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Speaker 1: Hi everyone, I'm Katie Couric and this is Next Question.

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Speaker 1: Hi everybody, welcome. Once again, it's Katie plus one. As

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Speaker 1: you guys know, just to switch things up, I'm inviting

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Speaker 1: a friend to co host the podcast from time to time,

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Speaker 1: and my date today is the one and only Kara Swisher. Now,

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Speaker 1: Kara is the ultimate multi hyphenate, as they say these days, writer, podcaster, author,

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Speaker 1: rock conteur, stripper. Oh sorry, you're not a stripper overall

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Speaker 1: that ass So, Kara, thank you so much. We are

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Speaker 1: both under the weather, so I think we need each

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Speaker 1: other today. You've got a cold.

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Speaker 2: You sound better than I sound terrible, and I had

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Speaker 2: to do four podcasts today.

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Speaker 1: Oh my god, how did you do it?

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Speaker 2: I didn't know we were dating. This is so exciting

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Speaker 2: for me as a lesbian that we're finally finally admitting

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Speaker 2: our deepen abiding affection and really lust for each other.

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Speaker 2: It's fantastic.

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Speaker 1: Well, I am very happy to have you here because, seriously,

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Speaker 1: not to gush, you're one of my favorite people. You're

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Speaker 1: one of the smartest people I know, thinks, an incredible reporter.

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Speaker 1: I think everyone in the business respects you so much. Kara,

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Speaker 1: and you're really fearless, which is what I love about you.

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Speaker 1: And you know, I thought you'd be the perfect person

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Speaker 1: to write Shotgun with me, although I can't imagine you're

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Speaker 1: willing to give up the driver's seat. But we're going

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Speaker 1: to be chatting with Kevin Sistrom, who you know well.

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Speaker 1: But before I just want to give our listeners a

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Speaker 1: little bit about us, Kara. How did we meet? I

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Speaker 1: was trying to remember when I first met you.

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Speaker 2: When I broke the story about you going to Yahoo?

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Speaker 1: I think, oh, is that when? Yes? But I was

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Speaker 1: reading your stuff all the time.

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Speaker 2: We sense because you were thinking about going to Yahoo,

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Speaker 2: you had to, right, Yeah.

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Speaker 1: But so that was I guess in around twenty twelve.

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Speaker 2: Yeah, I guess, yeah.

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Speaker 1: And who were you writing for back then?

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Speaker 2: My own thing, Recode? Oh, that's right, Recode. Yeah.

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Speaker 1: And you were breaking stories right and left, including the

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Speaker 1: one about me.

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Speaker 2: I was and I thought it was intriguing. I thought

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Speaker 2: it was super intriguing that someone like you, you'd been

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Speaker 2: at all the broadcast networks. It was a big moment

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Speaker 2: for people to make that crossover. You were one of

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Speaker 2: the few and the early ones. Now it didn't work

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Speaker 2: out quite the way you wanted to, but it still

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Speaker 2: was pretty brave to do something like that and to

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Speaker 2: try something out, and you know, you kind of got

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Speaker 2: snowed by Merissa Mayer.

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Speaker 1: I did. And I think in retrospect, not only was

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Speaker 1: it a bad fit because I don't think her goals

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Speaker 1: and my goals aligned right in terms of turning Yahoo

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Speaker 1: into a really major digital news network, but you know,

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Speaker 1: I also think I might have been a bit too early.

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Speaker 2: Kara, Yeah, because you're not unlike what you're doing now

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Speaker 2: with podcasting. You know, you were kind of doing That's

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Speaker 2: what you were kind of doing, but you did it

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Speaker 2: in more traditional sense, which was interviews and things like that.

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Speaker 2: What was your title? It was so big? It was

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Speaker 2: like global news anchor.

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Speaker 1: Yes, my husband made fun of me and said, why

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Speaker 1: don't they call you intergalactic news anchor? I know it

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Speaker 1: was a blood news anchor. It was a little a

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Speaker 1: little much.

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Speaker 2: But it was early, and it was really important for

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Speaker 2: people who who didn't understand what was happening in news

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Speaker 2: on the internet to for have someone like you to

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Speaker 2: go over and very few people did that. You know,

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Speaker 2: I'm trying to think. I think it was you and

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Speaker 2: nobody else. Yeah, there were a couple, you know, but

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Speaker 2: mostly what happened is later people that were on networks

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Speaker 2: did podcasts or they did you know, it's different things,

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Speaker 2: but podcasts and newsletters, which was an impairy thing, or

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Speaker 2: else ape here has an influencer on TikTok or Instagram

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Speaker 2: and stuff like that, and so you were early to

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Speaker 2: all those things. As I recall, you were very early

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Speaker 2: to Instagram, you were on Twitter early. Yeah, you were

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Speaker 2: very embracing of the digital part. You didn't make fun

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Speaker 2: of it the way most media people did.

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Speaker 3: Well.

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Speaker 1: I think I saw early on. Honestly, I think part

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Speaker 1: from my own experience at CBS. You know, there was

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Speaker 1: the decline of linear television. It was going steadily declining

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Speaker 1: year over year, and I realized that, you know, in

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Speaker 1: two thousand and eight. It was two thousand and eight

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Speaker 1: when the iPhone came out. I mean that totally changed

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Speaker 1: the game. And care I remember being at CBS and

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Speaker 1: having somebody say to me, I forget who he was.

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Speaker 1: He goes, the future is mobile, But I remember thinking,

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Speaker 1: what is he talking about? And he was so spot on,

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Speaker 1: but whatever was going to happen, I knew something was changing.

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Speaker 1: And meanwhile, you have been on the forefront of everything.

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Speaker 2: Well mobile, you know Walt and I called Mobile Web

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Speaker 2: two point zero. I think we were very when we

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Speaker 2: saw the iPhone, and you know, Jobs had denied he

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Speaker 2: was making it to us the year before he introduced it. No,

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Speaker 2: I'm not working on a phone but an interview, but

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Speaker 2: he was. The minute that happened, the iPhone changed everything,

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Speaker 2: including you know, for Kevin System, you wouldn't have had Instagram,

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Speaker 2: you wouldn't have had Uber, you wouldn't have had a

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Speaker 2: lot of Airbnb. There's so much you wouldn't have without

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Speaker 2: the apogonomy. And of course that's when companies likeness came

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Speaker 2: into being, really because of the iPhone.

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Speaker 1: It's amazing how much things have changed when you think

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Speaker 1: about when we got into journalism and the things that

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Speaker 1: have tanked as a result of the Internet and things

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Speaker 1: that have exploded. Well, you've got a lot going on

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Speaker 1: in your life. I'm excited to have you back on

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Speaker 1: this podcast when your new book comes out in twenty

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Speaker 1: twenty four. It's called burn Book, Right, you'll like it.

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Speaker 2: Kaaney, you're in it.

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Speaker 1: Oh God, I hope you're nice to meet Kara.

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Speaker 2: I am. It's a low bar though it's a low

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Speaker 2: bar for people in the Internet.

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Speaker 1: Well, I know you're not a fan of a lot

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Speaker 1: of people in Silicon Valley, but you are a fan

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Speaker 1: of our guest, Kevin Sistrom.

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Speaker 2: I am very much.

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Speaker 1: So well, let's let him in so you can talk

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Speaker 1: about him and he can his ears can actually burn

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Speaker 1: in person.

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Speaker 3: Kevin, Hi, how are you guys? How are you wonderful?

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Speaker 1: What a coincidence, Kevin? We were just talking about you,

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Speaker 1: and I was saying to Kara there are a lot

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Speaker 1: of people in Silicon Valley she's not crazy about, but

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Speaker 1: one of the people she really really likes Kevin is you.

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Speaker 1: You're in rare company. Now, what is it about Kevin,

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Speaker 1: Kara that you like?

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Speaker 2: Well, you know, I really do admire you know, there's

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Speaker 2: a lot of people I had a lot of wrangling with,

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Speaker 2: like Steve Jobs, who I actually did like too. I

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Speaker 2: like people who love products. I love people who have

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Speaker 2: a design sense, have a real tear about products and

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Speaker 2: designing them correctly. I like someone who's thoughtful and is

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Speaker 2: willing to change their minds. You know, Kevin was always

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Speaker 2: open to criticism in a way that didn't It wasn't

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Speaker 2: hurt all the time.

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Speaker 1: And Kevin I mean, it seems like you have a

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Speaker 1: lot of humility, which is a quality that's probably hard

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Speaker 1: to come by in Silicon Valley. How have you been

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Speaker 1: able to maintain some openness, some humility as you've approached

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Speaker 1: your work.

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Speaker 3: I was having dinner with the Promise site and we

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Speaker 3: were talking about Artifact and my current project and how

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Speaker 3: it's going and the future of it, and I said,

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Speaker 3: I think the difference between the people that succeed in

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Speaker 3: the long run and the people that continue to fail

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Speaker 3: are the people that do their best to recognize their

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Speaker 3: blind spots and that everyone has them. And the problem is,

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Speaker 3: at least in Silicon Valley, that these companies grow to

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Speaker 3: be so large that if you stay in charge, you

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Speaker 3: can ignore your blind spots because you've got your moat,

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Speaker 3: you've got your defense, and you can ignore all of

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Speaker 3: the things you don't know about yourself because you're successful,

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Speaker 3: and you continue to be successful, and you have all

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Speaker 3: this money. The problem is, let's imagine you sell your company.

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Speaker 3: You're no longer in charge of your company, and you

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Speaker 3: have to go face the real world. You have to

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Speaker 3: get in touch with your failings and your weaknesses pretty quickly,

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Speaker 3: otherwise you get chewed up and spit out the other side.

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Speaker 3: That's what every entrepreneur has to do at some point

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Speaker 3: in their life. The problem is that people that cares

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Speaker 3: talking about, I believe, are the people who get to

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Speaker 3: the point where they don't have to really think about

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Speaker 3: those things because they're just riding the wave that they

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Speaker 3: caused maybe ten or twenty years ago. Have that wave anymore?

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Speaker 3: You have to create a new wave. And in order

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Speaker 3: to create that wave, I think you need to understand

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Speaker 3: where you're good, where you're not good, and sometimes that

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Speaker 3: can be a painful process.

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Speaker 2: Well you know, Kevin, it's also a question of maturity, right,

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Speaker 2: I sort of link I split people between adults and toddlers. Really,

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Speaker 2: I don't know what else to say, is adult toddlers

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Speaker 2: who get enabled and coddled. And you know this from

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Speaker 2: having money. You don't know who's your friend. You have

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Speaker 2: people in violent agreement with you almost all the time,

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Speaker 2: and the ability to take feedback is very hard when

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Speaker 2: everybody is enabling you not to not to do so,

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Speaker 2: and I think it makes you a lesser executive in

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Speaker 2: my opinion. And you don't hear let me tell you

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Speaker 2: who you don't hear from about that who doesn't complain

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Speaker 2: when you have a good about their product is the

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Speaker 2: people from Apple. You don't hear Tim Cook belly aching

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Speaker 2: about anything because he's an adult, and so I think,

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Speaker 2: and I don't think you have to be old to

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Speaker 2: be an adult. I think you were an adult from

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Speaker 2: very early on. I mean that was my feeling at

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Speaker 2: the time.

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Speaker 3: I appreciate that.

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Speaker 1: Well, let's talk about early on, Kevin, because I know

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Speaker 1: we have so much to cover, But I do want

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Speaker 1: to start with Instagram, just because I'm addicted to it

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Speaker 1: and I've been going down endless rabbit holes, much to

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Speaker 1: my estegrint. I mean constantly. It's really hard. It is addictive.

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Speaker 1: But where did the idea from Instagram come from?

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Speaker 3: It came from We were working on a different app,

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Speaker 3: not Instagram, called Bourbon, and it was spelled b u

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Speaker 3: RBN and the name doesn't matter. It was funny, but

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Speaker 3: it was a check in app. It led you share

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Speaker 3: your location, so you could say I'm at a restaurant,

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Speaker 3: I'm at a bar, and all your friends would see

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Speaker 3: where you were. And it was kind of riding this

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Speaker 3: wave of check an app.

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Speaker 2: Poor Square was the popular yeah.

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Speaker 3: Or Square Goala Hot Potato there were a bunch of them.

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Speaker 2: Was looped in.

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Speaker 3: There was looped yep, yep. Here's the thing people forget

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Speaker 3: that maybe they don't forget, but it's easy to forget that.

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Speaker 3: We see these waves of like everyone's doing generative AI

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Speaker 3: all at once, everyone's doing Web three. My version of

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Speaker 3: that when I started was check and apps. Everyone was

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Speaker 3: doing check and apps. And we started this check and app.

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Speaker 3: And the one feature that we had that no other

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Speaker 3: check and app had was the ability to add photos.

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Speaker 3: And you can attach a photo to your check in,

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Speaker 3: so you could say, I'm at the beach, here's me

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Speaker 3: at the beach. And no one really liked our check

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Speaker 3: and app. No one really wanted to use it. I mean,

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Speaker 3: we had a small group of people playing with it,

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Speaker 3: and you know, we took a step back, Mike Kreeger

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Speaker 3: and I and Mike cofounder, we took a step back

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Speaker 3: and we said, why and what is it about the

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Speaker 3: thing we've built that people do love? So we crossed

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Speaker 3: everything out. We had a whiteboard and we wrote everything

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Speaker 3: that people used on the app up on the whiteboard

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Speaker 3: and crossed everything off, and we ended up basically with

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Speaker 3: one thing circled, which was photos. We said, okay, what

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Speaker 3: if we threw away literally everything about this app and

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Speaker 3: repositioned it around photos. So we did that. But that's

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Speaker 3: not the end of the story. A very quick addition

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Speaker 3: to the story is we did that pivot. We built

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Speaker 3: this app, we didn't call it Instagram yet, and I

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Speaker 3: was I decided I needed a week off because I

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Speaker 3: was exhausted. I was like, I don't think this pivot's

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Speaker 3: going to work. So I'm going to go to Mexico

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Speaker 3: for a week to a little little seaside town with

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Speaker 3: who would become my wife, who was my girlfriend at

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Speaker 3: the time, Nicole. And we we're walking along the beach

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Speaker 3: and I said, do you think you'll use this new

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Speaker 3: version of this app called Bourbon that's photos only? And

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Speaker 3: she said, no, I don't think I will because I

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Speaker 3: don't like sharing my photos. My photos aren't good enough.

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Speaker 3: I said, why aren't your photos good enough? And she said, well,

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Speaker 3: because all your friends take these amazing, beautiful filtered photos.

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Speaker 3: And I was like, yeah, that's because they use filter apps.

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Speaker 3: And she's like, well, you should probably add filters to

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Speaker 3: the app. I said, that's a brilliant idea. So we

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Speaker 3: finished that walk on the beach I went back to

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Speaker 3: the little hotel room we were staying in and I

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Speaker 3: researched how to make the first filter. And if you

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Speaker 3: look way back on my profile, the first photo on

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Speaker 3: my profile, the first photo ever on Instagram, is a

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Speaker 3: square photo of a very small dog in Mexico when

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Speaker 3: we went out to lunch after I built the first

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Speaker 3: filter on Instagram because of that walk on the beach. Wow,

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Speaker 3: I'm proud to say she is now my wife and

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Speaker 3: I love her dearly.

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Speaker 2: Well did you pay her? Did you pay her for it?

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Speaker 1: I was gonna say, but I think I don't think

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Speaker 1: she has a good prenup.

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Speaker 2: Yeah.

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Speaker 3: Well, I think we're both very, very happy with the situation.

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Speaker 3: I'm very happy to be married to her, and we

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Speaker 3: just we have this great life now. So it's awesome.

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Speaker 3: But how do we knock down on that walk?

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Speaker 1: I remember I was at Yahoo, you guys when when

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Speaker 1: Instagram came out, and somebody on my team says, you

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Speaker 1: need to be on Instagram. You know, it's this great

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Speaker 1: new thing, and I was like what, But I was

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Speaker 1: I kind of got into it pretty quickly, and it

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Speaker 1: just grew so fast, Kevin, to the point you sold

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Speaker 1: it to Mark Zuckerberg for one billion dollars, which is

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Speaker 1: a nice chunk of change.

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Speaker 2: Actually, Katie, it was cheap, you know, are really Oh yeah, really,

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Speaker 2: Zuckerberg got the bargain of a century getting that fantastic.

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Speaker 1: Oh, you're right, I've read that. How much do you

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Speaker 1: think you could have sold it for in retrospect, Kevin?

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Speaker 1: Or do you hate that question?

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Speaker 3: I don't hate the question because I'm so used to

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Speaker 3: getting it now. I think I hated it the first

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Speaker 3: couple of times, but now now I feel like I've

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Speaker 3: come to terms with my answer, which is, at the time,

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Speaker 3: do you know how many people, Katie, we had at

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Speaker 3: the company when we sold it for a billion dollars?

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Speaker 2: Seven?

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Speaker 1: Right?

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Speaker 2: Seven? Maybe more?

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Speaker 3: It was nine? I think maybe nine or ten. It's okay.

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Speaker 3: You imagine you have a group of kids in a

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Speaker 3: room working on a photo app and someone comes along

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Speaker 3: and says, how about a billion? You know, I don't

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Speaker 3: know many people that would turn that deal down?

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Speaker 2: Yeah, and you.

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Speaker 3: Know, Listen could have should have would a had we

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Speaker 3: stayed the course been independent. I don't know. I mean,

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Speaker 3: how many examples of people, maybe I know more of

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Speaker 3: them personally have turned down acquisition offers Facebook for one

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Speaker 3: hundred billion dollars. Well, you know, Facebook's the easy one.

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Speaker 3: That's the one we all talked about. Let's talk about

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Speaker 3: the one is that didn't work out. Yeah, you're right,

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Speaker 3: hundred that turned down one two hundred million dollar offers

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Speaker 3: saying you know what, we're going to stick the course.

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Speaker 3: Now you literally never heard of these companies.

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Speaker 2: I think my point, Kevin, was that you were making

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Speaker 2: something that was special and different. Having seen everything, I

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Speaker 2: think while I think they did help you grow quickly,

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Speaker 2: I suspect you could have done it by yourselves, because

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Speaker 2: your product was quite magical in a way that not

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Speaker 2: a lot of them are. How much do you imagine

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Speaker 2: they helped you grow? I don't think I've ever asked

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Speaker 2: you that. How much do you think they being within

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Speaker 2: the juggernaut of Facebook, which was at that moment still

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Speaker 2: is really did you think they really did help you?

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Speaker 2: I assume you did.

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Speaker 3: I think they helped us in a bunch of ways,

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Speaker 3: and we helped them back in a bunch of ways.

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Speaker 3: And there's a little bit of this dynamic of we

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Speaker 3: and them, which I find so strange. By the way, Yeah,

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Speaker 3: because you know, like sure, we had a little building

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Speaker 3: on campus and had a little Instagram logo on the outside,

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Speaker 3: but we were all part of the same company. And

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Speaker 3: I'm bringing this up not to point out the way

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Speaker 3: you're talking about us, but rather the way we talked

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Speaker 3: about ourselves internally. When I was there, it was such

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Speaker 3: an US versus then dynamic, and it was very strange

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Speaker 3: in my head always because I was like, here, we

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Speaker 3: are now producing billions of dollars, years in billions of dollars,

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Speaker 3: but it's as if we're like two siblings fighting over

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Speaker 3: who gets the remote and we're not.

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Speaker 1: Well. It sounded like that to me, though, Kevin, because

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Speaker 1: everything I read it sounds like, and correct me if

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Speaker 1: I'm wrong that Mark Zuckerberg was kind of threatened by

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Speaker 1: you and your success and the fact that a lot

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Speaker 1: of resources were going to Instagram, and I don't know,

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Speaker 1: it sounds like his ego got in the way. Is

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Speaker 1: that accurate.

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Speaker 3: I don't know that I can speak on his bath

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Speaker 3: for that. You'd have to ask him directly.

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Speaker 1: I mean, is that how you felt.

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Speaker 3: The way that I felt was that nothing made sense

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Speaker 3: logically about the way we were running the two companies. Logically.

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Speaker 3: It was amazing that we had lightning in a bottle,

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Speaker 3: and we were producing, you know, a product that was

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Speaker 3: growing all over the world and you know, double digit

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Speaker 3: growth rates per month and then on top of that,

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Speaker 3: producing billions of dollars. Yet for summer reason, internally, the

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Speaker 3: dynamic was that we were disappointed. Yeah, and that was

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Speaker 3: very strange. And like, basically the reason I left, by

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Speaker 3: the way, and I've said this to friends, and I'm

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Speaker 3: not sure I've ever said it to anyone else, but

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Speaker 3: like the reason I left is because the more I

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Speaker 3: felt that I put in and the more that we won,

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Speaker 3: the harder my job got. The more difficult the more

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Speaker 3: and not that like not that jobs don't get harder

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Speaker 3: as things go on, But it wasn't like that's that

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Speaker 3: success was a good thing. It was almost as if

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Speaker 3: that success was a bad thing because we had this product,

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Speaker 3: Facebook Blue, which was going through some tough times. And

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Speaker 3: I get that I probably, you know, could have been

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Speaker 3: a better you know, I don't know, sibling or whatever

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Speaker 3: in terms of understanding how challenging that must be for

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Speaker 3: those people and for those teams and for the brand.

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Speaker 3: And at the same time, I found it so strange

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Speaker 3: that we didn't look at our situation as holy crap.

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Speaker 3: We are the luckiest people on earth and maybe the

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Speaker 3: luckiest company on Earth. That feels like a real tragedy

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Speaker 3: in retrospect.

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Speaker 1: Yeah, well, I read that you were on I Guess

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Speaker 1: doing some interviews and Mark and Cheryl said basically you

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Speaker 1: couldn't do interviews without getting permissioned from them. So it

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Speaker 1: does sound like a bit of a power struggle. What's

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Speaker 1: your take on that, Kiara.

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Speaker 2: I think they were jealous of I know they were

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Speaker 2: jealous of Kevin largely because of creativity. And the knock

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Speaker 2: on them was that they stole ideas, that they were shoplifters,

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Speaker 2: essentially of other people's theories and ideas. Now, as it

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Speaker 2: turned out, Instagram became an enormous engine for Facebook. As

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Speaker 2: Facebook started to wane in usage, in excitement in young people,

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Speaker 2: being especially young people, it was critical. To me. There's

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Speaker 2: certain purchases in technology that are critical that really changed them.

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Speaker 2: I think Google buying you Tube was one of them.

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Speaker 2: And I think there are certain purchases where it's a

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Speaker 2: real turning point. I think it wasn't a critical critical thing,

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Speaker 2: and it's sort of as rich and famous as you get,

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Speaker 2: it doesn't matter if it wasn't you who did. And

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Speaker 2: I think Bill Gates suffered from this, you know, probably

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Speaker 2: more towards Steve Jobs. Is like Bill Gates before he

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Speaker 2: did all the philanthropy when he if he had died

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Speaker 2: then it would have been the world's richest man died today.

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Speaker 2: And if Steve Jobs done, which he later did, the

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Speaker 2: world's greatest tech visionary died today. And I think Kevin

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Speaker 2: was more in the visionary part of that. And Mark,

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Speaker 2: you know, he's like a Henry Ford character. And so

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Speaker 2: that's what makes it hard. And again let me I'd

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Speaker 2: love to ask you getting back to the product, and

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Speaker 2: that's really what you have to get to is the

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Speaker 2: product itself and the iterations you make around it, including

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Speaker 2: as I've talked with Kevin about doing stories that was

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Speaker 2: a snapchat thing that then Instagram did. Now Kevin's quite

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Speaker 2: smartly and very cleverly. Is said to me, well, they

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Speaker 2: made a radio in a car, and we just made

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Speaker 2: a better radio in a car. And I kind of

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Speaker 2: accept that now. I accept that now, Kevin.

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Speaker 3: It's funny, by the way, Kara for a second that

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Speaker 3: you know you'll say that Facebook or shoplifters, but like

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Speaker 3: to be clear, story was a very direct. You know,

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Speaker 3: it wasn't a replica because I think we added some

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Speaker 3: really neat features to it.

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Speaker 2: You did.

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Speaker 3: But I do believe that, like you know, as much

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Speaker 3: as Facebook might have invented the Facebook news feed. Yes,

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Speaker 3: now you can't see a social product without a news feed,

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Speaker 3: but that wasn't a given back then.

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Speaker 2: That's true.

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Speaker 3: So these things are not property the founder. Yeah, it's

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Speaker 3: about who actecutes best on them. And now we're seeing

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Speaker 3: that play out with the Twitter feed effectively across multiple products.

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Speaker 2: Yeah, everyone's doing a version of Twitter, including you and

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Speaker 2: your new you know, a version of But the idea

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Speaker 2: of it is a feed, isn't It really is a

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Speaker 2: feed when you think about it. But one of the

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Speaker 2: things that I think is important to remember is that

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Speaker 2: not just from a creative point of view, it gave

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Speaker 2: Facebook and enormous amount of credibility to own a product

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Speaker 2: like this, it also was financially enormous, like enormous, and

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Speaker 2: a safer place than what was going on at Facebook.

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Speaker 2: I think that was really important, a pleasant place. Facebook

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Speaker 2: had started to get different right as they got criticized.

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Speaker 2: But Instagram, even though there are lots of problems on

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Speaker 2: Instagram around lots of problems. You know, it still was

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Speaker 2: a place of product of enjoyment. I guess. I don't

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Speaker 2: know else to put it, but a product of enjoyment

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Speaker 2: more than anything else and delight. And I think that's

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Speaker 2: hard to do and sustain. Twitter has never been enjoyable.

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Speaker 2: It's been funny, it's been vexing, it's been addictive, But

436
00:20:36,760 --> 00:20:39,199
Speaker 2: enjoying I don't think so. I don't, you know, I

437
00:20:39,200 --> 00:20:42,520
Speaker 2: guess in a broader sense, and that's very hard to do.

438
00:20:45,560 --> 00:20:48,680
Speaker 1: After this break, we dive into how tech companies can

439
00:20:48,680 --> 00:20:53,159
Speaker 1: build products that select for something other than outrage. Kevin

440
00:20:53,200 --> 00:20:55,760
Speaker 1: has some great ideas on how to do just that.

441
00:20:59,720 --> 00:21:02,400
Speaker 1: I want to get smarter every morning with a breakdown

442
00:21:02,400 --> 00:21:05,680
Speaker 1: of the news and fascinating takes on health and wellness

443
00:21:05,680 --> 00:21:08,840
Speaker 1: and pop culture. Sign up for our daily newsletter, Wake

444
00:21:08,920 --> 00:21:16,160
Speaker 1: Up Call by going to Katiecuric dot com. And we're

445
00:21:16,200 --> 00:21:19,400
Speaker 1: back with our guest, Kevin Sistrom and my co pilot

446
00:21:19,520 --> 00:21:24,000
Speaker 1: Kara Swisher. I wanted to ask you about the negative

447
00:21:24,040 --> 00:21:27,320
Speaker 1: side of Instagram, Kevin. Obviously, there are a lot of

448
00:21:27,840 --> 00:21:34,840
Speaker 1: negative impacts on girls, on mental health. On the comparison

449
00:21:35,280 --> 00:21:39,480
Speaker 1: that it encourages, and is that just part of the deal.

450
00:21:39,680 --> 00:21:44,280
Speaker 1: I mean, can anything be done about the psychosocial impact

451
00:21:44,400 --> 00:21:47,439
Speaker 1: of some of these platforms, and specifically Instagram, and is

452
00:21:47,880 --> 00:21:52,879
Speaker 1: as you saw it having this impact. I'm curious what

453
00:21:53,000 --> 00:21:54,000
Speaker 1: went through your mind.

454
00:21:54,960 --> 00:21:58,240
Speaker 3: I think it all comes down to leadership, the idea

455
00:21:58,400 --> 00:22:03,400
Speaker 3: that you have a school and that tool take nuclear

456
00:22:03,560 --> 00:22:08,840
Speaker 3: energy can be used for amazing things. It can produce clean,

457
00:22:09,000 --> 00:22:14,000
Speaker 3: sustainable energy, but also, if used not in the right way,

458
00:22:14,640 --> 00:22:23,200
Speaker 3: can create massive destruction. Tools themselves rarely have a very

459
00:22:23,240 --> 00:22:28,280
Speaker 3: clear positive or negative effect. It's when you put that

460
00:22:28,320 --> 00:22:32,120
Speaker 3: tool in someone's hand and that person decides to start

461
00:22:32,119 --> 00:22:35,000
Speaker 3: making rules around it, in judgments about what's allowed what's

462
00:22:35,040 --> 00:22:39,840
Speaker 3: not allowed, the way they decide to moderate things, their

463
00:22:39,960 --> 00:22:42,840
Speaker 3: community guidelines, the tone they set as a leader with

464
00:22:42,920 --> 00:22:47,120
Speaker 3: their own posts. If we're talking social media, and as

465
00:22:47,160 --> 00:22:52,159
Speaker 3: a leader at Instagram, early on, I decided that we

466
00:22:52,200 --> 00:22:55,560
Speaker 3: should focus on being the nicest place on the Internet.

467
00:22:55,600 --> 00:22:58,200
Speaker 3: And nice is like a really lame word, but let's

468
00:22:58,320 --> 00:23:02,399
Speaker 3: move past that to maybe dness. So, for instance, we

469
00:23:02,400 --> 00:23:04,879
Speaker 3: were one of the first, if not the first, major

470
00:23:04,920 --> 00:23:09,760
Speaker 3: social network to use machine learning to detect bullying and

471
00:23:09,880 --> 00:23:13,719
Speaker 3: intervene in bullying situations. Most people were worried about spam

472
00:23:13,760 --> 00:23:16,119
Speaker 3: at this point. So if you went to any other network,

473
00:23:16,160 --> 00:23:19,640
Speaker 3: they'd had spam filters and spand detectors, and we were

474
00:23:19,720 --> 00:23:23,520
Speaker 3: focused on interactions that didn't qualify as spam, but were

475
00:23:23,600 --> 00:23:26,720
Speaker 3: human to human interactions that were negative, and we would

476
00:23:26,760 --> 00:23:29,760
Speaker 3: intervene and try to stop those things. Those are the

477
00:23:29,800 --> 00:23:32,280
Speaker 3: types of decisions that I think made Instagram such a

478
00:23:32,320 --> 00:23:34,960
Speaker 3: great place early on, because we didn't We used to

479
00:23:35,040 --> 00:23:38,359
Speaker 3: have caro. We used to have this phrase internally called

480
00:23:38,400 --> 00:23:42,119
Speaker 3: prune the trolls. Yeah, and we used to just get

481
00:23:42,200 --> 00:23:44,800
Speaker 3: rid of We used to block accounts of people who

482
00:23:44,920 --> 00:23:49,679
Speaker 3: were causing issues very very early on, and that was

483
00:23:49,760 --> 00:23:51,600
Speaker 3: getting rid of the negative. But then we would also

484
00:23:51,640 --> 00:23:55,280
Speaker 3: host these community meetups called instamets, and we would bring

485
00:23:55,359 --> 00:24:00,639
Speaker 3: together people on the platform in person, in a to

486
00:24:00,680 --> 00:24:02,680
Speaker 3: meet each other, to put a face to a name,

487
00:24:03,200 --> 00:24:05,600
Speaker 3: and those types of interactions very early on, I think

488
00:24:05,680 --> 00:24:09,640
Speaker 3: set an amazing tone for the community that lasted well

489
00:24:09,640 --> 00:24:13,479
Speaker 3: beyond my tenure. But as you get bigger and bigger

490
00:24:13,520 --> 00:24:16,960
Speaker 3: and you get into the billions, the law of large

491
00:24:17,040 --> 00:24:20,480
Speaker 3: numbers says that you get just about everyone on the platform,

492
00:24:21,320 --> 00:24:24,439
Speaker 3: every type of person, so it becomes much harder to

493
00:24:24,440 --> 00:24:27,919
Speaker 3: make these decisions. So maybe in one country something is

494
00:24:27,960 --> 00:24:30,680
Speaker 3: well accepted, will in another country it's not accepted. You

495
00:24:30,760 --> 00:24:33,600
Speaker 3: have to make these really hard choices about what's allowed

496
00:24:33,640 --> 00:24:36,159
Speaker 3: and what's not allowed, and you start to make people

497
00:24:36,200 --> 00:24:39,240
Speaker 3: angry with these choices. But it all comes down to leadership.

498
00:24:39,280 --> 00:24:41,720
Speaker 3: It all comes down to those fundamental decisions you make

499
00:24:42,160 --> 00:24:44,480
Speaker 3: as a human holding that tool in your hand, with

500
00:24:44,520 --> 00:24:45,600
Speaker 3: the control which.

501
00:24:45,440 --> 00:24:47,159
Speaker 2: I think is lost for a lot of people. A

502
00:24:47,160 --> 00:24:49,520
Speaker 2: lot of tech people try to abrogate. I don't want

503
00:24:49,520 --> 00:24:51,359
Speaker 2: to have anything to do even as they built it,

504
00:24:51,840 --> 00:24:54,000
Speaker 2: like I didn't mean to build this city.

505
00:24:53,800 --> 00:24:56,560
Speaker 1: Right, Well we're a platform, we're not a publisher, right.

506
00:24:56,480 --> 00:24:58,080
Speaker 2: Yeah, but they built it in the first place, and

507
00:24:58,080 --> 00:25:00,359
Speaker 2: they think one of the things is important Keavn can

508
00:25:00,480 --> 00:25:02,240
Speaker 2: talk to this about a new thing is you have

509
00:25:02,320 --> 00:25:04,119
Speaker 2: to have a set of rules. And it's okay. You

510
00:25:04,160 --> 00:25:07,080
Speaker 2: know this whole canard that it's a public square. It's

511
00:25:07,080 --> 00:25:09,680
Speaker 2: not a public anything. It's a private money making company.

512
00:25:09,920 --> 00:25:11,639
Speaker 2: I mean, I don't know, Kevin. I think that I

513
00:25:11,680 --> 00:25:14,960
Speaker 2: think these are these are companies and you know company

514
00:25:15,200 --> 00:25:16,840
Speaker 2: as it's rules and so should this.

515
00:25:17,119 --> 00:25:19,440
Speaker 1: Are there any things that you see Kevin when you

516
00:25:19,520 --> 00:25:22,840
Speaker 1: go on Instagram today that you wish wasn't happening, or

517
00:25:23,000 --> 00:25:26,399
Speaker 1: changes you think, Oh, I'm so pissed there letting this happen,

518
00:25:26,720 --> 00:25:28,840
Speaker 1: or if I were there, I would do X, Y

519
00:25:29,000 --> 00:25:29,200
Speaker 1: or Z.

520
00:25:30,119 --> 00:25:31,639
Speaker 3: At the end of the day, the question is how

521
00:25:31,680 --> 00:25:34,440
Speaker 3: you incentivize people and who's in control? And I think

522
00:25:34,480 --> 00:25:36,399
Speaker 3: what we've seen so you asked, you know, what do

523
00:25:36,480 --> 00:25:38,919
Speaker 3: I wish was different? Yeah, I'm not sure it's an

524
00:25:38,920 --> 00:25:43,159
Speaker 3: Instagram problem specifically, but you know, products like reels and

525
00:25:43,240 --> 00:25:47,359
Speaker 3: product like like YouTube shorts or even TikTok, they're so

526
00:25:47,640 --> 00:25:52,320
Speaker 3: optimized on engagement that they will show you things that

527
00:25:52,359 --> 00:25:55,200
Speaker 3: you are not actually interested in, but they will make

528
00:25:55,240 --> 00:25:58,479
Speaker 3: you stare at them forever, and then you wake up

529
00:25:58,520 --> 00:26:00,159
Speaker 3: one day and you look around you go, god, I

530
00:26:00,200 --> 00:26:02,400
Speaker 3: just spend an hour. Was that like a useful hour

531
00:26:02,440 --> 00:26:03,040
Speaker 3: of my life?

532
00:26:03,240 --> 00:26:03,440
Speaker 2: Right?

533
00:26:03,520 --> 00:26:05,840
Speaker 3: And part of why I started Artifact was the belief

534
00:26:05,880 --> 00:26:09,040
Speaker 3: that you could use some of the same technology to personalize,

535
00:26:09,720 --> 00:26:12,520
Speaker 3: but do it in a way that actually showed people

536
00:26:12,600 --> 00:26:16,359
Speaker 3: things that made their life more informed, maybe a little

537
00:26:16,400 --> 00:26:16,840
Speaker 3: bit better.

538
00:26:17,240 --> 00:26:18,679
Speaker 2: Kevin's talking a little bit. If you want to make

539
00:26:18,680 --> 00:26:21,480
Speaker 2: an analogy to sugar, right, isn't this doughnut delicious, what

540
00:26:21,560 --> 00:26:23,479
Speaker 2: a delicious done? And you may even not want it.

541
00:26:23,840 --> 00:26:26,680
Speaker 2: You may want something healthy, or you might want something different,

542
00:26:27,080 --> 00:26:28,200
Speaker 2: but it's hard to resist.

543
00:26:28,440 --> 00:26:29,719
Speaker 1: But it's sitting in front of you.

544
00:26:29,880 --> 00:26:32,880
Speaker 2: Well, it's how you architect things. And Kevin's a designer.

545
00:26:32,920 --> 00:26:35,920
Speaker 2: If you architect for virality and speed, you're going to

546
00:26:36,000 --> 00:26:38,440
Speaker 2: get a different thing. And if you architect for context

547
00:26:39,000 --> 00:26:43,080
Speaker 2: and content, like really good what you're looking for right, absolutely,

548
00:26:43,359 --> 00:26:45,840
Speaker 2: And so it's a question of what architecture you put

549
00:26:45,880 --> 00:26:48,640
Speaker 2: into place and so many of these things, or else

550
00:26:48,680 --> 00:26:51,520
Speaker 2: you don't put anything into place. And people generally trend

551
00:26:51,840 --> 00:26:54,280
Speaker 2: towards shitty stuff. Look at the shitty stuff, look at

552
00:26:54,280 --> 00:26:56,240
Speaker 2: the accent. And that's what's going on on Twitter right now.

553
00:26:56,400 --> 00:26:59,720
Speaker 2: He's just removed everything, and so people who are bad

554
00:27:00,440 --> 00:27:03,119
Speaker 2: can come in and really attract you in a way

555
00:27:03,240 --> 00:27:05,560
Speaker 2: that is just the human brain. It's it crawls down

556
00:27:05,600 --> 00:27:07,280
Speaker 2: your cerebral cortex.

557
00:27:07,359 --> 00:27:11,640
Speaker 3: Really, Kara, I have an example. Sure, I love coffee, okay,

558
00:27:11,680 --> 00:27:14,679
Speaker 3: and I go to Starbucks and by the way, like

559
00:27:15,240 --> 00:27:18,480
Speaker 3: you know people who I claim on a coffee er,

560
00:27:18,520 --> 00:27:20,119
Speaker 3: and then I tell people I go to Starbucks and

561
00:27:20,119 --> 00:27:22,520
Speaker 3: they're like wait what, But like I do.

562
00:27:22,800 --> 00:27:26,080
Speaker 2: I'm surprised. I'm surprised you went to Starbucks. I'm surprised.

563
00:27:26,119 --> 00:27:29,440
Speaker 3: Listen, I'm a busy guy with like two kids. Sometimes

564
00:27:29,480 --> 00:27:31,240
Speaker 3: you need a great, great quick cos.

565
00:27:31,119 --> 00:27:33,439
Speaker 2: He's kind of a coffee snob. You are a coffee

566
00:27:33,440 --> 00:27:33,680
Speaker 2: you were.

567
00:27:33,720 --> 00:27:36,280
Speaker 3: Here's the thing. I've been going to Starbucks for god

568
00:27:36,359 --> 00:27:41,680
Speaker 3: knows how many years, and like, Starbucks is a milkshake company. Guys,

569
00:27:42,040 --> 00:27:44,720
Speaker 3: it's a milkshake company. Go into any Starbucks and just

570
00:27:44,760 --> 00:27:48,439
Speaker 3: sit there and watch people ordering. They're not ordering dripped coffees,

571
00:27:49,200 --> 00:27:52,080
Speaker 3: maybe once in a while a latte. People walk out

572
00:27:52,119 --> 00:27:55,520
Speaker 3: of there with huge milkshakes with whipped cream on top.

573
00:27:55,920 --> 00:27:59,960
Speaker 3: And yes, there's caffeine inside, but think about what machine produced,

574
00:28:00,119 --> 00:28:05,840
Speaker 3: what set of incentives produced that milkshake shop. It's like, well, okay,

575
00:28:05,840 --> 00:28:07,760
Speaker 3: if people like our coffee, but like, how can we

576
00:28:07,840 --> 00:28:11,119
Speaker 3: have them have coffee during the day, not the morning. Well,

577
00:28:11,560 --> 00:28:14,000
Speaker 3: let's blend up some ice with it, Let's add some sugar.

578
00:28:14,560 --> 00:28:16,960
Speaker 3: What do people like, Oh, okay, we'll do summer drinks.

579
00:28:16,960 --> 00:28:19,160
Speaker 3: And before you know it, like one of the most

580
00:28:19,160 --> 00:28:24,280
Speaker 3: original coffee companies in the world now like primarily sells milkshakes, right,

581
00:28:24,440 --> 00:28:26,760
Speaker 3: And if you think about it in terms of social media,

582
00:28:26,840 --> 00:28:29,320
Speaker 3: that's exactly what happens. You start off about being this

583
00:28:29,400 --> 00:28:32,720
Speaker 3: time square and ideas and everything, and then you say, oh, well,

584
00:28:32,760 --> 00:28:34,679
Speaker 3: actually what gets people to stay around and what you

585
00:28:34,800 --> 00:28:38,160
Speaker 3: end up with is like fight videos and car crashes

586
00:28:38,280 --> 00:28:40,840
Speaker 3: and silly animal dances like.

587
00:28:40,920 --> 00:28:43,840
Speaker 2: And dunking and not new. But I would argue though,

588
00:28:44,080 --> 00:28:47,200
Speaker 2: that news is important that people are still on Twitter

589
00:28:47,240 --> 00:28:49,800
Speaker 2: because news is there. It's the best place to get

590
00:28:49,800 --> 00:28:51,920
Speaker 2: the most up to minute news because the people on

591
00:28:52,000 --> 00:28:55,400
Speaker 2: it so there are you can move people towards quality

592
00:28:55,480 --> 00:28:58,760
Speaker 2: things very easily, even if you can sort of do

593
00:28:58,840 --> 00:29:00,600
Speaker 2: this with the jazz hands with the milkshake.

594
00:29:00,720 --> 00:29:02,840
Speaker 3: I think I just I want to be clear that

595
00:29:03,000 --> 00:29:05,600
Speaker 3: like I still love Starbucks, I still go there. It's

596
00:29:05,680 --> 00:29:09,880
Speaker 3: just you got to look at what incentives produce at

597
00:29:09,880 --> 00:29:11,800
Speaker 3: the end of the day in your business, what do

598
00:29:11,840 --> 00:29:15,400
Speaker 3: they produce, and if you chase profit, if you chase margin,

599
00:29:15,440 --> 00:29:18,719
Speaker 3: if you chase expansion, you will get to a point

600
00:29:18,800 --> 00:29:22,400
Speaker 3: where what you end up with are products that are

601
00:29:22,520 --> 00:29:25,959
Speaker 3: purely engineered for that rather than maybe the original mission.

602
00:29:26,280 --> 00:29:29,280
Speaker 2: But I think I'm curious Kevin with artifact explain what

603
00:29:29,280 --> 00:29:31,240
Speaker 2: it is for people who do know. And also you're

604
00:29:31,280 --> 00:29:34,760
Speaker 2: going in a much more vegetable direction. Really, you're going

605
00:29:34,800 --> 00:29:37,040
Speaker 2: for full vegetable or full news junkie.

606
00:29:37,120 --> 00:29:40,280
Speaker 3: Essentially, I'll challenge that we're going full vegetable, but I'll

607
00:29:40,320 --> 00:29:43,719
Speaker 3: get there first by explaining what it is. Artifact is

608
00:29:43,880 --> 00:29:48,680
Speaker 3: a fully machine learning driven personalized news reader. So the

609
00:29:48,760 --> 00:29:50,920
Speaker 3: idea is that you show up and we're going to

610
00:29:50,960 --> 00:29:52,960
Speaker 3: show you a bunch of things. Because you told us

611
00:29:53,000 --> 00:29:58,440
Speaker 3: you're interested in technology in NFL and cars, we're you're

612
00:29:58,440 --> 00:30:03,960
Speaker 3: interested in fashion, and you're from San Francisco, and we

613
00:30:04,040 --> 00:30:08,520
Speaker 3: will crawl the Internet, not the entire Internet, but what

614
00:30:08,560 --> 00:30:12,320
Speaker 3: we deem is the trustworthy Internet, and we'll bring all

615
00:30:12,320 --> 00:30:14,120
Speaker 3: that content together and then we'll serve it to you

616
00:30:14,160 --> 00:30:16,080
Speaker 3: in a feed, and depending on what you tap on

617
00:30:16,560 --> 00:30:19,520
Speaker 3: and what you engage with, we'll try to learn what

618
00:30:19,560 --> 00:30:22,240
Speaker 3: your actual interests are, and then we'll customize that feed

619
00:30:22,280 --> 00:30:25,239
Speaker 3: over time. So what's happened for me personally is when

620
00:30:25,320 --> 00:30:27,280
Speaker 3: it started, it was just a bunch of tech news,

621
00:30:27,560 --> 00:30:31,680
Speaker 3: and now it's a mix of Japanese architecture and travel recommendations,

622
00:30:32,440 --> 00:30:36,200
Speaker 3: parenting tips because I have two young kids, and local

623
00:30:36,240 --> 00:30:39,200
Speaker 3: San Francisco politics, and that's great for me. It's a

624
00:30:39,240 --> 00:30:42,120
Speaker 3: mix of wonderful publications that I never would have heard

625
00:30:42,160 --> 00:30:45,440
Speaker 3: of otherwise and helped me discover local publications like the

626
00:30:45,480 --> 00:30:50,320
Speaker 3: San Francisco Standard. Things like this bring content to you

627
00:30:50,880 --> 00:30:54,400
Speaker 3: rather than having you get served content because someone decided

628
00:30:54,440 --> 00:30:55,280
Speaker 3: to post about it.

629
00:30:55,480 --> 00:30:58,800
Speaker 1: Or searching for it across a million different platforms. But

630
00:30:58,880 --> 00:31:02,080
Speaker 1: Apple News does the same for me, Kevin, how's this different?

631
00:31:02,800 --> 00:31:04,480
Speaker 3: I'm going to say this and it's going to sound

632
00:31:04,480 --> 00:31:07,200
Speaker 3: like a non answer, but you have to see it

633
00:31:07,480 --> 00:31:11,520
Speaker 3: to know the difference. Like my pitch would be that

634
00:31:11,600 --> 00:31:19,040
Speaker 3: we focus on high quality, non trashy publications that aren't

635
00:31:19,240 --> 00:31:23,560
Speaker 3: so intellectual that they feel out of touch, but that

636
00:31:23,800 --> 00:31:26,160
Speaker 3: aren't like kind of one of the you know, content

637
00:31:26,240 --> 00:31:29,880
Speaker 3: mills that just show you more celebrity photos and that

638
00:31:30,000 --> 00:31:35,040
Speaker 3: it's like, thank you, someone finally built a news recommendation

639
00:31:35,160 --> 00:31:38,440
Speaker 3: service that understands me as someone who is and when

640
00:31:38,440 --> 00:31:41,480
Speaker 3: I say me, I mean someone who loves tech, who

641
00:31:41,520 --> 00:31:43,600
Speaker 3: loves things that are on the bleeding edge, wants to

642
00:31:43,680 --> 00:31:46,520
Speaker 3: learn about AI, maybe that have a budding interest in crypto,

643
00:31:47,160 --> 00:31:50,520
Speaker 3: like those types of things. It's like we go beyond

644
00:31:50,640 --> 00:31:54,960
Speaker 3: just the major publications too. We find interesting substacks we

645
00:31:55,040 --> 00:31:58,440
Speaker 3: find interesting recipe authors. So you're not going to find

646
00:31:58,480 --> 00:32:00,320
Speaker 3: that on a place like Apple News. You're not going

647
00:32:00,400 --> 00:32:02,400
Speaker 3: to find that on Google News. And that's okay because

648
00:32:02,400 --> 00:32:05,040
Speaker 3: they're focused on different things. But I think we go

649
00:32:05,240 --> 00:32:07,720
Speaker 3: a little bit more intellectual, and we go a little

650
00:32:07,760 --> 00:32:10,840
Speaker 3: deeper in terms of unique sources, and then on top

651
00:32:10,920 --> 00:32:13,840
Speaker 3: of that the competitive angle. I do believe our machine

652
00:32:13,880 --> 00:32:16,000
Speaker 3: learning is better than a bunch of these, so we

653
00:32:16,080 --> 00:32:18,880
Speaker 3: will personalize better for you, or at least that's our goal.

654
00:32:19,640 --> 00:32:20,680
Speaker 3: So that's how we're different.

655
00:32:21,160 --> 00:32:24,440
Speaker 1: You name four areas you're interested in, you know, you

656
00:32:24,480 --> 00:32:29,520
Speaker 1: said local San Francisco politics, parenting articles, Japanese architecture, and

657
00:32:29,800 --> 00:32:32,040
Speaker 1: I forget the fourth one. What was the fourth one, Kevin? I?

658
00:32:32,200 --> 00:32:33,560
Speaker 3: I remember, I don't either.

659
00:32:33,640 --> 00:32:36,560
Speaker 1: But what about like someone like me and care I

660
00:32:36,560 --> 00:32:40,040
Speaker 1: imagine you're like me. I'm interested in probably twenty five

661
00:32:40,120 --> 00:32:43,760
Speaker 1: different things. You know, I'm interest I'm a generalist. I

662
00:32:43,800 --> 00:32:48,480
Speaker 1: want to know what's happening from Megan and Harry to

663
00:32:48,480 --> 00:32:51,800
Speaker 1: Tom Friedman's latest column about the Middle East to what

664
00:32:51,960 --> 00:32:55,719
Speaker 1: Richard coss might have written in Foreign Affairs, to what

665
00:32:55,760 --> 00:32:59,800
Speaker 1: the economist is saying about Israel, to everything to how

666
00:32:59,840 --> 00:33:02,880
Speaker 1: it'll affect you. I mean, obviously I'm heavy on foreign

667
00:33:02,880 --> 00:33:06,160
Speaker 1: policy right now, given everything that's going on in the world,

668
00:33:06,240 --> 00:33:10,320
Speaker 1: But how can you serve me up over such a

669
00:33:10,360 --> 00:33:13,960
Speaker 1: broad area of interest things that I want to see

670
00:33:14,000 --> 00:33:15,920
Speaker 1: without completely overwhelming me.

671
00:33:16,880 --> 00:33:19,479
Speaker 3: They're a couple of ways. The first thing that I

672
00:33:19,520 --> 00:33:22,560
Speaker 3: think is really interesting to talk about here is you

673
00:33:22,720 --> 00:33:27,800
Speaker 3: just discussed revealed versus stated preferences. And if we ask

674
00:33:27,920 --> 00:33:29,760
Speaker 3: you to name all your preferences and we put a

675
00:33:29,760 --> 00:33:32,320
Speaker 3: piece of paper in front of you, For most people,

676
00:33:32,360 --> 00:33:36,040
Speaker 3: that's actually very, very difficult. It's very hard to say

677
00:33:36,120 --> 00:33:41,600
Speaker 3: all the things that you love without seeing them. But

678
00:33:42,120 --> 00:33:44,800
Speaker 3: if a system learned, and this is called exploration in

679
00:33:44,840 --> 00:33:49,840
Speaker 3: the machine learning verbiage, if you can explore potential topics

680
00:33:49,880 --> 00:33:52,440
Speaker 3: for someone and then just note Katie spend a bunch

681
00:33:52,480 --> 00:33:55,560
Speaker 3: of time on foreign affairs. She loves Thomas Friedman. Whenever

682
00:33:55,600 --> 00:33:58,440
Speaker 3: Thomas Freeman writes, she spends a bunch of time reading

683
00:33:58,440 --> 00:34:02,040
Speaker 3: this article. But she also loves like the latest Harry

684
00:34:02,040 --> 00:34:04,959
Speaker 3: and Meghan gossip. Those things are not mutually exclusive, but

685
00:34:05,000 --> 00:34:08,560
Speaker 3: they are on major publications. When you open up a

686
00:34:08,600 --> 00:34:12,120
Speaker 3: major publication, you have sections, you have the front page,

687
00:34:12,160 --> 00:34:14,880
Speaker 3: Harry and Meghan are not on the front page of

688
00:34:14,920 --> 00:34:17,400
Speaker 3: the New York Times or the Washington Post most of

689
00:34:17,440 --> 00:34:21,880
Speaker 3: the time probably ever, but for you, maybe they should be.

690
00:34:22,400 --> 00:34:25,399
Speaker 3: And that's really the dream here is that via exploration,

691
00:34:25,520 --> 00:34:28,200
Speaker 3: we can make that front page sing for you, that

692
00:34:28,280 --> 00:34:31,440
Speaker 3: it can feel like it was designed literally just for you.

693
00:34:31,680 --> 00:34:34,319
Speaker 2: Which has been an old goal of everybody. Yahoo. You

694
00:34:34,360 --> 00:34:38,680
Speaker 2: had personalization, Everyone's tried to sort of create this individualized

695
00:34:38,920 --> 00:34:42,200
Speaker 2: news feed for everyone. That's sort of been a long

696
00:34:42,280 --> 00:34:42,840
Speaker 2: time goal.

697
00:34:43,160 --> 00:34:45,680
Speaker 3: Yeah, and maybe what I could do quickly is just

698
00:34:45,719 --> 00:34:48,960
Speaker 3: talk about where we've expanded recently, because the scope of

699
00:34:49,000 --> 00:34:51,400
Speaker 3: the company has changed pretty significantly. And that's some of

700
00:34:51,440 --> 00:34:54,160
Speaker 3: what Karen was talking about when she said we're building

701
00:34:54,200 --> 00:34:57,280
Speaker 3: our own little Twitter. We've always believed that we wanted

702
00:34:57,320 --> 00:35:02,080
Speaker 3: to build this personalized homepage for you that other people

703
00:35:02,080 --> 00:35:04,400
Speaker 3: have tried and not done it very well. One of

704
00:35:04,400 --> 00:35:07,719
Speaker 3: the realizations through this, I believe is that it's not

705
00:35:07,760 --> 00:35:11,160
Speaker 3: that it's necessarily hard to do. It's that I'm not

706
00:35:11,200 --> 00:35:14,480
Speaker 3: sure people are that impressed, not necessarily with us, but

707
00:35:14,719 --> 00:35:18,200
Speaker 3: just they need more. They need more than articles. They

708
00:35:18,239 --> 00:35:22,359
Speaker 3: want spice, they want unique, interesting content, and where that

709
00:35:22,400 --> 00:35:26,600
Speaker 3: typically comes from is user generated content when people actually

710
00:35:26,640 --> 00:35:29,400
Speaker 3: post something that they're thinking that's unique that you can't

711
00:35:29,440 --> 00:35:32,759
Speaker 3: find anywhere else. So we added this thing, this tab

712
00:35:32,920 --> 00:35:36,520
Speaker 3: called links, which now will let you. It lets you

713
00:35:36,560 --> 00:35:39,680
Speaker 3: post links to things that you find interesting and say

714
00:35:39,680 --> 00:35:43,800
Speaker 3: something about them, which could be not from a major publication,

715
00:35:43,880 --> 00:35:45,560
Speaker 3: it could be a random blog that you found or

716
00:35:45,600 --> 00:35:48,280
Speaker 3: maybe your own blog. But it also lets you post

717
00:35:48,600 --> 00:35:50,919
Speaker 3: just on your own so if you want to write

718
00:35:50,920 --> 00:35:53,600
Speaker 3: four or five paragraphs about something, you can and post

719
00:35:53,640 --> 00:35:56,040
Speaker 3: into it. And this feed has been really fun to

720
00:35:56,080 --> 00:35:58,239
Speaker 3: watch take off in the last few weeks. It's really

721
00:35:58,320 --> 00:36:01,239
Speaker 3: added a different life to Artifacts. Now you can get

722
00:36:01,280 --> 00:36:03,279
Speaker 3: your news, which is fine, but you can get it

723
00:36:03,360 --> 00:36:06,280
Speaker 3: to other places. But now you have these really unique

724
00:36:06,320 --> 00:36:09,080
Speaker 3: posts and links that you can get basically only on

725
00:36:09,200 --> 00:36:12,080
Speaker 3: Artifact on this other tab. But it's all part of

726
00:36:12,120 --> 00:36:16,520
Speaker 3: discovering content using personalization. That's the dream here is that

727
00:36:16,560 --> 00:36:20,239
Speaker 3: we can create this market where producers and consumers can

728
00:36:20,239 --> 00:36:22,000
Speaker 3: get matched and their interests are matched.

729
00:36:22,200 --> 00:36:25,160
Speaker 2: So interest matching. There used to be a company called

730
00:36:25,280 --> 00:36:28,239
Speaker 2: six degrees. Do you remember them. Yeah, Amazon ended up

731
00:36:28,280 --> 00:36:31,520
Speaker 2: buying them, and the idea of putting interests together has

732
00:36:31,600 --> 00:36:34,720
Speaker 2: always been another dream. And what's happened is to generate

733
00:36:34,760 --> 00:36:38,480
Speaker 2: it into chaos, which is whatever is whatever bubbles up

734
00:36:38,520 --> 00:36:42,600
Speaker 2: in terms of enragement is what wins versus because it's

735
00:36:42,680 --> 00:36:45,840
Speaker 2: like a car traffic accident versus your interest. One of

736
00:36:45,840 --> 00:36:48,520
Speaker 2: the reasons TikTok is so successful. It does see your

737
00:36:48,560 --> 00:36:52,080
Speaker 2: interests and it knows what you like and you know more.

738
00:36:52,400 --> 00:36:55,560
Speaker 2: That's more media than social, right, And so the goal

739
00:36:55,640 --> 00:36:58,359
Speaker 2: is to be more media than social because social has

740
00:36:58,400 --> 00:37:00,879
Speaker 2: become so toxic in a lot of ways. And that's

741
00:37:00,920 --> 00:37:03,200
Speaker 2: what's difficult about these businesses.

742
00:37:05,160 --> 00:37:07,000
Speaker 1: When we come back, what in the world is coming

743
00:37:07,040 --> 00:37:10,480
Speaker 1: next for news and media online? Kevin and Kara have

744
00:37:10,560 --> 00:37:22,399
Speaker 1: some ideas and there's real reason to be optimistic. We're

745
00:37:22,440 --> 00:37:28,200
Speaker 1: back with Kara Swisher and Kevin's sistrom. How is business, Kevin?

746
00:37:28,280 --> 00:37:30,760
Speaker 1: I mean, are you doing well? How are you getting

747
00:37:30,800 --> 00:37:34,680
Speaker 1: people to download yet another app and want to kind

748
00:37:34,719 --> 00:37:36,520
Speaker 1: of change their habits.

749
00:37:37,080 --> 00:37:40,800
Speaker 3: I think what we've done is create a beautiful product

750
00:37:41,000 --> 00:37:44,520
Speaker 3: for some very passionate people, but nowhere near the amount

751
00:37:44,560 --> 00:37:48,200
Speaker 3: of people that use Instagram right, And the question is

752
00:37:48,880 --> 00:37:51,120
Speaker 3: how do you go from one to the other? Because

753
00:37:51,160 --> 00:37:53,440
Speaker 3: Instagram started off very small at the beginning. I mean,

754
00:37:53,440 --> 00:37:56,120
Speaker 3: everyone likes to think, oh, was this overnight success. And

755
00:37:56,600 --> 00:37:59,600
Speaker 3: don't get me wrong, the first day of Instagram we

756
00:37:59,600 --> 00:38:02,120
Speaker 3: had twenty five thousand people sign up and it was great,

757
00:38:02,360 --> 00:38:05,120
Speaker 3: and it continued to grow over time and it retained people.

758
00:38:05,680 --> 00:38:08,320
Speaker 3: The question is not can you get attention? The question

759
00:38:08,440 --> 00:38:11,879
Speaker 3: is can you retain people with a product that they love?

760
00:38:12,440 --> 00:38:15,280
Speaker 3: And we have a group of people that love this product,

761
00:38:15,640 --> 00:38:19,200
Speaker 3: and our main challenge is can we be mainstream? And

762
00:38:19,280 --> 00:38:23,720
Speaker 3: where's the white space? Where can people succeed? Because I mean, Carot,

763
00:38:23,760 --> 00:38:27,359
Speaker 3: what's the last successful consumer startup you have seen? I'm

764
00:38:27,360 --> 00:38:28,440
Speaker 3: curious here.

765
00:38:28,440 --> 00:38:31,719
Speaker 2: It hasn't been in a long time, right, Oh, not

766
00:38:31,800 --> 00:38:34,240
Speaker 2: by a big company. It's been a long time. Someone's

767
00:38:34,280 --> 00:38:37,359
Speaker 2: broken through, Right, it's been a long time. I can't

768
00:38:37,360 --> 00:38:39,360
Speaker 2: think of one. You're very good. And also it also

769
00:38:39,440 --> 00:38:41,759
Speaker 2: has the law of big numbers. Is that you know

770
00:38:41,800 --> 00:38:43,960
Speaker 2: this is something Ben Horowitz of all people said to me.

771
00:38:44,040 --> 00:38:46,080
Speaker 2: He's like, no one's going to create a search engine.

772
00:38:46,320 --> 00:38:49,399
Speaker 2: No one's going to create a consumer commerce company because

773
00:38:49,400 --> 00:38:52,319
Speaker 2: of Amazon search engine, because of Google. No one's going

774
00:38:52,360 --> 00:38:55,920
Speaker 2: to create all these various things because of the large players.

775
00:38:55,960 --> 00:38:57,879
Speaker 2: And that's the real problem is how do you even

776
00:38:57,920 --> 00:39:02,040
Speaker 2: break through. Now. The one example is I gotta say TikTok, right,

777
00:39:02,440 --> 00:39:03,360
Speaker 2: came out of nowhere.

778
00:39:03,560 --> 00:39:06,640
Speaker 3: I actually I'll challenge I'll change, which is I think

779
00:39:06,680 --> 00:39:09,200
Speaker 3: it's very easy as someone who maybe I was twenty

780
00:39:09,200 --> 00:39:11,880
Speaker 3: five at the time something like that Instagram started, it's

781
00:39:11,960 --> 00:39:15,960
Speaker 3: very easy to be optimistic and green and just believe

782
00:39:16,000 --> 00:39:18,960
Speaker 3: there's all this opportunity and I and then it's very easy.

783
00:39:19,000 --> 00:39:21,040
Speaker 3: Now on the other side, I'm about to turn forty,

784
00:39:21,640 --> 00:39:24,600
Speaker 3: I'm thirty nine right now to believe that there's no

785
00:39:24,719 --> 00:39:28,560
Speaker 3: opportunity or believe that maybe some doors have closed along

786
00:39:28,560 --> 00:39:31,320
Speaker 3: the way. But here's the wonderful thing about the Internet

787
00:39:31,360 --> 00:39:34,600
Speaker 3: that it surprises everyone. I mean, when we found it Instagram,

788
00:39:34,640 --> 00:39:36,880
Speaker 3: could you imagine that anyone would be able to have

789
00:39:36,920 --> 00:39:41,520
Speaker 3: found an image sharing social network to compete with Instagram?

790
00:39:41,560 --> 00:39:44,880
Speaker 3: And then snap came along, and then after stap do

791
00:39:44,920 --> 00:39:48,560
Speaker 3: you believe could you believe anyone could compete with YouTube

792
00:39:48,600 --> 00:39:52,799
Speaker 3: Instagram and snap in video and by the way, not

793
00:39:52,920 --> 00:39:56,840
Speaker 3: even a US company like this is incredible, Like, of course,

794
00:39:56,960 --> 00:39:59,319
Speaker 3: there are always opportunities. So would you have to do

795
00:39:59,360 --> 00:40:02,560
Speaker 3: I think in these situations is fite the urge to

796
00:40:02,600 --> 00:40:05,440
Speaker 3: believe that all the doors have closed and instead look

797
00:40:05,480 --> 00:40:08,560
Speaker 3: out and say, what are the opportunities that have changed

798
00:40:08,600 --> 00:40:13,520
Speaker 3: because of some fundamental technology change, like, for instance, generative AI.

799
00:40:13,960 --> 00:40:16,160
Speaker 2: Oh, that's full of ideas because there's going to be

800
00:40:16,200 --> 00:40:19,400
Speaker 2: general AI for insurance, for healthcare, all kinds of areas,

801
00:40:19,440 --> 00:40:21,360
Speaker 2: so you can It reminds me a little bit of

802
00:40:21,360 --> 00:40:24,640
Speaker 2: when the mobile phone came right that you couldn't have

803
00:40:24,680 --> 00:40:27,880
Speaker 2: imagined Instagram before the mobile phone could do easily.

804
00:40:28,440 --> 00:40:31,759
Speaker 3: Now most people when they see companies start thinking, oh,

805
00:40:31,800 --> 00:40:32,800
Speaker 3: that idea is too small.

806
00:40:32,880 --> 00:40:33,439
Speaker 2: Yeah, it's true.

807
00:40:33,480 --> 00:40:35,920
Speaker 3: And the question isn't is the idea too small at

808
00:40:35,960 --> 00:40:38,000
Speaker 3: the beginning, it's what is the ambition of the person

809
00:40:38,000 --> 00:40:40,680
Speaker 3: who's running it and what direction are they headed? Because

810
00:40:40,680 --> 00:40:42,759
Speaker 3: if you can map out that mark is going to

811
00:40:42,800 --> 00:40:45,680
Speaker 3: take it from Harvard to other Ivy League schools, to

812
00:40:45,760 --> 00:40:48,520
Speaker 3: every school, to every other college, to high schools, et cetera,

813
00:40:48,880 --> 00:40:51,680
Speaker 3: and then take over the world. Like then you say, okay,

814
00:40:51,719 --> 00:40:53,080
Speaker 3: this is interesting.

815
00:40:53,120 --> 00:40:53,839
Speaker 2: But I don't know.

816
00:40:54,080 --> 00:40:55,879
Speaker 3: There are a lot of companies that get started and

817
00:40:55,960 --> 00:40:59,120
Speaker 3: stay very happy with very small audiences. So it's not

818
00:40:59,200 --> 00:41:00,880
Speaker 3: about the idea, it's about the direction.

819
00:41:01,440 --> 00:41:03,800
Speaker 1: I want to just spend a couple of minutes talking

820
00:41:03,840 --> 00:41:07,279
Speaker 1: about the media landscape and the state of news, which

821
00:41:07,320 --> 00:41:10,799
Speaker 1: is what prompted you to create Artifact, Kevin in the

822
00:41:10,840 --> 00:41:14,480
Speaker 1: first place. And I'd love to get your take on

823
00:41:15,200 --> 00:41:19,279
Speaker 1: what is happening on Twitter now or X and what

824
00:41:19,360 --> 00:41:24,239
Speaker 1: Elon Musk has done to turn it into such a cesspool. Obviously,

825
00:41:24,400 --> 00:41:27,880
Speaker 1: people can buy blue checks, so nobody is really verified.

826
00:41:28,280 --> 00:41:33,160
Speaker 1: The ad model has changed, there's ai I think that's

827
00:41:33,200 --> 00:41:36,759
Speaker 1: creating a lot of dis and misinformation. But I'd love

828
00:41:36,800 --> 00:41:40,319
Speaker 1: to ask you, Kara, what has X becommon Why?

829
00:41:41,560 --> 00:41:44,120
Speaker 2: Well, it's interesting because it's still a little necessary because

830
00:41:44,120 --> 00:41:46,600
Speaker 2: it's so everyone's there and it's frantic, you know what

831
00:41:46,640 --> 00:41:48,279
Speaker 2: I mean. And so if they're like, if there's I

832
00:41:48,320 --> 00:41:49,120
Speaker 2: still go on it?

833
00:41:49,160 --> 00:41:49,400
Speaker 1: I do.

834
00:41:49,680 --> 00:41:52,600
Speaker 2: Sure, it's useful. It's because everybody's there, everybody, But it's

835
00:41:52,640 --> 00:41:54,920
Speaker 2: sort of like one of those clubs or a place

836
00:41:55,000 --> 00:41:57,239
Speaker 2: a downtown that you know you still have to kind

837
00:41:57,239 --> 00:41:59,880
Speaker 2: of go to. But it sucks now. It's like it's dirtier,

838
00:42:00,480 --> 00:42:02,280
Speaker 2: there's really weird people hanging around.

839
00:42:02,440 --> 00:42:04,480
Speaker 3: No one says that about San Francisco. I'm not sure

840
00:42:04,480 --> 00:42:05,239
Speaker 3: what you're talking about.

841
00:42:05,239 --> 00:42:07,680
Speaker 2: No, no, no, no, no. I love Sirence. Don't insult

842
00:42:07,680 --> 00:42:10,799
Speaker 2: San Francisco to Karas for sure. So I find it

843
00:42:10,880 --> 00:42:14,040
Speaker 2: really hard to use. I have to turn off comments

844
00:42:14,080 --> 00:42:17,520
Speaker 2: now because of the really the flood of really crazy people.

845
00:42:17,719 --> 00:42:20,160
Speaker 2: And I'm joking about Elon must but he also you know,

846
00:42:20,920 --> 00:42:24,640
Speaker 2: it's really unpleasant, and so it's become an unpleasant experience.

847
00:42:25,200 --> 00:42:27,160
Speaker 2: But you put up with it because of the benefits

848
00:42:27,200 --> 00:42:29,560
Speaker 2: of getting instant, like there's no other place to go

849
00:42:29,640 --> 00:42:31,320
Speaker 2: right now to watch the vote happening.

850
00:42:31,480 --> 00:42:34,680
Speaker 1: And didn't he fire everybody who was kind of evaluating

851
00:42:34,760 --> 00:42:37,040
Speaker 1: content and flagging content.

852
00:42:36,719 --> 00:42:39,600
Speaker 2: A lot a lot, Well, they say, not everybody.

853
00:42:39,800 --> 00:42:42,600
Speaker 1: And then I keep getting these ads what doctors don't

854
00:42:42,640 --> 00:42:44,959
Speaker 1: want you to do to your coffee? Like why why

855
00:42:45,000 --> 00:42:47,839
Speaker 1: do they keep why do they keep feeding me that ad?

856
00:42:47,920 --> 00:42:50,799
Speaker 2: Because they're paying because the check is cashing. I don't know.

857
00:42:50,840 --> 00:42:52,880
Speaker 2: I think it's really I think it could go for

858
00:42:52,920 --> 00:42:55,160
Speaker 2: a while. These things can go for a while. Kevin

859
00:42:55,200 --> 00:42:57,600
Speaker 2: knows that these things can hold on for and he's

860
00:42:57,600 --> 00:43:00,000
Speaker 2: the richest man in the world, so he can afford.

861
00:43:00,160 --> 00:43:02,719
Speaker 2: It's like having a one of these Megga yachts that's

862
00:43:02,719 --> 00:43:04,759
Speaker 2: seeping oil out of it. He can keep doing it

863
00:43:04,800 --> 00:43:06,920
Speaker 2: and paying the fines for it. For a long time.

864
00:43:07,520 --> 00:43:10,719
Speaker 1: What was frustrating to you, Kevin about the news environment

865
00:43:11,160 --> 00:43:14,000
Speaker 1: and how did you say, Oh, I need to fix

866
00:43:14,040 --> 00:43:16,120
Speaker 1: this or I need to fill a hole that's missing.

867
00:43:16,600 --> 00:43:19,000
Speaker 3: I want to be clear that I think Artifact is

868
00:43:19,080 --> 00:43:21,319
Speaker 3: much more than just news. Like, of course we're in

869
00:43:21,360 --> 00:43:23,640
Speaker 3: the news category in the app store, and that's the

870
00:43:23,680 --> 00:43:25,960
Speaker 3: easiest way to talk about what we are. But I

871
00:43:25,960 --> 00:43:30,200
Speaker 3: think by frustration actually is that people only think about news.

872
00:43:30,239 --> 00:43:32,759
Speaker 3: When you talk about news, they don't think about all

873
00:43:32,760 --> 00:43:35,759
Speaker 3: the amazing content out there that has nothing to do

874
00:43:35,840 --> 00:43:36,960
Speaker 3: with the day as headlines.

875
00:43:37,360 --> 00:43:39,400
Speaker 1: We should probably call it a content app.

876
00:43:39,719 --> 00:43:45,080
Speaker 3: Really, Yeah, that's right, And I think people are thirsty

877
00:43:45,200 --> 00:43:48,279
Speaker 3: for that type of information because they don't want yet

878
00:43:48,280 --> 00:43:51,640
Speaker 3: another if it bleeds, it leads story. What they want

879
00:43:51,719 --> 00:43:55,560
Speaker 3: is some value in their life, a discovery. Like there's

880
00:43:55,600 --> 00:43:59,319
Speaker 3: this guy who just documented his trip throughout Japan in

881
00:43:59,360 --> 00:44:02,799
Speaker 3: a photo assay and I found it on Artifact and

882
00:44:02,840 --> 00:44:05,399
Speaker 3: it was this moment where I've been to Japan only

883
00:44:05,400 --> 00:44:07,520
Speaker 3: a few times. It's one of my favorite places on Earth.

884
00:44:07,840 --> 00:44:10,000
Speaker 3: But I scrolled through and I was just like, Okay,

885
00:44:10,000 --> 00:44:14,440
Speaker 3: I'm taken back and I'm not reading about some awful

886
00:44:14,480 --> 00:44:17,520
Speaker 3: thing that happened in downtown San Francisco today because I

887
00:44:17,520 --> 00:44:21,360
Speaker 3: can get that elsewhere. That's the opportunity is not necessarily

888
00:44:21,400 --> 00:44:24,920
Speaker 3: the news industry, but rather what are people reading, what

889
00:44:25,000 --> 00:44:28,080
Speaker 3: are people being served and why? And if you focus

890
00:44:28,120 --> 00:44:32,640
Speaker 3: on these platforms that focus on the most insane stories

891
00:44:32,680 --> 00:44:35,719
Speaker 3: being pushed to you, you're just going to get that

892
00:44:35,800 --> 00:44:37,719
Speaker 3: type of content I said I wanted to avoid. So

893
00:44:37,760 --> 00:44:41,160
Speaker 3: the real opportunity here is and you learn someone's interests

894
00:44:41,160 --> 00:44:43,839
Speaker 3: and can you delight them with content that doesn't make

895
00:44:43,880 --> 00:44:46,040
Speaker 3: them want to shut the app and anger every single day.

896
00:44:46,520 --> 00:44:49,480
Speaker 2: I think the word delight you're using is absolutely the case.

897
00:44:49,520 --> 00:44:51,520
Speaker 2: I mean, that's why I do have a good feeling

898
00:44:51,520 --> 00:44:54,080
Speaker 2: about threads. I find it delightful sometimes. I was laughing

899
00:44:54,120 --> 00:44:57,160
Speaker 2: at it the other day. They have some astronomy person

900
00:44:57,440 --> 00:44:59,759
Speaker 2: right on there, and I'm not interested in astronomy, but

901
00:44:59,760 --> 00:45:01,719
Speaker 2: I and I don't know why. Or they had a

902
00:45:01,800 --> 00:45:04,040
Speaker 2: video that made me laugh, or cat videos or whatever.

903
00:45:04,280 --> 00:45:07,280
Speaker 2: And on artifact just now stuff I wouldn't have found,

904
00:45:07,320 --> 00:45:10,239
Speaker 2: Like there's a piece that someone else discovered that then

905
00:45:10,400 --> 00:45:12,920
Speaker 2: showed me, which was when was the last time Mark

906
00:45:12,960 --> 00:45:15,120
Speaker 2: injuries and talked to a poor person. It made me laugh.

907
00:45:15,320 --> 00:45:18,440
Speaker 2: I was like, probably never, you know, since he was

908
00:45:18,440 --> 00:45:20,759
Speaker 2: a kid, essentially when he was poor, and that's the

909
00:45:20,840 --> 00:45:22,480
Speaker 2: kind of thing you need. I think there's a real

910
00:45:22,680 --> 00:45:26,000
Speaker 2: if there's a trend, Kevin, maybe you could answers there's

911
00:45:26,000 --> 00:45:29,160
Speaker 2: a trend toward getting sick of crap, like everyone is

912
00:45:29,280 --> 00:45:32,120
Speaker 2: sick of crap. And I do think there is a

913
00:45:32,200 --> 00:45:34,320
Speaker 2: trend towards And I think it's the same with voters.

914
00:45:34,520 --> 00:45:38,000
Speaker 2: They don't want to hear anymore from screaming people, screaming

915
00:45:38,040 --> 00:45:40,719
Speaker 2: angry people. They want to hear about things they like

916
00:45:40,800 --> 00:45:43,720
Speaker 2: about their family. And I think that's kind of a secret,

917
00:45:43,800 --> 00:45:48,000
Speaker 2: silent majority of people being delighted by things or discovering

918
00:45:48,040 --> 00:45:50,080
Speaker 2: things that are of interest in them, even if they're

919
00:45:50,200 --> 00:45:51,560
Speaker 2: hard stories or whatever.

920
00:45:52,000 --> 00:45:53,880
Speaker 1: But do you think they want to hear things that

921
00:45:53,920 --> 00:45:58,120
Speaker 1: are not so partisan too, I mean anything, You know,

922
00:45:58,680 --> 00:46:03,440
Speaker 1: I'm desperate to actually have someone explained to me what

923
00:46:03,600 --> 00:46:08,600
Speaker 1: is going on with this committee that's investigating Joe Biden

924
00:46:08,719 --> 00:46:13,160
Speaker 1: and claiming that his family has made ten million dollars

925
00:46:13,200 --> 00:46:15,880
Speaker 1: in you know, it's on some right wing news site

926
00:46:15,920 --> 00:46:18,520
Speaker 1: that I actually get their newsletter because I want to

927
00:46:18,560 --> 00:46:21,640
Speaker 1: hear what they're saying. But I sent it to a

928
00:46:21,680 --> 00:46:24,480
Speaker 1: friend and I said, I'm so confused. Is any of

929
00:46:24,520 --> 00:46:26,560
Speaker 1: this actually true? Right?

930
00:46:26,800 --> 00:46:27,200
Speaker 2: Yeah?

931
00:46:27,239 --> 00:46:31,200
Speaker 3: I think verifying information is really hard today. You never

932
00:46:31,360 --> 00:46:35,399
Speaker 3: know who to trust, even with large publications. You don't

933
00:46:35,400 --> 00:46:38,920
Speaker 3: know if there's some ulterior motive or partisan angle. And

934
00:46:38,960 --> 00:46:41,000
Speaker 3: I think one of the reasons why I'm excited about

935
00:46:41,120 --> 00:46:44,799
Speaker 3: artifacts and the algorithmic approach is there's all these new

936
00:46:44,840 --> 00:46:49,560
Speaker 3: advancements in balancing perspectives. So there's this thing called bridging algorithms.

937
00:46:49,840 --> 00:46:52,240
Speaker 3: The idea is like you can kind of lump people

938
00:46:52,280 --> 00:46:56,000
Speaker 3: based on their history of reading into you know, right

939
00:46:56,120 --> 00:46:59,040
Speaker 3: or left politically, and what you can do is look

940
00:46:59,040 --> 00:47:02,960
Speaker 3: for articles that actually resonate with both rather than just

941
00:47:03,160 --> 00:47:07,240
Speaker 3: deepen the divide. And this is well studied. It's actually

942
00:47:07,360 --> 00:47:10,879
Speaker 3: used on Twitter today on acts ironically Kara for their

943
00:47:10,880 --> 00:47:14,360
Speaker 3: community notes product. That's how they decide which community notes

944
00:47:14,400 --> 00:47:17,360
Speaker 3: actually get shown, because otherwise you have people on the

945
00:47:17,440 --> 00:47:20,760
Speaker 3: right doing community notes, correcting the lefties and the lefties

946
00:47:20,760 --> 00:47:23,600
Speaker 3: correcting the righting right. So like, the way it can

947
00:47:23,640 --> 00:47:28,120
Speaker 3: be applied in mass to news and information is by

948
00:47:28,239 --> 00:47:31,520
Speaker 3: noticing that certain things have a bias not in terms

949
00:47:31,600 --> 00:47:35,120
Speaker 3: of content, but who they resonate with yeah, and then

950
00:47:35,200 --> 00:47:38,440
Speaker 3: finding content that brings people together. We're far too small

951
00:47:38,480 --> 00:47:40,440
Speaker 3: and early right now for a lot of this to

952
00:47:40,480 --> 00:47:41,040
Speaker 3: make sense.

953
00:47:41,320 --> 00:47:44,200
Speaker 1: Is anybody doing that, Kevin, I haven't heard of anyone

954
00:47:44,200 --> 00:47:45,680
Speaker 1: else even considering it.

955
00:47:46,040 --> 00:47:46,799
Speaker 2: Yeah, it's hard.

956
00:47:46,960 --> 00:47:49,760
Speaker 3: Well, what's funny, care is it's actually not hard, meaning

957
00:47:49,800 --> 00:47:53,120
Speaker 3: technically it's not hard. What's hard is to make the

958
00:47:53,239 --> 00:47:56,600
Speaker 3: choice to do it. Because you are seen as somehow

959
00:47:57,120 --> 00:48:01,600
Speaker 3: trying to push liberal content to conservatives or conservative content liberals.

960
00:48:02,200 --> 00:48:05,040
Speaker 3: You violate one of the groups. And I think that's

961
00:48:05,120 --> 00:48:07,399
Speaker 3: very hard when you're very large and you know you're

962
00:48:07,400 --> 00:48:10,960
Speaker 3: trying to balance whatever party is in power with legislation

963
00:48:11,040 --> 00:48:14,279
Speaker 3: against your company and investigations and so it becomes a

964
00:48:14,400 --> 00:48:18,120
Speaker 3: very difficult place to be as a large company, but

965
00:48:18,239 --> 00:48:20,879
Speaker 3: not a difficult place if you're a smaller you're trying

966
00:48:20,880 --> 00:48:21,200
Speaker 3: to grow.

967
00:48:21,360 --> 00:48:25,640
Speaker 1: It's anesthetical though, to what Kara often calls engagement through enragement,

968
00:48:25,800 --> 00:48:28,800
Speaker 1: you know, like, if you want people you want to

969
00:48:28,840 --> 00:48:31,799
Speaker 1: feed the dogs the dog food and you want affirmation

970
00:48:31,960 --> 00:48:37,040
Speaker 1: instead of information, challenging people's worldview to me would work

971
00:48:37,120 --> 00:48:40,600
Speaker 1: against the whole visceral connection. You have to content that

972
00:48:40,680 --> 00:48:42,880
Speaker 1: makes you stay on the platform, right.

973
00:48:43,200 --> 00:48:46,120
Speaker 3: Well, in this case, I'm explaining something slightly different, which

974
00:48:46,200 --> 00:48:49,680
Speaker 3: is you're looking for content that resonates with both sides,

975
00:48:50,640 --> 00:48:54,360
Speaker 3: so it actually drives engagement on both sides because people

976
00:48:54,840 --> 00:48:56,680
Speaker 3: see some common thread in it.

977
00:48:56,680 --> 00:48:57,680
Speaker 2: It's commonality.

978
00:48:57,960 --> 00:48:59,080
Speaker 1: Yeah, that's right.

979
00:48:59,239 --> 00:49:01,759
Speaker 2: Years ago a Well started. That's how it started. And

980
00:49:02,080 --> 00:49:04,360
Speaker 2: the first thing I ever noticed it was when he

981
00:49:04,440 --> 00:49:07,880
Speaker 2: had a group of quilters who had met on AOL

982
00:49:08,000 --> 00:49:10,640
Speaker 2: and they had made a quilt of an AOL symbol

983
00:49:11,120 --> 00:49:13,400
Speaker 2: and they finally met in person and met him, and

984
00:49:13,440 --> 00:49:15,680
Speaker 2: they felt like they knew him. And it was so

985
00:49:15,880 --> 00:49:18,719
Speaker 2: positive because these were people so different from each other

986
00:49:19,120 --> 00:49:21,880
Speaker 2: that just liked to quilt and they managed to create

987
00:49:21,920 --> 00:49:24,759
Speaker 2: it online. And I remember thinking this could be used

988
00:49:24,800 --> 00:49:26,840
Speaker 2: for such good things, and it could be used for

989
00:49:26,960 --> 00:49:30,440
Speaker 2: such bad things, like I could see the opposite people

990
00:49:30,440 --> 00:49:32,759
Speaker 2: that like to make bombs and blow up people they.

991
00:49:32,640 --> 00:49:34,760
Speaker 1: Don't like, or white supremacists.

992
00:49:34,920 --> 00:49:37,719
Speaker 2: Yeah, yoh no it listen. AOL was good for white

993
00:49:37,760 --> 00:49:42,239
Speaker 2: supremacists early on too, So connection is what you're talking about.

994
00:49:42,480 --> 00:49:45,759
Speaker 1: Well, I'm excited to check out artifact and use it.

995
00:49:45,760 --> 00:49:46,160
Speaker 2: It's great.

996
00:49:46,239 --> 00:49:49,319
Speaker 1: I downloaded it. Appreciate that, Kevin, Thank you so much

997
00:49:49,360 --> 00:49:51,400
Speaker 1: for doing this. It was really fun to talk to you.

998
00:49:51,440 --> 00:49:54,160
Speaker 1: Good luck with your latest venture, Tevin.

999
00:49:54,320 --> 00:49:56,759
Speaker 2: I'll call you. I'll be in San Francisco soon. We'll

1000
00:49:56,760 --> 00:49:58,960
Speaker 2: walk around the Hellsgate, which is not a hellscape.

1001
00:49:58,960 --> 00:50:07,239
Speaker 3: Okay, no, actually quite nice.

1002
00:50:08,000 --> 00:50:10,400
Speaker 1: I feel like you two speak a whole different language

1003
00:50:10,440 --> 00:50:13,480
Speaker 1: than me. But I think I was able to keep them.

1004
00:50:13,520 --> 00:50:16,400
Speaker 1: You kept too, You kept up. Yeah, he's a nice guy,

1005
00:50:16,440 --> 00:50:18,440
Speaker 1: isn't he? What do you think quality guy? Do you

1006
00:50:18,480 --> 00:50:20,719
Speaker 1: think artifact is going to be successful? Kiara?

1007
00:50:20,960 --> 00:50:23,439
Speaker 2: I think it's hard, Like it's just hard because people

1008
00:50:23,480 --> 00:50:26,799
Speaker 2: are attracted by terrible things, right, that's the problem. We've

1009
00:50:26,840 --> 00:50:29,839
Speaker 2: been trained in this. The internet went a certain way.

1010
00:50:30,080 --> 00:50:32,359
Speaker 2: It's not a good way. But I do believe when

1011
00:50:32,360 --> 00:50:35,440
Speaker 2: I use that or threads now, I'm very happy and

1012
00:50:35,480 --> 00:50:38,000
Speaker 2: I like it. And so maybe that maybe you can

1013
00:50:38,080 --> 00:50:40,040
Speaker 2: change your habits, your bad habits.

1014
00:50:40,080 --> 00:50:42,040
Speaker 1: I guess what do you think is going to happen

1015
00:50:42,120 --> 00:50:44,080
Speaker 1: to the news business. I don't want to start this

1016
00:50:44,120 --> 00:50:48,200
Speaker 1: whole conversation, but it is a long one. But but

1017
00:50:48,600 --> 00:50:50,359
Speaker 1: how do you think it's going to shake out? Carara?

1018
00:50:50,440 --> 00:50:54,840
Speaker 1: I mean, it's just in a really difficult state.

1019
00:50:55,320 --> 00:50:57,600
Speaker 2: I think it'll be just fine. You do, I think

1020
00:50:57,640 --> 00:51:00,000
Speaker 2: there are new economic models that everybody has to get

1021
00:51:00,080 --> 00:51:03,520
Speaker 2: adjusted to, whether especially in Hollywood for example, around streaming

1022
00:51:03,760 --> 00:51:05,880
Speaker 2: and cable news. But you know, I just did an

1023
00:51:05,920 --> 00:51:07,920
Speaker 2: interview with Perry Diller, and I think he's right. These

1024
00:51:07,960 --> 00:51:13,239
Speaker 2: are worldwide distribution networks of information. Still, you know, television

1025
00:51:13,320 --> 00:51:15,920
Speaker 2: is everywhere, and so the question is how do you

1026
00:51:15,960 --> 00:51:19,920
Speaker 2: get people to engage in the content itself? And maybe

1027
00:51:19,960 --> 00:51:23,319
Speaker 2: we have to stop thinking less about how than the

1028
00:51:23,360 --> 00:51:25,960
Speaker 2: content itself. And I'll give you one example, which I've

1029
00:51:26,000 --> 00:51:27,840
Speaker 2: told this story before, but I was just in a

1030
00:51:27,840 --> 00:51:31,359
Speaker 2: frontline documentary about Twitter, and I had participated in their

1031
00:51:31,360 --> 00:51:33,319
Speaker 2: previous one when I think they do great work. And

1032
00:51:33,360 --> 00:51:35,719
Speaker 2: so I was doing it and my phone rang and

1033
00:51:35,760 --> 00:51:37,799
Speaker 2: my son called and he said, what are you doing, mom?

1034
00:51:37,800 --> 00:51:39,719
Speaker 2: I said, I'm doing a frontline interview and he goes,

1035
00:51:39,760 --> 00:51:42,360
Speaker 2: I love Frontline and I said really, And then he

1036
00:51:42,440 --> 00:51:45,239
Speaker 2: started talking about all the frontlines he watches. I don't

1037
00:51:45,239 --> 00:51:47,239
Speaker 2: watch it as much as he does, and I put

1038
00:51:47,280 --> 00:51:49,120
Speaker 2: on the speaker because these people are like, look, it's

1039
00:51:49,120 --> 00:51:51,160
Speaker 2: a twenty one year old loves frontline. Look at this.

1040
00:51:51,719 --> 00:51:54,279
Speaker 2: And I said to him, I didn't know you watched PBS.

1041
00:51:54,280 --> 00:51:56,319
Speaker 2: And he said, I don't watch PBS. Why would I

1042
00:51:56,320 --> 00:51:59,719
Speaker 2: watch PBS. I see it on YouTube. Well that's a

1043
00:51:59,719 --> 00:52:02,680
Speaker 2: win as far as I'm concerned, if we become adaptable

1044
00:52:03,040 --> 00:52:05,719
Speaker 2: to where people are. People are giving up cable for

1045
00:52:06,000 --> 00:52:09,000
Speaker 2: YouTube TV, and so that's where I'm work like, people

1046
00:52:09,120 --> 00:52:13,600
Speaker 2: are not listening, they're not watching. It's just it's just changed.

1047
00:52:13,640 --> 00:52:16,200
Speaker 2: And then the economics have changed, and that's the problem.

1048
00:52:16,400 --> 00:52:17,360
Speaker 2: That's what's happened.

1049
00:52:17,440 --> 00:52:19,760
Speaker 1: And I think if you build quality, they will come,

1050
00:52:20,000 --> 00:52:22,440
Speaker 1: you know, I do think, yes, I do. I mean,

1051
00:52:22,480 --> 00:52:25,320
Speaker 1: and they might be in smaller numbers because I always

1052
00:52:25,360 --> 00:52:27,360
Speaker 1: say mass media is and oxymoron.

1053
00:52:27,440 --> 00:52:29,480
Speaker 2: Now I think we started with you going to Yahoo.

1054
00:52:29,480 --> 00:52:31,759
Speaker 2: You're a testimony to this, right, you have much more

1055
00:52:31,800 --> 00:52:32,960
Speaker 2: control over your content.

1056
00:52:33,200 --> 00:52:36,160
Speaker 1: Well, we have a whole different financial model where we

1057
00:52:36,239 --> 00:52:40,279
Speaker 1: work with companies and tell stories often in conjunction with them,

1058
00:52:40,320 --> 00:52:44,400
Speaker 1: because as trust in media and other institutions has declined,

1059
00:52:44,760 --> 00:52:48,319
Speaker 1: trusting companies has increased and employees are demanding it. So

1060
00:52:48,760 --> 00:52:52,239
Speaker 1: we actually our revenue model is to work with companies

1061
00:52:52,719 --> 00:52:56,760
Speaker 1: for you know, for year long or multiple year sponsorships

1062
00:52:56,800 --> 00:52:59,680
Speaker 1: and partnerships. Really in good storytelling.

1063
00:53:00,080 --> 00:53:02,680
Speaker 2: Yeah, but I'm saying you're making as much money. It

1064
00:53:02,719 --> 00:53:05,760
Speaker 2: may not be the big organizations that are right. Maybe

1065
00:53:05,800 --> 00:53:07,319
Speaker 2: that's what it is. There'll be a whole bunch of

1066
00:53:07,520 --> 00:53:11,719
Speaker 2: media entrepreneurs like yourself, Like myself, I'm doing great. I

1067
00:53:11,840 --> 00:53:14,680
Speaker 2: just am not attached to a big, giant ocean liners all.

1068
00:53:14,680 --> 00:53:16,239
Speaker 2: I just have a little, speedy, little boat and it

1069
00:53:16,280 --> 00:53:16,959
Speaker 2: does really well.

1070
00:53:17,120 --> 00:53:20,080
Speaker 1: And you love that and you love not being beholden

1071
00:53:20,239 --> 00:53:24,680
Speaker 1: to these big corporations. Yeah, because nobody tells Kara Swish

1072
00:53:24,760 --> 00:53:25,319
Speaker 1: or what to do.

1073
00:53:25,600 --> 00:53:27,319
Speaker 2: Nobody tells Katie Kirk what to do.

1074
00:53:27,400 --> 00:53:28,920
Speaker 1: Is it very awesome though, Kia.

1075
00:53:29,200 --> 00:53:31,759
Speaker 2: Yes, we're always like this or not. This is the

1076
00:53:31,800 --> 00:53:33,319
Speaker 2: way we are, and I think it does appeal to

1077
00:53:33,360 --> 00:53:37,239
Speaker 2: our entrepreneurial natures. And I think any journalist is not entrepreneurial.

1078
00:53:37,280 --> 00:53:39,120
Speaker 2: It's going to have a harder time going forward. That's

1079
00:53:39,160 --> 00:53:42,600
Speaker 2: my definite feeling. You have to sort of start to

1080
00:53:42,600 --> 00:53:45,160
Speaker 2: think it's okay, like Kevin was talking about, if it's

1081
00:53:45,160 --> 00:53:47,800
Speaker 2: a small business, it doesn't have to be Instagram, right,

1082
00:53:48,080 --> 00:53:50,319
Speaker 2: It's okay. You can do very well with a very

1083
00:53:50,360 --> 00:53:52,680
Speaker 2: small business. You can do very well, and you get

1084
00:53:52,719 --> 00:53:53,399
Speaker 2: to do what you want.

1085
00:53:53,680 --> 00:53:55,799
Speaker 1: I get a smaller audience than I did when I

1086
00:53:55,880 --> 00:53:57,759
Speaker 1: was at the Today Show. But I also feel like

1087
00:53:57,800 --> 00:53:59,719
Speaker 1: I'm still serving a need. You know.

1088
00:54:00,120 --> 00:54:00,520
Speaker 2: That's right.

1089
00:54:00,640 --> 00:54:03,920
Speaker 1: The stuff that I'm doing is reaching people who want it,

1090
00:54:04,000 --> 00:54:06,799
Speaker 1: the people who find it useful. That's right, And that

1091
00:54:06,880 --> 00:54:09,400
Speaker 1: makes me feel like I have purpose.

1092
00:54:10,000 --> 00:54:12,560
Speaker 2: That's correct. That's correct. It's just different, that's all. I

1093
00:54:12,600 --> 00:54:15,440
Speaker 2: don't think it's I think people are still desperate for information,

1094
00:54:15,560 --> 00:54:19,040
Speaker 2: good information, and new good news, and not just good news,

1095
00:54:19,040 --> 00:54:22,600
Speaker 2: but news done well. And I think this recent situation

1096
00:54:22,760 --> 00:54:25,560
Speaker 2: Israel sort of underscores it. People are very confused by

1097
00:54:25,600 --> 00:54:28,920
Speaker 2: bad information and they need good information to make good

1098
00:54:28,960 --> 00:54:31,960
Speaker 2: decisions about what's happening and what to do about it.

1099
00:54:32,040 --> 00:54:35,359
Speaker 2: And that's critical. It remains critical, Kara.

1100
00:54:35,600 --> 00:54:37,520
Speaker 1: But I'll let you go because if you keep talking,

1101
00:54:37,600 --> 00:54:39,600
Speaker 1: you're never going to get your voice back.

1102
00:54:39,880 --> 00:54:42,680
Speaker 2: No, Katie, I never take a break. I never take

1103
00:54:42,719 --> 00:54:44,400
Speaker 2: a break like you. I let you know. You're my

1104
00:54:44,520 --> 00:54:46,440
Speaker 2: year o. Katie. You never take a break.

1105
00:54:46,480 --> 00:54:47,880
Speaker 1: Do you I like working?

1106
00:54:48,400 --> 00:54:49,640
Speaker 2: I know you do. You're good at it.

1107
00:54:50,000 --> 00:54:52,319
Speaker 1: Kara, thank you for being my plus one. This was

1108
00:54:52,400 --> 00:54:52,960
Speaker 1: so fun.

1109
00:54:53,160 --> 00:54:53,840
Speaker 2: No problem.

1110
00:54:53,960 --> 00:55:04,960
Speaker 1: Let's do it again anytime. Thanks for listening. Everyone. If

1111
00:55:05,000 --> 00:55:07,600
Speaker 1: you have a question for me, a subject you want

1112
00:55:07,680 --> 00:55:10,040
Speaker 1: us to cover, or you want to share your thoughts

1113
00:55:10,080 --> 00:55:13,880
Speaker 1: about how you navigate this crazy world reach out. You

1114
00:55:13,920 --> 00:55:16,799
Speaker 1: can leave a short message at six oh nine five

1115
00:55:16,800 --> 00:55:20,040
Speaker 1: point two five to five five, or you can send

1116
00:55:20,080 --> 00:55:22,680
Speaker 1: me a DM on Instagram. I would love to hear

1117
00:55:22,760 --> 00:55:26,560
Speaker 1: from you. Next Question is a production of iHeartMedia and

1118
00:55:26,680 --> 00:55:30,760
Speaker 1: Katie Kuric Media. The executive producers are Me, Katie Kuric,

1119
00:55:30,880 --> 00:55:35,480
Speaker 1: and Courtney Ltz. Our supervising producer is Ryan Martz, and

1120
00:55:35,560 --> 00:55:40,720
Speaker 1: our producers are Adriana Fazzio and Meredith Barnes. Julian Weller

1121
00:55:40,840 --> 00:55:45,400
Speaker 1: composed our theme music. For more information about today's episode,

1122
00:55:45,640 --> 00:55:48,040
Speaker 1: or to sign up for my newsletter, wake Up Call,

1123
00:55:48,480 --> 00:55:51,400
Speaker 1: go to the description in the podcast app, or visit

1124
00:55:51,480 --> 00:55:54,680
Speaker 1: us at Katiecuric dot com. You can also find me

1125
00:55:54,719 --> 00:55:58,439
Speaker 1: on Instagram and all my social media channels. For more

1126
00:55:58,520 --> 00:56:03,840
Speaker 1: podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, or

1127
00:56:03,880 --> 00:56:05,960
Speaker 1: wherever you listen to your favorite shows.