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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 Bridget Tad and this

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Speaker 1: is there are No Girls on the Internet. I'm here

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Speaker 1: with my producer, Mike Hey.

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Speaker 2: Mike Hey, Bridget.

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Speaker 1: How about this smoke? Right?

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Speaker 2: It's really something here in duc. It's like the only

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Speaker 2: thing anybody's been able to talk about for days.

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Speaker 1: I have not left my house in forty eight hours.

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Speaker 1: And here's what you might have missed this week on

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Speaker 1: the internet. You know that song that goes I always

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Speaker 1: feel like somebody's watching me. Well, if you have a

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Speaker 1: ring camera, that somebody watching might be an Amazon employee.

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Speaker 1: And that's because before twenty seventeen, Amazon employees could just

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Speaker 1: access whoever's ring camera they wanted, and some of them did.

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Speaker 1: This is according to a court filing from the Federal

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Speaker 1: Trade Commission when in announced a five point eight million

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Speaker 1: dollar settlement with Amazon over privacy violations. So this whole

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Speaker 1: thing is about as creepy as you would expect. It

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Speaker 1: sounds like there was just over broad access given to

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Speaker 1: employees and also contractors to customers ring footage, and that

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Speaker 1: there might have been just a generally lax attitude around

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Speaker 1: accessing that footage at Amazon. According to the filing, Ring

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Speaker 1: gave every employee full access to every customer video before

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Speaker 1: twenty seventeen and failed to patch bugs in the system

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Speaker 1: that allowed hackers to access cameras and scare consumers. Now,

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Speaker 1: I gotta say this was not just like a one

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Speaker 1: time thing. It sounds like a pervasive issue. Ring employees

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Speaker 1: were spying on women. In twenty seventeen, an employee of

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Speaker 1: Ring viewed videos made by at least eighty one female

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Speaker 1: consumers and Ring employees using Ring products undetected by Ring.

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Speaker 1: The employee continued spuying for months. He was looking specifically

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Speaker 1: for cameras with labels that suggested they were in people's

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Speaker 1: intimate spaces. So they had labels like master, bedroom camera

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Speaker 1: or bathroom camera, so it's pretty clear what was going on.

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Speaker 1: In this instance, this employee was only caught after a

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Speaker 1: supervisor noticed that the male employee was only viewing videos

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Speaker 1: of quote pretty girls, which even that supervisor's explanation, I

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Speaker 1: feel like, is pretty gross. In another incident, an employee

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Speaker 1: gave someone's ex husband access to their Ring footage without

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Speaker 1: their consent. So you can kind of get a sense

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Speaker 1: of how dangerous and serious. That could be like if

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Speaker 1: you're going through a contentious divorce or you have an

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Speaker 1: abusive X. The fact that Ring was just handing over

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Speaker 1: your ring footage to your ex without your consent or

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Speaker 1: knowledge is pretty problematic. So it was not just random

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Speaker 1: women that these Ring employees didn't know. Ring employees were

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Speaker 1: also spying on each other. Another incident allegedly occurred in

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Speaker 1: twenty eighteen when a male employee allegedly accessed a fellow

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Speaker 1: female employees camera and watched her stored video recordings without

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Speaker 1: her permission. And can you imagine, Like you go to work,

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Speaker 1: there's Greg at the water cooler, cut to Greg watching

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Speaker 1: you in your home. Like that is so fucked. So

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Speaker 1: Ring employees were also gifting people with cameras and then

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Speaker 1: using those cameras to spy on them. An employee was

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Speaker 1: found to have given Ring devices to people and then

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Speaker 1: watched their videos without their knowledge, Like some gift. Oh

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Speaker 1: here's the present, it's a Ring camera, I'll see you later.

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Speaker 1: Totally fucked. Give the gift of Greg watching, lurking spying,

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Speaker 1: terrible gift. So separately, Amazon also had to pay twenty

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Speaker 1: five million to settle allegations that it violated children's privacy

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Speaker 1: rights when it failed to delete Alecxa recordings at the

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Speaker 1: request of parents and kept them for longer than necessary.

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Speaker 2: Wow. Wow, So parents requested did Amazon delete them and

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Speaker 2: then they just didn't. That's an additional level.

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Speaker 1: Yeah, My understanding is that they said that they would

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Speaker 1: delete those recordings and then did not. So it kind

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Speaker 1: of goes back to this idea of you know, I

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Speaker 1: don't think that companies can just say one thing and

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Speaker 1: do another. And it sounds like the FTC agrees.

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Speaker 2: We talked about this last week with Google where they

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Speaker 2: said they were going to delete users abortion data and

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Speaker 2: then they just didn't.

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Speaker 1: Exactly like it definitely paints a larger portrait of negligence.

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Speaker 1: You know, this is all part of a push by

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Speaker 1: the FTC to regulate big tech and hold companies accountable

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Speaker 1: to putting profit above privacy. Now, I have said this

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Speaker 1: probably a hundred times on this show. I get why

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Speaker 1: someone would want a ring camera for their safety or

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Speaker 1: to feel secure in their homes, but I would never

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Speaker 1: allow one of these devices in my home. You know,

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Speaker 1: not that I would ever break any laws myself, but

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Speaker 1: people should be aware that police can and have accessed

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Speaker 1: your RING footage without your consent and without a warrant

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Speaker 1: because Ring partners with police departments. It sounds like even

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Speaker 1: after having to pay out millions of dollars for these

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Speaker 1: violations around spying and privacy, Amazon is still not admitting wrongdoing,

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Speaker 1: saying in a statement that they disagree with how these

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Speaker 1: instances were framed by the FTC, but they did, you know,

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Speaker 1: pay these fines. And so it just goes to show

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Speaker 1: like these companies don't care. They don't care about your security,

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Speaker 1: they don't care about your privacy, and they're callously praying

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Speaker 1: on and fostering a climate of fear, fear around crime,

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Speaker 1: fear around your neighbors, and tricking us into thinking that

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Speaker 1: it is a safe choice to have their devices in

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Speaker 1: your home, while all the while they are out here

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Speaker 1: putting us in danger. You know, I completely get a

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Speaker 1: lot of us feel vulnerable right now, feel scared right now.

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Speaker 1: I totally get it. But I believe that Amazon is

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Speaker 1: inflaming and exploiting and taking advantage of this vulnerability that

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Speaker 1: we might feel to sell us technology that ultimately harms us.

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Speaker 2: Yeah, and like you mentioned, this story happens to be

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Speaker 2: about Amazon, but it could just as well be a

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Speaker 2: story about Google we talked about last week, or or Tesla,

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Speaker 2: who a few months ago was in the news because

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Speaker 2: their engineers similarly had unfettered access to the cameras inside

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Speaker 2: people's cars, and they were using that to share videos

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Speaker 2: of each other of like, hey, look at this guy

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Speaker 2: picking his nose in his car hahaha Lol. But you know,

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Speaker 2: it could be Facebook, could be any of these big companies,

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Speaker 2: because this is just the sort of thing that we

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Speaker 2: get in surveillance capitalism, when we bring these devices into

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Speaker 2: our homes, where privacy is just an afterthought and the

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Speaker 2: commodification of our personal data is a gold rush for

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Speaker 2: these companies, so much so that you know, a few

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Speaker 2: million dollars in fines here and there is well worth

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Speaker 2: it to them. And so in this case, you know,

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Speaker 2: it's not like the Amazon executives were getting in on

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Speaker 2: the creeping. I assume it was just Greg and maybe

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Speaker 2: some of these buddies.

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Speaker 1: But I feel like I'm using Greg as a stand

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Speaker 1: in for the creepy employee because I've have been binge

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Speaker 1: washing session, so I'm like, oh, someone was doing something creepy,

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Speaker 1: has to be Greg, just like the name on the

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Speaker 1: top of my mind that I'm associating with like leccherous creeps.

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Speaker 1: No offense to any Greg's out there listening. You're not

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Speaker 1: all bad, No, just.

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Speaker 2: The one who's a member of the disgusting Brothers. But yeah, they,

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Speaker 2: I mean, yeah they, you know, Greg's the one creeping.

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Speaker 2: But it's the executives at the top that allowed it

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Speaker 2: to happen with these lack of security controls when they

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Speaker 2: I would are you had a responsibility to limit access

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Speaker 2: in a way that would protect people's privacy, but they didn't,

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Speaker 2: because why would they willingly put road bumps in the

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Speaker 2: way of unfettered access to all of the data just

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Speaker 2: to feed back into their profits and helping them make

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Speaker 2: more sales, and without regulation, that's just going to keep happening.

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Speaker 1: And I just don't think that what like thirty million

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Speaker 1: dollars is an amount that a come any like Amazon

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Speaker 1: is really going to feel. To me this I mean,

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Speaker 1: I am happy that they're having to have some kind

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Speaker 1: of a show of accountability to how they have wronged

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Speaker 1: the public, But I don't think this is amount of

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Speaker 1: money that they are going to feel. And just the

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Speaker 1: fact that before twenty seventeen anybody a ring employee and

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Speaker 1: their vast network of contractors could just look at anybody

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Speaker 1: from their ring cameras they wanted. Is just the scale

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Speaker 1: of harm is so much bigger than the amount that

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Speaker 1: they have to pay in punishment that I cannot imagine

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Speaker 1: this is going to be something that gives them pause

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Speaker 1: in terms of how they're harming people in the future.

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Speaker 1: And you know you, I didn't even know about the

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Speaker 1: fact that Tesla was using people's cameras to like share

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Speaker 1: jokes with each other. Think about the grossest, longest car

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Speaker 1: trip that you've ever taken, where there's just Wendy's bags

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Speaker 1: and used Kleenex on the ground and you're driving barefoot

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Speaker 1: and you're disgusting. Imagine that video being used in Greg's

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Speaker 1: slack channel just to have a laugh.

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Speaker 2: Yeah, thanks a lot, Greg.

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Speaker 1: We're really we're really beating up on the Gregs here.

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Speaker 1: Let's let's let's switch gears. Let's beat up on the

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Speaker 1: Ron's for a minute. Because Ron DeSantis's campaign just recently

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Speaker 1: used AI generated images of Trump hugging and kissing Fauci

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Speaker 1: in their campaign material. So we've said many times on

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Speaker 1: the show about the spread of deep fakes, and on

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Speaker 1: the Internet, and as AI image generation software gets better

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Speaker 1: and more available, it is so easy for bad actors

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Speaker 1: to create fake images of celebrities and politicians. And I

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Speaker 1: think especially when those images are weaponized in political campaigns

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Speaker 1: during climates that are like politically fraught or sensitive or inflammatory.

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Speaker 1: It's concerning because these fake images can often appear real.

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Speaker 1: I am not too proud to admit that I got

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Speaker 1: I got got by that image of the Pope in

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Speaker 1: the Balenciaga puffer. It was early morning, I had had

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Speaker 1: my coffee. I was just scrolling Twitter on my iPad.

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Speaker 1: I just saw it and I thought, Okay, the Pope's

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Speaker 1: wearing a Balenciaga puffer. Checks out. It didn't. I didn't

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Speaker 1: have My brain was not primed. Even though I'm somebody

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Speaker 1: who studies disinformation and like talks about it for a living,

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Speaker 1: my brain was not yet primed to have that seer

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Speaker 1: of skepticism. So these fake images can get the best

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Speaker 1: of us. Right, you shouldn't have to necessarily be so

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Speaker 1: primed and poised and ready to tell the zoom in

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Speaker 1: on the fingers and be like, oh, that's fake, to

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Speaker 1: tell if an image is real or not. So that

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Speaker 1: I definitely am. I've gotten got before.

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Speaker 2: Yeah, it's a good point you make that we shouldn't

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Speaker 2: have to be constantly hyper vigilant. You know, if you

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Speaker 2: if I think about the times that I'm looking at

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Speaker 2: social media, it's when I'm waiting for the metro or

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Speaker 2: bored or you know, waiting on this or that, or

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Speaker 2: I don't know, I'm not like sitting down to critically

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Speaker 2: engage in like deep and critical thought about what I'm

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Speaker 2: looking at right, Like, I just want to see some cats.

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Speaker 2: I want to see some jokes. I want to see

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Speaker 2: some stupid stuff that makes me laugh. And yeah, you

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Speaker 2: see the pope in a puffer jacket. I don't know,

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Speaker 2: I probably would have got got too.

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Speaker 1: So this week, Ronda Santis's campaign joined in on the

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Speaker 1: AI generated deep fake fun and shared a set of

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Speaker 1: fake images of Donald Trump hugging and kissing Anthony Fauci.

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Speaker 1: They were kind of clever about it, mixing in the

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Speaker 1: fake images with some real ones, but they weren't that

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Speaker 1: clever about it because with a little scrutiny, the images

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Speaker 1: appear to be obviously fake, Like in one of them,

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Speaker 1: Trump's arm kind of wraps all the way around Fauci's

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Speaker 1: body in a very unnatural way, like a long snake,

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Speaker 1: like he's like got double the arm around him kind

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Speaker 1: of in another one the letters in the phrase white

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Speaker 1: house or garble, so you kind of know it's AI

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Speaker 1: or that something is going on there. Other details are

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Speaker 1: also off, like the stars in the American flag, or

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Speaker 1: unnatural details in Trump's hair, which somehow kind of manages

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Speaker 1: to look more unnatural than his actual, honest to god

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Speaker 1: human hair. I don't know how that's possible. So the

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Speaker 1: French media entity AFP first reported on the fake photos,

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Speaker 1: which were included in a video released by the official

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Speaker 1: Dasantis campaign.

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Speaker 2: You know, I really thought, in hope that we had

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Speaker 2: more time before US presidential candidates were using deep fakes

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Speaker 2: as part of their official campaigns. I don't know why

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Speaker 2: I thought that. I guess maybe just wishful thinking. But

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Speaker 2: you know, politicians like DeSantis and also Trump, like it

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Speaker 2: happens to be that like DeSantis did this against Trump,

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Speaker 2: but I could just as easily see it going the

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Speaker 2: other way. They have no qualms about speaking lies and

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Speaker 2: spreading lies, so why wouldn't they take advantage of AI

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Speaker 2: images to spread visual lies?

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Speaker 1: And I think there's really something about visual lies that

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Speaker 1: works on a different level than when you read something

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Speaker 1: that's not true. The same way that I was just like,

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Speaker 1: didn't have my class, hadn't had my coffee, scrolling ands

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Speaker 1: all picture of the Pope and said, oh that's fine.

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Speaker 1: Visual images can hit us so much differently. They can

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Speaker 1: hit us quickly, more quickly than the written word, and

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Speaker 1: they can sort of stoke a more emotionally resonant space

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Speaker 1: in us. I think, like in the interview that we

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Speaker 1: did with the Foma Uzoma who was formally at pinterest,

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Speaker 1: who was kind of in charge of getting medical misinformation

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Speaker 1: and other you know, bad stuff, I'll have Pinterest, she

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Speaker 1: said that one of the reasons why it was so

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Speaker 1: prevalent on Pinterest is because it's a visual, a visual platform,

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Speaker 1: and so there would be these highly visually visceral images,

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Speaker 1: like when it came to abortion disinformation, it was these

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Speaker 1: like very visually charged images and they of course would

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Speaker 1: stoke an emotional response on people very quickly. So definitely

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Speaker 1: the threat of image based AI manipulated deep fake images

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Speaker 1: is a real concern.

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Speaker 2: Yeah, that's I think you really hit on something there

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Speaker 2: that the like she said, the images evoke this visual

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Speaker 2: emotion reaction. And also it's just new I think in

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Speaker 2: certainly in my lifetime, and I think possibly all of

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Speaker 2: human experience that we have to be so questioning of

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Speaker 2: what we visually see in front of us.

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Speaker 1: Right.

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Speaker 2: We have all these phrases like he said, she said,

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Speaker 2: you can't believe everything you read, and so we're used

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Speaker 2: to having to like sort through what's true and what

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Speaker 2: isn't in these like verbal domains. But we also have

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Speaker 2: the phrase like you don't believe what's in front of

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Speaker 2: your own eyes, right, which is usually a pejorative thing

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Speaker 2: because typically in human experience, we can believe what we

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Speaker 2: see for ourselves. When we directly see something, it's generally

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Speaker 2: assumed to be true. But even that is no longer true.

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Speaker 2: And so, you know, of all the scary stuff that

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Speaker 2: you've talked about on this show with our guests, I

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Speaker 2: feel like deep fakes are one of the scariest because

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Speaker 2: if people aren't able to tell what's real and what isn't,

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Speaker 2: it does not bode well for solving the big problems

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Speaker 2: that are coming our way. Right Like outside the windows

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Speaker 2: right now, the city is blanketed in smoke from the

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Speaker 2: worst wildfires on the East Coast that I can remember

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Speaker 2: in my lifetime, made worse by climate change. We're gonna

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Speaker 2: have like serious problems that a society we need to

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Speaker 2: come together to solve. And Yeah, if we can't have

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Speaker 2: a shared understanding of what is real and what isn't,

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Speaker 2: that's gonna be hard.

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Speaker 3: Let's take a quick break at our back.

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Speaker 1: Let's talk about YouTube. YouTube, which is owned by Google,

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Speaker 1: will no longer remove videos falsely claiming that the twenty

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Speaker 1: twenty presidential in the United States was stolen, reversing a

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Speaker 1: policy put in place after the twenty twenty vote. In

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Speaker 1: a blog post, the company says, quote, it will stop

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Speaker 1: removing content that advances false claims that widespread fraud, errors,

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Speaker 1: or a glitches accord in twenty twenty in other past

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Speaker 1: US presidential elections because things have changed. Well what's changed?

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Speaker 1: Why are they doing this? According to YouTube, because free speech,

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Speaker 1: they said, in the current environment, we find that while

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Speaker 1: removing this content does curb some misinformation, it could also

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Speaker 1: have the unintended effect of curtailing political speech without meaningfully

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Speaker 1: reducing the risk of violence and other real world to harm.

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Speaker 2: I just want to jump in there real quick to

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Speaker 2: break down that quote that you just read, because it's

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Speaker 2: so telling. They say, we find that while removing this

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Speaker 2: content does curb some misinformation, it could have the unintended

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Speaker 2: effect of curtailing political speech. Right. So they're on the

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Speaker 2: one hand, they're acknowledging that it does curb misinformation, it

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Speaker 2: is actively today preventing harm from being done, and yet

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Speaker 2: they are going to remove those protections out of potential

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Speaker 2: maybe fear about something that could potentially occur in the future.

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Speaker 2: And it's so backwards and silly and infuriating.

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Speaker 1: Yeah, it's like the Gettysburg Address of cow towing tech

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Speaker 1: pr bullshit speak where they say, we are we acknowledge

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Speaker 1: that what we are doing will has prevented harm, but

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Speaker 1: what if it could increase for speech? Question mark, let's

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Speaker 1: find out, right. And I gotta say, like, I feel

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Speaker 1: a little bit personally invested in this because getting Google

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Speaker 1: to agree to take down this kind of misinformation is

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Speaker 1: something that I personally worked on in my platform accountability work.

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Speaker 1: This has definitely been I've tried, I mean, I've tried

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Speaker 1: not to dwell on it too much because what does

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Speaker 1: that get you? But this has definitely been the year

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Speaker 1: of a lot of policies that did verifiable, verifyable good

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Speaker 1: and verifiably made platforms safer in like clear ways. This

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Speaker 1: has been the year of seeing those policies be walked back,

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Speaker 1: be changed. So it's a little personally distressing to me,

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Speaker 1: but that's either here nor there. They do say that

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Speaker 1: they will continue to take down content that misleads voters

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Speaker 1: about when, where, and how to vote, and claims that

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Speaker 1: discourage voting, and content that encourages others to interfere with

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Speaker 1: the democratic process. But knowing a little bit about this,

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Speaker 1: like that's just not how it works, right. Donald Trump

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Speaker 1: didn't go on television and say I think people should

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Speaker 1: go to polls and harass pole workers. I don't think

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Speaker 1: he explicitly said that, but that was how that message

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Speaker 1: was interpreted and filtered down right, And so this is

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Speaker 1: really flies in the face with like what we know

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Speaker 1: about how election disinformation and misinformation works. People don't go

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Speaker 1: on TV and say do x y z in an

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Speaker 1: explicit way. It's very roundabout. It's very the implication. And

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Speaker 1: so saying like, oh, well, can we definitely understand that

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Speaker 1: misleading people about how to vote, content that encourages people

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Speaker 1: to interfere with the democratic process. Saying that that is

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Speaker 1: content that you will take down because you recognize that

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Speaker 1: as harmful and dangerous. It kind of it doesn't make

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Speaker 1: sense that you would think that that is dangerous. But

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Speaker 1: that is not how it really works, Right, Like, bad

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Speaker 1: actors are really good at staying just on the right

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Speaker 1: side of not needing to be have their content remove.

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Speaker 1: That is like something that they are very good at.

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Speaker 1: It is their bread and butter. And so saying that

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Speaker 1: someone will have to meet this very specific threshold to

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Speaker 1: have their content removed by YouTube is just inviting people

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Speaker 1: to make content that stays just a hair on that

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Speaker 1: side of plausible deniability that essentially encourages just that you.

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Speaker 2: Know, yeah, that's right, and it's a moving, shifting target,

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Speaker 2: and to really meaningfully address it or moderate that content,

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Speaker 2: to remove that sort of content that is sneakily just

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Speaker 2: on the just the hair shy of being over the line.

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Speaker 2: You know, it's a tough problem, and I can understand

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Speaker 2: why platforms like Google really just want to punt on it,

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Speaker 2: but it's also super important for our democracy and the

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Speaker 2: cohesion of society.

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Speaker 1: And also, let's just talk about this bs oh, it

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Speaker 1: could threaten free speech literally. This morning, I saw a

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Speaker 1: post from Trump on truth Social that said that the

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Speaker 1: twenty twenty election was stolen. It's not as if there

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Speaker 1: are no places in society or on the Internet that

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Speaker 1: one could say those lies if they wanted to. Trump

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Speaker 1: does it literally every day and has been for the

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Speaker 1: last few years, right, And so what I am saying

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Speaker 1: is that there is no reason for a company like

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Speaker 1: YouTube to allow that on their platform. Not being able

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Speaker 1: to say it on YouTube doesn't mean that people aren't

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Speaker 1: able to say it. People say it all the time, right.

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Speaker 1: It's just like it's such an abdication of responsibility and leadership.

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Speaker 1: And I should say that this is actually one of

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Speaker 1: the last planks of like post insurrection digital infrastructure that

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Speaker 1: was put in place after the violent insurrection. YouTube was

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Speaker 1: actually the last one of the last platforms to have

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Speaker 1: a policy against twenty twenty election denial. Twitter started adding

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Speaker 1: false labeling of false claims about the twenty twenty election

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Speaker 1: early last year, but then they walked it back, saying

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Speaker 1: that it had been more than a year since you know,

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Speaker 1: Biden took office and there was an eventually an exchange

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Speaker 1: of power. Facebook also walked back their labeling of false

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Speaker 1: claims to.

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Speaker 2: The decisions of these platforms about what sort of content

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Speaker 2: they're going to allow and what sort of lying, disingenuous,

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Speaker 2: dangerous content they might prohibit. That's not a free speech issue,

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Speaker 2: right like that is what these That is a business

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Speaker 2: decision by these companies of how they they want to

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Speaker 2: operate and what role they want to play in a

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Speaker 2: pluralistic society.

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Speaker 1: And I think it really shows it's just like another

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Speaker 1: plank and how these platforms are I guess I'll use

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Speaker 1: the word preparing, but really it's the opposite of preparing

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Speaker 1: for the upcoming election. Like YouTube restored Trump's account back

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Speaker 1: in March so that users could quote hear equally from

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Speaker 1: major national candidates. You know. I think it really shows

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Speaker 1: that platforms and also media outlets like CNN, who platform

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Speaker 1: Trump to just like lie and smear and slander people

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Speaker 1: for an hour. I think that these platforms have really

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Speaker 1: learned nothing from the last few years. You know, verifiable

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Speaker 1: lies about our democratic process and our elections. It's not discourse.

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Speaker 1: It's not a difference of opinion. It's not an issue

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Speaker 1: that you need to show both sides to or give

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Speaker 1: credence to. It is a lie. It is a verifiable lie.

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Speaker 1: By now, platforms should have a game plan about how

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Speaker 1: they're going to deal with verifiable lies about our democratic

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Speaker 1: process in a way that is ethical and responsible, or

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Speaker 1: at least more ethical and more responsible than just like

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Speaker 1: let anybody lie, because that's what free speech is.

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Speaker 2: Yeah, I mean, they just want that sweet, sweet engagement.

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Speaker 2: They know that trumpy outrage drives clicks and eyeballs, and

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Speaker 2: they want a piece of the action. You know, Google's

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Speaker 2: business is selling ads, and integrity and responsibility really have

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Speaker 2: nothing to do with it. And it's tragic and dangerous

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Speaker 2: because YouTube is so powerful and it has such a

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Speaker 2: large impact on our discourse, on our democracy that they

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Speaker 2: should feel a sense of responsibility for the content that

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Speaker 2: they amplify and promote. But they've just demonstrated time and

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Speaker 2: again that they don't, and that they're going to choose

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Speaker 2: outraged engagement and selling ads every time. Platforms. Huh.

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Speaker 1: Yeah, Let's talk about another platform that is generating a

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Speaker 1: bit of outrage, and that is Reddit. So popular platform

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Speaker 1: Reddit announce some changes this week and users are not happy,

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Speaker 1: to say the least. So if you don't know what

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Speaker 1: Reddit is, I love Reddit. It's kind of known as

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Speaker 1: the front page of the Internet, to a point where, like,

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Speaker 1: if you need to answer a question or you need

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Speaker 1: some like real, like human vetted reliable information, it is

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Speaker 1: a common practice to search whatever you need plus Reddit

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Speaker 1: to quickly get to an actual answer. I want to

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Speaker 1: heart somebody say that, like, if they were in a fire,

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Speaker 1: the last thing googled on their phone would be like

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Speaker 1: how to fight fires plus Reddit, Like I died trying

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Speaker 1: to get the answer from Reddit.

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Speaker 2: So and Bridget, didn't you used to be like a

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Speaker 2: power moderator on Reddit, like years ago, I was a.

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Speaker 1: Former Reddit moderator. I was. I mean, it was a

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Speaker 1: site that I spent a lot of my free labor

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Speaker 1: moderating and caring about and thinking about. So if folks

434
00:24:49,720 --> 00:24:51,840
Speaker 1: use Reddit, and they probably already know that, when you

435
00:24:51,960 --> 00:24:55,359
Speaker 1: log onto Reddit from a computer, generally like it's fine,

436
00:24:55,400 --> 00:24:57,520
Speaker 1: the user experience is fine. But if you log on

437
00:24:57,600 --> 00:25:01,280
Speaker 1: on your phone the app, the Reddit app is very janky,

438
00:25:01,400 --> 00:25:03,439
Speaker 1: and it's also full of ads, to the point that

439
00:25:03,720 --> 00:25:06,480
Speaker 1: I would say that it's like, I won't say unusable,

440
00:25:06,680 --> 00:25:10,320
Speaker 1: but it's not a pleasant user experience. It's like almost unusable.

441
00:25:10,359 --> 00:25:13,119
Speaker 1: The amount of ads that pop up when you're trying

442
00:25:13,119 --> 00:25:14,920
Speaker 1: to use it. So to get around that, a lot

443
00:25:14,960 --> 00:25:17,520
Speaker 1: of folks who use Reddit on a mobile use third

444
00:25:17,520 --> 00:25:20,880
Speaker 1: party apps like Apollo, and these apps only work because

445
00:25:20,880 --> 00:25:23,679
Speaker 1: Reddit allowed those third party apps to have access to

446
00:25:23,720 --> 00:25:26,680
Speaker 1: their API, basically have access to their back ends. And

447
00:25:26,840 --> 00:25:29,520
Speaker 1: all of that is changing because now Reddit announce that

448
00:25:29,520 --> 00:25:32,520
Speaker 1: they're going to start charging those third party apps a

449
00:25:32,760 --> 00:25:36,160
Speaker 1: pretty high price for the access that they've always had.

450
00:25:36,359 --> 00:25:39,000
Speaker 1: You might remember that Twitter did something pretty recently too,

451
00:25:39,320 --> 00:25:42,640
Speaker 1: so pretty much every third party app that relies on

452
00:25:42,760 --> 00:25:45,560
Speaker 1: Twitter's API has announced that they will not be able

453
00:25:45,560 --> 00:25:49,200
Speaker 1: to operate if Reddit continues with this plan to charge

454
00:25:49,240 --> 00:25:52,280
Speaker 1: them the amount that they're asking to be charged to

455
00:25:52,359 --> 00:25:54,000
Speaker 1: continue to have access to the back end.

456
00:25:55,000 --> 00:25:59,840
Speaker 2: Wow, this is like such a surprising trend for platforms

457
00:26:00,080 --> 00:26:03,240
Speaker 2: to make because I think I was reading like a

458
00:26:03,320 --> 00:26:09,239
Speaker 2: Tom Friedman book a while ago. Tom Friedman, Yeah, it

459
00:26:09,280 --> 00:26:12,560
Speaker 2: was a I don't remember why. I think it was

460
00:26:12,560 --> 00:26:14,360
Speaker 2: like in an airport and it felt like the right

461
00:26:14,400 --> 00:26:17,400
Speaker 2: thing to do or something. But he was talking about

462
00:26:17,440 --> 00:26:20,920
Speaker 2: like after the nineties and the dot com boom, how

463
00:26:20,960 --> 00:26:24,840
Speaker 2: like APIs were the big thing that enabled the Internet

464
00:26:24,920 --> 00:26:27,040
Speaker 2: to like take off and flourish because you had all

465
00:26:27,040 --> 00:26:30,800
Speaker 2: this interoperability, and I think it was right about that.

466
00:26:31,040 --> 00:26:34,920
Speaker 2: It was wrong about a lot of other stuff. But

467
00:26:34,920 --> 00:26:40,199
Speaker 2: but yeah, like APIs were a great invention, right and

468
00:26:40,480 --> 00:26:45,359
Speaker 2: allowed platform arguably. You know, these all the third party

469
00:26:45,560 --> 00:26:51,479
Speaker 2: apps that allow people to interact with Reddit in ways

470
00:26:51,520 --> 00:26:57,800
Speaker 2: that are better than Reddit's native app makes available, help

471
00:26:57,880 --> 00:27:01,400
Speaker 2: people use it, help grow their user base, and it's

472
00:27:01,480 --> 00:27:07,000
Speaker 2: so surprising to see platforms like Reddit and Twitter clamping

473
00:27:07,119 --> 00:27:11,880
Speaker 2: down on the very thing that helped them grow.

474
00:27:12,640 --> 00:27:15,960
Speaker 1: Well. So, one of my favorite third party apps for

475
00:27:16,000 --> 00:27:19,800
Speaker 1: Twitter block Party, which is a great tool to mass

476
00:27:19,800 --> 00:27:24,240
Speaker 1: block people who are like harassers or bad actors on Twitter.

477
00:27:24,640 --> 00:27:27,600
Speaker 1: They announce that they're taking an indefinite hiatus because of

478
00:27:27,640 --> 00:27:30,680
Speaker 1: this change where they're now charging for Twitter access to

479
00:27:30,720 --> 00:27:34,040
Speaker 1: Twitter's API. Now, Reddit did walk this back a little bit,

480
00:27:34,119 --> 00:27:36,120
Speaker 1: kind of along the lines of exactly what you were saying,

481
00:27:36,440 --> 00:27:39,760
Speaker 1: saying that these new API terms would carve out an

482
00:27:39,760 --> 00:27:43,240
Speaker 1: exception for accessibility apps which allow users who are blind

483
00:27:43,359 --> 00:27:46,280
Speaker 1: or visually impaired to browse Reddit, because I guess Reddit

484
00:27:46,600 --> 00:27:48,439
Speaker 1: does not have a way for people who are visually

485
00:27:48,440 --> 00:27:50,560
Speaker 1: impaired to browse it. So exactly what you were saying

486
00:27:50,560 --> 00:27:55,639
Speaker 1: that these third party apps via API access are able

487
00:27:55,680 --> 00:27:59,439
Speaker 1: to create a more inclusive experience to to include more users,

488
00:27:59,480 --> 00:28:02,040
Speaker 1: which Reddit have not done. So really, like, I'm the

489
00:28:02,080 --> 00:28:03,760
Speaker 1: expert on this, but in my book, it's like Reddit

490
00:28:03,760 --> 00:28:06,440
Speaker 1: should really be paying the people who It's like, oh, well,

491
00:28:06,480 --> 00:28:11,000
Speaker 1: you just completely shut out blind users. Luckily we have

492
00:28:11,119 --> 00:28:13,480
Speaker 1: found a workaround to include them.

493
00:28:13,880 --> 00:28:17,680
Speaker 2: You're welcome. Yeah, And that's a that is an interesting

494
00:28:17,720 --> 00:28:22,360
Speaker 2: note here, right like, Reddit is pretty different than Twitter

495
00:28:22,560 --> 00:28:26,200
Speaker 2: in a lot of ways. Right Like, Reddit, to my understanding,

496
00:28:26,280 --> 00:28:31,240
Speaker 2: really survives and thrives on the active participation of its

497
00:28:31,400 --> 00:28:34,560
Speaker 2: users U and I would imagine that some of them,

498
00:28:34,880 --> 00:28:39,480
Speaker 2: particularly like you just mentioned, those who are blind who

499
00:28:39,520 --> 00:28:42,960
Speaker 2: rely on these third party apps to use it, I

500
00:28:42,960 --> 00:28:47,840
Speaker 2: would imagine some of those users might not love this change.

501
00:28:48,200 --> 00:28:50,720
Speaker 1: While they certainly do not, and in fact, the Reddit

502
00:28:50,760 --> 00:28:53,360
Speaker 1: community is very vocal and they do not take stuff

503
00:28:53,400 --> 00:28:56,280
Speaker 1: like this without a fight, so they are organizing to

504
00:28:56,280 --> 00:28:59,959
Speaker 1: fight back. The platform relies on an army of unpaid moderators.

505
00:29:00,080 --> 00:29:02,000
Speaker 1: I used to be one of them, and honestly, like

506
00:29:02,240 --> 00:29:06,880
Speaker 1: Reddit would not function without these moderators giving a lot

507
00:29:06,920 --> 00:29:10,320
Speaker 1: of their free time and labor to keep Reddit subreddits,

508
00:29:10,360 --> 00:29:13,240
Speaker 1: which are like they're like, you know, the different communities

509
00:29:13,240 --> 00:29:16,440
Speaker 1: on Reddit going. They all signed an open letter to

510
00:29:16,440 --> 00:29:20,720
Speaker 1: Reddit saying that oftentimes third party tools offer better moderation

511
00:29:20,840 --> 00:29:23,240
Speaker 1: tools than the ones that Reddit does. They say, many

512
00:29:23,320 --> 00:29:25,640
Speaker 1: of us rely on third party apps to manage our

513
00:29:25,640 --> 00:29:28,640
Speaker 1: communities effectively. The potential loss of these services due to

514
00:29:28,640 --> 00:29:32,560
Speaker 1: the pricing change would significantly impact our ability to moderate efficiently,

515
00:29:32,640 --> 00:29:36,520
Speaker 1: thus negatively affecting the experience for users in our communities

516
00:29:36,560 --> 00:29:39,920
Speaker 1: and for us as mods and users ourselves. It honestly

517
00:29:39,960 --> 00:29:42,440
Speaker 1: sounds like these moderators are just generally fed up with

518
00:29:42,520 --> 00:29:45,000
Speaker 1: what they feel as a lack of communication and transparency

519
00:29:45,200 --> 00:29:48,680
Speaker 1: from Redder higher ups to Reddit moderators, who, again basically

520
00:29:49,240 --> 00:29:51,920
Speaker 1: their unpaid labor is the reason why this site is

521
00:29:51,960 --> 00:29:55,080
Speaker 1: able to function. On June twelfth, much of the site's

522
00:29:55,120 --> 00:29:58,240
Speaker 1: subreddits are planning a blackout, which means that individual subreddits

523
00:29:58,280 --> 00:30:00,600
Speaker 1: will lock into private mode, meaning that and anybody who

524
00:30:00,680 --> 00:30:02,960
Speaker 1: is not already a follower of these subredits will not

525
00:30:03,000 --> 00:30:05,040
Speaker 1: be able to access them during that time or see

526
00:30:05,040 --> 00:30:08,240
Speaker 1: that content. So, if you don't use Reddit and you're thinking,

527
00:30:08,640 --> 00:30:11,560
Speaker 1: who cares, what's the big deal, We're talking about millions

528
00:30:11,600 --> 00:30:13,960
Speaker 1: of people, right Some of these big subreddits that are

529
00:30:13,960 --> 00:30:16,920
Speaker 1: going dark in protests have upwards of like three or

530
00:30:16,960 --> 00:30:19,840
Speaker 1: four million people on them, and I think it does

531
00:30:19,960 --> 00:30:21,800
Speaker 1: kind of come back to what you were saying, Mike

532
00:30:21,840 --> 00:30:24,880
Speaker 1: about how I mean. I don't want to give Thomas

533
00:30:24,880 --> 00:30:27,520
Speaker 1: Freeman too much credit, but this idea of APIs and

534
00:30:27,640 --> 00:30:30,640
Speaker 1: opening things up and having it be a more inclusive experience.

535
00:30:31,120 --> 00:30:33,800
Speaker 1: I really see this reddit thing and the reason that

536
00:30:33,840 --> 00:30:36,200
Speaker 1: I wanted to talk about it here, I really say

537
00:30:36,240 --> 00:30:38,600
Speaker 1: it as a part of a larger fight about the

538
00:30:38,640 --> 00:30:41,280
Speaker 1: Internet and who the Internet is for and what it

539
00:30:41,320 --> 00:30:43,960
Speaker 1: is for. Right There is this great piece in Wired

540
00:30:44,000 --> 00:30:47,920
Speaker 1: about the inthitification of the Internet which kind of posits

541
00:30:47,960 --> 00:30:50,920
Speaker 1: that this is how platforms die. First they are good

542
00:30:50,920 --> 00:30:53,719
Speaker 1: to their users, then they abuse their users to make

543
00:30:53,760 --> 00:30:57,480
Speaker 1: things better for their business customers. Finally they abuse those

544
00:30:57,520 --> 00:31:00,520
Speaker 1: business customers to claw back all the value for them themselves,

545
00:31:00,680 --> 00:31:05,040
Speaker 1: and then they die. I totally agree with this, and

546
00:31:05,200 --> 00:31:08,760
Speaker 1: I feel it everywhere, like Ie, not even just on

547
00:31:08,800 --> 00:31:12,840
Speaker 1: social media platforms, just everywhere. I feel like everything online

548
00:31:13,200 --> 00:31:18,400
Speaker 1: eventually has to whatever little joy or life or love

549
00:31:18,800 --> 00:31:22,240
Speaker 1: it has to just bleed it to make a little

550
00:31:22,280 --> 00:31:25,160
Speaker 1: bit more money for people who are already rich. You

551
00:31:25,160 --> 00:31:29,760
Speaker 1: know Instagram. Ten years ago, Instagram felt fun and cool,

552
00:31:29,800 --> 00:31:33,040
Speaker 1: Like I remember when Instagram first was a thing I didn't.

553
00:31:33,240 --> 00:31:35,240
Speaker 1: I wasn't on Instagram because I didn't feel cool enough.

554
00:31:35,240 --> 00:31:36,600
Speaker 1: I was like, oh, there's nothing cool in my life

555
00:31:36,640 --> 00:31:41,280
Speaker 1: to show. Everybody is like putting Sepia filters on their pictures,

556
00:31:41,320 --> 00:31:43,960
Speaker 1: and it was like, it felt cool. It felt like

557
00:31:43,960 --> 00:31:46,600
Speaker 1: a community where you wanted to be, And now it

558
00:31:46,680 --> 00:31:49,440
Speaker 1: just feels like a virtual dead mall. You know, it's

559
00:31:49,480 --> 00:31:53,320
Speaker 1: not enough that HBO, Max or Netflix cancels your favorite

560
00:31:53,360 --> 00:31:56,959
Speaker 1: series only after one season. Now they have to remove

561
00:31:57,080 --> 00:32:00,479
Speaker 1: the entire back catalog so you cannot so it's not canceled,

562
00:32:00,680 --> 00:32:04,480
Speaker 1: you can never watch the existing episodes again, just to

563
00:32:04,520 --> 00:32:06,560
Speaker 1: save a little bit of money on residuals and like

564
00:32:06,640 --> 00:32:09,280
Speaker 1: having to pay the writers and the actors more. You know.

565
00:32:09,600 --> 00:32:13,200
Speaker 1: On this new version of Twitter verification, people with something

566
00:32:13,240 --> 00:32:16,360
Speaker 1: to sell can buy influence via paying eight dollars a

567
00:32:16,360 --> 00:32:18,920
Speaker 1: month for a blue check mark to give them more

568
00:32:18,960 --> 00:32:22,080
Speaker 1: influence to sell whatever it is that they sell more effectively.

569
00:32:22,320 --> 00:32:25,360
Speaker 1: But where is the internet infrastructure that exists to prop

570
00:32:25,480 --> 00:32:30,040
Speaker 1: things up other than building and squeezing capital from people?

571
00:32:30,120 --> 00:32:34,120
Speaker 2: You know, Ooh, that is dark and heavy, but you're

572
00:32:34,160 --> 00:32:40,360
Speaker 2: absolutely right. I do like this phrase and shitification. First

573
00:32:40,480 --> 00:32:45,480
Speaker 2: them bigan, then they shitify. But yeah, it's a good question,

574
00:32:45,520 --> 00:32:50,560
Speaker 2: like where is that internet infrastructure that exists? Yeah, well it's.

575
00:32:50,720 --> 00:32:54,320
Speaker 1: A perfectly cromulent question. Luke Plummet, a tech writer, captured

576
00:32:54,360 --> 00:32:57,680
Speaker 1: this feeling so well on Twitter. He writes, a huge

577
00:32:57,680 --> 00:33:00,520
Speaker 1: part of the bad vibes you feel everywhere these days

578
00:33:00,800 --> 00:33:03,240
Speaker 1: is because every single aspect of our lives is being

579
00:33:03,280 --> 00:33:06,040
Speaker 1: squeezed by companies shaking us down, and we're reaching a

580
00:33:06,080 --> 00:33:10,200
Speaker 1: breaking point. Every platform, every service, every product, every form

581
00:33:10,240 --> 00:33:14,160
Speaker 1: of entertainment just keeps tightening the grip. Each quarterly growth

582
00:33:14,160 --> 00:33:17,120
Speaker 1: report looks good in isolation, but we're reaching the point

583
00:33:17,120 --> 00:33:22,480
Speaker 1: of collective societal exhaustion. And boy, I really felt that,

584
00:33:22,680 --> 00:33:25,240
Speaker 1: I really identified with that. I think I'm there where

585
00:33:25,400 --> 00:33:28,960
Speaker 1: it feels like every little bit of joy is being

586
00:33:29,120 --> 00:33:33,080
Speaker 1: squeezed and mined for whatever little capital can be taken

587
00:33:33,120 --> 00:33:35,520
Speaker 1: from it to make some rich guy who's already rich

588
00:33:35,560 --> 00:33:37,640
Speaker 1: a little bit more rich. And I think I'm really

589
00:33:37,760 --> 00:33:40,680
Speaker 1: yearning for online spaces that felt like they felt when

590
00:33:40,680 --> 00:33:42,200
Speaker 1: I was a bit younger, you know, that felt like

591
00:33:42,280 --> 00:33:45,560
Speaker 1: connection and community building and joy and it feels like

592
00:33:45,600 --> 00:33:48,680
Speaker 1: we are seating more and more of the Internet solely

593
00:33:48,680 --> 00:33:50,480
Speaker 1: to people who want to make money, right, whether it's

594
00:33:50,520 --> 00:33:53,960
Speaker 1: capital for wealthy investors or people who want to sell

595
00:33:54,000 --> 00:33:56,000
Speaker 1: you something or outright scams.

596
00:33:56,440 --> 00:33:59,960
Speaker 2: Yeah, we got to bring the weird, joyful internet.

597
00:34:00,880 --> 00:34:03,800
Speaker 1: Yeah, I want to see Like I don't want to

598
00:34:03,880 --> 00:34:08,200
Speaker 1: date myself, but I want to see more weird Internet

599
00:34:08,200 --> 00:34:12,200
Speaker 1: spaces that are just like, here's my weird cartoon website.

600
00:34:12,239 --> 00:34:16,960
Speaker 1: Here's my big spoon or my salad fingers or my

601
00:34:17,120 --> 00:34:21,080
Speaker 1: teen girls squad. All those are real things. Look them up, kids,

602
00:34:21,200 --> 00:34:22,320
Speaker 1: They're very funny.

603
00:34:23,320 --> 00:34:25,920
Speaker 2: Yeah, there was like funny stuff. There is joyful stuff.

604
00:34:26,080 --> 00:34:28,680
Speaker 2: I feel like it's out there too, right, like they're

605
00:34:28,719 --> 00:34:32,920
Speaker 2: instill the infrastructure to create those things. Maybe the problem

606
00:34:32,920 --> 00:34:35,680
Speaker 2: is that we're all spending our time on the big

607
00:34:35,719 --> 00:34:38,960
Speaker 2: platforms because everybody else is there. Maybe we gotta get off.

608
00:34:39,000 --> 00:34:41,239
Speaker 2: I don't know. I'm just like speculating and losing the

609
00:34:41,320 --> 00:34:41,799
Speaker 2: thread here.

610
00:34:42,560 --> 00:34:45,359
Speaker 1: So that's I mean, it's pretty messed up in dark

611
00:34:45,400 --> 00:34:47,000
Speaker 1: and I have to we have to talk about this,

612
00:34:47,200 --> 00:34:50,120
Speaker 1: like speaking of dark, messed up stuff online.

613
00:34:50,600 --> 00:34:51,759
Speaker 2: I want to talk about this.

614
00:34:52,040 --> 00:34:53,719
Speaker 1: I know I don't want to spend too much time

615
00:34:53,760 --> 00:34:56,200
Speaker 1: on it because it like genuinely nauseates me. But we

616
00:34:56,280 --> 00:34:58,360
Speaker 1: have to talk about this new Wall Street Journal report

617
00:34:58,360 --> 00:35:04,240
Speaker 1: about Instagram. A trigger warning here about abuse of children.

618
00:35:04,480 --> 00:35:07,560
Speaker 1: It is horrific. The Wall Street Journal just published an

619
00:35:07,600 --> 00:35:11,640
Speaker 1: expose showing that Instagram has been algorithmically promoting a vast

620
00:35:11,719 --> 00:35:15,480
Speaker 1: trade of child sexual exploitation material. The journal said that

621
00:35:15,520 --> 00:35:19,080
Speaker 1: it conducted an investigation into child sexual exploitation material on

622
00:35:19,160 --> 00:35:22,280
Speaker 1: Instagram in collaboration with researchers at Stanford and the University

623
00:35:22,320 --> 00:35:26,120
Speaker 1: of Massachusetts Amherst. They found that pedophiles have long used

624
00:35:26,160 --> 00:35:29,400
Speaker 1: the Internet, but unlike forums and file transfer services that

625
00:35:29,480 --> 00:35:32,759
Speaker 1: cater to people who have interest and illicit content, Instagram

626
00:35:32,880 --> 00:35:37,399
Speaker 1: does not merely host these activities. Its algorithms promote them.

627
00:35:37,800 --> 00:35:41,120
Speaker 1: Instagram connects pedophiles and guides them to content sellers via

628
00:35:41,200 --> 00:35:45,440
Speaker 1: recommendation systems that excel at linking those who share niche interests.

629
00:35:45,600 --> 00:35:48,240
Speaker 1: Here's how it all works. The researchers found that Instagram

630
00:35:48,320 --> 00:35:51,719
Speaker 1: enabled people to search explicit hashtags and then connected them

631
00:35:51,840 --> 00:35:55,240
Speaker 1: to accounts that use those same terms to advertise child

632
00:35:55,280 --> 00:35:58,440
Speaker 1: sex material for sale. According to the journal, test accounts

633
00:35:58,440 --> 00:36:01,200
Speaker 1: were set up by researchers that viewed a single such account,

634
00:36:01,239 --> 00:36:04,560
Speaker 1: and then we're immediately hit with suggested for you recommendations

635
00:36:04,840 --> 00:36:08,040
Speaker 1: of purported child sex content sellers and buyers, as well

636
00:36:08,040 --> 00:36:11,640
Speaker 1: as accounts that we're linking to off platform content trading sites.

637
00:36:11,880 --> 00:36:15,360
Speaker 1: Following just a handful of these recommendations was enough to

638
00:36:15,480 --> 00:36:20,080
Speaker 1: flood their test account with content that sexualizes children. In

639
00:36:20,080 --> 00:36:24,720
Speaker 1: addition to that, it's horrifying. In addition to that, certain

640
00:36:24,760 --> 00:36:28,839
Speaker 1: Instagram accounts invite buyers to commission specific acts, with men

641
00:36:28,960 --> 00:36:32,160
Speaker 1: us listing prices for videos of children harming themselves or

642
00:36:32,200 --> 00:36:35,759
Speaker 1: imagery of minor children performing sex acts with animals. This

643
00:36:35,800 --> 00:36:38,080
Speaker 1: is all, according to the Wall Street Journals report, citing

644
00:36:38,160 --> 00:36:42,000
Speaker 1: the findings of the Stanford Internet Observatory researchers. At the

645
00:36:42,080 --> 00:36:45,000
Speaker 1: right price children are available for in person meetups. The

646
00:36:45,040 --> 00:36:50,600
Speaker 1: journal reported, h Yeah, it's stomach churning, it's horrifying. It's terrifying.

647
00:36:50,800 --> 00:36:54,120
Speaker 1: But I have to say it is not terribly surprising

648
00:36:54,160 --> 00:36:57,520
Speaker 1: to me, especially right now when we're having so many

649
00:36:57,560 --> 00:37:02,160
Speaker 1: conversations about protecting kids online, and if lawmakers were serious

650
00:37:02,200 --> 00:37:06,279
Speaker 1: about that, they would be regulating Facebook and companies that

651
00:37:06,360 --> 00:37:09,920
Speaker 1: Facebook runs like Instagram, because according to the data, Facebook

652
00:37:10,040 --> 00:37:13,480
Speaker 1: is by far the biggest defender when it comes to

653
00:37:13,640 --> 00:37:16,359
Speaker 1: child sexual abuse content online. This is not just when

654
00:37:16,360 --> 00:37:18,759
Speaker 1: you compare it to other social media platforms, but when

655
00:37:18,760 --> 00:37:21,680
Speaker 1: you compare it to pornography sites as well. According to

656
00:37:21,680 --> 00:37:24,360
Speaker 1: an independent study released by the National Center for missigan

657
00:37:24,440 --> 00:37:29,080
Speaker 1: Exploited Children, mind Geek, which is the parent company of Pornhub, RedTube, Uporn,

658
00:37:29,400 --> 00:37:33,280
Speaker 1: and several other adult tube sites, accounted for thirteen thousand,

659
00:37:33,360 --> 00:37:36,440
Speaker 1: two hundred and twenty nine instances of what they deemed

660
00:37:36,560 --> 00:37:39,960
Speaker 1: child sexual abuse material, while Snapchat had one hundred and

661
00:37:40,000 --> 00:37:44,120
Speaker 1: forty four thousand, ninety five instances. Google had five hundred

662
00:37:44,120 --> 00:37:47,640
Speaker 1: and forty six seven hundred and four instances. Facebook topped

663
00:37:47,800 --> 00:37:53,279
Speaker 1: everybody with twenty point three million instances of this child

664
00:37:53,440 --> 00:37:57,880
Speaker 1: exploitation material. So if we're actually serious about protecting kids online,

665
00:37:58,239 --> 00:38:00,840
Speaker 1: it needs to start with looking at the biggest defender,

666
00:38:01,080 --> 00:38:03,799
Speaker 1: looking at the worst bad actor, and that is undoubtedly,

667
00:38:03,920 --> 00:38:06,839
Speaker 1: by a by have a vast majority Facebook.

668
00:38:07,600 --> 00:38:10,879
Speaker 2: Jesus, I thought we started out dark, but this is

669
00:38:11,040 --> 00:38:17,200
Speaker 2: like next level stuff and like it's I got to

670
00:38:17,320 --> 00:38:22,000
Speaker 2: hand it to Facebook. You know, we've talked about Amazon

671
00:38:22,480 --> 00:38:26,640
Speaker 2: in this episode. We've talked about Google doing bad stuff,

672
00:38:27,160 --> 00:38:32,360
Speaker 2: but once again, Facebook just blows away the competition at

673
00:38:32,400 --> 00:38:41,120
Speaker 2: being unbelievably bad. Actor. Oh, this is disgusting, and I

674
00:38:41,120 --> 00:38:44,160
Speaker 2: mean in printing in the this, this was in the

675
00:38:44,160 --> 00:38:48,479
Speaker 2: Wall Street Journal, so like, hopefully something will come from this.

676
00:38:49,360 --> 00:38:51,680
Speaker 1: Well, the Wall Street Journal is also where Francis Hogan

677
00:38:51,760 --> 00:38:57,320
Speaker 1: published her information about harms that Facebook knowingly did against children.

678
00:38:57,400 --> 00:38:59,960
Speaker 1: So I don't know, I don't know, they're goals with no,

679
00:39:00,440 --> 00:39:01,440
Speaker 1: I don't know what to tell you.

680
00:39:01,760 --> 00:39:06,200
Speaker 2: I let's move on it like a well traveled Wall

681
00:39:06,239 --> 00:39:08,799
Speaker 2: Street Journal to nothing pipeline, got it?

682
00:39:09,120 --> 00:39:12,160
Speaker 1: Uh? Yeah, I mean I wouldn't say nothing. After Francis

683
00:39:12,200 --> 00:39:15,680
Speaker 1: Hogan published that information in the Wall Street Journal, Facebook

684
00:39:15,680 --> 00:39:18,080
Speaker 1: did change their name to Meta So we got that

685
00:39:18,120 --> 00:39:19,040
Speaker 1: out of it, all.

686
00:39:19,000 --> 00:39:21,600
Speaker 2: Right, that's true. Yeah, still working on the legs.

687
00:39:22,120 --> 00:39:27,120
Speaker 1: Yeah, they're not doing there. They're not doing the metaverse anymore.

688
00:39:27,200 --> 00:39:29,360
Speaker 1: You're never gonna get those legs. Might keep dreaming.

689
00:39:30,280 --> 00:39:33,040
Speaker 2: Okay, thank god, Okay, back to jokes please.

690
00:39:33,800 --> 00:39:36,040
Speaker 1: Okay, So let's let's move on. I know I can't.

691
00:39:36,080 --> 00:39:37,920
Speaker 2: I we have to move on.

692
00:39:38,040 --> 00:39:40,040
Speaker 1: I can't. I can't even sum make it. So let's

693
00:39:40,080 --> 00:39:42,680
Speaker 1: move back to Twitter. So last month, Elon must announced

694
00:39:42,680 --> 00:39:44,680
Speaker 1: that he was stepping down as a CEO of Twitter

695
00:39:44,719 --> 00:39:48,480
Speaker 1: and named a former NBC Universal executive, Linda Yakarino, as

696
00:39:48,520 --> 00:39:51,480
Speaker 1: the new CEO. Musk initially said that she would take

697
00:39:51,480 --> 00:39:54,320
Speaker 1: over in about six weeks, but on Monday, after about

698
00:39:54,360 --> 00:39:56,960
Speaker 1: three weeks, she tweeted that she had officially started, saying

699
00:39:57,160 --> 00:39:59,880
Speaker 1: it happened first day in the books. So who is

700
00:40:00,040 --> 00:40:03,560
Speaker 1: Linda Yakarino. Well, she spent twelve years at NBC Universal,

701
00:40:03,600 --> 00:40:06,600
Speaker 1: where she was most recently the chairperson of Global Advertising

702
00:40:06,640 --> 00:40:09,440
Speaker 1: and Partnerships. She was a big part of launching NBC's

703
00:40:09,440 --> 00:40:12,480
Speaker 1: streaming service Peacock in twenty twenty, which I gotta say

704
00:40:12,520 --> 00:40:14,800
Speaker 1: shout out to Peacock because I watch a lot of Peacock.

705
00:40:15,239 --> 00:40:18,960
Speaker 1: She seems pretty buddy buddy with Elon Musk. At a conference,

706
00:40:19,000 --> 00:40:21,319
Speaker 1: she interviewed him and said, many of you in this

707
00:40:21,440 --> 00:40:23,600
Speaker 1: room know me and know that I pride myself on

708
00:40:23,640 --> 00:40:26,720
Speaker 1: my work ethic, But buddy, I have met my match.

709
00:40:26,880 --> 00:40:29,359
Speaker 1: She said that to Elon Musk when everybody was kind

710
00:40:29,360 --> 00:40:31,560
Speaker 1: of criticizing Elon Musk in the early days of him

711
00:40:31,560 --> 00:40:34,359
Speaker 1: at the helm of Twitter. She urged people to give

712
00:40:34,400 --> 00:40:36,360
Speaker 1: him a minute, let's see what he's gonna do. She

713
00:40:36,480 --> 00:40:39,520
Speaker 1: has some ties to Trump. In twenty eighteen, Yakarino was

714
00:40:39,600 --> 00:40:42,080
Speaker 1: named by Trump to the President's counsel on Sports and

715
00:40:42,120 --> 00:40:46,200
Speaker 1: Fitness and Nutrition. The queer focused news outlet them reported

716
00:40:46,280 --> 00:40:49,760
Speaker 1: that she follows some troubling accounts on Twitter, like libs

717
00:40:49,760 --> 00:40:53,040
Speaker 1: of TikTok, which we know is known for attacking LGBTQ

718
00:40:53,200 --> 00:40:56,720
Speaker 1: people and their allies for just like minding their business.

719
00:40:57,000 --> 00:41:00,560
Speaker 1: Deb notes that she also follows some like stand one

720
00:41:00,560 --> 00:41:04,200
Speaker 1: of the mill Twitter accounts, like mainstream journalists. I actually

721
00:41:04,200 --> 00:41:06,480
Speaker 1: could kind of see her being the kind of person

722
00:41:06,680 --> 00:41:10,239
Speaker 1: who thinks that if you follow mainstream journalists, that means

723
00:41:10,239 --> 00:41:12,719
Speaker 1: that you also have to follow accounts like libs of

724
00:41:12,760 --> 00:41:16,640
Speaker 1: TikTok to sort of represent both sides and have balance.

725
00:41:16,680 --> 00:41:19,359
Speaker 1: Like I was like, I probably I could easily see

726
00:41:19,400 --> 00:41:22,279
Speaker 1: her being the kind of person that feels this way. Now,

727
00:41:22,400 --> 00:41:25,760
Speaker 1: her coming on as CEO does not necessarily signal big

728
00:41:25,880 --> 00:41:28,520
Speaker 1: changes at Twitter. Musk is staying on as the owner,

729
00:41:28,800 --> 00:41:30,880
Speaker 1: and he says that he wants to focus more on

730
00:41:30,920 --> 00:41:34,560
Speaker 1: like tech issues. Media Matters reported that Twitter's lawyers told

731
00:41:34,560 --> 00:41:37,520
Speaker 1: a court that hiring Koris the new CEO will not

732
00:41:37,680 --> 00:41:41,200
Speaker 1: result in different content moderation strategies. So if you had,

733
00:41:41,280 --> 00:41:45,560
Speaker 1: you know, high hopes for new content moderation strategies that

734
00:41:45,640 --> 00:41:48,319
Speaker 1: maybe don't allow for things like hate speech, attacks on

735
00:41:48,400 --> 00:41:52,879
Speaker 1: trans folks, crypto scams, and pornbots, you might be disappointed.

736
00:41:53,160 --> 00:41:54,719
Speaker 1: What's also kind of funny to me is that when

737
00:41:54,760 --> 00:41:57,400
Speaker 1: she was first announced as CEO, a bunch of right

738
00:41:57,480 --> 00:42:02,280
Speaker 1: wing and extremist influencers criticized her because she had talked

739
00:42:02,280 --> 00:42:04,680
Speaker 1: about wanting to hire more women and people of color

740
00:42:04,680 --> 00:42:07,360
Speaker 1: when she was at NBC and they had a video

741
00:42:07,400 --> 00:42:11,080
Speaker 1: of her in twenty twenty talking about the importance of masks,

742
00:42:11,160 --> 00:42:13,759
Speaker 1: like that was their big find. Just goes to show

743
00:42:13,760 --> 00:42:18,080
Speaker 1: that these people are literally never satisfied. Like anybody that

744
00:42:18,200 --> 00:42:20,040
Speaker 1: Musk was going to pick, they would still find a

745
00:42:20,080 --> 00:42:22,359
Speaker 1: way to make that a grievance, to make that an

746
00:42:22,400 --> 00:42:23,600
Speaker 1: attack on them.

747
00:42:23,800 --> 00:42:29,879
Speaker 2: Yeah, anyone to the left of Mussolini is like unacceptable

748
00:42:29,920 --> 00:42:30,520
Speaker 2: to these people.

749
00:42:30,920 --> 00:42:34,360
Speaker 1: So she's coming in as CEO at a self inflicted

750
00:42:34,400 --> 00:42:37,399
Speaker 1: difficult time for Twitter. The platform is not doing well.

751
00:42:37,400 --> 00:42:40,520
Speaker 1: It's not doing well with this regular users or with advertisers.

752
00:42:40,719 --> 00:42:42,799
Speaker 1: A recent poll by Pugh found that six and ten

753
00:42:42,840 --> 00:42:45,880
Speaker 1: adults in the US, which is Twitter's largest user base,

754
00:42:46,120 --> 00:42:48,200
Speaker 1: were taking a break, and a quarter of them said

755
00:42:48,200 --> 00:42:50,480
Speaker 1: that they did not expect to be using Twitter in

756
00:42:50,520 --> 00:42:53,279
Speaker 1: a year. When it comes to advertisers, of Twitter's top

757
00:42:53,320 --> 00:42:56,439
Speaker 1: one thousand advertisers from last September before Musk took over,

758
00:42:56,840 --> 00:42:59,960
Speaker 1: only forty three percent of them were still using Twitter

759
00:43:00,040 --> 00:43:03,080
Speaker 1: as of April. Now, Musk had been kind of cagey

760
00:43:03,160 --> 00:43:05,600
Speaker 1: about this, like he has not liked to talk about

761
00:43:05,640 --> 00:43:08,719
Speaker 1: the dire financial straits that the company was in, But

762
00:43:09,040 --> 00:43:11,800
Speaker 1: this week he finally did acknowledge that in a Twitter

763
00:43:11,840 --> 00:43:16,040
Speaker 1: spaces with presidential candidate and COVID conspiracy theorist Robert Kennedy Junior,

764
00:43:16,160 --> 00:43:18,440
Speaker 1: where he did admit that the revenue at Twitter had

765
00:43:18,480 --> 00:43:21,960
Speaker 1: been cut by about fifty percent. You know, advertisers buying

766
00:43:22,000 --> 00:43:25,520
Speaker 1: ads on Twitter is how the platform makes money, and

767
00:43:25,560 --> 00:43:29,799
Speaker 1: basically right now they're not doing that because what advertiser

768
00:43:29,880 --> 00:43:33,320
Speaker 1: wants to see their branding next to a tweet calling

769
00:43:33,360 --> 00:43:36,279
Speaker 1: somebody a racial slur or like a porn bot or

770
00:43:36,320 --> 00:43:38,960
Speaker 1: a scam or something. Right. I saw a pretty interesting

771
00:43:39,000 --> 00:43:43,120
Speaker 1: piece in BBC about how with Yakanaro's background working with

772
00:43:43,200 --> 00:43:47,120
Speaker 1: advertisers Musk was basically trying to purchase trust to woo

773
00:43:47,239 --> 00:43:48,400
Speaker 1: advertisers back.

774
00:43:49,040 --> 00:43:56,160
Speaker 2: Maybe she'll be less like chaotic than Musk. Maybe.

775
00:43:56,360 --> 00:43:58,600
Speaker 1: So if you're thinking that she sounds like she might

776
00:43:58,680 --> 00:44:00,840
Speaker 1: be a grown up in the room, might be somebody

777
00:44:00,840 --> 00:44:03,799
Speaker 1: who can sort of steer the ship in a better

778
00:44:04,239 --> 00:44:09,120
Speaker 1: direction than Musk has. That is a well worn phenomena

779
00:44:09,239 --> 00:44:11,560
Speaker 1: in business. There is this theory in business called the

780
00:44:11,600 --> 00:44:15,200
Speaker 1: glass cliff, where women are basically brought in to clean

781
00:44:15,280 --> 00:44:18,879
Speaker 1: up the messes made by terrible men in power. I'm

782
00:44:18,880 --> 00:44:20,880
Speaker 1: a good example of the glass cliff was after the

783
00:44:20,920 --> 00:44:26,080
Speaker 1: gaming company Blizzard had a massive gender discrimination and harassment lawsuit,

784
00:44:26,200 --> 00:44:28,719
Speaker 1: they hired in twenty twenty one Jen O'Neil, who was

785
00:44:28,880 --> 00:44:31,000
Speaker 1: the first female lead of the company, right, who was

786
00:44:31,000 --> 00:44:34,359
Speaker 1: sort of like brought in seeming lead to kind of

787
00:44:34,400 --> 00:44:37,920
Speaker 1: clean up this mess. Now, I absolutely do think that

788
00:44:37,920 --> 00:44:39,880
Speaker 1: that is what some of what's going on here, that

789
00:44:39,920 --> 00:44:41,640
Speaker 1: a woman is being brought in to clean up this

790
00:44:41,760 --> 00:44:44,520
Speaker 1: mess made by a man, and this sort of signal

791
00:44:44,680 --> 00:44:47,120
Speaker 1: that a grown up is in charge and that it's

792
00:44:47,120 --> 00:44:50,319
Speaker 1: no longer like a frat boy in charge. But I

793
00:44:50,440 --> 00:44:53,600
Speaker 1: also think that she is kind of being set up

794
00:44:53,680 --> 00:44:56,640
Speaker 1: to fail in a lot of ways. You know, it's

795
00:44:56,800 --> 00:45:00,920
Speaker 1: tough to be a such a high profile higher one

796
00:45:01,760 --> 00:45:05,440
Speaker 1: have to appease a demagogue, which we know Elon Musk

797
00:45:05,640 --> 00:45:10,719
Speaker 1: is too, and then have to handle that, navigate that

798
00:45:10,840 --> 00:45:15,080
Speaker 1: while also signaling to advertisers that big changes are coming

799
00:45:15,160 --> 00:45:19,920
Speaker 1: to woo them back. You know, it's this very difficult dance.

800
00:45:19,960 --> 00:45:22,640
Speaker 1: I would say it's an impossible dance to have to dance.

801
00:45:22,880 --> 00:45:26,000
Speaker 1: The way that people are talking about her background really

802
00:45:26,040 --> 00:45:27,960
Speaker 1: signals to me that she is being set up to

803
00:45:28,000 --> 00:45:31,280
Speaker 1: have to accomplish something that seems at least very difficult,

804
00:45:31,360 --> 00:45:35,200
Speaker 1: if not impossible. People have described her as someone who

805
00:45:35,280 --> 00:45:38,280
Speaker 1: really likes to be a superwoman and someone who can

806
00:45:38,840 --> 00:45:42,440
Speaker 1: who would see a mess of a company and voluntarily

807
00:45:42,680 --> 00:45:45,120
Speaker 1: want to go in and feel like they can fix things.

808
00:45:45,320 --> 00:45:48,160
Speaker 1: By the way, I hate this framing. I can't even

809
00:45:48,200 --> 00:45:51,680
Speaker 1: really get, like verbalize why I hate this. There's just

810
00:45:51,680 --> 00:45:55,560
Speaker 1: something about it that feels very much like women have

811
00:45:55,640 --> 00:45:59,719
Speaker 1: to be super women to be in the room that

812
00:45:59,760 --> 00:46:02,359
Speaker 1: they have to be. They can't just be included from

813
00:46:02,400 --> 00:46:06,160
Speaker 1: the jump. They have to be super women who are

814
00:46:06,200 --> 00:46:09,560
Speaker 1: not just able, but excited to clean up a mess

815
00:46:09,600 --> 00:46:13,000
Speaker 1: that was just clearly made by a man who had

816
00:46:13,040 --> 00:46:15,120
Speaker 1: too much power and didn't know how to handle it,

817
00:46:15,200 --> 00:46:15,400
Speaker 1: you know.

818
00:46:15,800 --> 00:46:18,600
Speaker 2: Yeah, And if you think about the mess that is Twitter,

819
00:46:19,680 --> 00:46:25,200
Speaker 2: it really all started when Elon took over, right, Like,

820
00:46:25,719 --> 00:46:30,560
Speaker 2: I guess, it had financial problems before then, but it

821
00:46:30,719 --> 00:46:37,520
Speaker 2: wasn't the chaotic, toxic place that it is now. Where

822
00:46:38,520 --> 00:46:41,759
Speaker 2: I mean, among my friends, I don't know too many

823
00:46:41,800 --> 00:46:45,160
Speaker 2: people that really spend much time there at all anymore.

824
00:46:45,239 --> 00:46:49,279
Speaker 2: He's really I don't know, Tank, the brand, whoever you

825
00:46:49,320 --> 00:46:50,600
Speaker 2: want to say it.

826
00:46:50,600 --> 00:46:53,759
Speaker 1: It'll be interesting to see how bringing on this new

827
00:46:53,840 --> 00:46:56,960
Speaker 1: CEO will be for Twitter. There was a very interesting

828
00:46:57,000 --> 00:47:00,160
Speaker 1: piece about the glass Cliff phenomena and wired twitch Yaknaro

829
00:47:00,280 --> 00:47:03,680
Speaker 1: responded on Twitter quote as someone used to wearing foreign cheels.

830
00:47:03,800 --> 00:47:06,960
Speaker 1: Let's be crystal clear. I don't teeter which, Okay, I'll

831
00:47:07,000 --> 00:47:08,480
Speaker 1: give it to her. Kind of a good line. I'm

832
00:47:08,520 --> 00:47:11,440
Speaker 1: not gonna lie, but it's clear, like we need to

833
00:47:11,440 --> 00:47:13,880
Speaker 1: be clear, Musk is staying on at Twitter. So even

834
00:47:13,880 --> 00:47:16,319
Speaker 1: with a new CEO, this is still his company. He's

835
00:47:16,360 --> 00:47:19,880
Speaker 1: not going away. And Musk does not have a great

836
00:47:19,960 --> 00:47:23,000
Speaker 1: track record when it comes to working alongside women. I

837
00:47:23,040 --> 00:47:25,960
Speaker 1: believe that Mosque is a misogynist. You don't even have

838
00:47:26,000 --> 00:47:27,879
Speaker 1: to look very far to see the ways in which

839
00:47:27,920 --> 00:47:30,440
Speaker 1: he is a misogynist either. There are like a hundred

840
00:47:30,600 --> 00:47:32,359
Speaker 1: different examples, and I could give you off the top

841
00:47:32,400 --> 00:47:34,360
Speaker 1: of my head, but immediately come to mind if we

842
00:47:34,440 --> 00:47:36,920
Speaker 1: listed all of the ways that Trump or Trump Oh

843
00:47:37,000 --> 00:47:42,440
Speaker 1: my god, he's also a massageist. No, keep that shit in.

844
00:47:42,520 --> 00:47:44,920
Speaker 1: They're both misogynists. They actually reminded me of each other.

845
00:47:44,920 --> 00:47:47,480
Speaker 1: A sound surprising to me that I confuse one for

846
00:47:47,600 --> 00:47:50,120
Speaker 1: the other. So you know, if we listed all the

847
00:47:50,280 --> 00:47:51,839
Speaker 1: different examples that come to the top of my head,

848
00:47:51,880 --> 00:47:54,799
Speaker 1: we'd be here all night. He tweeted a crass joke

849
00:47:54,920 --> 00:47:58,440
Speaker 1: about wanting to start a university called the Texas Institute

850
00:47:58,480 --> 00:48:03,440
Speaker 1: of Technology and Science TITS as the acronym. Side note,

851
00:48:03,760 --> 00:48:08,520
Speaker 1: it's never even a good sexist joke, right, Like, I

852
00:48:08,600 --> 00:48:12,319
Speaker 1: hate misogyny and sexism, but I love humor, and if

853
00:48:12,320 --> 00:48:16,520
Speaker 1: a sexist joke was legitimately funny, I would acknowledge it.

854
00:48:16,719 --> 00:48:19,680
Speaker 1: This isn't even a good joke. It's not even good misogyny.

855
00:48:19,760 --> 00:48:22,600
Speaker 1: Like if you're gonna tell, if you're gonna be a CEO,

856
00:48:23,040 --> 00:48:26,719
Speaker 1: that is this powerful and tell misogynistic jokes. Don't give

857
00:48:26,800 --> 00:48:28,840
Speaker 1: the joke that a million of us have heard in

858
00:48:28,880 --> 00:48:30,920
Speaker 1: the frat a thousand different times.

859
00:48:30,960 --> 00:48:33,520
Speaker 2: You know it's a bad joke, Like it's it's like

860
00:48:33,560 --> 00:48:37,239
Speaker 2: a Beavis and butt Head level joke, but like not

861
00:48:37,360 --> 00:48:39,719
Speaker 2: even good enough to actually be on Beavis and butt Head,

862
00:48:40,360 --> 00:48:43,920
Speaker 2: which is an excellent show, including the reboot.

863
00:48:44,200 --> 00:48:48,120
Speaker 1: Like I am someone who deeply appreciates stupid jokes and

864
00:48:48,160 --> 00:48:51,000
Speaker 1: stupid humor, and this is not even like I can't

865
00:48:51,040 --> 00:48:53,319
Speaker 1: even appreciate it. So the day after he tweeted this,

866
00:48:53,800 --> 00:48:57,640
Speaker 1: Tesla became the subject of a gender discrimination lawsuit from

867
00:48:57,680 --> 00:49:01,479
Speaker 1: multiple women, and I remember engineer and tech organizer Share

868
00:49:01,520 --> 00:49:03,920
Speaker 1: Scarlett tweeted in response to all this, I heard that

869
00:49:04,040 --> 00:49:07,239
Speaker 1: sexualizing women is a top down, systemic issue in tech.

870
00:49:07,640 --> 00:49:10,440
Speaker 1: Might be wrong, thou lighty k And to be honest,

871
00:49:11,080 --> 00:49:14,120
Speaker 1: that's how you do a funny joke about gender and tech. Elon,

872
00:49:14,480 --> 00:49:15,400
Speaker 1: take a note.

873
00:49:15,600 --> 00:49:17,600
Speaker 2: Yes, acronyms are not the way.

874
00:49:17,840 --> 00:49:20,719
Speaker 1: Yeah an acronym that spells out tits, which is a

875
00:49:21,120 --> 00:49:25,160
Speaker 1: body part that is sometimes found on female anatomy. Oh

876
00:49:25,200 --> 00:49:27,759
Speaker 1: my god, Like, get this, get this guy a Mark

877
00:49:27,800 --> 00:49:31,760
Speaker 1: Twain Award, somebody. So, according to a report from Business insider,

878
00:49:31,880 --> 00:49:36,000
Speaker 1: Musk secretly fathered twins with Chavon Zill's, a female executive

879
00:49:36,040 --> 00:49:38,840
Speaker 1: at his company, Neuralik. So we don't know much about

880
00:49:38,880 --> 00:49:41,360
Speaker 1: their relationship. But if you're the head of a company

881
00:49:41,400 --> 00:49:44,520
Speaker 1: and you're having sex with your underlings and your staff,

882
00:49:44,920 --> 00:49:47,480
Speaker 1: I feel comfortable saying that, Like, at the very least,

883
00:49:47,480 --> 00:49:50,200
Speaker 1: it's not a great look. All of this information is public, right,

884
00:49:50,239 --> 00:49:53,080
Speaker 1: So by all the accounts, Jacanaro, this new Twitter CEO

885
00:49:53,600 --> 00:49:56,719
Speaker 1: seems like a smart, competent person who would have looked

886
00:49:56,719 --> 00:49:59,239
Speaker 1: at this information and decided that Twitter and Elon Musk

887
00:49:59,280 --> 00:50:01,080
Speaker 1: were who and what what she wanted to be mixed

888
00:50:01,120 --> 00:50:04,800
Speaker 1: up with. And if that's what you decided, as a confident,

889
00:50:04,880 --> 00:50:08,000
Speaker 1: smart adult, that's what you wanted. If it doesn't work out,

890
00:50:08,040 --> 00:50:10,759
Speaker 1: like you kind of in my book, like get what

891
00:50:10,840 --> 00:50:13,319
Speaker 1: you get, Like this is all public information is if

892
00:50:13,320 --> 00:50:15,840
Speaker 1: this is the company that you decided that you wanted

893
00:50:16,040 --> 00:50:18,799
Speaker 1: to stake your reputation on, girl do you but you

894
00:50:18,840 --> 00:50:20,719
Speaker 1: get what you get, you know, And I want to

895
00:50:20,719 --> 00:50:24,279
Speaker 1: be clear, I want Yakanero to do well the same

896
00:50:24,320 --> 00:50:26,920
Speaker 1: way that I want like all women to do well.

897
00:50:27,120 --> 00:50:29,880
Speaker 1: You know, I'm not like rooting for her to fail.

898
00:50:30,239 --> 00:50:34,000
Speaker 1: But to me, doing well is not just bringing back

899
00:50:34,040 --> 00:50:38,440
Speaker 1: advertisers or appeasing Elon Musk or helping Twitter make money.

900
00:50:38,719 --> 00:50:41,640
Speaker 1: Doing well would be making Twitter a platform that does

901
00:50:41,680 --> 00:50:46,239
Speaker 1: not elevate and amplify toxicity, lives, abuse, scams, and harassment.

902
00:50:46,239 --> 00:50:49,759
Speaker 1: And so I wish her well and hope that she's

903
00:50:49,800 --> 00:50:54,280
Speaker 1: able to achieve that. But I think that her vision

904
00:50:54,440 --> 00:50:57,480
Speaker 1: for doing well and what I have just articulated might

905
00:50:57,520 --> 00:50:58,799
Speaker 1: be two different things.

906
00:50:59,360 --> 00:51:04,759
Speaker 2: Yeah, to be interesting to watch it develop. Uh you know,

907
00:51:04,840 --> 00:51:11,359
Speaker 2: maybe I've bought into the glass cliff mythology, but uh, yeah,

908
00:51:11,520 --> 00:51:16,080
Speaker 2: it seems like having having a smart, competent woman in

909
00:51:16,080 --> 00:51:20,240
Speaker 2: the room probably couldn't hurt and hopefully it'll be good.

910
00:51:20,360 --> 00:51:24,120
Speaker 2: But I guess we'll just have to wait and see

911
00:51:24,400 --> 00:51:29,279
Speaker 2: as this Twitter, this latest Twitter drama unfolds.

912
00:51:30,040 --> 00:51:33,080
Speaker 1: Now, I don't trust any institution or company that doesn't

913
00:51:33,080 --> 00:51:37,759
Speaker 1: have some women at the at the highest levels, the priesthood,

914
00:51:38,360 --> 00:51:42,440
Speaker 1: the NFL. Uh yeah, if you don't have the military,

915
00:51:42,600 --> 00:51:45,799
Speaker 1: if there's not women all up through that, I have

916
00:51:45,920 --> 00:51:50,040
Speaker 1: questions that I'm a little skeptical just in general. That's

917
00:51:50,040 --> 00:51:51,920
Speaker 1: a blanket statement. If I don't see, if I don't

918
00:51:51,920 --> 00:51:55,480
Speaker 1: see a woman making decisions something.

919
00:51:56,360 --> 00:51:58,360
Speaker 2: Yeah, it's it's a set of somebody.

920
00:51:58,480 --> 00:52:00,680
Speaker 1: Somebody's tweeting the word tits. So all, let's put it

921
00:52:00,760 --> 00:52:02,280
Speaker 1: at the very least.

922
00:52:04,480 --> 00:52:07,000
Speaker 2: You know, I've never thought of those three institutions as

923
00:52:07,000 --> 00:52:14,960
Speaker 2: a set together before, so thank you for that. More.

924
00:52:14,960 --> 00:52:28,000
Speaker 3: After a quick break, let's get right back into it.

925
00:52:32,600 --> 00:52:34,600
Speaker 1: So. I know that this has been a little dark,

926
00:52:34,640 --> 00:52:36,200
Speaker 1: but I do have a little bit of a good news.

927
00:52:36,400 --> 00:52:37,279
Speaker 1: Would you like to hear it?

928
00:52:38,000 --> 00:52:39,560
Speaker 2: Yes? Please, So it's.

929
00:52:39,440 --> 00:52:41,360
Speaker 1: Going to start with some bad news, but trust me,

930
00:52:41,400 --> 00:52:44,279
Speaker 1: it'll get good. Stick with me. I probably don't need

931
00:52:44,320 --> 00:52:46,720
Speaker 1: to tell y'all that book bands are on the rise

932
00:52:46,760 --> 00:52:50,719
Speaker 1: in the US, with books that center LGBTQ voices accounting

933
00:52:50,719 --> 00:52:53,279
Speaker 1: for about forty one percent of challenged books. This is

934
00:52:53,320 --> 00:52:56,080
Speaker 1: according to Pan America. Attempted book bands at school and

935
00:52:56,120 --> 00:52:58,920
Speaker 1: public library set a record high in twenty twenty two.

936
00:52:59,320 --> 00:53:03,200
Speaker 1: This is according to information from the American Library Association. Obviously,

937
00:53:03,440 --> 00:53:05,960
Speaker 1: that is terrible, but here's the good news. At a

938
00:53:06,000 --> 00:53:09,480
Speaker 1: White House Pride event yesterday, Biden announced a slate of

939
00:53:09,520 --> 00:53:13,799
Speaker 1: actions aimed at curbing discrimination against LGBTQ communities, including the

940
00:53:13,840 --> 00:53:16,120
Speaker 1: appointment of a new point person who will serve as

941
00:53:16,120 --> 00:53:19,480
Speaker 1: a coordinator at the Education Department to address the increase

942
00:53:19,560 --> 00:53:22,560
Speaker 1: in book bands. That's good, I like to see that.

943
00:53:22,880 --> 00:53:25,839
Speaker 1: But here's a little bit more positive news. Despite all

944
00:53:25,880 --> 00:53:28,400
Speaker 1: of those bands and all of those restrictions and all

945
00:53:28,440 --> 00:53:32,359
Speaker 1: of those attempted attacks by extremists to challenge and ban

946
00:53:32,480 --> 00:53:37,640
Speaker 1: books about LGBTQ people, people still really really want to

947
00:53:37,640 --> 00:53:39,560
Speaker 1: read about queer folks and are going out of their

948
00:53:39,560 --> 00:53:43,640
Speaker 1: way to do so. Sales of LGBTQ plus books soared

949
00:53:43,680 --> 00:53:45,920
Speaker 1: to record highs in twenty twenty two, even as a

950
00:53:45,920 --> 00:53:48,520
Speaker 1: small but vocal army of extremists try to ban queer

951
00:53:48,560 --> 00:53:51,960
Speaker 1: theme titles and attack inclusive education across the country, US

952
00:53:52,040 --> 00:53:56,240
Speaker 1: readers bought six point one million LGBTQ plus fiction titles

953
00:53:56,520 --> 00:53:58,600
Speaker 1: over the past year ending in May twenty twenty three.

954
00:53:58,680 --> 00:54:00,600
Speaker 1: This is according to a new report put out on

955
00:54:00,680 --> 00:54:04,520
Speaker 1: Tuesday by consumer analyst group CIRCANNA that marks an eleven

956
00:54:04,600 --> 00:54:08,040
Speaker 1: percent jump in growth since last year, when around five

957
00:54:08,120 --> 00:54:10,880
Speaker 1: million total units were sold, and a massive one hundred

958
00:54:10,880 --> 00:54:14,480
Speaker 1: and seventy three percent explosions in twenty nineteen before the

959
00:54:14,480 --> 00:54:17,520
Speaker 1: COVID nineteen pandemic. This is a really important context. The

960
00:54:17,600 --> 00:54:21,640
Speaker 1: growth in LGBTQ fiction has outpaced the overall market for

961
00:54:21,719 --> 00:54:25,640
Speaker 1: fiction sales, including adult, kids and young adult fiction combined,

962
00:54:25,880 --> 00:54:29,200
Speaker 1: which remained relatively flat. This is from Kristen MacLean, a

963
00:54:29,239 --> 00:54:32,120
Speaker 1: book industry analyst. So it just goes to show you

964
00:54:32,200 --> 00:54:35,879
Speaker 1: can try to ban queerness and transness and gainness out

965
00:54:35,960 --> 00:54:39,360
Speaker 1: of existence, people still want to see it represented. People

966
00:54:39,360 --> 00:54:41,880
Speaker 1: will go out of their way to get that inclusion

967
00:54:41,960 --> 00:54:45,160
Speaker 1: because that is what people want. The extremists who are

968
00:54:45,200 --> 00:54:48,960
Speaker 1: trying to ban and legislate that out of existence are

969
00:54:49,080 --> 00:54:51,960
Speaker 1: out of step with the desires of the majority of

970
00:54:51,960 --> 00:54:55,320
Speaker 1: the country. I believe they are a small but vocal

971
00:54:55,480 --> 00:54:58,040
Speaker 1: group of extremists, and there are more of us than

972
00:54:58,040 --> 00:55:00,479
Speaker 1: there are of them, and I think that is news.

973
00:55:01,080 --> 00:55:03,960
Speaker 2: That is good news. Thank you for sharing that. It's

974
00:55:04,040 --> 00:55:08,919
Speaker 2: good to be reminded that the right wing bigots are

975
00:55:08,960 --> 00:55:13,839
Speaker 2: a minority and they are freaking out because they know it,

976
00:55:14,000 --> 00:55:17,040
Speaker 2: and they know that they are going to go extinct.

977
00:55:17,440 --> 00:55:21,000
Speaker 1: So I've got a little bit of bonus good news.

978
00:55:20,719 --> 00:55:25,200
Speaker 2: For you, two different good news stories in one episode.

979
00:55:26,560 --> 00:55:29,880
Speaker 1: It's not really good news exactly, but the good news

980
00:55:30,040 --> 00:55:32,280
Speaker 1: is that one of my favorite things in the world

981
00:55:32,600 --> 00:55:36,040
Speaker 1: is low stakes online internet drama where there are no

982
00:55:36,280 --> 00:55:39,080
Speaker 1: clear like good guys to root for, and the entire

983
00:55:39,120 --> 00:55:41,120
Speaker 1: internet is like weighing in on what they think. And

984
00:55:41,160 --> 00:55:43,160
Speaker 1: some of that happened, and so it's good news for

985
00:55:43,280 --> 00:55:48,479
Speaker 1: me personally, Bridget. So here's what we've been down. There's

986
00:55:48,520 --> 00:55:51,799
Speaker 1: two moms, let's call one park Mom and the other

987
00:55:52,040 --> 00:55:55,799
Speaker 1: birthday cake Mom. So park Mom gets on TikTok and

988
00:55:55,880 --> 00:55:58,160
Speaker 1: explains the situation. She says that she took her kid

989
00:55:58,280 --> 00:56:00,320
Speaker 1: to a public park and there was another f family

990
00:56:00,360 --> 00:56:02,479
Speaker 1: there who is having a birthday party for their kid.

991
00:56:02,880 --> 00:56:06,760
Speaker 1: Her kid basically starts playing with this other family having

992
00:56:06,760 --> 00:56:10,200
Speaker 1: this party. It's time to sing Happy Birthday and due cake.

993
00:56:10,600 --> 00:56:13,719
Speaker 1: So park Mom is watching her kid. It sounds like

994
00:56:13,719 --> 00:56:16,000
Speaker 1: from the other side of the playground. Park Mom says

995
00:56:16,040 --> 00:56:19,560
Speaker 1: that she watches her kid get a plate, sing happy

996
00:56:19,600 --> 00:56:22,880
Speaker 1: Birthday and clearly have the intention that they're going to

997
00:56:22,960 --> 00:56:27,360
Speaker 1: have birthday cake. That is when birthday cake Mom takes

998
00:56:27,360 --> 00:56:31,000
Speaker 1: the plate away from her the kid and says, you're

999
00:56:31,040 --> 00:56:33,200
Speaker 1: not going to have a piece of cake. These are

1000
00:56:33,200 --> 00:56:36,520
Speaker 1: not your friends, this is not your party. Where is

1001
00:56:36,560 --> 00:56:37,000
Speaker 1: your mother?

1002
00:56:37,360 --> 00:56:40,279
Speaker 2: Devastating So park.

1003
00:56:40,120 --> 00:56:44,280
Speaker 1: Mom, in her TikTok says basically, am I the asshole?

1004
00:56:44,760 --> 00:56:49,279
Speaker 1: Park Mom is horrified. She cannot believe that birthday cake

1005
00:56:49,360 --> 00:56:51,720
Speaker 1: mom would speak to a kid this way. She cannot

1006
00:56:51,760 --> 00:56:55,280
Speaker 1: believe that birthday cake mom, who had what she describes

1007
00:56:55,360 --> 00:56:57,680
Speaker 1: as a big sheet cake with lots of lots of

1008
00:56:57,680 --> 00:56:59,680
Speaker 1: cake to go around, plenty of cake for her kid,

1009
00:56:59,719 --> 00:57:04,600
Speaker 1: would deny her kid a slice of cake. She asks

1010
00:57:04,640 --> 00:57:07,160
Speaker 1: the Internet on TikTok is she wrong?

1011
00:57:07,480 --> 00:57:07,560
Speaker 2: So?

1012
00:57:07,960 --> 00:57:11,520
Speaker 1: This is why I love this drama so much. It's

1013
00:57:11,520 --> 00:57:15,279
Speaker 1: one of those things where there is no clear right

1014
00:57:15,360 --> 00:57:20,520
Speaker 1: answer and everybody is weighing in, and like what people

1015
00:57:20,560 --> 00:57:23,480
Speaker 1: weigh in with actually says more about them than it

1016
00:57:23,520 --> 00:57:26,000
Speaker 1: does about the situation, because the situation, we actually don't

1017
00:57:26,040 --> 00:57:28,920
Speaker 1: have a lot of information, like how old are these kids?

1018
00:57:29,000 --> 00:57:31,680
Speaker 1: You know. Some people were like, oh, well, I wouldn't

1019
00:57:31,680 --> 00:57:34,560
Speaker 1: give food to someone else's kid that I didn't know,

1020
00:57:34,600 --> 00:57:36,840
Speaker 1: Like what if they have an allergy? Other people were like, well,

1021
00:57:36,880 --> 00:57:39,040
Speaker 1: who's allergic to birthday cake? That seems like a weird

1022
00:57:39,040 --> 00:57:41,480
Speaker 1: thing that to just suggest that maybe they're allergyp to

1023
00:57:41,520 --> 00:57:44,920
Speaker 1: birthday cake? Read every comment, Love every minute of it,

1024
00:57:45,120 --> 00:57:49,280
Speaker 1: you know, I it sounds to me like, if I'm

1025
00:57:49,320 --> 00:57:52,960
Speaker 1: being honest, it sounds to me like Park mom just

1026
00:57:53,040 --> 00:57:56,960
Speaker 1: kind of let her kid join this other family and

1027
00:57:57,080 --> 00:57:59,680
Speaker 1: never went over and introduced herself or said like, hey,

1028
00:58:00,080 --> 00:58:02,600
Speaker 1: I'm whoever. Is it cool if my kid hangs out, like,

1029
00:58:02,680 --> 00:58:04,920
Speaker 1: let me know if they get annoying, just assume that

1030
00:58:04,960 --> 00:58:09,320
Speaker 1: it was fine. Kind of a point against Park Mom. Also,

1031
00:58:09,400 --> 00:58:11,400
Speaker 1: I feel like snatching a plate from a kid and

1032
00:58:11,440 --> 00:58:14,160
Speaker 1: saying these are not your friends a little bit harsh.

1033
00:58:14,280 --> 00:58:18,200
Speaker 1: I probably wouldn't do that, but I'm like, I don't

1034
00:58:18,240 --> 00:58:20,640
Speaker 1: know who is in the right here. I just love

1035
00:58:20,720 --> 00:58:24,640
Speaker 1: that it's low stakes. There's no clear correct answer. Everyone

1036
00:58:24,680 --> 00:58:27,280
Speaker 1: on the internet is weighing in, and their way in

1037
00:58:28,000 --> 00:58:31,200
Speaker 1: says more about who they are and what their values are,

1038
00:58:31,800 --> 00:58:33,400
Speaker 1: and you know who they are as people in the

1039
00:58:33,440 --> 00:58:37,160
Speaker 1: world that it does about the actual situation. Tad out

1040
00:58:37,160 --> 00:58:40,760
Speaker 1: of ten love this kind of low stakes internet drama.

1041
00:58:40,880 --> 00:58:44,760
Speaker 2: Yes, please, It is nice that it's so low stakes,

1042
00:58:45,240 --> 00:58:47,280
Speaker 2: you know. No, Like I feel for the kid who

1043
00:58:47,360 --> 00:58:50,480
Speaker 2: didn't get the cake. It sounds like park Mom was

1044
00:58:50,560 --> 00:58:52,760
Speaker 2: also pretty upset.

1045
00:58:54,000 --> 00:58:56,400
Speaker 1: Yes, I'm sat are entitled Mike?

1046
00:58:57,080 --> 00:59:01,520
Speaker 2: Yeah, well, you know, I'm trying to refrain from sharing

1047
00:59:01,560 --> 00:59:02,680
Speaker 2: my thoughts here.

1048
00:59:02,800 --> 00:59:05,080
Speaker 1: No, what do you you have? You have a take,

1049
00:59:05,280 --> 00:59:07,760
Speaker 1: like what's like, who do you think is in the wrong?

1050
00:59:08,080 --> 00:59:11,240
Speaker 2: Well, I mean, just give the kids some damn cake,

1051
00:59:11,360 --> 00:59:15,120
Speaker 2: Like what the hell? Like, one person's an adult, the

1052
00:59:15,200 --> 00:59:18,959
Speaker 2: other person is a kid who wanted who like came

1053
00:59:19,040 --> 00:59:21,240
Speaker 2: to sing the birthday song and like play with some

1054
00:59:21,280 --> 00:59:24,600
Speaker 2: other kids and like have some cake. Like regardless of

1055
00:59:24,680 --> 00:59:29,680
Speaker 2: who's like truly morally in the right or like violating

1056
00:59:29,720 --> 00:59:33,120
Speaker 2: someone else's personal property or whatever. Like one of them

1057
00:59:33,200 --> 00:59:35,760
Speaker 2: is a kid who sang the birthday song and wanted

1058
00:59:35,800 --> 00:59:38,040
Speaker 2: a piece of cake. The other one's an adult.

1059
00:59:38,080 --> 00:59:39,960
Speaker 1: Well, I saw a lot of people on the internet

1060
00:59:40,000 --> 00:59:44,120
Speaker 1: being like this kid the birthday cake. Mom probably was

1061
00:59:44,160 --> 00:59:46,560
Speaker 1: annoyed by this kid the whole time and was probably like,

1062
00:59:46,600 --> 00:59:48,720
Speaker 1: where's your mom to come get you? And was like

1063
00:59:49,440 --> 00:59:52,320
Speaker 1: just in this it not not to like excuse her behavior,

1064
00:59:52,360 --> 00:59:54,520
Speaker 1: but was like in one of those situations where you're

1065
00:59:54,520 --> 00:59:56,640
Speaker 1: getting more and more and more annoyed and then you're

1066
00:59:56,680 --> 00:59:59,440
Speaker 1: just like, now it's coming out of an outburst that

1067
00:59:59,480 --> 01:00:01,200
Speaker 1: doesn't really makes sense, and it's kind of that the

1068
01:00:01,200 --> 01:00:05,720
Speaker 1: wrong person, which I know very well in my personal life.

1069
01:00:05,920 --> 01:00:08,800
Speaker 1: But yeah, I kind of see all sides. I think

1070
01:00:08,800 --> 01:00:11,320
Speaker 1: that I have been park mom I probably would have.

1071
01:00:12,120 --> 01:00:15,840
Speaker 1: I find it frankly unfathomable that at this that someone

1072
01:00:15,880 --> 01:00:18,000
Speaker 1: could watch their kid playing with another family, but it

1073
01:00:18,040 --> 01:00:19,800
Speaker 1: wouldn't occur to them at some point to go up

1074
01:00:19,800 --> 01:00:23,000
Speaker 1: town and be like, hey, like I'm Sally, this is

1075
01:00:23,040 --> 01:00:25,440
Speaker 1: my kid, Like this is fine, You're you're cool with this.

1076
01:00:26,000 --> 01:00:27,960
Speaker 1: I think it's a It is surprising to me that

1077
01:00:28,360 --> 01:00:32,000
Speaker 1: that a mom wouldn't, you know, do that. I think

1078
01:00:32,040 --> 01:00:34,880
Speaker 1: that's probably what I would do. Uh probably honestly would

1079
01:00:34,920 --> 01:00:37,120
Speaker 1: have like solved this whole thing. It also was surprising

1080
01:00:37,160 --> 01:00:39,000
Speaker 1: to me that a grown woman would be like snatching

1081
01:00:39,000 --> 01:00:41,560
Speaker 1: a plate from a child. That's that's why it's so good,

1082
01:00:41,600 --> 01:00:45,720
Speaker 1: Because everybody but this kid has done something that I

1083
01:00:45,760 --> 01:00:49,240
Speaker 1: would not suggest adults do. Everybody's behavior is a little

1084
01:00:49,280 --> 01:00:49,680
Speaker 1: bit off.

1085
01:00:50,000 --> 01:00:52,160
Speaker 2: Maybe that's part of what makes this so satisfying. It's

1086
01:00:52,160 --> 01:00:55,440
Speaker 2: almost like reality TV, where like like am I the asshole? Like,

1087
01:00:55,520 --> 01:00:59,840
Speaker 2: actually everyone's the asshole? You know, park mom probably should

1088
01:00:59,840 --> 01:01:02,200
Speaker 2: have been keeping it better around her kid. Birthday Mom

1089
01:01:02,520 --> 01:01:04,840
Speaker 2: probably could have given the kids some cake. I guess

1090
01:01:04,880 --> 01:01:07,760
Speaker 2: I do want to give birthday mom a little bit

1091
01:01:07,880 --> 01:01:12,320
Speaker 2: of grace here, because like I've thrown a party in

1092
01:01:12,360 --> 01:01:16,640
Speaker 2: my life, you know, a couple of times, and it's stressful,

1093
01:01:16,760 --> 01:01:18,120
Speaker 2: and it kind of makes me a bit of a

1094
01:01:18,160 --> 01:01:20,920
Speaker 2: head case. I like to think that I would still

1095
01:01:21,040 --> 01:01:25,280
Speaker 2: be like kind to a child, but you know, it's

1096
01:01:25,320 --> 01:01:29,600
Speaker 2: a high pressure thing. Maybe she had trouble tracking down

1097
01:01:29,640 --> 01:01:32,000
Speaker 2: the sheet cake, and like the kids keep running around

1098
01:01:32,040 --> 01:01:34,320
Speaker 2: and yelling and like where's birthday?

1099
01:01:34,400 --> 01:01:34,680
Speaker 1: Dad?

1100
01:01:34,800 --> 01:01:36,760
Speaker 2: Is he helping? I don't hear anything about him in

1101
01:01:36,800 --> 01:01:37,320
Speaker 2: this story.

1102
01:01:39,240 --> 01:01:42,440
Speaker 1: It makes it better that it's two moms. I feel, yeah,

1103
01:01:42,480 --> 01:01:44,080
Speaker 1: it actually I think I think I was telling you

1104
01:01:44,160 --> 01:01:46,520
Speaker 1: about this that it reminds me so you and I

1105
01:01:46,560 --> 01:01:48,120
Speaker 1: had very I know that you and I had very

1106
01:01:48,160 --> 01:01:51,560
Speaker 1: different upbringing sess children. I grew up in the suburbs.

1107
01:01:51,640 --> 01:01:53,480
Speaker 1: You grew up on a farm and like in a

1108
01:01:53,600 --> 01:01:56,120
Speaker 1: very rural community, so this was not something that you

1109
01:01:56,160 --> 01:01:58,920
Speaker 1: really knew about. But when I was a kid, I

1110
01:01:59,000 --> 01:02:02,880
Speaker 1: remember I have several memories of in the summertime going

1111
01:02:02,920 --> 01:02:06,160
Speaker 1: out to play on our street with other kids. One

1112
01:02:06,160 --> 01:02:07,960
Speaker 1: of the other kids would be like, hey, you want

1113
01:02:07,960 --> 01:02:10,000
Speaker 1: to come back to my house. I would say sure.

1114
01:02:10,480 --> 01:02:12,760
Speaker 1: I would go back to this kid's house, like a

1115
01:02:12,760 --> 01:02:15,360
Speaker 1: couple of blocks away. I would get there, their mom

1116
01:02:15,440 --> 01:02:18,880
Speaker 1: would be there, so they'll be like, oh, you are

1117
01:02:18,920 --> 01:02:21,240
Speaker 1: now expected to like keep an eye on this like

1118
01:02:21,440 --> 01:02:24,320
Speaker 1: stranger kid from down the street, and half the time

1119
01:02:24,360 --> 01:02:27,560
Speaker 1: I think we would expect food. So it's like, oh, hi, Mom,

1120
01:02:27,920 --> 01:02:30,840
Speaker 1: it's not just me the kid that you had that

1121
01:02:30,880 --> 01:02:34,840
Speaker 1: you you know, aren't caring for. It's a stranger's kid

1122
01:02:34,880 --> 01:02:38,840
Speaker 1: that you don't even know, and she expects lunch. Like

1123
01:02:39,680 --> 01:02:42,680
Speaker 1: I think there is something kind of entitled about sending

1124
01:02:42,720 --> 01:02:46,880
Speaker 1: your kids with strangers and expecting them to be fed.

1125
01:02:47,360 --> 01:02:50,040
Speaker 1: But I absolutely that was my I mean, like maybe

1126
01:02:50,080 --> 01:02:52,400
Speaker 1: I misremembering, but I feel like that's how it was

1127
01:02:52,440 --> 01:02:53,400
Speaker 1: when I was growing up.

1128
01:02:53,720 --> 01:02:56,560
Speaker 2: Yeah, that was different from my upbringing. You know, there

1129
01:02:56,560 --> 01:03:00,200
Speaker 2: were like four other kids within a mile radius of

1130
01:03:00,280 --> 01:03:03,640
Speaker 2: our house, right Like I knew them all and also

1131
01:03:03,720 --> 01:03:06,720
Speaker 2: needed a ride from my parents if I wanted to

1132
01:03:06,720 --> 01:03:09,800
Speaker 2: go see them, So that, just like straight was not happening.

1133
01:03:10,200 --> 01:03:13,440
Speaker 1: So I want to know where you stand on this drama. Again,

1134
01:03:13,520 --> 01:03:16,520
Speaker 1: it's low stakes, so no judgment. If you would have

1135
01:03:17,120 --> 01:03:20,320
Speaker 1: snatched that paper plate from that kid so fast it

1136
01:03:20,320 --> 01:03:21,960
Speaker 1: makes your head spend, I want to know about it.

1137
01:03:22,000 --> 01:03:24,960
Speaker 1: If you would have gotten Mom's Venmo information to Venmo

1138
01:03:25,040 --> 01:03:26,760
Speaker 1: her for her share of the cake. I want to

1139
01:03:26,800 --> 01:03:29,600
Speaker 1: know that too. I'm obsessed. Let me know. Hit me

1140
01:03:29,680 --> 01:03:31,960
Speaker 1: up on email at Hello at tango dot com. You

1141
01:03:32,000 --> 01:03:35,120
Speaker 1: can find me on social or you can subscribe to

1142
01:03:35,160 --> 01:03:39,360
Speaker 1: our Patreon. We are having interesting conversations over there. Thank

1143
01:03:39,360 --> 01:03:41,400
Speaker 1: you so much to the folks who have subscribed. I've

1144
01:03:41,440 --> 01:03:45,800
Speaker 1: got some really exciting stuff coming up on Patreon soon.

1145
01:03:46,960 --> 01:03:49,720
Speaker 1: I'll give you a little teaser. It involves Elon Musk

1146
01:03:49,760 --> 01:03:54,880
Speaker 1: and Azalea Banks, my problematic fave. So please subscribe. We

1147
01:03:54,880 --> 01:03:57,800
Speaker 1: would love to have you there, and thanks so much

1148
01:03:57,840 --> 01:03:59,040
Speaker 1: for listening. We'll see you next time.

1149
01:03:59,440 --> 01:04:01,120
Speaker 2: Yeah, so listening, and thanks for having me.

1150
01:04:01,120 --> 01:04:06,120
Speaker 1: Bridget always Mike. If you're looking for ways to support

1151
01:04:06,120 --> 01:04:08,600
Speaker 1: the show, check out our merch store at tangody dot

1152
01:04:08,600 --> 01:04:12,240
Speaker 1: com slash store. Got a story about an interesting thing

1153
01:04:12,240 --> 01:04:14,240
Speaker 1: in tech, or just want to say hi, You can

1154
01:04:14,320 --> 01:04:16,560
Speaker 1: reach us at Hello at tangody dot com. You can

1155
01:04:16,560 --> 01:04:19,520
Speaker 1: also find transcripts for today's episode at TENG Goody dot com.

1156
01:04:19,640 --> 01:04:21,320
Speaker 1: There Are No Girls on the Internet was created by

1157
01:04:21,320 --> 01:04:24,680
Speaker 1: me Bridget tod It's a production of iHeartRadio and Unbossed Creative,

1158
01:04:25,200 --> 01:04:28,800
Speaker 1: edited by Joey pat Jonathan Strickland as our executive producer.

1159
01:04:29,120 --> 01:04:32,360
Speaker 1: Tari Harrison is our producer and sound engineer. Michael Amado

1160
01:04:32,440 --> 01:04:35,440
Speaker 1: is our contributing producer. I'm your host, Bridget Todd. If

1161
01:04:35,440 --> 01:04:37,160
Speaker 1: you want to help us grow, rate and review.

1162
01:04:37,080 --> 01:04:38,120
Speaker 3: Us on Apple Podcasts.

1163
01:04:38,880 --> 01:04:41,720
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1164
01:04:41,720 --> 01:04:48,040
Speaker 1: Apple Podcasts, or wherever you get your podcasts.