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Speaker 1: Welcome to Stupidity, home of the greatest media mind ever

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Speaker 1: to walk the planet. Okay, sure, here's the deal.

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Speaker 2: He's a true icon in every sense of the word.

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Speaker 2: He's loved and feared more than any being. To Grace's plummet, there's.

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Speaker 1: A bad with a voice that sounds like Verry White

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Speaker 1: and be got say he let you with Baby, God

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Speaker 1: himself would pay thirty nine ninety nine for a cameo.

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Speaker 1: Fact of the matter is you are about to embark

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Speaker 1: on a transcendent experience that can only be described as

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Speaker 1: psychological nudity.

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Speaker 2: This is and this is stupidity.

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Speaker 3: Here we go, Jumpy.

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Speaker 2: Billy, have a serious question for you.

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Speaker 4: Yeah, are you surprised at some of the things I've

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Speaker 4: been saying, yes too lately, like wasteland and what we're

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Speaker 4: about to do right now.

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Speaker 5: This is what I would say, what we've kind of

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Speaker 5: run into at the moment, and I don't know how.

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Speaker 2: We got here.

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Speaker 5: If you were a third base coach, everyone would be

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Speaker 5: going home on every play is where we kind of arrived.

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Speaker 5: Everybody's going home on this single.

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Speaker 2: I'm sending you home if you're a round third. I mean,

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Speaker 2: we don't come near my bag.

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Speaker 5: Well, look, we are being I don't know what that means.

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Speaker 5: We're being quite aggressive with the guests that we're having on.

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Speaker 5: And by the way, it is working out for us

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Speaker 5: because the guests that we've had on have been really good,

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Speaker 5: and we're going after some people that we wouldn't normally

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Speaker 5: you wouldn't expect us to be talking to, but they've

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Speaker 5: been great guests.

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Speaker 2: Yes, we're gonna have Cash hill On.

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Speaker 4: She's a I can't believe I'm saying this a New

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Speaker 4: York Times investigative journalist.

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Speaker 2: What am I doing? Yeah? And White Tea. Do you

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Speaker 2: have a New York Times subscription? By the way, Billy, No,

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Speaker 2: what kind of question is that?

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Speaker 6: No?

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Speaker 2: I have one? Why what'd you have to read?

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Speaker 4: I had to read something for our show. I can't

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Speaker 4: remember what it was. And now, I mean all they do.

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Speaker 3: You can't figure out how to cancel it.

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Speaker 2: I can't get out of it. I mean, unbelievable, Billy.

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Speaker 2: Mike Yea.

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Speaker 5: I was talking about it on the main show the

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Speaker 5: other day. I cannot, for the life of me figure

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Speaker 5: out how to cancel my ESPN Plus subscription because I

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Speaker 5: signed up and I now have Hulu, which comes with

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Speaker 5: ESPN included in it with the version that I have,

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Speaker 5: and the closest I've gott into is a page that

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Speaker 5: says you must unsubscribe from the same device you use

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Speaker 5: to subscribe on, which is like the strangest rule I've

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Speaker 5: ever heard, and I can't possibly figure out which device

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Speaker 5: I used to sign up.

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Speaker 2: It's the weirdest name.

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Speaker 3: And you must get Steven A. Smith to sign off

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Speaker 3: on you want to see.

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Speaker 2: Yeah, it's just it's on your phone. They keep making

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Speaker 2: it harder.

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Speaker 5: Yeah, did you did you? Secott's I don't think you've

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Speaker 5: ever seen this show, Mikey. Did you ever see the

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Speaker 5: show Nathan for you?

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Speaker 3: No?

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Speaker 6: No?

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Speaker 2: Okay? Well on the show?

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Speaker 5: So he it's his whole It's a comedy show where

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Speaker 5: the guy goes and he's allegedly trying to help these

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Speaker 5: small businesses and companies better their business, but he really

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Speaker 5: is just making a mess of things. Right, And one

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Speaker 5: of the things that he came up with was for

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Speaker 5: a TV.

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Speaker 2: Repair shop or TV company.

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Speaker 5: It's like combat best buy by having them promised to

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Speaker 5: give away free TVs and all you had to do

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Speaker 5: was go to the store and pick up the TV.

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Speaker 5: Right now, what he didn't tell you and the thing

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Speaker 5: was the TV was you.

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Speaker 2: Had to go all the way to the back of

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Speaker 2: the store.

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Speaker 5: There was like a limited quantity, and then I don't

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Speaker 5: remember the specifics, but you had to jump through a

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Speaker 5: number of hoops to get there.

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Speaker 2: And then the final thing was the TV was sitting

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Speaker 2: on a.

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Speaker 5: Table in a room with an alligator locked in it,

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Speaker 5: and you had to go into the room, like crawl

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Speaker 5: through a doggy door into a room with an alligator

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Speaker 5: to go claim your free TV.

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Speaker 2: That's what I have to do to cancel my ESPN.

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Speaker 2: Plus it's gonna have to find the multiples.

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Speaker 4: You have to find the device you worded it on,

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Speaker 4: and then you have to, like what would be the

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Speaker 4: equivalent of that at ESPN.

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Speaker 5: I don't know because I haven't, like I haven't even

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Speaker 5: gotten into that step yet to figure out if there's

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Speaker 5: something after that.

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Speaker 2: Right, But I think Mike's right.

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Speaker 4: It's like, once you find the device that you did

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Speaker 4: it on, then it's like, all right, Steven A. Smith

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Speaker 4: needs to actually do it, you knoweah, yeah, or something

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Speaker 4: like that. Facial recognition, Billy, this is I think this

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Speaker 4: is something that's interesting to you.

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Speaker 2: Right. I don't like it one bit. I'm not surprised

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Speaker 2: you don't like it. I don't like it either, No

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Speaker 2: one likes it. I mean, yeah, I'm not like. I

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Speaker 2: don't know why we have to do this.

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Speaker 5: I don't know when we have to do the AI stuff,

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Speaker 5: or we're just faking videos of people saying things that

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Speaker 5: don't happen, Like what like can we like can we

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Speaker 5: cure diseases? Can we can we do something beneficial with

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Speaker 5: this technology?

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Speaker 2: No, we're too busy on TikTok. I mean enough of TikTok.

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Speaker 5: Jeez, I thought they weren't they going to vote to

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Speaker 5: band TikTok in the US?

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Speaker 2: What happened to that?

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Speaker 4: Not banning anything in the US? What do you tell

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Speaker 4: people are making money off of it?

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Speaker 2: That's not happening. Why do you hate TikTok so much?

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Speaker 5: I don't. I'm just, you know, going along with the whole.

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Speaker 5: I don't like this. I don't like that thing. I

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Speaker 5: feel like I feel like a real team player.

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Speaker 2: Yeah, I'm trying to be a team player.

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Speaker 5: I feel like in real life I'm more a lot

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Speaker 5: more easy going than I am portrayed in the public.

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Speaker 2: Do you really don't care about any of this shit? Yeah?

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Speaker 5: Like I honestly, like my perfect day and it's like

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Speaker 5: a strange thing is like just being left alone, you

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Speaker 5: know what I mean. And it's not like and I'm

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Speaker 5: not saying that like if oh, you see me walking around,

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Speaker 5: you come and say hi, like leave me alone.

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Speaker 2: It's not that at all.

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Speaker 5: Like I love like meeting people and like fans of

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Speaker 5: the show or whatever and like talking to them. Like

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Speaker 5: if I could, just if I could have, like if

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Speaker 5: my weekend consisted of like just waking up, laying in

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Speaker 5: bed for a little bit, maybe I get up, have

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Speaker 5: a snack, go outside, breathe some fresh air, go back

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Speaker 5: and lay down a little bit, turned on the TV

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Speaker 5: and just watch nothing but TV for like a day.

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Speaker 5: That would be a perfect day, not not really talk

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Speaker 5: to anyone, you.

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Speaker 4: Know, yeah, yep, with Mikey, what's your perfect day?

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Speaker 3: I don't know. I'm trying to steal Billies right now,

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Speaker 3: as long as it's you know.

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Speaker 2: It sounds like it was a great day.

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Speaker 4: And fortunately for Billy, right but unfortunately for Billy, he's

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Speaker 4: got me a levator in his life.

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Speaker 5: And so you know, I'm trying to think of like

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Speaker 5: what day, what would your perfect day of the week be,

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Speaker 5: Like what day would you want your perfect day?

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Speaker 2: Would it be Sunday so you have.

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Speaker 3: Football, it would have to be Sunday?

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Speaker 4: Yeah yeah, really Yeah, Somedays like a bittersweet day.

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Speaker 2: I'm enjoying it.

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Speaker 4: I'm watching football, but I know I got to wake

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Speaker 4: up early the next day, get back to work, all

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Speaker 4: that stuff. Like some days like a workday almost, I

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Speaker 4: would say, like Thursday or Thursday headed into the weekend.

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Speaker 3: Yeah, yeah, because you don't have to wake up early

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Speaker 3: on Friday.

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Speaker 2: Yeah.

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Speaker 5: Most people will work on Friday, so it's a little

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Speaker 5: more complicated than that.

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Speaker 2: I think that you know, you should be working on Fridays.

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Speaker 2: I didn't ask for any of this.

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Speaker 5: We we talked about it on God Bless Football on Monday.

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Speaker 5: She has a perfect setup and that her Saturday is

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Speaker 5: more important to her for sports viewing, and she has

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Speaker 5: all of Sunday to recover, which is just amazing. Could

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Speaker 5: you imagine after a football Sunday and you've been trying

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Speaker 5: to do this for the Super Bowl for a long time,

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Speaker 5: just just every Sunday, like you can recover on Monday

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Speaker 5: from all the football you watch the day before. You're fine,

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Speaker 5: don't worry about it, just come in fresh on Tuesday.

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Speaker 2: Oh, that'd be great. Yeah, we're not going there.

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Speaker 5: Would you let me ask Let me ask you guys

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Speaker 5: a question for your perfect.

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Speaker 4: Every thing about Lucy's schedule? Billy, Her Friday is a Tuesday.

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Speaker 4: Did you know that she's not on Tuesday.

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Speaker 5: Well, that's because she's traveling the country the rest of

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Speaker 5: the time.

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Speaker 2: But I know she's got a great schedule, great job,

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Speaker 2: and great at her job. Yeah.

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Speaker 5: Well, I mean, I don't know what Lucy running for

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Speaker 5: office and you're endorsing her. What's going on right now?

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Speaker 2: It's weird. God bless football every Monday morning with us,

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Speaker 2: she's been great. I did too, I think I really

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Speaker 2: you know what I like?

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Speaker 5: I think that she has a great like energy and

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Speaker 5: enthusiasm that we don't have.

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Speaker 2: Yes on Monday morning, right because she's just in general.

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Speaker 5: No, we've just we've been doing it so long that

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Speaker 5: like the joy has been beaten out of us. Yeah. Right, anyway,

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Speaker 5: what are we talking about? Oh, I have a question

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Speaker 5: for you guys, like in your perfect days? Is your

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Speaker 5: family involved in your perfect day?

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Speaker 4: Jesus put me on the spots. I forgot what you

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Speaker 4: said your perfect day was all about?

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Speaker 3: Is your family I will guarantee you this. They're not

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Speaker 3: there the whole day.

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Speaker 2: Morning. Sure, at what time?

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Speaker 5: Because if the morning involves like waking you up, not

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Speaker 5: one o'clock, that's a kickoff.

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Speaker 6: Is.

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Speaker 2: Yeah, but Mike wants the family out, then maybe like yeah, okay,

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Speaker 2: well you're more generous.

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Speaker 5: You're more generous than I was being.

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Speaker 3: My father listens to this.

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Speaker 5: I think I think I told you, get what are

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Speaker 5: you cooking for him this weekend?

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Speaker 3: I'm thinking about smash burgers.

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Speaker 2: Okay.

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Speaker 5: I think that I've told you guys in the past,

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Speaker 5: and it's never worked for me when I like m asked,

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Speaker 5: what do you want for your birthday or you know, Christmas.

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Speaker 2: Holiday whatever, like, oh, what would you like?

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Speaker 5: And I just always say, like I just want a

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Speaker 5: quiet take and you just give me a quiet day

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Speaker 5: and I have silence, No just a date, just give

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Speaker 5: me like a quiet I've yet to receive it. Not

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Speaker 5: once has anyone just written quiet day, giving me a

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Speaker 5: piece of paper with it. I feel like I'm very

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Speaker 5: direct with the two, like that's it's all I want?

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Speaker 4: What so you want it delivered just on a piece

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Speaker 4: of paper? You like it breaks down a quiet.

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Speaker 5: Day like a voucher, Like I don't know if you guys,

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Speaker 5: I mean you got you're a little bit older, and Mike,

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Speaker 5: you don't know how long like you were with your

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Speaker 5: wife before.

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Speaker 2: How long how long you been married eight years? Eight years?

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Speaker 2: And how long did you like date before that or whatever?

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Speaker 3: Two and a half.

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Speaker 5: So like you maybe got like the early end of this.

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Speaker 5: But like in the like dating world, there's like you'll

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Speaker 5: see like on social media and stuff like that. There's

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Speaker 5: like companies now that'll sell you like little coupons that

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Speaker 5: you can like, you know.

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Speaker 2: Like oh, date night out. Oh here here's flowers.

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Speaker 5: Oh like a foot rub or something like that, you

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Speaker 5: know what I mean, Like things that you can buy

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Speaker 5: and they're like, oh, I'm redeeming my thing. We're going

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Speaker 5: on a date today. I got this coupon for it, right,

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Speaker 5: Like that's more what I'm thinking.

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Speaker 2: Like, here's three coupons for three quiet days.

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Speaker 5: It's like, oh my god, I'm gonna catch one in today,

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Speaker 5: Like get out of here, just catch my coop.

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Speaker 3: Is there waiting to catch that coupon in? To your wife? No,

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Speaker 3: where You're not an asshole?

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Speaker 2: Not successfully, I don't think.

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Speaker 7: Is there away you can hand her that coupon and

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Speaker 7: just be like this this is what I want.

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Speaker 5: Well, the thing is is that I don't mean it

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Speaker 5: in a like way too, of course you don't.

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Speaker 2: But like the only way that works, Mikey is if

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Speaker 2: the wife gives it to you. That's that thing.

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Speaker 5: Well, yeah, no, obviously I can't just I can't just

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Speaker 5: get out of it.

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Speaker 2: I got this from Uncle Ted.

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Speaker 3: I printed this out myself.

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Speaker 2: Yeah. Uncle Ted said that I could use it on anyone.

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Speaker 2: It applies. There's no restriction to fly. Yeah, I can't

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Speaker 2: get mad at me.

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Speaker 3: It's a coupon.

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Speaker 2: All right? Are there still teds what you say? Are

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Speaker 2: there's still tends? Teddy Bridgewater? There you go? Oh man,

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Speaker 2: what are we doing? What is this? Still? Put that

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Speaker 2: on the pole?

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Speaker 5: You know what I have that this is just related

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Speaker 5: to coupons. I have a group on that I was

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Speaker 5: gifted for my birthday in April for a massage.

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Speaker 2: That is.

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Speaker 5: I'm getting emails saying it's set to expire, and I

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Speaker 5: legitimately like am looking ahead and like you have twenty

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Speaker 5: one days before this expires.

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Speaker 2: I'm like, I don't think I'm gonna make it. I don't.

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Speaker 5: I don't see where in twenty one days, they're gonna

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Speaker 5: fit a massage and gotta be honest with you. And

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Speaker 5: I also like to to the point of like the

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Speaker 5: Quiet Day coupons, Like I'm not sure how I'm gonna

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Speaker 5: tell my wife, Like, Hey, I got this group on

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Speaker 5: that I've got as a gift that I need to use,

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Speaker 5: and you gotta have to take care of the two

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Speaker 5: kids while I go and just have a relaxing massage.

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Speaker 3: Just tell her that one before you give her the

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Speaker 3: Quiet Day one.

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Speaker 2: Yeah, just everything on, Uncle Teddy. Yeah, Teddy told me.

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Speaker 2: You give her one too, Billy. Yeah, you give her

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Speaker 2: what you say. Hey, you can redeem this whenever you want,

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Speaker 2: give it to me. I'll take care of the kids

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Speaker 2: for the day. That's how you get your quiet. This

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Speaker 2: just can't be the same day as me, right, exactly right,

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Speaker 2: all right.

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Speaker 4: Let's get to Cash Shill here. She's a New York

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Speaker 4: Times tech reporter and an author. Knew a book at

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Speaker 4: your Facebook Loss to Us, A Secret of Startups, Quest

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Speaker 4: to End Privacy. As we know, I don't know what's

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Speaker 4: gotten into me, but I'm kind of into these stories.

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Speaker 4: Let's get to Cash Cash. You're a New York Times

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Speaker 4: Tech reporter. Were you surprised when you got an invitation

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Speaker 4: to do this show, A show called Stupidity whose logo

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Speaker 4: is me sitting on a toilet bowl.

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Speaker 6: Well, I had done the Dann Levatard show before, and

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Speaker 6: I really liked talking about tracking my husband with air

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Speaker 6: tags there and was left with a good impression. So

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Speaker 6: the Levatard incompany me is what got me in here?

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Speaker 2: Wow, the rare good impression that we left with somebody.

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Speaker 6: Yeah, I think you did call me really creepy.

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Speaker 2: I do kind of good. That's great, and you left

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Speaker 2: with a good impression.

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Speaker 6: You're the ones who should be scared of me.

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Speaker 2: Why is that?

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Speaker 3: Cat?

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Speaker 6: I'm just going to run all your faces through a

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Speaker 6: face search engine and find the photos on the internet

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Speaker 6: you didn't want people to know about.

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Speaker 2: Oh my god, it's terrifying the whole thing.

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Speaker 4: If she has a new book out your Facebook Hugs

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Speaker 4: to Us, a Secret of Startups, Quest to End Privacy

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Speaker 4: as we know, And again cat kill is with us.

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Speaker 2: Why would you write the book?

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Speaker 6: Like?

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Speaker 2: Why did this topic kind of grab you?

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Speaker 6: I mean I just when I found out about this company,

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Speaker 6: Clearview AI a few years ago, it was just one

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Speaker 6: of the craziest tips I've gotten as a reporter that

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Speaker 6: they had scraped the Internet of a billion photos, you know,

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Speaker 6: without people's consent, put all these faces in the database,

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Speaker 6: made the spacial recognition app secretly telling it to the police.

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Speaker 6: I mean that alone was wild. And then the more

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Speaker 6: I dunk into the company, the more crazy things kept

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Speaker 6: coming out. And in facial recognition technology itself, how we

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Speaker 6: got to this point. I was just obsessed and I

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Speaker 6: wanted everything about it, and I honestly have never felt

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Speaker 6: quite like that about a story before. And everyone around me,

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Speaker 6: my editors the New York Times, said you just you

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Speaker 6: need to do a book. You're you're too obsessed.

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Speaker 5: Well what are the other crazy things that you started

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Speaker 5: discovering about this company?

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Speaker 6: Well, I mean just right off that, you know, I

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Speaker 6: googled Clearview AI. I find on there's not much on

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Speaker 6: the internet about them, But on a startup tracking website

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Speaker 6: called pitchbook, there's not much information I except for two investors,

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Speaker 6: one I'd never heard of before and the other being

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Speaker 6: Peter Teel, who's a big name in Silicon Valley, and

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Speaker 6: you know, reached reached out to a spokesperson. Spokesperson's like, never,

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Speaker 6: I don't know, I don't think i've heard a clearview

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Speaker 6: eye before. Let me look into it, and then stops

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Speaker 6: talking to me, And and uh, that happened to me

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Speaker 6: a lot. I would reach try to find people connected

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Speaker 6: the company, and they wouldn't want to talk to me.

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Speaker 2: Designing on you know, they.

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Speaker 6: Had one employee on LinkedIn. His name was John Good.

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Speaker 6: He had two connections. I said, that looks like a

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Speaker 6: fake person. Send a message, didn't hear back. They had

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Speaker 6: an address on their you know, their very bare website.

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Speaker 6: It was just a few blocks away from the New

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Speaker 6: York Times office. I walked over to where Google Maps

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Speaker 6: said the building should be. It did not exist, And yeah,

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Speaker 6: it just kept getting weirder and weirder from there. They

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Speaker 6: were they were trying to they you know, they were

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Speaker 6: exposing all this information about people, all the places on

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Speaker 6: the Internet where their face appeared, but they wanted to

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Speaker 6: stay in the shadows. And it was just like a

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Speaker 6: it was like a detective novel, I mean, just kind

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Speaker 6: of thrilling to try to find out what was going

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Speaker 6: on there?

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Speaker 2: Did you find out about the company?

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Speaker 6: So I got an email from a tipster who I

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Speaker 6: knew he was a public researcher really interested in police

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Speaker 6: surveillance technologies, and he sent me an email with a

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Speaker 6: twenty six page PDF attached to it, and he said, Hey,

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Speaker 6: I did a foyer to the Atlanta Police Department and

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Speaker 6: they sent me this and it's pretty wild. I think

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Speaker 6: that this company has passed the rubicon on facial recognition technology,

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Speaker 6: is how he put it. And I start reading this

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Speaker 6: PDF and it starts with a privileged, incidential legal memo

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Speaker 6: that's been written by a really high profile lawyer that

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Speaker 6: Clearview AI has hired. His name is Paul Clement in

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Speaker 6: private practice now, but he had been a Solicitor General

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Speaker 6: of the United States. And in this memo he's saying

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Speaker 6: that CLEARVIEWI works really well, that he ran on lawyers

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Speaker 6: at the firm and it brought up photos of them.

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Speaker 6: And he's essentially explaining to police why this tool is

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Speaker 6: not illegal and just reassuring them that they won't break,

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Speaker 6: you know, state and federal laws by using a tool.

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Speaker 6: And then there were some like advertising materials on clear

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Speaker 6: y AI to saying, hey, this is Google for faces,

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Speaker 6: this is great, get a free trial. And I was

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Speaker 6: one of many hundreds thousands of police departments that were

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Speaker 6: trying out the app on a free trial basis.

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Speaker 2: I would have loved to hear that pitch, like, do

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Speaker 2: you know what the pitch was? Do you know anything

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Speaker 2: about the pitch?

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Speaker 6: I remember, I remember the some of the email advertisements

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Speaker 6: I said, and it said stop searching, start solving. They

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Speaker 6: had a lot of mottos that were just kind of

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Speaker 6: like Google your way to closing that case.

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Speaker 2: Wow, that is crazy.

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Speaker 4: And so as you dug into this story and you

400
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Speaker 4: started to get intrigued and looked into.

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Speaker 2: What it is this company was doing. What did what

402
00:17:56,320 --> 00:17:57,080
Speaker 2: did you discover?

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Speaker 6: So clear, yod I did not want to tell to me, And.

404
00:18:01,160 --> 00:18:03,840
Speaker 2: So like relentless.

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Speaker 4: You're a great reporter, you're a great writer. So you

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Speaker 4: were relentless, and no one wanted to speak to you.

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Speaker 6: Yeah, not not at first. They were really I think

408
00:18:11,640 --> 00:18:14,800
Speaker 6: they were just hoping, let's ignore this woman, let's ignore

409
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Speaker 6: this reporter, and she'll, you know, she'll just go away,

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00:18:18,560 --> 00:18:22,639
Speaker 6: she'll go away. But you know this, this memo said

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Speaker 6: that hundreds of police departments were using it. So I

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00:18:26,000 --> 00:18:28,720
Speaker 6: started trying to find police officers who would use the app,

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00:18:29,119 --> 00:18:31,320
Speaker 6: And so I reached out to a lot of departments

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Speaker 6: and I found this detective in Gainesville, Florida, financial crimes detective,

415
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Speaker 6: and you know, he's telling me, I love this app.

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00:18:39,119 --> 00:18:42,919
Speaker 6: It's it's great. I had a stack of unsolved cases

417
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Speaker 6: where I had somebody at an ATM or at a

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Speaker 6: bank counter and they hadn't worked when I ran it

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Speaker 6: through the state face recognition database, like going through criminal

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Speaker 6: mug shots and uh, you know, state driver's license photos.

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Speaker 6: And then I put all these photos through Clearview AI

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Speaker 6: and it's just solving, you know, case after case after case.

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Speaker 6: From here, I'm getting hit after hit after hit. You

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Speaker 6: do need to do, ideally, some more investigating after you

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00:19:07,119 --> 00:19:09,440
Speaker 6: get a facial recognition hit. He said, yeah, it's incredible.

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Speaker 6: I was on patrol one day one night and there

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00:19:13,000 --> 00:19:15,600
Speaker 6: were a bunch of University of Florida, you know, college

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00:19:15,600 --> 00:19:17,919
Speaker 6: students hanging out outside of a bar. I asked them

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Speaker 6: if I could try the app on them, and I

430
00:19:20,080 --> 00:19:23,159
Speaker 6: was able to identify most of them. It linked me

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00:19:23,200 --> 00:19:26,200
Speaker 6: to their you know, their Facebook profile, their Instagram profile,

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Speaker 6: and he said it was The kids were like, oh,

433
00:19:29,720 --> 00:19:32,959
Speaker 6: that's cool, Like I want that, and he's like, sorry,

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00:19:33,000 --> 00:19:36,040
Speaker 6: this is only for the cops. And he said he'd

435
00:19:36,040 --> 00:19:38,920
Speaker 6: be their spokesperson if he could. And once I got

436
00:19:38,960 --> 00:19:42,080
Speaker 6: police talking to me, that kind of helped open the

437
00:19:42,200 --> 00:19:44,320
Speaker 6: door to get some people who were connected to CLEARVIEWAI

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Speaker 6: to talk to me.

439
00:19:45,560 --> 00:19:48,960
Speaker 5: So obviously the police departments would justify this as being

440
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Speaker 5: for good if they're using it to solve crimes or whatever,

441
00:19:51,800 --> 00:19:55,479
Speaker 5: but this is technology that can be used for bad

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Speaker 5: as well, correct.

443
00:19:57,800 --> 00:20:02,000
Speaker 6: Yeah, I mean this is a way to unmask somebody,

444
00:20:02,040 --> 00:20:05,760
Speaker 6: to find out somebody's identity who doesn't want you to

445
00:20:05,760 --> 00:20:08,760
Speaker 6: know who they are, and to find photos of them

446
00:20:08,920 --> 00:20:11,680
Speaker 6: on the Internet that they might not know is there,

447
00:20:11,960 --> 00:20:14,639
Speaker 6: might not want you to find photos that may have

448
00:20:14,640 --> 00:20:18,119
Speaker 6: been obscurely out there, not attached to their name, but

449
00:20:18,200 --> 00:20:20,600
Speaker 6: now if you search the Internet by face, they come up.

450
00:20:20,640 --> 00:20:23,359
Speaker 6: So I've been thinking a lot about this because I

451
00:20:23,359 --> 00:20:25,840
Speaker 6: don't know if you've been falling this. Like local political

452
00:20:25,920 --> 00:20:31,520
Speaker 6: race in Virginia, this woman who had made sex tapes

453
00:20:31,800 --> 00:20:36,200
Speaker 6: online with their husband on a site called chatterbait, which

454
00:20:36,240 --> 00:20:40,720
Speaker 6: is the combination of chatting and masturbating, and she's now

455
00:20:40,880 --> 00:20:44,520
Speaker 6: she's a nurse, she's running for office, and somebody found

456
00:20:44,640 --> 00:20:48,560
Speaker 6: these old sex tapes didn't have her name. I don't

457
00:20:48,600 --> 00:20:51,600
Speaker 6: know how the Republican operative who dug them up and

458
00:20:51,600 --> 00:20:54,439
Speaker 6: gave them to the Washington Washington Post found them, but

459
00:20:54,800 --> 00:20:57,680
Speaker 6: you know, very possible that it was a face search.

460
00:20:59,000 --> 00:21:01,000
Speaker 4: But Billy's right, it could use like there is some

461
00:21:01,040 --> 00:21:02,800
Speaker 4: good in this, but there's also a lot of evil

462
00:21:02,800 --> 00:21:03,000
Speaker 4: in it.

463
00:21:03,080 --> 00:21:06,040
Speaker 5: Right when did we stop using technology for good? Like

464
00:21:06,080 --> 00:21:08,199
Speaker 5: when did we stop trying to advance things and make

465
00:21:08,240 --> 00:21:10,280
Speaker 5: things better and just use it for pure evil?

466
00:21:11,880 --> 00:21:14,000
Speaker 6: I mean, it's solving crimes, period.

467
00:21:14,040 --> 00:21:16,679
Speaker 4: I mean, I think there's no no, no, but people's

468
00:21:16,680 --> 00:21:19,000
Speaker 4: pc if you're a bad guy, he is solving crimes.

469
00:21:19,040 --> 00:21:25,800
Speaker 6: Is evil, Yeah, I mean I I think that this

470
00:21:26,080 --> 00:21:29,720
Speaker 6: can be very creepy and just the idea that you

471
00:21:29,760 --> 00:21:32,560
Speaker 6: can't just be anonymous in public and then you might

472
00:21:32,600 --> 00:21:36,399
Speaker 6: have a sensitive conversation and somebody's like, oh that sounds juicy.

473
00:21:36,440 --> 00:21:38,359
Speaker 6: I wonder who those people are. And they take a

474
00:21:38,400 --> 00:21:40,080
Speaker 6: picture of your face and then look you up and

475
00:21:40,800 --> 00:21:44,159
Speaker 6: they know or you know, you're buying some hemorrhoid cream

476
00:21:44,280 --> 00:21:46,760
Speaker 6: at the pharmacy and somebody just snaps a photo and

477
00:21:46,760 --> 00:21:50,680
Speaker 6: they're like haha. You know, a woman walking out of

478
00:21:50,720 --> 00:21:53,320
Speaker 6: a planned parenthood who just had an abortion, and protesters

479
00:21:53,359 --> 00:21:55,920
Speaker 6: take a photo of her and can find out who

480
00:21:55,960 --> 00:21:58,320
Speaker 6: she is. I mean, there are so many creepy ways

481
00:21:58,359 --> 00:22:01,639
Speaker 6: that could be deployed as well as good ways of

482
00:22:02,040 --> 00:22:02,800
Speaker 6: solving crimes.

483
00:22:02,920 --> 00:22:05,320
Speaker 2: Billy, what did the hemorrhoid kream get? I just thought

484
00:22:05,400 --> 00:22:07,399
Speaker 2: I thought it was a good example. I thought it

485
00:22:07,440 --> 00:22:09,600
Speaker 2: was a good example of like the haha at the end.

486
00:22:09,920 --> 00:22:13,000
Speaker 3: We've all been there. Huh.

487
00:22:13,200 --> 00:22:15,400
Speaker 2: I'm starting to think if anyone's taking picture.

488
00:22:18,280 --> 00:22:20,200
Speaker 4: So cash, is there a way that the public can

489
00:22:20,240 --> 00:22:22,560
Speaker 4: prevent this from happening to them?

490
00:22:23,000 --> 00:22:25,840
Speaker 6: Well, so, right now, depending where you live, you might

491
00:22:25,880 --> 00:22:30,520
Speaker 6: be better protected than other places. So if you're in Illinois,

492
00:22:31,119 --> 00:22:33,720
Speaker 6: you there's a law there to protect you. If you

493
00:22:33,760 --> 00:22:39,520
Speaker 6: live in California or Connecticut or Virginia or Colorado, there's

494
00:22:39,600 --> 00:22:42,639
Speaker 6: a law that says you have the right to access

495
00:22:42,800 --> 00:22:45,320
Speaker 6: information a company holds on you and get it deleted.

496
00:22:45,720 --> 00:22:48,960
Speaker 6: So you can go to clearview AI or to Pimie

497
00:22:49,000 --> 00:22:52,760
Speaker 6: one of the other public face search engines. So that's

498
00:22:52,760 --> 00:22:55,000
Speaker 6: out there that's very much like Clearview, but available for

499
00:22:55,040 --> 00:22:57,800
Speaker 6: public use, and you can send them your photo and

500
00:22:57,840 --> 00:23:00,320
Speaker 6: your driver's license, which kind of creeps some people out

501
00:23:00,359 --> 00:23:02,439
Speaker 6: and say, get me out of your database. But if

502
00:23:02,440 --> 00:23:05,320
Speaker 6: you don't live in one of those places you don't

503
00:23:05,359 --> 00:23:08,080
Speaker 6: really have much protection beyond just wearing a ski mask

504
00:23:08,160 --> 00:23:08,960
Speaker 6: all of the time.

505
00:23:09,359 --> 00:23:12,080
Speaker 5: The idea of sending a company that you don't know

506
00:23:12,200 --> 00:23:16,440
Speaker 5: more information about yourself, hoping that that they then voluntarily

507
00:23:16,520 --> 00:23:19,480
Speaker 5: delete all the information they have on you seems insane.

508
00:23:20,480 --> 00:23:24,760
Speaker 6: Yeah, people don't. People don't love this about about Yes,

509
00:23:25,160 --> 00:23:28,000
Speaker 6: you are having to send this. They do say you can,

510
00:23:28,119 --> 00:23:31,960
Speaker 6: you know, blank out your address and stuff like that.

511
00:23:32,040 --> 00:23:33,320
Speaker 6: They asked you to say, get.

512
00:23:33,200 --> 00:23:35,920
Speaker 2: A long clear view, Well in that company too, exactly right. Yeah,

513
00:23:35,960 --> 00:23:38,600
Speaker 2: you're just fighting them more information for yourself. So I

514
00:23:38,640 --> 00:23:42,400
Speaker 2: have a question. I came through I came through.

515
00:23:42,200 --> 00:23:44,080
Speaker 5: Customs not too long ago. I was on a cruise.

516
00:23:44,080 --> 00:23:45,240
Speaker 5: I think it was like a year or two ago.

517
00:23:45,480 --> 00:23:48,280
Speaker 5: I came through customs. I have my passport out. At

518
00:23:48,280 --> 00:23:50,480
Speaker 5: no point does anyone check my passport. They just have

519
00:23:50,560 --> 00:23:53,080
Speaker 5: cameras or whatever that are just following everybody on their

520
00:23:53,080 --> 00:23:55,159
Speaker 5: way through. They're like, are you you a citizen? You

521
00:23:55,160 --> 00:23:57,520
Speaker 5: could just walk through? Is this the technology that they're

522
00:23:57,600 --> 00:24:00,320
Speaker 5: using just kind of scanning our faces as we're walking through?

523
00:24:00,720 --> 00:24:02,200
Speaker 6: Did you scan your passport somewhere?

524
00:24:02,200 --> 00:24:03,520
Speaker 2: I didn't.

525
00:24:03,920 --> 00:24:05,720
Speaker 5: I mean I may have on the way in, but

526
00:24:05,800 --> 00:24:06,920
Speaker 5: on the way out, I mean it was just to

527
00:24:06,960 --> 00:24:09,040
Speaker 5: the Bahamas, so it wasn't like it was a lot

528
00:24:09,040 --> 00:24:11,480
Speaker 5: of international travel, but it was just like everybody just

529
00:24:11,520 --> 00:24:13,639
Speaker 5: walked right on through. And then you're walking through, you

530
00:24:13,680 --> 00:24:15,719
Speaker 5: see those cameras kind of mounted on the ceiling, and

531
00:24:16,000 --> 00:24:18,879
Speaker 5: that was the entire check that they did for everyone.

532
00:24:19,080 --> 00:24:21,479
Speaker 6: I'm not sure in that specific situation. I did have

533
00:24:21,520 --> 00:24:25,199
Speaker 6: the experience. You know, I traveled to London for the

534
00:24:25,240 --> 00:24:28,479
Speaker 6: book to report on facial recognition technology because they're doing

535
00:24:28,520 --> 00:24:31,000
Speaker 6: kind of crazy things. They're like putting cameras on top

536
00:24:31,040 --> 00:24:33,520
Speaker 6: of mobile vans and just scanning the crowd for people

537
00:24:33,600 --> 00:24:36,440
Speaker 6: that are wanted by the courts and just arresting them.

538
00:24:37,200 --> 00:24:42,119
Speaker 6: But when I got to Heathrow Airport, I didn't have

539
00:24:42,200 --> 00:24:44,520
Speaker 6: to wait in a line for hours. I just took

540
00:24:44,520 --> 00:24:46,919
Speaker 6: my passport, put it on the scanner. There's a biometric

541
00:24:47,000 --> 00:24:51,520
Speaker 6: chip in your passport that has your facial print on it,

542
00:24:51,840 --> 00:24:54,080
Speaker 6: and so a camera just looked at me, made sure

543
00:24:54,080 --> 00:24:56,600
Speaker 6: that my face matched the chip in my passport, and

544
00:24:56,640 --> 00:24:59,439
Speaker 6: I just walked right in and it was it was

545
00:24:59,480 --> 00:25:00,240
Speaker 6: really CONVENI.

546
00:25:00,720 --> 00:25:02,600
Speaker 5: See, I think that's too God, So Mike, you will

547
00:25:02,600 --> 00:25:04,040
Speaker 5: agree with me on this. I'm not sure that this

548
00:25:04,119 --> 00:25:06,800
Speaker 5: is one of your primary concerns with this technology and

549
00:25:06,840 --> 00:25:09,360
Speaker 5: what it's doing. But when I had that experience coming

550
00:25:09,400 --> 00:25:10,960
Speaker 5: off the cruise ship, one of the first things that

551
00:25:10,960 --> 00:25:12,639
Speaker 5: I thought was, look, I like action movies.

552
00:25:12,680 --> 00:25:13,600
Speaker 2: I'm not going to lie to you.

553
00:25:13,760 --> 00:25:16,040
Speaker 5: I thought, how is Michael Bourne going to be able

554
00:25:16,080 --> 00:25:18,200
Speaker 5: to survive situations like this moving forward?

555
00:25:18,240 --> 00:25:18,840
Speaker 2: You know what I mean?

556
00:25:19,119 --> 00:25:21,000
Speaker 5: Like, if you know immediately who he is, a fake,

557
00:25:21,000 --> 00:25:22,320
Speaker 5: passports aren't going to work anymore.

558
00:25:22,400 --> 00:25:22,960
Speaker 2: How are we going to.

559
00:25:22,960 --> 00:25:25,720
Speaker 5: Continue to have these great pieces of cinema moving forward

560
00:25:25,720 --> 00:25:28,840
Speaker 5: if this technology exists to kind of prevent these heroes

561
00:25:28,840 --> 00:25:30,680
Speaker 5: from getting through international borders.

562
00:25:31,359 --> 00:25:34,320
Speaker 3: Yeah, just before you answer that, it's Jason Bourne and

563
00:25:34,359 --> 00:25:34,880
Speaker 3: get it right.

564
00:25:35,119 --> 00:25:37,760
Speaker 2: Oh yeah, oh Michael Bourne. Now I was thinking about the.

565
00:25:37,680 --> 00:25:44,000
Speaker 6: Houston Michael Bourne.

566
00:25:44,160 --> 00:25:44,760
Speaker 2: Jason Bourne.

567
00:25:44,800 --> 00:25:48,680
Speaker 6: Sorry, sports in your brain?

568
00:25:49,000 --> 00:25:52,080
Speaker 5: Yeah, what was the question?

569
00:25:52,440 --> 00:25:55,280
Speaker 2: I don't know, it doesn't matter, do you remember the question?

570
00:25:55,320 --> 00:25:55,760
Speaker 2: He asked?

571
00:25:56,160 --> 00:25:59,320
Speaker 6: Well, what I was going to say is that as

572
00:25:59,359 --> 00:26:03,320
Speaker 6: I was finished the book, the CIA actually sent out

573
00:26:03,480 --> 00:26:06,600
Speaker 6: a kind of warning to all of their officers around

574
00:26:06,600 --> 00:26:09,480
Speaker 6: the world and said, you need to be more careful

575
00:26:09,800 --> 00:26:14,360
Speaker 6: meeting with informants because there's all of these artificial intelligence

576
00:26:15,119 --> 00:26:18,320
Speaker 6: tools for tracking people as are moving through public spaces

577
00:26:18,359 --> 00:26:22,399
Speaker 6: now and people are getting killed because of various AI tools,

578
00:26:22,480 --> 00:26:25,600
Speaker 6: including facial recognition. And I've thought about this kind of

579
00:26:25,640 --> 00:26:30,760
Speaker 6: with my yeah, my sources. Just meeting somebody in you know,

580
00:26:30,840 --> 00:26:32,840
Speaker 6: a dive bar where you left your phone at home,

581
00:26:33,080 --> 00:26:34,879
Speaker 6: used to be kind of a safe way to meet someone.

582
00:26:35,520 --> 00:26:37,920
Speaker 6: But now if you're in a place that has cameras

583
00:26:37,960 --> 00:26:41,320
Speaker 6: everywhere and they're running facial recognition technology on those cameras,

584
00:26:41,600 --> 00:26:46,359
Speaker 6: just happening in places like Moscow, Russia, in China, you

585
00:26:46,440 --> 00:26:49,560
Speaker 6: know you, I mean, there's very sensitive ways that this

586
00:26:49,640 --> 00:26:53,680
Speaker 6: can this going to affect your life, and especially if

587
00:26:53,680 --> 00:26:58,600
Speaker 6: you're a Jason Bourne or Michael Bourne has going on,

588
00:26:58,760 --> 00:26:59,480
Speaker 6: but you.

589
00:26:59,440 --> 00:27:01,600
Speaker 2: Know he's just a lead off guy for the astros.

590
00:27:01,640 --> 00:27:04,320
Speaker 6: I think, yeah, center fielder, it would be hard for

591
00:27:04,400 --> 00:27:04,960
Speaker 6: Jason Boord.

592
00:27:05,760 --> 00:27:08,440
Speaker 2: Cashel is with us. She's a New York Times tech reporter.

593
00:27:08,680 --> 00:27:10,680
Speaker 4: She has a new book out, Your Face Belongs to Us,

594
00:27:10,680 --> 00:27:13,040
Speaker 4: a secret of startups, quest end privacy.

595
00:27:13,760 --> 00:27:14,320
Speaker 2: As we know.

596
00:27:14,560 --> 00:27:17,560
Speaker 4: So they brought this, They brought it to Facebook and

597
00:27:17,600 --> 00:27:19,679
Speaker 4: Google correct and what was their response to it.

598
00:27:19,680 --> 00:27:21,680
Speaker 2: They wanted to try to sell it to them.

599
00:27:21,720 --> 00:27:26,200
Speaker 6: Correct, Well, Google and Facebook, I mean, this is something

600
00:27:26,240 --> 00:27:29,080
Speaker 6: that was really interested in me researching the book. They

601
00:27:29,119 --> 00:27:34,040
Speaker 6: had both basically developed this technology themselves, like they had

602
00:27:34,280 --> 00:27:37,000
Speaker 6: developed the ability to take a picture of someone's face

603
00:27:37,200 --> 00:27:39,920
Speaker 6: and you know, match it to other photos of them,

604
00:27:40,520 --> 00:27:43,919
Speaker 6: and they both decided it was too risky, like it

605
00:27:43,960 --> 00:27:49,240
Speaker 6: was too dangerous for them to release that ability to

606
00:27:49,359 --> 00:27:51,960
Speaker 6: the world. Which is which is I mean, as a

607
00:27:52,000 --> 00:27:55,000
Speaker 6: privacy technology reporter, I don't think of Google and Facebook

608
00:27:55,040 --> 00:27:57,880
Speaker 6: as necessarily being super careful when it comes to using

609
00:27:57,920 --> 00:28:02,280
Speaker 6: people's data or being afraid of crossing lines. Google is

610
00:28:02,320 --> 00:28:05,399
Speaker 6: the company that sent street few cars around the world

611
00:28:05,480 --> 00:28:07,919
Speaker 6: to map, you know, take photos of everyone's home and

612
00:28:07,960 --> 00:28:10,760
Speaker 6: put it on the Internet. And so that was interesting

613
00:28:10,760 --> 00:28:16,040
Speaker 6: to me that Clearview, what Clearview did wasn't a technological breakthrough,

614
00:28:16,320 --> 00:28:19,800
Speaker 6: It was an ethical breakthrough. They were willing to do

615
00:28:19,840 --> 00:28:23,320
Speaker 6: something that these other companies had decided was taboo.

616
00:28:23,760 --> 00:28:24,960
Speaker 3: Is this kind of inevitable?

617
00:28:25,040 --> 00:28:27,720
Speaker 7: I mean, we're all kind of sort of okay with

618
00:28:27,800 --> 00:28:29,880
Speaker 7: the fact that our phones are always listening to us.

619
00:28:29,880 --> 00:28:33,040
Speaker 7: You know, you mentioned, you know, taking a trip to Tahiti,

620
00:28:33,280 --> 00:28:34,760
Speaker 7: and then all of a sudden, your phone is showing

621
00:28:34,800 --> 00:28:37,480
Speaker 7: you ads for you know, to hit round trip.

622
00:28:37,240 --> 00:28:39,560
Speaker 3: Flights to Tahiti. So is this sort of like inevitable

623
00:28:39,560 --> 00:28:40,720
Speaker 3: to happen next.

624
00:28:41,240 --> 00:28:44,400
Speaker 6: I don't know if it's inevitable. I think there is

625
00:28:44,440 --> 00:28:47,880
Speaker 6: a possibility we could have a future where we all

626
00:28:47,960 --> 00:28:50,600
Speaker 6: have an app like this on our phone and we're

627
00:28:50,640 --> 00:28:54,000
Speaker 6: face searching each other or you know, yeah, companies are

628
00:28:54,080 --> 00:28:56,200
Speaker 6: face searching us all the time. I mean, I think

629
00:28:56,200 --> 00:28:59,680
Speaker 6: about Madison Square Garden. I think you guys have heard

630
00:28:59,720 --> 00:29:02,360
Speaker 6: of it, got some It've got some teams that play there,

631
00:29:02,880 --> 00:29:06,520
Speaker 6: and they installed facial recognition technology a few years ago

632
00:29:07,000 --> 00:29:09,160
Speaker 6: for security reasons to keep out, you know, people who

633
00:29:09,160 --> 00:29:12,760
Speaker 6: are violent in the arena. And then James Stolen decided

634
00:29:13,280 --> 00:29:16,840
Speaker 6: this would be a good way to punish lawyers law

635
00:29:16,880 --> 00:29:19,880
Speaker 6: firms that sued us, because they're always dealing with you know,

636
00:29:20,040 --> 00:29:23,360
Speaker 6: slip and fall cases and shareholder suits, and so they

637
00:29:23,400 --> 00:29:25,880
Speaker 6: went and banned thousands of lawyers that work at firms

638
00:29:25,920 --> 00:29:28,600
Speaker 6: that have sued them. And if you're you know, a

639
00:29:28,680 --> 00:29:31,760
Speaker 6: lawyer that's at one of the personal injury law firms

640
00:29:31,800 --> 00:29:34,040
Speaker 6: that's on that list, when you try to get in,

641
00:29:34,360 --> 00:29:36,120
Speaker 6: they just turned you away at the door and say

642
00:29:36,120 --> 00:29:38,200
Speaker 6: you're not welcome here until that case gets dropped, even

643
00:29:38,240 --> 00:29:40,080
Speaker 6: if you're not working on the case. And so I

644
00:29:40,080 --> 00:29:42,360
Speaker 6: could imagine this world in which companies are kind of

645
00:29:43,040 --> 00:29:45,600
Speaker 6: tracking us in the real world in the same way

646
00:29:45,640 --> 00:29:48,600
Speaker 6: that we are currently tracked on our phones. And I

647
00:29:48,640 --> 00:29:51,560
Speaker 6: do think that's a dystopian outcome, and I don't think

648
00:29:51,560 --> 00:29:54,480
Speaker 6: it's inevitable because one of the lessons of the book

649
00:29:54,520 --> 00:29:57,720
Speaker 6: is that privacy laws work. You know, Clearbewai got kicked

650
00:29:57,760 --> 00:30:00,640
Speaker 6: out of Europe. The European privacy regulator said, this is

651
00:30:01,240 --> 00:30:04,280
Speaker 6: breaks are privacy laws, but in the US we don't

652
00:30:04,280 --> 00:30:05,560
Speaker 6: have a federal privacy law.

653
00:30:06,360 --> 00:30:08,080
Speaker 2: Mikey, I want you to make your own good joke,

654
00:30:08,120 --> 00:30:09,040
Speaker 2: because it's a good joke.

655
00:30:11,680 --> 00:30:15,200
Speaker 7: Madison Square Garden installed facial recognition to keep good players

656
00:30:15,240 --> 00:30:16,720
Speaker 7: off the next That's why they did it.

657
00:30:18,400 --> 00:30:22,840
Speaker 4: What are you shaking your head about, Michael Boord, We're

658
00:30:22,840 --> 00:30:25,200
Speaker 4: all out one episode.

659
00:30:26,160 --> 00:30:28,080
Speaker 6: Feel free to insert that in earlier.

660
00:30:29,080 --> 00:30:32,040
Speaker 4: So Google and Facebook said no where they have the technology,

661
00:30:32,240 --> 00:30:34,840
Speaker 4: and but this company forms the head right and so

662
00:30:35,120 --> 00:30:36,200
Speaker 4: where are they at right now?

663
00:30:37,240 --> 00:30:41,000
Speaker 6: So claveryy, I is I mean still working with police

664
00:30:41,040 --> 00:30:47,920
Speaker 6: departments around around the country. They have contracts with the

665
00:30:47,920 --> 00:30:51,800
Speaker 6: Department of Homeland Security, the FBI. They have gotten funding

666
00:30:51,840 --> 00:30:55,800
Speaker 6: from the Army and from the Air Force. The Air

667
00:30:55,840 --> 00:31:00,280
Speaker 6: Force had them doing research into augmented reality glasses that

668
00:31:00,560 --> 00:31:03,320
Speaker 6: can just do this in real time as you look

669
00:31:03,360 --> 00:31:06,080
Speaker 6: around at people. I've actually tried. I tried them out

670
00:31:06,120 --> 00:31:10,320
Speaker 6: whan Ton Tat showed them to me. So yeah, I

671
00:31:10,360 --> 00:31:13,480
Speaker 6: mean they're still doing okay. They've been sued in a

672
00:31:13,480 --> 00:31:16,920
Speaker 6: few states in the United States, in Illinois, in California

673
00:31:16,920 --> 00:31:20,400
Speaker 6: and Vermont, and those suits move slowly. They're fighting them,

674
00:31:21,760 --> 00:31:24,960
Speaker 6: so they're kind of embattled, but still in business.

675
00:31:26,160 --> 00:31:28,320
Speaker 2: How concerned should we all be about this?

676
00:31:30,640 --> 00:31:35,680
Speaker 6: I mean, it's your face, right, Like I think if

677
00:31:35,720 --> 00:31:40,840
Speaker 6: you're if you're worried about, you know, a world in

678
00:31:40,920 --> 00:31:44,280
Speaker 6: which you can't walk down the street and just assume

679
00:31:44,280 --> 00:31:49,040
Speaker 6: you're anonymous. If you're yeah, I mean worried about somebody

680
00:31:49,080 --> 00:31:51,560
Speaker 6: just taking your photo and going to pimies, which is

681
00:31:51,600 --> 00:31:54,840
Speaker 6: a public face search engine much like Clearview, but that

682
00:31:54,920 --> 00:31:57,880
Speaker 6: anyone can use, and that they might find photos of

683
00:31:57,880 --> 00:32:00,080
Speaker 6: you on the Internet that you don't want out there

684
00:32:00,080 --> 00:32:03,200
Speaker 6: embarrassed about, Like you should be concerned. I've kind of

685
00:32:03,200 --> 00:32:06,320
Speaker 6: been telling people like, go try pim ice like find

686
00:32:06,320 --> 00:32:08,320
Speaker 6: out if you have photos that you don't want on

687
00:32:08,360 --> 00:32:11,280
Speaker 6: the Internet, and piem ice does allow people to opt out.

688
00:32:11,320 --> 00:32:14,160
Speaker 6: You can get your photos out, and if you are

689
00:32:14,240 --> 00:32:15,720
Speaker 6: lucky enough to live in one of those states with

690
00:32:15,760 --> 00:32:18,800
Speaker 6: the privacy law, you can you can ask clear View

691
00:32:18,840 --> 00:32:20,120
Speaker 6: and PIMI is to delete your faith.

692
00:32:20,520 --> 00:32:22,320
Speaker 5: What were the glasses like when you tried them on?

693
00:32:23,640 --> 00:32:26,040
Speaker 6: Uh, so they've come a long way. I've tried as

694
00:32:26,040 --> 00:32:27,880
Speaker 6: a technology report over the years, I've tried a lot

695
00:32:27,880 --> 00:32:31,920
Speaker 6: of augmented reality glasses and some have been pretty awkward

696
00:32:31,960 --> 00:32:35,520
Speaker 6: over the years. This was made by another company, the Musics,

697
00:32:35,720 --> 00:32:39,840
Speaker 6: and they're pretty like lightweight, and the screen worked really

698
00:32:39,880 --> 00:32:42,120
Speaker 6: well in a way that like Google Glass did not,

699
00:32:43,320 --> 00:32:46,200
Speaker 6: and so Clearview AI the app was loaded up on it,

700
00:32:46,520 --> 00:32:48,840
Speaker 6: and so I looked at Juantan Tat, who's the CEO,

701
00:32:49,320 --> 00:32:51,720
Speaker 6: and it just brought up all these little photos of

702
00:32:51,760 --> 00:32:54,080
Speaker 6: him from around the web along with the caption, so

703
00:32:54,240 --> 00:32:56,800
Speaker 6: very quickly had his name there. And then I looked

704
00:32:56,800 --> 00:33:00,520
Speaker 6: at his spokeswoman, who's a crisis communications consultant that hired

705
00:33:00,880 --> 00:33:03,680
Speaker 6: after I started looking into the company a few years ago,

706
00:33:04,120 --> 00:33:06,800
Speaker 6: and it brought up photos of her like at a

707
00:33:06,800 --> 00:33:09,920
Speaker 6: at a personal event, and then with a client who

708
00:33:10,000 --> 00:33:11,880
Speaker 6: is a pretty big name, and she said, oh, can

709
00:33:11,920 --> 00:33:14,640
Speaker 6: you please not mention that person's name in the book.

710
00:33:15,400 --> 00:33:18,120
Speaker 6: I'm not like public about the fact that I worked

711
00:33:18,200 --> 00:33:19,760
Speaker 6: with this person and.

712
00:33:20,640 --> 00:33:22,959
Speaker 2: You are seconds.

713
00:33:23,720 --> 00:33:24,560
Speaker 5: I mean, I thought it was.

714
00:33:24,520 --> 00:33:27,000
Speaker 6: Really revealing, like these are the people that are selling

715
00:33:27,000 --> 00:33:30,280
Speaker 6: this technology, and you know, she's telling me that's a

716
00:33:30,320 --> 00:33:32,680
Speaker 6: little too invasive for me. So it was just this

717
00:33:32,880 --> 00:33:37,600
Speaker 6: casual reveal about how uncomfortable this can be. I've been

718
00:33:37,600 --> 00:33:39,880
Speaker 6: trying to sell this book and I'm trying to like

719
00:33:39,880 --> 00:33:41,920
Speaker 6: come up with stunts to do. So the night before

720
00:33:42,200 --> 00:33:44,680
Speaker 6: it went on saying, hey, if you you know, send

721
00:33:44,720 --> 00:33:47,719
Speaker 6: me a screenshot of your pre order, I'll run your

722
00:33:47,840 --> 00:33:51,120
Speaker 6: your your face through Pemis and I have a subscription

723
00:33:51,280 --> 00:33:53,760
Speaker 6: so I get to see the full photo and see

724
00:33:53,760 --> 00:33:56,080
Speaker 6: where it came from. And so people were sending me

725
00:33:56,120 --> 00:33:58,080
Speaker 6: their photos and I was doing this and it was

726
00:33:58,240 --> 00:34:01,520
Speaker 6: just it really is wild how far the technology has

727
00:34:01,560 --> 00:34:03,720
Speaker 6: come from where it used to be. It just used

728
00:34:03,760 --> 00:34:06,320
Speaker 6: to not work very well, and it was bringing up photos.

729
00:34:06,640 --> 00:34:11,360
Speaker 6: There's this one photo of somebody who it was from

730
00:34:11,400 --> 00:34:17,120
Speaker 6: like a site that was revealing as to his sexual

731
00:34:17,160 --> 00:34:21,080
Speaker 6: preferences and he is just in the photo in the

732
00:34:21,120 --> 00:34:25,040
Speaker 6: background in this little crowd like watching this exotic dance.

733
00:34:25,640 --> 00:34:27,600
Speaker 6: And I was just like, I can't believe the technology

734
00:34:27,600 --> 00:34:29,080
Speaker 6: works this well and it's able to bring this up.

735
00:34:29,080 --> 00:34:31,000
Speaker 6: And He's like, I had no idea that photo was

736
00:34:31,040 --> 00:34:32,760
Speaker 6: on the internet. I didn't even realize they were taking

737
00:34:32,840 --> 00:34:35,360
Speaker 6: like photos at that event. It's crazy.

738
00:34:36,000 --> 00:34:38,279
Speaker 5: How easy would this technology be to fake? Like if

739
00:34:38,320 --> 00:34:40,120
Speaker 5: I got a nose job or something, or if I

740
00:34:40,200 --> 00:34:42,120
Speaker 5: was going around with like a fake mustache.

741
00:34:42,560 --> 00:34:44,560
Speaker 2: It still is able to pick up stuff like that.

742
00:34:45,160 --> 00:34:47,960
Speaker 5: No, but like if you were to change the structure

743
00:34:48,000 --> 00:34:50,920
Speaker 5: of your face, is that something that it's still because

744
00:34:50,960 --> 00:34:53,000
Speaker 5: it checks so many points or however it works, it's

745
00:34:53,000 --> 00:34:54,359
Speaker 5: still able to identify you.

746
00:34:55,320 --> 00:34:58,720
Speaker 6: So these algorithms, it's neural net technology. It's a little

747
00:34:58,760 --> 00:35:01,440
Speaker 6: hard to know exactly what they're looking for, but it

748
00:35:01,480 --> 00:35:04,680
Speaker 6: does seem like a lot of the information comes from

749
00:35:04,760 --> 00:35:07,000
Speaker 6: kind of around your eyes. There are certain parts of

750
00:35:07,040 --> 00:35:09,759
Speaker 6: your face that are more high information. So yeah, like

751
00:35:09,880 --> 00:35:13,480
Speaker 6: maybe if you've got extensive plastic surgery, it would work.

752
00:35:14,160 --> 00:35:16,320
Speaker 6: It does not work to just wear a COVID mask.

753
00:35:16,480 --> 00:35:22,320
Speaker 6: I've tested that myself. Actually, I talked to Edward Snowden

754
00:35:22,360 --> 00:35:24,840
Speaker 6: the NSA whistleblower about this, because I was wondering how

755
00:35:24,920 --> 00:35:28,279
Speaker 6: much were they talking about facial recognition technology when he

756
00:35:28,360 --> 00:35:30,560
Speaker 6: was at the NASA, and he's like, yeah, I think

757
00:35:30,560 --> 00:35:32,360
Speaker 6: that everyone's going to have to start wearing these like

758
00:35:32,440 --> 00:35:36,399
Speaker 6: three D printed plastic mask. That's what Jason Bourne will

759
00:35:36,400 --> 00:35:39,160
Speaker 6: have to do. He'll have to like get your face

760
00:35:39,520 --> 00:35:41,799
Speaker 6: on on a mask and then wear it, and that's

761
00:35:41,840 --> 00:35:44,760
Speaker 6: how he'll get through the cruise ship security line.

762
00:35:44,960 --> 00:35:47,600
Speaker 2: And Mike michael Bourne too, Yeah, Michael Bourne too. Yeah,

763
00:35:48,280 --> 00:35:50,840
Speaker 2: Borns the whole family.

764
00:35:51,719 --> 00:35:53,799
Speaker 4: But this technology in the right hand, you could see

765
00:35:53,800 --> 00:35:56,440
Speaker 4: the positives of it, if it's in the right hands, correct.

766
00:35:57,280 --> 00:35:57,520
Speaker 2: Yeah.

767
00:35:57,600 --> 00:35:59,919
Speaker 6: I mean I've talked to police officers who have saw

768
00:36:00,600 --> 00:36:03,920
Speaker 6: horrific crimes against children, I mean, gotten children out of

769
00:36:04,000 --> 00:36:08,160
Speaker 6: abusive situations because you know, people make these images, they

770
00:36:08,160 --> 00:36:10,200
Speaker 6: put them out on the internet on the dark Web.

771
00:36:10,800 --> 00:36:14,200
Speaker 6: The officers get it and they're able to find out

772
00:36:14,239 --> 00:36:18,840
Speaker 6: who the perpetrator is or even sometimes who the child

773
00:36:19,000 --> 00:36:22,680
Speaker 6: victim is. Because that's something that some of these investigators

774
00:36:22,680 --> 00:36:25,000
Speaker 6: told me. Clearview AI is the first time we have

775
00:36:25,040 --> 00:36:28,640
Speaker 6: a database, a facial recognition database that has children in it.

776
00:36:29,760 --> 00:36:35,080
Speaker 6: And so yeah, I mean, there are clearly good use cases.

777
00:36:35,440 --> 00:36:37,839
Speaker 6: At the same time, police can make mistakes. There are

778
00:36:37,920 --> 00:36:40,480
Speaker 6: a handful of people who have been arrested for the

779
00:36:40,640 --> 00:36:43,799
Speaker 6: crime of looking like someone else. They have been you know,

780
00:36:43,880 --> 00:36:47,040
Speaker 6: kept in jail for a day, for a week, charged

781
00:36:47,080 --> 00:36:50,480
Speaker 6: with crimes, had to hire lawyers to get these cases dropped.

782
00:36:50,880 --> 00:36:54,000
Speaker 6: So even even when it's being used for you know,

783
00:36:54,160 --> 00:36:56,680
Speaker 6: the right reason, it still needs to be used appropriately.

784
00:36:58,239 --> 00:37:00,480
Speaker 4: And how about the future of this company, Like, where

785
00:37:00,480 --> 00:37:02,440
Speaker 4: do you see what do you see happening with this

786
00:37:02,800 --> 00:37:04,960
Speaker 4: with this private company that's not so small by the

787
00:37:04,960 --> 00:37:07,480
Speaker 4: way they like to they like to talk about how

788
00:37:07,520 --> 00:37:08,560
Speaker 4: small of a company they are.

789
00:37:08,600 --> 00:37:10,280
Speaker 2: They're not. They're growing and they're growing quickly.

790
00:37:11,239 --> 00:37:15,280
Speaker 6: Yeah, I mean they are. They are a pretty scrappy company.

791
00:37:15,320 --> 00:37:18,200
Speaker 6: It's pretty wild. How much yeah, yeah, I mean, it's

792
00:37:18,560 --> 00:37:22,360
Speaker 6: it's wild were able to do with pretty limited resources.

793
00:37:23,640 --> 00:37:26,000
Speaker 6: You know, they wouldn't exist if Peter Thiel hadn't given

794
00:37:26,000 --> 00:37:28,040
Speaker 6: them that first two hundred thousand dollars. But beyond that,

795
00:37:28,080 --> 00:37:30,839
Speaker 6: they've only raised something like thirty million dollars, which is

796
00:37:30,880 --> 00:37:33,759
Speaker 6: not a lot in the kind of tech startup land.

797
00:37:35,080 --> 00:37:39,200
Speaker 6: So they are dependent on continuing get these contracts from

798
00:37:39,480 --> 00:37:43,319
Speaker 6: police departments, and you know, if they get a big

799
00:37:43,400 --> 00:37:47,120
Speaker 6: judgment against them, like in Illinois that has that strong law,

800
00:37:47,680 --> 00:37:49,640
Speaker 6: or if they're forced to pay the fines that have

801
00:37:49,680 --> 00:37:52,400
Speaker 6: been levied against them in Europe, it would be the

802
00:37:52,520 --> 00:37:55,880
Speaker 6: end for them. But what they've done is I said earlier,

803
00:37:56,200 --> 00:37:58,759
Speaker 6: you know, it could be replicated. So it's not just

804
00:37:58,800 --> 00:38:01,759
Speaker 6: about this one company, it's about what they've shown us

805
00:38:01,760 --> 00:38:02,440
Speaker 6: as possible.

806
00:38:02,960 --> 00:38:05,279
Speaker 5: What kind of business is this, like contract wise, Like

807
00:38:05,280 --> 00:38:06,640
Speaker 5: what do these contracts look like?

808
00:38:08,520 --> 00:38:13,040
Speaker 6: So the Department of Homeland Security has total paid something

809
00:38:13,120 --> 00:38:17,160
Speaker 6: like two million dollars to clear VIEWAI. The FBI contract

810
00:38:17,200 --> 00:38:21,080
Speaker 6: is much smaller. It's just tens of thousands of dollars

811
00:38:21,080 --> 00:38:23,920
Speaker 6: for like an annual subscription. It was something that struck

812
00:38:23,960 --> 00:38:26,880
Speaker 6: me when I first started investigating CLEARVIEWAI. It was way

813
00:38:27,040 --> 00:38:30,080
Speaker 6: cheaper than any of the other facial recognition vendors that

814
00:38:30,080 --> 00:38:33,080
Speaker 6: I'd seen. They were selling subscriptions to some you know

815
00:38:33,200 --> 00:38:36,880
Speaker 6: kind of like tiny police departments for like two thousand

816
00:38:36,920 --> 00:38:39,719
Speaker 6: dollars a year. Six thousand dollars a year. I mean,

817
00:38:40,000 --> 00:38:44,840
Speaker 6: like this is just so much less than most government

818
00:38:44,880 --> 00:38:46,120
Speaker 6: contractors are charging.

819
00:38:46,480 --> 00:38:48,040
Speaker 4: It kind of makes me feel like that's not what

820
00:38:48,040 --> 00:38:49,879
Speaker 4: they're in business for It's not for the good, it's

821
00:38:49,880 --> 00:38:50,279
Speaker 4: for the bad.

822
00:38:50,280 --> 00:38:52,560
Speaker 2: It's for the evil, right, like you have the same feeling.

823
00:38:53,280 --> 00:38:56,400
Speaker 6: Well, what you know, when I met with Wanton Tat,

824
00:38:56,640 --> 00:38:58,960
Speaker 6: you know, when they find talking to me, realized I

825
00:38:58,960 --> 00:39:01,680
Speaker 6: wasn't going away. I remember he said, you know, this

826
00:39:01,920 --> 00:39:04,960
Speaker 6: is the best use of this technology. We are selling

827
00:39:04,960 --> 00:39:08,720
Speaker 6: it to the police. It is getting used to catch pedophiles,

828
00:39:08,800 --> 00:39:11,560
Speaker 6: you know, not being used by pedophiles. But when I

829
00:39:11,560 --> 00:39:14,480
Speaker 6: started digging more into the company, you know, for the

830
00:39:14,520 --> 00:39:17,839
Speaker 6: book I did, I did find that originally they were

831
00:39:17,920 --> 00:39:21,200
Speaker 6: just looking for people that wanted to buy this product,

832
00:39:21,280 --> 00:39:23,320
Speaker 6: and it wasn't necessarily for the police. They were pitching

833
00:39:23,360 --> 00:39:28,000
Speaker 6: it to you know, hotels and commercial real estate buildings

834
00:39:28,080 --> 00:39:30,839
Speaker 6: and shopping markets, and they were just giving it to

835
00:39:31,239 --> 00:39:33,280
Speaker 6: the people they are trying to pitch and the people

836
00:39:33,280 --> 00:39:36,480
Speaker 6: they are trying to get money from. So it was

837
00:39:36,600 --> 00:39:41,279
Speaker 6: you know, billionaires and venture capitalists. Joe Montana randomly was

838
00:39:41,360 --> 00:39:45,040
Speaker 6: one of their users. I meant to mention that to

839
00:39:45,080 --> 00:39:52,600
Speaker 6: you what wait a second, Yeah, Joe Montana's disester. Now

840
00:39:52,600 --> 00:39:55,520
Speaker 6: he has like a VC firm, and so he has

841
00:39:55,600 --> 00:39:58,520
Speaker 6: VC friends. And Juan told me, you know, he'd been

842
00:39:58,520 --> 00:40:01,400
Speaker 6: trying to pitch Sequoia Capit, which he considered kind of

843
00:40:01,440 --> 00:40:04,359
Speaker 6: the Harvard of the venture capital firms. He really wanted

844
00:40:04,400 --> 00:40:06,560
Speaker 6: to get an investment from them. And there was a

845
00:40:06,560 --> 00:40:09,400
Speaker 6: partner there that liked using clearview Ai a lot, and

846
00:40:09,400 --> 00:40:12,439
Speaker 6: he would use it work conferences. And one day Juan

847
00:40:12,560 --> 00:40:16,280
Speaker 6: gets an email from somebody named Joe being like, hey,

848
00:40:16,440 --> 00:40:19,600
Speaker 6: you know, Doug at Sequoia told me that the clearuai

849
00:40:19,760 --> 00:40:21,480
Speaker 6: is great and I might want to invest in it

850
00:40:21,520 --> 00:40:23,720
Speaker 6: and I'd really like to try it. And so Juan

851
00:40:23,840 --> 00:40:27,600
Speaker 6: sent this note to his business partner, Richard Schwartz, this

852
00:40:27,760 --> 00:40:30,400
Speaker 6: like guy he used to work for Rudy Giuliani, and

853
00:40:30,520 --> 00:40:32,799
Speaker 6: was like, oh, I'm so annoyed Doug at Sequoia won't

854
00:40:32,840 --> 00:40:35,480
Speaker 6: invest us, and now he's telling his random friends about us,

855
00:40:35,520 --> 00:40:37,400
Speaker 6: and they were trying to keep the company a secret,

856
00:40:37,640 --> 00:40:40,600
Speaker 6: and Richard Swartz is like, Wan, that's Joe Montana. He

857
00:40:40,760 --> 00:40:43,680
Speaker 6: is very famous person. And Juan grew up in Australia.

858
00:40:43,719 --> 00:40:47,440
Speaker 6: He had no idea and yeah, so yeah, Joe Montanna

859
00:40:47,520 --> 00:40:49,560
Speaker 6: did get to use the app. I guess he has

860
00:40:49,719 --> 00:40:54,120
Speaker 6: trouble sometimes for calling faces. And want showed me this

861
00:40:54,200 --> 00:40:57,160
Speaker 6: photo that he took with Joe Montana. And you know,

862
00:40:57,239 --> 00:41:00,000
Speaker 6: Joe is huge, has this like tiny smartphone in his huge,

863
00:41:00,040 --> 00:41:03,799
Speaker 6: huge hand, and one loves showing that photo to the

864
00:41:03,800 --> 00:41:07,560
Speaker 6: police departments he works with, because everybody there loves Joe Montana.

865
00:41:07,920 --> 00:41:10,600
Speaker 5: I like the idea of Joe Montana using this technology

866
00:41:10,680 --> 00:41:12,880
Speaker 5: just so like his assistant or whatever is like following

867
00:41:12,960 --> 00:41:15,360
Speaker 5: around and they just quickly take pictures of people, like

868
00:41:15,400 --> 00:41:17,160
Speaker 5: look at people as they're coming up to Joe, like

869
00:41:17,320 --> 00:41:19,239
Speaker 5: Joe remembering He's like, oh yeah, of course I met

870
00:41:19,239 --> 00:41:21,200
Speaker 5: you in nineteen ninety three, and they're going back to

871
00:41:21,239 --> 00:41:22,560
Speaker 5: like old pictures of fans.

872
00:41:22,600 --> 00:41:26,000
Speaker 4: A great way to utilize it, though, Like guys like Billy,

873
00:41:26,400 --> 00:41:28,560
Speaker 4: it's like when we go outside our studio, I don't

874
00:41:28,560 --> 00:41:29,480
Speaker 4: know half the people in there.

875
00:41:29,680 --> 00:41:31,200
Speaker 2: I would love that. That's what. That's what.

876
00:41:31,560 --> 00:41:33,800
Speaker 6: That's what I'm saying. It's not like it's just pure evil.

877
00:41:33,840 --> 00:41:35,480
Speaker 6: I mean there are some good uses.

878
00:41:35,400 --> 00:41:39,000
Speaker 2: It's just also evil, but that can be used.

879
00:41:39,719 --> 00:41:42,239
Speaker 4: But that's the Like someone's job though, is to tell

880
00:41:42,280 --> 00:41:44,520
Speaker 4: the vite Like in VIEP have you seen Veep? Yes,

881
00:41:44,600 --> 00:41:47,399
Speaker 4: they tell the vice president, like who the person you're

882
00:41:47,440 --> 00:41:47,880
Speaker 4: talking to?

883
00:41:47,920 --> 00:41:52,080
Speaker 2: Your cousin? Right, now you know. Now you're taking away jobs, Billy.

884
00:41:52,480 --> 00:41:54,759
Speaker 4: If you have this, if you have this technology, you

885
00:41:54,800 --> 00:41:58,160
Speaker 4: know anyway, this was fascinating. I haven't seen Billy this

886
00:41:58,239 --> 00:42:00,200
Speaker 4: is interested in anything and a lot of time.

887
00:42:02,520 --> 00:42:04,279
Speaker 2: Can I ask you something before you go? Is it

888
00:42:04,320 --> 00:42:05,239
Speaker 2: intimidating to.

889
00:42:05,239 --> 00:42:08,040
Speaker 5: Go and meet with these people knowing that they have

890
00:42:08,120 --> 00:42:10,920
Speaker 5: the technology to know everything about you and knowing that

891
00:42:10,960 --> 00:42:12,960
Speaker 5: you're kind of I don't want to say, being a pest,

892
00:42:13,000 --> 00:42:15,320
Speaker 5: but being a thorn in their side writing books and

893
00:42:15,320 --> 00:42:17,799
Speaker 5: stuff about this and knowing they can just have all

894
00:42:17,840 --> 00:42:20,560
Speaker 5: of your information at any moment has to be intimidating.

895
00:42:21,520 --> 00:42:29,000
Speaker 6: Thanks for reminding me. Oh sorry, yeah, I mean none

896
00:42:29,080 --> 00:42:31,840
Speaker 6: of us is, you know, perfect? Like I sometimes I worry,

897
00:42:32,040 --> 00:42:34,560
Speaker 6: like what photo is going to be on the Internet

898
00:42:34,600 --> 00:42:38,799
Speaker 6: that I have forgotten about in the decades I've been

899
00:42:38,800 --> 00:42:40,799
Speaker 6: on there, Like yeah, I mean I do this.

900
00:42:40,880 --> 00:42:42,520
Speaker 2: Entire time looking through my photos.

901
00:42:43,400 --> 00:42:46,520
Speaker 6: How are you on pimies right now? Just scrolling through deleting?

902
00:42:49,160 --> 00:42:52,359
Speaker 2: Yeah, I'm terrifying. I got it. I'm so torn on it.

903
00:42:52,440 --> 00:42:54,520
Speaker 4: I see the good knit, I see how cool it is,

904
00:42:54,880 --> 00:42:56,960
Speaker 4: and yet at the same time, it is terrifying that

905
00:42:57,000 --> 00:42:59,960
Speaker 4: someone may have all my information and picture.

906
00:43:00,080 --> 00:43:01,080
Speaker 2: I don't want anyone to you.

907
00:43:01,960 --> 00:43:04,359
Speaker 6: Yeah, I mean I think it is hard to say

908
00:43:04,400 --> 00:43:07,479
Speaker 6: whether the technology is good or it's evil. It's because

909
00:43:07,480 --> 00:43:10,440
Speaker 6: it's ultimately about who is using it, and it's a

910
00:43:11,040 --> 00:43:12,920
Speaker 6: you know, you can only trust the technology if you

911
00:43:12,960 --> 00:43:14,799
Speaker 6: trust the person who's wielding it.

912
00:43:15,800 --> 00:43:18,520
Speaker 2: Joe is using it for good. I'm coming for sharing.

913
00:43:19,800 --> 00:43:20,719
Speaker 6: Can we trust Joe?

914
00:43:21,120 --> 00:43:25,160
Speaker 2: Yeah? Cash, this was great again.

915
00:43:25,280 --> 00:43:27,719
Speaker 4: Check out the new book Your Face Belongs to Us,

916
00:43:27,719 --> 00:43:30,960
Speaker 4: A Secret of Startups, Quest to End Privacy as we

917
00:43:31,040 --> 00:43:33,640
Speaker 4: know a New York Times tech reporter and Cash hell

918
00:43:33,719 --> 00:43:36,719
Speaker 4: with us. We really appreciate it. Very interesting stuff. Good

919
00:43:36,800 --> 00:43:39,520
Speaker 4: luck with the book, and thank you for your time.

920
00:43:40,080 --> 00:43:42,120
Speaker 6: Thank you, this is so funs.

921
00:43:42,120 --> 00:43:45,239
Speaker 5: Two guys, how did you feel when Cash remembered you

922
00:43:45,400 --> 00:43:48,560
Speaker 5: from an interview that I, between us you one hundred

923
00:43:48,560 --> 00:43:49,799
Speaker 5: percent did not remember doing.

924
00:43:50,800 --> 00:43:51,600
Speaker 2: I was.

925
00:43:53,040 --> 00:43:57,640
Speaker 5: Thank you, Billy, just between us, it's just amongst friends here.

926
00:43:58,640 --> 00:44:04,319
Speaker 4: I know, Uh, I wish I had that technology so

927
00:44:04,360 --> 00:44:05,680
Speaker 4: I could have run her face through.

928
00:44:06,200 --> 00:44:08,400
Speaker 5: I was thinking maybe Cash I had the technology and

929
00:44:08,840 --> 00:44:11,279
Speaker 5: ran our faces through some things beforehand.

930
00:44:12,000 --> 00:44:17,160
Speaker 4: Yes, so you sensed my uh discomfort? Yeah, that she

931
00:44:17,200 --> 00:44:19,000
Speaker 4: knew me and I had no idea who she was

932
00:44:19,040 --> 00:44:20,319
Speaker 4: even though she was on the show with us for

933
00:44:20,360 --> 00:44:21,200
Speaker 4: twenty five minutes.

934
00:44:21,400 --> 00:44:23,560
Speaker 5: Well knew you and then had called you out on

935
00:44:23,640 --> 00:44:26,400
Speaker 5: something that you did seemingly months ago, and you're.

936
00:44:26,280 --> 00:44:33,120
Speaker 4: Like, ooh, remember that one, thanks for bringing it back up.

937
00:44:33,400 --> 00:44:34,439
Speaker 2: Yeah, and you.

938
00:44:34,360 --> 00:44:37,279
Speaker 3: Called her creepy I did.

939
00:44:38,880 --> 00:44:42,480
Speaker 5: I mean, come on, whoa I called Cash Breebe in

940
00:44:42,560 --> 00:44:43,320
Speaker 5: the other interview.

941
00:44:43,440 --> 00:44:47,960
Speaker 2: Yeah, in the other interview. Yeah, I don't remember. Yeah,

942
00:44:48,040 --> 00:44:48,480
Speaker 2: I like you.

943
00:44:48,560 --> 00:44:50,319
Speaker 5: I like you it either way, you seem to live life,

944
00:44:50,360 --> 00:44:53,320
Speaker 5: which is basically like if I don't remember, it didn't happen, right.

945
00:44:53,200 --> 00:44:58,319
Speaker 2: Well, yes, you guys were intrigued by that. It was.

946
00:44:58,440 --> 00:45:01,359
Speaker 2: I thought she was great. I'll never forget her again.

947
00:45:01,400 --> 00:45:02,160
Speaker 2: I'll tell you that much.

948
00:45:02,320 --> 00:45:06,359
Speaker 5: I'm going to write down let's put cash in like

949
00:45:06,480 --> 00:45:10,040
Speaker 5: four months, and let's see if let's see if we stick.

950
00:45:09,880 --> 00:45:12,839
Speaker 2: By that, I will never forget there again. Because I'm not.

951
00:45:12,760 --> 00:45:15,560
Speaker 7: Sure Connecticut is one of the states that you can

952
00:45:15,680 --> 00:45:17,719
Speaker 7: pull all your stuff. I think we should do an

953
00:45:17,719 --> 00:45:20,080
Speaker 7: episode where we run my name, where we run my

954
00:45:20,160 --> 00:45:22,759
Speaker 7: face through it and we and we we scrubbed me

955
00:45:22,880 --> 00:45:25,320
Speaker 7: from from this stuff, because that scary stuff.

956
00:45:25,440 --> 00:45:27,759
Speaker 4: Yeah, man, Billy, have a question for you is we're

957
00:45:27,760 --> 00:45:31,560
Speaker 4: asking questions. Sure, how'd you feel about Jason Boord and

958
00:45:31,600 --> 00:45:32,200
Speaker 4: Michael Born?

959
00:45:32,520 --> 00:45:35,440
Speaker 2: Har fright? It was. It was a low for me, honestly.

960
00:45:36,880 --> 00:45:40,120
Speaker 5: Okay, you know, here's a strange thing. Here's a strange thing.

961
00:45:40,640 --> 00:45:44,279
Speaker 5: It felt worse than the Doug Moron situation. And that

962
00:45:44,360 --> 00:45:47,319
Speaker 5: should have that should have felt worse because I did

963
00:45:47,360 --> 00:45:50,279
Speaker 5: that straight to Doug Peterson's face. But I was like,

964
00:45:51,280 --> 00:45:53,560
Speaker 5: I don't feel that bad about this one. The Jason

965
00:45:53,600 --> 00:45:55,480
Speaker 5: Boord and Michael Bourne. When I do feel bad, and

966
00:45:55,560 --> 00:45:57,200
Speaker 5: now obviously I am prisoner of the moment because it

967
00:45:57,320 --> 00:45:57,880
Speaker 5: just happened.

968
00:45:58,120 --> 00:46:00,960
Speaker 2: I feel a lot worse now than that one. But yeah,

969
00:46:01,200 --> 00:46:02,280
Speaker 2: not not my best.

970
00:46:02,719 --> 00:46:03,920
Speaker 3: For those did you catch it?

971
00:46:05,800 --> 00:46:08,680
Speaker 2: What did I catch what? Jason Board? Yes, No you didn't.

972
00:46:09,239 --> 00:46:10,319
Speaker 2: No I did, Billy I did.

973
00:46:10,360 --> 00:46:12,440
Speaker 4: And for those of you wondering what Billy's talking about,

974
00:46:12,680 --> 00:46:15,000
Speaker 4: we had Doug Peterson, a god bless football Billy took

975
00:46:15,040 --> 00:46:17,480
Speaker 4: control of the interview and introduced him as Doug Moreau.

976
00:46:17,920 --> 00:46:20,440
Speaker 5: Well, I was trying to get things on track and

977
00:46:20,440 --> 00:46:24,920
Speaker 5: it backfired spectacularly in my face because we were not

978
00:46:25,080 --> 00:46:27,759
Speaker 5: getting anywhere with him, and it was just like pleasantries

979
00:46:27,800 --> 00:46:29,560
Speaker 5: all day long and it's like we need to do that.

980
00:46:29,960 --> 00:46:31,480
Speaker 5: You have like five minutes left, we need to do

981
00:46:31,520 --> 00:46:33,480
Speaker 5: this interview. Let me ask an actual question. And then

982
00:46:33,480 --> 00:46:34,440
Speaker 5: I called him the wrong name.

983
00:46:35,640 --> 00:46:37,919
Speaker 2: But in my defense, Doug, you called him coach.

984
00:46:38,600 --> 00:46:41,480
Speaker 5: I was trying to be respectful. I don't know why,

985
00:46:42,040 --> 00:46:46,480
Speaker 5: but in my defense, like I'm just like Ted's there's

986
00:46:46,520 --> 00:46:48,279
Speaker 5: not many Dugs anymore, you know what I mean, Like

987
00:46:48,320 --> 00:46:51,400
Speaker 5: it's an easy mistake to make. And then like you

988
00:46:51,480 --> 00:46:54,640
Speaker 5: have essentially back to back Doug coaches for the Jaguars

989
00:46:54,640 --> 00:46:56,640
Speaker 5: where you had an urban in between.

990
00:46:56,640 --> 00:46:58,560
Speaker 4: What you consider how many dogs there are in the

991
00:46:58,600 --> 00:47:00,680
Speaker 4: world for the Jaguars that have two of them as

992
00:47:00,719 --> 00:47:01,520
Speaker 4: their head coach.

993
00:47:01,680 --> 00:47:06,920
Speaker 5: Right, right, let's blame bad con has a thing I

994
00:47:06,920 --> 00:47:10,040
Speaker 5: guess for Dougs. Just blame it on Uncle Teddy.

995
00:47:09,760 --> 00:47:12,200
Speaker 2: Yeah, it's the body

996
00:47:16,800 --> 00:47:16,840
Speaker 7: M