45:37,520
Speaker 1: get and commercials and the objectification of women, hyper sexualization

915
00:45:37,840 --> 00:45:39,480
Speaker 1: of women. I had to think, you know, when this

916
00:45:39,520 --> 00:45:42,920
Speaker 1: whole meat too movement was exploding, the Victoria's Secrets fashion

917
00:45:42,960 --> 00:45:45,480
Speaker 1: show was on CBS, and I was like, no wonder,

918
00:45:45,520 --> 00:45:49,719
Speaker 1: women are confused, No wonder, everybody is confused, right, right?

919
00:45:49,800 --> 00:45:52,640
Speaker 1: But then you have the backlash and you talked about you.

920
00:45:52,640 --> 00:45:54,520
Speaker 1: You you interviewed James to more for that, right or

921
00:45:54,640 --> 00:45:56,120
Speaker 1: right others? You went to one of his party. You

922
00:45:56,200 --> 00:45:57,680
Speaker 1: told me, I'm going to his party. I went to

923
00:45:57,960 --> 00:46:03,200
Speaker 1: a cookout conserving sausages where they of course they were.

924
00:46:03,239 --> 00:46:06,960
Speaker 1: There's sausages everywhere where I work, Katie, everywhere I go,

925
00:46:07,160 --> 00:46:11,439
Speaker 1: sausage Sausage Fest. That's the name. That was the name

926
00:46:11,440 --> 00:46:15,120
Speaker 1: of my memoirs, Sausage Fest. Um. But it's true, I

927
00:46:15,160 --> 00:46:18,760
Speaker 1: always it's it's so true. Um. But what was interesting

928
00:46:18,800 --> 00:46:21,160
Speaker 1: about when you were talking about that was that I

929
00:46:21,280 --> 00:46:23,040
Speaker 1: glad that you were open to hearing them because one

930
00:46:23,040 --> 00:46:25,120
Speaker 1: of the things in Zilia Valley right now, you know,

931
00:46:25,160 --> 00:46:27,560
Speaker 1: Peter Teel has to move because he can't be concerned.

932
00:46:27,719 --> 00:46:32,800
Speaker 1: Which come on, come on, come on, yeh, let's discuss that, alright.

933
00:46:32,840 --> 00:46:34,640
Speaker 1: We only have a few minutes. Oh come on, I

934
00:46:34,719 --> 00:46:37,719
Speaker 1: just please. I just don't even know what to say.

935
00:46:37,880 --> 00:46:40,960
Speaker 1: This is a person who is a victimizer that acts

936
00:46:40,960 --> 00:46:43,080
Speaker 1: like a victim typical, you know what I mean. Like

937
00:46:43,160 --> 00:46:45,760
Speaker 1: this guy's soothed company out of business, he's got billions

938
00:46:45,760 --> 00:46:48,239
Speaker 1: of dollars, he's all kinds of things at his disposal.

939
00:46:48,600 --> 00:46:50,319
Speaker 1: And if you want me to imagine that he and

940
00:46:50,360 --> 00:46:52,240
Speaker 1: he gets to speak up, he gets to give speeches,

941
00:46:52,280 --> 00:46:53,600
Speaker 1: he gets to you know what I mean, and he's

942
00:46:53,640 --> 00:46:55,960
Speaker 1: still a victim. Is Well, let me ask you something, Kara,

943
00:46:56,040 --> 00:46:59,640
Speaker 1: in terms of like a policy discussion. Do you believe

944
00:47:00,480 --> 00:47:06,719
Speaker 1: that in certain circles that conservative point of view is

945
00:47:06,719 --> 00:47:09,640
Speaker 1: is actually heard at all and there can be an

946
00:47:09,680 --> 00:47:14,840
Speaker 1: open conversation with people of differing opinions. I think some

947
00:47:14,960 --> 00:47:17,440
Speaker 1: places are conservatives, in some places aren't. I can't operate

948
00:47:17,440 --> 00:47:20,040
Speaker 1: in certain parts of the country either, like in certain companies.

949
00:47:20,080 --> 00:47:22,880
Speaker 1: It's just companies have their point of view. And I

950
00:47:22,880 --> 00:47:24,680
Speaker 1: think the reason a lot of these companies pretend they

951
00:47:24,719 --> 00:47:26,760
Speaker 1: don't is because when you have to say your values,

952
00:47:26,840 --> 00:47:29,600
Speaker 1: you have to argue about them. Right, values is what

953
00:47:29,640 --> 00:47:32,120
Speaker 1: you argue about. But when you have I had this

954
00:47:32,200 --> 00:47:34,160
Speaker 1: really interesting time YouTube. I went there to talk to

955
00:47:34,200 --> 00:47:35,840
Speaker 1: them and they were talking about how it used to

956
00:47:35,840 --> 00:47:38,640
Speaker 1: be all squirrel videos and nice things, and now they

957
00:47:38,680 --> 00:47:41,040
Speaker 1: have a college ethical debate every day, you know, whether

958
00:47:41,080 --> 00:47:45,040
Speaker 1: it's Logan Paul or whatever, um and And on some level,

959
00:47:45,080 --> 00:47:48,440
Speaker 1: I'm like, well that's what. What's what it's about having values?

960
00:47:48,640 --> 00:47:50,879
Speaker 1: You have to state your values, and I don't think

961
00:47:50,920 --> 00:47:53,960
Speaker 1: that they can. I'm having an interest. I'm gonna have

962
00:47:53,960 --> 00:47:55,720
Speaker 1: a pike as a guy who's doing all these polls

963
00:47:55,719 --> 00:47:59,480
Speaker 1: on conservatives. They don't get to talk. It isn't it

964
00:47:59,640 --> 00:48:02,520
Speaker 1: is a liberal environment. It is. It just becase these

965
00:48:02,560 --> 00:48:06,040
Speaker 1: companies are more tolerant. Tech has been more tolerant, and

966
00:48:06,120 --> 00:48:09,160
Speaker 1: these are their values, And so I don't know if

967
00:48:09,239 --> 00:48:11,959
Speaker 1: you can't talk, because I don't think that's I'm sorry.

968
00:48:12,040 --> 00:48:14,240
Speaker 1: These people have so many opportunities to talk. At Google,

969
00:48:14,239 --> 00:48:18,600
Speaker 1: there's like nine places to talk and all kinds of opportunities.

970
00:48:18,920 --> 00:48:21,799
Speaker 1: But I think once you say something that's not in

971
00:48:21,840 --> 00:48:23,960
Speaker 1: their value system, maybe it's not a place you need

972
00:48:24,000 --> 00:48:26,399
Speaker 1: to work, or maybe you should work somewhere else, or

973
00:48:26,800 --> 00:48:29,359
Speaker 1: you know, I think that's been for I mean, as

974
00:48:29,360 --> 00:48:32,080
Speaker 1: a gay person, you couldn't be gay like you couldn't

975
00:48:32,120 --> 00:48:35,359
Speaker 1: and that of course that ended up being illegal in

976
00:48:35,360 --> 00:48:38,319
Speaker 1: some places. It's still not that illegal in many places. UM.

977
00:48:38,400 --> 00:48:39,920
Speaker 1: But I just think you have to think about what

978
00:48:40,080 --> 00:48:43,319
Speaker 1: values you have and if you have those values, not

979
00:48:43,440 --> 00:48:46,680
Speaker 1: being cowed into saying you have to have everyone's point

980
00:48:46,680 --> 00:48:48,520
Speaker 1: of view. This, this is our value, this is what

981
00:48:48,560 --> 00:48:51,320
Speaker 1: we you know, every Internet company has a little statement

982
00:48:51,320 --> 00:48:53,720
Speaker 1: of who they are, UM, and I think they're scared

983
00:48:53,719 --> 00:48:57,240
Speaker 1: about that. They're scared about stating them. Essentially, that's interesting.

984
00:48:57,280 --> 00:49:00,320
Speaker 1: But I also think that there are some issue Jews

985
00:49:00,520 --> 00:49:06,799
Speaker 1: that respectable, intelligent, well meaning people can can disagree, and

986
00:49:06,880 --> 00:49:10,880
Speaker 1: I do you know, I wonder about our inability to

987
00:49:11,160 --> 00:49:16,839
Speaker 1: have a respectful conversation about maybe, you know, certain things

988
00:49:16,840 --> 00:49:20,319
Speaker 1: are non negotiable. I understand that, but certain things that

989
00:49:20,360 --> 00:49:22,680
Speaker 1: you can have a different point of view and you

990
00:49:22,719 --> 00:49:25,359
Speaker 1: can learn from somebody and they can say, you know,

991
00:49:26,000 --> 00:49:29,200
Speaker 1: this is how I feel about this, And I feel

992
00:49:29,200 --> 00:49:32,839
Speaker 1: like those conversations aren't happening, and it really bumps me out,

993
00:49:32,920 --> 00:49:37,040
Speaker 1: and I think it's really yes, it's so politicized, but

994
00:49:37,120 --> 00:49:38,919
Speaker 1: maybe I was just thinking of the days some other

995
00:49:39,200 --> 00:49:41,279
Speaker 1: point of view came out and I was like, I'm

996
00:49:41,320 --> 00:49:43,960
Speaker 1: so glad to hear this point of view, like now

997
00:49:44,000 --> 00:49:46,399
Speaker 1: I know like people are like I can't believe people

998
00:49:46,400 --> 00:49:48,440
Speaker 1: are like this. Thing, They've always been like this. They

999
00:49:48,520 --> 00:49:51,600
Speaker 1: just have an outlet, and especially social media amplifies and

1000
00:49:51,640 --> 00:49:54,560
Speaker 1: weaponizes a lot of right, you know. And I when

1001
00:49:54,600 --> 00:49:56,920
Speaker 1: I think about it, I'm like, well, okay, now I

1002
00:49:57,000 --> 00:49:59,600
Speaker 1: soon see it. It's out in broad daylight. I understand

1003
00:50:00,040 --> 00:50:02,560
Speaker 1: the ignorance or whatever I think of whatever the point

1004
00:50:02,560 --> 00:50:05,560
Speaker 1: of view is most most many of my finding durant.

1005
00:50:05,680 --> 00:50:08,160
Speaker 1: But but you know, you know, you can't really persuade

1006
00:50:08,200 --> 00:50:11,440
Speaker 1: somebody if you're not talking to them. There's a really

1007
00:50:11,480 --> 00:50:14,080
Speaker 1: good book that's written by the incoming president of the

1008
00:50:14,160 --> 00:50:18,560
Speaker 1: University of Virginia, Jim Ryan. It's called Wait What And

1009
00:50:18,560 --> 00:50:21,759
Speaker 1: And he gave a great graduation speech at at the

1010
00:50:21,760 --> 00:50:25,839
Speaker 1: Harvard School of Education, and it's basically, we've lost our

1011
00:50:25,840 --> 00:50:31,319
Speaker 1: ability to be even a tiny bit circumspect, you know.

1012
00:50:31,440 --> 00:50:36,560
Speaker 1: We we we have these instantaneous reactions and sometimes just

1013
00:50:36,640 --> 00:50:40,560
Speaker 1: to take a moment and say, wait what. And anyway,

1014
00:50:40,600 --> 00:50:44,960
Speaker 1: it's very interesting to the way we hear things, the

1015
00:50:45,000 --> 00:50:47,680
Speaker 1: way we react to things, the way that we are

1016
00:50:47,719 --> 00:50:51,280
Speaker 1: in our own echo chambers, the way that we were

1017
00:50:51,360 --> 00:50:54,400
Speaker 1: preaching to the choir, especially on social media and Twitter.

1018
00:50:54,520 --> 00:50:57,160
Speaker 1: That's something I just wish once in a while we

1019
00:50:57,200 --> 00:51:00,480
Speaker 1: could all say wait what and then here each other

1020
00:51:00,600 --> 00:51:03,319
Speaker 1: a little bit, not on everything care of. But I'm

1021
00:51:03,360 --> 00:51:05,080
Speaker 1: being pushed back on in a very big way because

1022
00:51:05,120 --> 00:51:07,360
Speaker 1: I do think we're hearing each other. That's the problem,

1023
00:51:07,480 --> 00:51:09,840
Speaker 1: do you I was I'm just yes, because I'm reading.

1024
00:51:09,880 --> 00:51:12,200
Speaker 1: I'm reading the actual book on Hamilton's, not the musical,

1025
00:51:12,200 --> 00:51:16,399
Speaker 1: which I really much enjoyed. If you read Turn, If

1026
00:51:16,440 --> 00:51:18,920
Speaker 1: you read that book, the stuff that was going on

1027
00:51:19,160 --> 00:51:25,960
Speaker 1: between Hamilton's, Jefferson Madison and Washington, Yeah, exactly who created

1028
00:51:26,000 --> 00:51:28,600
Speaker 1: a problem at the end. But um, it was really

1029
00:51:28,880 --> 00:51:31,680
Speaker 1: quite the same, like it is even worse, like the

1030
00:51:31,800 --> 00:51:35,440
Speaker 1: kind of like an our democracy hung by a thread

1031
00:51:35,760 --> 00:51:38,920
Speaker 1: so many times, the Whiskey rebellion, the x y Z affair,

1032
00:51:39,440 --> 00:51:41,399
Speaker 1: we have no sense of history, is what it is.

1033
00:51:41,719 --> 00:51:43,839
Speaker 1: And if you read that, you're like, oh my god,

1034
00:51:43,960 --> 00:51:46,080
Speaker 1: oh my, like you you realize how and and the

1035
00:51:46,160 --> 00:51:50,200
Speaker 1: invective was so vicious, and through these different newspaper articles

1036
00:51:50,239 --> 00:51:52,319
Speaker 1: they wrote against each other. There was an act as

1037
00:51:52,520 --> 00:51:55,360
Speaker 1: the Sedition Act for people remember it like that you

1038
00:51:55,600 --> 00:51:58,320
Speaker 1: people went to jail for having a Republican point of

1039
00:51:58,400 --> 00:52:01,359
Speaker 1: view if they if they resulted the government, and that

1040
00:52:01,440 --> 00:52:03,359
Speaker 1: was law on the books for a very long time.

1041
00:52:03,840 --> 00:52:07,920
Speaker 1: UM that that if you insulted the government, you were jailed.

1042
00:52:08,000 --> 00:52:10,920
Speaker 1: So people who are not in the of the Adams group,

1043
00:52:11,000 --> 00:52:14,160
Speaker 1: the Federalists, were put in jail for years and their

1044
00:52:14,160 --> 00:52:16,400
Speaker 1: lives were changing. So I think this has been an

1045
00:52:16,440 --> 00:52:19,040
Speaker 1: American problem for years, is the lack of ability to

1046
00:52:19,239 --> 00:52:21,920
Speaker 1: have any memory and at the same time realize that

1047
00:52:21,960 --> 00:52:24,440
Speaker 1: we have always been like you know what I mean?

1048
00:52:24,440 --> 00:52:26,759
Speaker 1: And then social media and what's happened is Trump has

1049
00:52:26,880 --> 00:52:30,319
Speaker 1: just under given voice to all of it, and now

1050
00:52:30,360 --> 00:52:34,000
Speaker 1: we see it instantly, and that's what's discomforting about it. Um,

1051
00:52:34,000 --> 00:52:36,439
Speaker 1: but we don't this is not something. Go read that book.

1052
00:52:36,440 --> 00:52:38,799
Speaker 1: Because then I sort of felt a little better. I

1053
00:52:38,880 --> 00:52:40,640
Speaker 1: was like, oh wow, we've been doing this for centuries,

1054
00:52:40,680 --> 00:52:48,240
Speaker 1: were on the cusp of anarchy at every single second. Um, alright, alright,

1055
00:52:48,520 --> 00:52:50,399
Speaker 1: But because I think it's not I think social media

1056
00:52:50,400 --> 00:52:52,800
Speaker 1: has made it worse and that these companies have a responsibility.

1057
00:52:53,080 --> 00:52:54,920
Speaker 1: And I will end on that because one of the

1058
00:52:54,960 --> 00:52:57,680
Speaker 1: things when you're talking about how do I get liked disliked?

1059
00:52:57,760 --> 00:52:59,680
Speaker 1: I what I think happens. And I think the reason

1060
00:52:59,760 --> 00:53:03,640
Speaker 1: yours successful is because we just I hate to have

1061
00:53:03,800 --> 00:53:05,640
Speaker 1: something in common with Donald Trump, but you say it

1062
00:53:05,680 --> 00:53:07,520
Speaker 1: like it like it is for you, and I think

1063
00:53:07,560 --> 00:53:10,640
Speaker 1: people do appreciate that, whether they disagree with you or

1064
00:53:10,680 --> 00:53:13,399
Speaker 1: don't agree with you, if you have a cogent point

1065
00:53:13,440 --> 00:53:17,799
Speaker 1: of view and you're genuine these mediums, you thrive in them.

1066
00:53:18,000 --> 00:53:22,000
Speaker 1: I guess you know. I I still quite careful. I mean,

1067
00:53:22,040 --> 00:53:25,600
Speaker 1: I think that you are sort of you know, Carabar

1068
00:53:25,800 --> 00:53:30,640
Speaker 1: the door. I'm a little more careful about some of

1069
00:53:30,640 --> 00:53:33,240
Speaker 1: the things I put out there in the world because

1070
00:53:34,040 --> 00:53:36,080
Speaker 1: I don't know, you know, I want to get the

1071
00:53:36,280 --> 00:53:39,680
Speaker 1: I don't care gene from you somehow, because I still

1072
00:53:40,719 --> 00:53:44,520
Speaker 1: I have that want, that desire to be liked, which

1073
00:53:44,600 --> 00:53:47,520
Speaker 1: is um you know, I have it less as I've

1074
00:53:47,520 --> 00:53:50,759
Speaker 1: gotten older, but I still have it. Sevent you're gonna

1075
00:53:50,800 --> 00:53:54,360
Speaker 1: say fuck you? What when is it? When? When? What

1076
00:53:54,440 --> 00:53:55,960
Speaker 1: age are you going to do that at? Well, I'm

1077
00:53:56,040 --> 00:54:00,200
Speaker 1: I'm starting to say, uh, not not f you. But

1078
00:54:00,840 --> 00:54:05,759
Speaker 1: it's so sweet, shut hush, you get get out of

1079
00:54:07,480 --> 00:54:11,120
Speaker 1: fight me. That's about as far as I go. But

1080
00:54:11,160 --> 00:54:13,160
Speaker 1: I don't know, but I do think you get an

1081
00:54:13,280 --> 00:54:16,719
Speaker 1: enormous amount of criticism that I can't imagine having. Like

1082
00:54:16,760 --> 00:54:18,800
Speaker 1: I was thinking there was a story about Lena Dunham

1083
00:54:18,840 --> 00:54:23,600
Speaker 1: in Vanity that really I mean, but this is this

1084
00:54:23,680 --> 00:54:26,799
Speaker 1: is the world we live in, and I think I

1085
00:54:26,840 --> 00:54:30,120
Speaker 1: think you can you can say nothing and stand for nothing,

1086
00:54:30,719 --> 00:54:33,520
Speaker 1: or you can, you know, say when you feel strongly

1087
00:54:33,560 --> 00:54:36,120
Speaker 1: about things. You know, I've been pretty open about saying

1088
00:54:36,440 --> 00:54:39,240
Speaker 1: we have to have a conversation about sensible gun laws.

1089
00:54:39,360 --> 00:54:43,200
Speaker 1: It is insanity. It is insanity. And no, it's not

1090
00:54:43,239 --> 00:54:47,759
Speaker 1: a panacea. No, it will never prevent gun violence, but

1091
00:54:47,880 --> 00:54:49,880
Speaker 1: it can reduce it, and it has to be a

1092
00:54:49,960 --> 00:54:53,120
Speaker 1: multi pronged approach. I agree mental illness is a part

1093
00:54:53,160 --> 00:54:56,360
Speaker 1: of it, but it's a you know, easy access to

1094
00:54:56,440 --> 00:55:01,640
Speaker 1: firearms is really a horrific thing. And I've been pretty

1095
00:55:01,719 --> 00:55:05,239
Speaker 1: vocal about that. So what's your next to you? You've done.

1096
00:55:05,280 --> 00:55:07,120
Speaker 1: You've got me to have a have my coal And

1097
00:55:07,360 --> 00:55:10,440
Speaker 1: I'm actually taking a well known person to get screened

1098
00:55:10,440 --> 00:55:13,920
Speaker 1: in March. I'm not going to I'm going to escort

1099
00:55:14,040 --> 00:55:16,920
Speaker 1: this individual. I am not going to know. I am

1100
00:55:16,920 --> 00:55:20,960
Speaker 1: not going to actually perform the colonoscopy because I'm I'm

1101
00:55:20,960 --> 00:55:23,920
Speaker 1: not qualified, but I'm going to be sort of the escort,

1102
00:55:23,920 --> 00:55:26,360
Speaker 1: which will be fun because you know it's such a

1103
00:55:26,560 --> 00:55:30,399
Speaker 1: preventable disease, and you know, nothing feels better to me.

1104
00:55:30,440 --> 00:55:32,560
Speaker 1: I mean, if you talk about anything I've done in

1105
00:55:32,600 --> 00:55:35,320
Speaker 1: my life, when people come up to me, Karen say,

1106
00:55:35,520 --> 00:55:38,760
Speaker 1: you know what I got screened for calling cancer because

1107
00:55:38,760 --> 00:55:42,120
Speaker 1: of you, and that screening saved my life, I mean

1108
00:55:42,280 --> 00:55:44,880
Speaker 1: that makes me feel like I'm walking on a cloud.

1109
00:55:45,000 --> 00:55:47,919
Speaker 1: So I have the colon of a twenty year old

1110
00:55:47,920 --> 00:55:52,839
Speaker 1: just in case you model clean clean? Have you? When

1111
00:55:52,960 --> 00:55:54,560
Speaker 1: was your last call? Well you're not? How old are

1112
00:55:54,560 --> 00:55:57,719
Speaker 1: you now? I'm old? Okay? So how many you've had

1113
00:55:57,719 --> 00:55:59,799
Speaker 1: one coal in oscopy? One? Yes, I'm gonna have one

1114
00:55:59,840 --> 00:56:02,319
Speaker 1: next you Okay? Five years? Right? Five years and and

1115
00:56:02,320 --> 00:56:06,359
Speaker 1: and really five years every five years? Yeah? Tell everything, Well,

1116
00:56:06,400 --> 00:56:09,880
Speaker 1: depending on what they find. They found a McDonald cheeseburger

1117
00:56:09,920 --> 00:56:12,880
Speaker 1: when I did mine. You didn't take the pills. I

1118
00:56:13,360 --> 00:56:15,120
Speaker 1: know I will take take. But I want to end

1119
00:56:15,120 --> 00:56:17,919
Speaker 1: on one thing. So you where do you imagine you're

1120
00:56:18,480 --> 00:56:20,720
Speaker 1: gonna do next? I mean, obviously you're talking about Instagram,

1121
00:56:20,760 --> 00:56:22,440
Speaker 1: which I think is really interesting, but what and then

1122
00:56:22,480 --> 00:56:23,879
Speaker 1: I will tell you what I'm going to do next.

1123
00:56:23,960 --> 00:56:26,040
Speaker 1: But what if you want to know? I do want

1124
00:56:26,080 --> 00:56:27,920
Speaker 1: to know, of course, I want what what What do

1125
00:56:28,000 --> 00:56:30,719
Speaker 1: you imagine if you could like design a career right now,

1126
00:56:30,760 --> 00:56:33,240
Speaker 1: like you're doing these documentaries, You're doing all kinds of things.

1127
00:56:33,280 --> 00:56:35,200
Speaker 1: What do you what would be the most interesting way?

1128
00:56:35,280 --> 00:56:38,480
Speaker 1: Still storytelling? I mean storytelling. I do love talking to

1129
00:56:38,560 --> 00:56:43,320
Speaker 1: interesting people. I like understanding sort of where they came from,

1130
00:56:43,360 --> 00:56:45,800
Speaker 1: how they got there. I love learning all the time.

1131
00:56:45,840 --> 00:56:49,680
Speaker 1: I'm sort of insatiably curious. So I think I don't

1132
00:56:49,719 --> 00:56:52,640
Speaker 1: know exactly I need some career advice from you, Kara,

1133
00:56:52,760 --> 00:56:58,480
Speaker 1: because as I also like being connected to an audience

1134
00:56:58,560 --> 00:57:02,680
Speaker 1: or two people. I like feeling that that I have,

1135
00:57:03,520 --> 00:57:06,799
Speaker 1: through the access to people, that I can make them

1136
00:57:07,320 --> 00:57:11,200
Speaker 1: more I can make complicated subjects more understandable, or that

1137
00:57:11,400 --> 00:57:14,200
Speaker 1: I can introduce them to something that they're not aware

1138
00:57:14,200 --> 00:57:17,440
Speaker 1: of that will improve their lives or that will just

1139
00:57:17,560 --> 00:57:20,120
Speaker 1: make their day more interesting. I like being sort of

1140
00:57:20,160 --> 00:57:24,520
Speaker 1: that conduit for people. And I think I think I

1141
00:57:24,560 --> 00:57:27,400
Speaker 1: have a pretty good sensibility about things. I think I've

1142
00:57:27,400 --> 00:57:29,640
Speaker 1: got a nose for news, as they say, I think

1143
00:57:29,680 --> 00:57:31,920
Speaker 1: I know I can sense when something is going to

1144
00:57:32,160 --> 00:57:35,960
Speaker 1: kind of be in the ethos, So I don't know exactly,

1145
00:57:36,000 --> 00:57:38,600
Speaker 1: but I just want to keep learning and discovering. And

1146
00:57:38,720 --> 00:57:41,480
Speaker 1: that sounds so cheesy and weird, but you know, I

1147
00:57:41,960 --> 00:57:45,280
Speaker 1: just enjoy being engaged and I like to take people along,

1148
00:57:46,480 --> 00:57:48,160
Speaker 1: and you should do interviews. I'm just telling you not

1149
00:57:48,200 --> 00:57:50,040
Speaker 1: just because this is what I mean. What do you

1150
00:57:50,080 --> 00:57:53,440
Speaker 1: imagine your greatest interview was? I think I'm most impactful,

1151
00:57:53,480 --> 00:57:55,120
Speaker 1: which really isn't a word, but now I think it

1152
00:57:55,200 --> 00:57:56,919
Speaker 1: is a work because it's used so much. I think

1153
00:57:57,080 --> 00:58:01,080
Speaker 1: it's probably was Sarah Palin. That was a hell of

1154
00:58:01,080 --> 00:58:04,240
Speaker 1: an interview. Well, you know, it having nothing to do

1155
00:58:04,320 --> 00:58:08,360
Speaker 1: with me. I just I think I basically went there

1156
00:58:08,400 --> 00:58:14,120
Speaker 1: with with questions that required critical thinking and accumulated knowledge,

1157
00:58:14,800 --> 00:58:18,920
Speaker 1: and I think I was very careful about asking them

1158
00:58:19,000 --> 00:58:22,840
Speaker 1: in a non confrontational way, and as a result, I

1159
00:58:22,880 --> 00:58:25,760
Speaker 1: think it exposed a lot about her and I think

1160
00:58:25,800 --> 00:58:28,880
Speaker 1: that was very helpful for voters. Yeah you were took

1161
00:58:28,880 --> 00:58:31,480
Speaker 1: a photograph, you know what I mean, And that's more

1162
00:58:31,520 --> 00:58:33,960
Speaker 1: like an X ray. Yeah you did, and you couldn't

1163
00:58:33,960 --> 00:58:36,040
Speaker 1: deny it. It was like, Okay, I see, you know

1164
00:58:36,040 --> 00:58:37,400
Speaker 1: what I mean. It was really interest But I you know,

1165
00:58:37,520 --> 00:58:40,160
Speaker 1: I I feel like I've done a lot of pretty

1166
00:58:40,160 --> 00:58:44,960
Speaker 1: good interviews like this one. For example, this one Katie,

1167
00:58:45,080 --> 00:58:49,680
Speaker 1: Oh wait, wait, hold on a second more question, Hold on, okay,

1168
00:58:49,680 --> 00:58:53,280
Speaker 1: this from Gianna, my producer. Alright, what muscles and skills

1169
00:58:53,560 --> 00:58:59,440
Speaker 1: do you think entrepreneurship draws upon compared to journalism? Um, Katie,

1170
00:58:59,480 --> 00:59:03,200
Speaker 1: I think I being irritating is I think the most

1171
00:59:03,240 --> 00:59:06,880
Speaker 1: important muscle skilled anyone has to be in irritating, irritating,

1172
00:59:07,280 --> 00:59:10,200
Speaker 1: being irritable and irritating and not being looking at something

1173
00:59:10,200 --> 00:59:12,400
Speaker 1: and saying why is this done this way? I think

1174
00:59:12,440 --> 00:59:16,480
Speaker 1: every great entrepreneur from Steve Jobs to down to today,

1175
00:59:16,560 --> 00:59:19,000
Speaker 1: lots of great entrepreneurs are every one of them is

1176
00:59:19,040 --> 00:59:22,160
Speaker 1: irritating and irritated. And so they see something and they

1177
00:59:22,200 --> 00:59:24,440
Speaker 1: want to they don't They don't let anything stop them

1178
00:59:24,480 --> 00:59:26,320
Speaker 1: from doing it, and I think it's really hard. I

1179
00:59:26,360 --> 00:59:29,440
Speaker 1: think agreeable people don't invent yeah, you know, And I

1180
00:59:29,480 --> 00:59:36,560
Speaker 1: think that is important word probably and entrepreneurs uh vocabulary

1181
00:59:36,720 --> 00:59:40,360
Speaker 1: is why why? Yeah? Maybe why not? When under say

1182
00:59:40,360 --> 00:59:42,360
Speaker 1: it's it's more like I don't like this, I don't

1183
00:59:42,360 --> 00:59:43,600
Speaker 1: want to do this, I don't want to do this.

1184
00:59:43,600 --> 00:59:46,000
Speaker 1: And I think our greatest you know, that will be

1185
00:59:46,080 --> 00:59:49,720
Speaker 1: from very difficult people Anyway, Katie, thank you so much.

1186
00:59:50,000 --> 00:59:52,640
Speaker 1: Fun when you come to New York so we can

1187
00:59:53,560 --> 00:59:55,280
Speaker 1: thank you so much. By the way, I wanted to

1188
00:59:55,280 --> 00:59:58,040
Speaker 1: ask you you're thinking about running for mayor of San Francisca.

1189
00:59:58,480 --> 01:00:00,040
Speaker 1: Get a million questions, kat you have to do and

1190
01:00:00,040 --> 01:00:03,480
Speaker 1: it's funny, funny, free. Maybe we'll see. I've decided perhaps

1191
01:00:03,480 --> 01:00:05,840
Speaker 1: I might aim even higher, Katie. Really you're gonna run

1192
01:00:05,880 --> 01:00:10,840
Speaker 1: for president? No, it would be senator am I talking

1193
01:00:10,840 --> 01:00:14,840
Speaker 1: about you. Can I be your your press secretary? Oh

1194
01:00:14,960 --> 01:00:16,720
Speaker 1: my god? We would just go down and flames would

1195
01:00:16,760 --> 01:00:19,800
Speaker 1: be so good. Hey, it sounds like a sitcom, doesn't it?

1196
01:00:19,800 --> 01:00:25,320
Speaker 1: It does? It does, Let's write it. That's a wrap

1197
01:00:25,400 --> 01:00:28,360
Speaker 1: for us today. Thanks to our producer Gianna Palmer, our

1198
01:00:28,440 --> 01:00:32,440
Speaker 1: audio engineer Jared O'Connell, and our assistant producer Nora Richie.

1199
01:00:32,560 --> 01:00:35,240
Speaker 1: A big thank you to Emily Beana of Katie Current Media,

1200
01:00:35,480 --> 01:00:38,080
Speaker 1: to my assistant Beth de mos, and to Allison Presnett

1201
01:00:38,080 --> 01:00:41,040
Speaker 1: who tears it up on social media. You know we're

1202
01:00:41,040 --> 01:00:43,600
Speaker 1: going to run out of these things after a while. Anyway,

1203
01:00:43,640 --> 01:00:47,360
Speaker 1: our theme music, you ask Mark Phillips wrote it. Katie

1204
01:00:47,360 --> 01:00:50,640
Speaker 1: and I are the show's executive producers and Cody Scully

1205
01:00:50,800 --> 01:00:53,520
Speaker 1: is our terrific engineer here in l A. And here's

1206
01:00:53,520 --> 01:00:56,000
Speaker 1: your weekly reminder that you can drop us the line

1207
01:00:56,040 --> 01:00:59,160
Speaker 1: at comments at current podcast dot com or at nine

1208
01:00:59,240 --> 01:01:01,880
Speaker 1: to nine to four four six three seven. We really

1209
01:01:01,920 --> 01:01:06,360
Speaker 1: do value your feedback and your guest ideas as well. Meanwhile,

1210
01:01:06,400 --> 01:01:09,160
Speaker 1: you can find me on social media under Katie Kuric

1211
01:01:09,240 --> 01:01:11,560
Speaker 1: how Original, and you can find me on Twitter at

1212
01:01:11,640 --> 01:01:14,560
Speaker 1: Goldsmith b. We'll be back next week with the final

1213
01:01:14,640 --> 01:01:18,600
Speaker 1: installment in our Da Da Da Wonder women's series, where

1214
01:01:18,640 --> 01:01:21,680
Speaker 1: we'll be talking with dvf herself. That is right, people,

1215
01:01:22,040 --> 01:01:25,840
Speaker 1: fashion icon Dion von Furstenberg will be joining our show.

1216
01:01:26,120 --> 01:01:28,840
Speaker 1: Did you know she's also a former princess or maybe

1217
01:01:28,840 --> 01:01:31,720
Speaker 1: a current princess. Once a princess, always a princess. Anyway,

1218
01:01:31,760 --> 01:01:34,280
Speaker 1: get excited everyone, and by all means call in with

1219
01:01:34,320 --> 01:01:38,320
Speaker 1: your questions. Our voicemail line once again to nine to

1220
01:01:38,520 --> 01:01:41,560
Speaker 1: two four for six three seven. Thanks for listening and

1221
01:01:41,680 --> 01:01:43,640
Speaker 1: we will talk to you next week