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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 Tot and this

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Speaker 1: is There Are No Girls on the Internet. Welcome to

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

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Speaker 1: intersection of identity, social media, technology, and the Internet experience.

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Speaker 2: And this is another installment of.

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Speaker 1: Our weekly news roundup, where we summarize Internet news that

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Speaker 1: you might have missed.

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Speaker 2: Joey, thank you so much for being here.

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Speaker 3: Hey, Bridget, thanks for having me.

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Speaker 1: Okay, so I have to start out with a question.

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Speaker 1: Do you have any tech related pet peeves? You might

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Speaker 1: have guessed this is like me asking you so that

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Speaker 1: I can grape about mine, but I want to hear

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Speaker 1: yours first.

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Speaker 3: Joey, Oh, Bridget.

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Speaker 4: So many why do you think about the show? So Okay,

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Speaker 4: this is like a very smalling in the grand scheme

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Speaker 4: of things pet peeve. But lately I've been really really

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Speaker 4: annoyed with the Spotify algorithm. Uh, just because I don't

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Speaker 4: know if y'all have tried, like they have this new

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Speaker 4: not new, I guess it's been around for like a minute.

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Speaker 4: But if you type in like angry mix or like

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Speaker 4: happy mix, like it'll come up with like a collection

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Speaker 4: of songs so they have created for you, and it

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Speaker 4: just like hasn't been good. I've got some really weird

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Speaker 4: butns I think especially, I don't know, I think I.

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Speaker 3: Maybe it's also just like, like.

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Speaker 4: I've listened to a very wide variety of music, so

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Speaker 4: I feel like a lot of times too, like a

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Speaker 4: lot of it will get like mixed up together when

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Speaker 4: I don't like it'll it'll label things in certain genres

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Speaker 4: that they aren't.

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Speaker 3: Just because I've been listening to it a lot.

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Speaker 2: I don't know.

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Speaker 4: Anyways, I've been very annoyous to the Spotify algorithm lately.

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Speaker 4: I'm not And also I've realized it has been very

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Speaker 4: hard to find like new music to listen to because

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Speaker 4: it just keeps recommending the same artists that I already

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Speaker 4: listened to, like when I'm looking for new music, which

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Speaker 4: you know is fun if I like, I'm just trying

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Speaker 4: to listen to songs that I like. But like, I think,

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Speaker 4: especially trying to find new stuff now just because of

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Speaker 4: this new like these mixes that are tailored specifically for you,

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Speaker 4: it makes it so much harder to find new stuff

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Speaker 4: which I don't like.

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Speaker 3: Yeah, so and I don't know.

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Speaker 4: There's so many issues that Spotify just as a company,

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Speaker 4: and like the way that like the streaming sort of

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Speaker 4: net industry works that I it's annoying.

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Speaker 3: It's very annoying.

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Speaker 1: You have like activated something in me because I could

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Speaker 1: talk about this all day. So I think this is

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Speaker 1: just I haven't done any research into this because it's

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Speaker 1: just banter. But I think I know what's happening with

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Speaker 1: your playlist, which I think that Spotify is probably if

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Speaker 1: I had to say, deprioritizing human people who make curated

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Speaker 1: playlists and curated recommendations. Like I know that they used

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Speaker 1: to have like big teams of humans working at Spotify

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Speaker 1: that made playlists, and I know that like they are

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Speaker 1: using AI to do some of that now, so I

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Speaker 1: wonder if that's had a hand in why the playlist

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Speaker 1: don't earnest good. I also think like with the play

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Speaker 1: with like when you're looking for new music, you want

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Speaker 1: you when you listen to a song, you want the

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Speaker 1: next algorithmically generated song to be like not the same

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Speaker 1: artist or a song that you've heard before, but but

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Speaker 1: spiritually the same.

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Speaker 2: Like I know exactly what you mean.

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Speaker 1: It's hard to put into words, like I want it

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Speaker 1: to be like you're looking for something. It's it's very

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Speaker 1: hard to verbalize, but do you know what I mean?

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Speaker 4: Yeah, it's just weird, I think, especially with they keep

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Speaker 4: doing these these ones that are based on emotion and

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Speaker 4: it's like you can't have an AI pick out. I

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Speaker 4: have a screenshot on my phone of one that was

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Speaker 4: like happy mix, and the artists that they use in

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Speaker 4: the picture it's Midski and like, like I.

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Speaker 3: Listened to a lot of good Ski. That's not necessarily

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Speaker 3: my happy music.

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Speaker 5: I don't think many people would call up the happy music,

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Speaker 5: but like the algorithm was like, oh, this has like

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Speaker 5: an up tempo beat this song. I don't know what's

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Speaker 5: got I totally, I totally think you're right though. I

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Speaker 5: think it's a lot of the AI algorithm is sort

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Speaker 5: of stuff regardless of.

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Speaker 6: Because I you know what, I have a lot of

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Speaker 6: friends that make great playlists.

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Speaker 5: I think I make a pretty decent playlist. Like there's

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Speaker 5: there's clearly something something's some lot of.

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Speaker 3: Like TikTok music too.

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Speaker 2: Oh, I've noticed the same thing.

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Speaker 1: Something else I've really taken umbrage with on Spotify is

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Speaker 1: how bad their podcast player is.

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Speaker 2: Like I have Spotify Premium.

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Speaker 1: I have to say, it is where I listen to

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Speaker 1: my podcasts, but I am almost in like a toxic

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Speaker 1: relationship with Spotify's podcast player. You'll try to rewind it

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Speaker 1: thirty seconds and it's like, oh, did you want to

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Speaker 1: start playing a totally different podcast?

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Speaker 3: Oh, it's so weird.

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Speaker 4: Yeah, there's certain shows that they like showed the ads

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Speaker 4: are different, like how they Yeah, it's really annoying for

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Speaker 4: you know, for a company that is like meant not monopolized.

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Speaker 4: I guess a lot of people use Apple Music like

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Speaker 4: other platforms that really like taken over this market, like.

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Speaker 3: They don't operate well.

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Speaker 2: And I don't know.

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Speaker 4: I keep reading things too, and I think this might

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Speaker 4: lead into what you're going to talk about, But I

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Speaker 4: keep reading things too about like so much of our

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Speaker 4: music and media and stuff that used to have like

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Speaker 4: analog copies, like now people are collecting. Because I was like,

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Speaker 4: I can't even think of, like I don't even think

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Speaker 4: about the option of leaving Spotify because I'm like I

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Speaker 4: have all of my mus I've had Spotify since I

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Speaker 4: was like like in high school, Like I have like

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Speaker 4: all of my music there. I don't have hard copies

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Speaker 4: of those you know songs that I like. I don't

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Speaker 4: want to lose all of that.

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Speaker 1: Yeah, I have a love hate relationship with analog, So

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Speaker 1: I'm an analog person. Like because I am a woman

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Speaker 1: of a certain age, I was really into record collecting

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Speaker 1: like most like hip music people were in a certain era.

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Speaker 1: And let me tell you, I've had to I have,

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Speaker 1: So I have a massive record collection in my house.

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Speaker 1: I have had to schlep this collection to multiple apartments

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Speaker 1: when I move multiple cities. Had I and I started

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Speaker 1: collecting records before streaming was ever a thing, So I

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Speaker 1: never imagined that I would live in a world where

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Speaker 1: you could just get every single piece of music that

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Speaker 1: Devo ever put out at the touch of a fingertip.

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Speaker 1: So it's like, no, I need to have every vinyl

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Speaker 1: that they've ever made. That's the only way I'll ever

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Speaker 1: be able to hear it. And then you have to

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Speaker 1: shot them from like New York to San Francisco to

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Speaker 1: apartment to the apartment.

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Speaker 2: Like yeah, but that said.

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Speaker 1: Like, as media companies and streaming companies delete stuff, like

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Speaker 1: I've been hearing more and more about like, oh you

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Speaker 1: bought this game, well guess what, Like we could actually

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Speaker 1: just delete it. It kind of feels like in twenty

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Speaker 1: twenty four, like what does it mean to own something

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Speaker 1: digitally if you never really own it in a real

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Speaker 1: sense if the company that you bought it from can

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Speaker 1: just like take it away. And I don't know, part

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Speaker 1: of me, especially as Netflix and Hulu like raise their prices,

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Speaker 1: part of me is like, might have to dust off

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Speaker 1: that old DVD player because I have a lot of

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Speaker 1: those too, and that actually it does lead to my

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Speaker 1: big tech pet peeves that I have like just been.

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Speaker 2: Enraged by.

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Speaker 1: I was visiting my parents and my mom has got

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Speaker 1: a new car, so I was driving her car and

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Speaker 1: it's brand new, but it's super slick, and her car

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Speaker 1: barely has any buttons in it, like physical pressable, clunky

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Speaker 1: old school buttons. Everything is done on a touchscreen mounted

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Speaker 1: on the dashboard pretty much everything. So I'm like driving

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Speaker 1: and I'm trying to use my hand to you know,

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Speaker 1: turn up the volume, turn the song, or put on

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Speaker 1: the heat or whatever, and I'm feeling around expecting there

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Speaker 1: to be like a touchable button.

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Speaker 2: It's all on a touch screen.

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Speaker 1: I don't know if you've driven a car like this,

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Speaker 1: I'm sure there are people listening who are like, oh,

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Speaker 1: I prefer the touchscreen, but.

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Speaker 2: Whatever happened to a good old fashioned button?

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Speaker 1: Like what is this assumption that touch screens are automatically

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Speaker 1: better than a good old fashion clunky button that you press.

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Speaker 3: Oh yeah, no, I.

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Speaker 4: My mom also has a car with this sort of technology.

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Speaker 4: And it's the like Tesla effect where everybody's picking up

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Speaker 4: because I think Tesla was the first one to have

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Speaker 4: the like just iPad screen in there, and it's awful,

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Speaker 4: like driving, it is so annoying and like trying to

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Speaker 4: deal with the control.

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Speaker 3: Yeah no, I don't understand the appeal of it.

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Speaker 1: So we actually might not be alone in this. Because

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Speaker 1: this is from life Wire. The European New Car Assessment

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Speaker 1: Program or euro en CAP gives safety ratings for cars,

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Speaker 1: and next January, cars will not be able to get

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Speaker 1: a five out of five rating unless they use buttons,

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Speaker 1: stocks or dials for essential safety features. That's what I'm

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Speaker 1: talking about. I'm sure people listening are like, it's better on.

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Speaker 2: A touch screen.

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Speaker 1: No, it's not. Buttons were fine. What did buttons ever

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Speaker 1: do to anybody?

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Speaker 3: Exactly? It's the same with everything. It's the same with

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Speaker 3: like iPhones, Like as soon as they got rid of

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Speaker 3: the this is my back in, you.

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Speaker 7: Know, all the technology these days, but like I feel

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Speaker 7: like once they got rid of the home screen on

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Speaker 7: like iPhones or like the little home button home screen

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Speaker 7: button on iPhones, like that was it.

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Speaker 2: That was the end, That was the end of everything.

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Speaker 1: Everything went to shit, her whole her, whole culture. I

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Speaker 1: was just on the podcast also on Outspoken, Black Fat

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Speaker 1: and Fem and one of the questions they were they

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Speaker 1: asked was like, what's your what was your favorite piets technology?

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Speaker 1: And it sent me down this rabbit hole of how

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Speaker 1: much I loved BlackBerry. And part of it was that

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Speaker 1: it had the clickable button and this like clickable kind

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Speaker 1: of mouse stingy in the middle, like a circular button,

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Speaker 1: And I swear to you I would type messages on

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Speaker 1: my BlackBerry like I thought I was like working for

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Speaker 1: the Obama White House or something like.

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Speaker 2: I took it so seriously.

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Speaker 1: I thought I thought I was like, you know, sending

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Speaker 1: high pressure, high stakes emails.

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Speaker 2: Mine.

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Speaker 1: I was in my early twenties, so I definitely was

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Speaker 1: not sending anything of any import. But something about the

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Speaker 1: clickable button made me feel like I was really doing business.

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Speaker 3: Yeah, there was thing.

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Speaker 4: About blackberries too that I feel. I don't know at

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Speaker 4: least so I understand. I was a child when blackberries

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Speaker 4: were a thing, so I always associated it with like

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Speaker 4: it being my dad's like serious work phone that he

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Speaker 4: had to So I was like in my mind, like

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Speaker 4: blackberries are like this serious, like I am doing.

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Speaker 3: I am going to work.

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Speaker 4: You know what a child assumes an adults, Uh, you know,

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Speaker 4: job and careers like bridget.

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Speaker 3: Have you seen the BlackBerry movie?

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Speaker 2: But I sure have. I thought it.

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Speaker 1: I was lucky enough to get sent a screener. Thank

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Speaker 1: you whoever made that happen. But I wait, did you

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Speaker 1: see it?

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Speaker 3: I have not seen it.

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Speaker 4: I do love my god, I'm Glenn Howardton, though, so

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Speaker 4: I I gotta see it.

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Speaker 1: This is okay. So I love Glenn Howardton, I love

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Speaker 1: Always Sunny. I love their podcast. Or I listened to

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Speaker 1: it for a while. I couldn't fallen off on it.

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Speaker 1: But when I tell you that, like I believe he

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Speaker 1: could have been nominated for an Oscar for Best Actor

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Speaker 1: for his work in this movie, like the BlackBerry Movie?

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Speaker 2: Is his Citizen Kane like he is? He is?

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Speaker 6: He?

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Speaker 1: I didn't I guess there are I don't know if

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Speaker 1: you watch Always Sunny, But there are times in it

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Speaker 1: when his character Dennis has a real like white hot intensity,

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Speaker 1: and I think and I never really yeah, I never

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Speaker 1: really thought he I never really put that together like, oh,

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Speaker 1: this is like very good acting. He is like a

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Speaker 1: very good actor. You gotta see it. Please watch it

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Speaker 1: and tell me what you.

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Speaker 2: Think it is.

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Speaker 4: It's definitely on my list. Yeah, that was my I

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Speaker 4: feel like that's a great character for him. I would

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Speaker 4: love to see him play more like somebody. Actually, I think, God,

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Speaker 4: there's something some.

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Speaker 3: Tweeters something I saw right.

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Speaker 4: I am against the idea of these types of remakes,

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Speaker 4: by the way, just disclaim her, but somebody like they

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Speaker 4: might be making an American Psycho remake or something. And

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Speaker 4: somebody immediately posted like a picture of him as like

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Speaker 4: the oh this guest.

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Speaker 3: And I was like, that would be perfect, that would

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Speaker 3: be so funny.

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Speaker 4: That is the one actor I actually would go see

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Speaker 4: again another needless remake of a movie, but.

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Speaker 1: Oh my god, I would I would absolutely watch that.

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Speaker 1: I would absolutely watch that. Yes, cannot like ten out

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Speaker 1: of ten BlackBerry movie. Also, it really captures that time

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Speaker 1: very well, just the time of like you know when

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Speaker 1: iPhone came out and it was like that Steve Jobs

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Speaker 1: announcement up on the stage, you know, like just this

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Speaker 1: how we were all communicating that it really it really is.

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Speaker 1: It does a great send up of that era, and

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Speaker 1: I feel like this whole segment is kind of like

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Speaker 1: er kids these days technology, which leads us into our

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Speaker 1: first topic very well, which is an update on what

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Speaker 1: is happening in the fight to potentially ban TikTok.

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Speaker 2: Have you been following this?

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Speaker 4: I found out about this probably the same way a

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Speaker 4: lot of people did, which is that I opened TikTok

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Speaker 4: and there was a very alarming in pographic thing that

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Speaker 4: like immediately pops up being like save TikTok.

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Speaker 3: But yeah, that's that's about as far.

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Speaker 4: I'm not gonna lie. Honestly, I saw it and kind

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Speaker 4: of exited out of it and just kept scrolling.

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Speaker 3: I was not in the mood to think about reality

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Speaker 3: at that point.

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Speaker 1: But yes, you're like, I'm just trying to disassociate with

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Speaker 1: some tiktoks.

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Speaker 4: That was not why I opened TikTok was to find

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Speaker 4: out about the government collapsing.

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Speaker 3: I don't know whatever is happening.

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Speaker 1: So if you like Joey opened your TikTok app and

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Speaker 1: saw a big black and white banner that said stop

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Speaker 1: a TikTok shutdown. Congress is planning a total ban of TikTok.

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Speaker 1: Speak up now before your government strips one hundred and

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Speaker 1: seventy million amy Americans of their constitutional right to free expression.

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Speaker 1: This will damage millions of businesses, destroy the livelihoods of

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Speaker 1: countless creators across the country. And then I, artists and audience,

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Speaker 1: let Congress know what TikTok means to you. So here's

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Speaker 1: what's going on. A bill that would force TikTok's Chinese owner,

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Speaker 1: Byte Dance to sell passed a big vote today. The

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Speaker 1: House Energy and Commerce Committee voted unanimously to pass this bill,

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Speaker 1: meaning that TikTok is one step closer to essentially kind

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Speaker 1: of being banned of the United States. Now, to be clear,

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Speaker 1: this legislation would force Byte Dance to sell TikTok to

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Speaker 1: an American owner, But because of the complicated nature of that,

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Speaker 1: like who would they sell to, how would work? We

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Speaker 1: break all of this data in an episode with Abbey

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Speaker 1: Richards that will put in the show description.

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Speaker 2: Basically, people are calling it.

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Speaker 1: A ban even though it technically isn't because forcing TikTok

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Speaker 1: to sell to an American owner is like so complicated

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Speaker 1: that it may as well be a ban. This bill

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Speaker 1: in order to become a law would stove the past

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Speaker 1: the House and the Senate, and some senators have already

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Speaker 1: expressed opposition to it. So if you open your TikTok

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Speaker 1: app like Joey and got that big alert urging you

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Speaker 1: to call your congress person, that is why basically TikTok

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Speaker 1: is kind of going on the offensive here. And even

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Speaker 1: though this is just one hurdle of several other hurdles

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Speaker 1: that would have to be satisfied for this to become

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Speaker 1: the law of the land, I think TikTok is.

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Speaker 2: Really feeling the heat.

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Speaker 1: I actually did not get one of these alerts my

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Speaker 1: open TikTok today.

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Speaker 2: I wonder if it's because they know that I'm in Washington,

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Speaker 2: d C.

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Speaker 1: And I don't have a voting member of Congress and

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Speaker 1: I can actually call on So if you don't live

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Speaker 1: in Washington, DC and you actually get to enjoy meaningful

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Speaker 1: congressional representation, well congratulations, call your congress person for me

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Speaker 1: and tell them that I like TikTok.

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Speaker 4: I imagine that having congressional representation. I do think I

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Speaker 4: gotta say, I do think it is a little bit

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Speaker 4: funny because and not to single out of TikTok. Obviously

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Speaker 4: this is like a universal issue, but TikTok has done

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Speaker 4: so much to repress activists within, you know, particularly recently,

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Speaker 4: it is a little bit funny to see them now

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Speaker 4: utilizing their platform to.

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Speaker 3: Be like, come on, call your congress people.

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Speaker 2: We love free expression. What are you talking about?

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Speaker 1: Yes, I mean, that's one of the things that is

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Speaker 1: so tough about this conversation is that I have a

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Speaker 1: lot of gripes with TikTok. I have a lot of

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Speaker 1: gripes about their moderation. I have a lot of gripes

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Speaker 1: about how content is promoted or not promoted, whether or

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Speaker 1: not certain topics are being suppressed. I'm not the only

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Speaker 1: person in hearings. Lawmakers have asked about this too, And

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Speaker 1: so I don't want to make it seem like I

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Speaker 1: am like yay TikTok. TikTok has no problems, but some

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Speaker 1: of the way that these lawmakers are framing TikTok I

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Speaker 1: really take issue with. And so it's an issue where

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Speaker 1: it's like it almost sounds like I am very pro TikTok,

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Speaker 1: even though I really like you, Joey, I know that

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Speaker 1: that TikTok has a lot of big problems, and I

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Speaker 1: have a lot of big concerns about how they're moderating

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Speaker 1: certain things and how they're some of their policies. And

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Speaker 1: I do have to say it does sound like this

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Speaker 1: push to get folks to call their Congress people is working.

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Speaker 1: One house GOP staff or told Politico quote, it's so

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Speaker 1: so bad. Our phones have not stopped ringing. They're teenagers

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Speaker 1: and old people saying they spend their whole day on

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Speaker 1: the app and we can't take it away. Here's Representative

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Speaker 1: Jamal Bauman from New York saying that banning TikTok would

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Speaker 1: silence the voices of younger Americans, particularly who are using

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Speaker 1: the app to organize for things like climate justice or

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Speaker 1: a full cease fire.

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Speaker 2: My colleagues are trying to ban TikTok, which is crazy.

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Speaker 8: They're doing it because of the oppression, because of your organizing,

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Speaker 8: It's because of your good worth. One million email sent

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Speaker 8: to ban the Wiggle Project, full million emails sent to

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Speaker 8: demand a sees via much more work to do as

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Speaker 8: we head into these and lectures and beyond. Again, they're

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Speaker 8: not trying to do anything to Facebook, even though China

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Speaker 8: gets most of this information from Facebook. They're going after

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Speaker 8: TikTok because they're going after young people.

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Speaker 1: Let's take a quick break.

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Speaker 2: At or back.

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Speaker 4: Yeah, yeah, I know, and like I mean to clarify

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Speaker 4: what I said before too, I think I think honestly

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Speaker 4: like for you know, obviously TikTok itself and I agree

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Speaker 4: with you like TikTok is it's not a lot of

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Speaker 4: messed up stuff, but at the same time, it is

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Speaker 4: this platform for particularly young people and uh, you know,

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Speaker 4: like he said in the video, I think, you know,

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Speaker 4: it's part of the preason TikTok that gets targeted out

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Speaker 4: these other platforms is because it isn't primarily younger audience.

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Speaker 3: And yeah, we've seen all these like movements.

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Speaker 4: You know, TikTok may not necessarily treat those movements well

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Speaker 4: and treat those you know kind of voice as well

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Speaker 4: on their app, but it is a platform for a

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Speaker 4: lot of these more progressive movements that I think, especially

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Speaker 4: like you know, this past year, and that is something

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Speaker 4: that there are people that have stakes in silencing that.

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Speaker 1: Yeah, I mean, I can't sort of turn off the

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Speaker 1: part of the conversation that does feel sort of like

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Speaker 1: handwringing about like what are the youth doing on their phones?

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Speaker 1: And like I am a huge proponent of you know,

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Speaker 1: safer digital experiences, particularly for young people.

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Speaker 2: But people are.

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Speaker 1: Describing the views and attitudes of young people in this

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Speaker 1: way that it's like, oh, well, it must be the

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Speaker 1: app that is making them feel this way. And it's

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Speaker 1: like it couldn't possibly be that young people are smart

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Speaker 1: and empathetic and they've looked at the facts.

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Speaker 2: I'm like, they have the point of view.

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Speaker 1: It's like it just seems it just seems very disingenuous

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Speaker 1: to make it seem like TikTok is the reason why

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Speaker 1: young people are you know, organizing for a full ceasefire

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Speaker 1: and things like that. Like it just it just feels

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Speaker 1: very belittling to their perspective and their point of view.

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Speaker 1: And I just I don't, I don't do you know,

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Speaker 1: do you know what I'm saying?

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Speaker 2: I don't know.

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Speaker 3: If I'm being clined, I totally agree.

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Speaker 4: I mean, I think it's a kind of like tale

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Speaker 4: as old at time, there's always you know, the latest

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Speaker 4: technology or like the latest thing. It's always you know this,

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Speaker 4: this thing is exposing our kids to this new idea.

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Speaker 3: It's never like hey, there's just this idea out there.

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Speaker 4: That is appealing to people because you know X, Y Z,

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Speaker 4: Like I don't know, but but again, yeah, like this

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Speaker 4: is the same thing with every kind of new technology,

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Speaker 4: every kind of new art form.

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Speaker 3: Not to say that.

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Speaker 4: TikTok is necessarily an art form, but I don't know,

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Speaker 4: like a new kind of platform or of like communication.

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Speaker 4: This is kind of the conversation that has had over

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Speaker 4: and over and over again, and like A, there's that

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Speaker 4: and then B I think they're genuinely I mean, I

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Speaker 4: don't want to say I don't know what is up,

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Speaker 4: because I do think I know what is up, and

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Speaker 4: it is it is so weird, like with the calls

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Speaker 4: for ceaspire, I think with like previously, when like the

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Speaker 4: Black Lives Matter protests were kind of in a bull swing,

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Speaker 4: like every single time, there's sort of this idea of

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Speaker 4: like oh this, well, like my kid couldn't actually think that,

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Speaker 4: or like general public couldn't think this because it is

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Speaker 4: against what the status quo is or against what is

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Speaker 4: like the most convenient kind of point two, I don't

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Speaker 4: know like it is sort of part of the thing

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Speaker 4: that is like politically most convenient.

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Speaker 3: That kind of argument is connected to so many things.

442
00:21:49,440 --> 00:21:51,919
Speaker 4: I think that's where you get like what like Nancy

443
00:21:51,920 --> 00:21:55,960
Speaker 4: Pelosi tell like protesters to like go back to Russia

444
00:21:56,080 --> 00:21:59,159
Speaker 4: or whatever because they're like agents of the crumbling, like

445
00:21:59,160 --> 00:22:01,480
Speaker 4: it was some crud. We're talking about Palestide, which is

446
00:22:01,480 --> 00:22:04,479
Speaker 4: a totally different, Like I don't know, like if this

447
00:22:04,640 --> 00:22:07,960
Speaker 4: it's this idea that people in general can't think for themselves,

448
00:22:08,000 --> 00:22:12,119
Speaker 4: and especially young people and especially progressive young people, And

449
00:22:12,200 --> 00:22:14,920
Speaker 4: I think that is not surprising, and I don't think

450
00:22:14,960 --> 00:22:17,720
Speaker 4: it's gonna stop necessarily, but yeah, it is, like clearly

451
00:22:17,800 --> 00:22:19,760
Speaker 4: that's the root of the problem, not the fact that.

452
00:22:19,840 --> 00:22:23,000
Speaker 3: TikTok is like poisoning people's minds.

453
00:22:23,520 --> 00:22:24,840
Speaker 2: Yet it's so insulting.

454
00:22:25,600 --> 00:22:27,960
Speaker 1: We have talked about a TikTok ban on the show before,

455
00:22:28,000 --> 00:22:30,040
Speaker 1: and so I think folks probably know how I feel

456
00:22:30,040 --> 00:22:33,040
Speaker 1: about it. You know, just like any social media platform

457
00:22:33,080 --> 00:22:37,160
Speaker 1: in twenty twenty four, there are definitely valid concerns about TikTok.

458
00:22:38,000 --> 00:22:38,239
Speaker 3: You know.

459
00:22:38,600 --> 00:22:41,640
Speaker 1: Anybody who tells you that there are not security concerns

460
00:22:41,640 --> 00:22:44,560
Speaker 1: with TikTok just doesn't know the facts. There were reports

461
00:22:44,560 --> 00:22:48,280
Speaker 1: that TikTok accessed journalists' information in an attempt to identify

462
00:22:48,640 --> 00:22:52,480
Speaker 1: which employees were leaking information about the app. TikTok actually

463
00:22:52,520 --> 00:22:55,119
Speaker 1: admitted to doing this, according to an internal email, but

464
00:22:55,160 --> 00:22:59,920
Speaker 1: when asked about it directly, TikTok CEO responded that, oh, well,

465
00:23:00,080 --> 00:23:02,040
Speaker 1: spy is not the right way to describe that, which,

466
00:23:02,119 --> 00:23:05,520
Speaker 1: like it did sound like spying to me, so TikTok doesn't.

467
00:23:05,520 --> 00:23:06,560
Speaker 2: I don't want to make it seem like.

468
00:23:06,560 --> 00:23:10,200
Speaker 1: TikTok has like a squeaky clean record, because they do not. However,

469
00:23:10,480 --> 00:23:13,120
Speaker 1: this is not the kind of opposition that lawmakers are

470
00:23:13,320 --> 00:23:16,960
Speaker 1: levying against TikTok. They're saying that TikTok is a big

471
00:23:17,080 --> 00:23:20,520
Speaker 1: national security threat because it is a Chinese owned company

472
00:23:20,840 --> 00:23:24,200
Speaker 1: and the platform is being used to like steal American

473
00:23:24,280 --> 00:23:26,280
Speaker 1: data and feed it to the Chinese Communist Party.

474
00:23:26,440 --> 00:23:27,520
Speaker 2: So not only is.

475
00:23:27,480 --> 00:23:30,760
Speaker 1: There no smoking gun or no evidence of this being

476
00:23:30,800 --> 00:23:35,560
Speaker 1: the case, it's also just like a plainly xenophobic thing

477
00:23:35,640 --> 00:23:39,080
Speaker 1: to say, Like the way that lawmakers have spoken to

478
00:23:39,080 --> 00:23:41,359
Speaker 1: the head of TikTok makes it clear to me that

479
00:23:41,400 --> 00:23:45,159
Speaker 1: there is some obvious xenophobia going on, And so I

480
00:23:45,200 --> 00:23:48,800
Speaker 1: think that lawmakers have sense that people want them to

481
00:23:48,880 --> 00:23:51,959
Speaker 1: crack down on big tech, and I think that lawmakers

482
00:23:52,040 --> 00:23:54,600
Speaker 1: want to look tough on China always, right, and so

483
00:23:54,920 --> 00:23:58,000
Speaker 1: going after TikTok as this singular boogieyman is a way

484
00:23:58,040 --> 00:24:00,280
Speaker 1: for them to kill two birds with one stone and

485
00:24:00,359 --> 00:24:03,000
Speaker 1: really do that. I also think that the reality here

486
00:24:03,119 --> 00:24:06,320
Speaker 1: is that the United States wants to remain the sort

487
00:24:06,320 --> 00:24:08,920
Speaker 1: of major, big player when it comes to big tech.

488
00:24:09,200 --> 00:24:12,640
Speaker 1: They don't like the idea of other countries, you know,

489
00:24:13,040 --> 00:24:16,240
Speaker 1: becoming major players in the big tech landscape and the

490
00:24:16,240 --> 00:24:19,280
Speaker 1: social media landscape. They wanted to just be for you know,

491
00:24:19,720 --> 00:24:22,600
Speaker 1: your Mark Zuckerberg's and your Elon Musk's of the world

492
00:24:22,720 --> 00:24:25,119
Speaker 1: and not your shows these shoes of the world.

493
00:24:25,800 --> 00:24:27,439
Speaker 2: And I think that's what it really comes down to.

494
00:24:27,840 --> 00:24:28,600
Speaker 3: Yeah, definitely.

495
00:24:28,680 --> 00:24:31,480
Speaker 4: I mean they've been very transparent about the fact that

496
00:24:31,520 --> 00:24:33,280
Speaker 4: it is more to do with China than it has

497
00:24:33,320 --> 00:24:37,440
Speaker 4: to do with like protecting people's data or whatever, which

498
00:24:37,520 --> 00:24:40,119
Speaker 4: like I don't know, yeah, like Facebook's probably doing just

499
00:24:40,160 --> 00:24:44,080
Speaker 4: as much harm, if not more. And uh, I mean

500
00:24:44,119 --> 00:24:47,760
Speaker 4: that that clip of the like Senate hearing where they just.

501
00:24:47,760 --> 00:24:49,359
Speaker 3: Kept asking the guy if he was part of the

502
00:24:49,440 --> 00:24:50,440
Speaker 3: Chinese part.

503
00:24:50,320 --> 00:24:53,640
Speaker 1: Like what's their connection to China? Right, but really, what's

504
00:24:53,640 --> 00:24:54,560
Speaker 1: your connection to China?

505
00:24:54,720 --> 00:24:57,480
Speaker 2: Like it's so fucked up. The fact that people.

506
00:24:57,440 --> 00:25:02,040
Speaker 4: Like still think this is about genuine safety concerns and

507
00:25:02,080 --> 00:25:06,439
Speaker 4: not just yeah xenophobia. Like after that, I think just

508
00:25:06,520 --> 00:25:08,800
Speaker 4: kind of goes to show how messed up a lot

509
00:25:08,800 --> 00:25:11,080
Speaker 4: of this is. But yeah, again, like it is sort

510
00:25:11,119 --> 00:25:14,919
Speaker 4: of the double edge or the sort of two sided

511
00:25:14,920 --> 00:25:18,680
Speaker 4: issue of like this, there's still all these issues with

512
00:25:18,760 --> 00:25:21,240
Speaker 4: this platform. They've still done a lot of messed up stuff.

513
00:25:21,320 --> 00:25:25,040
Speaker 4: But also like, clearly this is not coming from a

514
00:25:25,080 --> 00:25:29,200
Speaker 4: good place or from a genuine concern for people's safety.

515
00:25:29,440 --> 00:25:32,320
Speaker 1: Because if, for we're coming from a genuine concern for

516
00:25:32,400 --> 00:25:35,000
Speaker 1: all of our data privacy, we would have some sort

517
00:25:35,040 --> 00:25:37,920
Speaker 1: of meaningful data privacy legislation, which we in the United

518
00:25:37,920 --> 00:25:41,320
Speaker 1: States do not. It does not begin an end with

519
00:25:41,440 --> 00:25:44,879
Speaker 1: banning TikTok. All of our data is essentially on sale

520
00:25:44,920 --> 00:25:48,840
Speaker 1: for whoever wants it, including China. Only a few weeks ago,

521
00:25:48,960 --> 00:25:52,119
Speaker 1: Biden signed an executive order that limited the sale of

522
00:25:52,680 --> 00:25:56,320
Speaker 1: some of our data in some ways to quote countries

523
00:25:56,359 --> 00:25:59,639
Speaker 1: of concern, including China. But as Wired points out, this

524
00:26:00,000 --> 00:26:03,320
Speaker 1: scative order only means that US data brokers need to

525
00:26:03,320 --> 00:26:09,240
Speaker 1: take some steps and some security requirements during transfer, many

526
00:26:09,280 --> 00:26:12,280
Speaker 1: of which were already required by law, and so like,

527
00:26:12,520 --> 00:26:15,000
Speaker 1: I have a hard time understanding why TikTok is this

528
00:26:15,160 --> 00:26:18,400
Speaker 1: massive threat of all of our data being given to China,

529
00:26:18,440 --> 00:26:21,560
Speaker 1: given that a foreign adversary like China would not even

530
00:26:21,640 --> 00:26:24,639
Speaker 1: need TikTok to get that data right now, you know,

531
00:26:24,720 --> 00:26:28,120
Speaker 1: as long as they follow certain specific guidelines, they can

532
00:26:28,160 --> 00:26:32,080
Speaker 1: totally legally buy that data from US based data brokers.

533
00:26:32,480 --> 00:26:35,200
Speaker 1: And so that to me is a huge problem. I

534
00:26:35,240 --> 00:26:37,280
Speaker 1: don't think that we should be making TikTok this big,

535
00:26:37,920 --> 00:26:42,080
Speaker 1: you know, boogeyman while not meaningfully addressing the actual root

536
00:26:42,280 --> 00:26:44,240
Speaker 1: cause of the issue, which is that we don't really

537
00:26:44,280 --> 00:26:47,479
Speaker 1: have the kind of data protections and privacy protections that

538
00:26:47,520 --> 00:26:50,600
Speaker 1: we need in this country. And so, just to sort

539
00:26:50,640 --> 00:26:53,040
Speaker 1: of wrap this up, I think it is still too

540
00:26:53,160 --> 00:26:55,879
Speaker 1: soon to say whether or not TikTok will actually be banned.

541
00:26:56,480 --> 00:27:01,040
Speaker 1: If I was a betting woman, I believe it could

542
00:27:01,080 --> 00:27:04,200
Speaker 1: be banned. Like like, I think it's more likely than not,

543
00:27:04,760 --> 00:27:08,040
Speaker 1: but that's just my opinion. But even still, this bill

544
00:27:08,160 --> 00:27:10,439
Speaker 1: still needs to pass both the House and the Senate

545
00:27:10,520 --> 00:27:13,160
Speaker 1: and be signed into law. By the President, in which case,

546
00:27:13,240 --> 00:27:15,480
Speaker 1: if it did become the law, Bite Dance will still

547
00:27:15,480 --> 00:27:17,440
Speaker 1: have six months to sell before any kind of band

548
00:27:17,440 --> 00:27:18,000
Speaker 1: ticks effect.

549
00:27:18,040 --> 00:27:19,119
Speaker 2: So we'll keep following this.

550
00:27:21,040 --> 00:27:25,280
Speaker 3: Yeah, yeah, yeah, I guess we'll find out.

551
00:27:25,359 --> 00:27:29,560
Speaker 4: I will say, I personally, I don't think it's gonna

552
00:27:29,600 --> 00:27:30,439
Speaker 4: end up being banned.

553
00:27:30,560 --> 00:27:31,760
Speaker 2: I think, ooh tell me more.

554
00:27:32,880 --> 00:27:34,440
Speaker 3: I just think.

555
00:27:36,119 --> 00:27:39,680
Speaker 4: I just think it's it's like ben in the kind

556
00:27:39,720 --> 00:27:42,880
Speaker 4: of culturals I guess too long, Like it's like if

557
00:27:42,880 --> 00:27:46,320
Speaker 4: this the first round of this happening, I was like, oh, yeah,

558
00:27:46,320 --> 00:27:48,199
Speaker 4: they're definitely gonna ban tich Talk. I feel like by

559
00:27:48,240 --> 00:27:50,840
Speaker 4: this point, by like twenty twenty four, I feel like

560
00:27:51,480 --> 00:27:52,480
Speaker 4: it's too far gone.

561
00:27:52,920 --> 00:27:54,280
Speaker 3: And also, like they said, you.

562
00:27:54,200 --> 00:27:57,480
Speaker 4: Know, there's all these like teenagers and older people too,

563
00:27:57,520 --> 00:28:00,439
Speaker 4: I guess like calling in and complaining about it.

564
00:28:00,480 --> 00:28:04,639
Speaker 3: I do think. I think at least if there is

565
00:28:04,680 --> 00:28:06,160
Speaker 3: a band, I don't think it's gonna last.

566
00:28:06,160 --> 00:28:08,720
Speaker 4: I think it'll it'll or there's gonna be some sort

567
00:28:08,720 --> 00:28:09,840
Speaker 4: of way of going around it.

568
00:28:09,960 --> 00:28:13,800
Speaker 1: But oh, for sure. That's something I really think about

569
00:28:13,840 --> 00:28:17,520
Speaker 1: a lot. Is like in like you could like there

570
00:28:17,520 --> 00:28:19,600
Speaker 1: are so many ways to get around this band. I

571
00:28:19,600 --> 00:28:21,760
Speaker 1: would also be really curious how it will be enforced,

572
00:28:22,000 --> 00:28:24,080
Speaker 1: and you know, it has to be said that I

573
00:28:24,160 --> 00:28:29,560
Speaker 1: do think TikTok has really been instrumental in traditionally marginalized

574
00:28:29,560 --> 00:28:32,640
Speaker 1: communities really being able to have a bigger voice. You know,

575
00:28:33,000 --> 00:28:35,760
Speaker 1: our communities have you know, don't unless you like know,

576
00:28:35,840 --> 00:28:37,640
Speaker 1: somebody on the mask tedd at the New York Times

577
00:28:37,680 --> 00:28:41,080
Speaker 1: or whatever. Sometimes it's hard for our communities to really

578
00:28:41,240 --> 00:28:44,720
Speaker 1: have access to the kind of media power that other

579
00:28:44,800 --> 00:28:47,400
Speaker 1: groups have. And so I do think that this is

580
00:28:47,680 --> 00:28:50,400
Speaker 1: if it is banned, I think that marginalized creators and

581
00:28:50,440 --> 00:28:55,280
Speaker 1: marginalized communities would really suffer the most because we don't

582
00:28:55,320 --> 00:28:57,680
Speaker 1: always have those avenues and those channels that are ready

583
00:28:57,680 --> 00:29:00,840
Speaker 1: built to get our voices and stories out there. There

584
00:29:00,880 --> 00:29:05,000
Speaker 1: are so many things pertaining to marginalized communities that I

585
00:29:05,080 --> 00:29:07,600
Speaker 1: personally would not have known about if not for TikTok,

586
00:29:07,640 --> 00:29:11,840
Speaker 1: and so I'm concerned that that as a platform for

587
00:29:11,960 --> 00:29:16,000
Speaker 1: me staying informed about what's happening in other traditionally marginalized

588
00:29:16,000 --> 00:29:19,600
Speaker 1: communities other than my own. I'm concerned for what the

589
00:29:19,640 --> 00:29:22,440
Speaker 1: banning of that app means for me being able to

590
00:29:22,480 --> 00:29:23,760
Speaker 1: stay informed with what's going on.

591
00:29:24,480 --> 00:29:27,280
Speaker 4: Definitely, yeah, I totally agree, And I mean, I feel

592
00:29:27,320 --> 00:29:29,440
Speaker 4: like part of the reason why right now this is

593
00:29:29,480 --> 00:29:32,560
Speaker 4: so concerning is just the fact that it's like Twitter's

594
00:29:32,560 --> 00:29:34,880
Speaker 4: gone to shit too, Like there's not necessarily like I

595
00:29:34,880 --> 00:29:37,520
Speaker 4: feel like TikTok was kind of where I turned when

596
00:29:38,000 --> 00:29:40,440
Speaker 4: Twitter stopped being like functional.

597
00:29:40,720 --> 00:29:43,400
Speaker 3: So I don't know, I don't know what's gonna where

598
00:29:43,400 --> 00:29:44,440
Speaker 3: people are gonna go next.

599
00:29:45,360 --> 00:29:48,840
Speaker 1: Yeah, I feel the exact same, speaking of Twitter being

600
00:29:48,960 --> 00:29:52,360
Speaker 1: kind of a garbage factory, Well, this week over on Twitter,

601
00:29:52,640 --> 00:29:55,040
Speaker 1: they rolled out video and voice calls.

602
00:29:55,520 --> 00:29:57,280
Speaker 2: Y'all might recall that Elon Musk.

603
00:29:57,200 --> 00:29:59,920
Speaker 1: Really wants Twitter to be like an everything app where

604
00:30:00,040 --> 00:30:03,520
Speaker 1: you do your banking, your phone calls, your emails, all

605
00:30:03,560 --> 00:30:05,800
Speaker 1: the things that you already do online now. But I

606
00:30:05,800 --> 00:30:08,400
Speaker 1: guess like you can do all of those things over

607
00:30:08,480 --> 00:30:10,960
Speaker 1: on Twitter, but I guess at great security risk to

608
00:30:11,000 --> 00:30:12,280
Speaker 1: yourselves and also shitty.

609
00:30:12,440 --> 00:30:14,120
Speaker 2: I guess that's how he's envisioning it.

610
00:30:14,680 --> 00:30:18,680
Speaker 4: Yeah, you never want him to like access your bank account,

611
00:30:18,880 --> 00:30:22,720
Speaker 4: but in a less secure and more annoying way.

612
00:30:23,160 --> 00:30:23,800
Speaker 3: Appreciate it.

613
00:30:25,280 --> 00:30:30,680
Speaker 1: I mean, like, finally a solution to this problem. So,

614
00:30:30,920 --> 00:30:33,640
Speaker 1: because we're talking about Elon Musk, here the rollout of

615
00:30:33,680 --> 00:30:36,920
Speaker 1: these video and voice calls has not been good and

616
00:30:37,120 --> 00:30:38,760
Speaker 1: it's been rolled out to everyone.

617
00:30:38,880 --> 00:30:39,520
Speaker 2: By default.

618
00:30:39,800 --> 00:30:42,400
Speaker 1: You do not get the option of opting in if

619
00:30:42,440 --> 00:30:44,640
Speaker 1: you had the Twitter app on your phone. I don't

620
00:30:44,640 --> 00:30:46,880
Speaker 1: think it's on the browser yet, but you have it.

621
00:30:47,240 --> 00:30:49,800
Speaker 1: So here's what you need to know about this rollout.

622
00:30:50,080 --> 00:30:54,040
Speaker 1: First of all, Twitter's new video and voice calls leaks

623
00:30:54,040 --> 00:30:56,400
Speaker 1: your IP address to anybody that you talk with, and

624
00:30:56,440 --> 00:30:58,880
Speaker 1: it's really complicated to limit who you can talk to.

625
00:30:59,320 --> 00:31:02,160
Speaker 1: Tech Crunch has a really good explainer which we'll link

626
00:31:02,200 --> 00:31:04,120
Speaker 1: to in the show notes, where they say that a

627
00:31:04,120 --> 00:31:08,760
Speaker 1: person's IP addressed is not like hugely sensitive necessarily, but

628
00:31:09,560 --> 00:31:12,640
Speaker 1: these online identifiers can be used to infer location and

629
00:31:12,680 --> 00:31:15,600
Speaker 1: can be linked to a person's online activity, which can

630
00:31:15,640 --> 00:31:18,520
Speaker 1: be dangerous for high risk users. So if you're an activist,

631
00:31:18,840 --> 00:31:21,160
Speaker 1: if you're a public figure, if you're a dissident, if

632
00:31:21,160 --> 00:31:26,080
Speaker 1: you're somebody who you know is engaged in sensitive conversations

633
00:31:26,160 --> 00:31:29,479
Speaker 1: or sensitive work, that could be concerning for you. Another

634
00:31:29,560 --> 00:31:32,120
Speaker 1: thing to know about this is that Twitter does not

635
00:31:32,400 --> 00:31:35,720
Speaker 1: mention encryption in any of their official help center pages

636
00:31:35,760 --> 00:31:38,560
Speaker 1: at all, so their calls probably are not end to

637
00:31:38,680 --> 00:31:41,480
Speaker 1: end encrypted, which potentially allows Twitter to listen in on

638
00:31:41,560 --> 00:31:45,760
Speaker 1: conversations into end encrypted messaging apps such as Signal or WhatsApp.

639
00:31:46,040 --> 00:31:48,960
Speaker 1: Those prevent anybody other than the caller and the recipient

640
00:31:49,200 --> 00:31:53,360
Speaker 1: from listening in. And I do feel like, luckily we're

641
00:31:53,360 --> 00:31:55,760
Speaker 1: going to a place where that is like more of

642
00:31:55,800 --> 00:31:58,880
Speaker 1: the norm. And it's kind of interesting to me that

643
00:31:58,920 --> 00:32:03,800
Speaker 1: Twitter rolled this out without even referencing whether or not

644
00:32:03,880 --> 00:32:06,840
Speaker 1: calls are encrypted in any of their messaging. When tech

645
00:32:06,880 --> 00:32:11,040
Speaker 1: Crunch actually emailed Twitter to ask about this, like incredibly

646
00:32:11,240 --> 00:32:14,560
Speaker 1: basic privacy and security thing, they of course got the

647
00:32:14,640 --> 00:32:17,320
Speaker 1: standard Twitter reply, which is like, oh, we're busy now,

648
00:32:17,440 --> 00:32:21,160
Speaker 1: please check back later, which again to me, really speaks

649
00:32:21,200 --> 00:32:24,920
Speaker 1: to the carelessness with which this was rolled out, you know,

650
00:32:25,280 --> 00:32:28,600
Speaker 1: giving it to everybody by default, you know, not having

651
00:32:28,640 --> 00:32:32,080
Speaker 1: people opt in or even like meaningfully telling them what's

652
00:32:32,160 --> 00:32:34,600
Speaker 1: going on, and then not being able to answer some

653
00:32:34,640 --> 00:32:37,840
Speaker 1: of these basic security questions to me is like a

654
00:32:37,880 --> 00:32:41,040
Speaker 1: big red flag. So my advice to everybody is, unless

655
00:32:41,080 --> 00:32:45,720
Speaker 1: you have some particular need to be doing calls over Twitter,

656
00:32:46,240 --> 00:32:47,360
Speaker 1: you should turn this off.

657
00:32:47,520 --> 00:32:48,760
Speaker 2: It's pretty easy to turn off.

658
00:32:48,760 --> 00:32:51,400
Speaker 1: We will drop the tech Crunch piece with pretty clear

659
00:32:51,480 --> 00:32:53,920
Speaker 1: instructions with images on how to do this.

660
00:32:53,960 --> 00:32:54,680
Speaker 2: In the show notes.

661
00:32:54,720 --> 00:32:58,080
Speaker 1: But unless you've got some real pressing need to have

662
00:32:58,120 --> 00:33:01,040
Speaker 1: elon musk, like listening to your sensitive phone call, I

663
00:33:01,360 --> 00:33:02,880
Speaker 1: suggest that everybody.

664
00:33:02,440 --> 00:33:20,880
Speaker 2: Turn this off. Let's take a quick break at our back.

665
00:33:24,680 --> 00:33:27,800
Speaker 1: So, speaking of online shenanigans, I have to talk about

666
00:33:27,800 --> 00:33:32,040
Speaker 1: this recent report from BBC breaking down a new ish

667
00:33:32,200 --> 00:33:34,680
Speaker 1: disinformation trend that we're seeing ahead of the twenty twenty

668
00:33:34,680 --> 00:33:39,520
Speaker 1: four US presidential election, which is fake AI generated images

669
00:33:39,920 --> 00:33:44,240
Speaker 1: of Trump with black people. So I've actually seen a

670
00:33:44,440 --> 00:33:47,120
Speaker 1: bunch of these in the wild. The one that sticks

671
00:33:47,120 --> 00:33:50,400
Speaker 1: in my mind is an image of Trump posing with

672
00:33:50,400 --> 00:33:53,360
Speaker 1: a bunch of young black men. This was shared un

673
00:33:53,480 --> 00:33:56,480
Speaker 1: ironically by somebody that I follow on Facebook or like

674
00:33:56,480 --> 00:33:59,000
Speaker 1: I'm friends with on Facebook, and so like was not

675
00:33:59,080 --> 00:34:00,959
Speaker 1: shared in a like, look how stupid this is kind

676
00:34:01,000 --> 00:34:03,560
Speaker 1: of way, shared in a like yay Trump, this is

677
00:34:03,600 --> 00:34:06,120
Speaker 1: great kind of way. And so the caption of this

678
00:34:06,200 --> 00:34:10,480
Speaker 1: fake image was like Trump's motorcade was driving around Baltimore

679
00:34:10,520 --> 00:34:13,760
Speaker 1: when these kids asked him to stop and take a picture.

680
00:34:14,280 --> 00:34:16,960
Speaker 1: And it was seen by one point three million people.

681
00:34:17,400 --> 00:34:20,040
Speaker 1: And it's one of those images where like, if you

682
00:34:20,160 --> 00:34:23,200
Speaker 1: thought about it for ten seconds, like think about it critically,

683
00:34:23,280 --> 00:34:26,920
Speaker 1: for ten seconds. If Trump's motorcade was driving through Baltimore

684
00:34:27,200 --> 00:34:31,880
Speaker 1: and a bunch of random kids on the street were like, Hey, Trump,

685
00:34:32,560 --> 00:34:35,080
Speaker 1: stop your motorcade and get out of a car and

686
00:34:35,080 --> 00:34:38,239
Speaker 1: take a picture with us. Do you think that would happen? Like,

687
00:34:38,280 --> 00:34:39,799
Speaker 1: it's just like it's one of those things where it's

688
00:34:39,800 --> 00:34:43,040
Speaker 1: like the image is compelling. I will give them that,

689
00:34:43,360 --> 00:34:45,640
Speaker 1: But if you just thought about it, you would realize

690
00:34:45,680 --> 00:34:47,040
Speaker 1: this is this doesn't make any sense.

691
00:34:47,040 --> 00:34:48,200
Speaker 2: It doesn't it doesn't hold water.

692
00:34:48,840 --> 00:34:53,480
Speaker 3: Yeah, I don't think.

693
00:34:54,120 --> 00:34:58,640
Speaker 4: Yeah, I would say I would not expect that to

694
00:34:58,680 --> 00:35:02,600
Speaker 4: be something that Trump would do realistically. I'm also like,

695
00:35:02,680 --> 00:35:05,480
Speaker 4: looking at this photo, I mean, it's the whole it's

696
00:35:05,520 --> 00:35:07,399
Speaker 4: the AI thing, where like I can I get how

697
00:35:07,400 --> 00:35:10,240
Speaker 4: people could like maybe mistake this for an actual image

698
00:35:10,280 --> 00:35:13,640
Speaker 4: at first, but they're so like allthough the people in

699
00:35:13,680 --> 00:35:16,920
Speaker 4: the picture look so like airbrushed, it's so weird.

700
00:35:17,400 --> 00:35:21,000
Speaker 1: Yes, their skin is like way too polished and smooth

701
00:35:21,040 --> 00:35:23,759
Speaker 1: and kind of kind of like shiny in that way

702
00:35:23,760 --> 00:35:26,680
Speaker 1: that just like your normal skin doesn't skin unless it's fake.

703
00:35:27,160 --> 00:35:27,560
Speaker 3: Yeah.

704
00:35:27,960 --> 00:35:31,239
Speaker 4: Yeah, one of these pictures, because I'm just seeing them

705
00:35:31,239 --> 00:35:33,959
Speaker 4: now for the first time, one of them genuinely does

706
00:35:34,320 --> 00:35:36,480
Speaker 4: like it actually is a little freaky, like it look

707
00:35:36,560 --> 00:35:38,040
Speaker 4: kind of looks like a real photo. And I think

708
00:35:38,040 --> 00:35:39,880
Speaker 4: if I was like scrolling on like Instagram and I

709
00:35:39,880 --> 00:35:41,560
Speaker 4: saw it, I would assume it was a real photo.

710
00:35:41,960 --> 00:35:47,360
Speaker 4: But like, yeah, no, it all of these photos like whenever,

711
00:35:47,560 --> 00:35:49,080
Speaker 4: like AI photos always.

712
00:35:48,719 --> 00:35:52,040
Speaker 3: Like have a weird kind of like inhuman quality to them.

713
00:35:52,640 --> 00:35:53,960
Speaker 2: Yeah, I mean they do.

714
00:35:54,280 --> 00:35:58,480
Speaker 1: Now it concerns me, like, like not even that long ago,

715
00:35:58,560 --> 00:36:00,399
Speaker 1: we were always like, oh, look at the hand, look

716
00:36:00,400 --> 00:36:03,240
Speaker 1: at the fingers, And now it's like it's it's figured

717
00:36:03,239 --> 00:36:04,840
Speaker 1: out how to do the hands on the fingers, and

718
00:36:04,880 --> 00:36:06,360
Speaker 1: now we have to look at other tells.

719
00:36:06,400 --> 00:36:08,000
Speaker 2: And so I'm with you.

720
00:36:08,080 --> 00:36:10,680
Speaker 1: I do think a lot of these pictures like I'm

721
00:36:10,680 --> 00:36:14,399
Speaker 1: not above this, like I have been taken by AI

722
00:36:14,560 --> 00:36:18,400
Speaker 1: pictures before, even as somebody who thinks about disinformation and

723
00:36:18,480 --> 00:36:23,880
Speaker 1: AI a lot, Like I think it was the.

724
00:36:22,200 --> 00:36:25,360
Speaker 2: Pope image the Pope. Yeah, that one got me.

725
00:36:25,560 --> 00:36:27,480
Speaker 1: But it was exactly like you said it was the

726
00:36:27,520 --> 00:36:31,319
Speaker 1: morning I was I had not I didn't have my

727
00:36:31,360 --> 00:36:34,080
Speaker 1: contact lenses in yet. I was just like drinking coffee

728
00:36:34,120 --> 00:36:37,879
Speaker 1: and scrolling social media on my iPad in the morning

729
00:36:37,880 --> 00:36:41,480
Speaker 1: while having breakfast, and like you, like of course, in

730
00:36:41,520 --> 00:36:44,319
Speaker 1: that instance, when you're just quickly scrolling and you're not

731
00:36:44,440 --> 00:36:48,560
Speaker 1: necessarily primed and poised to be having your critical thinking

732
00:36:48,600 --> 00:36:51,600
Speaker 1: hat on, you might see something quickly and be like, oh, okay, sure,

733
00:36:51,800 --> 00:36:55,720
Speaker 1: Like guess the Pope is wearing this Balenciaga puffer. Guess

734
00:36:55,880 --> 00:36:58,160
Speaker 1: Trump is hanging out in Baltimore with these kids on

735
00:36:58,160 --> 00:37:01,000
Speaker 1: the stoop, Like, guess it makes sense, and we should

736
00:37:01,040 --> 00:37:03,960
Speaker 1: have a media ecosystem where you don't have to have

737
00:37:04,000 --> 00:37:07,240
Speaker 1: your critical thinking cap on twenty four to seven whenever

738
00:37:07,239 --> 00:37:09,640
Speaker 1: you're on social media to determine what is true and

739
00:37:09,640 --> 00:37:11,719
Speaker 1: what is fake. Like it is wild to me that

740
00:37:11,800 --> 00:37:15,040
Speaker 1: we all have to be so on our toes all

741
00:37:15,080 --> 00:37:16,960
Speaker 1: the time, but I do think in this climate we

742
00:37:17,080 --> 00:37:17,840
Speaker 1: kind of do.

743
00:37:19,480 --> 00:37:23,600
Speaker 4: Yeah, definitely and yeah again, Like this this first photo, I.

744
00:37:25,200 --> 00:37:27,600
Speaker 3: That that if this one it's it's.

745
00:37:27,520 --> 00:37:30,359
Speaker 4: Just like with a group of like the women, yah,

746
00:37:30,760 --> 00:37:33,120
Speaker 4: the women, yeah, the one with the yeah, this first one,

747
00:37:33,280 --> 00:37:36,319
Speaker 4: that one's freaky that that I think that could trick

748
00:37:36,360 --> 00:37:39,480
Speaker 4: me like that you can still tell even with that one,

749
00:37:39,520 --> 00:37:41,279
Speaker 4: like the hands are a little bit miss messed up,

750
00:37:41,320 --> 00:37:43,320
Speaker 4: but the way they have it, like you can only

751
00:37:43,360 --> 00:37:46,359
Speaker 4: really see like two people's like one hand on two

752
00:37:46,400 --> 00:37:51,120
Speaker 4: different people. So so it's easier to kind of look

753
00:37:51,160 --> 00:37:52,680
Speaker 4: over I think it's easier to kind of.

754
00:37:52,640 --> 00:37:55,200
Speaker 3: Like not not really catch on.

755
00:37:56,239 --> 00:38:03,640
Speaker 4: Uh yeah, this is just a perpetual aid a nightmare.

756
00:38:04,320 --> 00:38:07,799
Speaker 1: But you know, so, as far as we know, these

757
00:38:07,840 --> 00:38:11,360
Speaker 1: images are not coming from anybody connected to Trump or

758
00:38:11,360 --> 00:38:14,640
Speaker 1: Trump's campaign, but the co founder of the organization Black

759
00:38:14,719 --> 00:38:17,080
Speaker 1: Voters Matter, which is a group that encourages black folks

760
00:38:17,080 --> 00:38:20,960
Speaker 1: to vote, says that the manipulated images were clearly pushing

761
00:38:21,040 --> 00:38:24,960
Speaker 1: a kind of strategic narrative designed to show Trump as

762
00:38:25,080 --> 00:38:27,560
Speaker 1: popular in the black community. And so we don't even

763
00:38:27,600 --> 00:38:31,040
Speaker 1: need to look to AI to see this everywhere, this

764
00:38:31,280 --> 00:38:36,480
Speaker 1: notion that black folks like Trump. I you know, try

765
00:38:36,560 --> 00:38:41,120
Speaker 1: to monitor what's happening in known disinformation spaces and in

766
00:38:41,360 --> 00:38:45,240
Speaker 1: far right extremist media. They say things they're so fucking racist,

767
00:38:45,239 --> 00:38:47,960
Speaker 1: but they say things like, oh, well, the Trump mugshot

768
00:38:48,080 --> 00:38:50,480
Speaker 1: means that black people are gonna love Trump, or like

769
00:38:50,680 --> 00:38:53,640
Speaker 1: the Trump sneakers, you know how black people love sneakers.

770
00:38:53,680 --> 00:38:56,520
Speaker 1: It's like it's the so like it's not just coming

771
00:38:56,560 --> 00:39:01,640
Speaker 1: from these AI visual disinformation pieces that message that black

772
00:39:01,680 --> 00:39:05,759
Speaker 1: people are excited about Trump. I'm seeing being pushed in

773
00:39:05,880 --> 00:39:08,360
Speaker 1: spaces that have nothing to do with AI, and it's

774
00:39:08,760 --> 00:39:09,960
Speaker 1: it's very telling to me.

775
00:39:10,400 --> 00:39:11,920
Speaker 2: And again, they're always so.

776
00:39:14,000 --> 00:39:17,600
Speaker 1: Offensive the way, like like the way that they are.

777
00:39:17,920 --> 00:39:19,400
Speaker 3: The sneakers one was crazy.

778
00:39:19,600 --> 00:39:23,960
Speaker 4: Yeah, the sneakers one was so like I was like, oh, okay, we're.

779
00:39:23,800 --> 00:39:24,719
Speaker 2: Doing that all right?

780
00:39:25,680 --> 00:39:30,239
Speaker 1: Yeah it is And so like what I guess, even

781
00:39:30,320 --> 00:39:35,239
Speaker 1: though you don't need AI to make this kind of offensive,

782
00:39:35,920 --> 00:39:40,120
Speaker 1: you know, digital fakeries, it is concerning. So the Washington

783
00:39:40,160 --> 00:39:43,160
Speaker 1: Posts Tech Vertical spoke to the person who made the

784
00:39:43,239 --> 00:39:45,479
Speaker 1: image that you're talking about that that you said looked

785
00:39:45,480 --> 00:39:49,040
Speaker 1: so real. He is Mark Ka, a host of a

786
00:39:49,040 --> 00:39:52,320
Speaker 1: conservative radio show in Florida, who said that he created

787
00:39:52,360 --> 00:39:55,279
Speaker 1: the image using the AI image tool mid Journey to

788
00:39:55,400 --> 00:39:59,840
Speaker 1: illustrate a November twenty nine post about Trump's alleged growing

789
00:40:00,000 --> 00:40:03,200
Speaker 1: support among black voters. He said that he knew that

790
00:40:03,239 --> 00:40:05,560
Speaker 1: posts that have an image tend to perform better on

791
00:40:05,560 --> 00:40:09,680
Speaker 1: social media platforms, so he just made this image on

792
00:40:09,800 --> 00:40:11,760
Speaker 1: mid Journey and he said it took him thirty seconds

793
00:40:11,800 --> 00:40:14,719
Speaker 1: to create, which is concerning that like, in less than

794
00:40:14,719 --> 00:40:18,400
Speaker 1: a minute somebody could make this like pretty convincing image.

795
00:40:18,680 --> 00:40:21,960
Speaker 1: The Washington Post also spoke to doctor Joan Donovan, who

796
00:40:22,080 --> 00:40:25,000
Speaker 1: made a really good point about that coverage of this

797
00:40:25,160 --> 00:40:28,080
Speaker 1: kind of thing is kind of tricky and can also

798
00:40:28,160 --> 00:40:30,960
Speaker 1: sort of feed into the problem because the people who

799
00:40:30,960 --> 00:40:33,919
Speaker 1: make these kinds of images want people to be talking

800
00:40:34,000 --> 00:40:36,880
Speaker 1: about them, right, and so the image itself might not

801
00:40:37,000 --> 00:40:39,799
Speaker 1: be newsworthy until it gets a kind of coverage that

802
00:40:39,880 --> 00:40:43,000
Speaker 1: makes it go viral. Doctor Donovan says, one of the

803
00:40:43,040 --> 00:40:45,239
Speaker 1: things we have to consider about campaigns like this is

804
00:40:45,280 --> 00:40:47,400
Speaker 1: how much they are stunting in terms of trying to

805
00:40:47,400 --> 00:40:51,120
Speaker 1: get media attention for something that otherwise would not merit headlines.

806
00:40:51,680 --> 00:40:55,960
Speaker 1: Some propagandists might recognize that it's possibly not newsworthy that

807
00:40:56,000 --> 00:40:59,360
Speaker 1: black people support Trump, but it is newsworthy that AI

808
00:40:59,480 --> 00:41:03,000
Speaker 1: generated photos of fake voters are circulating. And to doctor

809
00:41:03,000 --> 00:41:07,239
Speaker 1: Donovan's point, Marquaye actually said that his AI generated fake

810
00:41:07,320 --> 00:41:10,760
Speaker 1: Trump images did not go viral until they were covered

811
00:41:10,760 --> 00:41:14,120
Speaker 1: by BBC, and so you know, doctor Donovan might have

812
00:41:14,160 --> 00:41:14,719
Speaker 1: a point there.

813
00:41:14,880 --> 00:41:17,080
Speaker 2: So doctor Donovan went further and spoke to.

814
00:41:17,040 --> 00:41:21,600
Speaker 1: This idea that yes, like AI that gives people the

815
00:41:21,640 --> 00:41:26,440
Speaker 1: ability to quickly and effectively make this kind of visual

816
00:41:26,440 --> 00:41:30,920
Speaker 1: disinformation is really scary and like bad but cheap fakes

817
00:41:30,960 --> 00:41:34,440
Speaker 1: and other kinds of medium manipulation also exists, and it's

818
00:41:34,440 --> 00:41:37,520
Speaker 1: also a big concern because you know, whereas these Trump

819
00:41:37,560 --> 00:41:41,799
Speaker 1: deep fakes now have labels on Facebook and Instagram that

820
00:41:41,960 --> 00:41:45,040
Speaker 1: say they are not real, cheap fakes and other kind

821
00:41:45,040 --> 00:41:48,960
Speaker 1: of low budget media manipulation might not trigger that the

822
00:41:49,080 --> 00:41:51,600
Speaker 1: same kind of misinformation detectors in the same way and

823
00:41:51,680 --> 00:41:53,280
Speaker 1: can potentially spread further.

824
00:41:54,160 --> 00:41:58,239
Speaker 4: Yeah, definitely, And yeah, like like something that Trump has

825
00:41:58,320 --> 00:42:02,600
Speaker 4: been very good at, like you know, monopolized. They're taking

826
00:42:02,680 --> 00:42:07,160
Speaker 4: advantage of media coverage and media coverage of like you know,

827
00:42:07,360 --> 00:42:09,400
Speaker 4: outrageous or sort of out their behavior.

828
00:42:10,440 --> 00:42:11,879
Speaker 3: This kind of reminds me of like.

829
00:42:13,320 --> 00:42:17,280
Speaker 4: Early on, I think this was more the twenty sixteen election,

830
00:42:17,400 --> 00:42:19,720
Speaker 4: but I look the twenty twenty election too, Like whenever

831
00:42:19,760 --> 00:42:22,600
Speaker 4: there would be like some sort of group of like

832
00:42:23,040 --> 00:42:24,239
Speaker 4: marginalized people that.

833
00:42:24,239 --> 00:42:26,560
Speaker 3: Supported Like I remember there was a big like kind of.

834
00:42:27,040 --> 00:42:29,960
Speaker 4: Article about this like gaze per Trump like thing, and

835
00:42:30,040 --> 00:42:30,399
Speaker 4: it was.

836
00:42:30,400 --> 00:42:33,520
Speaker 3: Like, Okay, it doesn't even like it's probably like.

837
00:42:33,600 --> 00:42:36,960
Speaker 4: A a tiny group, and then b it's like the

838
00:42:37,000 --> 00:42:39,600
Speaker 4: whole like sort of like shock value. It is like, Wow,

839
00:42:39,680 --> 00:42:42,719
Speaker 4: this marginalized group that like the Republican Party kind of

840
00:42:42,719 --> 00:42:46,960
Speaker 4: hates uh is supporting like their super right wing candidate.

841
00:42:48,320 --> 00:42:52,480
Speaker 4: But yeah, like again, that's not necessarily newsworthy. It's sort

842
00:42:52,480 --> 00:42:55,440
Speaker 4: of not showing to scale the actual kind of impact

843
00:42:55,600 --> 00:42:57,719
Speaker 4: of these there or not showing to scale like the

844
00:42:57,760 --> 00:43:02,640
Speaker 4: actual support or numbers or whatever what that means. What

845
00:43:02,680 --> 00:43:07,359
Speaker 4: that argument is, there's probably what there's people of you know,

846
00:43:08,239 --> 00:43:12,399
Speaker 4: whatever marginalized group that support Trump or the Republicans for

847
00:43:12,440 --> 00:43:16,640
Speaker 4: like whatever reason, God and of itself is not necessarily newsworthy.

848
00:43:16,680 --> 00:43:18,600
Speaker 3: But what it does is it kind of like distorts

849
00:43:20,440 --> 00:43:22,560
Speaker 3: distorts like the wider story and.

850
00:43:23,880 --> 00:43:29,680
Speaker 4: Yeah, it's it's it's just weird. It's like, yeah, once

851
00:43:31,160 --> 00:43:34,840
Speaker 4: everything about this election is just gonna be so insane.

852
00:43:34,880 --> 00:43:35,799
Speaker 3: It already has been.

853
00:43:36,040 --> 00:43:37,480
Speaker 2: But yeah, yeah, I.

854
00:43:37,440 --> 00:43:40,000
Speaker 1: Think you make a really good point that I think

855
00:43:40,000 --> 00:43:43,560
Speaker 1: that's what doctor Donovan is saying, is that, you know,

856
00:43:44,440 --> 00:43:46,360
Speaker 1: we really need to be thinking a little deeper about

857
00:43:46,360 --> 00:43:48,960
Speaker 1: these stories and what makes them do is worthy Because

858
00:43:49,440 --> 00:43:53,200
Speaker 1: a group of gay people loudly advocating like a small

859
00:43:53,200 --> 00:43:58,359
Speaker 1: group of gay folks advocating their support for Trump, it's

860
00:43:58,360 --> 00:44:02,280
Speaker 1: not like there's a deeper story about well, has Trump

861
00:44:02,440 --> 00:44:05,680
Speaker 1: actually you know, been good for this community, and what

862
00:44:05,960 --> 00:44:08,400
Speaker 1: are the actual numbers of folks who support Trump? Like

863
00:44:09,080 --> 00:44:12,560
Speaker 1: I do, I do wonder if it it like makes

864
00:44:12,600 --> 00:44:16,719
Speaker 1: it tempting to turn what otherwise would just be like

865
00:44:16,800 --> 00:44:20,440
Speaker 1: maybe a small stunt or something into a larger pattern.

866
00:44:20,560 --> 00:44:25,680
Speaker 3: You know. It definitely, like yeah, it definitely.

867
00:44:25,760 --> 00:44:27,960
Speaker 4: It feels like the issue is mainly just that, like

868
00:44:28,040 --> 00:44:32,120
Speaker 4: it's sort of changing what the actual meaning of Like

869
00:44:32,200 --> 00:44:35,760
Speaker 4: it changes changing what the story is. It's implying something

870
00:44:37,320 --> 00:44:39,360
Speaker 4: about the way a certain group of people votes. I

871
00:44:39,360 --> 00:44:42,600
Speaker 4: feel like the whole kind of way of like tracking

872
00:44:42,719 --> 00:44:46,360
Speaker 4: votes based on like you know, particular identities that people

873
00:44:46,400 --> 00:44:48,960
Speaker 4: have too, Like that already is so outdated and like

874
00:44:49,040 --> 00:44:51,640
Speaker 4: we've already seen the kind of nuances of that, and

875
00:44:51,719 --> 00:44:57,560
Speaker 4: like you know, yeah, there's different factors in people's lives

876
00:44:57,640 --> 00:45:00,480
Speaker 4: that make them vote certain ways or do certain things

877
00:45:00,560 --> 00:45:03,040
Speaker 4: or believe certain things and just kind of like groping

878
00:45:03,080 --> 00:45:03,839
Speaker 4: in it into like.

879
00:45:05,239 --> 00:45:05,759
Speaker 3: I don't know this.

880
00:45:05,880 --> 00:45:08,360
Speaker 4: Yeah, again, it feels like they're following for what the

881
00:45:08,840 --> 00:45:12,560
Speaker 4: this kind of campaign wants them to, like what message

882
00:45:12,560 --> 00:45:15,080
Speaker 4: they want them to circulate, which doesn't seem.

883
00:45:14,880 --> 00:45:19,360
Speaker 1: Good exactly, And that's exactly what Disinformation specialist Nina Jenklitz,

884
00:45:19,400 --> 00:45:23,160
Speaker 1: who was also on the podcast before, said that we

885
00:45:23,200 --> 00:45:27,160
Speaker 1: don't actually need to be totally terrified because we do

886
00:45:27,600 --> 00:45:31,240
Speaker 1: have common sense, and common sense is still a really

887
00:45:31,280 --> 00:45:33,920
Speaker 1: good deep fake detector. And Nina says, you know you

888
00:45:33,920 --> 00:45:36,400
Speaker 1: should when you see images like this, you should ask yourself, like,

889
00:45:37,160 --> 00:45:40,800
Speaker 1: is Trump actually a great friend to the African American community?

890
00:45:41,080 --> 00:45:42,640
Speaker 2: If something seems.

891
00:45:42,280 --> 00:45:44,960
Speaker 1: Off about it, it is probably a deep fake, right,

892
00:45:45,040 --> 00:45:49,120
Speaker 1: And so just really going back to our common sense

893
00:45:49,280 --> 00:45:52,160
Speaker 1: of well, what do I know about this person? Does

894
00:45:52,200 --> 00:45:56,040
Speaker 1: this seem like something that would actually be doing. I

895
00:45:56,040 --> 00:45:58,600
Speaker 1: also would go further and say Donald Trump is a

896
00:45:59,080 --> 00:46:03,160
Speaker 1: known germa phone, He's not usually photographed like like that.

897
00:46:03,280 --> 00:46:06,120
Speaker 1: And the one deep fake image he's like hugging these

898
00:46:06,120 --> 00:46:08,080
Speaker 1: two women, and it's like he's not someone who is

899
00:46:08,160 --> 00:46:11,360
Speaker 1: generally photographed being that touchy feely with people, let alone

900
00:46:11,480 --> 00:46:12,120
Speaker 1: black women.

901
00:46:12,360 --> 00:46:16,440
Speaker 2: So is that something that you would see right right? Right?

902
00:46:17,760 --> 00:46:22,040
Speaker 3: Known racist? Like this is not I literally I that

903
00:46:22,120 --> 00:46:23,319
Speaker 3: can like the twenty.

904
00:46:23,080 --> 00:46:25,160
Speaker 4: Six er I guess yeah, thought that would be twenty

905
00:46:25,200 --> 00:46:29,240
Speaker 4: six back in twenty sixteen, like because I was I'm

906
00:46:29,320 --> 00:46:32,160
Speaker 4: from Chicago originally, and there was like a rally that

907
00:46:32,239 --> 00:46:35,440
Speaker 4: he canceled in Chicago because he was afraid he was

908
00:46:35,480 --> 00:46:37,319
Speaker 4: going to be like get shot. Like it was because

909
00:46:37,360 --> 00:46:39,319
Speaker 4: of all of his stuff that he was like it

910
00:46:39,360 --> 00:46:42,200
Speaker 4: was insane, like this man and and I'm not saying,

911
00:46:42,200 --> 00:46:44,280
Speaker 4: I don't know who's to say what would have happened,

912
00:46:44,280 --> 00:46:45,600
Speaker 4: but it's like one of those things of like this

913
00:46:45,680 --> 00:46:49,439
Speaker 4: man is so like I don't think he is going

914
00:46:49,440 --> 00:46:54,840
Speaker 4: into predominantly black neighborhoods uh in Baltimore if like, I

915
00:46:55,360 --> 00:46:57,040
Speaker 4: just that just not seemed to be the kind of

916
00:46:57,080 --> 00:47:00,279
Speaker 4: thing that he uh would be putting himself. But that

917
00:47:00,400 --> 00:47:02,800
Speaker 4: situation because of certain beliefs that he has.

918
00:47:02,920 --> 00:47:06,560
Speaker 1: You know, you don't see Donald Trump stopping his motorcade

919
00:47:06,600 --> 00:47:09,200
Speaker 1: and chilling with the homies on the stoop in Baltimore.

920
00:47:09,239 --> 00:47:09,960
Speaker 2: You don't see it.

921
00:47:10,480 --> 00:47:13,440
Speaker 3: You know, anything could happen.

922
00:47:18,520 --> 00:47:34,600
Speaker 1: More after a quick break, let's get right back into it. Well,

923
00:47:34,880 --> 00:47:37,720
Speaker 1: speaking of AI, you know, we talk on this show

924
00:47:37,800 --> 00:47:42,759
Speaker 1: a lot about AI deep fakes, specifically non consensual deep

925
00:47:42,800 --> 00:47:46,239
Speaker 1: fake images, and it really does feel like every week

926
00:47:46,320 --> 00:47:48,640
Speaker 1: there's like a new school where it's happening, or a

927
00:47:48,640 --> 00:47:52,680
Speaker 1: new celebrity who is being targeted but now representative Alexandria

928
00:47:52,719 --> 00:47:57,000
Speaker 1: Okazio Cortez has a plan to stop it. AOC told

929
00:47:57,080 --> 00:47:59,240
Speaker 1: Rolling Stone that she's going to be leading the House

930
00:47:59,280 --> 00:48:04,239
Speaker 1: companion of the disrupt Explicit Forged Images and Non Consensual

931
00:48:04,400 --> 00:48:07,279
Speaker 1: Edits Act of twenty twenty four, also known as the

932
00:48:07,280 --> 00:48:10,200
Speaker 1: Defiance Act. It's a anacronym. That's why it's such a

933
00:48:10,200 --> 00:48:14,400
Speaker 1: mouthful to say. With a bipartisan group of representatives. So

934
00:48:14,520 --> 00:48:17,000
Speaker 1: this bill is her first move since being named to

935
00:48:17,000 --> 00:48:20,880
Speaker 1: the House of Representatives by partisan Task Force on AI. So,

936
00:48:20,920 --> 00:48:23,080
Speaker 1: how this legislation would work is that it amends the

937
00:48:23,160 --> 00:48:26,759
Speaker 1: current Violence Against Women Act so that people can sue

938
00:48:26,920 --> 00:48:31,319
Speaker 1: anybody who produces, distributes, or even receives deep fake, non

939
00:48:31,320 --> 00:48:36,120
Speaker 1: consensual pornographic images if they knew or recklessly disregarded that

940
00:48:36,200 --> 00:48:39,920
Speaker 1: the victim did not consent to those images. AOC says

941
00:48:39,960 --> 00:48:44,200
Speaker 1: that she developed the legislation working with survivors and survivors groups,

942
00:48:44,239 --> 00:48:48,319
Speaker 1: which to me is very important because oftentimes legislation that

943
00:48:48,360 --> 00:48:51,239
Speaker 1: doesn't really like center and listen to the people impacted

944
00:48:51,520 --> 00:48:54,480
Speaker 1: can end up having, you know, a different impact than

945
00:48:54,520 --> 00:48:57,120
Speaker 1: the intended impact, and like can just end up like

946
00:48:57,200 --> 00:48:59,920
Speaker 1: not making the lives of people who are targeted or

947
00:49:00,040 --> 00:49:04,600
Speaker 1: survivors better more than twenty five organizations have endorsed this

948
00:49:04,719 --> 00:49:08,520
Speaker 1: bipartisan legislation, including the National Women's Law Center, the Sexual

949
00:49:08,600 --> 00:49:12,640
Speaker 1: Violence Prevention Association, the National Domestic Violence Hotline, and Ultraviolet,

950
00:49:12,719 --> 00:49:15,680
Speaker 1: where I used to work. AOC said that she started

951
00:49:15,680 --> 00:49:20,080
Speaker 1: working on this legislation the week after those viral Taylor

952
00:49:20,120 --> 00:49:25,160
Speaker 1: Swift AI generated deep fakes happened on Twitter. So again,

953
00:49:25,400 --> 00:49:28,319
Speaker 1: for as much as we talk about the harm that

954
00:49:28,360 --> 00:49:34,839
Speaker 1: deep fakes represent for women, girls, BIPOC people, other marginalized

955
00:49:34,880 --> 00:49:38,120
Speaker 1: people who, according to the UN and just common sense

956
00:49:38,120 --> 00:49:41,600
Speaker 1: and life experience, are at a heightened risk for experiencing

957
00:49:41,640 --> 00:49:46,080
Speaker 1: technology facilitated gender based violence, and given the way that

958
00:49:46,120 --> 00:49:50,440
Speaker 1: we know technology like AI deep fakes is already disrupting

959
00:49:50,480 --> 00:49:55,000
Speaker 1: democracy amazingly, there are no federal laws criminalizing it.

960
00:49:55,040 --> 00:49:56,880
Speaker 2: Like every time I think about that, I just think.

961
00:49:56,719 --> 00:50:01,160
Speaker 1: About how wild it is that it's just like kind

962
00:50:01,239 --> 00:50:05,880
Speaker 1: of allowed, Like some states have taken steps, but federally nothing.

963
00:50:06,320 --> 00:50:09,920
Speaker 1: And so this legislation, if it goes through, would be

964
00:50:10,000 --> 00:50:13,200
Speaker 1: the first federal law taking any kind of action against

965
00:50:13,760 --> 00:50:16,560
Speaker 1: non consensual AI generated deep fakes.

966
00:50:16,880 --> 00:50:18,240
Speaker 3: Yeah, that really is crazy.

967
00:50:18,320 --> 00:50:20,839
Speaker 4: I mean I mean, like yeah, like this type of

968
00:50:21,680 --> 00:50:26,759
Speaker 4: deep fake, you know, is obviously kind of a new thing,

969
00:50:27,000 --> 00:50:29,200
Speaker 4: but like, I feel like this has kind of been

970
00:50:29,239 --> 00:50:31,120
Speaker 4: an issue for a while, and you would think at

971
00:50:31,200 --> 00:50:35,920
Speaker 4: least like there would be some sort of like libel thing.

972
00:50:35,880 --> 00:50:42,120
Speaker 3: You could like put it under somehow. But yeah, I mean,

973
00:50:44,600 --> 00:50:48,480
Speaker 3: like I've said before, I think swifties can change the world.

974
00:50:48,680 --> 00:50:51,680
Speaker 4: Once again, I'm a little skeptical about this chik Tawk

975
00:50:51,800 --> 00:50:57,640
Speaker 4: fan going through. I believe in the power of fangirls

976
00:50:57,920 --> 00:51:03,960
Speaker 4: and like teenagers that just a deep obsession and parasocial

977
00:51:04,000 --> 00:51:07,600
Speaker 4: relationship with Taylor Swift, amongst many other celebrities.

978
00:51:07,760 --> 00:51:10,000
Speaker 1: Have you ever read that book Everything I Need I

979
00:51:10,040 --> 00:51:12,600
Speaker 1: get from you How fangirls created the Internet as we

980
00:51:12,640 --> 00:51:12,960
Speaker 1: know it?

981
00:51:13,480 --> 00:51:15,120
Speaker 3: I am not, but like I should.

982
00:51:15,200 --> 00:51:19,680
Speaker 4: That sounds like that's totally up my alley, Caitlyn Tiffany,

983
00:51:19,880 --> 00:51:25,120
Speaker 4: Is it changed my whole basically, long story short, You're

984
00:51:25,200 --> 00:51:28,640
Speaker 4: right that fangirls created the Internet.

985
00:51:28,640 --> 00:51:31,560
Speaker 2: They control the Internet, they control everything.

986
00:51:33,000 --> 00:51:38,000
Speaker 4: Look, I mean, yeah, I got I've spent a lot

987
00:51:38,000 --> 00:51:43,880
Speaker 4: of my formative years on Tumblr and I do it

988
00:51:43,920 --> 00:51:46,600
Speaker 4: was this g I was listening to it like another show,

989
00:51:46,640 --> 00:51:49,880
Speaker 4: and they were talking about that that new movie that

990
00:51:49,920 --> 00:51:51,680
Speaker 4: is coming out that's like based on Harry Styles.

991
00:51:52,040 --> 00:51:54,520
Speaker 2: Oh yeah, I just watched the trailer for that a

992
00:51:54,560 --> 00:51:55,040
Speaker 2: moment ago.

993
00:51:55,400 --> 00:51:59,040
Speaker 6: Yeah, because it was so funny.

994
00:51:59,040 --> 00:52:01,120
Speaker 4: They were talking about this whole phenomenon of these like

995
00:52:01,160 --> 00:52:04,720
Speaker 4: fan fiction movies, fan fiction book to book to movie,

996
00:52:04,719 --> 00:52:06,319
Speaker 4: and I'm like, yeah, no, this has been like a

997
00:52:06,360 --> 00:52:09,920
Speaker 4: thing like this is I like, the fan fiction writers

998
00:52:09,920 --> 00:52:13,959
Speaker 4: are like a pillar of the online community and now

999
00:52:14,080 --> 00:52:17,200
Speaker 4: are making their way into the big screen as well,

1000
00:52:17,719 --> 00:52:21,520
Speaker 4: which is is an interesting phenomenon. But h yeah, I

1001
00:52:21,840 --> 00:52:23,879
Speaker 4: love that. I definitely will check that book out.

1002
00:52:24,080 --> 00:52:28,080
Speaker 1: Oh, speaking of the big screen, we have to talk

1003
00:52:28,200 --> 00:52:30,400
Speaker 1: about this lawsuit.

1004
00:52:30,000 --> 00:52:35,719
Speaker 2: The most recent like jaded, jilted white guy lawsuit.

1005
00:52:35,800 --> 00:52:38,000
Speaker 4: So you do that should be a new segment, like

1006
00:52:38,160 --> 00:52:40,600
Speaker 4: in addition to the thelon now.

1007
00:52:41,080 --> 00:52:42,120
Speaker 3: White guy law suit.

1008
00:52:42,120 --> 00:52:47,480
Speaker 1: Alert Like yes, er er white guy lawsuit, new new

1009
00:52:47,520 --> 00:52:52,439
Speaker 1: white guy lawsuit just drapped. Okay, we're adding that that's

1010
00:52:52,480 --> 00:52:53,440
Speaker 1: gonna be a new segment.

1011
00:52:53,760 --> 00:52:54,160
Speaker 3: Love it.

1012
00:52:54,719 --> 00:52:57,480
Speaker 1: Okay, So since the Supreme Court struck down the race

1013
00:52:57,600 --> 00:53:00,840
Speaker 1: portion of affirmative action, we've been covering all these different

1014
00:53:00,880 --> 00:53:03,120
Speaker 1: legal challenges. We're gonna have our new segment, so keep

1015
00:53:03,120 --> 00:53:05,080
Speaker 1: any it out for that. But all of these different

1016
00:53:05,120 --> 00:53:08,359
Speaker 1: legal challenges have been rolling in from white folks who

1017
00:53:08,360 --> 00:53:11,400
Speaker 1: were like salty, they didn't get something they wanted, and

1018
00:53:11,440 --> 00:53:13,360
Speaker 1: they're being like, oh, it's because a woman or a

1019
00:53:13,360 --> 00:53:17,400
Speaker 1: person of color unfairly took it, and that's racism against

1020
00:53:17,400 --> 00:53:21,200
Speaker 1: me as a white person. And so this newest lawsuit

1021
00:53:21,239 --> 00:53:24,040
Speaker 1: has been filed by a script coordinator on the show

1022
00:53:24,160 --> 00:53:28,720
Speaker 1: Seal Team named Brian Bennecker, who claims that quote, heterosexual

1023
00:53:28,840 --> 00:53:34,320
Speaker 1: white men need extra qualifications to be hired in Hollywood. Historically, yes, historically,

1024
00:53:34,600 --> 00:53:38,319
Speaker 1: you know how it's always been heterosexual white men who

1025
00:53:38,560 --> 00:53:41,600
Speaker 1: can't get a break in any industry, whether it's Hollywood,

1026
00:53:42,280 --> 00:53:45,160
Speaker 1: you know, especially Hollywood.

1027
00:53:45,160 --> 00:53:48,160
Speaker 2: It's like historically, historically, you know.

1028
00:53:48,120 --> 00:53:51,400
Speaker 1: How, like it was white men who like weren't allowed

1029
00:53:51,440 --> 00:53:53,600
Speaker 1: to be in movies, had to enter through the back

1030
00:53:53,640 --> 00:53:56,720
Speaker 1: interest of nightclubs when they were performing all of that historically,

1031
00:53:56,719 --> 00:54:01,040
Speaker 1: remember how that happened. Oh yeah, so let's let's pause

1032
00:54:01,080 --> 00:54:04,800
Speaker 1: and imagine that this reality where it was straight white

1033
00:54:04,800 --> 00:54:06,960
Speaker 1: men who needed to work like twice as hard to

1034
00:54:07,000 --> 00:54:11,360
Speaker 1: prove themselves and not everybody else in Hollywood. So basically

1035
00:54:11,440 --> 00:54:14,759
Speaker 1: he is being represented by America First Legal, which is

1036
00:54:14,760 --> 00:54:17,800
Speaker 1: the legal initiative of the former Trump White House advisor

1037
00:54:17,840 --> 00:54:21,719
Speaker 1: Stephen Miller. Stephen Miller of all of the like Trump administration.

1038
00:54:23,680 --> 00:54:26,760
Speaker 1: One of my favorite outlets, Wanket always uses the phrase

1039
00:54:26,880 --> 00:54:29,359
Speaker 1: chuckle fucks of all of them, like he's the one

1040
00:54:29,360 --> 00:54:32,880
Speaker 1: that sort of I found the most personally odious. But

1041
00:54:33,120 --> 00:54:36,600
Speaker 1: their thing is basically filing complaints with the Equal Employment

1042
00:54:36,600 --> 00:54:41,080
Speaker 1: Opportunity Commission against major companies including Starbucks, McDonald's, Morgan Stanley

1043
00:54:41,400 --> 00:54:45,680
Speaker 1: over their corporate diversity and hiring practices. I believe that

1044
00:54:45,800 --> 00:54:49,000
Speaker 1: CBS is the first entertainment company that they have targeted

1045
00:54:49,040 --> 00:54:53,120
Speaker 1: in this way, so his lawsuit is pretty ridiculous. Basically,

1046
00:54:53,360 --> 00:54:56,600
Speaker 1: he argues that CBS has diversity quotas and that he

1047
00:54:56,760 --> 00:54:59,120
Speaker 1: was promised like a writing job when one opened up

1048
00:54:59,120 --> 00:55:02,520
Speaker 1: on the show, that instead they hired a bunch of

1049
00:55:02,680 --> 00:55:07,520
Speaker 1: unqualified bimbos instead of him, a white man who deserved it.

1050
00:55:07,719 --> 00:55:11,080
Speaker 1: That's basically the gist of the lawsuit. He says that

1051
00:55:11,440 --> 00:55:15,800
Speaker 1: CBS's hiring practices have created a situation where heterosexual white

1052
00:55:15,840 --> 00:55:21,160
Speaker 1: men need extra qualifications, including military experience or previous writing credits,

1053
00:55:21,200 --> 00:55:23,839
Speaker 1: to be hired as staff writers compared to their non

1054
00:55:23,880 --> 00:55:26,880
Speaker 1: white LGBTQ or female peers.

1055
00:55:26,920 --> 00:55:33,200
Speaker 6: Extra qualifications as in previous credits, like writing experience, you know,

1056
00:55:34,239 --> 00:55:35,120
Speaker 6: a resume.

1057
00:55:36,239 --> 00:55:37,960
Speaker 3: I'm being discriminated against.

1058
00:55:38,040 --> 00:55:40,560
Speaker 4: Oh so I am so this Maybe this is just

1059
00:55:40,600 --> 00:55:43,120
Speaker 4: specifically I have a lot of friends that work in film.

1060
00:55:43,320 --> 00:55:44,759
Speaker 3: I have a.

1061
00:55:44,719 --> 00:55:49,360
Speaker 4: Background working in film, so maybe this is particularly like

1062
00:55:49,440 --> 00:55:50,719
Speaker 4: pissing me off because of that.

1063
00:55:50,880 --> 00:55:53,359
Speaker 3: But like go to.

1064
00:55:53,560 --> 00:55:58,600
Speaker 4: Any film set, it is so like a historically it

1065
00:55:58,680 --> 00:56:02,600
Speaker 4: is a deeply, deeply massogynistic, deeply raised this industry. And

1066
00:56:02,719 --> 00:56:05,160
Speaker 4: still it is like the majority of the people you're

1067
00:56:05,200 --> 00:56:07,719
Speaker 4: gonna see, they are gonna be why men, Like yes,

1068
00:56:08,280 --> 00:56:10,919
Speaker 4: oh my god, especially in the writer's room.

1069
00:56:11,840 --> 00:56:14,160
Speaker 1: Yeah, I mean it just sends to me like what

1070
00:56:14,200 --> 00:56:16,879
Speaker 1: he's really saying is like I want a system where

1071
00:56:16,920 --> 00:56:19,600
Speaker 1: being a white, straight male means I get stuff and

1072
00:56:19,600 --> 00:56:22,440
Speaker 1: that is never questioned. Like that's the system that I want,

1073
00:56:22,880 --> 00:56:25,319
Speaker 1: Like that's what That's what I think we should have.

1074
00:56:25,719 --> 00:56:28,640
Speaker 1: And just to be real for a second, like I

1075
00:56:28,680 --> 00:56:31,200
Speaker 1: almost didn't include this story in the roundup, but it's

1076
00:56:31,239 --> 00:56:33,360
Speaker 1: a little bit of a smoke screen because I really

1077
00:56:33,400 --> 00:56:37,320
Speaker 1: wanted to read some of these comments that Deadline published

1078
00:56:37,920 --> 00:56:40,920
Speaker 1: from women writers and writers of color about this, because

1079
00:56:40,960 --> 00:56:44,520
Speaker 1: they are hilarious. They're a plus gold. So Deadline did

1080
00:56:44,600 --> 00:56:48,080
Speaker 1: a roundup of people responding to this lawsuit. Here a

1081
00:56:48,160 --> 00:56:50,160
Speaker 1: couple of my favorites. So a lot of them point

1082
00:56:50,239 --> 00:56:53,400
Speaker 1: out that this person is a script coordinator and he

1083
00:56:53,520 --> 00:56:58,319
Speaker 1: is demanding that he bypassed like script supervisor and be

1084
00:56:58,440 --> 00:57:00,279
Speaker 1: made straight like just I want to go right to

1085
00:57:00,320 --> 00:57:02,759
Speaker 1: the top. I demand to be made a producer. This

1086
00:57:02,920 --> 00:57:06,399
Speaker 1: quote that mansuming CBS is also demanding they make him

1087
00:57:06,400 --> 00:57:09,640
Speaker 1: a producer. If that's not peak whiteness, I don't know

1088
00:57:09,680 --> 00:57:13,000
Speaker 1: what the fuck else is Lomo? Please somebody go find

1089
00:57:13,000 --> 00:57:15,520
Speaker 1: a writing sample of his that's from Kelly Terrell, which

1090
00:57:15,520 --> 00:57:16,480
Speaker 1: I thought was really funny.

1091
00:57:17,000 --> 00:57:19,800
Speaker 3: Wait, really quick, I've never heard somebody say Lomo before.

1092
00:57:20,760 --> 00:57:21,880
Speaker 2: Oh is it l m ao?

1093
00:57:22,120 --> 00:57:25,360
Speaker 5: I just say lbao, but maybe oh, I don't know.

1094
00:57:25,440 --> 00:57:28,600
Speaker 5: It was like, maybe that's a is that a millennial?

1095
00:57:28,720 --> 00:57:33,320
Speaker 1: Just wait, I'm realizing I have always said it in

1096
00:57:33,440 --> 00:57:38,320
Speaker 1: my head and I've never said it out loud, And

1097
00:57:38,360 --> 00:57:40,640
Speaker 1: now I'm wondering if that's like not a millennial thing,

1098
00:57:40,760 --> 00:57:43,200
Speaker 1: if it's just a Bridget Todd thing, that's just like

1099
00:57:43,360 --> 00:57:44,600
Speaker 1: how I've always said it.

1100
00:57:45,040 --> 00:57:46,120
Speaker 2: Wait, I'm gonna listen to this.

1101
00:57:46,720 --> 00:57:50,800
Speaker 1: I mean, I say, wait, here's Okay, So I found

1102
00:57:50,800 --> 00:57:53,320
Speaker 1: an ask a Reddit how do you pronounce lmao?

1103
00:57:53,760 --> 00:57:56,360
Speaker 2: Top comment? If you're one of those people who say.

1104
00:57:56,600 --> 00:58:00,440
Speaker 1: Lmao or l l out loud rather than laughing that

1105
00:58:00,560 --> 00:58:02,760
Speaker 1: I think it's pronounced, Please disown me.

1106
00:58:03,480 --> 00:58:06,080
Speaker 2: So we'll never know. We'll never know, you know what,

1107
00:58:07,320 --> 00:58:07,840
Speaker 2: Keep this in.

1108
00:58:08,120 --> 00:58:11,280
Speaker 1: I want this as a digital record of people get

1109
00:58:11,320 --> 00:58:11,800
Speaker 1: back to us.

1110
00:58:11,840 --> 00:58:13,920
Speaker 3: Do you say lamo? Do you say l m a O?

1111
00:58:14,760 --> 00:58:15,040
Speaker 3: Is it a?

1112
00:58:15,600 --> 00:58:16,560
Speaker 2: Do you say something else?

1113
00:58:17,280 --> 00:58:21,440
Speaker 3: Yeah? Do you say something else? God? I but yeah, no.

1114
00:58:21,560 --> 00:58:24,600
Speaker 4: I think that's what I'm gonna start telling people for Like,

1115
00:58:24,600 --> 00:58:26,920
Speaker 4: career advice now is if if you want to be

1116
00:58:27,120 --> 00:58:28,600
Speaker 4: if you want to get a producer gig, you just

1117
00:58:28,600 --> 00:58:30,000
Speaker 4: gotta sue a major.

1118
00:58:30,720 --> 00:58:32,840
Speaker 2: Just sue them and demand it.

1119
00:58:33,200 --> 00:58:33,720
Speaker 3: My heart.

1120
00:58:34,000 --> 00:58:38,400
Speaker 2: Uh yes, I hope you're listening.

1121
00:58:42,520 --> 00:58:46,880
Speaker 3: That truly? Yeah, that is that is That is peak whiteness.

1122
00:58:47,040 --> 00:58:48,560
Speaker 3: Uh as a as a white person.

1123
00:58:50,160 --> 00:58:54,240
Speaker 1: This is my favorite from Miles Warden that Seal Team

1124
00:58:54,360 --> 00:58:57,200
Speaker 1: lawsuit reads like a series of mad libs, which is

1125
00:58:57,200 --> 00:59:02,800
Speaker 1: ironic because he's mad at libs. Oh chuckling to myself

1126
00:59:02,840 --> 00:59:04,640
Speaker 1: about that one earlier today, it.

1127
00:59:04,720 --> 00:59:07,439
Speaker 3: Is seal teab Like, I've never heard of this show.

1128
00:59:07,560 --> 00:59:08,640
Speaker 2: I've never heard of it.

1129
00:59:08,720 --> 00:59:10,200
Speaker 1: I feel like it's the kind of show that like

1130
00:59:10,800 --> 00:59:13,560
Speaker 1: somebody's dad probably watches, Like it's like I think it's

1131
00:59:13,600 --> 00:59:17,919
Speaker 1: about like it's got David Bryannis.

1132
00:59:17,960 --> 00:59:20,360
Speaker 4: It seems like it has a very very dedicated like

1133
00:59:20,440 --> 00:59:24,040
Speaker 4: fandom on tumbler somewhere, and then everybody else who watches it, yeah,

1134
00:59:24,160 --> 00:59:25,120
Speaker 4: is like somebody's dad.

1135
00:59:25,320 --> 00:59:29,600
Speaker 1: It's like, oh, I'm sure this reminds me of like

1136
00:59:30,040 --> 00:59:32,800
Speaker 1: there are so many shows when I'm flipping channels, and

1137
00:59:32,840 --> 00:59:34,360
Speaker 1: part part of it is because I just came back

1138
00:59:34,360 --> 00:59:38,120
Speaker 1: from visiting my parents and like they're watching stuff I've

1139
00:59:38,240 --> 00:59:41,000
Speaker 1: never even heard of, Like we live in such different

1140
00:59:41,080 --> 00:59:46,160
Speaker 1: like television watching silos. I guess like my dad has

1141
00:59:46,160 --> 00:59:49,120
Speaker 1: gotten really into this show about a bodyguard. I think

1142
00:59:49,160 --> 00:59:52,120
Speaker 1: it might as be called Bodyguard and it's all about

1143
00:59:52,160 --> 00:59:55,080
Speaker 1: a guy who's a bodyguard. And it's like part of

1144
00:59:55,120 --> 00:59:57,600
Speaker 1: me is like are these real shows? Like where are

1145
00:59:57,640 --> 00:59:59,280
Speaker 1: you getting these are real?

1146
00:59:59,400 --> 01:00:01,680
Speaker 4: There's just like an endless list of I feel like

1147
01:00:01,720 --> 01:00:03,920
Speaker 4: there also is like that's what I would saying. I

1148
01:00:04,200 --> 01:00:06,400
Speaker 4: remember like I had a friend telling me about a

1149
01:00:06,440 --> 01:00:10,520
Speaker 4: show that was very very similar to this, but I yeah,

1150
01:00:10,520 --> 01:00:12,480
Speaker 4: I feel like there's just like an endless like list

1151
01:00:12,520 --> 01:00:16,600
Speaker 4: of like military, police, firefighter, whatever.

1152
01:00:17,400 --> 01:00:20,560
Speaker 1: Oh my god, it is sort of like one of

1153
01:00:20,560 --> 01:00:25,200
Speaker 1: those things where when did we decide that the main show,

1154
01:00:25,400 --> 01:00:28,760
Speaker 1: the main occupations for television shows is gonna be firefighter

1155
01:00:28,920 --> 01:00:34,200
Speaker 1: police maybe like doctor, nurse, like military person.

1156
01:00:35,280 --> 01:00:39,080
Speaker 3: There's too many police shows. Oh my god, they're way,

1157
01:00:39,160 --> 01:00:40,840
Speaker 3: way too many police shows.

1158
01:00:40,960 --> 01:00:41,800
Speaker 2: I'm telling you.

1159
01:00:41,840 --> 01:00:46,000
Speaker 1: Come spend a weekend at the Todds House in Richmond, Virginia,

1160
01:00:46,040 --> 01:00:48,920
Speaker 1: and you will, like it's all they watch, like the shield,

1161
01:00:49,120 --> 01:00:52,320
Speaker 1: that this, that, the blue line like It's like, I

1162
01:00:52,360 --> 01:00:53,040
Speaker 1: had no idea.

1163
01:00:53,080 --> 01:00:56,760
Speaker 2: My parents were so into this, into this like law

1164
01:00:56,880 --> 01:01:00,080
Speaker 2: enforcement universe. I had no ideas. Was like new information

1165
01:01:00,200 --> 01:01:00,400
Speaker 2: to me.

1166
01:01:00,800 --> 01:01:04,560
Speaker 1: So as hilarious as all of these these comments on

1167
01:01:04,600 --> 01:01:06,640
Speaker 1: this lawsuit are, there were two that I wanted to

1168
01:01:06,720 --> 01:01:09,320
Speaker 1: highlight that really made me think. One is from Britney

1169
01:01:09,400 --> 01:01:13,160
Speaker 1: Van Horn, who says, deeply embarrassing on the script coordinator's part,

1170
01:01:13,400 --> 01:01:17,600
Speaker 1: But everyone who uses diversity as a quote easy excuse

1171
01:01:17,680 --> 01:01:20,680
Speaker 1: for not hiring or promoting people are complicit here too.

1172
01:01:21,160 --> 01:01:24,040
Speaker 1: Diversity is way too often used as an excuse for

1173
01:01:24,120 --> 01:01:27,760
Speaker 1: not hiring or promoting someone you had no intention to hire.

1174
01:01:28,040 --> 01:01:30,480
Speaker 1: And that really rings true to me that you know,

1175
01:01:30,520 --> 01:01:34,160
Speaker 1: this person who issuing CBS was a script coordinator for

1176
01:01:34,200 --> 01:01:38,840
Speaker 1: like fifteen years, right, Like I can understand being annoyed

1177
01:01:39,120 --> 01:01:42,680
Speaker 1: at never being promoted after like fifteen years, never getting

1178
01:01:42,680 --> 01:01:46,120
Speaker 1: to be a producer. But and like if you're someone

1179
01:01:46,160 --> 01:01:49,400
Speaker 1: who was a manager of this person, being like, oh, well,

1180
01:01:49,720 --> 01:01:51,919
Speaker 1: they want a diverse writer's room, that's why you didn't

1181
01:01:51,920 --> 01:01:52,360
Speaker 1: get hired.

1182
01:01:52,560 --> 01:01:54,560
Speaker 2: I could totally see people saying.

1183
01:01:54,280 --> 01:01:56,960
Speaker 1: That as just an easy way to avoid having to

1184
01:01:57,000 --> 01:02:00,440
Speaker 1: have a conversation that's like, actually, your work isn't cutting it,

1185
01:02:00,480 --> 01:02:02,520
Speaker 1: you can't hack it. We're not gonna promote you for

1186
01:02:02,600 --> 01:02:06,160
Speaker 1: whatever reason. We're not interested in, you know, you having

1187
01:02:06,200 --> 01:02:08,920
Speaker 1: a bigger role in what we're doing here. Like I

1188
01:02:08,960 --> 01:02:12,000
Speaker 1: do think Britney's point is really interesting. And this one

1189
01:02:12,080 --> 01:02:15,800
Speaker 1: from Friend of the Show Ish Danny Fernandez. She used

1190
01:02:15,800 --> 01:02:17,440
Speaker 1: to have a podcast on iHeart. I don't know if

1191
01:02:17,480 --> 01:02:19,960
Speaker 1: she does anymore, but I friend in my head, I

1192
01:02:19,960 --> 01:02:21,640
Speaker 1: don't know if I don't know, she's never been on

1193
01:02:21,680 --> 01:02:25,200
Speaker 1: the show, But Danny call us, we love you, Danny tweeted.

1194
01:02:25,840 --> 01:02:29,640
Speaker 1: UCLA releases a diversity report every single year. Anyone can

1195
01:02:29,640 --> 01:02:33,440
Speaker 1: google it. White men are the majority of writers in Hollywood.

1196
01:02:33,640 --> 01:02:36,080
Speaker 1: They make up the majority of writers room. This is

1197
01:02:36,160 --> 01:02:39,320
Speaker 1: not an opinion. This is a fact. You lose jobs

1198
01:02:39,360 --> 01:02:42,960
Speaker 1: to each other, to other white people, and that I

1199
01:02:43,000 --> 01:02:46,400
Speaker 1: think is so key because Danny is right. The numbers,

1200
01:02:46,880 --> 01:02:50,800
Speaker 1: as you said, Joey, are super clear. That it is

1201
01:02:50,840 --> 01:02:54,280
Speaker 1: not white men who are underrepresented in the entertainment industry

1202
01:02:54,720 --> 01:02:57,160
Speaker 1: is just not It's just a fact. And so you

1203
01:02:57,200 --> 01:03:01,400
Speaker 1: cannot sue your way into a career. Nobody is owed

1204
01:03:01,480 --> 01:03:03,800
Speaker 1: a career in entertainment. And you know who knows this

1205
01:03:03,960 --> 01:03:08,040
Speaker 1: better than anyone. The black people and queer people and

1206
01:03:08,160 --> 01:03:11,320
Speaker 1: trans people and women and other people of color who

1207
01:03:11,360 --> 01:03:14,880
Speaker 1: are underrepresented in the field. The people who drop out

1208
01:03:14,920 --> 01:03:17,400
Speaker 1: after ten years because they're like, yeah, I'm never gonna

1209
01:03:17,440 --> 01:03:21,040
Speaker 1: move up. I have hit this ceiling of as high

1210
01:03:21,080 --> 01:03:23,360
Speaker 1: as I can go and so I'm leaving. That happens

1211
01:03:23,400 --> 01:03:26,240
Speaker 1: time and time again. And so being told that it

1212
01:03:26,320 --> 01:03:30,640
Speaker 1: is people of color and other marginalized people who dominate

1213
01:03:30,680 --> 01:03:33,680
Speaker 1: the industry, not only is it just like laughable, but

1214
01:03:33,720 --> 01:03:36,440
Speaker 1: it just like flies in the face of the cold

1215
01:03:36,480 --> 01:03:37,280
Speaker 1: hard facts.

1216
01:03:37,720 --> 01:03:41,120
Speaker 4: Absolutely, And I mean, I don't know what the deal

1217
01:03:41,240 --> 01:03:43,120
Speaker 4: is with this case, but like I'm willing to guess

1218
01:03:43,120 --> 01:03:44,919
Speaker 4: that most of the writers in the writer's room are

1219
01:03:44,920 --> 01:03:49,919
Speaker 4: probably also white men. And yeah, it is like there's

1220
01:03:49,960 --> 01:03:53,640
Speaker 4: so many different issues here. It is super super hard

1221
01:03:53,640 --> 01:03:55,720
Speaker 4: to work in the entertainment industry. It's super hard to

1222
01:03:55,720 --> 01:03:56,720
Speaker 4: work in the film industry.

1223
01:03:58,520 --> 01:03:58,720
Speaker 3: You know.

1224
01:04:00,120 --> 01:04:04,840
Speaker 4: I know that firsthand. I know that through friends experiences.

1225
01:04:05,280 --> 01:04:08,280
Speaker 4: I think this sort of phenomenon and again, yeah, like

1226
01:04:08,320 --> 01:04:10,600
Speaker 4: a lot of these these companies and these production houses

1227
01:04:10,600 --> 01:04:13,960
Speaker 4: that have a stake in or that it kind of

1228
01:04:14,000 --> 01:04:16,080
Speaker 4: and again, like to go to that point about like

1229
01:04:16,160 --> 01:04:19,280
Speaker 4: diversity being an easy kind of excuse quote unquote. The

1230
01:04:19,360 --> 01:04:22,400
Speaker 4: issue isn't the the you know, the people that are

1231
01:04:22,400 --> 01:04:25,200
Speaker 4: being hired for quote unquote diversity, if that is actually

1232
01:04:25,200 --> 01:04:26,840
Speaker 4: happening oftentimes it's not.

1233
01:04:28,040 --> 01:04:28,720
Speaker 3: The problem is.

1234
01:04:28,680 --> 01:04:31,160
Speaker 4: These studios that are like, look, I don't have to

1235
01:04:31,200 --> 01:04:33,360
Speaker 4: have yeah, again, like I don't even really have to

1236
01:04:33,360 --> 01:04:36,160
Speaker 4: be doing the work of trying to hire more people

1237
01:04:36,160 --> 01:04:38,880
Speaker 4: from diverse backgrounds or people that aren't just white men.

1238
01:04:39,240 --> 01:04:42,800
Speaker 3: I can just say that diversity is the.

1239
01:04:42,680 --> 01:04:44,920
Speaker 4: Issue, and then I get out of here without really

1240
01:04:44,960 --> 01:04:47,200
Speaker 4: like having to deal with all of the bigger issues

1241
01:04:47,240 --> 01:04:50,840
Speaker 4: with like Hollywood and how it operates and but yeah,

1242
01:04:50,880 --> 01:04:55,720
Speaker 4: it's it's yeah, nobody's owed a career these same people,

1243
01:04:56,080 --> 01:04:58,760
Speaker 4: like yeah, it is like again it's coming from these

1244
01:04:58,760 --> 01:05:02,120
Speaker 4: same people that are oftentimes very like pull yourself up

1245
01:05:02,120 --> 01:05:03,680
Speaker 4: by your bootstraps kind of thing.

1246
01:05:03,720 --> 01:05:04,520
Speaker 3: And it's like, yeah, I know.

1247
01:05:04,640 --> 01:05:06,760
Speaker 4: This is the dark side of all of this, is

1248
01:05:06,760 --> 01:05:08,520
Speaker 4: that a lot of times it doesn't really work out.

1249
01:05:10,520 --> 01:05:12,840
Speaker 4: And yeah, yeah again again, all of this to say,

1250
01:05:13,000 --> 01:05:15,680
Speaker 4: you go to the actual reality and the actual numbers,

1251
01:05:15,720 --> 01:05:20,720
Speaker 4: like white cispen are still the dominant force in Hollywood,

1252
01:05:20,960 --> 01:05:23,720
Speaker 4: like that that's a fact.

1253
01:05:24,200 --> 01:05:26,760
Speaker 1: Yes, As I was reading about this kind of to

1254
01:05:26,840 --> 01:05:28,840
Speaker 1: your point, do you remember how there was a time

1255
01:05:28,920 --> 01:05:31,760
Speaker 1: when folks like this would say things like facts don't

1256
01:05:31,800 --> 01:05:35,320
Speaker 1: care about your feelings unless that feeling is I would

1257
01:05:35,360 --> 01:05:36,200
Speaker 1: like a job please.

1258
01:05:37,160 --> 01:05:39,280
Speaker 2: I feel like I have been overlooked.

1259
01:05:39,400 --> 01:05:41,720
Speaker 3: Actually, facts don't care about your feelings.

1260
01:05:41,760 --> 01:05:43,760
Speaker 6: Like I'm saying it right, it's the same like all

1261
01:05:43,760 --> 01:05:47,640
Speaker 6: of these idiots Ben Shapiro and whatnot, the people that

1262
01:05:47,640 --> 01:05:50,480
Speaker 6: are like they're all failed screenwriters.

1263
01:05:50,600 --> 01:05:52,720
Speaker 4: Like it's these people that want to blame their personal

1264
01:05:52,760 --> 01:05:57,760
Speaker 4: failings on quote unquote diversity and like marginalized people. And

1265
01:05:57,800 --> 01:06:00,640
Speaker 4: then they turn around and they're like actually, you guys

1266
01:06:00,680 --> 01:06:04,080
Speaker 4: are the ones doing that. You're the ones being snowflakes

1267
01:06:04,160 --> 01:06:07,920
Speaker 4: and being like your feelings and not playing attention to facts.

1268
01:06:08,320 --> 01:06:10,080
Speaker 3: It's it's so weird.

1269
01:06:11,160 --> 01:06:15,960
Speaker 4: It's such a like victim complex that I don't know,

1270
01:06:16,200 --> 01:06:18,360
Speaker 4: Like I don't know what kind of how removed from

1271
01:06:18,400 --> 01:06:22,640
Speaker 4: reality slash just completely in your own head narcissists you

1272
01:06:22,640 --> 01:06:24,400
Speaker 4: have to be to kind of view the world that way.

1273
01:06:24,560 --> 01:06:28,320
Speaker 2: But here we are, here, we are. Well, good luck

1274
01:06:28,320 --> 01:06:32,360
Speaker 2: on your lawsuit. Yeah, I will say that when I

1275
01:06:32,400 --> 01:06:32,960
Speaker 2: found out.

1276
01:06:32,840 --> 01:06:35,800
Speaker 1: That Ben Shapiro got his start as a screenwriter and

1277
01:06:35,840 --> 01:06:39,000
Speaker 1: it didn't work out, so much click into place for me.

1278
01:06:39,040 --> 01:06:42,240
Speaker 4: It was like, oh, he's just mad that people didn't

1279
01:06:42,320 --> 01:06:44,919
Speaker 4: like his stuff. Like so many of these people are

1280
01:06:45,000 --> 01:06:47,840
Speaker 4: just mad that people don't think they're funny or interesting

1281
01:06:48,000 --> 01:06:51,240
Speaker 4: or what. Elon Musk didn't try to be a screenwrinner,

1282
01:06:51,280 --> 01:06:53,480
Speaker 4: but so much screenwriter, but so much of his like

1283
01:06:53,800 --> 01:06:56,040
Speaker 4: thing is just that he is. He is so mad

1284
01:06:56,040 --> 01:06:58,880
Speaker 4: that people don't find him funny. I all of Yeah,

1285
01:06:59,080 --> 01:07:02,080
Speaker 4: I don't know. There, I think we just need to

1286
01:07:02,360 --> 01:07:06,160
Speaker 4: full on like like no more white men making entertainment

1287
01:07:06,400 --> 01:07:08,880
Speaker 4: period for like a couple of years.

1288
01:07:10,520 --> 01:07:12,920
Speaker 3: Like actually, obviously think we should do that.

1289
01:07:13,040 --> 01:07:15,000
Speaker 4: I know that's what they think is going on already,

1290
01:07:15,040 --> 01:07:16,920
Speaker 4: but I think we actually need to do that, like

1291
01:07:16,920 --> 01:07:17,840
Speaker 4: we need to reset.

1292
01:07:18,200 --> 01:07:21,680
Speaker 1: Oh my god, imagine if it really happened, like you

1293
01:07:21,720 --> 01:07:23,520
Speaker 1: want to. You want to talk about like this guy

1294
01:07:23,560 --> 01:07:27,040
Speaker 1: being a cry baby. Now, imagine if what he what

1295
01:07:27,080 --> 01:07:29,480
Speaker 1: he is laying out is happening.

1296
01:07:29,680 --> 01:07:31,160
Speaker 2: Imagine if that happened for real.

1297
01:07:31,400 --> 01:07:36,200
Speaker 1: Just just just marinate on that for a moment, Listeners, the.

1298
01:07:36,120 --> 01:07:39,959
Speaker 4: Most insufferable man you know has lost his hobby, and

1299
01:07:40,240 --> 01:07:40,520
Speaker 4: you know.

1300
01:07:42,320 --> 01:07:43,960
Speaker 3: I have had to deal with a lot of men

1301
01:07:44,000 --> 01:07:46,080
Speaker 3: in film. It is terrible.

1302
01:07:48,120 --> 01:07:50,920
Speaker 2: Oh my god. We need to do a whole like.

1303
01:07:51,520 --> 01:07:53,600
Speaker 3: Just dish out all I want to.

1304
01:07:54,000 --> 01:07:54,360
Speaker 2: I want to.

1305
01:07:54,560 --> 01:07:56,760
Speaker 1: I want to hear it. You can, we can anonymize it,

1306
01:07:56,800 --> 01:07:58,400
Speaker 1: but I want to hear it. I'm sure I can

1307
01:07:58,480 --> 01:08:03,320
Speaker 1: only imagine for sure. So the last thing I want

1308
01:08:03,360 --> 01:08:07,680
Speaker 1: to do before we end is folks may know someone

1309
01:08:07,760 --> 01:08:10,479
Speaker 1: that we had on the show, one of our earliest guests.

1310
01:08:10,480 --> 01:08:12,800
Speaker 1: I think it was maybe the first interview I did

1311
01:08:12,840 --> 01:08:15,400
Speaker 1: for There Are No Girls on the Internet with Shafika Hudson,

1312
01:08:15,520 --> 01:08:19,800
Speaker 1: the creator of the hashtag and movement Your slip is

1313
01:08:19,840 --> 01:08:24,920
Speaker 1: showing passed away, and we did an episode where put

1314
01:08:24,920 --> 01:08:26,559
Speaker 1: her episode back on the feed and I shared some

1315
01:08:26,600 --> 01:08:30,040
Speaker 1: of my thoughts and I just wanted to say I've

1316
01:08:30,040 --> 01:08:34,240
Speaker 1: really been wrestling with her death and the loss of

1317
01:08:34,280 --> 01:08:38,960
Speaker 1: her and what it means for the internet and social media.

1318
01:08:39,040 --> 01:08:43,240
Speaker 1: It feels like the end of a period, like thinking

1319
01:08:43,240 --> 01:08:45,840
Speaker 1: about it, and it was like, oh yeah, back when

1320
01:08:45,840 --> 01:08:48,719
Speaker 1: Shafika was, you know, doing her thing on the internet,

1321
01:08:48,800 --> 01:08:51,080
Speaker 1: it was a time when I was really active online

1322
01:08:51,080 --> 01:08:53,000
Speaker 1: and it felt really fun and exciting, and it was

1323
01:08:53,040 --> 01:08:57,280
Speaker 1: just really not just mourning her, but also mourning that

1324
01:08:57,520 --> 01:09:01,439
Speaker 1: the death of that time online. And I got reached

1325
01:09:01,479 --> 01:09:04,680
Speaker 1: out to by Penelope Green, who is a writer at

1326
01:09:04,720 --> 01:09:07,600
Speaker 1: The New York Times who was doing an obituary on

1327
01:09:07,600 --> 01:09:11,840
Speaker 1: Shaffika Hudson. And Penelope was great. We had many conversations

1328
01:09:12,200 --> 01:09:15,679
Speaker 1: about Chaffika's life and her work, and she said that

1329
01:09:16,360 --> 01:09:18,360
Speaker 1: the reason she was getting in touch with me was

1330
01:09:18,360 --> 01:09:24,000
Speaker 1: because somebody, I think a listener of this podcast reached

1331
01:09:24,000 --> 01:09:26,560
Speaker 1: out through I guess the New York Times has like

1332
01:09:26,600 --> 01:09:30,320
Speaker 1: an obituary request form where you can flag people that

1333
01:09:30,400 --> 01:09:32,400
Speaker 1: have recently passed that you think the New York Times

1334
01:09:32,400 --> 01:09:35,160
Speaker 1: should write an obituary on, which led to Penelope Green

1335
01:09:35,240 --> 01:09:37,760
Speaker 1: contacting me, which led to the obituary. So we'll put

1336
01:09:37,800 --> 01:09:40,160
Speaker 1: a link to the obituary in the show notes. I

1337
01:09:40,160 --> 01:09:42,640
Speaker 1: believe it will be in print in the New York Times.

1338
01:09:43,160 --> 01:09:47,599
Speaker 1: If you are the person who reached out to Penelope

1339
01:09:47,720 --> 01:09:53,000
Speaker 1: Green on behalf of Shaffika Hudson to get her obituary

1340
01:09:53,040 --> 01:09:54,920
Speaker 1: in the New York Times, I just want to say

1341
01:09:54,920 --> 01:09:57,559
Speaker 1: thank you. You're probably not listening to this, but it

1342
01:09:57,600 --> 01:09:59,800
Speaker 1: really meant a lot to me, and it really meant

1343
01:09:59,840 --> 01:10:02,640
Speaker 1: a lot of people who knew Shaffiica and work with

1344
01:10:02,680 --> 01:10:05,639
Speaker 1: Shafka and Shafika, to whom Shabika touched their.

1345
01:10:05,520 --> 01:10:06,439
Speaker 2: Lives in some way.

1346
01:10:06,560 --> 01:10:11,120
Speaker 1: And you know, one of my disappointments is that I

1347
01:10:11,240 --> 01:10:16,760
Speaker 1: don't feel like Shaffika's loss was mourned by the tech

1348
01:10:16,840 --> 01:10:21,240
Speaker 1: community and the disinformation community as I think it deserves

1349
01:10:21,280 --> 01:10:21,920
Speaker 1: to be mourned.

1350
01:10:22,320 --> 01:10:22,720
Speaker 2: And so.

1351
01:10:24,520 --> 01:10:28,439
Speaker 1: Taking part in this series of interviews with Penelope Green

1352
01:10:28,439 --> 01:10:31,720
Speaker 1: from New York Times was really personally cathartic for me

1353
01:10:32,000 --> 01:10:34,320
Speaker 1: and gave me a lot of closure on that. And

1354
01:10:34,400 --> 01:10:38,400
Speaker 1: I think it's really important that Shaffika Hudson's name and

1355
01:10:38,479 --> 01:10:43,760
Speaker 1: legacy is memorialized in this way. So all of that

1356
01:10:43,880 --> 01:10:46,160
Speaker 1: is to say, if you are that person, it really

1357
01:10:46,200 --> 01:10:46,840
Speaker 1: meant a lot to me.

1358
01:10:47,560 --> 01:10:47,920
Speaker 2: Thank you.

1359
01:10:48,800 --> 01:10:51,640
Speaker 1: Thank you to Penelope Green for reaching out to me

1360
01:10:51,840 --> 01:10:54,360
Speaker 1: and other people who knew and work with Shafeica, and

1361
01:10:54,439 --> 01:10:59,439
Speaker 1: for writing such a comprehensive and beautiful tribute to somebody

1362
01:10:59,520 --> 01:11:02,439
Speaker 1: who I just thought was fucking great and is no

1363
01:11:02,520 --> 01:11:03,160
Speaker 1: longer here.

1364
01:11:03,240 --> 01:11:04,639
Speaker 2: And folks can.

1365
01:11:04,520 --> 01:11:07,479
Speaker 1: Read the obituary in the show notes, or you can

1366
01:11:07,520 --> 01:11:09,559
Speaker 1: pick up a paper. I think it might be being

1367
01:11:09,600 --> 01:11:13,800
Speaker 1: published today. It's Thursday now, but Friday when you hear this.

1368
01:11:14,800 --> 01:11:17,439
Speaker 1: So yeah, I have a lot of people to thank

1369
01:11:17,760 --> 01:11:24,640
Speaker 1: for what ended up being a moment of personal disappointment

1370
01:11:24,960 --> 01:11:28,240
Speaker 1: that I get to now sort of process with something

1371
01:11:28,240 --> 01:11:32,080
Speaker 1: that feels good. So thank you, and thank you Joey

1372
01:11:32,120 --> 01:11:34,439
Speaker 1: for for being here and for listening.

1373
01:11:34,720 --> 01:11:38,280
Speaker 3: Oh my god. Of course happy to be here. And yeah,

1374
01:11:38,360 --> 01:11:39,880
Speaker 3: totally echo what you said.

1375
01:11:40,520 --> 01:11:42,880
Speaker 4: You know, the work that Shafika did is just so

1376
01:11:43,840 --> 01:11:46,479
Speaker 4: foundational to a lot of the stuff that we cover

1377
01:11:46,560 --> 01:11:51,519
Speaker 4: on here, and I think, you know, it's really it's

1378
01:11:51,560 --> 01:11:55,000
Speaker 4: really important to uplift those stories and to see you know,

1379
01:11:55,080 --> 01:11:57,280
Speaker 4: the New York Times spotlighting this. So yeah, absolutely echo

1380
01:11:57,280 --> 01:11:59,840
Speaker 4: with that. But yeah, of course always happy to be

1381
01:12:00,400 --> 01:12:03,719
Speaker 4: talk about the chaos of the world.

1382
01:12:04,080 --> 01:12:07,880
Speaker 1: Uh with you same and thanks to all of you

1383
01:12:08,040 --> 01:12:16,280
Speaker 1: for listening. I will see you on the Internet. If

1384
01:12:16,280 --> 01:12:18,400
Speaker 1: you're looking for ways to support the show, check out

1385
01:12:18,400 --> 01:12:22,280
Speaker 1: our merch store at tangody dot com slash store. Got

1386
01:12:22,280 --> 01:12:24,280
Speaker 1: a story about an interesting thing in tech, or just

1387
01:12:24,280 --> 01:12:26,280
Speaker 1: want to say hi, You can read us at Hello

1388
01:12:26,320 --> 01:12:28,840
Speaker 1: at tangodi dot com. You can also find transcripts for

1389
01:12:28,880 --> 01:12:31,559
Speaker 1: today's episode at tenggody dot com. There Are No Girls

1390
01:12:31,600 --> 01:12:34,000
Speaker 1: on the Internet was created by me bridgetpod. It's a

1391
01:12:34,000 --> 01:12:37,679
Speaker 1: production of iHeartRadio and Unbossed Creative edited by Joey pat

1392
01:12:38,320 --> 01:12:41,280
Speaker 1: Jonathan Strickland as our executive producer. Tari Harrison is our

1393
01:12:41,320 --> 01:12:44,799
Speaker 1: producer and sound engineer. Michael Almato is our contributing producer.

1394
01:12:45,080 --> 01:12:46,200
Speaker 1: I'm your host, Bridget Todd.

1395
01:12:46,520 --> 01:12:48,320
Speaker 2: If you want to help us grow, grate and review

1396
01:12:48,360 --> 01:12:49,360
Speaker 2: us on Apple Podcasts.

1397
01:12:50,160 --> 01:12:53,000
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1398
01:12:53,040 --> 01:12:55,560
Speaker 1: Apple Podcasts, or wherever you get your podcasts.