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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 Todd, and this

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

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

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

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Speaker 1: another installment of our weekly roundup of news stories that

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Speaker 1: you might have missed on the Internet. Mike, Happy day

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Speaker 1: after Valentine's Day. Did you see that all of the

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Speaker 1: lift drivers and Uber drivers and door dash folks were striking?

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Speaker 1: They were doing a Valentine's Day strike for better wages.

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Speaker 2: I did, and I love to see it.

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Speaker 3: I love to see people and workers taking collective action

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Speaker 3: to demand better pay, respect, to increase their visibility.

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Speaker 2: Love to see it.

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Speaker 1: Okay, So I agree with all of that, plus plus

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Speaker 1: plus plus to all of that. However, I have to

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Speaker 1: admit that even I talk so much crap about Uber

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Speaker 1: and Lyft and door Dash and the way that they

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Speaker 1: run their companies on this podcast, I do use those

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Speaker 1: services like I take Uber and Lyft a lot here

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Speaker 1: in DC where I live. And so this news that

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Speaker 1: Uber drivers and Lyft drivers were striking on Valentine's Day

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Speaker 1: and asking folks not to break the strike and cross

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Speaker 1: the picket lines and use those services. Set me into

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Speaker 1: a little bit of an existential tailspin because I don't

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Speaker 1: know if folks live in DC, you know what I'm

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Speaker 1: talking about. Like, I've lived in the I've lived in

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Speaker 1: cities my whole life, and I've lived in DC for

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Speaker 1: the longest, and I would say Uber and Lyft have

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Speaker 1: really changed the landscape of the city. And it's interesting.

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Speaker 1: I was like, how am I going to get to

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Speaker 1: my I'm had to go to dinner, Like what am

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Speaker 1: I going to do? Should I drive? But if I

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Speaker 1: am drinking? Am I risking in duy? Like is it

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Speaker 1: safe to even to even like be out driving at night?

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Speaker 1: Like I'm not the best driver. I was like racking

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Speaker 1: my brain trying to figure out what to do, And

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Speaker 1: when you know it, it was completely fine. All I

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Speaker 1: had to do was walk out of my apartment. Oh

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Speaker 1: there's a cab. I got in it. I told them

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Speaker 1: where I wanted to go, took me there without incident,

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Speaker 1: went had my dinner, came back out of the restaurant,

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Speaker 1: Oh there's a cab, just got in it. It is

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Speaker 1: so interesting to me how Uber and Lyft their rise

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Speaker 1: and their ubiquity had made me think like, oh, there

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Speaker 1: is no other alternative. Hey, I would never cross a

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Speaker 1: picket line. There's a scene from that sitcoms That Nanny

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Speaker 1: with Fran Dresser, where she's meant to be going to

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Speaker 1: a fancy dinner but all the bus boys are outside striking,

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Speaker 1: and she's like, one thing my mother told me is

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Speaker 1: you never cross a cricket line. And so I agree

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Speaker 1: with Fran Dresher's mom's advice and this, But it's so

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Speaker 1: funny to me, how like I had convinced to myself

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Speaker 1: that if I wasn't taking Uber or Lyft, there was

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Speaker 1: no other options. And it's like, oh, actually, cab was

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Speaker 1: very easy. It was right there, no no problem, do

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Speaker 1: you know what I mean? How strange it is that

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Speaker 1: that technology makes us think we have less options than

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Speaker 1: we actually do.

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Speaker 3: Yeah, it is funny how that works, because yeah, like

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Speaker 3: the cabs are still there, Metro is still there, buses

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Speaker 3: are still there. There's a bunch of bikes around.

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Speaker 1: Don't even get me started on bikes.

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Speaker 2: Okay, well I won't.

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Speaker 1: I mean, yes for the city run bike share program

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Speaker 1: in DC. But again, if I'm gonna circle back and

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Speaker 1: make this a deeper complaint about Uber and Lyft. Uber

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Speaker 1: purchased those jump bikes and then the line bikes and

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Speaker 1: basically junked them, and so biking was a much more

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Speaker 1: viable option in DC. I can't speak for other cities

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Speaker 1: before Uber and Lyft got involved in it, and now

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Speaker 1: it is like a husk of its former self. You

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Speaker 1: acknowledge that.

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Speaker 3: Yeah, so I have a lot of thoughts about what

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Speaker 3: has happened to the dockless vehicles here. I remember back

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Speaker 3: in like I don't know, almost have been twenty seventeen,

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Speaker 3: twenty eighteen, remarking to a friend that we were living

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Speaker 3: through peak dockless vehicle because that was the period when

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Speaker 3: all these companies like jump Birds, Spin, Lime, a whole

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Speaker 3: bunch of others that are now gone. They had so

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Speaker 3: much venture capital that they were just like dumping electric

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Speaker 3: bikes and electric scooters all over the city and you could,

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Speaker 3: you know, check them out on your phone using the

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Speaker 3: app for like pennies, right, it was like ridiculously cheap.

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Speaker 3: There were a million of these things. Yeah, they were

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Speaker 3: a blight on the city. People did dumb things like

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Speaker 3: parking them on sidewalks and ways that made the sidewalks inaccessible,

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Speaker 3: which was like definitely not cool, but for somebody who

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Speaker 3: wanted to like get around the city, it was amazing.

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Speaker 3: And now most of them are gone. Like you say that,

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Speaker 3: it's just a handful that are left. It is kind

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Speaker 3: of sad.

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Speaker 1: Okay, So this is something you know, we don't see

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Speaker 1: EyeT of eye on. I think that bit that you

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Speaker 1: just said about them being a blight on the city,

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Speaker 1: I don't think that deserves to be glossed over because

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Speaker 1: they're so in DC. They are everywhere. They are blocking intersections,

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Speaker 1: they are on sidewalks. It's a nightmare. And half of

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Speaker 1: them don't even work. So it's like at this point,

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Speaker 1: you know, I think it was different when it's like, oh, well,

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Speaker 1: these are bikes that are working that you could use

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Speaker 1: to get around. Hearing DC, part of me is like,

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Speaker 1: it's at this point, it's just like eWays delittering the

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Speaker 1: streets for no reason. They half of them do not work.

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Speaker 3: It would be nice if more of them worked. Yeah,

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Speaker 3: we don't see eye to eye on that.

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Speaker 2: I don't know.

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Speaker 3: I think it's super convenient to have like multiple transportation

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Speaker 3: options if I want to get downtown and then I

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Speaker 3: can just like ditch the thing and be done with it.

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Speaker 1: I mean, if it actually worked that way. Yeah, that

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Speaker 1: does sound like a good situation. I guess Uber and

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Speaker 1: Lyft had to get involved and innovate that convenient reality

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Speaker 1: out of existence. So thank you Uber and Lyft. Okay, so,

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Speaker 1: speaking of another tech company that maybe is doing some

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Speaker 1: shady stuff. You watched the Super Bowl. Did you see

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Speaker 1: all of those like very weird possibly AI generated ads

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Speaker 1: for Tmu? Actually, apparently it's Tamu. I've been saying it

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Speaker 1: wrong this whole time, but I thought it was Temu.

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Speaker 3: I did see those ads, and they were so weird.

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Speaker 3: It was weird in the same way that their advertisements

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Speaker 3: for products, which are all over the web and social media,

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Speaker 3: are also weird. It's just like just a little bit off,

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Speaker 3: like appealing and sort of interesting, but also just like

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Speaker 3: strange and a little bit off, as if like every

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Speaker 3: step of the production process were performed by AI.

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Speaker 1: Did I ever show you the Tamu ad that I

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Speaker 1: got for the purse that looks like a gun?

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Speaker 2: You did show me that.

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Speaker 1: It's like, I'm gonna I'll put a link to it

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Speaker 1: in the show notes. I'll try to describe it. I know,

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Speaker 1: this is a not a visual medium. But it's like

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Speaker 1: a handbag on a chain that hangs about hip level,

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Speaker 1: and the handbag itself is shaped like a gun. There's

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Speaker 1: really not more to it than that. And so I'm

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Speaker 1: sure someone somewhere was like, maybe this is edge design,

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Speaker 1: but it looks so if you were to go out,

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Speaker 1: it just looks like you're holding a gun on your hip,

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Speaker 1: which I don't know. I don't think that's the kind

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Speaker 1: of perse that me, as a black person, wants to

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Speaker 1: be out and about carrying, like, oh, just going to

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Speaker 1: the bank with this gun, this visible gun on my hip.

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Speaker 1: Thanks Tamu. But that's what you're sort of getting at

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Speaker 1: that even the products somehow seem like they were designed

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Speaker 1: with no human at any step in the process.

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Speaker 3: Yeah, And I frequently get ads for products that like,

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Speaker 3: it's not even clear what it is. It's some sort

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Speaker 3: of interesting looking gadget that's somewhere between like high tech

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Speaker 3: and steampunk, but like does not have a clear function

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Speaker 3: from the ad, And sometimes I'm like genuinely curious. They

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Speaker 3: do a good job of hooking my curiosity and I'll

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Speaker 3: almost click on it until I see that it is

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Speaker 3: Tamu Okay.

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Speaker 1: Well, let's see if you will ever click on another

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Speaker 1: Tamu ad again after we talk about what's actually going

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Speaker 1: on there. So Tamu, they did have a Super Bowl

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Speaker 1: commercial back in twenty twenty three, but this year they

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Speaker 1: ran four identical commercials with a jingle that says like

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Speaker 1: shop like a billionaire, and they also advertised fifteen million

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Speaker 1: dollars in giveaways. So I guess those ads are really

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Speaker 1: paying off because people are really downloading Tamu after those ads,

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Speaker 1: according to NBC, who talked to the mobile intelligence company

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Speaker 1: app Topias vice president of research, Tom Grant, who said

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Speaker 1: in a statement that Tamu's app downloads increased thirty four

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Speaker 1: percent on Super Bowl Sunday from the day before, which

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Speaker 1: was Tamu's fastest day over day growth since November. So

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Speaker 1: this is the part where I have to give a

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Speaker 1: big loud warning caution about Tamu. Please be careful with Tamu.

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Speaker 1: I would even go so far as to say, maybe

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Speaker 1: don't use Tamu, and by use it, I mean like

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Speaker 1: don't even download it, let alone make a purchase on Tamu.

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Speaker 1: And after that Super Bowl ad, maybe the person in

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Speaker 1: your family who warns your mom, your aunt, to use

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Speaker 1: your cousins whatever about Taymu too. So when I first

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Speaker 1: started researching this segment, I was like, I don't want

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Speaker 1: to get sued. I'm gonna like say everything very carefully.

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Speaker 1: I don't really need to do that anymore, and you'll

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Speaker 1: find out why. It's a minute. So there are multiple

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Speaker 1: reports of people saying that they have had their identity

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Speaker 1: stolen after they downloaded Tamu. I say, downloading with intention

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Speaker 1: because they didn't necessarily have to make purchases. Tamu is

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Speaker 1: one of those apps. In order to see the great

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Speaker 1: deals or find out what that item is that it's

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Speaker 1: been advertised to you, the only way to see that

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Speaker 1: is to download the app. And so Mike, you're saying, oh,

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Speaker 1: I see these novelty goods that they pique my curiosity

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Speaker 1: on social media, but I always stop short of clicking

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Speaker 1: on them. That is good. I think that that is

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Speaker 1: part of Tamu's marketing strategy of peaking your interest with

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Speaker 1: these deals or with these novelty goods, getting you to

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Speaker 1: go through the process of downloading the app, and that

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Speaker 1: is where they get you.

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Speaker 3: Yeah, it seems pretty obvious, right, Like if their business

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Speaker 3: model were selling goods. They would make it possible to

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Speaker 3: buy those goods without downloading the app, but it seems

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Speaker 3: like one hundred percent of what they're trying to do

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Speaker 3: is to get me to download the app, which is skitch.

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Speaker 1: So there are hella posts on Reddit about people who

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Speaker 1: think they have had their identity stolen after getting mixed

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Speaker 1: up with Temu. Here's one. I idiotically installed Temu on

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Speaker 1: my phone last week to see what these deals were

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Speaker 1: that I keep hearing about. Uninstalled the app after ten minutes. Today,

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Speaker 1: I woke up to see an odd notification on my

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Speaker 1: phone pertaining to an approved Facebook ad. Apparently they made

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Speaker 1: a page on my account, made a post about selling

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Speaker 1: women's lingerie all in Mandarin. Temu is a Chinese owned company,

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Speaker 1: had Facebook boost it as an ad, and now people

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Speaker 1: are asking why I'm selling women's lingerie and if I

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Speaker 1: am Chinese. I've deleted the page and now I'm worried

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Speaker 1: ads manager will demand payment for the three hours of

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Speaker 1: ads they've run on my page. Mike, there are so

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Speaker 1: many posts like this, people saying I didn't even purchase anything.

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Speaker 1: I just it piqued my curiosity. I downloaded the app

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Speaker 1: I had it on my phone for less than ten minutes,

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Speaker 1: and now some sort of weird behavior is.

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Speaker 3: Going on in my name, and it is so consistent

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Speaker 3: with their slightly off branding that like, it's not just

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Speaker 3: a normal scam that takes his money. It's like, now

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Speaker 3: people are asking why I'm selling women's lingerie, and if

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Speaker 3: I'm Chinese.

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Speaker 1: I know it's not just a normal scam. It is

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Speaker 1: a weird This is what I'm saying about this company.

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Speaker 1: It seems like there are no humans anywhere in the mix.

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Speaker 1: And it's like the kind of scam that is written

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Speaker 1: by AI. It's like it can't even be a normal scam.

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Speaker 1: It has to be a weird scam. Even their scams

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Speaker 1: are weird.

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Speaker 2: Yeah, it's like a scam within a scam.

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Speaker 1: Okay. So when I was thinking about how to talk

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Speaker 1: about this issue, I was like, oh, I really I

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Speaker 1: just want to be like people are saying, here are

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Speaker 1: some experiences. I'll just like share people's experiences and let

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Speaker 1: the listeners decide, because I'm like not trying to get

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Speaker 1: sued by TAMU. I'm sure they're very litigious. However, come

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Speaker 1: to find out that TAMU has faced multiple class action

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Speaker 1: lawsuits alleging that they are misleading customers about the scope

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Speaker 1: and reach of data access and collection and intentionally has

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Speaker 1: loaded dangerous malware and spywear on to use devices. This

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Speaker 1: is from a piece in Fashion and Dive that we

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Speaker 1: will put in the show notes. So, attorneys for the

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Speaker 1: plaintiffs claim that Tamu collects data beyond what is necessary

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Speaker 1: for an online shopping app, including biometric information such as

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Speaker 1: facial characteristics, voice prints, and fingerprints. The lawsuit quotes experts

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Speaker 1: who said that TAMU gains access to literally everything on

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Speaker 1: your phone, and the suit further alleges that TAMU is

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Speaker 1: able to read private messages, make changes to a phone setting,

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Speaker 1: and track notifications.

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Speaker 3: I mean, that's just like a ridiculous amount of privileges

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Speaker 3: for an app that is about purchasing goods.

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Speaker 2: Like I can see.

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Speaker 3: Why they would want to why they would want to

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Speaker 3: harvest every piece of information about you, including your biometrics

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Speaker 3: and the content of your private messages. But it's difficult

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Speaker 3: to think about a world where like that's okay for

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Speaker 3: an app to do well.

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Speaker 1: Mike, do you want to shop like a billionaire or not?

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Speaker 1: Do you want these eye catching deals or not? Is

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Speaker 1: it just the costs. I'm doing business to shop like

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Speaker 1: a billionaire?

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Speaker 2: What does that even mean?

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Speaker 3: Like our billionaires out there being like, oh there's things

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Speaker 3: only three bucks?

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Speaker 2: What a deal?

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Speaker 3: I feel like that's exactly not what billionaires do.

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Speaker 1: I know. Even the slogan doesn't make sense, Like nothing

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Speaker 1: about it makes any sense.

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Speaker 3: The only thing that makes sense is that they're like

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Speaker 3: clearly trying to just harvest all of your data.

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Speaker 1: Well. The newest complaint against Tamu cites experts who have

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Speaker 1: studied the Tamu app and concluded that it is quote

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Speaker 1: purposefully and intentionally loaded with tools to execute virulent and

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Speaker 1: dangerous malware and spyware activities on user devices. The complaint

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Speaker 1: further alleges great efforts were taken to intentionally hide the

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Speaker 1: malicious intent and intrusiveness of the software.

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Speaker 2: My god, that's intense.

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Speaker 3: Like we talk a lot about bad apps, bad companies

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Speaker 3: that are like not taking appropriate protections to protect their users,

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Speaker 3: but this is just malicious straight.

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Speaker 1: Up, according to this complaint, like straight up malwares. I

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Speaker 1: guess you probably never expectant, but when you buy something

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Speaker 1: online from a company that's like kind of sketch, Like

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Speaker 1: like when I first started making purchases. I think I've

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Speaker 1: made two purchases on TikTok shop. I was like, oh

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Speaker 1: my god, is this is this? Am I about to

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Speaker 1: get my identity stolen? I thought people were going off

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Speaker 1: of mostly vibes that like it felt sketchy, didn't feel right, whatever, whatever. No,

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Speaker 1: this is like legit, real deal malware. All of this

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Speaker 1: to say, like, I guess I feel pretty comfortable saying

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Speaker 1: people should really be thinking long and hard before downloading

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Speaker 1: the app, even if you only downloaded to look because

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Speaker 1: it's some novel the item that you can't believe is real,

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Speaker 1: Like a gun shaped purse has come across your feed.

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Speaker 1: Just think really long and hard before you click, and

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Speaker 1: tell your aunties and your mama's and your cousins about like,

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Speaker 1: send them this segment if they're thinking about buying something

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Speaker 1: on table or you know that the kind of person who,

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Speaker 1: like you know, can't resist a good deal online and

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Speaker 1: wants to shop like a billionaire.

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Speaker 3: Yeah, I wonder if we're gonna hear from them. But

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Speaker 3: you know, based on these experts and many lawsuits and

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Speaker 3: many Reddit posts, it definitely seems like the sort of

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Speaker 3: thing that should be avoided.

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Speaker 1: From what I have seen, I think that Temu might

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Speaker 1: be litigious. They were gotten into it with En back

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Speaker 1: in twenty twenty three, where they so like Sheien is

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Speaker 1: another kind of like crappy fast fashion retailer. Tamu is

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Speaker 1: one of their big rivals. Tamu sued Sheen alleging quote

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Speaker 1: mafia style intimidation, and so something tells me that this

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Speaker 1: company is like kind of litigious. I don't know all

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Speaker 1: the details between what happened between Tamu and Sheien, but

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Speaker 1: I was like, oh, I don't want to get mixed

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Speaker 1: up with this company. But now I feel very confident

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Speaker 1: saying that folks should really think twice before tabloating it

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Speaker 1: at the very least. So Temu, if y'all are listening,

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Speaker 1: feel free to come on the show and plead your case.

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Speaker 1: I would love to hear how you justify this. Maybe

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Speaker 1: it's just like by hook up our remote recording software.

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Speaker 1: It's like, God, they got my identity, like they're so good.

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Speaker 3: Yeah, hold on, I'm getting a notification about something that's

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Speaker 3: trying to install.

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Speaker 1: Mike, Why does this ad say that you're selling Chinese laingerie?

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Speaker 2: The scam is coming from inside of me? Oh, No,

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Speaker 2: they are good. They are good. It is a cool

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Speaker 2: little gadget.

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Speaker 1: Though.

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Speaker 4: Let's take a quick break at our back.

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Speaker 1: Let's talk about another big story going on, which is

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Speaker 1: Meta deprioritizing political content. So we have talked a lot

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Speaker 1: about the different changes happening for our social media landscape. Honestly,

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Speaker 1: it feels like every day it's a new thing. I

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Speaker 1: am exhausted trying to keep up with it. I cannot

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Speaker 1: imagine how people who don't do this for a living field.

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Speaker 1: I guess I'll put it that way. And so this

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Speaker 1: is a change that I think could have big consequences,

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Speaker 1: especially for traditionally marginalized people. So Meta, the parent company

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Speaker 1: and Facebook, Instagram, and Threads, announced this week that they

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Speaker 1: would be deprioritizing political content from threads, Facebook, and Instagram.

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Speaker 1: This comes from Adam Mosseerri, my personal nemesis, who said

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Speaker 1: the company will no longer quote proactively amplify political content

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Speaker 1: from accounts who don't follow most Aari said that the

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Speaker 1: platform will still show you content from people that you

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Speaker 1: have chosen to follow, but that the company will avoid

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Speaker 1: recommending political content to the broader masses. Our goal is

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Speaker 1: to reserve the ability for people to choose to interact

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Speaker 1: with political content while respecting each person's appetite for it.

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Speaker 1: So I think that this is likely Facebook kind of

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Speaker 1: admitting or acknowledging that they have no real ability to

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Speaker 1: control things like hate speech or conspiracy theories on their platforms,

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Speaker 1: the kind of things that led to, you know, among others,

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Speaker 1: January sixth, you know, a genocide and Meanmar, you know,

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Speaker 1: really chaos and havoc globally. I think that this is

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Speaker 1: a decision that is like, Yep, we don't know how

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Speaker 1: to control it, and honestly, we can't be bothered to

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Speaker 1: figure it out. I also think it dovetails with a

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Speaker 1: story that we covered pretty extensively last summer about Facebook

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Speaker 1: dropping news content altogether. I think that they've kind of

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Speaker 1: decided that news and political content is just like not

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Speaker 1: worth it, and so they're just going to be like, Yep,

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Speaker 1: we can't figure out how to manage it responsibly, and

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Speaker 1: we're just going to sort of abdicate that responsibility.

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Speaker 3: Yeah, I think that's exactly right. I think they're responding

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Speaker 3: to those two different pressures. The one pressure that they

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Speaker 3: don't really want.

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Speaker 2: To be in the news business anymore.

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Speaker 3: There's this article in The New Yorker yesterday about how

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Speaker 3: people are just like burnt out on news in general

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Speaker 3: and how it's like rippling across media, and so I think,

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Speaker 3: you know, this is meta. So that's probably what's driving

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Speaker 3: their real decision. Is they just like it's not profitable

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Speaker 3: to be serving this kind of content. But then also, yeah,

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Speaker 3: I think they just don't want to be seen as

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Speaker 3: having to have responsibility for moderating like responsible political content,

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Speaker 3: and so they're trying to just like take their hands

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Speaker 3: off of it entirely.

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Speaker 2: But you know, good luck with that.

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Speaker 1: Yeah, I have two things to say about that. I

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Speaker 1: was reading this piece from Charlie Wurtzel at The Atlantic

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Speaker 1: about how perhaps that does in some ways reflect what

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Speaker 1: people are saying they want from these companies. Like Ortel

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Speaker 1: argues that people do not necessarily want to feel like

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Speaker 1: Facebook is just picking and choosing what they see and

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Speaker 1: moderating things. But however, they also don't want it to

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Speaker 1: be the wild wild West of lies and disinformation and

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Speaker 1: hate speech, and so in some ways Rtil argues that

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Speaker 1: Facebook kind of is in a tough situation of wanting

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Speaker 1: to give people what they want but also not wanting

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Speaker 1: to do too much and sort of like trying to

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Speaker 1: figure out like what it is people want in that

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Speaker 1: like sweet spot. I also want to say something about

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Speaker 1: this idea about folks being burnt out on news that

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Speaker 1: really resonates with me, and it's one of those things

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Speaker 1: that I don't really know what to do with. I

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Speaker 1: actually started and then abandoned a Patreon episode about this,

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Speaker 1: and so if you're wondering where the most recent Patreon

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Speaker 1: episode is, it's still floating around in my brain because

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Speaker 1: it's a tough thing to navigate. I feel like I'm

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Speaker 1: navigating it. I'm really curious how listeners are feeling about it.

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Speaker 1: It does feel like we've reached a fever pitch where

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Speaker 1: there is so much difficult news and that is real.

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Speaker 1: Like I can speak for myself personally, a lot of

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Speaker 1: the coverage coming out of Palestine, for instance, is the

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Speaker 1: kind of thing that I have historically had a lot

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Speaker 1: of issues with following very closely. It's the kind of

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Speaker 1: tragedy that I would get very invested in and feel

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Speaker 1: the need to follow quite carefully. But also it's the

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Speaker 1: kind of thing that nobody could follow closely without it

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Speaker 1: really getting to you. You know, journalists from the Ground

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Speaker 1: have talked about this too, and I do think it's

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Speaker 1: one of those things where it makes sense that it

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Speaker 1: feels so absurd that all of this is going on

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Speaker 1: meanwhile we're meant to be like going to work and

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Speaker 1: living our lives as if it's not. It's really difficult.

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Speaker 1: And I say that from a place of like extreme privilege,

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Speaker 1: of like I have the ability to say, like, I

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Speaker 1: don't want to see pictures of dead children anymore because

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Speaker 1: it's really wreaking havoc on my mental health. If I

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Speaker 1: was in Palestine, I would not have the ability to

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Speaker 1: say to say that, right. It would be like, oh, yeah,

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Speaker 1: I'm sure you would like to not be experiencing this

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Speaker 1: happening in your real life. And so I say that cautiously,

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Speaker 1: really aware of the fact that, like, it's a privilege

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Speaker 1: to be a to say, like, oh, this news is

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Speaker 1: such a bummer, but I also want to acknowledge it

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Speaker 1: is a lot like I think when you think about

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Speaker 1: what's happening globally, not just in Palestine but all over

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Speaker 1: it just part of me understands what people are saying

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Speaker 1: when they say that they're burnt out on news content,

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Speaker 1: and even from somebody who makes a podcast, Like, I

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Speaker 1: see the numbers for how episodes perform, and it does

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Speaker 1: seem like people are looking for content that it's not

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Speaker 1: necessarily anchored to the news. And yeah, I guess all

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Speaker 1: of that to say is I'm curious how that lands

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Speaker 1: for folks. I'm curious how folks are navigating that in

434
00:22:40,760 --> 00:22:43,199
Speaker 1: their own lives. I'm definitely trying to navigate it as

435
00:22:43,240 --> 00:22:46,879
Speaker 1: somebody who creates a thing. And I think it's important

436
00:22:46,920 --> 00:22:50,200
Speaker 1: that we all stay engaged and informed and checked in

437
00:22:50,359 --> 00:22:54,160
Speaker 1: and like, don't it's so easy just to retreat. Again,

438
00:22:54,240 --> 00:22:56,680
Speaker 1: speaking for myself, it is so easy just to retreat

439
00:22:56,680 --> 00:23:00,359
Speaker 1: into like Real housewives and like nostalgia and like watching

440
00:23:00,400 --> 00:23:03,159
Speaker 1: The Office a million times and things that feel good.

441
00:23:03,720 --> 00:23:06,439
Speaker 1: But we still have to find ways to stay informed

442
00:23:06,480 --> 00:23:09,560
Speaker 1: and checked in. And Yeah, I'm curious, Mike, if you

443
00:23:09,560 --> 00:23:11,200
Speaker 1: have thoughts around that, or if listeners, if you have

444
00:23:11,200 --> 00:23:13,800
Speaker 1: thoughts around that, please let me know. I'm genuinely very

445
00:23:13,880 --> 00:23:16,200
Speaker 1: curious how folks are navigating this this time.

446
00:23:16,800 --> 00:23:21,480
Speaker 3: Yeah, that all really resonates. It's tough times. It's been

447
00:23:21,520 --> 00:23:29,120
Speaker 3: tough times for years, right, you know, there's terrible wars happening.

448
00:23:29,440 --> 00:23:35,719
Speaker 3: Domestic politics is anxiety provoking, to say the least, and

449
00:23:35,760 --> 00:23:40,760
Speaker 3: it's really difficult to stay engaged. That New Yorker article

450
00:23:40,840 --> 00:23:43,000
Speaker 3: was interesting. We should link to it in the show notes.

451
00:23:43,359 --> 00:23:46,520
Speaker 3: I feel like this is kind of in some ways

452
00:23:47,080 --> 00:23:51,360
Speaker 3: not surprising that collectively a lot of people in society

453
00:23:51,400 --> 00:23:53,680
Speaker 3: are feeling this way right now. Right we've had ten,

454
00:23:53,720 --> 00:23:58,359
Speaker 3: almost like twenty years of social media where algorithms and

455
00:23:58,440 --> 00:24:05,000
Speaker 3: platforms and bad actors and nefarious, demagogic politicians you know

456
00:24:05,000 --> 00:24:09,679
Speaker 3: who I'm talking about, have really perfected the art of

457
00:24:10,800 --> 00:24:15,800
Speaker 3: dialing up outrage to get us engaged, to get our attention,

458
00:24:15,880 --> 00:24:17,439
Speaker 3: to get our money, to get our votes.

459
00:24:17,960 --> 00:24:19,000
Speaker 2: And it's just.

460
00:24:19,000 --> 00:24:23,640
Speaker 3: Exhausting, right, It's just gotten more and more exhausting. And

461
00:24:24,400 --> 00:24:26,359
Speaker 3: you know, I guess maybe in some ways this move

462
00:24:26,440 --> 00:24:29,040
Speaker 3: by Meta can be seen as like a reaction to

463
00:24:29,320 --> 00:24:33,000
Speaker 3: that that we need something else other than just a

464
00:24:33,080 --> 00:24:38,120
Speaker 3: continual ratcheting up, an increase and increase of like outrage

465
00:24:38,200 --> 00:24:43,640
Speaker 3: and terrible stuff, but just you know, stripping political content

466
00:24:43,720 --> 00:24:47,720
Speaker 3: from the platform. That doesn't really seem like the right

467
00:24:47,760 --> 00:24:50,840
Speaker 3: approach either, because there are legit problems and issues in

468
00:24:50,880 --> 00:24:54,040
Speaker 3: the world that people need to be informed about and

469
00:24:54,080 --> 00:24:55,680
Speaker 3: should be engaged with.

470
00:24:55,880 --> 00:24:59,280
Speaker 1: Well, that's what I'm saying. I think that Facebook was

471
00:24:59,320 --> 00:25:03,240
Speaker 1: a huge driver of the polarization that you described a

472
00:25:03,280 --> 00:25:06,119
Speaker 1: moment ago, this ratcheting up of more and more hate,

473
00:25:06,240 --> 00:25:10,000
Speaker 1: more and more you know, engagement farming by making people

474
00:25:10,040 --> 00:25:12,560
Speaker 1: angry and outraged and more divided and less trustful of

475
00:25:12,560 --> 00:25:15,080
Speaker 1: each other and all that. And it's just I don't

476
00:25:15,240 --> 00:25:17,520
Speaker 1: like that they can just be like and oopsie's swe

477
00:25:17,680 --> 00:25:21,040
Speaker 1: don't want to do that anymore. You can't just create

478
00:25:21,119 --> 00:25:24,000
Speaker 1: this chaos globally and then step back and say and

479
00:25:24,160 --> 00:25:26,520
Speaker 1: wash your hands of it and say it's not your problem,

480
00:25:26,560 --> 00:25:28,720
Speaker 1: because it is your problem. It's your problem that you cause.

481
00:25:28,760 --> 00:25:30,359
Speaker 1: And I think it's I think it's pretty telling that

482
00:25:30,400 --> 00:25:32,760
Speaker 1: now they're like, h we don't want to do it anymore.

483
00:25:33,080 --> 00:25:36,320
Speaker 1: And I have seen people, some of whom are people

484
00:25:36,320 --> 00:25:38,919
Speaker 1: that I trust and sometimes agree with, say that this

485
00:25:39,080 --> 00:25:43,000
Speaker 1: is a good thing, that less politics on platforms means

486
00:25:43,119 --> 00:25:46,080
Speaker 1: less chances for polarization and all of that stuff, Right,

487
00:25:46,280 --> 00:25:47,960
Speaker 1: But I am not so sure. And I think that

488
00:25:48,560 --> 00:25:51,760
Speaker 1: a change like this has the ability to be very

489
00:25:51,920 --> 00:25:55,000
Speaker 1: bad and destabilizing at a time in our media ecosystem

490
00:25:55,200 --> 00:25:59,480
Speaker 1: it's already not great. So if threads and Instagram and

491
00:25:59,480 --> 00:26:02,439
Speaker 1: Facebook are no longer going to be prioritizing any kind

492
00:26:02,480 --> 00:26:04,560
Speaker 1: of political content. That means, first of all, that means

493
00:26:04,600 --> 00:26:06,960
Speaker 1: that there's going to be a bigger strain on Twitter

494
00:26:07,080 --> 00:26:08,560
Speaker 1: to be a place where you go for news. And

495
00:26:08,600 --> 00:26:11,280
Speaker 1: Twitter is a mess, and so we're going to make

496
00:26:11,560 --> 00:26:15,080
Speaker 1: Twitter a bigger piece of the pie for our media

497
00:26:15,160 --> 00:26:17,520
Speaker 1: diet as it pertains to politics and news and what's

498
00:26:17,560 --> 00:26:19,840
Speaker 1: going on. That is a problem because Twitter is a

499
00:26:19,960 --> 00:26:23,000
Speaker 1: sesspool right now. And I also think, you know, Facebook

500
00:26:23,000 --> 00:26:26,359
Speaker 1: has really not made it clear what they consider political content.

501
00:26:26,400 --> 00:26:28,480
Speaker 1: They haven't really given any information as to what they

502
00:26:28,560 --> 00:26:32,440
Speaker 1: consider political and I just think the idea that there's

503
00:26:32,760 --> 00:26:37,359
Speaker 1: one big bucket of clearly defined political content is just

504
00:26:37,720 --> 00:26:39,840
Speaker 1: so incorrect. That is not how people live their lives.

505
00:26:40,040 --> 00:26:44,199
Speaker 1: The reality is everything is intertwined and intersectional, right Like

506
00:26:44,280 --> 00:26:48,600
Speaker 1: the super Bowl was political, Star Wars is political, you know,

507
00:26:49,080 --> 00:26:53,480
Speaker 1: Real Housewives is political. You know, like everything is political.

508
00:26:53,560 --> 00:26:56,800
Speaker 1: Everything is politics. And I think that this idea that oh,

509
00:26:56,840 --> 00:26:58,760
Speaker 1: we're going to start moderating what is and is not

510
00:26:58,840 --> 00:27:01,480
Speaker 1: political without giving any insight into what that's going to

511
00:27:01,480 --> 00:27:04,200
Speaker 1: look like or any kind of concrete examples, is very

512
00:27:04,440 --> 00:27:06,879
Speaker 1: worrying for me. So I guess CNN reached out to

513
00:27:06,920 --> 00:27:10,040
Speaker 1: Adam Moseri, who conveniently was traveling and could not give

514
00:27:10,080 --> 00:27:12,480
Speaker 1: any information. And you know, Adam mos Ari doesn't really

515
00:27:12,520 --> 00:27:15,879
Speaker 1: do interviews. What he does is like tweet and then

516
00:27:16,160 --> 00:27:19,720
Speaker 1: selectively respond to some people's tweets, Like he tweeted about

517
00:27:19,720 --> 00:27:22,000
Speaker 1: this change. Mark Cuban was like, Oh, how are you

518
00:27:22,040 --> 00:27:24,200
Speaker 1: going to be deciding what's political and what's not. And

519
00:27:24,280 --> 00:27:27,680
Speaker 1: adamos Ari replied to Cuban's tweet, so like, that's how

520
00:27:27,720 --> 00:27:30,919
Speaker 1: ineffectively we're getting information that it's poised to change our

521
00:27:31,080 --> 00:27:33,920
Speaker 1: entire media ecosystem. What a gem of a guy at

522
00:27:33,920 --> 00:27:36,600
Speaker 1: a Mossy. However, so, even though he did not respond

523
00:27:36,760 --> 00:27:39,719
Speaker 1: to requests to clarify what is going to be considered

524
00:27:39,720 --> 00:27:43,600
Speaker 1: political content, a META spokesperson did give this very vague statement,

525
00:27:43,760 --> 00:27:47,399
Speaker 1: informed by research. Our definition of political content. It's content

526
00:27:47,680 --> 00:27:50,200
Speaker 1: likely to be about topics related to government or elections,

527
00:27:50,240 --> 00:27:54,520
Speaker 1: for example, posts about laws, elections, or social topics. These

528
00:27:54,560 --> 00:27:57,920
Speaker 1: global issues are complex and dynamics, which means this definition

529
00:27:57,960 --> 00:28:00,679
Speaker 1: will evolve as we continue to engage with the people

530
00:28:00,720 --> 00:28:04,080
Speaker 1: and communities who use our platforms and external experts to

531
00:28:04,119 --> 00:28:06,679
Speaker 1: refine our approach. Scott really doesn't say anything at all

532
00:28:06,720 --> 00:28:09,760
Speaker 1: to me. They threw in the word communities and people

533
00:28:10,280 --> 00:28:12,960
Speaker 1: and basically they're like, we don't know, y'all. I can't

534
00:28:13,240 --> 00:28:16,320
Speaker 1: like that statement is so vague. It basically says nothing.

535
00:28:16,800 --> 00:28:19,399
Speaker 3: Yeah, it really reads like it says nothing. Like it

536
00:28:19,720 --> 00:28:21,920
Speaker 3: one gets the sense that they don't want to be

537
00:28:21,960 --> 00:28:24,919
Speaker 3: in the business of deciding what kind of speech is

538
00:28:24,920 --> 00:28:27,120
Speaker 3: okay and what kind of speech isn't. They don't want

539
00:28:27,119 --> 00:28:29,040
Speaker 3: to have to make those value judgments because they're going

540
00:28:29,119 --> 00:28:33,280
Speaker 3: to make people bad, So they're just going to blanketly

541
00:28:33,800 --> 00:28:36,440
Speaker 3: exclude any sort of political content. But all they've done

542
00:28:36,560 --> 00:28:40,720
Speaker 3: is just shift those value judgments from you know, what

543
00:28:40,920 --> 00:28:46,400
Speaker 3: speech is harmful or hateful to what speech is political.

544
00:28:46,080 --> 00:28:49,920
Speaker 1: And in doing so, that is a value judgment. Like

545
00:28:50,360 --> 00:28:54,680
Speaker 1: not by saying like we're just going to deprioritize political content,

546
00:28:55,320 --> 00:28:59,360
Speaker 1: that is them picking and choosing what is politics and

547
00:28:59,400 --> 00:29:02,200
Speaker 1: what is something else, Like whose issues are going to

548
00:29:02,240 --> 00:29:05,880
Speaker 1: be considered political and who's are going to be considered okay.

549
00:29:06,040 --> 00:29:08,080
Speaker 1: I feel like we have a lot of precedents for

550
00:29:08,560 --> 00:29:12,600
Speaker 1: Facebook doing that, Like Facebook already is involved in the

551
00:29:12,600 --> 00:29:14,960
Speaker 1: business of making those kinds of decisions, So we do

552
00:29:15,040 --> 00:29:17,600
Speaker 1: have some precedent to look at how they might go

553
00:29:17,640 --> 00:29:21,240
Speaker 1: about deciding what is or is not political. And spoiler alert,

554
00:29:21,720 --> 00:29:24,080
Speaker 1: I believe that if it's something that pertains to somebody

555
00:29:24,080 --> 00:29:27,920
Speaker 1: who is traditionally marginalized, women, black folks, queer folks, folks

556
00:29:27,920 --> 00:29:30,920
Speaker 1: of color, trans folks, that is going to be much

557
00:29:30,920 --> 00:29:34,240
Speaker 1: more easily deemed as political. And if it doesn't, that

558
00:29:34,360 --> 00:29:36,800
Speaker 1: is going to be much more easily deemed by Facebook

559
00:29:37,000 --> 00:29:40,280
Speaker 1: as not political. Facebook has already established such a clear

560
00:29:40,320 --> 00:29:42,880
Speaker 1: precedent of doing this. We've talked about it before, like

561
00:29:43,000 --> 00:29:47,280
Speaker 1: when it comes to how they moderate their ads. For instance,

562
00:29:47,680 --> 00:29:50,080
Speaker 1: any kind of ads that are related to things that

563
00:29:50,280 --> 00:29:53,160
Speaker 1: are related to the sexual health of people who are

564
00:29:53,160 --> 00:29:56,600
Speaker 1: not CIS men, so queer folks, trans folks, women, ads

565
00:29:56,640 --> 00:29:59,960
Speaker 1: for things like pelvic pain during sex, Facebook has deemed

566
00:30:00,080 --> 00:30:03,280
Speaker 1: to those sexually explicit and will not allow them on

567
00:30:03,280 --> 00:30:06,239
Speaker 1: the platform. However, products that deal with things like our

568
00:30:06,240 --> 00:30:10,200
Speaker 1: rectile dysfunction, Facebook has deemed those products health products, and

569
00:30:10,240 --> 00:30:13,360
Speaker 1: so they're fine. And so I would argue that Facebook

570
00:30:13,720 --> 00:30:17,560
Speaker 1: is already in the business of deciding what is and

571
00:30:17,720 --> 00:30:21,240
Speaker 1: is not acceptable, what is it is not legitimate political

572
00:30:21,280 --> 00:30:24,160
Speaker 1: issues or legitimate health issues or whatever. So the fact

573
00:30:24,160 --> 00:30:28,320
Speaker 1: that Facebook is already involved in baking this kind of

574
00:30:28,400 --> 00:30:31,360
Speaker 1: bias into how they make decisions like that does not

575
00:30:31,520 --> 00:30:34,520
Speaker 1: fill me with confidence as they continue with this new

576
00:30:34,560 --> 00:30:36,880
Speaker 1: direction of deprioritizing political content.

577
00:30:37,240 --> 00:30:40,520
Speaker 3: They're so powerful, they have so much power to shape discourse,

578
00:30:40,840 --> 00:30:45,480
Speaker 3: shape the information ecosystem in which we all live. It's

579
00:30:45,920 --> 00:30:48,560
Speaker 3: laughable to think that they could just like wash their

580
00:30:48,600 --> 00:30:53,680
Speaker 3: hands of a huge swath of content, you know, and

581
00:30:53,760 --> 00:30:58,520
Speaker 3: just like abdicate any responsibility for political content. It's you know,

582
00:30:58,560 --> 00:31:01,440
Speaker 3: it's like the Spider Man quote. With great power cups

583
00:31:01,480 --> 00:31:06,120
Speaker 3: great responsibility and they're not even attempting to meet it.

584
00:31:06,440 --> 00:31:11,240
Speaker 1: I agree, And from a larger broader perspective, we really

585
00:31:11,240 --> 00:31:14,400
Speaker 1: got to ask just that data is super clear that

586
00:31:14,480 --> 00:31:17,840
Speaker 1: the majority of these people making the decisions are white

587
00:31:17,960 --> 00:31:20,040
Speaker 1: CIS men, and not even just white CIS men, like

588
00:31:20,080 --> 00:31:23,400
Speaker 1: a very specific type of white CIS male, Like they

589
00:31:23,400 --> 00:31:26,000
Speaker 1: live on the coasts, they make a certain amount of money,

590
00:31:26,160 --> 00:31:30,560
Speaker 1: a very specific, narrow sub section of people making decisions

591
00:31:30,600 --> 00:31:32,240
Speaker 1: that impact all of us. And so I would I

592
00:31:32,240 --> 00:31:34,680
Speaker 1: would step back and say, like, are we really served

593
00:31:34,720 --> 00:31:38,440
Speaker 1: by a media landscape where this small amount of hyper narrow,

594
00:31:38,520 --> 00:31:42,560
Speaker 1: specific white men make decisions that impact everybody. I would

595
00:31:42,600 --> 00:31:44,960
Speaker 1: say no, And I just can't imagine this is going

596
00:31:45,000 --> 00:31:48,000
Speaker 1: to be a change that helps people who are traditionally marginalized,

597
00:31:48,080 --> 00:31:51,840
Speaker 1: people who already have a difficult time building platforms and

598
00:31:51,840 --> 00:31:54,640
Speaker 1: getting messages out there about what's happening in their lives

599
00:31:54,640 --> 00:31:56,880
Speaker 1: and their experiences that people need to know about. People

600
00:31:56,960 --> 00:31:58,800
Speaker 1: might not want to hear about, but people need to

601
00:31:58,880 --> 00:32:01,200
Speaker 1: know about. I can not imagine that this is going

602
00:32:01,240 --> 00:32:03,560
Speaker 1: to make the platform less possible to folks like that.

603
00:32:03,680 --> 00:32:06,080
Speaker 1: And so yeah, I guess we'll really see we will.

604
00:32:06,200 --> 00:32:09,240
Speaker 3: I mean, there's a world where Meta makes this sort

605
00:32:09,280 --> 00:32:13,960
Speaker 3: of announcement and they set up a very transparent, accountable

606
00:32:14,320 --> 00:32:19,720
Speaker 3: process whereby decisions about what sort of content is political

607
00:32:19,800 --> 00:32:23,960
Speaker 3: or not are made, and they have built in checks

608
00:32:24,080 --> 00:32:30,080
Speaker 3: to prevent exactly those kinds of bias against women, transgender people,

609
00:32:30,560 --> 00:32:33,880
Speaker 3: all the groups who typically get excluded from those kinds

610
00:32:33,880 --> 00:32:37,000
Speaker 3: of decisions. There's a world where that process is part

611
00:32:37,040 --> 00:32:42,880
Speaker 3: of this and this new policy like positively affirms some values.

612
00:32:43,440 --> 00:32:45,320
Speaker 3: But that's not the world that we live in, right.

613
00:32:45,320 --> 00:32:48,040
Speaker 3: This is we live in a world where we just

614
00:32:48,080 --> 00:32:51,360
Speaker 3: get a vague statement that basically says it's going to

615
00:32:51,400 --> 00:32:52,880
Speaker 3: be whatever they decide.

616
00:32:52,560 --> 00:32:56,440
Speaker 1: It is exactly, And we already know so much about

617
00:32:56,440 --> 00:33:00,000
Speaker 1: how Facebook has demonstrated very clear bias about how these

618
00:33:00,040 --> 00:33:02,720
Speaker 1: decisions get made. So The Guardian published this thing in

619
00:33:02,760 --> 00:33:06,960
Speaker 1: twenty seventeen called the Facebook Papers, which showed internally the

620
00:33:07,000 --> 00:33:11,200
Speaker 1: training documents that Facebook uses to train their moderators on

621
00:33:11,240 --> 00:33:13,360
Speaker 1: how to decide what content is okay and what content

622
00:33:13,400 --> 00:33:16,560
Speaker 1: breaks their rules. And it is so clear that that

623
00:33:17,200 --> 00:33:21,120
Speaker 1: training material is biased against marginalized people. It's just very clear.

624
00:33:21,400 --> 00:33:23,520
Speaker 1: We'll throw some links to the pieces in the show notes,

625
00:33:23,560 --> 00:33:28,000
Speaker 1: but so Facebook already has this precedent for coding in

626
00:33:28,240 --> 00:33:31,960
Speaker 1: bias against marginalized people into how decisions get made within

627
00:33:32,000 --> 00:33:34,400
Speaker 1: the company. And so yeah, I just don't think that

628
00:33:34,440 --> 00:33:37,320
Speaker 1: we should be leaving it up to this very small

629
00:33:37,360 --> 00:33:41,200
Speaker 1: sub section of whites, traits cis men to make decisions

630
00:33:41,200 --> 00:33:43,240
Speaker 1: about what kind of content the rest of us are seeing.

631
00:33:43,440 --> 00:33:46,040
Speaker 1: And it's not even really about Facebook taking a step back.

632
00:33:46,120 --> 00:33:48,800
Speaker 1: I would argue that that dynamic is not a healthy one.

633
00:33:48,840 --> 00:33:51,920
Speaker 1: It's not a dynamic that leads to anybody being better

634
00:33:51,960 --> 00:33:54,520
Speaker 1: informed and having a better media.

635
00:33:54,320 --> 00:33:56,840
Speaker 3: Diet, you know, it's interesting thinking about this story in

636
00:33:56,920 --> 00:33:59,520
Speaker 3: contrast with the Tamu story that we talked about. We're

637
00:33:59,520 --> 00:34:02,120
Speaker 3: on the one hand and unscrupless companies are just going

638
00:34:02,160 --> 00:34:04,520
Speaker 3: out of their way to collect all of the information

639
00:34:04,600 --> 00:34:07,200
Speaker 3: about us that they possibly can, and at the same time,

640
00:34:07,200 --> 00:34:12,400
Speaker 3: we have this trend where social media platforms are restricting

641
00:34:12,600 --> 00:34:17,000
Speaker 3: the types of information that were exposed to and the

642
00:34:17,040 --> 00:34:18,920
Speaker 3: types of discourse that we're able to have.

643
00:34:19,320 --> 00:34:21,160
Speaker 2: It's like opposite directions.

644
00:34:21,320 --> 00:34:22,920
Speaker 1: And yeah, it really goes back to what you were

645
00:34:22,960 --> 00:34:26,560
Speaker 1: saying about folks just feeling squeezed and feeling burnt out

646
00:34:26,600 --> 00:34:30,640
Speaker 1: and feeling exploited, and also feeling less nourished by these

647
00:34:30,640 --> 00:34:33,240
Speaker 1: online experiences like who wants to have an online experience

648
00:34:33,280 --> 00:34:35,640
Speaker 1: where on the one hand, when I just go look

649
00:34:35,719 --> 00:34:38,120
Speaker 1: up an app, they steal my identity And on the

650
00:34:38,120 --> 00:34:40,520
Speaker 1: other hand, I can't even be nourished by the content

651
00:34:40,560 --> 00:34:42,919
Speaker 1: that I'm seeing on the internet, like I do think

652
00:34:43,000 --> 00:34:44,240
Speaker 1: something that's got to give.

653
00:34:47,280 --> 00:35:00,960
Speaker 4: More after a quick break, get right back into it.

654
00:35:02,320 --> 00:35:07,400
Speaker 3: So the online world pretty scary, lots of threats to privacy. Fortunately,

655
00:35:07,560 --> 00:35:10,239
Speaker 3: we can feel safe when we're just walking around out

656
00:35:10,280 --> 00:35:12,439
Speaker 3: in the offline world, right You.

657
00:35:12,360 --> 00:35:16,359
Speaker 1: Sure about that that's my I think you should leave

658
00:35:16,400 --> 00:35:19,840
Speaker 1: Tim Robinson impression. But no, you can't feel safe in

659
00:35:19,880 --> 00:35:23,080
Speaker 1: the irrail world either, because data brokers are out there

660
00:35:23,160 --> 00:35:27,320
Speaker 1: selling your sensitive information to whoever. So last year, a

661
00:35:27,360 --> 00:35:30,360
Speaker 1: Law Street Journal report revealed that the anti choice organization

662
00:35:31,000 --> 00:35:34,360
Speaker 1: Veritas Society was using cell phone location data shared with

663
00:35:34,440 --> 00:35:37,640
Speaker 1: online advertisers to target people who were visiting a Wisconsin

664
00:35:37,719 --> 00:35:41,480
Speaker 1: Planned Parenthood clinic with misinformation about reproductive health. So you

665
00:35:41,480 --> 00:35:43,360
Speaker 1: would if you were in Wisconsin and you went to

666
00:35:44,040 --> 00:35:48,680
Speaker 1: Planned Parenthood, they would then bombarde you with inaccurate information

667
00:35:48,920 --> 00:35:53,040
Speaker 1: about abortion. So after that, Senator Ron Wyden started investigating,

668
00:35:53,080 --> 00:35:57,520
Speaker 1: and this week Widen found that it went far beyond Wisconsin.

669
00:35:57,719 --> 00:36:01,040
Speaker 1: Veritus was actually running the largest location data driven anti

670
00:36:01,120 --> 00:36:04,120
Speaker 1: abortion ad campaign in the nation that we know of,

671
00:36:04,400 --> 00:36:06,680
Speaker 1: and they were doing it by getting cell phone location

672
00:36:06,840 --> 00:36:10,719
Speaker 1: data from a broker called near Intelligence and using that

673
00:36:10,840 --> 00:36:14,240
Speaker 1: information to target people who had visited six hundred abortion

674
00:36:14,320 --> 00:36:18,760
Speaker 1: clinics across the country with these misleading anti abortion ads.

675
00:36:19,120 --> 00:36:22,080
Speaker 1: So Wyden is now calling on the FTC and the

676
00:36:22,120 --> 00:36:25,359
Speaker 1: SEC to quickly take action against the data broker Near

677
00:36:25,360 --> 00:36:28,480
Speaker 1: Intelligence to really make sure that the privacy of patients

678
00:36:28,560 --> 00:36:32,320
Speaker 1: whose data was exploited is being protected. He sent letters

679
00:36:32,320 --> 00:36:36,320
Speaker 1: to the SEC and FTC outlining exactly that. So I

680
00:36:36,360 --> 00:36:39,000
Speaker 1: should say this is not really new, but it is

681
00:36:39,040 --> 00:36:41,560
Speaker 1: the first time that we know of that location data

682
00:36:41,600 --> 00:36:44,760
Speaker 1: has been used in this way. As early as twenty fifteen.

683
00:36:44,840 --> 00:36:47,560
Speaker 1: You even have one ad firm bragging that they could

684
00:36:47,760 --> 00:36:51,439
Speaker 1: quote tag all the smartphones entering and leaving nearly seven

685
00:36:51,520 --> 00:36:54,239
Speaker 1: hundred planned parenthood clinics in the United States. And I

686
00:36:54,280 --> 00:36:56,000
Speaker 1: was back in twenty fifteen. So this is something that

687
00:36:56,640 --> 00:36:59,799
Speaker 1: unfortunately has been going on for a while, but we

688
00:36:59,840 --> 00:37:02,480
Speaker 1: have never seen it to this scale and scope as

689
00:37:02,520 --> 00:37:07,080
Speaker 1: we have with this Verariti Society situation. Gross I know,

690
00:37:07,239 --> 00:37:10,480
Speaker 1: it's really bad. So according to Politico, who spoke to

691
00:37:10,600 --> 00:37:13,880
Speaker 1: Justin Sherman, a researcher who studies data brokers at Duke University,

692
00:37:14,200 --> 00:37:19,359
Speaker 1: says that this campaign's scale is unprecedented. Sherman says, this

693
00:37:19,440 --> 00:37:22,040
Speaker 1: is the largest targeting campaign we've seen to date against

694
00:37:22,080 --> 00:37:25,840
Speaker 1: reproductive health clinics based on broker data. According to Politico.

695
00:37:26,000 --> 00:37:28,520
Speaker 1: In a February twenty twenty three filing, the company said

696
00:37:28,520 --> 00:37:31,000
Speaker 1: that it ensures that the data it obtains was collected

697
00:37:31,360 --> 00:37:35,359
Speaker 1: with the user's permission. However, the company Near Intelligence, their

698
00:37:35,480 --> 00:37:38,520
Speaker 1: former chief privacy officer, told Widen staff that the company

699
00:37:38,600 --> 00:37:41,120
Speaker 1: collected and sold data without consent.

700
00:37:41,680 --> 00:37:45,720
Speaker 3: Okay, the idea that people who traveled to an abortion

701
00:37:45,880 --> 00:37:51,080
Speaker 3: clinic or a planned parenthood clinic somehow willingly and with

702
00:37:51,160 --> 00:37:54,759
Speaker 3: informed consent gave permission to this company to collect their

703
00:37:54,800 --> 00:37:58,799
Speaker 3: geolocation data is absurd. Like, it's absurd that they would

704
00:37:58,800 --> 00:38:01,480
Speaker 3: even make that claim that this data was collected with

705
00:38:01,520 --> 00:38:02,440
Speaker 3: the user's permission.

706
00:38:02,760 --> 00:38:06,120
Speaker 1: So Near Intelligence, as former chief privacy officer Jay Angelo,

707
00:38:07,160 --> 00:38:09,799
Speaker 1: really just saying like a canary here, God love them

708
00:38:09,840 --> 00:38:13,439
Speaker 1: Jay Angelo. Angelo says that while the company stopped selling

709
00:38:13,520 --> 00:38:17,440
Speaker 1: location data belonging to Europeans, it continued for Americans because

710
00:38:17,440 --> 00:38:19,920
Speaker 1: of the lack of federal privacy regulations.

711
00:38:20,200 --> 00:38:25,000
Speaker 2: Mister Angelo, Boom, there it is like black and white.

712
00:38:25,239 --> 00:38:28,719
Speaker 1: Yeah, just like saying it. I honestly, I appreciate the clarity. Jay.

713
00:38:29,120 --> 00:38:31,160
Speaker 1: Mister Angelo revealed that while he had to put a

714
00:38:31,160 --> 00:38:33,839
Speaker 1: stop to the company's sale of data about Europeans, which

715
00:38:33,880 --> 00:38:36,680
Speaker 1: is subject to Europe's strong privacy law, the company was

716
00:38:36,760 --> 00:38:41,960
Speaker 1: still selling location data about Americans. This is kind of gross,

717
00:38:42,120 --> 00:38:45,200
Speaker 1: but it sounds like this sensitive data was just part

718
00:38:45,239 --> 00:38:47,400
Speaker 1: of like a going out of business sale. For this company,

719
00:38:47,840 --> 00:38:51,520
Speaker 1: Near Intelligence filed for bankruptcy in December and started selling

720
00:38:51,520 --> 00:38:54,880
Speaker 1: off its businesses and assets, which could include a trove

721
00:38:54,960 --> 00:38:58,319
Speaker 1: of data collected from planned parents and facilities. So Senator White,

722
00:38:58,360 --> 00:39:01,479
Speaker 1: it is asking the FTC to prevent from selling any

723
00:39:01,480 --> 00:39:04,880
Speaker 1: more of that data. The company's privacy policy does say

724
00:39:04,960 --> 00:39:08,080
Speaker 1: that in the event of bankruptcy or sale of assets,

725
00:39:08,239 --> 00:39:10,160
Speaker 1: that the company could transfer any of the data that

726
00:39:10,239 --> 00:39:14,600
Speaker 1: it collects to its successor. That is really gross, especially

727
00:39:14,640 --> 00:39:17,760
Speaker 1: when we're talking about something as sensitive as health data.

728
00:39:18,080 --> 00:39:21,920
Speaker 1: But apparently it is not uncommon. But this concern is

729
00:39:22,000 --> 00:39:25,640
Speaker 1: part of a larger FTC crackdown about data broker selling

730
00:39:25,680 --> 00:39:29,040
Speaker 1: health data, specifically political rights that in recent months, the

731
00:39:29,120 --> 00:39:31,960
Speaker 1: FTC has been cracking down on data brokers collecting and

732
00:39:32,000 --> 00:39:35,440
Speaker 1: sharing health related information. The agency settlement against the location

733
00:39:35,560 --> 00:39:38,880
Speaker 1: data broker x Mode highlights that the company ran ads

734
00:39:38,920 --> 00:39:42,120
Speaker 1: targeted to people who visited medical facilities, and its lawsuit

735
00:39:42,160 --> 00:39:45,560
Speaker 1: against the data broker Cochava also notes that the data

736
00:39:45,680 --> 00:39:49,160
Speaker 1: tracked people who visited reproductive healthcare clinics. So this is

737
00:39:49,200 --> 00:39:51,600
Speaker 1: really gross. It is gross to think of your sensitive

738
00:39:51,680 --> 00:39:54,319
Speaker 1: data being sold off as like just part of a

739
00:39:54,360 --> 00:39:56,759
Speaker 1: going out of business sale or a fire sale, but

740
00:39:56,840 --> 00:39:59,120
Speaker 1: it does sound like that is exactly what's going on,

741
00:39:59,280 --> 00:40:02,399
Speaker 1: and that your Intelligence is not the only company who

742
00:40:02,400 --> 00:40:03,160
Speaker 1: has been doing that.

743
00:40:03,640 --> 00:40:07,440
Speaker 3: Yeah, and I think people have a false sense of

744
00:40:07,440 --> 00:40:12,320
Speaker 3: security that HIPPA protects them in these cases. That HIPPA

745
00:40:12,360 --> 00:40:15,759
Speaker 3: is the law in the US that protects the privacy

746
00:40:15,840 --> 00:40:17,520
Speaker 3: of some health information.

747
00:40:17,760 --> 00:40:19,200
Speaker 2: But people often have.

748
00:40:19,160 --> 00:40:25,040
Speaker 3: A really overly large understanding of what HIPPA actually protects,

749
00:40:25,120 --> 00:40:26,640
Speaker 3: and in a lot of cases it just it offers

750
00:40:26,680 --> 00:40:28,719
Speaker 3: no protection at all where people would expect it to.

751
00:40:28,920 --> 00:40:32,160
Speaker 3: So we really need better privacy laws in this country.

752
00:40:32,440 --> 00:40:34,799
Speaker 3: Is really the long and short of it.

753
00:40:35,080 --> 00:40:37,560
Speaker 1: Well, that's the thing is that I don't think that

754
00:40:37,680 --> 00:40:41,960
Speaker 1: any any regular person would assume that when you go

755
00:40:42,000 --> 00:40:46,520
Speaker 1: to a help a private healthcare provider, a health care facility,

756
00:40:46,560 --> 00:40:49,840
Speaker 1: something that is so intimate and private, that that data

757
00:40:49,920 --> 00:40:51,600
Speaker 1: could be sold in this way. I think that most

758
00:40:51,600 --> 00:40:54,719
Speaker 1: people would probably assume that we had protections that would

759
00:40:54,719 --> 00:40:57,440
Speaker 1: prevent that, and it's we just deserve better, We deserve

760
00:40:57,560 --> 00:41:00,520
Speaker 1: we should have those protections. It is common sense. But

761
00:41:00,600 --> 00:41:03,120
Speaker 1: I guess if it makes some company a little bit richer,

762
00:41:03,320 --> 00:41:05,560
Speaker 1: that's the grift, Like it's like, okay, well, what won't

763
00:41:05,560 --> 00:41:08,040
Speaker 1: we sell about people? It doesn't matter how intimate or

764
00:41:08,040 --> 00:41:10,400
Speaker 1: how sensitive it is. They will sell anything if it

765
00:41:10,400 --> 00:41:11,000
Speaker 1: makes them a buck.

766
00:41:11,040 --> 00:41:14,880
Speaker 3: It's disgusting, and it also underscores the importance of jealously

767
00:41:14,960 --> 00:41:18,719
Speaker 3: protecting our privacy, even for things that aren't sensitive. Right, Like,

768
00:41:19,200 --> 00:41:24,080
Speaker 3: you know, you might imagine that geolocation data from your

769
00:41:24,120 --> 00:41:26,520
Speaker 3: cell phone about where you're going. You know, if you

770
00:41:26,560 --> 00:41:29,319
Speaker 3: go to the grocery store, you go to a coffee shop,

771
00:41:29,360 --> 00:41:32,400
Speaker 3: that's not so sensitive. So maybe it's fine, who cares

772
00:41:32,480 --> 00:41:35,080
Speaker 3: if somebody is like tracking that and associating it with

773
00:41:35,160 --> 00:41:39,440
Speaker 3: my online shopping history. But opening ourselves up to that

774
00:41:39,560 --> 00:41:44,080
Speaker 3: kind of willing surrender of our privacy to allow ourselves

775
00:41:44,160 --> 00:41:47,560
Speaker 3: to be tracked, our data to be harvested, these profiles

776
00:41:47,560 --> 00:41:49,800
Speaker 3: to be creative of us and sold from one broker

777
00:41:49,840 --> 00:41:52,759
Speaker 3: to another, even if ninety five percent of it is

778
00:41:52,800 --> 00:41:56,200
Speaker 3: not sensitive. There's some sensitive stuff in there, and once

779
00:41:56,239 --> 00:41:57,600
Speaker 3: it's out there, it's out there, and somebody's going to

780
00:41:57,640 --> 00:42:01,560
Speaker 3: find it and exploit it to do gross things like

781
00:42:01,960 --> 00:42:05,840
Speaker 3: serving misinformation to people who have visited planned parenthood clinics.

782
00:42:06,280 --> 00:42:08,200
Speaker 1: So we did a story a couple of weeks ago

783
00:42:08,200 --> 00:42:11,120
Speaker 1: about how open Ai quietly I say quietly because I

784
00:42:11,120 --> 00:42:13,279
Speaker 1: think they tried to make it quiet, but folks like

785
00:42:13,400 --> 00:42:17,200
Speaker 1: us made it loud. Quietly dropped their band I'm using

786
00:42:17,280 --> 00:42:20,960
Speaker 1: Ai for military uses. Well, this week, open AI's headquarters

787
00:42:20,960 --> 00:42:25,719
Speaker 1: in San Francisco was protested over this change. Protesters outside

788
00:42:25,840 --> 00:42:29,239
Speaker 1: of their San Francisco headquarters had signs that said things

789
00:42:29,320 --> 00:42:32,680
Speaker 1: like don't trust Sam Altman, a reference to open AI's CEO,

790
00:42:32,800 --> 00:42:36,600
Speaker 1: who was fired and then rehired and basically now seems

791
00:42:36,640 --> 00:42:38,319
Speaker 1: like maybe he thinks he can do whatever he wants

792
00:42:38,320 --> 00:42:42,359
Speaker 1: because he came back after being fired. So. Bloomberg did

793
00:42:42,360 --> 00:42:46,280
Speaker 1: a really interesting interview with the two activists who organized

794
00:42:46,280 --> 00:42:49,520
Speaker 1: this protest. Holly Elmore, who helped organize the protest, said

795
00:42:49,560 --> 00:42:52,800
Speaker 1: that the underlying problem was much bigger than open AI's

796
00:42:52,840 --> 00:42:55,920
Speaker 1: military work. It's the way that open ai publicly stated

797
00:42:55,920 --> 00:42:58,960
Speaker 1: it would not work with militaries and then retracted that commitment.

798
00:42:59,360 --> 00:43:02,759
Speaker 1: There's no teeth to those boundaries, Elmore said, even when

799
00:43:02,760 --> 00:43:05,359
Speaker 1: they are very sensible limits set by the companies, they

800
00:43:05,360 --> 00:43:08,480
Speaker 1: can just change them whenever they want so. Sam Kircher,

801
00:43:08,560 --> 00:43:12,520
Speaker 1: another organizer of the protest, sounds just like an interesting person. Sam,

802
00:43:12,560 --> 00:43:14,960
Speaker 1: if you're listening to this, you sound interesting as hell,

803
00:43:15,000 --> 00:43:16,920
Speaker 1: and I want you to come on the show. Actually,

804
00:43:16,960 --> 00:43:18,440
Speaker 1: both of you sound interesting as hell, and I want

805
00:43:18,440 --> 00:43:20,560
Speaker 1: you to come on the show. But Sam Kircher says

806
00:43:20,600 --> 00:43:24,640
Speaker 1: that she protests regularly in Seattle against artificial general intelligence.

807
00:43:24,920 --> 00:43:27,840
Speaker 1: Open AI and other companies are aiming to create AGI,

808
00:43:28,160 --> 00:43:31,240
Speaker 1: which they define as AI as smart as the average person.

809
00:43:31,680 --> 00:43:34,400
Speaker 1: Kircher says that AGI will remove meaning from the human

810
00:43:34,440 --> 00:43:38,359
Speaker 1: existence by hindering our ability to contribute and make discoveries.

811
00:43:38,600 --> 00:43:41,080
Speaker 1: And so I think it's really interesting that that Sam

812
00:43:41,160 --> 00:43:46,600
Speaker 1: Kirscher's objection is like more like existential. It's like, I

813
00:43:46,680 --> 00:43:53,239
Speaker 1: object to the existential threat to humanity that AGI specifically proses.

814
00:43:53,880 --> 00:43:57,800
Speaker 3: Yeah, Sam is certainly not the only one talking about

815
00:43:57,800 --> 00:43:59,680
Speaker 3: it as an existential threat.

816
00:44:01,480 --> 00:44:02,480
Speaker 2: In so many ways.

817
00:44:03,360 --> 00:44:06,560
Speaker 1: So I think that this protest really shows that people

818
00:44:06,640 --> 00:44:10,000
Speaker 1: are paying attention to what's happening around technology like AI

819
00:44:10,080 --> 00:44:12,920
Speaker 1: and saying, wait, this isn't good. And you know, we

820
00:44:12,960 --> 00:44:14,480
Speaker 1: can't leave that to the fact that all of this

821
00:44:14,560 --> 00:44:17,080
Speaker 1: is happening against the backdrop of what's happening in Palestine,

822
00:44:17,120 --> 00:44:18,880
Speaker 1: And so it is clear that This is not just

823
00:44:18,880 --> 00:44:22,520
Speaker 1: like theoretical, it is very much real life. For someone

824
00:44:22,560 --> 00:44:26,040
Speaker 1: like a Sam Altman, just saying JKA and deciding that

825
00:44:26,040 --> 00:44:29,480
Speaker 1: their technology can in fact be used by the military

826
00:44:29,840 --> 00:44:32,880
Speaker 1: comes with very high stakes and to be super clear,

827
00:44:33,040 --> 00:44:35,960
Speaker 1: as far as we know, open ai is not making weapons,

828
00:44:36,000 --> 00:44:38,360
Speaker 1: and they say that they will not, But as the

829
00:44:38,480 --> 00:44:41,360
Speaker 1: organizers of this protest point out, they also said that

830
00:44:41,400 --> 00:44:44,040
Speaker 1: they would not let militaries use their tools, and now

831
00:44:44,040 --> 00:44:46,480
Speaker 1: they've gone back on that, And so why should we

832
00:44:46,560 --> 00:44:48,719
Speaker 1: trust people like Sam Altman that they're going to do

833
00:44:48,760 --> 00:44:51,320
Speaker 1: what they say? And it's very clear from this protest

834
00:44:51,440 --> 00:44:53,640
Speaker 1: that people are paying attention to that and being like, yeah,

835
00:44:53,680 --> 00:44:55,839
Speaker 1: you say one thing and then you do another. It

836
00:44:55,920 --> 00:44:58,400
Speaker 1: really matters what you do and what you say, and

837
00:44:58,719 --> 00:45:00,920
Speaker 1: we feel like we cannot trust you at your word

838
00:45:01,000 --> 00:45:02,000
Speaker 1: to stick by anything.

839
00:45:02,320 --> 00:45:06,080
Speaker 3: Yeah, just you know, I guess my role today is

840
00:45:06,120 --> 00:45:08,359
Speaker 3: to connect stories with the previous story we talked about,

841
00:45:08,360 --> 00:45:10,799
Speaker 3: but like it reminds me of Facebook, which is so

842
00:45:11,440 --> 00:45:16,759
Speaker 3: powerful and an unavoidable responsibility for shaping what our information

843
00:45:16,840 --> 00:45:19,800
Speaker 3: ecosystem looks like. Open ai is really pushing the boundaries

844
00:45:19,800 --> 00:45:23,560
Speaker 3: of this incredibly powerful technology and a lot of people

845
00:45:23,840 --> 00:45:28,359
Speaker 3: like Sam Kircher feel it as an existential threat, and that,

846
00:45:28,440 --> 00:45:35,200
Speaker 3: combined with how unaccountable these companies are, is really unsettling

847
00:45:35,360 --> 00:45:38,160
Speaker 3: and scary right Like it's they have so much power,

848
00:45:38,840 --> 00:45:43,520
Speaker 3: so little accountability. It feels like a scary time to

849
00:45:43,560 --> 00:45:44,040
Speaker 3: be a human.

850
00:45:44,360 --> 00:45:49,640
Speaker 1: Well, the humans are fighting back. Speaking of connecting stories,

851
00:45:49,920 --> 00:45:52,400
Speaker 1: we got to talk about another. I'll call it a

852
00:45:52,440 --> 00:45:56,080
Speaker 1: protest that happened in San Francisco. People on the street

853
00:45:56,560 --> 00:46:01,279
Speaker 1: all got together and destroyed a way Mow self drive vehicle. Now,

854
00:46:01,320 --> 00:46:03,960
Speaker 1: the vehicle was not transporting anybody at that time, and

855
00:46:04,040 --> 00:46:06,920
Speaker 1: nobody was hurt. But listen to how Verge reports it.

856
00:46:07,360 --> 00:46:10,200
Speaker 1: A person jumped on the hood of a Waymou driverless

857
00:46:10,200 --> 00:46:14,960
Speaker 1: taxi and smashed its windshield in San Francisco's Chinatown, generating applause,

858
00:46:15,239 --> 00:46:18,160
Speaker 1: before a crowd formed around the car and covered it

859
00:46:18,200 --> 00:46:21,400
Speaker 1: in spray paint, breaking its windows, and ultimately set it

860
00:46:21,440 --> 00:46:25,279
Speaker 1: on fire. The fire department arrived minutes later, but by

861
00:46:25,320 --> 00:46:28,520
Speaker 1: then the flames had fully engulfed the car. So can

862
00:46:28,520 --> 00:46:31,000
Speaker 1: you like just the idea that somebody was like, I'm

863
00:46:31,000 --> 00:46:33,880
Speaker 1: gonna smash this car, and then a group of strangers

864
00:46:33,920 --> 00:46:36,680
Speaker 1: were all like we like this and we will help

865
00:46:36,719 --> 00:46:39,480
Speaker 1: you destroy this car, and they all came together and

866
00:46:39,520 --> 00:46:40,400
Speaker 1: set it on fire.

867
00:46:40,920 --> 00:46:42,080
Speaker 3: Like I said at the top of the show, I

868
00:46:42,120 --> 00:46:44,759
Speaker 3: do enjoy seeing people come together for collective action.

869
00:46:48,480 --> 00:46:52,319
Speaker 1: I mean, I'm sorry, I this is kind of this

870
00:46:52,400 --> 00:46:54,279
Speaker 1: is this sounds kind of cool, right, And I'm not

871
00:46:54,320 --> 00:46:55,600
Speaker 1: the only person that thinks this.

872
00:46:56,320 --> 00:46:59,040
Speaker 3: Right, Yeah, I mean, you know, you'd hate to think

873
00:46:59,080 --> 00:47:01,800
Speaker 3: that with all these problems that we've been talking about,

874
00:47:02,040 --> 00:47:06,960
Speaker 3: people feel that like their only path of recours is

875
00:47:06,960 --> 00:47:08,719
Speaker 3: to go in the street and like smash things and

876
00:47:08,760 --> 00:47:12,120
Speaker 3: burn them. Maybe that's where we are. I mean, they

877
00:47:12,120 --> 00:47:13,560
Speaker 3: did effectively get that car off the.

878
00:47:13,520 --> 00:47:18,040
Speaker 1: Street, so I should say there is no word on motive.

879
00:47:18,200 --> 00:47:21,600
Speaker 1: But this does all take place against the backdrop of

880
00:47:21,800 --> 00:47:26,760
Speaker 1: rising tensions between citizens in California and self driving car companies.

881
00:47:26,960 --> 00:47:30,160
Speaker 1: We reported on this like awful story a while back

882
00:47:30,200 --> 00:47:33,960
Speaker 1: that Cruz, who is Waimo's rival, lost their ability to

883
00:47:34,000 --> 00:47:37,839
Speaker 1: operate in California after one of its cars hit and

884
00:47:37,960 --> 00:47:42,160
Speaker 1: dragged a pedestrian, and worse, the company basically lied about

885
00:47:42,200 --> 00:47:45,160
Speaker 1: it to save their own assets. At every step of

886
00:47:45,200 --> 00:47:48,760
Speaker 1: the way, they tried to mislead regulators about what happened,

887
00:47:48,800 --> 00:47:54,200
Speaker 1: including giving them doctored footage of the incident. So yeah,

888
00:47:54,280 --> 00:47:57,920
Speaker 1: I can understand why citizens are not loving these companies.

889
00:47:58,200 --> 00:48:00,400
Speaker 1: Even as I was just putting together the research for

890
00:48:00,480 --> 00:48:03,840
Speaker 1: this segment, I found two unrelated stories that happened days

891
00:48:03,880 --> 00:48:09,280
Speaker 1: apart that involved close call almost incidents where self driving

892
00:48:09,320 --> 00:48:13,480
Speaker 1: cars almost hit children. In one, the car was fully

893
00:48:13,520 --> 00:48:16,560
Speaker 1: stopped and then it started when two people had gotten

894
00:48:16,600 --> 00:48:19,000
Speaker 1: maybe a third of the way across the intersection. She

895
00:48:19,040 --> 00:48:21,680
Speaker 1: says that the car then started to accelerate toward them

896
00:48:21,719 --> 00:48:24,439
Speaker 1: as if they were not there. Her seven year old

897
00:48:24,560 --> 00:48:27,839
Speaker 1: child had to run and serve out of the way

898
00:48:27,920 --> 00:48:31,520
Speaker 1: to avoid being hit. And this happened just the day before.

899
00:48:31,880 --> 00:48:35,120
Speaker 1: Another cruise incident was caught on camera and posted to Reddit,

900
00:48:35,160 --> 00:48:37,960
Speaker 1: where a car came barreling toward two women and a

901
00:48:38,040 --> 00:48:41,600
Speaker 1: child who were fully walking in a crosswalk. So it

902
00:48:41,680 --> 00:48:44,200
Speaker 1: is clear that people do not want these cars on

903
00:48:44,280 --> 00:48:47,959
Speaker 1: their streets. City officials and residents in San Francisco opposed

904
00:48:48,080 --> 00:48:50,160
Speaker 1: the cars being given a license for twenty four to

905
00:48:50,200 --> 00:48:53,120
Speaker 1: seven operation last year, and some residents are even doing

906
00:48:53,160 --> 00:48:57,480
Speaker 1: a less involved form of protest by putting orange cones

907
00:48:57,600 --> 00:48:59,759
Speaker 1: on top of the car's hoods as a kind of

908
00:48:59,840 --> 00:49:05,280
Speaker 1: like less Flamey protest less Flamey.

909
00:49:05,640 --> 00:49:08,000
Speaker 3: It's not good when you have a brand that people

910
00:49:08,040 --> 00:49:11,399
Speaker 3: hate so much that they like spontaneously come together to

911
00:49:11,440 --> 00:49:14,920
Speaker 3: set your product on fire, right Like you would think

912
00:49:14,920 --> 00:49:18,720
Speaker 3: that that would maybe prompt some reflection or doing things differently,

913
00:49:18,920 --> 00:49:20,279
Speaker 3: or maybe just not doing things at all.

914
00:49:20,280 --> 00:49:23,160
Speaker 1: In this case, Yeah, but I get it. I mean,

915
00:49:23,920 --> 00:49:28,160
Speaker 1: why would you want to risk your life and the

916
00:49:28,239 --> 00:49:32,400
Speaker 1: life of your child so that a self driving car

917
00:49:32,440 --> 00:49:36,200
Speaker 1: company can make money that you never get a cut up.

918
00:49:36,280 --> 00:49:38,880
Speaker 1: It's like I when I walk out on my streets,

919
00:49:38,960 --> 00:49:41,320
Speaker 1: I'd never agreed to be a crash test, an unpaid,

920
00:49:41,920 --> 00:49:45,680
Speaker 1: unconsenting crash test dummy for Cruise or way MO. I

921
00:49:45,719 --> 00:49:48,719
Speaker 1: don't think anybody agreed to that. So I can understand

922
00:49:48,840 --> 00:49:51,319
Speaker 1: why residents are fighting back in any way they can

923
00:49:51,719 --> 00:49:54,680
Speaker 1: against the system that says your life and the life

924
00:49:54,719 --> 00:49:59,000
Speaker 1: of your child is worth less than our company making money.

925
00:49:59,239 --> 00:50:02,400
Speaker 1: I can understand while people are angry and frustrated at

926
00:50:02,400 --> 00:50:04,719
Speaker 1: that dynamic because it's not one that is working for

927
00:50:04,760 --> 00:50:06,680
Speaker 1: anybody except for these car companies.

928
00:50:07,120 --> 00:50:09,560
Speaker 3: I'd be curious to see national poll data about like

929
00:50:09,640 --> 00:50:12,360
Speaker 3: what Americans think about these cars.

930
00:50:12,719 --> 00:50:15,040
Speaker 1: Well, I can't give you national poll data about that.

931
00:50:15,160 --> 00:50:17,319
Speaker 1: But you know what, I can give you national.

932
00:50:17,000 --> 00:50:19,560
Speaker 2: Poll data about what's that bridget.

933
00:50:19,320 --> 00:50:24,160
Speaker 1: The Taylor Swift psyop campaign that we're all currently witnessing.

934
00:50:24,719 --> 00:50:26,080
Speaker 1: We have talked about this a little bit on the

935
00:50:26,080 --> 00:50:29,160
Speaker 1: show before. Taylor Swift is the focal point of a

936
00:50:29,239 --> 00:50:32,200
Speaker 1: new conspiracy theory. It gets a little bit fuzzy for

937
00:50:32,239 --> 00:50:35,279
Speaker 1: me once I try to describe the actual like what

938
00:50:35,400 --> 00:50:37,600
Speaker 1: is going on here? I kind of loose a thread.

939
00:50:37,920 --> 00:50:40,280
Speaker 1: But as far as I can tell, it's that Taylor

940
00:50:40,360 --> 00:50:45,279
Speaker 1: Swift is being artificially pumped up and propped up to

941
00:50:45,400 --> 00:50:50,560
Speaker 1: help the Democrats and also vaccines. You have voices like

942
00:50:51,280 --> 00:50:55,520
Speaker 1: former Republican presidential candidate viviak Ramaswami saying this, So this

943
00:50:55,600 --> 00:50:58,000
Speaker 1: is not just coming from fringe places on the Internet.

944
00:50:58,120 --> 00:51:01,560
Speaker 1: It is being elevated at a much more mainstream level.

945
00:51:01,680 --> 00:51:05,000
Speaker 1: And now Mamath just puts some numbers behind this. They

946
00:51:05,040 --> 00:51:07,279
Speaker 1: did a national poll that found that nearly one in

947
00:51:07,440 --> 00:51:11,480
Speaker 1: five Americans, or eighteen percent, believe that Taylor Swift is

948
00:51:11,520 --> 00:51:15,200
Speaker 1: part of a covert government effort to re elect President Biden.

949
00:51:15,719 --> 00:51:18,360
Speaker 1: Among this group, seventy one percent identified with the GOP.

950
00:51:18,800 --> 00:51:21,040
Speaker 1: Eighty three percent are likely to vote for Trump, and

951
00:51:21,120 --> 00:51:24,520
Speaker 1: seventy three percent also believe that Biden won twenty twenty

952
00:51:24,600 --> 00:51:25,200
Speaker 1: by fraud.

953
00:51:25,920 --> 00:51:28,960
Speaker 3: One in five Americans believing that Taylor Swift is part

954
00:51:28,960 --> 00:51:32,400
Speaker 3: of a covert government effort is so many people like,

955
00:51:32,480 --> 00:51:36,280
Speaker 3: we are so screwed here, We're cooked.

956
00:51:36,640 --> 00:51:41,280
Speaker 1: We're cooked. This is not good. The data is not good.

957
00:51:42,000 --> 00:51:43,719
Speaker 1: It's not looking good for humanity.

958
00:51:44,080 --> 00:51:44,120
Speaker 4: No.

959
00:51:44,560 --> 00:51:46,160
Speaker 1: I will say this, though I don't want to say

960
00:51:46,160 --> 00:51:48,440
Speaker 1: too much. I don't want to get the Swifties angry

961
00:51:48,440 --> 00:51:51,160
Speaker 1: at me. I don't need Swifties and Tamu coming after

962
00:51:51,239 --> 00:51:56,360
Speaker 1: me in this episode. However, I am curious how Taylor

963
00:51:56,480 --> 00:52:01,799
Speaker 1: Swift's recent vibe has impacted this conspiracy theory, because I

964
00:52:01,840 --> 00:52:05,080
Speaker 1: do feel like something has kind of shifted where people

965
00:52:05,120 --> 00:52:07,000
Speaker 1: are kind of turning on Taylor Swift a little bit

966
00:52:07,040 --> 00:52:10,719
Speaker 1: after her speeches at the Grammys. It's it's I don't

967
00:52:10,760 --> 00:52:12,800
Speaker 1: know this. I don't I'm not tapped into the Swift

968
00:52:12,800 --> 00:52:14,680
Speaker 1: everse so like, forgive me if I'm speaking out of turn,

969
00:52:14,719 --> 00:52:16,960
Speaker 1: but I have witnessed that I think that people are

970
00:52:17,040 --> 00:52:19,000
Speaker 1: kind of turning on her a little bit, and so

971
00:52:19,160 --> 00:52:21,879
Speaker 1: I am curious as to how that fits into this

972
00:52:22,280 --> 00:52:25,759
Speaker 1: larger conspiracy theory that she is being artificially propped up

973
00:52:26,040 --> 00:52:29,040
Speaker 1: to like help Biden win. Like I remember, I think

974
00:52:29,200 --> 00:52:32,040
Speaker 1: on the day of the super Bowl Trump was on

975
00:52:32,080 --> 00:52:36,520
Speaker 1: Trump's social basically like bad mouthing Taylor Swift and being like, oh,

976
00:52:36,560 --> 00:52:39,560
Speaker 1: she's planning on endorsing Biden at the super Bowl? How

977
00:52:39,560 --> 00:52:41,680
Speaker 1: would she have even done that? Like, she's not a

978
00:52:41,760 --> 00:52:44,560
Speaker 1: perform she wasn't performing at the halftime show, She's not

979
00:52:44,840 --> 00:52:48,120
Speaker 1: a player, like she could was the plan that she

980
00:52:48,200 --> 00:52:51,000
Speaker 1: was going to wear a Biden's shirt? Like, what was

981
00:52:51,000 --> 00:52:51,800
Speaker 1: the what was the plan?

982
00:52:52,520 --> 00:52:54,880
Speaker 3: It doesn't even need to be connected to reality, right,

983
00:52:54,920 --> 00:52:58,520
Speaker 3: He just says things. Sometimes they make sense, sometimes they don't.

984
00:52:58,560 --> 00:53:01,120
Speaker 3: Where they definitely make people laying you know, And I'm

985
00:53:01,160 --> 00:53:03,959
Speaker 3: sure people who believe in this conspiracy with this new

986
00:53:04,040 --> 00:53:07,680
Speaker 3: news cycle where like you say, people or maybe like

987
00:53:07,719 --> 00:53:10,760
Speaker 3: turning on her a little bit, I'm sure that's only

988
00:53:10,880 --> 00:53:14,879
Speaker 3: more evidence that makes the people who believe this conspiracy

989
00:53:15,480 --> 00:53:19,080
Speaker 3: like further believe in it. That's just how these conspiracy

990
00:53:19,080 --> 00:53:19,719
Speaker 3: theories work.

991
00:53:19,920 --> 00:53:22,840
Speaker 1: Oh, that is absolutely the thing with conspiracy theories. I

992
00:53:22,840 --> 00:53:25,719
Speaker 1: shouldn't even be trying to ask rational logical questions about

993
00:53:25,719 --> 00:53:28,680
Speaker 1: what's going on here. Necessarily because let's say that Taylor

994
00:53:28,800 --> 00:53:31,400
Speaker 1: Swift came out and endorsed Trump somehow, that would be

995
00:53:31,560 --> 00:53:34,000
Speaker 1: used as evidence that, like, see, they were right all along.

996
00:53:34,000 --> 00:53:36,440
Speaker 1: It doesn't matter what it is. If you've ever studied

997
00:53:36,560 --> 00:53:40,800
Speaker 1: how movements like Q work, it's like any new data

998
00:53:40,840 --> 00:53:46,080
Speaker 1: point can be used to confirm their their previously held idea.

999
00:53:46,239 --> 00:53:48,879
Speaker 1: So Mike like, it's it was almost like not even

1000
00:53:48,920 --> 00:53:51,480
Speaker 1: really worth it to try to find the logic of

1001
00:53:51,520 --> 00:53:53,359
Speaker 1: what they're saying or what they think is happening here.

1002
00:53:54,040 --> 00:53:54,880
Speaker 2: One in five.

1003
00:53:55,800 --> 00:53:57,440
Speaker 1: I don't even I don't even have it much to

1004
00:53:57,480 --> 00:53:59,160
Speaker 1: say about that. It's just so bad.

1005
00:54:00,120 --> 00:54:02,360
Speaker 3: Yeah, like what kind of a conversation can we have

1006
00:54:02,440 --> 00:54:04,759
Speaker 3: with those people that? I mean, I guess to be clear,

1007
00:54:05,239 --> 00:54:07,960
Speaker 3: I'm coming from a place where I don't believe that

1008
00:54:08,080 --> 00:54:11,480
Speaker 3: Taylor Swift is part of a covert government siop not

1009
00:54:11,600 --> 00:54:15,200
Speaker 3: really aware of any evidence suggesting that she might be.

1010
00:54:15,640 --> 00:54:19,319
Speaker 3: She seems pretty apolitical like most of the time. But yeah,

1011
00:54:19,320 --> 00:54:21,080
Speaker 3: here we are like trying to make sense of it,

1012
00:54:21,200 --> 00:54:25,959
Speaker 3: and it's not like a sense making thing, like these

1013
00:54:26,080 --> 00:54:28,920
Speaker 3: eighteen percent of Americans, they just believe it.

1014
00:54:29,040 --> 00:54:31,799
Speaker 1: Well, even though this is not a sense making thing.

1015
00:54:31,920 --> 00:54:33,840
Speaker 1: I hope that we have helped people make sense of

1016
00:54:33,880 --> 00:54:37,800
Speaker 1: this wacky and wild news and media and tech climate

1017
00:54:37,880 --> 00:54:39,640
Speaker 1: that we're in. Mike, thank you for being here and

1018
00:54:39,680 --> 00:54:40,319
Speaker 1: helping us do that.

1019
00:54:40,600 --> 00:54:42,959
Speaker 2: Bridgette, thanks for having me. It's always a pleasure.

1020
00:54:42,880 --> 00:54:44,719
Speaker 1: And thanks to all of you for listening. I will

1021
00:54:44,719 --> 00:54:51,880
Speaker 1: see you on the Internet. Got a story about an

1022
00:54:51,920 --> 00:54:53,839
Speaker 1: interesting thing in tech, or just want to say hi,

1023
00:54:54,239 --> 00:54:56,480
Speaker 1: you can be just said Hello at tegody dot com.

1024
00:54:56,560 --> 00:54:58,960
Speaker 1: You can also find transcripts for today's episode at tengody

1025
00:54:59,000 --> 00:55:01,080
Speaker 1: dot com. There Are No Girls on the Internet was

1026
00:55:01,080 --> 00:55:04,000
Speaker 1: created by me bridget Toad. It's a production of iHeartRadio

1027
00:55:04,040 --> 00:55:07,640
Speaker 1: and Unbossed creative Jonathan Strickland is our executive producer. Tari

1028
00:55:07,680 --> 00:55:10,800
Speaker 1: Harrison is our producer and sound engineer. Michael Amado is

1029
00:55:10,800 --> 00:55:14,360
Speaker 1: our contributing producer. I'm your host, bridget Tood. If you

1030
00:55:14,400 --> 00:55:16,120
Speaker 1: want to help us grow, rate and review us on

1031
00:55:16,120 --> 00:55:19,759
Speaker 1: Apple Podcasts. For more podcasts from iHeartRadio, check out the

1032
00:55:19,760 --> 00:55:33,160
Speaker 1: iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.