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Speaker 1: There Are No Girls on the Internet, as a production

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Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridgett and this is

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Speaker 1: there Are No Girls on the Internet. You're listening to

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Speaker 1: their No Girls on the Internet, where we explore the

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Speaker 1: intersection of technology, identity, and social media. And this is

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Speaker 1: another installment of our weekly news Roundup where we dig

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Speaker 1: into all the stories online that you might have missed,

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Speaker 1: so you don't have to. Okay, let's get into it.

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Speaker 1: Nobody really looks cool when they eat spaghetti, Mike, not

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Speaker 1: even Will Smith. I was just looking at this SAA

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Speaker 1: video of Will Smith eating spaghetti and this one was

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Speaker 1: actually pretty good. It was pretty convincing, and I'm just

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Speaker 1: so curious how Will Smith eating spaghetti becomes the benchmark

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Speaker 1: of AI video capabilities. Have you seen these Will Smith

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Speaker 1: eating spaghetti videos?

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Speaker 2: I have, you know, and you gave me a heads

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Speaker 2: up that we're going to talk about this way. Did

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Speaker 2: look into it a little bit? Yeah, there's just been

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Speaker 2: like a steady improvement in AI generated videos of Will

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Speaker 2: Smith eating spaghetti over the past several years. But I

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Speaker 2: couldn't find any you know, definitive or even speculative information

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Speaker 2: about why.

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Speaker 1: Ooh, I can answer this for you.

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Speaker 2: So you're right.

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Speaker 1: We have come a really long way on the Will

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Speaker 1: Smith spaghetti eating index, because back in twenty twenty three,

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Speaker 1: somebody shared an AI generated video titled Will Smith eating

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Speaker 1: spaghetti on the stable diffusion subreddit, and they had made

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Speaker 1: this video using model scopes text to video tool. This

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Speaker 1: was back in twenty twenty three, which I know doesn't

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Speaker 1: sound that long ago. It was just two years ago,

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Speaker 1: but AI video capabilities have come a long way since then.

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Speaker 1: The video looks like Will Smith looks like Claymation kind of,

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Speaker 1: and the way that he eats the spaghetti is grotesque.

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Speaker 1: He kind of eats it like a dog, like he

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Speaker 1: comes tot he like puts his whole face in it,

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Speaker 1: and he's kind of using his hands.

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Speaker 2: That is undignified.

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Speaker 1: It's an undignified way to eat spaghetti, that's for sure.

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Speaker 1: But this growtesque, creepy AF video ended up creating essentially

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Speaker 1: a litmus test for how AI video generation is progressing.

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Speaker 1: I am so curious how Will Smith feels about this.

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Speaker 1: I would hate it if video of meeting spaghetti had

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Speaker 1: become a benchmark about the progression of AI technology. How

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Speaker 1: would you feel about that?

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Speaker 2: I would not like it, No, it would be a nightmare.

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Speaker 2: But I do have a theory about why it's Will Smith.

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Speaker 2: I think he has a like poppy appeal and an

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Speaker 2: accessibility that is able to take this pretty arcane topic

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Speaker 2: of AI video generation and make it like accessible to

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Speaker 2: the common man, like maybe we you know, if there

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Speaker 2: were numbers or statistics about how good of a video

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Speaker 2: it was, that wouldn't really resonate. But like everybody can

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Speaker 2: connect with Will Smith and spaghetti, these are two very

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Speaker 2: accessible things.

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Speaker 1: Ooh, you are coming dangerously close to making me admit

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Speaker 1: what I know is an unpopular opinion among a lot

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Speaker 1: of people about Will Smith. I have an unpopular Will

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Speaker 1: Smith opinion in there, Oh you do.

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Speaker 2: What is your unpopular Will Smith opinion?

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Speaker 1: Oh my gosh, I might have Joey cut this because genuinely,

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Speaker 1: I'm nervous to admit this, and I know people are

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Speaker 1: gonna come for me. So we all we all know

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Speaker 1: what I'm talking about. The Will Smith infamous slap. People

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Speaker 1: act like Will Smith killed somebody. When you go on

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Speaker 1: the Internet and look how people respond. This is one

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Speaker 1: of those things where it was I only got wind

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Speaker 1: of this recently at white people and black people. There

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Speaker 1: are a lot of things that we have a lot

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Speaker 1: of common ground on, but there's certain things where we

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Speaker 1: just live in completely different worlds and completely different sort

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Speaker 1: of online silos. And I only recently found out that

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Speaker 1: white people, not all, but a lot of white people

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Speaker 1: really never forgave Will Smith for smacking Chris Rock at

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Speaker 1: the Oscars. Meanwhile, black people, it never comes up, it's

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Speaker 1: never mentioned.

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Speaker 2: We've all moved on.

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Speaker 1: It's it's like very clear where we stand on the issue.

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Speaker 1: And I only recently found this south that, oh this

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Speaker 1: is we we have very different opinions about Will Smith.

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Speaker 1: And if you don't spend a lot of time in

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Speaker 1: online spaces like Reddit, you might not know that people

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Speaker 1: really really have not forgiven Will Smith for what went

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Speaker 1: down on the Oscars. I'll just put it that way.

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Speaker 2: Yeah, it's funny you say that, because when I was

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Speaker 2: trying to look into the spaghetti thing, I was like, wow,

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Speaker 2: there's a lot of content about him slapping Chris Rock

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Speaker 2: on here.

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Speaker 1: People have never forgotten it.

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Speaker 2: Yeah. So in conclusion, and you're fine with physical violence,

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Speaker 2: you think it's cool. Do you think it should be

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Speaker 2: glorified on television?

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Speaker 1: Yeah? I'm a big advocate of physical silence. I think

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Speaker 1: I think we need more of it. The world will

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Speaker 1: be a better place.

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Speaker 2: Yeah, all right, cool.

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Speaker 1: Obviously, no, someone's gonna clip that, and that's gonna be.

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Speaker 1: That's gonna be. I can never run for office. Somebody

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Speaker 1: is gonna clip that out of context.

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Speaker 2: Thanks a lot, Mike, Hey, you said it.

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Speaker 1: So, while we're getting into our unpopular opinions, do you

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Speaker 1: have opinions on wearables like technology that you wear on

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Speaker 1: your face or your head or your body.

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Speaker 2: I not too much. I've never really been able to

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Speaker 2: make it work for me. I've always been intrigued. I've like,

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Speaker 2: you know, sometimes I'll play video games where you've got, like,

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Speaker 2: you know, it's a first person perspective and you've got

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Speaker 2: all kinds of like information on the screen, or when

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Speaker 2: you're driving a car that has like a lot of

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Speaker 2: information that might be relevant to you while you're driving.

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Speaker 2: That always seems kind of cool to me to be

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Speaker 2: able to have access to that while just like existing

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Speaker 2: in the world. But you know, there's a lot of

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Speaker 2: negatives that come with it too, one of them being that,

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Speaker 2: like you look like a dork with some like wearable

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Speaker 2: glasses on your head.

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Speaker 1: Huge dork. I'm so sad to admit that one of

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Speaker 1: my first way back in the day, one of my

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Speaker 1: first Twitter profile pictures was me wearing Google glass. Oh,

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Speaker 1: don't even get me started.

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Speaker 2: Yeah, I remember Google glass. I was in grad school

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Speaker 2: at the time, and I remember scheming with one of

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Speaker 2: my friends about how we were going to like pitch

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Speaker 2: a research project to Google to be able to get

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Speaker 2: our hands on some of Google Glass.

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Speaker 1: At that point, at Google, you might have actually been

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Speaker 1: able to do it, you know. I once demoed some

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Speaker 1: like VR goggles. I firmly believe that nobody wants to

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Speaker 1: sit in their house or be around other people with

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Speaker 1: like a massive thing trapped on their face. And I

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Speaker 1: once demoed some VR goggles and it just reminded me

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Speaker 1: of that. I think you should leave skit. You know,

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Speaker 1: there's too much shit on my face. I don't even

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Speaker 1: want to be around anymore. That's instantly how I felt.

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Speaker 2: Classic Skin, Classic skit.

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Speaker 1: TI. We are Tim Robinson. We are I swear that

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Speaker 1: Tim Robinson has found a way to describe so many

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Speaker 1: awkward scenarios that I have found myself in. Oh yeah,

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Speaker 1: we are fans of him are over here. I will say,

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Speaker 1: though Meta's ray bands. As much as I do not

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Speaker 1: like wearables and the idea of wearables, and I'm kind

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Speaker 1: of against them just in general, I think they probably

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Speaker 1: have their place and like a use case if you're

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Speaker 1: a truck driver or a long haul driver or something,

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Speaker 1: I get it. However, I will say Meta's ray bands,

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Speaker 1: if you've worn them, they look and feel just like

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Speaker 1: normal glasses, which, on the one hand, that's kind of cool.

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Speaker 1: It kind of solves the problem that I had just

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Speaker 1: articulated of that feeling of there's too much shit on

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Speaker 1: your face. However, them looking like regular glasses is also

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Speaker 1: a problem. Four or four media has to report out

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Speaker 1: about the fact that there are Instagram accounts, like big

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Speaker 1: Instagram accounts with lots of followers whose whole thing is

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Speaker 1: using Meta ray Ban glasses to film themselves going into

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Speaker 1: massage parlors and asking the women who work there to

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Speaker 1: perform sex acts on them. In these videos, the staff

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Speaker 1: do not seem like they know they're being filmed, and

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Speaker 1: because these glasses they look like just regular glasses, they

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Speaker 1: probably don't know they're being filmed. In most cases, the

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Speaker 1: staffers are confused when when the man is like asking

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Speaker 1: for a sex act, or they laugh at the man,

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Speaker 1: or they just dismiss him. But in a few instances,

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Speaker 1: the staffers are like okay and negotiate a price for

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Speaker 1: the sex act the man is asking for. These videos

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Speaker 1: have been shared and viewed by millions of people. And

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Speaker 1: what's worse, in some of these videos, it is obvious

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Speaker 1: where the location of these massage parlors are because the

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Speaker 1: men show themselves walking into the entrances of these places,

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Speaker 1: so they show the where they're at, so anybody could

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Speaker 1: essensibly find these women. And this is a problem because,

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Speaker 1: as four four reports, this is extremely dangerous to the

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Speaker 1: women in these videos, who can be targeted both by

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Speaker 1: law enforcement and racist sexist extremists. Back in twenty twenty one,

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Speaker 1: they reremined a man shot. A man who shot and

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Speaker 1: killed eight people at massage parlors told police that he

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Speaker 1: had specifically targeted them because he had a sexual addiction.

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Speaker 1: Now you might be thinking, how can this Kennedy grosser.

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Speaker 1: While these videos are basically a money making enterprise, they're

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Speaker 1: essentially social media advertisements that offer for people to spend

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Speaker 1: money to buy what they say is the full video

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Speaker 1: of the encounter. This is so gross they linked out

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Speaker 1: to an adult pay perview service called No Fans, which

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Speaker 1: allows users to buy and view non consensual content without

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Speaker 1: creating an account. One video on Instagram that's pitched as

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Speaker 1: a quote Latina house call sends viewers to No Fans

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Speaker 1: to buy the full video. On No Fans, users can

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Speaker 1: buy the quote Latina Tuggy bundle for twenty eight forty nine.

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Speaker 1: I should say, though it's not totally clear if the

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Speaker 1: actual massage staff is then the people who are in

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Speaker 1: these like quote full videos, it does seem like they're

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Speaker 1: creating these videos non consensually with massage staff who do

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Speaker 1: not know they're being recorded, and then the and then saying, oh,

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Speaker 1: if you want to see the full video of what happened,

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Speaker 1: go to this site. And then the people in that

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Speaker 1: video might not even be the actual staff that we

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Speaker 1: saw earlier. Does that make sense?

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Speaker 2: It does? Yeah. I can definitely see some deception taking

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Speaker 2: place in this ecosystem.

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Speaker 1: Oh yeah, you think you think these guys are deceiving people?

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Speaker 2: Yeah, I just something about it. I don't know my

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Speaker 2: six steps. I feel like they would not be above

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Speaker 2: leading with one video and then one does people make

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Speaker 2: that purchase it's actually different actors on the video, or

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Speaker 2: maybe nothing at all. Maybe they just take their credit

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Speaker 2: card and run with it. Guy's the limit.

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Speaker 1: It will never not shock me how much people are

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Speaker 1: willing to spend to be told that they're watching video

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Speaker 1: that was non consensually made, Because there's plenty of pornography

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Speaker 1: out there where it is consenting adults who know they

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Speaker 1: are being filmed, who have consented to make adult content,

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Speaker 1: adding on this kind of non consensual video they made

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Speaker 1: with somebody who works at a massage parlor who doesn't

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Speaker 1: even know they're being filmed, to give it the appearance of, oh,

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Speaker 1: this woman who didn't know I was filming her, if

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Speaker 1: you want to watch the whole encounter with her. It

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Speaker 1: just never ceases to amaze me that that would be

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Speaker 1: something that would give people a marketing edge, I guess,

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Speaker 1: I'll say. And I also think these videos they really

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Speaker 1: expose how Meta has essentially created an entire ecosystem that

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Speaker 1: fuels this creepy, misogynistic, privacy violating content online. They're selling

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Speaker 1: these smart glasses that let people secretly record others in public.

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Speaker 1: They are also running platforms like Instagram that reward the

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Speaker 1: most like shocking and extreme and outrageous posts. And then

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Speaker 1: they only step in to take this stuff down after

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Speaker 1: journalists from four oh four start asking questions because there's

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Speaker 1: an entire marketplace for low cost and by low cost

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Speaker 1: I mean like forty dollars low cost ways to obscure

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Speaker 1: what little privacy protective features metaglasses do have. Right so,

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Speaker 1: right now, metaglasses have a light on them that is

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Speaker 1: supposed to light up to indicate when somebody is recording.

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Speaker 1: So ostensibly, if I saw you wearing metaglasses and the

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Speaker 1: light was on, I would know this person is recording.

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Speaker 1: But you can just buy little things to obscure that

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Speaker 1: so that no one knows you're recording. No one knows

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Speaker 1: their metaglasses. When four four spoke to Meta about this,

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Speaker 1: they basically said, hey, you know, it's up to the

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Speaker 1: people who buy the glasses to adhere to the terms

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Speaker 1: of service. We don't really control that.

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Speaker 2: Bo That's such a good point that Meta is both

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Speaker 2: making and selling the hardware and making money on that

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Speaker 2: and then also make essensibly making money on the content

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Speaker 2: this like illicit content that is created from the hardware

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Speaker 2: that they sold. They're really what do you call that?

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Speaker 2: Like vertically integrated.

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Speaker 1: I guess. I mean, that's a fancy way to put it.

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Speaker 1: Where I'm from. They're running a criminal enterprise. I mean,

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Speaker 1: this is my opinion. At what point is meta we

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Speaker 1: are making money from a criminal enterprise knowingly best? I mean,

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Speaker 1: that's so I would love to have somebody smarter than

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Speaker 1: me explain how it's not that. Yeah, and it has

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Speaker 1: to be said that a lot of the women who

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Speaker 1: were at these kinds of massage parlors are migrant women

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Speaker 1: or immigrant women, or women who are engaged in sex work, right,

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Speaker 1: and so they're already marginalized. Sometimes they're very vulnerable. Four

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Speaker 1: h four spoke to Angela Lou, the executive director of

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Speaker 1: SWAN Vancouver, which is an organization that promotes rights and

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Speaker 1: safety of migrant and immigrant women engaged in sex work.

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Speaker 1: Wu said quote. Earlier this year, SWAN Vancouver became aware

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Speaker 1: of disturbing social media videos showing individuals wearing ray ban

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Speaker 1: metaglasses to enter massage parlors across North America and record

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Speaker 1: interactions with workers. Many of these workers are immigrant and

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Speaker 1: newcomer women who may or may not engage in sex

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Speaker 1: work but experienced stigma. Nonetheless, the shameless use of covert

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Speaker 1: recording technology at massage parlors to gain likes, attention, and

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Speaker 1: online notoriety is both disgusting and dangerous. Yes, due to

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Speaker 1: criminalization and stigma, sex workers face disproportionate levels of violence

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Speaker 1: and harassment. Violations of privacy can lead to arrest, immigration consequences,

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Speaker 1: and lasting harm. Swan's community made extensive efforts to report

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Speaker 1: these videos and were deeply disappointed that social media platforms

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Speaker 1: allow them to remain online. They say that they've also

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Speaker 1: created a system to warn the women who work at

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Speaker 1: these places, saying to warn immigrant and migrant women we support.

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Speaker 1: SWAN used our abuse of alert system to notify workers

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Speaker 1: about the use of RayBan metaglasses and the videos circulating online.

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Speaker 1: We also receive reports of community members about clients entering

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Speaker 1: massage parlors wearing the glasses and recording the women without

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Speaker 1: their knowledge. I am really grateful that organizations like SWAN

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Speaker 1: exist that can use technology to help support these women

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Speaker 1: from the kind of surveillance that this kind of technology represents.

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Speaker 1: But I do think like this is not just about

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Speaker 1: a handful of creeps with smart glasses. I think it

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Speaker 1: really is about what happens when companies like Meta and

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Speaker 1: Facebook filled tools that make exploitation easy, that make it

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Speaker 1: easy to turn that into a money making enterprise, to

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Speaker 1: make money from somebody non consensually being sexualized in this way,

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Speaker 1: and then to have the company just shrug when people

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Speaker 1: use them exactly that way. Meta has essentially built an

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Speaker 1: ecosystem where privacy violations are profitable, and that the only

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Speaker 1: form of real accountability that might ever even enter the

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Speaker 1: equation only happens after a journalist asks about it, after

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Speaker 1: some sort of public outrage.

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Speaker 2: Yeah, not cool and not surprising. You know, they've got

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Speaker 2: a whole ecosystem built around disrespecting privacy and just letting

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Speaker 2: harms run wild up until the point where they start

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Speaker 2: to get pushed back on it, and then maybe they'll

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Speaker 2: do something.

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Speaker 1: Maybe maybe, Although not for nothing. I did want to

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Speaker 1: see a very satisfying video where a guy in metaglasses

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Speaker 1: which are recording, and I believe that he uploaded the

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Speaker 1: footage and it's one of those things where did you

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Speaker 1: upload this thinking that it made you look cool, because

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Speaker 1: it's really the opposite. Where a guy is trying to

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Speaker 1: get into a strip club and the woman at the

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Speaker 1: door she knows the drill exactly. She's like, Oh, if

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Speaker 1: you want to come in hear home, you get pickles

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Speaker 1: glass saw and he keeps being like, oh, they're not,

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Speaker 1: They're just regular glasses, and she absolutely knows that they're not.

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Speaker 1: He keeps trying to like get them in, get them in.

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Speaker 1: It was a very satisfying watch just watching this this

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Speaker 1: creep think that he can out smart this woman because

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Speaker 1: she is associated with the strip club and being denied

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Speaker 1: and eventually being kicked out of the establishment. Very satisfying watch.

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Speaker 2: Yeah, I bet it was, and also funny that his

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Speaker 2: tactic was just to like lie when it sounds like

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Speaker 2: she clearly knew that, like they were the medaglasses. He's like, no,

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Speaker 2: they're not.

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Speaker 1: Let me tell you something. Nobody knows the drill around technology,

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Speaker 1: Like anybody who is even tangentially involved in sex work

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Speaker 1: of yours or a sex worger, you like, you have

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Speaker 1: to know the drill. Some smug tech bro is not

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Speaker 1: going to outsmart a woman who works the door at

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Speaker 1: a strip club when it comes to technology. There's just

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Speaker 1: no way. No.

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Speaker 2: Yeah, a woman working the door at a strip club,

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Speaker 2: don't cross her.

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Speaker 1: Yeah you're not. There's no outsmarting her. Let's take a

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Speaker 1: quick break at her back. Okay, So speaking of women

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Speaker 1: out smarting technology, this story from the Colorado Sun is

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Speaker 1: truly wild and also just illustrates how screwed up our

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Speaker 1: entire tech enabled surveillance landscape is. This time not regarding metaglasses.

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Speaker 1: It's regarding Flock, which is a company that operates a

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Speaker 1: vast network of AI powered video cameras, license plate readers,

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Speaker 1: and microphones for surveillance. If Flock that company, if they

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Speaker 1: sound familiar to you, it's probably because we talked about

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Speaker 1: them before. Regarding a situation in Texas where police used

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Speaker 1: Flock to track down a woman who they said had

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Speaker 1: an abortion, the police said, Hey, we used Flock license

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Speaker 1: plate readers to find this woman after her abortion because

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Speaker 1: her family was worried about her. That's the only reason

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Speaker 1: we were trying to find her. Or they were worried

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Speaker 1: about her safety after this abortion. They were worried that

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Speaker 1: she was, you know, in some sort of physical danger,

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Speaker 1: and so they had tracked her using Flock license plate

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Speaker 1: reader technology. However, for for Media again shout out to them.

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Speaker 1: They followed up and found that the police, even though

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Speaker 1: they said they were just looking for her because her

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Speaker 1: family was worried about her. Police had actually been looking

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Speaker 1: to charge her with a crime for having had an abortion.

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Speaker 1: So it wasn't just that her family was worried about

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Speaker 1: her and looking for her, it was that they wanted

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Speaker 1: to charge her with a crime. So Block is everywhere.

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Speaker 1: It is in cities all over the country. A lot

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Speaker 1: of towns and cities have contracts with Block. Balmar, which

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Speaker 1: is a small suburb northwest of Littleton, Colorado, is one

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Speaker 1: of several Colorado towns that has a contract with Block.

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Speaker 1: So this woman, Christiana in Denver, she got a visit

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Speaker 1: from the police who came to her door with a

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Speaker 1: summons for her, accusing her of stealing a package worth

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Speaker 1: less than twenty five dollars from somebody's doorstep in this

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Speaker 1: neighboring town of Bomar. Their proof, they said they had

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Speaker 1: footage from a flock surveillance camera showing her car, which

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Speaker 1: was a green Vivian, driving through the town of Bomar

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Speaker 1: from eleven fifty two am to twelve o nine pm

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Speaker 1: on the day of the theft. So she says that

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Speaker 1: police were super weird with her about it. They told her, quote,

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Speaker 1: you know, we have cameras in that town. You can't

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Speaker 1: get a breath of fresh air in or out of

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Speaker 1: that place without us knowing. Just as an example, we

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Speaker 1: know that you've driven there about twenty times in the

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Speaker 1: last month, which is a pretty weird thing. If a

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Speaker 1: cock came to my house and was saying that to me,

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Speaker 1: I'd be pretty freaked out.

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Speaker 2: Yeah, I wouldn't care for that at all. That the

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Speaker 2: police are just like aware of everything I've been doing

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Speaker 2: for the past months. Wouldn't like it.

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Speaker 1: I also would not like it. The police also told

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Speaker 1: her that they had seen ring a camera footage that

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Speaker 1: showed her taking this package from the porch. She was like,

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Speaker 1: that's not me. That did not helpen. I did not

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Speaker 1: do that. The police told her, I guess this is

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Speaker 1: a shock to you, but I'm telling you this is

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Speaker 1: a lock, one hundred percent, no doubt. So she was like,

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Speaker 1: I know that I did not do this. She asked

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Speaker 1: the police to see this ring camera footage that they

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Speaker 1: said was one hundred percent her. They had her dead

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Speaker 1: to rights taking this package, and they refused to show

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Speaker 1: her this footage. So Christiana drives a Rivian and I

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Speaker 1: guess Rivians have a camera in the dash, which captured

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Speaker 1: footage again proving that she had not driven to where

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Speaker 1: this crime had happened. When she told police like, hey,

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Speaker 1: I actually have a camera in my car, I can

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Speaker 1: show you that I drove to this town and didn't

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Speaker 1: make any you know, stops at anybody's house to steal

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Speaker 1: a package, they were like, it doesn't matter. They gave

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Speaker 1: her the summons. Christiana says that she works in finance,

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Speaker 1: so understandably was not thrilled about having her name associated

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Speaker 1: with a theft.

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Speaker 2: I bet not makes sense. Yeah, probably is not really

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Speaker 2: helpful in that field.

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Speaker 1: So Christiana said, I'm going to fight surveillance with surveillance.

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Speaker 1: So she and her husband essentially compiled a master file

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Speaker 1: with any kind of information about her whereabouts from her phone.

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Speaker 1: Right she had snapshots from her Google timeline, a tool

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Speaker 1: on her phone that can track each stop that she makes,

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Speaker 1: statements from people that she interacted with that day. The works.

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Speaker 1: She took a picture of the outfit that she wore,

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Speaker 1: which was a light pink top and black pants and

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Speaker 1: an olive green fleece, with a note that she took

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Speaker 1: off her sweater because it's her to get warm outside.

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Speaker 1: That ring camera footage that the police said showed her

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Speaker 1: definitively stealing that package, while somehow she was able to

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Speaker 1: track down that footage using next door, and that footage

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Speaker 1: does show a person coming up to a porch and

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Speaker 1: taking a package or running away, but it doesn't show

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Speaker 1: them getting into a car that looks anything like hers.

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Speaker 1: And so basically she had actually gone to this town

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Speaker 1: with a theft happened, but she had legitimate business there

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Speaker 1: with a tailor that was more than a quarter mile

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Speaker 1: from the house with this package was stolen. So she

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Speaker 1: collected all this surveillance footage, footage of her entering the

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Speaker 1: tailor's office and then leaving the tailor's office. She got

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Speaker 1: footage of her driving her car from the rivian that

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Speaker 1: shows that she basically drove from her house to this

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Speaker 1: tailor and back without any additional stops. She compiled all

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Speaker 1: of this evidence at her own expense and effort and

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00:23:58,320 --> 00:24:02,040
Speaker 1: sent it to the police. Eventually, that chief of police

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00:24:02,080 --> 00:24:06,639
Speaker 1: responded and congratulated her on her detective work and announced

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Speaker 1: that the police were going to be dismissing the charges

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Speaker 1: against her. In the email they wrote after reviewing the evidence,

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Speaker 1: he provided parentheses Nicely done BT dubs. We have avoided

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Speaker 1: the summons we issued, so it's great that they dropped

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Speaker 1: this bogus charge against her. But she was like, did

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Speaker 1: the police just use Flock to see that I happened

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Speaker 1: to drive to the same town where somebody happened to

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Speaker 1: have had a package stolen and decided that because I

436
00:24:36,680 --> 00:24:38,800
Speaker 1: was in that town that I did it.

437
00:24:39,520 --> 00:24:43,520
Speaker 2: And does raise questions like that police officer who came

438
00:24:43,600 --> 00:24:46,760
Speaker 2: to her house who said, one hundred percent it's a lock.

439
00:24:48,119 --> 00:24:51,199
Speaker 2: Clearly it wasn't. It's like, what made him think that?

440
00:24:51,880 --> 00:24:54,439
Speaker 2: Was it really just that that Flock said that she

441
00:24:54,560 --> 00:24:57,720
Speaker 2: was in the town. So curious that I guess we'll

442
00:24:57,760 --> 00:24:58,639
Speaker 2: probably never know.

443
00:24:59,080 --> 00:25:03,000
Speaker 1: Well. The Colorado asked the police about this. They were like, basically,

444
00:25:03,680 --> 00:25:06,840
Speaker 1: what happened here? The Shia police told The Colorado Sun

445
00:25:07,040 --> 00:25:10,760
Speaker 1: that Flock uses cameras to identify stolen vehicles, stolen license plates,

446
00:25:11,160 --> 00:25:15,359
Speaker 1: any wanted subjects that entertown or follow up investigations. Quote,

447
00:25:15,400 --> 00:25:19,040
Speaker 1: we can't see people inside the car. We follow up investigations.

448
00:25:19,080 --> 00:25:21,160
Speaker 1: If we have a crime, we'll go back and look

449
00:25:21,200 --> 00:25:23,800
Speaker 1: at the cameras and see who was in town at

450
00:25:23,800 --> 00:25:26,760
Speaker 1: the time of the crime. So it does kind of

451
00:25:26,840 --> 00:25:29,200
Speaker 1: just sound like this is a tool that police are

452
00:25:29,720 --> 00:25:32,840
Speaker 1: relying on to be like, oh, who is in town

453
00:25:32,960 --> 00:25:36,320
Speaker 1: when this crime happened? And it just doesn't sound like

454
00:25:36,480 --> 00:25:40,640
Speaker 1: more surveillance in this instance is actually leading to crimes

455
00:25:40,720 --> 00:25:43,440
Speaker 1: being solved. I think, if anything, it is leading police

456
00:25:43,480 --> 00:25:47,040
Speaker 1: to say, Oh, this person was here, was probably them.

457
00:25:47,200 --> 00:25:51,320
Speaker 2: This is something that we see pretty often that people

458
00:25:51,400 --> 00:25:56,960
Speaker 2: really have like an outsized level of confidence in results

459
00:25:57,000 --> 00:25:59,119
Speaker 2: that they get from a computer, like this belief that

460
00:25:59,440 --> 00:26:03,159
Speaker 2: if a software system says something, that it has to

461
00:26:03,200 --> 00:26:06,960
Speaker 2: be true. And I wonder if that's what's going on here,

462
00:26:07,040 --> 00:26:12,440
Speaker 2: that that they just like have way too much faith

463
00:26:12,520 --> 00:26:17,120
Speaker 2: and confidence in Flock to be tracking every single person

464
00:26:17,160 --> 00:26:22,200
Speaker 2: who's coming and going into that town to the detriment

465
00:26:22,400 --> 00:26:28,159
Speaker 2: of like reasonable skepticism that like, maybe there's more to

466
00:26:28,160 --> 00:26:31,200
Speaker 2: the story than the one person whose car was driving

467
00:26:31,240 --> 00:26:32,080
Speaker 2: through their little town.

468
00:26:32,520 --> 00:26:35,480
Speaker 1: Yes, And I would take that further and say that

469
00:26:35,840 --> 00:26:38,200
Speaker 1: I think it is with intention. I think that when

470
00:26:39,160 --> 00:26:42,359
Speaker 1: power system is when the state uses computer systems and

471
00:26:42,400 --> 00:26:47,199
Speaker 1: technology systems like Flock, it absolves them of having to

472
00:26:47,200 --> 00:26:51,119
Speaker 1: do any investigative work or the accountability of being wrong,

473
00:26:51,200 --> 00:26:54,159
Speaker 1: because you can just say, oh, well, it was the computer, like,

474
00:26:54,200 --> 00:26:56,320
Speaker 1: we were just looking at the AI. The AI is

475
00:26:56,359 --> 00:26:59,119
Speaker 1: never wrong. The AI told us that you were responsible,

476
00:26:59,240 --> 00:27:00,960
Speaker 1: and we were just followed up on that, and so

477
00:27:01,440 --> 00:27:04,160
Speaker 1: they don't have to have any accountability. I mean, Christianna

478
00:27:04,200 --> 00:27:07,760
Speaker 1: says she never received any kind of explanation from anybody

479
00:27:07,760 --> 00:27:10,639
Speaker 1: at the police department or even an apology, and it

480
00:27:10,760 --> 00:27:13,040
Speaker 1: just I know I've said this before, but it reminds

481
00:27:13,080 --> 00:27:16,439
Speaker 1: me of that IBM page from like the seventies. A

482
00:27:16,480 --> 00:27:19,160
Speaker 1: computer can never be held accountable. Therefore a computer must

483
00:27:19,160 --> 00:27:21,720
Speaker 1: never make a management decision. I think that the police

484
00:27:21,760 --> 00:27:26,720
Speaker 1: are with intention outsourcing this kind of police work to

485
00:27:27,880 --> 00:27:32,440
Speaker 1: technology and surveillance tools like fuck precisely because it means

486
00:27:32,440 --> 00:27:34,440
Speaker 1: that they do not have to be held accountable as

487
00:27:34,520 --> 00:27:36,960
Speaker 1: the human police when they fuck up as bad as this.

488
00:27:37,480 --> 00:27:40,320
Speaker 2: Yeah, I think you're absolutely right. It's a way, it's

489
00:27:40,320 --> 00:27:46,480
Speaker 2: like a backdoor way to reduce their own accountability. The

490
00:27:46,520 --> 00:27:48,679
Speaker 2: weird thing about it is though, that like it's not

491
00:27:48,720 --> 00:27:52,520
Speaker 2: like that accountability then gets transferred to the software company.

492
00:27:52,680 --> 00:27:56,080
Speaker 2: It just kind of evaporates into the air and there

493
00:27:56,160 --> 00:27:57,320
Speaker 2: is no accountability.

494
00:27:57,520 --> 00:28:01,960
Speaker 1: She didn't even get an apology. I mean, she will

495
00:28:01,960 --> 00:28:04,879
Speaker 1: put the piece in the show notes obviously, but she

496
00:28:05,000 --> 00:28:09,800
Speaker 1: describes sleepless nights and wondering if her finance job was

497
00:28:09,840 --> 00:28:13,080
Speaker 1: going to be coming to an end because of this accusation,

498
00:28:13,240 --> 00:28:16,560
Speaker 1: this completely unfounded accusation, and they did not even give

499
00:28:16,600 --> 00:28:19,480
Speaker 1: her an apology. Let me tell you something, I would begin.

500
00:28:19,640 --> 00:28:21,320
Speaker 1: I would need an apology to move on from this

501
00:28:21,359 --> 00:28:23,520
Speaker 1: if this doesn't happened to me. That would be the very

502
00:28:23,560 --> 00:28:25,280
Speaker 1: least of the things I would need. I would need it.

503
00:28:25,520 --> 00:28:28,240
Speaker 1: We would I would need a clear apology from somebody.

504
00:28:28,560 --> 00:28:31,960
Speaker 2: Yeah, I would be pretty mad and it. It also

505
00:28:32,000 --> 00:28:35,280
Speaker 2: sounds like she really had to do the work to

506
00:28:35,400 --> 00:28:41,200
Speaker 2: like prove herself innocent here, and that's not how it's

507
00:28:41,200 --> 00:28:42,160
Speaker 2: supposed to work.

508
00:28:42,560 --> 00:28:45,080
Speaker 1: Absolutely, you know, she said that she basically had to

509
00:28:45,200 --> 00:28:48,960
Speaker 1: exonerate herself. And my question is what would have happened

510
00:28:49,000 --> 00:28:51,600
Speaker 1: if Christiana was not the kind of person who was

511
00:28:51,640 --> 00:28:54,440
Speaker 1: able to spend so much time and her own expense

512
00:28:54,480 --> 00:28:58,360
Speaker 1: compiling so much proof to illustrate that she was innocent. Like,

513
00:28:58,400 --> 00:29:01,600
Speaker 1: I'm happy that she beat the charges, but she only

514
00:29:01,640 --> 00:29:04,760
Speaker 1: did that through out surveilling. The surveillance, and I think

515
00:29:04,800 --> 00:29:07,160
Speaker 1: if we're at the point where you need a tailor's

516
00:29:07,160 --> 00:29:10,720
Speaker 1: receipt and your own cars, dashcam footage and all of

517
00:29:10,760 --> 00:29:13,400
Speaker 1: this just to prove that you didn't steal a package

518
00:29:13,400 --> 00:29:16,080
Speaker 1: worth less than twenty five dollars. Maybe this level of

519
00:29:16,120 --> 00:29:20,440
Speaker 1: surveillance is not actually keeping anybody safer or deterring crime.

520
00:29:20,720 --> 00:29:22,760
Speaker 1: Maybe this is not actually the future that we want.

521
00:29:23,000 --> 00:29:26,520
Speaker 2: And meanwhile, there's still somebody out there stealing packages.

522
00:29:26,800 --> 00:29:30,360
Speaker 1: The real package set is still out there people. Okay,

523
00:29:30,400 --> 00:29:34,200
Speaker 1: So speaking of accountability, we were talking before we got

524
00:29:34,240 --> 00:29:38,120
Speaker 1: on the mic about this new law in China regulating influencer.

525
00:29:38,240 --> 00:29:41,280
Speaker 1: So there's this new law where if influencers or contact

526
00:29:41,320 --> 00:29:45,120
Speaker 1: creators want to make content online about specific regulated topics,

527
00:29:45,480 --> 00:29:47,880
Speaker 1: they will need to provide some kind of education or

528
00:29:47,920 --> 00:29:52,280
Speaker 1: training in those areas. So this new law requires social

529
00:29:52,360 --> 00:29:58,240
Speaker 1: media influencers to hold verified qualifications before discussing medicine, law, education,

530
00:29:58,440 --> 00:30:02,800
Speaker 1: or finance. And it's a at curbing misinformation. How will

531
00:30:02,800 --> 00:30:06,160
Speaker 1: this be regulated, Well, it'll be up to platforms like

532
00:30:06,240 --> 00:30:09,880
Speaker 1: the Chinese version of TikTok, which is Doin or Webo

533
00:30:10,160 --> 00:30:15,040
Speaker 1: and believably to verify content creators credentials before allowing that

534
00:30:15,160 --> 00:30:18,560
Speaker 1: content to be posted. Content creators if they want to

535
00:30:18,600 --> 00:30:22,560
Speaker 1: talk about these specific regulated topics, they will need credentials

536
00:30:22,640 --> 00:30:27,920
Speaker 1: like degrees, certifications, or professional license in those topics. It's

537
00:30:27,960 --> 00:30:31,200
Speaker 1: actually a pretty wide ranging set of new laws. The

538
00:30:31,240 --> 00:30:34,520
Speaker 1: Cyberspace Administration of China, which is the Chinese government agency

539
00:30:34,800 --> 00:30:38,240
Speaker 1: responsible for regulating and overseeing the country's Internet, online content

540
00:30:38,280 --> 00:30:41,400
Speaker 1: and data security, has also implemented some new regulations on

541
00:30:41,440 --> 00:30:45,200
Speaker 1: social media advertising and promotions. Under these new laws, any

542
00:30:45,240 --> 00:30:49,400
Speaker 1: campaign for medical products, supplements, and health foods will now

543
00:30:49,520 --> 00:30:53,400
Speaker 1: be prohibited unless it is clearly defined as such to

544
00:30:53,480 --> 00:30:57,520
Speaker 1: prevent misleading content disguised as educational materials. So basically you

545
00:30:57,520 --> 00:31:00,400
Speaker 1: can't just say, oh, this is just educational and information

546
00:31:00,480 --> 00:31:04,560
Speaker 1: and actually it is a campaign for a medical supplement

547
00:31:04,560 --> 00:31:07,719
Speaker 1: that I want you to buy. Influencers will also have

548
00:31:07,760 --> 00:31:11,600
Speaker 1: to disclose sources for studies or note when content is

549
00:31:11,640 --> 00:31:15,719
Speaker 1: ai generated under this new legislation. How do How are

550
00:31:15,720 --> 00:31:19,440
Speaker 1: you feeling about this? You and I had a meaty

551
00:31:19,560 --> 00:31:21,959
Speaker 1: conversation about it off Mike, I don't I don't know

552
00:31:21,960 --> 00:31:23,680
Speaker 1: how and how into it you want to get. But

553
00:31:23,720 --> 00:31:24,360
Speaker 1: how are we feeling?

554
00:31:24,960 --> 00:31:33,160
Speaker 2: Conflicted? Very conflicted? You know, it's obviously scary to be

555
00:31:33,320 --> 00:31:39,440
Speaker 2: like regulating speech, but also what we're doing in this

556
00:31:39,480 --> 00:31:42,440
Speaker 2: country is like not working at all right now. Uh,

557
00:31:42,640 --> 00:31:48,080
Speaker 2: Like the Internet is just filled with medical misinformation, uh,

558
00:31:48,200 --> 00:31:52,360
Speaker 2: which I you know, know a little bit of something

559
00:31:52,400 --> 00:31:55,400
Speaker 2: about enough to be like, yeah, this is a really

560
00:31:55,440 --> 00:31:58,840
Speaker 2: bad stay rehearse. I can only imagine, like what were

561
00:31:58,880 --> 00:32:03,480
Speaker 2: the other areas lead goal education and finance information. I

562
00:32:03,480 --> 00:32:07,880
Speaker 2: can only imagine that there's it's equally bad in those

563
00:32:07,920 --> 00:32:11,120
Speaker 2: domains as well. So there's and it's not just that

564
00:32:11,120 --> 00:32:15,680
Speaker 2: there's some bad information out there, but like our platform

565
00:32:15,840 --> 00:32:22,440
Speaker 2: social media platforms are designed to amplify and spread and

566
00:32:22,640 --> 00:32:27,800
Speaker 2: replicate that misinformation. So like, it's very bad, and I'm

567
00:32:30,000 --> 00:32:34,840
Speaker 2: open to ideas about like trying to rein that in

568
00:32:34,840 --> 00:32:39,440
Speaker 2: in some way. And so there's something appealing about some

569
00:32:39,800 --> 00:32:42,440
Speaker 2: laws to rate it in and I kind of think that,

570
00:32:42,520 --> 00:32:44,680
Speaker 2: like in this country, we do need some laws to

571
00:32:44,760 --> 00:32:47,760
Speaker 2: rein that in. But it's also pretty scary because if

572
00:32:47,800 --> 00:32:51,479
Speaker 2: you think about the administration in charge right now, what

573
00:32:51,480 --> 00:32:53,800
Speaker 2: would it look like for them to have the final

574
00:32:53,960 --> 00:32:57,800
Speaker 2: say in what kind of medical information is allowed to

575
00:32:57,800 --> 00:33:01,840
Speaker 2: be shared at not right Like there's spewing misinformation from

576
00:33:01,880 --> 00:33:07,760
Speaker 2: the White House, from the head of AHHS. So uh

577
00:33:08,360 --> 00:33:10,840
Speaker 2: so I don't know, what do you think about it.

578
00:33:11,320 --> 00:33:13,680
Speaker 1: You really said it. I mean, on the one hand,

579
00:33:14,120 --> 00:33:16,160
Speaker 1: I want to be crue that I'm skeptical about this

580
00:33:16,240 --> 00:33:20,400
Speaker 1: because it feels like censorship to me. And also part

581
00:33:20,480 --> 00:33:23,360
Speaker 1: of it's a real love hate thing that I have

582
00:33:23,440 --> 00:33:27,640
Speaker 1: with social media is that the democratization of media, where

583
00:33:28,720 --> 00:33:31,280
Speaker 1: having a platform or having a voice is not gate

584
00:33:31,360 --> 00:33:33,360
Speaker 1: kept like it is in traditional media. That is something

585
00:33:33,400 --> 00:33:36,320
Speaker 1: that I love. It is it is what has driven

586
00:33:36,360 --> 00:33:39,760
Speaker 1: me to being a podcaster, but it also I kind

587
00:33:39,760 --> 00:33:42,800
Speaker 1: of hate it because that means anybody can just get

588
00:33:42,800 --> 00:33:44,960
Speaker 1: a microphone and a ring light and just say whatever

589
00:33:45,000 --> 00:33:47,520
Speaker 1: they want. And yeah, so I want to be crue

590
00:33:47,560 --> 00:33:51,560
Speaker 1: that I'm skeptical of this, but like you, obviously what

591
00:33:51,880 --> 00:33:54,040
Speaker 1: the system that we have in the United States is

592
00:33:54,800 --> 00:33:59,880
Speaker 1: not working. What's fun in to me is so RFKG

593
00:34:00,120 --> 00:34:03,320
Speaker 1: here the head of AHHS. He has a law degree.

594
00:34:03,480 --> 00:34:05,800
Speaker 1: He doesn't have any kind of medical degree. Would he

595
00:34:05,920 --> 00:34:10,319
Speaker 1: not Would he not be able to make content or

596
00:34:11,080 --> 00:34:15,120
Speaker 1: you know, commentary about health advice or medical advice if

597
00:34:15,120 --> 00:34:16,920
Speaker 1: this law were in the United States because he only

598
00:34:17,000 --> 00:34:18,239
Speaker 1: has a lot of degree and not any kind of

599
00:34:18,239 --> 00:34:19,080
Speaker 1: medical expertise.

600
00:34:19,960 --> 00:34:24,160
Speaker 2: I mean, we know how much these guys care about laws.

601
00:34:24,640 --> 00:34:25,680
Speaker 1: You wouldn't stop him.

602
00:34:26,000 --> 00:34:28,840
Speaker 2: If it were a saying society, he would not be

603
00:34:30,000 --> 00:34:36,120
Speaker 2: making comments about health stuff. And even if he was,

604
00:34:36,200 --> 00:34:38,440
Speaker 2: if we were a saying society, people wouldn't be listening

605
00:34:38,480 --> 00:34:40,319
Speaker 2: to him. We wouldn't be amplifying him.

606
00:34:40,640 --> 00:34:45,200
Speaker 1: As DC residents. The day that he swam in Rock Creek,

607
00:34:46,560 --> 00:34:48,960
Speaker 1: nobody would. If you, if you live in a mid

608
00:34:49,000 --> 00:34:53,600
Speaker 1: Atlantic you know this homie just took a swim in poop.

609
00:34:54,400 --> 00:34:56,560
Speaker 2: Yeah, he just took a swim in poop, like and

610
00:34:56,600 --> 00:34:58,759
Speaker 2: he had his kids out there doing it. I love

611
00:34:58,840 --> 00:35:03,400
Speaker 2: Rock Creek. I go hiking along it like multiple times

612
00:35:03,480 --> 00:35:06,960
Speaker 2: every single week. I would not swim in it, Like

613
00:35:07,160 --> 00:35:10,160
Speaker 2: when it rains it smells like poop because a lot

614
00:35:10,160 --> 00:35:12,160
Speaker 2: of the sewers just like wash right in there. That's

615
00:35:12,200 --> 00:35:14,600
Speaker 2: just like how it is with combined sewers in an

616
00:35:14,640 --> 00:35:19,960
Speaker 2: old urban city like this. Like, uh, it's it's not

617
00:35:20,040 --> 00:35:21,600
Speaker 2: a good place for people to swim.

618
00:35:21,600 --> 00:35:23,799
Speaker 1: And I'm not even sure it's safe for dogs to swim.

619
00:35:24,239 --> 00:35:27,920
Speaker 2: No, it's not because they drink it. And the annoying

620
00:35:27,960 --> 00:35:30,600
Speaker 2: thing is that he when he did that, after he

621
00:35:30,719 --> 00:35:34,319
Speaker 2: like took his little splash around in Rock Creek, and

622
00:35:35,320 --> 00:35:37,920
Speaker 2: ostensibly he said he was fine. We don't know what

623
00:35:38,000 --> 00:35:40,640
Speaker 2: was going on in the bathrooms at home, but like

624
00:35:40,719 --> 00:35:43,080
Speaker 2: he says he was fine and holds that up as

625
00:35:43,120 --> 00:35:46,080
Speaker 2: like evidence that it's an okay thing for him to do.

626
00:35:46,440 --> 00:35:48,839
Speaker 2: But it's not just about him. This is like one

627
00:35:48,880 --> 00:35:51,480
Speaker 2: of the most frustrating things about him is that he

628
00:35:51,719 --> 00:35:57,360
Speaker 2: is like the leader of helping human services. Like people

629
00:35:57,400 --> 00:36:02,240
Speaker 2: look to him as a role model even though they shouldn't,

630
00:36:02,360 --> 00:36:06,120
Speaker 2: but like he has a responsibility to act in a

631
00:36:06,239 --> 00:36:11,319
Speaker 2: way that keeps people in general safe, whether or not

632
00:36:11,800 --> 00:36:15,759
Speaker 2: he himself, like got lucky rolling the dice. That's not

633
00:36:15,880 --> 00:36:18,400
Speaker 2: the point of public health.

634
00:36:18,920 --> 00:36:21,520
Speaker 1: Yes, I remember him saying, oh, well, nobody should take

635
00:36:21,680 --> 00:36:24,760
Speaker 1: health advice or medical advice for me. On the one hand,

636
00:36:25,440 --> 00:36:28,040
Speaker 1: I fucking uh. On the other hand, what are you

637
00:36:28,120 --> 00:36:29,680
Speaker 1: doing leading ahhs?

638
00:36:29,840 --> 00:36:32,560
Speaker 2: Like you know, yeah, Like I'm sorry to tell you,

639
00:36:32,600 --> 00:36:36,800
Speaker 2: people are going to be taking cues from you. Yeah.

640
00:36:36,840 --> 00:36:38,560
Speaker 1: So the reason that I wanted to talk about this

641
00:36:38,640 --> 00:36:40,960
Speaker 1: new law in China is not to advocate for it,

642
00:36:41,000 --> 00:36:44,239
Speaker 1: because I am skeptical of it. But I just did

643
00:36:44,280 --> 00:36:46,759
Speaker 1: have a moment where I thought, boy, what would it

644
00:36:46,800 --> 00:36:48,480
Speaker 1: look like if we had something like this in the

645
00:36:48,520 --> 00:36:50,960
Speaker 1: United States? Setting aside the point that you made, which

646
00:36:51,000 --> 00:36:52,839
Speaker 1: is a good one, which is why I'm a little

647
00:36:52,840 --> 00:36:56,680
Speaker 1: bit iffy around a lot of legislation around cracking down

648
00:36:56,719 --> 00:36:59,879
Speaker 1: on this kind of thing legislatively, because under a host

649
00:37:00,040 --> 00:37:02,640
Speaker 1: administration like this one, I would not want this administration

650
00:37:02,719 --> 00:37:04,160
Speaker 1: being the ones you.

651
00:37:04,120 --> 00:37:08,000
Speaker 2: Know, in charge of anything.

652
00:37:08,880 --> 00:37:12,000
Speaker 1: You get it, Yeah, you get what I'm trying to say. Yeah, however,

653
00:37:12,360 --> 00:37:16,080
Speaker 1: I putting that aside, I still can't help but like speculate,

654
00:37:16,160 --> 00:37:18,640
Speaker 1: like what would our internet landscape look like if you

655
00:37:18,719 --> 00:37:21,680
Speaker 1: needed a degree to talk about these things? And they

656
00:37:21,760 --> 00:37:24,439
Speaker 1: are things that I mean, Listen, I have been trying

657
00:37:24,480 --> 00:37:27,920
Speaker 1: to get my finances together lately, and the amount of

658
00:37:28,719 --> 00:37:32,279
Speaker 1: bad financial advice that is out there from people who

659
00:37:32,680 --> 00:37:36,480
Speaker 1: don't know what they're talking about. Financial advice. Generally, good

660
00:37:36,520 --> 00:37:39,920
Speaker 1: advice is like pretty standard and humdrum and boring, you know,

661
00:37:40,440 --> 00:37:43,520
Speaker 1: stuff like don't spend more than you have. But there

662
00:37:43,520 --> 00:37:47,360
Speaker 1: are so many people out there who are peddling the

663
00:37:47,520 --> 00:37:50,880
Speaker 1: worst financial advice you've ever heard in your life. And

664
00:37:51,040 --> 00:37:52,759
Speaker 1: come to find out, a lot of these people don't

665
00:37:52,760 --> 00:37:55,040
Speaker 1: even have any kind of credentials to be giving the

666
00:37:55,080 --> 00:37:59,200
Speaker 1: public financial advice. And so if we had this kind

667
00:37:59,200 --> 00:38:01,279
Speaker 1: of law in the United States. I mean, you would

668
00:38:01,320 --> 00:38:04,280
Speaker 1: have no more finance bros saying things like stop buying

669
00:38:04,280 --> 00:38:06,759
Speaker 1: avocado toast and then you can afford a house when

670
00:38:06,760 --> 00:38:09,320
Speaker 1: they a have no financial credentials to be telling anybody

671
00:38:09,320 --> 00:38:11,960
Speaker 1: how to run their finances and b are being like

672
00:38:12,080 --> 00:38:16,120
Speaker 1: bank rolls by their parents. No more wellness coaches selling

673
00:38:16,600 --> 00:38:20,080
Speaker 1: four hundred dollars moon water or any kind of like

674
00:38:20,160 --> 00:38:22,960
Speaker 1: weird supplements. I just think that if this kind of

675
00:38:23,040 --> 00:38:25,520
Speaker 1: law came to the United States, think about all of

676
00:38:25,560 --> 00:38:29,320
Speaker 1: the loud, big voices that would just vanish overnight.

677
00:38:29,960 --> 00:38:36,560
Speaker 2: Yeah, if you couldn't just say lies for profit, it's

678
00:38:36,560 --> 00:38:38,840
Speaker 2: hard not to be a little attracted to that.

679
00:38:38,840 --> 00:38:41,759
Speaker 1: That's what I'm saying. Like again, I'm not saying that

680
00:38:41,800 --> 00:38:46,359
Speaker 1: I am. I am skeptical of this law, but it's

681
00:38:46,400 --> 00:38:48,640
Speaker 1: hard not to see this and be like, Wow, we

682
00:38:48,719 --> 00:38:50,880
Speaker 1: really have a problem in the United States. And anybody

683
00:38:50,960 --> 00:38:54,360
Speaker 1: can just build a massive platform saying anything and it's fine.

684
00:38:54,960 --> 00:39:00,720
Speaker 2: Yeah, And in this country, it seems like areolitical leaders

685
00:39:00,719 --> 00:39:04,200
Speaker 2: and certainly the leaders of social media platforms have like

686
00:39:04,360 --> 00:39:08,320
Speaker 2: embraced the chaos. They're like, this is what makes America

687
00:39:08,400 --> 00:39:11,800
Speaker 2: strong is the ability to just like scream harmful lies

688
00:39:12,120 --> 00:39:16,640
Speaker 2: and drown out anyone who's trying to say something reasonable.

689
00:39:16,960 --> 00:39:19,640
Speaker 1: Our president was out here doing crypto scams and nobody

690
00:39:19,680 --> 00:39:22,640
Speaker 1: said boo, like we this is a scam economy. That's

691
00:39:22,640 --> 00:39:24,680
Speaker 1: all there is to it.

692
00:39:24,680 --> 00:39:29,080
Speaker 2: It's so true, so many scams. Like every day he

693
00:39:29,120 --> 00:39:33,319
Speaker 2: does a dozen things that for any other administration would

694
00:39:33,360 --> 00:39:38,520
Speaker 2: be an enormous scandal, and they just like vanish into

695
00:39:38,960 --> 00:39:40,080
Speaker 2: the media ether.

696
00:39:43,080 --> 00:39:57,359
Speaker 1: More. After a quick break, let's get right back into it.

697
00:40:00,760 --> 00:40:04,120
Speaker 1: So I wanted to briefly talk about this new research

698
00:40:04,200 --> 00:40:08,560
Speaker 1: from the Institute for Strategic Dialogue or ISD, who full disclosure,

699
00:40:08,640 --> 00:40:10,440
Speaker 1: I used to do a bunch of partnership work with.

700
00:40:11,080 --> 00:40:13,920
Speaker 1: They just put out a fascinating new study that really

701
00:40:13,920 --> 00:40:18,160
Speaker 1: shed some light into how the ecosystem of non consensual

702
00:40:18,280 --> 00:40:22,840
Speaker 1: deep fake material works online. Basically, tools to make and

703
00:40:22,880 --> 00:40:27,440
Speaker 1: distribute this kind of material are all over social media.

704
00:40:27,560 --> 00:40:31,080
Speaker 1: ISD analyzed web traffic to thirty one websites that provide

705
00:40:31,120 --> 00:40:34,000
Speaker 1: deep fake tools and found that those sites got a

706
00:40:34,000 --> 00:40:37,000
Speaker 1: combined twenty one million visits a month, with the most

707
00:40:37,000 --> 00:40:41,360
Speaker 1: popular sites getting over three million visits in one month.

708
00:40:41,719 --> 00:40:45,360
Speaker 1: As of May. ISD's analysis found thirty one active deep

709
00:40:45,400 --> 00:40:49,480
Speaker 1: fake tools that were easily discoverable on x four chan

710
00:40:49,680 --> 00:40:54,000
Speaker 1: and common search engines. These tools can create realistic, explicit

711
00:40:54,040 --> 00:40:56,920
Speaker 1: deep fakes from a single photo, and we already know

712
00:40:57,040 --> 00:40:59,520
Speaker 1: what that means people who are targeted with this kind

713
00:40:59,520 --> 00:41:03,440
Speaker 1: of thing. There's a potential for social exclusion, job discrimination,

714
00:41:03,840 --> 00:41:08,160
Speaker 1: and debilitating emotional stress for the victims targeted, especially people

715
00:41:08,280 --> 00:41:12,279
Speaker 1: in public positions. I've often said this, this is not

716
00:41:12,480 --> 00:41:17,920
Speaker 1: just about, you know, naughty pictures. It's horrifying, but in

717
00:41:18,000 --> 00:41:21,160
Speaker 1: my book, it is definitely a democracy issue. Right. If

718
00:41:21,360 --> 00:41:23,759
Speaker 1: the people who are targeted this kind of thing are

719
00:41:23,920 --> 00:41:28,560
Speaker 1: overwhelmingly women, those women, especially women in public positions or

720
00:41:28,760 --> 00:41:31,239
Speaker 1: elected officials and things like that, it is going to

721
00:41:31,360 --> 00:41:34,520
Speaker 1: keep women who are targeted from running for those positions

722
00:41:34,560 --> 00:41:38,279
Speaker 1: and taking a more public role in civic participation. And

723
00:41:38,320 --> 00:41:41,120
Speaker 1: it's going to keep us all from the representative democracy

724
00:41:41,120 --> 00:41:45,280
Speaker 1: that we deserve. So it's not just an issue of gross,

725
00:41:45,320 --> 00:41:48,440
Speaker 1: creepy pictures, which it is. It is a democracy issue

726
00:41:48,480 --> 00:41:50,440
Speaker 1: that we should all be concerned about.

727
00:41:51,400 --> 00:41:55,319
Speaker 2: Yes, And I think that's a really good point to make.

728
00:41:55,880 --> 00:41:58,760
Speaker 2: You know, after the segment that we just talked about

729
00:41:59,640 --> 00:42:06,840
Speaker 2: about regulating speech about health online as a democracy issue,

730
00:42:06,880 --> 00:42:12,239
Speaker 2: because it's democracy is complicated, and it doesn't just mean

731
00:42:12,480 --> 00:42:16,520
Speaker 2: anybody can say anything they want as like the be

732
00:42:16,680 --> 00:42:19,239
Speaker 2: all and all virtue of what it means to be

733
00:42:19,280 --> 00:42:24,480
Speaker 2: a democracy, Like you just said, the ability of women

734
00:42:24,560 --> 00:42:27,319
Speaker 2: to run for office and just like show up online

735
00:42:27,480 --> 00:42:30,680
Speaker 2: and exist and to be able to do that in

736
00:42:30,680 --> 00:42:36,040
Speaker 2: a way where they aren't being harassed and subject to

737
00:42:37,520 --> 00:42:41,520
Speaker 2: like new toify apps and things. That's also a democracy issue, right.

738
00:42:42,080 --> 00:42:44,799
Speaker 2: I think there's a lot to balance there, and it's

739
00:42:47,719 --> 00:42:52,520
Speaker 2: i think online, like so many things, the conversation gets

740
00:42:52,600 --> 00:42:58,399
Speaker 2: immediately taken to the extreme of like really fetishizing one

741
00:42:58,440 --> 00:43:03,279
Speaker 2: aspect of democracy and leaving out that aspect that you

742
00:43:03,400 --> 00:43:07,400
Speaker 2: mentioned of like in some cases there does you know

743
00:43:07,480 --> 00:43:11,239
Speaker 2: every single person can't act with complete freedom all the

744
00:43:11,280 --> 00:43:14,960
Speaker 2: time if that means that it's going to restrict the

745
00:43:15,000 --> 00:43:22,360
Speaker 2: ability of a whole class of people to participate in society.

746
00:43:21,440 --> 00:43:25,960
Speaker 1: Exactly very well put. So. You might think that these

747
00:43:26,080 --> 00:43:29,120
Speaker 1: newdify apps are hard to find, that they're like on

748
00:43:29,160 --> 00:43:33,280
Speaker 1: the dark web or something, but according to this research,

749
00:43:33,719 --> 00:43:37,719
Speaker 1: it is very simple to find tools like neudify apps online.

750
00:43:37,880 --> 00:43:41,479
Speaker 1: According to the authors, searches on Google, Yahoo, and Being

751
00:43:41,560 --> 00:43:45,600
Speaker 1: for terms like Newdify, undress app, or deep Nude usually

752
00:43:45,600 --> 00:43:49,160
Speaker 1: returned at least one of these tools within the first

753
00:43:49,160 --> 00:43:52,440
Speaker 1: twenty results last year or four for media also noticed

754
00:43:52,480 --> 00:43:55,160
Speaker 1: that Google was showing ads for some of these apps,

755
00:43:55,480 --> 00:43:59,040
Speaker 1: thing in particular made these tools especially easy to find,

756
00:43:59,239 --> 00:44:01,640
Speaker 1: with the top result for all three of these searches

757
00:44:01,719 --> 00:44:05,880
Speaker 1: being new toified tools. These findings focused on organic search results,

758
00:44:05,920 --> 00:44:09,640
Speaker 1: not paid ads. The researchers also found that X was

759
00:44:09,680 --> 00:44:13,160
Speaker 1: a major platform for spreading these tools. Does this shock you?

760
00:44:13,239 --> 00:44:17,640
Speaker 2: Mic it does not know? I mean, I'm What would

761
00:44:17,719 --> 00:44:21,680
Speaker 2: surprise me is if groc itself refused to just do

762
00:44:21,760 --> 00:44:23,800
Speaker 2: this for somebody, that would be surprising.

763
00:44:23,880 --> 00:44:26,320
Speaker 1: Ask Grock if you you can just put a picture

764
00:44:26,320 --> 00:44:29,000
Speaker 1: of anybody and ask Rock like, undress this person and

765
00:44:29,040 --> 00:44:31,279
Speaker 1: they'll they'll put them in a bikini. So, out of

766
00:44:31,320 --> 00:44:34,000
Speaker 1: almost half a million mentions between June twenty twenty and

767
00:44:34,040 --> 00:44:37,520
Speaker 1: July twenty twenty five, more than seventy percent nearly two

768
00:44:37,640 --> 00:44:40,439
Speaker 1: hundred and ninety thousand of the results of these things

769
00:44:40,480 --> 00:44:43,920
Speaker 1: were on X. Much of this activity appeared to come

770
00:44:43,920 --> 00:44:47,480
Speaker 1: from bots identified by repetitive user names, identical post styles,

771
00:44:47,520 --> 00:44:50,719
Speaker 1: and similar profile pictures. So even though a lot of

772
00:44:50,719 --> 00:44:53,880
Speaker 1: this seemed to be automated, the volume of it is

773
00:44:53,880 --> 00:44:57,120
Speaker 1: still pretty concerning because it is likely drawing new users

774
00:44:57,120 --> 00:45:00,680
Speaker 1: to tools that can be used illegally in certain situations.

775
00:45:01,520 --> 00:45:04,640
Speaker 1: This is absolutely horrifying, according to this research. In early

776
00:45:04,640 --> 00:45:08,320
Speaker 1: twenty twenty three, there was a notable surge in mentions

777
00:45:08,320 --> 00:45:11,560
Speaker 1: of these tools on Tumblr after a woman shared her

778
00:45:11,640 --> 00:45:16,520
Speaker 1: experience of being sexually harassed using newdify and deep fake tools.

779
00:45:17,480 --> 00:45:20,359
Speaker 1: As many victims of malicious deep thakes have repeatedly pointed out,

780
00:45:20,440 --> 00:45:24,040
Speaker 1: speaking about this kind of personal harassment or even calling

781
00:45:24,040 --> 00:45:27,040
Speaker 1: out the harassment of others just comes with the risk

782
00:45:27,080 --> 00:45:32,120
Speaker 1: of attracting further attention and thus attracting additional abuse. And

783
00:45:32,480 --> 00:45:37,880
Speaker 1: I guess that's what really infuriates me and simultaneously breaks

784
00:45:37,920 --> 00:45:41,120
Speaker 1: my heart about this is that whenever I research an incident,

785
00:45:41,440 --> 00:45:45,800
Speaker 1: like an incident in a school involving minor boys using

786
00:45:45,840 --> 00:45:48,560
Speaker 1: these tools to make and distribute images of the minor

787
00:45:48,600 --> 00:45:52,280
Speaker 1: girls in their class, something I see again and again

788
00:45:52,320 --> 00:45:56,279
Speaker 1: as the boys saying some iteration or something along the

789
00:45:56,320 --> 00:45:59,359
Speaker 1: lines of, well, this can't be illegal or this can't

790
00:45:59,400 --> 00:46:01,600
Speaker 1: be wrong, because it's so easy to find online that

791
00:46:01,719 --> 00:46:04,600
Speaker 1: this was illegal. I wouldn't be able to just Google

792
00:46:05,200 --> 00:46:08,400
Speaker 1: or use a mainstream social media platform to find this

793
00:46:08,480 --> 00:46:10,920
Speaker 1: thing so easily. Kind of assuming just because it's so

794
00:46:11,520 --> 00:46:14,360
Speaker 1: easily available, it's probably legal and find to be using.

795
00:46:14,400 --> 00:46:17,760
Speaker 1: And I can see why they would think that, because

796
00:46:17,760 --> 00:46:20,319
Speaker 1: in some ways they are absolutely correct, right, the fact

797
00:46:20,360 --> 00:46:24,520
Speaker 1: that platforms like X allow this stuff is essentially a

798
00:46:24,600 --> 00:46:27,560
Speaker 1: kind of implicit endorsement. But I think it just shows

799
00:46:27,920 --> 00:46:32,480
Speaker 1: how much we have failed our youth because when this

800
00:46:32,600 --> 00:46:36,360
Speaker 1: kind of harm is so easy to find online after

801
00:46:36,400 --> 00:46:39,480
Speaker 1: a while, they're right, it does kind of look like permission.

802
00:46:40,400 --> 00:46:44,560
Speaker 2: Yeah, that's a really good point. When it's that available,

803
00:46:45,480 --> 00:46:48,719
Speaker 2: it looks like permission. You know, it is like an

804
00:46:48,719 --> 00:46:52,120
Speaker 2: implicit either an implicit wink in a nod, or even

805
00:46:52,160 --> 00:46:57,440
Speaker 2: just an explicit thumbs up to go ahead and use it.

806
00:46:58,840 --> 00:47:02,200
Speaker 2: And you know, the availability of something harmful like this,

807
00:47:05,040 --> 00:47:08,359
Speaker 2: I guess I'm like really stuck on this like balancing

808
00:47:08,760 --> 00:47:13,040
Speaker 2: different competing aspects of democracy thing. But like there are

809
00:47:13,280 --> 00:47:16,000
Speaker 2: things that these platforms could rain this in, right, Like

810
00:47:16,040 --> 00:47:19,680
Speaker 2: they could deprioritize these results, make these tools harder for

811
00:47:19,760 --> 00:47:24,880
Speaker 2: people to find, and so it wouldn't be bad like

812
00:47:24,960 --> 00:47:29,359
Speaker 2: passing a law to ban them but these platforms, if

813
00:47:29,440 --> 00:47:34,640
Speaker 2: they really cared, could take steps to limit the availability,

814
00:47:35,120 --> 00:47:41,600
Speaker 2: which would have huge harm production benefits, And yet they don't.

815
00:47:42,160 --> 00:47:45,759
Speaker 2: You know, just because something is legal doesn't mean that

816
00:47:46,560 --> 00:47:51,480
Speaker 2: it should be just pushed to every kid who types

817
00:47:51,719 --> 00:47:55,359
Speaker 2: a search term for it into whatever platform they're using.

818
00:47:55,440 --> 00:47:56,319
Speaker 2: Probably X.

819
00:47:56,880 --> 00:47:59,160
Speaker 1: Well, it goes back to my question, and I mean

820
00:47:59,200 --> 00:48:02,200
Speaker 1: this in a meaningful this is above my pay grade.

821
00:48:02,200 --> 00:48:04,080
Speaker 1: I am not smart enough to be the definitive voice

822
00:48:04,080 --> 00:48:08,200
Speaker 1: on this, But at what point is this platforms materially

823
00:48:08,239 --> 00:48:11,480
Speaker 1: benefiting from an illegal enterprise? If it is illegal to

824
00:48:11,640 --> 00:48:14,080
Speaker 1: use some of these new Toify apps, and these apps

825
00:48:14,080 --> 00:48:17,719
Speaker 1: are easily findable on platforms, and sometimes some cases advertised

826
00:48:17,760 --> 00:48:20,520
Speaker 1: on these platforms, at what point is it, Oh, you

827
00:48:20,560 --> 00:48:24,480
Speaker 1: are making money from an illegal enterprise that is disproportionately

828
00:48:24,520 --> 00:48:26,200
Speaker 1: harming girls children.

829
00:48:26,920 --> 00:48:29,239
Speaker 2: That's right. And another thing that they mentioned in this

830
00:48:29,400 --> 00:48:33,600
Speaker 2: study was that there were a lot of ads being

831
00:48:33,640 --> 00:48:38,920
Speaker 2: taken out on these platforms using the using the names

832
00:48:39,080 --> 00:48:43,120
Speaker 2: of these particular tools. What was interesting was that the

833
00:48:43,920 --> 00:48:46,120
Speaker 2: it sounded like in a lot of cases, the new

834
00:48:46,120 --> 00:48:49,520
Speaker 2: Toify tools themselves were not buying ads, but when the

835
00:48:49,560 --> 00:48:54,719
Speaker 2: tools got taken down through some sort of action or

836
00:48:54,880 --> 00:48:58,200
Speaker 2: for whatever reason, and so the tool no longer existed,

837
00:48:58,440 --> 00:49:02,120
Speaker 2: but people were still searching for it. Other companies would

838
00:49:02,239 --> 00:49:04,879
Speaker 2: pay would be on those search terms when they would

839
00:49:04,920 --> 00:49:09,160
Speaker 2: buy their ads on you know, Meta or x or wherever.

840
00:49:09,600 --> 00:49:13,920
Speaker 2: And so there's a great example of just money flowing

841
00:49:13,960 --> 00:49:19,040
Speaker 2: directly to these platforms to keep these tools in the

842
00:49:19,120 --> 00:49:24,640
Speaker 2: zeitgeist in circulation. Yeah, you raise a great point, like

843
00:49:24,680 --> 00:49:29,040
Speaker 2: shouldn't they have some accountability for making money off of

844
00:49:29,040 --> 00:49:32,000
Speaker 2: these tools that in a lot of cases can be

845
00:49:32,120 --> 00:49:33,200
Speaker 2: like very armful.

846
00:49:33,480 --> 00:49:35,759
Speaker 1: I mean, Christianna had the cops show up to her

847
00:49:35,840 --> 00:49:39,600
Speaker 1: doorstep for supposedly stealing a package that they said was

848
00:49:39,680 --> 00:49:42,600
Speaker 1: worth less than twenty five dollars. At what point are

849
00:49:42,600 --> 00:49:45,800
Speaker 1: the cops gonna show up at Elon Musk's doorstep.

850
00:49:45,360 --> 00:49:49,800
Speaker 2: For this Dahn? That is another good question, Bridget. We

851
00:49:49,800 --> 00:49:52,120
Speaker 2: we better move on to the next segment before we

852
00:49:52,640 --> 00:49:54,840
Speaker 2: started going out full on revolution.

853
00:49:57,200 --> 00:49:59,040
Speaker 1: You know who I wanted to buy side of that revolution?

854
00:49:59,360 --> 00:49:59,960
Speaker 1: Will Smith?

855
00:50:01,480 --> 00:50:03,239
Speaker 2: Well, you're gonna get Bob Ferguson.

856
00:50:05,560 --> 00:50:07,240
Speaker 1: He just needs to charge his bone.

857
00:50:07,560 --> 00:50:10,759
Speaker 2: Yeah, I just used to charge his phone. Gotta make

858
00:50:10,800 --> 00:50:11,120
Speaker 2: a call.

859
00:50:11,520 --> 00:50:14,760
Speaker 1: Do you want to say when our Halloween costumes are gonna.

860
00:50:14,520 --> 00:50:19,080
Speaker 2: Be Oh yeah, happily. I am. I am Bob Ferguson

861
00:50:19,400 --> 00:50:25,160
Speaker 2: from the movie One Battle after Another, Leo's character. It's uh.

862
00:50:26,880 --> 00:50:29,880
Speaker 2: I put together what I think is a pretty pretty

863
00:50:29,920 --> 00:50:33,680
Speaker 2: good costume and I've just been like wearing it around

864
00:50:33,760 --> 00:50:37,200
Speaker 2: every time I've gone out for the past week. A

865
00:50:37,239 --> 00:50:39,200
Speaker 2: few people get it and they really like it.

866
00:50:40,160 --> 00:50:43,400
Speaker 1: Yeah, a few people. What's funny is that I know

867
00:50:43,560 --> 00:50:47,759
Speaker 1: you so well. You are Bob Ferguson for Halloween, and

868
00:50:47,800 --> 00:50:50,680
Speaker 1: you are also kind of Bob Ferguson in real life.

869
00:50:50,800 --> 00:50:53,120
Speaker 1: Like I'll let the listeners speculate on what I mean

870
00:50:53,160 --> 00:50:56,359
Speaker 1: by that, but you have a lot in common with him,

871
00:50:56,760 --> 00:51:00,560
Speaker 1: And when I saw the movie, I thought, this is Mike,

872
00:51:00,880 --> 00:51:03,680
Speaker 1: you are very similar to above. For I don't mean

873
00:51:03,719 --> 00:51:05,799
Speaker 1: this as an insult. I'm sure you know that.

874
00:51:06,120 --> 00:51:08,680
Speaker 2: No, I take it well, and to be clear, there

875
00:51:08,680 --> 00:51:14,200
Speaker 2: were also several key differences, but I yeah, it fits.

876
00:51:14,200 --> 00:51:16,560
Speaker 2: The costume fits. The funny thing about it, though, is

877
00:51:16,600 --> 00:51:18,960
Speaker 2: like if people don't recognize it from the movie, you know,

878
00:51:18,960 --> 00:51:22,759
Speaker 2: it got like a big oversized flannel robe and like

879
00:51:22,760 --> 00:51:27,080
Speaker 2: a hat and those uh, like big dark sunglasses that

880
00:51:27,320 --> 00:51:30,200
Speaker 2: people can wear over their regular glasses. If people don't

881
00:51:30,200 --> 00:51:33,440
Speaker 2: recognize the costume. I just look like a bumb which.

882
00:51:34,360 --> 00:51:39,799
Speaker 1: No offense, but like that's U. I don't know how

883
00:51:39,800 --> 00:51:41,920
Speaker 1: to finish the sentence without sounding offensive. But you know

884
00:51:41,960 --> 00:51:42,919
Speaker 1: what I'm getting out of here?

885
00:51:43,360 --> 00:51:46,319
Speaker 2: I think I do. I mean I generally in my

886
00:51:46,440 --> 00:51:50,360
Speaker 2: life people aren't mistaking me for a bum all that often.

887
00:51:51,160 --> 00:51:55,080
Speaker 2: I guess it comes up. How about you? What are

888
00:51:55,080 --> 00:51:56,280
Speaker 2: you gonna be for Halloween?

889
00:51:56,760 --> 00:52:01,600
Speaker 1: Blade? Blade from the movie Blaze in the Titular Titular

890
00:52:01,640 --> 00:52:04,560
Speaker 1: Blade from the movie Blade, which we you and I

891
00:52:04,680 --> 00:52:07,400
Speaker 1: rewatched recently, holds up very well.

892
00:52:07,480 --> 00:52:13,000
Speaker 2: I thought, Yeah, it moves along, it's action packed. He

893
00:52:13,080 --> 00:52:15,880
Speaker 2: barely speaks, but when he does, he's got some good lines.

894
00:52:16,520 --> 00:52:18,799
Speaker 1: He gotta talk like this. I've been working on my

895
00:52:18,880 --> 00:52:19,840
Speaker 1: Blade voice.

896
00:52:20,440 --> 00:52:22,360
Speaker 2: He has a very low voice.

897
00:52:21,960 --> 00:52:24,040
Speaker 1: But he doesn't really say a lot. But it's a

898
00:52:24,040 --> 00:52:28,600
Speaker 1: lot of cool one liners delivered like this.

899
00:52:29,200 --> 00:52:32,799
Speaker 2: Yeah, the cool one liners. That's that's That's what I

900
00:52:32,840 --> 00:52:38,520
Speaker 2: want in an action hero. Blade, Spider Man, uh.

901
00:52:39,560 --> 00:52:41,319
Speaker 1: Whoils A lot of them have.

902
00:52:41,320 --> 00:52:44,480
Speaker 2: Good one liners like that. You don't want long soliloquies.

903
00:52:44,520 --> 00:52:48,880
Speaker 2: You just want a quick little wood liner and then uh,

904
00:52:48,920 --> 00:52:49,800
Speaker 2: maybe some perchase.

905
00:52:50,040 --> 00:52:52,200
Speaker 1: I'm worried that people are just gonna think I'm Goth.

906
00:52:52,440 --> 00:52:55,760
Speaker 1: They're not gonna know that I'm Blade from the movie Blade.

907
00:52:55,880 --> 00:52:59,280
Speaker 1: They're gonna just think I'm Is this an old goth

908
00:52:59,360 --> 00:53:00,000
Speaker 1: An old blood?

909
00:53:02,640 --> 00:53:05,400
Speaker 2: Well, I think it's Katata will probably help them figure

910
00:53:05,400 --> 00:53:05,719
Speaker 2: it out.

911
00:53:06,040 --> 00:53:09,480
Speaker 1: An old black goth martial arts enthusiast just hanging out

912
00:53:09,480 --> 00:53:13,680
Speaker 1: on Halloween. Okay, wait, so I have one more thing.

913
00:53:13,920 --> 00:53:16,160
Speaker 1: It's actually kind of a cool story, I think, Can

914
00:53:16,200 --> 00:53:17,960
Speaker 1: I can I get? Can you give me one more thing?

915
00:53:18,160 --> 00:53:22,560
Speaker 2: Yeah? Please? I mean it's been, uh, just one bad

916
00:53:22,600 --> 00:53:24,879
Speaker 2: story after another. So if you've got something good, let's

917
00:53:24,920 --> 00:53:25,279
Speaker 2: hear it.

918
00:53:25,680 --> 00:53:29,200
Speaker 1: Good one good one and it involves good Reads. So

919
00:53:29,239 --> 00:53:31,680
Speaker 1: that was a good segue. So I love this story

920
00:53:31,719 --> 00:53:34,000
Speaker 1: so much. Shout out to four O four again for

921
00:53:34,160 --> 00:53:39,320
Speaker 1: another banger. So this rogue librarian on Goodreads is editing

922
00:53:39,360 --> 00:53:44,640
Speaker 1: book titles to protest Goodreads censorship. According to four four,

923
00:53:44,840 --> 00:53:49,279
Speaker 1: one of the sites, volunteer moderators, which Goodreads calls librarians,

924
00:53:49,719 --> 00:53:53,600
Speaker 1: swapped the blurbs and pictures and titles of a handful

925
00:53:53,640 --> 00:53:58,320
Speaker 1: of books, books like Reese Witherspoon's thriller Gone Before Goodbye,

926
00:53:58,360 --> 00:54:01,200
Speaker 1: which I did not even know Witherspoon, the actress, is

927
00:54:01,239 --> 00:54:03,600
Speaker 1: now writing thrillers. Love a thriller, I need to check

928
00:54:03,640 --> 00:54:07,399
Speaker 1: that out, And the Nicholas Sparks bestseller remain. They are

929
00:54:07,480 --> 00:54:10,399
Speaker 1: swapping out all of the information and blurbs of those

930
00:54:10,440 --> 00:54:15,400
Speaker 1: books with the pictures and blurbs from Eric Trump's book

931
00:54:15,760 --> 00:54:21,600
Speaker 1: Under Siege, adding the subtitle quote Goodreads censorship in favor

932
00:54:21,800 --> 00:54:24,080
Speaker 1: of Trump. So I did not even know that Eric

933
00:54:24,120 --> 00:54:26,319
Speaker 1: Trump had written a book. I don't even need to

934
00:54:26,320 --> 00:54:30,200
Speaker 1: look it up. Guarantee that thing was ghost written for sure. Basically,

935
00:54:30,239 --> 00:54:33,000
Speaker 1: they are altering all of these books and swapping in

936
00:54:33,239 --> 00:54:38,640
Speaker 1: Eric Trump's book, explaining that Goodreads is removing criticism of

937
00:54:38,760 --> 00:54:43,239
Speaker 1: Eric Trump's book from the site, saying quote silencing criticism

938
00:54:43,239 --> 00:54:47,520
Speaker 1: of political figures, especially those associated with authoritarian movements, helps

939
00:54:47,560 --> 00:54:53,160
Speaker 1: normalize and strengthen those movements. When we let powerful people's

940
00:54:53,200 --> 00:54:56,040
Speaker 1: books be protected from criticism, we give up the right

941
00:54:56,120 --> 00:54:59,839
Speaker 1: to hold power accountable. These changes were up on good

942
00:55:00,080 --> 00:55:03,120
Speaker 1: Reads for a few hours before being corrected, so.

943
00:55:04,040 --> 00:55:06,040
Speaker 2: That librarian is absolutely correct.

944
00:55:06,160 --> 00:55:06,800
Speaker 1: That is.

945
00:55:09,360 --> 00:55:13,280
Speaker 2: The story, in as far as I could deal. Every

946
00:55:13,600 --> 00:55:18,920
Speaker 2: democracy that has slidden into authoritarianism, that's how it happens,

947
00:55:19,000 --> 00:55:25,440
Speaker 2: just like people dialing back criticism of the people in power,

948
00:55:25,880 --> 00:55:31,160
Speaker 2: self censoring and just letting them get away with it.

949
00:55:31,480 --> 00:55:33,000
Speaker 2: So good on this librarian.

950
00:55:33,239 --> 00:55:37,720
Speaker 1: Absolutely so this librarian, this rogue librarian who was protesting Goodreads,

951
00:55:37,760 --> 00:55:40,840
Speaker 1: which is owned by Amazon, says that Goodreads is censoring

952
00:55:41,080 --> 00:55:44,799
Speaker 1: negative reviews of Eric Trump's book. They said that Goodreads

953
00:55:44,840 --> 00:55:47,719
Speaker 1: deleted negative reviews of Under Siege as they came in

954
00:55:47,840 --> 00:55:51,680
Speaker 1: after its publication on October fourteenth. These were honest opinions

955
00:55:51,680 --> 00:55:54,560
Speaker 1: from real readers who disagreed with the book's contents, the

956
00:55:54,560 --> 00:55:57,960
Speaker 1: librarian said in their post. When people noticed and complained,

957
00:55:58,239 --> 00:56:01,640
Speaker 1: Goodreads deleted all reviews use of the book, positive and

958
00:56:01,719 --> 00:56:05,280
Speaker 1: negative alike. This wasn't an accident or a one time glitch.

959
00:56:05,320 --> 00:56:08,160
Speaker 1: It was a deliberate pattern. So four or four reached

960
00:56:08,160 --> 00:56:11,320
Speaker 1: out to Goodreads to ask if the platform was disallowing

961
00:56:11,360 --> 00:56:14,319
Speaker 1: these reviews, and it does sound like Goodreads was trying

962
00:56:14,360 --> 00:56:18,400
Speaker 1: to prevent review bombing of Eric Trump's book. In response

963
00:56:18,480 --> 00:56:21,680
Speaker 1: to the questions about the reviews for the book, a

964
00:56:21,719 --> 00:56:25,239
Speaker 1: spokesperson from Goodreads told for for Media that Goodreads has

965
00:56:25,280 --> 00:56:28,760
Speaker 1: systems in place to detect unusual activity on book pages

966
00:56:28,800 --> 00:56:32,120
Speaker 1: and may temporarily limit rating and reviews that don't adhere

967
00:56:32,160 --> 00:56:35,000
Speaker 1: to our review in community guidelines. In all cases, we

968
00:56:35,160 --> 00:56:38,400
Speaker 1: enforce clear standards and remove content and or accounts that

969
00:56:38,520 --> 00:56:41,279
Speaker 1: violate these guidelines. So we did an episode about this.

970
00:56:41,400 --> 00:56:45,200
Speaker 1: But review bombing is a legit problem on Goodreads. But

971
00:56:45,719 --> 00:56:48,239
Speaker 1: this is also the nature of the complaint according to

972
00:56:48,280 --> 00:56:52,279
Speaker 1: this rogue librarian. They said, when a platform removes criticism

973
00:56:52,320 --> 00:56:55,640
Speaker 1: of a political book while leaving praise, or removes everything

974
00:56:55,680 --> 00:56:59,480
Speaker 1: to hide that criticism ever existed, they're not staying neutral

975
00:56:59,680 --> 00:57:03,080
Speaker 1: there a side. Goodreads is owned by Amazon, one of

976
00:57:03,120 --> 00:57:06,960
Speaker 1: the world's largest companies. When major platforms decide which opinions

977
00:57:06,960 --> 00:57:09,840
Speaker 1: can exist and which must disappear, they shape what people

978
00:57:09,880 --> 00:57:14,239
Speaker 1: think is true or acceptable. Honestly, I love everything about

979
00:57:14,239 --> 00:57:17,600
Speaker 1: this story. Hate everything about Eric Trump. It sounds like

980
00:57:17,640 --> 00:57:19,520
Speaker 1: people did not like his book. It sounds like they

981
00:57:19,520 --> 00:57:21,480
Speaker 1: read his book and legitimately took issue with it, and

982
00:57:21,520 --> 00:57:25,480
Speaker 1: so they were expressing that and I love that. I

983
00:57:25,520 --> 00:57:28,919
Speaker 1: also just love that it took a rogue of Goodreads

984
00:57:29,000 --> 00:57:33,640
Speaker 1: librarian volunteer to pull this off, like, not a whistleblower,

985
00:57:33,920 --> 00:57:38,400
Speaker 1: not a hacker, just a super annoyed, pissed off set

986
00:57:38,480 --> 00:57:42,440
Speaker 1: up volunteer. It really reminds me of that Margaret Mead quote.

987
00:57:42,880 --> 00:57:45,720
Speaker 1: Never doubt that a small group of thoughtful, committed citizens

988
00:57:45,720 --> 00:57:48,560
Speaker 1: can change the world. Indeed, it's the only thing that

989
00:57:48,600 --> 00:57:52,280
Speaker 1: ever has in this case, Never doubt that an annoyed,

990
00:57:52,440 --> 00:57:55,480
Speaker 1: bookished volunteer can also change the world.

991
00:57:56,080 --> 00:57:59,360
Speaker 2: Yeah, and not just any volunteer, a librarian.

992
00:57:59,600 --> 00:58:02,640
Speaker 1: Yes, shout out to the librarians. Sometimes it really does

993
00:58:02,680 --> 00:58:05,360
Speaker 1: feel like they are the only thing standing between us

994
00:58:05,440 --> 00:58:10,360
Speaker 1: and a complete descent into a fascist nightmare healthscape.

995
00:58:10,560 --> 00:58:13,800
Speaker 2: Absolutely, they are the keepers of knowledge during a time

996
00:58:14,040 --> 00:58:20,880
Speaker 2: when knowledge is being questions, reality is being questioned. We

997
00:58:20,920 --> 00:58:26,160
Speaker 2: live in different realities. Maybe librarians will be the ones

998
00:58:26,400 --> 00:58:32,200
Speaker 2: to help us make sense of it and save us.

999
00:58:32,800 --> 00:58:37,280
Speaker 2: So brig it. Today is Halloween. How are you going

1000
00:58:37,360 --> 00:58:39,320
Speaker 2: to be celebrating in your Blade costume?

1001
00:58:39,720 --> 00:58:42,240
Speaker 1: Oh? I give out candy every year. Even though I

1002
00:58:42,320 --> 00:58:44,960
Speaker 1: live in a building and a neighborhood where people might

1003
00:58:45,000 --> 00:58:48,800
Speaker 1: not associate giving out candy, It is truly one of

1004
00:58:48,840 --> 00:58:51,520
Speaker 1: the things I love the most. I love the kids

1005
00:58:51,560 --> 00:58:55,000
Speaker 1: in costumes, I love being in costume. Oh, I'll be

1006
00:58:55,080 --> 00:58:59,560
Speaker 1: giving out candy. If you see Blade, come say hello.

1007
00:59:00,040 --> 00:59:02,360
Speaker 1: Unless you're a vampire. In which case, watch out.

1008
00:59:02,920 --> 00:59:05,760
Speaker 2: Ooh scary words for the vampires.

1009
00:59:06,160 --> 00:59:09,800
Speaker 1: Well, Mike, where can folks keep in touch with us

1010
00:59:10,120 --> 00:59:12,640
Speaker 1: on this subooky season and beyond.

1011
00:59:13,040 --> 00:59:17,080
Speaker 2: People will can leave us a comment on Spotify. They

1012
00:59:17,160 --> 00:59:20,200
Speaker 2: can send us an email at Hello at tangote dot com.

1013
00:59:20,240 --> 00:59:23,640
Speaker 2: We love getting listener emails. We people have been sending

1014
00:59:23,720 --> 00:59:26,920
Speaker 2: in some really interesting, like thought provoking, interesting ones lately,

1015
00:59:26,960 --> 00:59:28,760
Speaker 2: so thank you for that. Please keep it up. And

1016
00:59:28,800 --> 00:59:31,560
Speaker 2: we're we're going to do that mailbag episode real student,

1017
00:59:31,600 --> 00:59:35,160
Speaker 2: so please keep the emails coming. People can check out

1018
00:59:35,160 --> 00:59:40,840
Speaker 2: Bridget socials. Her username is Bridget Marie in DC on

1019
00:59:40,920 --> 00:59:44,440
Speaker 2: both Instagram and TikTok, and we have a YouTube channel

1020
00:59:44,440 --> 00:59:46,760
Speaker 2: that we just posted something today. The name of the

1021
00:59:46,840 --> 00:59:48,840
Speaker 2: channel is there are no girls on the Internet. It's

1022
00:59:48,960 --> 00:59:49,960
Speaker 2: very easy to remember.

1023
00:59:50,280 --> 00:59:52,920
Speaker 1: Well, Mike, thank you so much for being here. Happy

1024
00:59:52,960 --> 00:59:55,560
Speaker 1: Halloween and thanks to all of you for listening. I

1025
00:59:55,600 --> 01:00:00,480
Speaker 1: hope you have a spooky and safe Halloween. I will

1026
01:00:00,520 --> 01:00:07,800
Speaker 1: see you on the internet. Got a story about an

1027
01:00:07,840 --> 01:00:09,800
Speaker 1: interesting thing in tech, or just want to say hi.

1028
01:00:10,200 --> 01:00:12,440
Speaker 1: You can reach us at Hello at tangody dot com.

1029
01:00:12,480 --> 01:00:14,920
Speaker 1: You can also find transcripts for today's episode at tenggody

1030
01:00:14,960 --> 01:00:17,040
Speaker 1: dot com There Are No Girls on the Internet was

1031
01:00:17,040 --> 01:00:19,960
Speaker 1: created by me bridget Tod. It's a production of iHeartRadio,

1032
01:00:20,000 --> 01:00:23,600
Speaker 1: an unbossed creative. Jonathan Strickland is our executive producer. Tarry

1033
01:00:23,640 --> 01:00:26,760
Speaker 1: Harrison is our producer and sound engineer. Michael Almato is

1034
01:00:26,760 --> 01:00:30,320
Speaker 1: our contributing producer. I'm your host, bridget Todd. If you

1035
01:00:30,320 --> 01:00:32,040
Speaker 1: want to help us grow, rate and review us on

1036
01:00:32,080 --> 01:00:35,680
Speaker 1: Apple Podcasts. For more podcasts from iHeartRadio, check out the

1037
01:00:35,720 --> 01:00:45,240
Speaker 1: iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.