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Speaker 1: Hey, it's Bridget. So when I'm not making There Are

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Speaker 1: No Girls on the Internet, I'm also the host of

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Speaker 1: a podcast called Beef, where we're serving up the juiciest

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Speaker 1: historical rivalries that you've never heard of. And I'm so

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Speaker 1: pleased to share that Beef is a finalist for three

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Speaker 1: Signal Awards. So could you do me a huge favor

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Speaker 1: and vote for Beef to win Best Writing, Best Emerging Podcast,

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Speaker 1: and Best Host. Just go to Ncpodcasts dot com slash Signal.

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Speaker 1: Voting is open until October fifth. Thank you so much.

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Speaker 1: It really means a lot.

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Speaker 2: There Are No Girls on the Internet.

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Speaker 1: As a production of iHeartRadio and Unbossed Creative, I'm Bridget

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Speaker 1: Todd and this is there Are No Girls on the Internet.

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Speaker 1: I am here with my producer, Joey. Joey, thank you

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Speaker 1: so much for joining us.

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

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Speaker 1: So I think we should just get right into it

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Speaker 1: because everybody on Twitter is talking about Linda Yakarino's performance

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Speaker 1: at the Big Tech conference Code. Oh my gosh, have

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Speaker 1: you seen or heard anything about this? I have not,

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Speaker 1: So usually we do a segment about like, oh, what's

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Speaker 1: Elon Musk done? Now what's Elon up to? This is

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Speaker 1: really what's Linda Yakarino up to? So Linda Yakarino for

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Speaker 1: folks who don't know, was named as the new CEO

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Speaker 1: of Twitter a while ago.

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Speaker 2: I would say, it kind of seems like.

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Speaker 1: Linda is not as publicly involved as you might expect

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Speaker 1: a CEO to be, Like it seems like Elon Musk

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Speaker 1: will say something and she like a B and now

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Speaker 1: it's a big change and she won't even like acknowledge

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Speaker 1: it or anything like that. So like the vibe has

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Speaker 1: been like is she really in charge? Is she really

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Speaker 1: the CEO? When she came on board, she definitely was

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Speaker 1: getting that treatment where she was talking about how she

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Speaker 1: really loves a challenge, like she's the person that you

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Speaker 1: call when you want someone who was like really going

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Speaker 1: to turn a ship around, And she was using a

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Speaker 1: lot of language that I I really quickly recognize as

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Speaker 1: setting up a woman to come in and clean up

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Speaker 1: the mess of a male CEO, a male leader. Like

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Speaker 1: I heard a lot of like this is someone who

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Speaker 1: really wants to be seen as someone who was really

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Speaker 1: like capable and going to come in and do a

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Speaker 1: good job.

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Speaker 2: While her performance at a tech conference.

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Speaker 1: Code did not go well and is not really doing

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Speaker 1: a good job of aligning with what I think is

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Speaker 1: her like public myth making around herself. So first, Kara

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Speaker 1: Swisher interviewed Joel Roth, former head of trust and Safety

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Speaker 1: at Twitter. Roth is someone who I've seen talked about

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Speaker 1: in some ways that I would say or not exactly accurate.

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Speaker 1: You might remember that Roth was working at Twitter in

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Speaker 1: the pre Elon Musk days and then stuck around once

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Speaker 1: Elon Musk took over. I've seen him described as a whistleblower,

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Speaker 1: but I really pushed back against that framing because when

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Speaker 1: Elon Musk took over Twitter, he was fine to go

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Speaker 1: along with all the practices that Elon Musk was putting forth.

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Speaker 1: There are other folks who left Twitter when Elon Musk

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Speaker 1: took over, who I would say, like were actual genuine

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Speaker 1: whistleblowers who were blowing the whistle on Twitter's internal practices

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Speaker 1: once Elon must took over. I would not put Yoel

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Speaker 1: Roth in that camp. You'll might remember that Joel Roth

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Speaker 1: was like on board until Musk very publicly turned on him.

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Speaker 1: Musk kind of publicly insinuated that Roth, who is openly gay,

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Speaker 1: is a sexual threat to children. And after this happened,

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Speaker 1: Roth and his family had to flee their home for

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Speaker 1: their own safety. So I will say this, had that

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Speaker 1: been me, had Elon Musk taken over my company and

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Speaker 1: then publicly smeared me as a threat to children, and

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Speaker 1: that I had to leave my home and I was

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Speaker 1: invited on a big platform to talk about Twitter, I

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Speaker 1: can just imagine what I would have said, like it

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Speaker 1: would have come up, I probably would have had a

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Speaker 1: lot to say. However, Roth really just kept it professional.

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Speaker 1: He talked about how there had been a rise and

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Speaker 1: hate speech on Twitter since Elon must took over, saying

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Speaker 1: by any measure, it is worse except by Twitter's own measure,

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Speaker 1: which is basically what we've all been saying all along.

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Speaker 1: So even though Roth just stuck to like clear stats

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Speaker 1: about Twitter, like talking about the platform, Linda Yakarino seemed

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Speaker 1: very rattled by him being there. Linda was interviewed right

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Speaker 1: after Roth, and to be honest, just came off really

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Speaker 1: unprepared and it didn't do a ton to you know,

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Speaker 1: address concerns that like Elon Musk is still running the

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Speaker 1: show and like you know, running Twitter off of his

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Speaker 1: whims without really consulting her.

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Speaker 2: Listen for yourself.

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Speaker 4: Elon Musk just announced a new monthly fee for users. Yeap,

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Speaker 4: And my question for you is do you want to

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Speaker 4: start charging all users of X as he said? And

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Speaker 4: how many users do you think.

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Speaker 2: You will lose as a result? Could you repeat?

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Speaker 4: Elon Musk announced You're moving to an entirely subscription based service. Yeah,

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Speaker 4: nothing free.

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Speaker 2: I'm about using X.

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Speaker 1: Do you say we were moving to it specifically or

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Speaker 1: is thinking about it?

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Speaker 4: He said, that's plan? Yeah, So did he consult you

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Speaker 4: before he announced that?

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Speaker 2: We talk about everything?

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Speaker 5: Marn I guess she sounds very PR trained. Sounds like

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Speaker 5: the like if I were the PR person for Twitter,

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Speaker 5: slash X whatever you want to call it right now,

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Speaker 5: I would be like, yeah, let's let's you know, do

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Speaker 5: you say it or is it just like an idea

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Speaker 5: that's out there or thinking about it?

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Speaker 3: Like I Yeah, that's so PR speak.

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Speaker 1: So Jakarino then tried to give some big, impressive number

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Speaker 1: about how advertisers were returning to the platform, but then

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Speaker 1: those numbers were refuted by external analysis. Then, when asked

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Speaker 1: about the current rise and anti Semitic content on Twitter,

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Speaker 1: including from her boss, Elon Musk. According to Business insiders

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Speaker 1: ben Bergman, she apparently looked down at her watch and said,

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Speaker 1: I need to leave to catch a flight. And that's

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Speaker 1: just like I can't imagine a more awkward thing to say, like, uh,

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Speaker 1: I think someone's.

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Speaker 2: Calling me in the other room. I gotta go.

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Speaker 3: Yeah.

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Speaker 5: No, that's like like, oh, look at my wrist, I

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Speaker 5: gotta go.

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Speaker 3: That is real.

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Speaker 2: Yeah.

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Speaker 1: So of all the things that you could say, I

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Speaker 1: feel like that's the most awkward, Like you know that emoji,

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Speaker 1: that awkward emoji that has the curly mouth. That's just like, oh,

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Speaker 1: that was basically everybody's face in the audience because it

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Speaker 1: was so awkward. People have described this as like a

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Speaker 1: scene from Arrested Development because that's how awkward it was. Now,

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Speaker 1: I think this is really just an instance of like

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Speaker 1: you work for a company, you have you have fired

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Speaker 1: or let go most, if not all, of your camm staff.

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Speaker 1: The person who like is at the very top of

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Speaker 1: the company, the owner Elon Musk, is someone who is

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Speaker 1: very erratic. I think that like, this is what you

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Speaker 1: get when all of those conditions are met. And so

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Speaker 1: some folks, some like pretty big name tech folks, accused

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Speaker 1: tech journalist Kara Swisher, you know, the organizer of the

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Speaker 1: conference of sandbagging Yakarbino by booking Roth as a surprise guest.

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Speaker 1: But this is not really what happened. Swisher confirmed that

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Speaker 1: Yacharino knew that Roth would be speaking, and was even

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Speaker 1: given the option to pick whether she wanted to speak

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Speaker 1: before him or after him, and that apparently Twitter like

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Speaker 1: decided that they wanted to have the last words. So

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Speaker 1: it's not like this was a total surprise. According to

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Speaker 1: Kara Swisher, she texted Linda Yakarino personally and she had

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Speaker 1: about twelve hours notice that, like, hey, this person's going

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Speaker 1: to be speaking too.

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Speaker 3: Yeah, like how how you were describing Roth before?

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Speaker 5: And this isn't like a dig on him, I'm sure whatever,

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Speaker 5: but it seems like he's like the most like mild,

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Speaker 5: sort of like center of the field person you could

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Speaker 5: ask to talk about this, because again it sounds like, yeah,

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Speaker 5: he didn't leave. He was sort of like I'm just

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Speaker 5: going to keep doing my job and see what happens.

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Speaker 5: And yeah, if you have a marginalized identity, you will

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Speaker 5: be targeted for that, regardless of how you know much

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Speaker 5: of a team player you are, and again, this is

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Speaker 5: like a good example of that.

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Speaker 3: But yeah, it sounds like he's sort of you don't

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Speaker 3: really know what's strict and he could go with this,

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Speaker 3: and yeah.

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Speaker 2: That's a good way to describe him.

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Speaker 1: And honestly, to me, like I said, if Elon Musk

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Speaker 1: had targeted me for my identity and put my kids

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Speaker 1: at risk, you can believe that when I got on

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Speaker 1: a stage, I wouldn't be talking about the platform stats, right, So,

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Speaker 1: like part of me is like, well, this is like

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Speaker 1: a testament to the fact that Roth is not going personal,

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Speaker 1: that he's just like sticking to the SATs. I completely

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Speaker 1: agree with your assessment of who he is in this situation.

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Speaker 2: And I was pretty.

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Speaker 1: Surprised to see a lot of big names in tech media,

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Speaker 1: people like Jason Kalakhanis from the All In podcast, which

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Speaker 1: is like a like probably the number one tech podcast

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Speaker 1: in the world, like every fucking week.

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Speaker 2: I have no problem with that, but like, it is

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Speaker 2: what it is.

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Speaker 1: And a business reporter at Axios they were on Twitter

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Speaker 1: saying like, oh, Linda Yacarno got sandbagged by Kara Swisher.

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Speaker 1: This is so unprofessional and Kara Swisher is never gonna

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Speaker 1: be able to book high profile tech leaders for this conference,

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Speaker 1: and like, this conference is really gonna be not as

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Speaker 1: big of a deal if this is how they're gonna

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Speaker 1: treat their their high profile guests.

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Speaker 2: And I really need to like push.

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Speaker 1: Back on that framing because you know, I think it

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Speaker 1: really it's one of those situations where it's like, wow,

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Speaker 1: you all have so little integrity as tech tech leaders

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Speaker 1: and journalists people are supposed to be informing the public.

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Speaker 1: You could not be making it clearer that what you

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Speaker 1: actually care about, what you actually value, is access. This

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Speaker 1: is something that Paris Marks, the host of Tech will

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Speaker 1: not save us. That podcast speaks to quite a bit,

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Speaker 1: which is like, these people could not have made it

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Speaker 1: any clearer that they don't care about holding tech leaders accountable.

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Speaker 1: They don't care about asking the kinds of questions that

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Speaker 1: are actually going to help us the public understand what's

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Speaker 1: going on. What they care about is access. And it's

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Speaker 1: not a journalist's job to make Linda Yakarino look good.

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Speaker 1: It's not a journalist's job to you know, play nice

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Speaker 1: with Dyacarino or any other tech leader and like make

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Speaker 1: them feel comfortable and make them look good and give

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Speaker 1: them like like they're not in pr they're journalists, And

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Speaker 1: so I was really surprised how quickly these journalists revealed

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Speaker 1: that they don't care about that, that all they care

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Speaker 1: about is like, Ooh, is this really gonna like hurt

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Speaker 1: Karras Swisher's ability to book big guests h And that

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Speaker 1: I found that to be really telling. You know, Linda

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Speaker 1: Yacarino is running one of the most important tech platforms

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Speaker 1: in the world. It's not any journalist's job to make

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Speaker 1: her look good. It's a journalist's job to ask her

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Speaker 1: questions that are going to be clarifying for us the public,

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Speaker 1: and to hold her accountable for the things that she

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Speaker 1: says and the things that she does.

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Speaker 5: Right, And even if it wasn't Linda Yakarino herself, like

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Speaker 5: she's the CEO of a company that's owned by Elon

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Speaker 5: Musk who has used that platform to spewges straight up

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Speaker 5: Nazi shit and yeah, apparently target a gay man in

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Speaker 5: a way that is very much rooted in homophobia.

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Speaker 3: Like it, it totally makes sense.

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Speaker 5: It's so weird to see like how accountability is like

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Speaker 5: framed because yeah, like you said, this seems like a

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Speaker 5: situation where she needs to be held accountable for what's

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Speaker 5: happening at her company, for what's happening in the name

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Speaker 5: of her company.

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Speaker 3: And yeah, like asking the most basic questions is apparently

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Speaker 3: too much.

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Speaker 5: I don't know, poor Linda Yakarino, her and her you know,

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Speaker 5: billion dollar company, so sad they're being bullied by mean journalists.

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Speaker 1: I almost see like a little bit of like sexism here,

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Speaker 1: Like I think it's I think it's I think it's

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Speaker 1: important to like not I try really heard when I'm

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Speaker 1: talking about Linda Yacarino to make sure that I'm not

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Speaker 1: trafficking in some sort of like internalized misogyny.

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Speaker 2: But the way that people are talking.

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Speaker 1: About her, it almost swings back around and it's like,

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Speaker 1: we're not talking about your best friend giving you a

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Speaker 1: heads up that your ex might be at the party

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Speaker 1: they're planning. This is somebody who is running one of

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Speaker 1: the most powerful thing EO of one of the most

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Speaker 1: powerful tech companies in the world. Where's this idea coming

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Speaker 1: from that she can't handle it if one of her

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Speaker 1: if a former staffer is there presenting his perspective as

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Speaker 1: a former staffer, it almost seems like insulting to her.

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Speaker 1: This assumption that like she needs more notice than other

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Speaker 1: tech CEOs that have gone to this conference that somebody's

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Speaker 1: being added to the lineup, and that if Joel Roth

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Speaker 1: got up there and spoke his piece about what he

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Speaker 1: saw at Twitter, that that's going to somehow rattle her.

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Speaker 1: It almost feels like like a weird kind of like

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Speaker 1: a weird assumption that I just I don't know where.

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Speaker 2: It's coming from.

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Speaker 1: And I don't see a lot of other tech leaders

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Speaker 1: getting these same kinds of like assumptions that they they

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Speaker 1: will fall they will simply fall apart if they are

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Speaker 1: asked to speak after somebody who has presented an alternative

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Speaker 1: perspective than their own. I thought to her whole thing,

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Speaker 1: she's been saying this whole time that Twitter is this

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Speaker 1: place where, oh, you need to be able to listen

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Speaker 1: when someone's got an opposing view, like you shouldn't. You

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Speaker 1: should run away from it when someone's got a different opinion.

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Speaker 1: But yet here are all these people saying, oh, well,

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Speaker 1: Linda Yakarino shouldn't have to listen to somebody's opposing opinion,

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Speaker 1: and if she does so, it is it is reasonable

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Speaker 1: for her to completely fall apart and shit the bed.

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Speaker 1: I have a lot of questions about it.

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Speaker 5: Yeah, a big part of feminism is being able to

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Speaker 5: acknowledge when women mess up too, and women are benefiting

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Speaker 5: from like, you know, classism, anti Semitism, general sort of

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Speaker 5: fascist tendencies, you know, in this case, and yeah, like

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Speaker 5: Linda Yacharino took this job knowing who Elon Musk was

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Speaker 5: and knowing what this company had kind.

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Speaker 3: Of positioned itself as at that point.

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Speaker 5: So it's sort of like, I don't know, it feels

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Speaker 5: like we're falling back into the whole like Girl Boss era,

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Speaker 5: where it's like it's okay if she does bad stuff

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Speaker 5: because she's she's doing it as a woman, and it

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Speaker 5: doesn't matter that other women are going to get brutalized

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Speaker 5: by the content that is produced by this company or whatever.

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Speaker 5: It's weird. It is a very weird thing to be watching.

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Speaker 1: It reminds me of this meme I see often that

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Speaker 1: I think about all the time. It's not exactly like, well,

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Speaker 1: whatever the meme is, I don't support all women. Some

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Speaker 1: of you bitches are very dumb. And I always think

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Speaker 1: about that of like, yeah, like this is she shot

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Speaker 1: the bed out there, and it really matters. It doesn't

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Speaker 1: just matter from like a business perspective, it matters for

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Speaker 1: all of us, like to put this in context. This

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Speaker 1: comes just days after a new study from the European

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Speaker 1: Union that said that Twitter is the number one biggest

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Speaker 1: source of disinformation when compared to other social media platforms,

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Speaker 1: with Spain, Poland, and Slovakia deemed as countries with the

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Speaker 1: highest risks.

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Speaker 2: The EUS Values.

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Speaker 1: And Transparency Commissioner Via Yorova warned Elon Musk, saying, you

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Speaker 1: have to comply with the hard law. We'll be watching

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Speaker 1: what you're doing. And what did he do in response, Well,

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Speaker 1: Elon Musk cut Twitter's election integrity and disinformation team despite

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Speaker 1: pledging that he would not do that, and removed the

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Speaker 1: election disinformation reporting tool even though we're like, what a

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Speaker 1: couple hundred days out of an election here in the

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Speaker 1: United States, and so this stuff really matters, like how

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Speaker 1: this platform is run really makes really matters to people.

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Speaker 1: On Friday, the day that this podcast comes out, Twitter's

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Speaker 1: new privacy policy goes into effect, which allows Twitter to

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Speaker 1: take a lot more data from us, including our employment information,

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Speaker 1: our job information, maybe read our DMS, our biometric data,

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Speaker 1: and of course use all of that data that they

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Speaker 1: take from us to train their AI, and a whole

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Speaker 1: lot more.

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Speaker 2: All of this.

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Speaker 1: After Twitter's former head of security turned actual whistleblower went

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Speaker 1: before the Senate and testified that Twitter is misleading the

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Speaker 1: public about the platform's extreme and egregious security deficiencies. So

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Speaker 1: all of this is to say that it really matters

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Speaker 1: how Twitter is being run, not just because it's this

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Speaker 1: big company, but because it really matters for global election

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Speaker 1: integrity and for our own personal security. So this is

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Speaker 1: not a business story. This is not a story about

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Speaker 1: like it's Kara Swisher gonna be able to get big

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Speaker 1: important guests on her show, where well, the CODE conference

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Speaker 1: continue to be really big and important. It's not a

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Speaker 1: story about whether or not this journalist was like nice

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Speaker 1: to Linda Yakarino. Our global democracy is at risk and

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Speaker 1: these people are just talking about like whether or not

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Speaker 1: CODE is going to be able to book guests is

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Speaker 1: because the journalist asked her about it. Like the conversation

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Speaker 1: is so deeply unserious, and I feel like we are

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Speaker 1: watching tech journalists fail us in real time and be

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Speaker 1: really public and open about it, Like they don't even

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Speaker 1: have the good sense to not publicly go out and

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Speaker 1: say like Oh, the most important thing is access, And

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Speaker 1: because they asked Linda Yacarino hard questions, they're blowing that

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Speaker 1: access the most important thing that matters to me as

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Speaker 1: a tech journalist, Like it is so deeply unserious and

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Speaker 1: they're putting us all at risk and not even having

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Speaker 1: the good sense to like not say that publicly voluntarily.

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Speaker 5: Yeah, I think coming from within the journalism industry in

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Speaker 5: particular and like having that perspective, this is really interesting

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Speaker 5: because it kind of reminds me of like, and you

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Speaker 5: mentioned the election, which this doesn't directly have to do

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Speaker 5: with the election, but you know, again Twitter is going

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Speaker 5: to be a big platform for that. This reminds me

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Speaker 5: of back in twenty sixteen when Trump was elected and

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Speaker 5: there was sort of this like conversation I think within

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Speaker 5: the journalism industry and within newsrooms about like what's the

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Speaker 5: media's responsibility and you know, what's the difference between holding

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Speaker 5: people accountable and like getting both sides or like hearing

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Speaker 5: all the sides, And like this this seems like we're

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Speaker 5: falling back into that idea of like getting all the

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Speaker 5: sides and hearing letting everybody just speak their mind without

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Speaker 5: question is more important than like actually holding people accountable

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Speaker 5: and actually asking people the hard questions about like their

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Speaker 5: actual policies that are going to affect people. Yeah, that's

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Speaker 5: concerning to me too. And again, like this doesn't directly

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Speaker 5: have to do with the election, but Twitter is going

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Speaker 5: to be a big platform when it comes to relection.

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Speaker 5: And are we going to see that sort of cycle

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Speaker 5: again where people are just like, yeah, we're gonna just

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Speaker 5: hear all the sides and not hold anybody accountable because

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Speaker 5: that never ends.

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Speaker 1: Well, yeah, I worry that folks in media have not

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Speaker 1: really learned a lot of hard truths, So we will see.

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Speaker 1: Let's take a quick break at our back, so we

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Speaker 1: have a little update for you. Last week during our newscast,

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Speaker 1: we told you that Andrew Tates MLM scam app called

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Speaker 1: The Real World formerly called Hustler's University, was taken off

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Speaker 1: of Google's play Store for being a predatory pyramid scheme

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Speaker 1: that charged subscribers fifty dollars a month and offered them

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Speaker 1: the chance to make millions through these like very scammy

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Speaker 1: sounding courses on things like copywriting, cryptocurrency, and also prompted

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Speaker 1: users to share Andrew Tate's content on social media. At

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Speaker 1: the time of publishing our episode, the app was still

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Speaker 1: available on Apple's app store well right after our episode

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Speaker 1: went live. On Friday of last week, Apple joined Google

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Speaker 1: in taking Tit's app down from the app store. Thank you, Apple.

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Speaker 1: Tits people say that they are appealing both of these decisions,

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Speaker 1: but for now, it is good news that that tit

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Speaker 1: is being cut from this income stream that just really

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Speaker 1: just takes advantage of young people.

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Speaker 3: Yeah.

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Speaker 5: First of all, adding on to last week's kind of

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Speaker 5: discussion of this, to be the third person now on

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Speaker 5: this podcast to say, I don't know why copywriting is

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Speaker 5: listed in there, because.

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Speaker 3: Oh I got experience with that. You do not make

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Speaker 3: billions of time.

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Speaker 2: Yeah.

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Speaker 1: Listener Sarah said the same thing as I like, what

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Speaker 1: is going on with copywriting? People don't make millions and

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Speaker 1: millions of dollars from copywriting and him promising people that

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Speaker 1: they're going to make that is truly a wild claim

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Speaker 1: to be making on his app.

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Speaker 2: Yeah.

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Speaker 5: I think generally media, if a company is telling you that,

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Speaker 5: like a media related job is going to make you

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Speaker 5: a lot of money, that's probably not true.

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Speaker 2: A rule of thumb.

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Speaker 5: Yeah, No, I that's good to hear. I feel like

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Speaker 5: this whole Entwtate saga. This is this is one of

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Speaker 5: those things where it's like this whole thing that's going

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Speaker 5: out the Andrew Tait has felt very big and like

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Speaker 5: very difficult to address, and it's like there's just so much,

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Speaker 5: so much harm he's causing that this is like an

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Speaker 5: example of like how any sort of action is good.

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Speaker 5: And I think, I don't know, I think it's it's

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Speaker 5: easy to get sort of caught up in all of

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Speaker 5: the bad stuff that's coming out of this, but it

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Speaker 5: is it's good to hear one when good things happened

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Speaker 5: because because of you know, people's advocacy and people trying

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Speaker 5: to combat this stuff.

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Speaker 1: Yeah, I take my w's where I can get them,

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Speaker 1: even the small ones. And if folks are interested to

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Speaker 1: hear more about Taate and the sort of ecosystem of

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Speaker 1: manosphere grifters that have popped up around him, folks like

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Speaker 1: just pearly Things and Sneako all of your mixed bag

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Speaker 1: of misogynistic right wing extremist online grifters. Check out our

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Speaker 1: episode of their No Girls on the Internet that came

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Speaker 1: out this week with Justin Horowitz and extremism researcher at

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Speaker 1: Media Matters. He breaks down all of it. So if

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Speaker 1: folks want to know more about Tate, what he's doing,

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Speaker 1: and the impact that it has on all of us,

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Speaker 1: definitely check out this week's episode. So over in Texas,

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Speaker 1: yelp the review website that is mostly known for I

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Speaker 1: guess like reviewing restaurants and coffee shops. While Yelp is

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Speaker 1: preemptively suing Texas to ensure that the site can continue

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Speaker 1: to tell users that crisis pregnancy centers also known as

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Speaker 1: CPCs listed on their site do not provide abortions or

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Speaker 1: abortion referrals. So if you're unfamiliar with a crisis pregnancy center,

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Speaker 1: according to the American College of Obstetricians and Gynecologists, always

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Speaker 1: have trouble saying, that word CPC is a term used

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Speaker 1: to refer to a certain facilities that represent themselves as

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Speaker 1: legitimate reproductive healthcare clinics providing care for pregnant people, but

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Speaker 1: actually aim to dissuade people from accessing certain types of

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Speaker 1: reproductive care, including abortion care and even contraceptives' options. So currently,

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Speaker 1: Yelp puts a label on crisis pregnancy centers that reads, quote,

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Speaker 1: this is a crisis pregnancy center. Crisis pregnancy centers do

438
00:22:23,560 --> 00:22:26,960
Speaker 1: not offer abortions or referrals to abortion providers. This is

439
00:22:27,080 --> 00:22:30,919
Speaker 1: just like fact based information. That is just like a fact.

440
00:22:30,960 --> 00:22:33,760
Speaker 1: I don't think that any CPC would object to that

441
00:22:33,760 --> 00:22:36,400
Speaker 1: that they do not offer abortions or referrals for abortions.

442
00:22:36,400 --> 00:22:38,600
Speaker 1: That its just like a true fact about their services.

443
00:22:38,880 --> 00:22:42,400
Speaker 1: But YELP suspects that Texas is going to sue them

444
00:22:42,680 --> 00:22:45,119
Speaker 1: to prevent them from applying this label, so they are

445
00:22:45,160 --> 00:22:49,000
Speaker 1: preemptively suing Texas first. According to CNN, in a complaint

446
00:22:49,000 --> 00:22:51,840
Speaker 1: filed Wednesday in San Francisco federal court, YELP said it

447
00:22:51,840 --> 00:22:55,240
Speaker 1: as suing the Texas Attorney General Ken Paxton preemptively to

448
00:22:55,280 --> 00:22:57,880
Speaker 1: head off a lawsuit it anticipates from his office as

449
00:22:57,880 --> 00:23:00,400
Speaker 1: soon as Friday that may seek to borrow YELP from

450
00:23:00,400 --> 00:23:03,400
Speaker 1: applying its label to crisis pregnancy centers. If the name

451
00:23:04,040 --> 00:23:07,800
Speaker 1: Attorney General Ken Paxton of Texas sounds familiar to you,

452
00:23:08,480 --> 00:23:11,359
Speaker 1: that is because he just got finished facing a very

453
00:23:11,400 --> 00:23:15,400
Speaker 1: serious impeachment threat from his own party for corruption.

454
00:23:15,720 --> 00:23:17,080
Speaker 2: Now he wasn't impeached.

455
00:23:17,680 --> 00:23:20,639
Speaker 1: That he won that battle, but he's still facing a

456
00:23:20,680 --> 00:23:24,720
Speaker 1: felony fraud case and an FBI investigation for securities fraud.

457
00:23:24,760 --> 00:23:26,920
Speaker 2: So, Ken Paxton has a lot going on.

458
00:23:27,200 --> 00:23:30,399
Speaker 1: Like, you know, if I were Ken Paxson, I'd probably

459
00:23:30,480 --> 00:23:32,520
Speaker 1: focused on that, but this is what he's doing instead.

460
00:23:32,840 --> 00:23:36,640
Speaker 5: Yeah, that's so crazy, Like just from hearing you explain

461
00:23:36,720 --> 00:23:40,600
Speaker 5: that they're not doing anything illegal. In fact, they're just yeah,

462
00:23:40,640 --> 00:23:43,520
Speaker 5: like they're just explaining what the service is, which is

463
00:23:43,840 --> 00:23:46,879
Speaker 5: what you're supposed to do if you're a service and

464
00:23:46,960 --> 00:23:50,800
Speaker 5: you want to get business. But you know, it's almost

465
00:23:50,840 --> 00:23:52,919
Speaker 5: like they don't want us to know that they don't

466
00:23:53,240 --> 00:23:55,919
Speaker 5: have abortions and they actually do other things.

467
00:23:56,560 --> 00:23:57,040
Speaker 3: Crazy.

468
00:23:57,760 --> 00:24:02,439
Speaker 5: I thought false advertising was illegal, apparently not in this case.

469
00:24:03,080 --> 00:24:05,600
Speaker 1: Yeah, okay, So what's interesting about what you just said

470
00:24:05,680 --> 00:24:09,840
Speaker 1: is that back in February, Paxton went after yelp for

471
00:24:10,040 --> 00:24:13,640
Speaker 1: putting a different label on crisis pregnancy centers. Their initial

472
00:24:13,720 --> 00:24:18,320
Speaker 1: label described crisis pregnancy centers as quote typically providing limited

473
00:24:18,359 --> 00:24:22,640
Speaker 1: medical services and may not have licensed medical professionals on site,

474
00:24:22,720 --> 00:24:26,080
Speaker 1: which is also true, but Paxton objected to that back

475
00:24:26,119 --> 00:24:29,679
Speaker 1: in February, and so when yelp changed their label to

476
00:24:29,720 --> 00:24:32,520
Speaker 1: read what I've read before about how crisis pregnancy centers

477
00:24:32,760 --> 00:24:36,840
Speaker 1: do not offer abortions or referral for abortions Paxton himself

478
00:24:37,119 --> 00:24:41,159
Speaker 1: commended that disclosure as quote accurate in a press release

479
00:24:41,200 --> 00:24:44,080
Speaker 1: that reads, YELP has agreed to remove its misleading label

480
00:24:44,119 --> 00:24:47,600
Speaker 1: of crisis pregnancy centers and replace it with an accurate description.

481
00:24:47,920 --> 00:24:51,879
Speaker 1: So just as you said, right that, like Paxton himself said,

482
00:24:51,960 --> 00:24:55,040
Speaker 1: oh well this new label, this label is accurate, but

483
00:24:55,200 --> 00:24:58,159
Speaker 1: now he is still coming after YELP for this label

484
00:24:58,200 --> 00:25:01,560
Speaker 1: that he himself in February said was accurate and was fine.

485
00:25:01,800 --> 00:25:04,560
Speaker 1: So the way that crisis pregnancy centers work is that

486
00:25:04,600 --> 00:25:08,600
Speaker 1: they really, they really take advantage of like scammy SEO

487
00:25:08,720 --> 00:25:11,919
Speaker 1: practices to prey on people, many of whom are in

488
00:25:12,040 --> 00:25:16,760
Speaker 1: desperate situations, to confuse them with inaccurate information. Crisis pregnancy

489
00:25:16,760 --> 00:25:19,800
Speaker 1: centers their whole mission is to basically waste the time

490
00:25:19,840 --> 00:25:22,840
Speaker 1: of somebody who was pregnant, to create an intentional.

491
00:25:22,359 --> 00:25:24,679
Speaker 2: Delay that will delay them in getting.

492
00:25:24,400 --> 00:25:27,159
Speaker 1: An abortion, in an attempt to trigger term restrictions that

493
00:25:27,200 --> 00:25:30,840
Speaker 1: will prevent them from getting abortion care altogether. So yelp's

494
00:25:30,880 --> 00:25:33,960
Speaker 1: lawsuit is asking the court to affirm that it's labeling

495
00:25:33,960 --> 00:25:36,719
Speaker 1: of crisis pregnancy centers was not misleading and that it

496
00:25:36,720 --> 00:25:40,120
Speaker 1: was an exercise of constitutionally protected speech. It is also

497
00:25:40,240 --> 00:25:42,480
Speaker 1: asking the court to block Texas from suing over the

498
00:25:42,520 --> 00:25:45,399
Speaker 1: labels in the future, and I think, yeah, it's just

499
00:25:45,440 --> 00:25:48,600
Speaker 1: another example of the ways that like abortion is a

500
00:25:48,640 --> 00:25:51,080
Speaker 1: tech issue, and that if you are trying to talk

501
00:25:51,080 --> 00:25:53,560
Speaker 1: about technology but you're you're doing so in a way

502
00:25:53,600 --> 00:25:56,000
Speaker 1: that does not talk about abortion care, then you're not

503
00:25:56,040 --> 00:25:58,960
Speaker 1: fully talking about technology because abortion is a tech issue.

504
00:25:59,080 --> 00:26:01,959
Speaker 1: You know, tech company should really be in the business

505
00:26:01,960 --> 00:26:04,840
Speaker 1: of providing accurate information about people's health, and a lot

506
00:26:04,880 --> 00:26:07,280
Speaker 1: of times we know that they don't. So in this case,

507
00:26:07,400 --> 00:26:10,400
Speaker 1: when yelp is actually trying to help people get accurate

508
00:26:10,440 --> 00:26:14,120
Speaker 1: information about you know, crisis pregnancy centers, it's really sad

509
00:26:14,119 --> 00:26:17,439
Speaker 1: that states like Texas are stepping in to prevent them

510
00:26:17,440 --> 00:26:18,000
Speaker 1: from doing that.

511
00:26:18,520 --> 00:26:21,000
Speaker 5: Yeah, and again it's like it's not like Yelp is

512
00:26:21,040 --> 00:26:24,480
Speaker 5: doing anything that's illegal. I use Google Maps all the

513
00:26:24,520 --> 00:26:28,720
Speaker 5: time because like I never know where I am. But

514
00:26:29,200 --> 00:26:31,159
Speaker 5: I mean one thing that like I rely on a

515
00:26:31,200 --> 00:26:34,200
Speaker 5: lot is like the descriptions of places that I'm going

516
00:26:34,240 --> 00:26:37,000
Speaker 5: to matching the place that I'm actually going to, And

517
00:26:37,040 --> 00:26:39,399
Speaker 5: it is really frustrating when they don't. You shouldn't be

518
00:26:39,440 --> 00:26:42,000
Speaker 5: hiding under the guys of medical care if that's not

519
00:26:42,160 --> 00:26:42,959
Speaker 5: what you're doing.

520
00:26:43,400 --> 00:26:47,160
Speaker 3: But yeah, I hate yeah, wow, it's it's scary.

521
00:26:47,320 --> 00:26:51,280
Speaker 5: Everything that's happening in Texas with this is terrifying. And

522
00:26:51,320 --> 00:26:55,200
Speaker 5: again all the support to like abortion activists, reproductive rights

523
00:26:55,480 --> 00:27:01,000
Speaker 5: activists in Texas, you guys are like, I admire the

524
00:27:01,000 --> 00:27:03,480
Speaker 5: work he all are doing so much, so important.

525
00:27:03,760 --> 00:27:06,960
Speaker 1: Absolutely, Like, if you've got some spare coin and you're

526
00:27:07,000 --> 00:27:09,159
Speaker 1: looking for a good home for it, donate to an

527
00:27:09,200 --> 00:27:12,920
Speaker 1: abortion fund because Lord knows they're doing important work and

528
00:27:12,960 --> 00:27:15,560
Speaker 1: they could use it. And I think this thing in Texas,

529
00:27:15,640 --> 00:27:18,840
Speaker 1: I really think that Paxton is just trying to do

530
00:27:18,880 --> 00:27:23,159
Speaker 1: a stunt to take away from his corruption investigation. I

531
00:27:23,200 --> 00:27:26,600
Speaker 1: think that, like he is newly back from almost being

532
00:27:27,040 --> 00:27:29,840
Speaker 1: impeached by his own party, and I think that he

533
00:27:29,960 --> 00:27:33,080
Speaker 1: is just like looking for some big, grand standing stunt.

534
00:27:33,320 --> 00:27:37,000
Speaker 1: And he already confirmed that the way that yelp is

535
00:27:37,040 --> 00:27:39,160
Speaker 1: describing CPCs is accurate.

536
00:27:39,320 --> 00:27:41,359
Speaker 2: So it's like we're visiting this now. It just seems

537
00:27:41,400 --> 00:27:41,919
Speaker 2: like a stunt.

538
00:27:41,960 --> 00:27:43,440
Speaker 1: And I think it just goes back to the idea

539
00:27:43,440 --> 00:27:45,600
Speaker 1: that a lot of these extremists, they don't have a

540
00:27:45,600 --> 00:27:49,320
Speaker 1: lot to offer their citizens other than stunts and grandstanding.

541
00:27:49,400 --> 00:27:50,840
Speaker 1: And I think that's exactly what this is.

542
00:27:51,520 --> 00:27:56,119
Speaker 5: Yeah, it's almost like the backlash against free productive rights

543
00:27:56,200 --> 00:27:59,680
Speaker 5: and trans people and all of this is just a

544
00:28:00,680 --> 00:28:02,240
Speaker 5: time to get more votes.

545
00:28:02,400 --> 00:28:02,960
Speaker 3: But you know.

546
00:28:05,080 --> 00:28:08,280
Speaker 1: So, folks might be familiar with Wirecutter. The New York

547
00:28:08,320 --> 00:28:10,760
Speaker 1: Times is Vertical, where they rate and review tech gadgets.

548
00:28:11,600 --> 00:28:15,880
Speaker 1: Wirecutter had been giving whyse the security camera system positive

549
00:28:15,920 --> 00:28:18,480
Speaker 1: reviews for six years, but all of that changed this

550
00:28:18,520 --> 00:28:22,480
Speaker 1: week because Wirecutter announced that they were pulling their recommendations

551
00:28:22,520 --> 00:28:26,679
Speaker 1: for whys from all their site's guides. Why Well because

552
00:28:26,760 --> 00:28:30,159
Speaker 1: Wirecutter explains that on September eighth, The Verge reported an

553
00:28:30,240 --> 00:28:33,160
Speaker 1: incident in which WYSE customers were able to access live

554
00:28:33,280 --> 00:28:37,240
Speaker 1: video from other users cameras through the WYSE web portal.

555
00:28:37,600 --> 00:28:41,000
Speaker 1: When Wirecutter reached out to WYS for details, a representative

556
00:28:41,080 --> 00:28:44,240
Speaker 1: characterized the incident as small in scope, saying they believe

557
00:28:44,320 --> 00:28:47,600
Speaker 1: no more than ten users were affected. So that's not great. Like,

558
00:28:47,880 --> 00:28:50,600
Speaker 1: even if it's only ten people strangers being able to

559
00:28:50,640 --> 00:28:53,440
Speaker 1: access your security camera and see what you're doing, it's

560
00:28:53,480 --> 00:28:57,320
Speaker 1: like pretty bad. But here's the kicker. Other than one

561
00:28:57,440 --> 00:29:01,560
Speaker 1: post on its user to user online forum Wise Communities

562
00:29:01,680 --> 00:29:04,320
Speaker 1: and Communications to those that they say were affected. The

563
00:29:04,360 --> 00:29:07,520
Speaker 1: company has not reached out to Wise customers, nor has

564
00:29:07,520 --> 00:29:12,000
Speaker 1: it provided meaningful details about the incident wirecutter rights. We

565
00:29:12,040 --> 00:29:15,240
Speaker 1: believe Wise is acting irresponsibly to its customers. As such,

566
00:29:15,320 --> 00:29:18,440
Speaker 1: we've made the difficult but unavoidable decision to revoke our

567
00:29:18,480 --> 00:29:22,120
Speaker 1: recommendation of all Wise cameras until the company implements meaningful

568
00:29:22,200 --> 00:29:25,960
Speaker 1: changes to its security and privacy procedures. The concern is

569
00:29:26,000 --> 00:29:28,600
Speaker 1: not that Wise had a security incident. Just about every

570
00:29:28,640 --> 00:29:30,640
Speaker 1: company or organization in the world we're probably at the

571
00:29:30,680 --> 00:29:32,600
Speaker 1: deal with some sort of security trip up, as we've

572
00:29:32,600 --> 00:29:35,480
Speaker 1: seen with big banks, the military, Las Vegas, casinos, schools,

573
00:29:35,520 --> 00:29:38,080
Speaker 1: and even Chick fil A. The greater issue is how

574
00:29:38,160 --> 00:29:41,160
Speaker 1: this company responds to a crisis. With this incident and

575
00:29:41,240 --> 00:29:43,280
Speaker 1: others in the past, it is clear that Wise has

576
00:29:43,320 --> 00:29:46,600
Speaker 1: failed to develop the sorts of robust procedures that adequately

577
00:29:46,640 --> 00:29:49,400
Speaker 1: protect its customers the way they deserve.

578
00:29:50,440 --> 00:29:50,800
Speaker 2: Damn.

579
00:29:51,920 --> 00:29:53,400
Speaker 3: Yeah, that's scary.

580
00:29:53,920 --> 00:29:57,840
Speaker 5: Yeah, I feel like security cameras, cameras in general, that's

581
00:29:57,880 --> 00:30:01,680
Speaker 5: just such a sensitive issue. It's like any like, if

582
00:30:01,680 --> 00:30:06,440
Speaker 5: there's any break of that privacy, that should be notified

583
00:30:06,480 --> 00:30:11,200
Speaker 5: to people that have the cameras that you sell exactly.

584
00:30:11,440 --> 00:30:14,000
Speaker 2: So I need to make this really clear. This is

585
00:30:14,200 --> 00:30:15,720
Speaker 2: very unusual. Right.

586
00:30:15,760 --> 00:30:18,840
Speaker 1: We talk about a lot of companies who behave in

587
00:30:18,880 --> 00:30:22,080
Speaker 1: ways that are irresponsible, but this is irresponsible even by

588
00:30:22,160 --> 00:30:26,560
Speaker 1: like irresponsible company standards. Wirecutters spoke to other folks in

589
00:30:26,600 --> 00:30:29,640
Speaker 1: the privacy space, including Gen cult Writer, program director at

590
00:30:29,640 --> 00:30:32,440
Speaker 1: Mozilla's Privacy not included, whose work we've talked about on

591
00:30:32,440 --> 00:30:34,480
Speaker 1: a show before. All of the folks they spoke to

592
00:30:34,560 --> 00:30:38,280
Speaker 1: agree that it is completely unusual and unacceptable that Whyse

593
00:30:38,680 --> 00:30:41,400
Speaker 1: did not reach out to their customer base proactively and

594
00:30:41,560 --> 00:30:44,040
Speaker 1: never said anything about how they are planning to prevent

595
00:30:44,160 --> 00:30:47,120
Speaker 1: these issues in the future. And this is not even

596
00:30:47,120 --> 00:30:49,479
Speaker 1: the first time that Wise has had issues like this.

597
00:30:49,920 --> 00:30:53,000
Speaker 1: In March twenty twenty two, a bit Defender study showed

598
00:30:53,040 --> 00:30:56,560
Speaker 1: that WYSE took nearly three years to fully address specific

599
00:30:56,640 --> 00:31:00,520
Speaker 1: vulnerabilities that affected all three models of Wise cameras. Eventually,

600
00:31:00,560 --> 00:31:03,320
Speaker 1: they did alert customers and told them that they're you know,

601
00:31:03,600 --> 00:31:06,920
Speaker 1: their security like that model of security camera was no

602
00:31:07,000 --> 00:31:09,160
Speaker 1: longer safe and that they should not be using them,

603
00:31:09,200 --> 00:31:10,960
Speaker 1: and that they did keep using them, they were doing

604
00:31:11,000 --> 00:31:14,440
Speaker 1: so like at their own risk. So like you were saying, Joey,

605
00:31:14,680 --> 00:31:18,160
Speaker 1: I would pretty much never advocate for someone putting an

606
00:31:18,160 --> 00:31:21,120
Speaker 1: additional camera in their home that they didn't need. But

607
00:31:21,600 --> 00:31:25,440
Speaker 1: when you do, like that is a trust relationship, as

608
00:31:25,440 --> 00:31:28,640
Speaker 1: you were saying, that you're entering into with the company, right,

609
00:31:28,680 --> 00:31:31,200
Speaker 1: you need to know that if that trust is broken,

610
00:31:31,680 --> 00:31:33,600
Speaker 1: that the company is going to handle it in a

611
00:31:33,640 --> 00:31:36,240
Speaker 1: way that is responsible. Like that's the only way that

612
00:31:36,760 --> 00:31:39,560
Speaker 1: having a camera in your house makes any sense at all,

613
00:31:39,640 --> 00:31:41,760
Speaker 1: is that the company is like acting in a way

614
00:31:41,760 --> 00:31:44,720
Speaker 1: that really makes it clear that they understand that that

615
00:31:44,720 --> 00:31:47,800
Speaker 1: that you're putting their your trust in them. As wier

616
00:31:47,880 --> 00:31:51,720
Speaker 1: Cutter points out, the fundamental relationship between smart home companies

617
00:31:51,760 --> 00:31:54,640
Speaker 1: and their customers is founded on trust. No company can

618
00:31:54,680 --> 00:31:57,200
Speaker 1: guarantee safety and security but one hundred percent of the time,

619
00:31:57,480 --> 00:31:59,920
Speaker 1: but customers need to be confident that those who make

620
00:32:00,040 --> 00:32:03,400
Speaker 1: and sell these products, especially security devices, are worthy of

621
00:32:03,440 --> 00:32:06,280
Speaker 1: their trust. Why is its inability to meet these basic

622
00:32:06,320 --> 00:32:09,760
Speaker 1: standards puts its customers and its devices at risk and

623
00:32:09,880 --> 00:32:13,400
Speaker 1: also cast doubt on the smart home industry as a whole.

624
00:32:13,520 --> 00:32:17,200
Speaker 1: So Wirecutter actually listed out some specific steps that Wise

625
00:32:17,200 --> 00:32:19,440
Speaker 1: would need to take in order for them to consider,

626
00:32:19,800 --> 00:32:22,760
Speaker 1: like reconsider looking at their products in the future. It's

627
00:32:22,760 --> 00:32:25,840
Speaker 1: like very basic stuff, honestly, like reaching out to all

628
00:32:25,840 --> 00:32:28,320
Speaker 1: customers proactively if there is a breach and describing the

629
00:32:28,360 --> 00:32:31,080
Speaker 1: issue in detail, including what steps are being taken to

630
00:32:31,120 --> 00:32:33,240
Speaker 1: prevent it from happening. Again, Like to me, it sounds

631
00:32:33,240 --> 00:32:36,240
Speaker 1: like very basic stuff. And I also think that it

632
00:32:36,320 --> 00:32:39,720
Speaker 1: is a pretty big step for an outlet that like

633
00:32:39,840 --> 00:32:43,480
Speaker 1: Wirecutter that most folks probably know for like Gadget Reviews,

634
00:32:43,520 --> 00:32:46,760
Speaker 1: to take this kind of action, And honestly, maybe it

635
00:32:46,800 --> 00:32:49,680
Speaker 1: should be more commonplace, Like even if you're mostly a

636
00:32:49,720 --> 00:32:53,480
Speaker 1: review outlet, it is still sort of service oriented tech

637
00:32:53,560 --> 00:32:57,320
Speaker 1: journalism for regular people to inform their purchasing decision making, right,

638
00:32:57,360 --> 00:32:59,760
Speaker 1: And so I think it's nice to see an outlet

639
00:33:00,000 --> 00:33:03,720
Speaker 1: making that responsibility seriously and using that as as a

640
00:33:03,760 --> 00:33:06,840
Speaker 1: way to advocate for a tech company just being accountable

641
00:33:06,840 --> 00:33:08,960
Speaker 1: to the people who are buying them buying their stuff.

642
00:33:09,680 --> 00:33:14,320
Speaker 5: Yeah, uh rare wind for the New York Times.

643
00:33:13,960 --> 00:33:20,120
Speaker 3: I guess Times Property Bridget. Did you ever watch.

644
00:33:21,800 --> 00:33:24,480
Speaker 5: There was the like Disney Channel movie that I watched

645
00:33:24,600 --> 00:33:26,480
Speaker 5: I was a kid that was called like smart Home.

646
00:33:26,600 --> 00:33:30,520
Speaker 2: Yeah, smart House. You know, I watched Smart House as

647
00:33:30,520 --> 00:33:31,600
Speaker 2: the word smart Home.

648
00:33:31,720 --> 00:33:33,520
Speaker 3: But I was like, I think that's why.

649
00:33:33,720 --> 00:33:36,120
Speaker 5: Now I think I'm realizing now because I've always been

650
00:33:36,120 --> 00:33:39,280
Speaker 5: somebody that, like, even with like computer cameras, have been

651
00:33:39,400 --> 00:33:43,240
Speaker 5: very like anxious about and I know most about it whatever, I.

652
00:33:44,800 --> 00:33:45,920
Speaker 3: In theory it's safe.

653
00:33:45,920 --> 00:33:47,800
Speaker 5: But yeah, I think I think that's how it started.

654
00:33:47,800 --> 00:33:49,920
Speaker 5: I think it was because of that movie, which this

655
00:33:50,080 --> 00:33:53,680
Speaker 5: just goes to prove that Disney Channel was right apparently,

656
00:33:54,520 --> 00:33:56,280
Speaker 5: But yeah.

657
00:33:56,240 --> 00:33:58,080
Speaker 3: No, that's that's so scary though.

658
00:33:58,240 --> 00:34:02,400
Speaker 5: I've never had a security camera like that in a

659
00:34:02,440 --> 00:34:04,040
Speaker 5: place that I've lived, but I know, like I had

660
00:34:04,120 --> 00:34:06,280
Speaker 5: friends growing up that like had that in their houses,

661
00:34:06,360 --> 00:34:11,319
Speaker 5: and that's scary. That is that's really scary what could

662
00:34:11,320 --> 00:34:11,880
Speaker 5: happen with that?

663
00:34:12,520 --> 00:34:12,880
Speaker 2: Yeah?

664
00:34:12,920 --> 00:34:17,640
Speaker 1: So first of all, like Disney Channel continue, Disney Channel

665
00:34:17,680 --> 00:34:21,200
Speaker 1: originals continue from like that two thousands continue to be prophetic,

666
00:34:21,280 --> 00:34:23,600
Speaker 1: like it is written. Yeah, maybe that's maybe that's our

667
00:34:23,760 --> 00:34:28,120
Speaker 1: origin story of paranoia around certain technology.

668
00:34:28,600 --> 00:34:29,359
Speaker 3: I think it is.

669
00:34:29,440 --> 00:34:31,880
Speaker 5: I think I'm connecting the dots now. I'm like, that's

670
00:34:31,960 --> 00:34:32,800
Speaker 5: that's how it starts.

671
00:34:32,880 --> 00:34:36,040
Speaker 1: Yeah, And it's funny because like I'm not like like

672
00:34:36,280 --> 00:34:40,520
Speaker 1: for my life having things like a Google Home or

673
00:34:40,600 --> 00:34:42,680
Speaker 1: like a security camera. It doesn't make sense for my

674
00:34:42,920 --> 00:34:46,359
Speaker 1: life personally, But I get that people's security needs might

675
00:34:46,400 --> 00:34:49,400
Speaker 1: be different. Like my parents have I actually don't know

676
00:34:49,440 --> 00:34:51,879
Speaker 1: what they use, but they have cameras in every room

677
00:34:51,920 --> 00:34:55,680
Speaker 1: in their house because my dad is disabled and sometimes

678
00:34:55,719 --> 00:34:58,399
Speaker 1: has like bad falls, and so it's like a way

679
00:34:58,400 --> 00:35:00,799
Speaker 1: to be like, oh, well, if I'm downstairs, I want

680
00:35:00,800 --> 00:35:02,480
Speaker 1: to be able to see if my mom is downstairs,

681
00:35:02,520 --> 00:35:03,640
Speaker 1: she wants to be able to be able to see

682
00:35:03,640 --> 00:35:05,560
Speaker 1: what my dad is doing, and vice versa. Because they're

683
00:35:05,600 --> 00:35:07,279
Speaker 1: older folks who live in a big house, and so

684
00:35:07,760 --> 00:35:12,880
Speaker 1: I'm not you know, if having devices that have cameras

685
00:35:12,920 --> 00:35:16,320
Speaker 1: in them in your life makes sense for your lifestyle,

686
00:35:17,040 --> 00:35:19,680
Speaker 1: like that, do what you gotta do. As wirecutter, I

687
00:35:19,680 --> 00:35:22,279
Speaker 1: think rightly points out, you should be able to do

688
00:35:22,320 --> 00:35:23,960
Speaker 1: that and trust that you are going to get the

689
00:35:24,000 --> 00:35:26,799
Speaker 1: information that you need to be able to be, you know,

690
00:35:26,920 --> 00:35:29,680
Speaker 1: deciding how you what role you want this technology to

691
00:35:29,680 --> 00:35:31,800
Speaker 1: play in your life. And I feel like what wise

692
00:35:31,960 --> 00:35:35,000
Speaker 1: is not being a good actor to allow consumers to

693
00:35:35,040 --> 00:35:35,600
Speaker 1: really do that.

694
00:35:40,400 --> 00:35:40,560
Speaker 5: More.

695
00:35:40,560 --> 00:35:53,680
Speaker 1: After a quick break, let's get right back into it.

696
00:35:55,440 --> 00:35:57,600
Speaker 1: So we've talked a little bit before about the threats

697
00:35:57,600 --> 00:36:01,600
Speaker 1: that deep fakes pose digitally re images of people, often

698
00:36:01,640 --> 00:36:04,560
Speaker 1: depicting them in sexual situations or meant to be used

699
00:36:04,560 --> 00:36:07,880
Speaker 1: for political deception. Now, new legislation is trying to combat

700
00:36:07,920 --> 00:36:11,200
Speaker 1: the harm posed by deep fakes. Representative Evet Clark, who

701
00:36:11,200 --> 00:36:14,359
Speaker 1: represents parts of Brooklyn, introduced new legislation in the House

702
00:36:14,400 --> 00:36:17,320
Speaker 1: that is meant to curb the harm of deep fakes, saying,

703
00:36:17,400 --> 00:36:19,080
Speaker 1: this bill is meant to take us into the twenty

704
00:36:19,080 --> 00:36:21,880
Speaker 1: first century and establish a baseline so we can discern

705
00:36:21,960 --> 00:36:24,200
Speaker 1: who is intended to harm us. Clark said that the

706
00:36:24,200 --> 00:36:28,640
Speaker 1: Deep Fakes Accountability Act would provide prosecutors, regulators, and particularly

707
00:36:28,719 --> 00:36:33,000
Speaker 1: victims with resources like detection technology that Clark believes they

708
00:36:33,040 --> 00:36:35,720
Speaker 1: need to stand up against the threat of nefarious deep fakes.

709
00:36:36,040 --> 00:36:39,040
Speaker 1: This bill would require all creators of deep fakes to

710
00:36:39,120 --> 00:36:43,080
Speaker 1: include content credentials, which means the origins and entire history

711
00:36:43,080 --> 00:36:45,280
Speaker 1: of a piece of content, including how it was captured

712
00:36:45,320 --> 00:36:48,600
Speaker 1: and how it's been changed. Under this legislation, online platforms

713
00:36:48,640 --> 00:36:51,680
Speaker 1: that host generative AI content would also be required to

714
00:36:51,680 --> 00:36:55,760
Speaker 1: display the origins of that content. Under this legislation, users

715
00:36:55,800 --> 00:36:58,719
Speaker 1: who failed to label malicious deep thakes would face a

716
00:36:58,800 --> 00:37:02,359
Speaker 1: criminal penalty include in prison time and fines. So this

717
00:37:02,440 --> 00:37:06,520
Speaker 1: category woulden compass deep fakes related to sexual content, criminal content,

718
00:37:06,840 --> 00:37:10,080
Speaker 1: incitement of violence, and foreign interference in elections. Now I've

719
00:37:10,120 --> 00:37:13,000
Speaker 1: looked into this legislation a little bit, it does seem

720
00:37:13,040 --> 00:37:16,640
Speaker 1: like there is some potential concern that the scope might

721
00:37:16,680 --> 00:37:19,359
Speaker 1: be a bit too narrow because it really focuses on

722
00:37:19,920 --> 00:37:25,320
Speaker 1: like people, So like deep fakes that depict images of people,

723
00:37:25,840 --> 00:37:29,440
Speaker 1: but what about malna deep fake does not depict a person,

724
00:37:29,520 --> 00:37:33,520
Speaker 1: Like recently faked AI generated images of the Pentagon on

725
00:37:33,600 --> 00:37:36,520
Speaker 1: fire went viral and caused a disruption where I live

726
00:37:36,560 --> 00:37:39,080
Speaker 1: here in DC, And so I have read that there

727
00:37:39,160 --> 00:37:42,319
Speaker 1: is concern that this legislation is too narrow and that

728
00:37:42,360 --> 00:37:46,440
Speaker 1: it does not account for those kinds of deep fakes

729
00:37:46,440 --> 00:37:48,640
Speaker 1: that are that do not depict a specific person.

730
00:37:49,520 --> 00:37:49,759
Speaker 3: Yeah.

731
00:37:49,800 --> 00:37:53,400
Speaker 5: That also, it concerns me that they're being very liberal

732
00:37:53,440 --> 00:37:57,680
Speaker 5: with like sexual content because and like, I don't know,

733
00:37:57,760 --> 00:38:00,640
Speaker 5: this might be a little bit more extreme of a take,

734
00:38:00,680 --> 00:38:03,960
Speaker 5: but I feel like if you're making AI content of

735
00:38:04,000 --> 00:38:09,080
Speaker 5: somebody that's like sexual without their permission, that's bad, that

736
00:38:09,239 --> 00:38:13,480
Speaker 5: is wrong. I don't think that should be allowed, like period.

737
00:38:13,920 --> 00:38:16,080
Speaker 5: So I don't know, it feels sort of like concerning

738
00:38:16,160 --> 00:38:18,399
Speaker 5: that they're sort of like you have to label.

739
00:38:18,120 --> 00:38:20,160
Speaker 3: This, but it can still exist.

740
00:38:21,239 --> 00:38:25,239
Speaker 1: Yeah, that's another I mean, like I just knowing what

741
00:38:25,320 --> 00:38:29,839
Speaker 1: I know about you know, the way that platforms will

742
00:38:29,880 --> 00:38:33,640
Speaker 1: sometimes add like oh this is misinformation or like get

743
00:38:33,640 --> 00:38:36,239
Speaker 1: the realist story. Like if you ever scroll Facebook and

744
00:38:36,280 --> 00:38:38,880
Speaker 1: it's like, oh, this post has been shown to be misleading.

745
00:38:39,600 --> 00:38:42,840
Speaker 1: Those are great, and I like think that platform should

746
00:38:42,840 --> 00:38:45,719
Speaker 1: be doing that, But if I'm being honest, there is

747
00:38:45,760 --> 00:38:48,239
Speaker 1: a lot of research that suggests that people are not

748
00:38:48,400 --> 00:38:51,319
Speaker 1: really like looking at those because social media platforms move

749
00:38:51,360 --> 00:38:53,520
Speaker 1: so quickly that people are not always clicking in to

750
00:38:53,520 --> 00:38:55,680
Speaker 1: be like, oh this is here's.

751
00:38:55,440 --> 00:38:56,279
Speaker 2: Some context for this.

752
00:38:56,400 --> 00:38:59,800
Speaker 1: And so I'm concerned that the way that the Internet

753
00:38:59,840 --> 00:39:02,440
Speaker 1: moves moves, the speed at which the Internet moves, I

754
00:39:02,480 --> 00:39:04,960
Speaker 1: think it's possible that deep fakes could travel in a

755
00:39:05,000 --> 00:39:08,680
Speaker 1: way because people are not necessarily looking at the context

756
00:39:08,760 --> 00:39:10,759
Speaker 1: or looking at the label because of the speed at

757
00:39:10,760 --> 00:39:13,319
Speaker 1: which social media platforms tend to move. And so it

758
00:39:13,400 --> 00:39:17,040
Speaker 1: is concerning, Like I think that something needs to be

759
00:39:17,120 --> 00:39:20,400
Speaker 1: done about the threat of deep fakes, Like I already know.

760
00:39:20,520 --> 00:39:22,399
Speaker 1: I'm sure we've talked about this on the show that

761
00:39:22,880 --> 00:39:25,719
Speaker 1: deep fakes have the potential to really disrupt our democracy,

762
00:39:25,719 --> 00:39:28,440
Speaker 1: and it's definitely going to be people who are traditionally

763
00:39:28,440 --> 00:39:35,479
Speaker 1: marginalized who are disproportionately facing that realities, like you know, women, LGBTQ, folks,

764
00:39:35,520 --> 00:39:36,200
Speaker 1: people of color.

765
00:39:37,320 --> 00:39:39,720
Speaker 2: That's just a reality. And so, like I do think.

766
00:39:39,600 --> 00:39:42,319
Speaker 1: Something needs to be done, it's also kind of hard

767
00:39:42,320 --> 00:39:45,759
Speaker 1: to believe that right now there is no national legislation

768
00:39:45,920 --> 00:39:50,040
Speaker 1: specifically addressing deep fakes or the deceptive uses of generative AI.

769
00:39:50,520 --> 00:39:54,359
Speaker 1: Earlier this month, technology executives did have a closed door

770
00:39:54,400 --> 00:39:58,120
Speaker 1: meeting with senators to discuss potential government regulation, But right

771
00:39:58,160 --> 00:40:02,640
Speaker 1: now there is no national regulation of this. And I

772
00:40:02,680 --> 00:40:05,280
Speaker 1: do want to say that this legislation is being introduced

773
00:40:05,280 --> 00:40:08,040
Speaker 1: by Representative Clark, and Clark is somebody that had actually

774
00:40:08,040 --> 00:40:08,560
Speaker 1: been really.

775
00:40:08,480 --> 00:40:09,279
Speaker 2: Keeping my eye on.

776
00:40:09,719 --> 00:40:12,839
Speaker 1: Y'all might recall that during the TikTok hearings, we talked

777
00:40:12,880 --> 00:40:14,600
Speaker 1: a lot about some of the stuff that came up

778
00:40:14,600 --> 00:40:17,640
Speaker 1: from lawmakers, the questions that they asked. Clark had some

779
00:40:17,800 --> 00:40:23,080
Speaker 1: legitimately very good questions about whether TikTok's moderation policies were

780
00:40:23,120 --> 00:40:25,840
Speaker 1: biased toward black and brown creators, and whether the platform

781
00:40:25,880 --> 00:40:28,879
Speaker 1: was suppressing abortion content. I remember like she was someone whole.

782
00:40:28,880 --> 00:40:32,480
Speaker 1: I was like, Oh, she's like asking very substantive questions

783
00:40:32,719 --> 00:40:34,960
Speaker 1: that clearly reflect her constituents in a way that I

784
00:40:35,000 --> 00:40:39,120
Speaker 1: thought was like very refreshing. She was also working to

785
00:40:39,200 --> 00:40:42,759
Speaker 1: regulate AI before doing so was cool way back when.

786
00:40:42,760 --> 00:40:45,840
Speaker 1: In twenty nineteen, she worked with Senators Wided and Corey

787
00:40:45,840 --> 00:40:49,320
Speaker 1: Booker to introduce the Algorithmic Accountability Act, a bill that

788
00:40:49,360 --> 00:40:53,000
Speaker 1: would require companies to conduct impact and privacy assessments when

789
00:40:53,000 --> 00:40:55,879
Speaker 1: they use automated decision making tools. And so we will

790
00:40:55,880 --> 00:40:58,880
Speaker 1: definitely keep an eye on this legislation, how it moves,

791
00:40:59,320 --> 00:41:01,719
Speaker 1: what happens with it. But yeah, it's sort of hard

792
00:41:01,760 --> 00:41:07,239
Speaker 1: to believe that there is no national legislation addressing the

793
00:41:07,280 --> 00:41:11,640
Speaker 1: threat of deep fakes or deceptive uses of AI. And yeah,

794
00:41:11,640 --> 00:41:13,160
Speaker 1: it's it's I will keep an eye on it.

795
00:41:13,880 --> 00:41:16,880
Speaker 5: Yeah, it It definitely feels like there should be I

796
00:41:16,880 --> 00:41:21,319
Speaker 5: feel like that should be covered under like libel or

797
00:41:21,400 --> 00:41:22,120
Speaker 5: something too.

798
00:41:22,200 --> 00:41:25,240
Speaker 3: Where it's like and again, I'm I'm not a lawyer.

799
00:41:25,400 --> 00:41:29,480
Speaker 5: I haven't looked at the concrete laws that exists around this,

800
00:41:29,719 --> 00:41:32,319
Speaker 5: but it feels like an image and an image is

801
00:41:32,520 --> 00:41:36,239
Speaker 5: like impact on somebody's reputation that should have the same

802
00:41:36,280 --> 00:41:39,200
Speaker 5: impact as like something that's spoken about somebody.

803
00:41:39,520 --> 00:41:42,160
Speaker 3: But yeah, like it's it's good.

804
00:41:41,960 --> 00:41:44,359
Speaker 5: To hear that somebody is doing something about this, and

805
00:41:44,440 --> 00:41:48,440
Speaker 5: somebody who it seems like has a history of actually

806
00:41:48,480 --> 00:41:51,960
Speaker 5: addressing tech issues and not just you know, selling out

807
00:41:52,000 --> 00:41:55,799
Speaker 5: to the sort of Heritage Foundation version of what the

808
00:41:55,800 --> 00:41:56,640
Speaker 5: Internet should be.

809
00:41:56,760 --> 00:42:00,640
Speaker 3: That's a refreshing take for once. But and again, like, this.

810
00:42:00,560 --> 00:42:04,960
Speaker 5: Is a very narrow legislation, but it's a step in

811
00:42:04,960 --> 00:42:07,120
Speaker 5: the right direction, and I guess that's good to hear.

812
00:42:07,760 --> 00:42:09,920
Speaker 1: Yeah, And to your point that you were making earlier,

813
00:42:10,000 --> 00:42:11,960
Speaker 1: I think this is a situation that really shows that

814
00:42:12,040 --> 00:42:17,040
Speaker 1: sometimes our technology progresses quicker than our laws can keep up.

815
00:42:17,200 --> 00:42:20,400
Speaker 1: And so I'm interested to see if we get to

816
00:42:20,440 --> 00:42:23,799
Speaker 1: a place where our laws actually can be somewhat more

817
00:42:23,840 --> 00:42:26,600
Speaker 1: aligned with the realities of the technology that we're that's

818
00:42:26,640 --> 00:42:30,880
Speaker 1: facing us today. Okay, so important question for you, Joey.

819
00:42:31,440 --> 00:42:34,080
Speaker 1: Did you go for First of all, are you a Swifty?

820
00:42:34,080 --> 00:42:35,080
Speaker 1: Are you into Taylor Swift?

821
00:42:36,040 --> 00:42:37,120
Speaker 3: I love Taylor Swift.

822
00:42:37,160 --> 00:42:40,120
Speaker 2: Oh my god, We've never talked about this, so I

823
00:42:40,440 --> 00:42:40,919
Speaker 2: wasn't sure.

824
00:42:41,400 --> 00:42:43,400
Speaker 5: I did go to the Airs tour. I went to

825
00:42:43,480 --> 00:42:47,200
Speaker 5: the Chicago one of the Chicago shows. She played the Lakes,

826
00:42:47,440 --> 00:42:51,600
Speaker 5: and I wish you would for those of you that are.

827
00:42:51,600 --> 00:42:54,080
Speaker 3: Wondering, the two of you that are wondering.

828
00:42:54,719 --> 00:42:59,560
Speaker 5: But it was a great show. Not being said the

829
00:43:00,040 --> 00:43:02,319
Speaker 5: it's a lot of stress leading up to it. So

830
00:43:02,400 --> 00:43:04,920
Speaker 5: I'm sure you're gonna get into some of that.

831
00:43:05,239 --> 00:43:07,520
Speaker 2: Yes, so I think. I so I'm not as swifty.

832
00:43:07,600 --> 00:43:11,480
Speaker 1: I am an aspiring swifty like I if I'm being honest,

833
00:43:11,480 --> 00:43:14,600
Speaker 1: I probably other than the big hits that everybody knows,

834
00:43:14,600 --> 00:43:15,839
Speaker 1: I probably could not name a.

835
00:43:15,800 --> 00:43:16,600
Speaker 2: Taylor Swift song.

836
00:43:16,880 --> 00:43:19,239
Speaker 1: But I want to be a swifty If there are

837
00:43:19,280 --> 00:43:22,160
Speaker 1: folks like someone send me a playlist, someone tell me

838
00:43:22,160 --> 00:43:26,320
Speaker 1: what to get into. I feel like jealousy. I wish

839
00:43:26,360 --> 00:43:28,280
Speaker 1: I was. I want to be part of the community.

840
00:43:28,400 --> 00:43:34,320
Speaker 5: I'll send you a playlist like Okay, yeah, I respect

841
00:43:34,320 --> 00:43:37,480
Speaker 5: Taylor Swift a lot, and I I want in.

842
00:43:37,760 --> 00:43:39,160
Speaker 2: I just don't know where to start.

843
00:43:39,760 --> 00:43:42,160
Speaker 1: So, as you were saying, like if anybody who tried

844
00:43:42,160 --> 00:43:44,440
Speaker 1: to go to Taylor Swift's eras toward the summer or

845
00:43:44,840 --> 00:43:46,920
Speaker 1: Beyonce's renaissance toward the summer, I didn't make it to

846
00:43:46,960 --> 00:43:47,359
Speaker 1: either of them.

847
00:43:47,400 --> 00:43:48,719
Speaker 2: So like Boomy, I.

848
00:43:48,719 --> 00:43:49,760
Speaker 3: Didn't make it to Renaissance.

849
00:43:49,800 --> 00:43:51,600
Speaker 5: I really didn't want to go to Renaissance and I

850
00:43:51,600 --> 00:43:55,480
Speaker 5: could not get a ticket Soli.

851
00:43:54,440 --> 00:43:57,520
Speaker 3: Yeah, glass half at least I kind of situation.

852
00:43:59,000 --> 00:44:02,160
Speaker 1: My brother went with his wife, and there was a

853
00:44:02,160 --> 00:44:05,000
Speaker 1: time where I was like, well, certainly, like he's gonna

854
00:44:05,000 --> 00:44:07,920
Speaker 1: ask me to go. He's gonna be like, Bridget, you

855
00:44:08,040 --> 00:44:09,680
Speaker 1: should go to Beyonce, take my ticket.

856
00:44:09,760 --> 00:44:11,319
Speaker 2: And I was like waiting by the phone and the

857
00:44:11,320 --> 00:44:12,080
Speaker 2: call never came.

858
00:44:12,280 --> 00:44:12,480
Speaker 3: Fell.

859
00:44:12,680 --> 00:44:14,719
Speaker 2: Yeah, I did, heart breaking.

860
00:44:15,440 --> 00:44:17,560
Speaker 1: It was heartbreaking, But I'll get him next time. So

861
00:44:17,800 --> 00:44:20,520
Speaker 1: if anybody went to either of those big summer concert

862
00:44:20,640 --> 00:44:24,320
Speaker 1: tours Taylor Swift, Beyonce, y'all probably know already that the

863
00:44:24,880 --> 00:44:29,239
Speaker 1: ticket buying process was plagued with predatory online ticket sale

864
00:44:29,280 --> 00:44:33,600
Speaker 1: platforms and resellers. It is so hard and expensive to

865
00:44:33,600 --> 00:44:36,000
Speaker 1: get tickets that they actually end up selling out really

866
00:44:36,040 --> 00:44:39,279
Speaker 1: quickly and then wind up on ticket reseller sites for

867
00:44:39,520 --> 00:44:42,960
Speaker 1: thousands of dollars. And now the IRS is getting involved

868
00:44:42,960 --> 00:44:46,400
Speaker 1: because they're putting more scrutiny on ticket resellers.

869
00:44:46,640 --> 00:44:48,000
Speaker 2: So I actually did not know this.

870
00:44:48,760 --> 00:44:51,839
Speaker 1: How it has worked before is that ticket websites had

871
00:44:51,840 --> 00:44:54,279
Speaker 1: to send ten ninety nine forms to anybody who made

872
00:44:54,280 --> 00:44:56,839
Speaker 1: more than twenty thousand dollars through two hundred or more

873
00:44:56,880 --> 00:45:00,759
Speaker 1: ticket sale transactions in a year, and now that law

874
00:45:00,800 --> 00:45:03,719
Speaker 1: has been updated as part of the American Rescue Plan Act,

875
00:45:03,719 --> 00:45:06,839
Speaker 1: which lowers that amount from twenty thousand dollars to six

876
00:45:06,960 --> 00:45:10,280
Speaker 1: hundred dollars regardless of the number of sales, and sellers

877
00:45:10,280 --> 00:45:12,440
Speaker 1: will only need to pay taxes on the profit that

878
00:45:12,480 --> 00:45:14,960
Speaker 1: they make. This is all part of Biden's plan to

879
00:45:15,080 --> 00:45:17,960
Speaker 1: pump the brakes on the out of control antics of

880
00:45:18,000 --> 00:45:21,400
Speaker 1: ticket resellers, to crack down on predatory practices.

881
00:45:20,920 --> 00:45:25,200
Speaker 2: Like tacking on hidden fees at checkout, which everybody hates.

882
00:45:25,280 --> 00:45:28,399
Speaker 1: It's like it's like, you'll buy tickets and then it's like, okay,

883
00:45:28,440 --> 00:45:31,280
Speaker 1: the tickets are fifty dollars and a twenty dollars fuck

884
00:45:31,320 --> 00:45:33,400
Speaker 1: you fee, so now it's seventy dollars. And then oh

885
00:45:33,480 --> 00:45:35,080
Speaker 1: you use the internet. O, now it's one hundred dollars.

886
00:45:35,160 --> 00:45:38,400
Speaker 1: Like it completely adds up. It's so predatory.

887
00:45:38,920 --> 00:45:43,120
Speaker 5: Yeah, the Swifties are powerful. I will say I feel

888
00:45:43,200 --> 00:45:47,719
Speaker 5: like the past couple months of show the Swifties are powerful.

889
00:45:48,360 --> 00:45:51,719
Speaker 1: That is one hundred percent correct. You know, when you

890
00:45:51,800 --> 00:45:53,719
Speaker 1: look at the average prices of some of these big

891
00:45:53,760 --> 00:45:56,880
Speaker 1: concerts this summer, it is clear that like something is wrong.

892
00:45:57,239 --> 00:45:59,520
Speaker 1: The Wall Street Journal reports at the average price for

893
00:45:59,560 --> 00:46:03,799
Speaker 1: a swift Era's tour was one ninety five dollars and

894
00:46:03,840 --> 00:46:08,120
Speaker 1: for Beyonce's Renaissance tour four hundred dollars. Now, stub Hub

895
00:46:08,200 --> 00:46:11,760
Speaker 1: did say that like this might be partly due to COVID,

896
00:46:11,800 --> 00:46:15,000
Speaker 1: because the live event industry is like still bouncing back

897
00:46:15,040 --> 00:46:18,480
Speaker 1: after like COVID shutdowns. I can't confirm or deny the

898
00:46:18,920 --> 00:46:21,440
Speaker 1: truth behind that. That's what they're saying. And as you

899
00:46:21,480 --> 00:46:24,839
Speaker 1: were saying, Joe, we really do have Swifties and they're

900
00:46:24,920 --> 00:46:28,680
Speaker 1: organizing and advocating to thank for this. After the Ara's tour,

901
00:46:28,920 --> 00:46:32,080
Speaker 1: Swifties reported not being able to buy Taylor's swift tickets

902
00:46:32,120 --> 00:46:34,640
Speaker 1: and then the site shut down. When it came back up,

903
00:46:34,719 --> 00:46:37,360
Speaker 1: tickets were sold out, but they were being listed for

904
00:46:37,560 --> 00:46:42,040
Speaker 1: exorbitant prices by ticket resellers. In a federal hearing, Ticketmaster

905
00:46:42,200 --> 00:46:45,560
Speaker 1: blamed bots for this, and then later Ticketmasters shut down

906
00:46:45,560 --> 00:46:48,279
Speaker 1: ticket sales in France for the Aras tour, and so

907
00:46:49,280 --> 00:46:53,040
Speaker 1: I guess Swifties were loud. They advocated that this was

908
00:46:53,080 --> 00:46:55,920
Speaker 1: not okay. They wanted change, they wanted to reform, And

909
00:46:56,000 --> 00:46:58,680
Speaker 1: I guess the moral of the story here is, don't

910
00:46:58,760 --> 00:47:01,080
Speaker 1: mess with the Swifties because, as they have the Biden

911
00:47:01,080 --> 00:47:04,360
Speaker 1: administration's ear, when the Swifties are upset about something, the

912
00:47:04,360 --> 00:47:05,959
Speaker 1: Biden administration takes action.

913
00:47:06,120 --> 00:47:07,320
Speaker 2: Do not mess with the Swifties.

914
00:47:07,920 --> 00:47:12,000
Speaker 5: Yeah, okay, going back to the COVID point real quick, please,

915
00:47:12,160 --> 00:47:15,840
Speaker 5: that makes me real mad, because Okay, it's twenty twenty

916
00:47:15,880 --> 00:47:18,479
Speaker 5: three now, this tour has been twenty twenty three.

917
00:47:19,239 --> 00:47:22,879
Speaker 3: The COVID pandemic is not over. It hasn't been over.

918
00:47:23,400 --> 00:47:27,239
Speaker 5: That being said, concerts have been open since twenty twenty one.

919
00:47:27,600 --> 00:47:30,560
Speaker 5: Like I remember, I had some gets to go to

920
00:47:30,600 --> 00:47:33,400
Speaker 5: the Green Day Fall Up Boy Weezer show in twenty

921
00:47:33,440 --> 00:47:36,600
Speaker 5: twenty one, and I decided not to go because I

922
00:47:36,640 --> 00:47:37,640
Speaker 5: was worried about COVID.

923
00:47:37,680 --> 00:47:39,760
Speaker 3: But I remember that concert still happened.

924
00:47:39,800 --> 00:47:43,239
Speaker 5: So concerts have been happening for two years now and

925
00:47:43,360 --> 00:47:44,440
Speaker 5: have been happening at.

926
00:47:44,320 --> 00:47:46,640
Speaker 3: These big stadiums with these big artists.

927
00:47:46,880 --> 00:47:49,520
Speaker 5: So I think we're past the point where we can

928
00:47:49,600 --> 00:47:55,319
Speaker 5: use COVID as the excuse for that. But yeah, no,

929
00:47:56,160 --> 00:47:59,239
Speaker 5: I remember living through all of this trying to get

930
00:47:59,239 --> 00:47:59,640
Speaker 5: back to I.

931
00:48:01,040 --> 00:48:02,080
Speaker 2: So I was on.

932
00:48:03,719 --> 00:48:07,080
Speaker 5: All day, like literally spent twenty four hours straight like

933
00:48:07,200 --> 00:48:09,200
Speaker 5: trying to get tickets could not.

934
00:48:10,640 --> 00:48:13,480
Speaker 3: Ended up like somebody I knew was able to get tickets.

935
00:48:13,480 --> 00:48:15,799
Speaker 3: So I was able to go through that, but it

936
00:48:15,920 --> 00:48:17,640
Speaker 3: was insane, and.

937
00:48:19,360 --> 00:48:23,479
Speaker 5: I gotta say even uh, most recently, like I tried

938
00:48:23,520 --> 00:48:29,840
Speaker 5: getting Boy Genius tickets in New York and it wasn't

939
00:48:29,960 --> 00:48:33,239
Speaker 5: as bad as Taylor Swift, but they also slipped out

940
00:48:33,280 --> 00:48:34,960
Speaker 5: right away. It was also a whole weird thing with

941
00:48:35,040 --> 00:48:38,840
Speaker 5: Ticketmaster disclaimer. I am going to the show on Monday.

942
00:48:38,840 --> 00:48:40,320
Speaker 5: I was able to get show. I was able to

943
00:48:40,320 --> 00:48:44,360
Speaker 5: get tickets last minute, but the day of when the

944
00:48:44,400 --> 00:48:48,600
Speaker 5: tickets went on sale, like, it was a nightmare. And yeah,

945
00:48:48,640 --> 00:48:50,359
Speaker 5: they're a big band too, but they're not as big

946
00:48:50,400 --> 00:48:52,799
Speaker 5: as Taylor Swift or Beyonce. So it is just it

947
00:48:52,880 --> 00:48:56,320
Speaker 5: is messed up right now. Ild something is being done.

948
00:48:57,080 --> 00:48:59,959
Speaker 5: The Swifties are very powerful, the Bare Harve is very power.

949
00:49:01,520 --> 00:49:02,120
Speaker 3: Yeah.

950
00:49:02,200 --> 00:49:04,640
Speaker 1: So I actually have a theory that kind of speaks

951
00:49:04,640 --> 00:49:06,719
Speaker 1: to your point. It's not tech related. This is just

952
00:49:06,760 --> 00:49:10,040
Speaker 1: I have no evidence. I have a theory that I

953
00:49:10,040 --> 00:49:13,239
Speaker 1: guess it's a little tech related. My theory is that

954
00:49:14,040 --> 00:49:17,719
Speaker 1: the rise of social media has completely changed what it

955
00:49:17,800 --> 00:49:20,640
Speaker 1: means to go to a concert. And it used to

956
00:49:20,719 --> 00:49:25,160
Speaker 1: be that if you liked a musician or a live act,

957
00:49:25,560 --> 00:49:27,080
Speaker 1: you went to see their concert because it's like I

958
00:49:27,120 --> 00:49:31,000
Speaker 1: gotta I love whoever, I gotta go see them. I

959
00:49:31,040 --> 00:49:34,200
Speaker 1: think that the rise of social media has turned concerts

960
00:49:34,239 --> 00:49:38,120
Speaker 1: from just an experience to like a luxury event right

961
00:49:38,160 --> 00:49:41,560
Speaker 1: where people want to go not even necessarily because they

962
00:49:41,640 --> 00:49:45,080
Speaker 1: like love the band, but because it's like they want

963
00:49:45,280 --> 00:49:48,120
Speaker 1: to flex for the grand that they were there. And

964
00:49:48,160 --> 00:49:50,880
Speaker 1: so I think that like before you were just competing

965
00:49:50,960 --> 00:49:54,520
Speaker 1: with people who were like fans of whoever, now you're

966
00:49:54,520 --> 00:49:57,319
Speaker 1: competing with everybody, because going to a concert is just like,

967
00:49:57,719 --> 00:50:01,040
Speaker 1: you know, a thing to do, and that is making

968
00:50:01,040 --> 00:50:06,480
Speaker 1: it this like luxury experience with these frankly like absurd

969
00:50:06,600 --> 00:50:09,600
Speaker 1: price tags, like the price of concerts has like I

970
00:50:09,840 --> 00:50:12,000
Speaker 1: don't don't ask me to back us up with backs,

971
00:50:12,000 --> 00:50:12,560
Speaker 1: because I cannot.

972
00:50:12,560 --> 00:50:13,319
Speaker 2: I've not looked into it.

973
00:50:13,320 --> 00:50:16,120
Speaker 1: I'm just like somebitting this this theory off the dome.

974
00:50:16,239 --> 00:50:19,240
Speaker 1: But like the I think the price, in my estimation,

975
00:50:19,280 --> 00:50:21,240
Speaker 1: the price has gone up, and I think it's because

976
00:50:21,880 --> 00:50:25,239
Speaker 1: people are seeing it as a luxury item and a

977
00:50:25,320 --> 00:50:28,279
Speaker 1: luxury experience. And whereas it used to be like you

978
00:50:28,520 --> 00:50:30,160
Speaker 1: want you just wanted to go see the show. Now

979
00:50:30,200 --> 00:50:34,080
Speaker 1: it's like, oh, well do you want the backstage or

980
00:50:34,120 --> 00:50:36,160
Speaker 1: like this experience or like that experience?

981
00:50:36,239 --> 00:50:38,640
Speaker 2: And like live.

982
00:50:38,560 --> 00:50:40,600
Speaker 1: Events places, No, they can attack on a bunch of

983
00:50:40,600 --> 00:50:42,319
Speaker 1: fees because people are already seeing this.

984
00:50:42,360 --> 00:50:44,680
Speaker 2: It's like a luxury experience. You know. Does that make sense?

985
00:50:44,719 --> 00:50:45,120
Speaker 2: I don't know.

986
00:50:45,960 --> 00:50:50,400
Speaker 3: No, I totally agree, And again I don't have any evidence.

987
00:50:49,960 --> 00:50:52,839
Speaker 5: To back it up, just my own experience, but yeah,

988
00:50:53,000 --> 00:50:55,759
Speaker 5: Like I think my comparison here is Boy Genius, which

989
00:50:55,800 --> 00:50:58,640
Speaker 5: is still a very popular band, and especially like now

990
00:50:58,760 --> 00:51:01,800
Speaker 5: histort of blown up with their new they are nowhere

991
00:51:01,800 --> 00:51:04,120
Speaker 5: near like Taylor Swift and the fact that I had

992
00:51:04,160 --> 00:51:06,360
Speaker 5: like just as hard as time, just as hard of

993
00:51:06,400 --> 00:51:08,360
Speaker 5: a time getting tickets for them as I did it

994
00:51:08,440 --> 00:51:09,480
Speaker 5: was Taylor Swift.

995
00:51:10,320 --> 00:51:13,960
Speaker 3: Like it's gotten ridiculous. I love me. I know we've

996
00:51:13,960 --> 00:51:16,840
Speaker 3: talked about this. I love music. I'm a big music person.

997
00:51:16,880 --> 00:51:18,479
Speaker 5: But that being said, like I feel like I don't

998
00:51:18,480 --> 00:51:20,759
Speaker 5: go to a lot of concerts now because it's just

999
00:51:20,800 --> 00:51:24,440
Speaker 5: so hard to get tickets. And I think Cosier was

1000
00:51:24,480 --> 00:51:26,279
Speaker 5: like the most recent ones. I remember he was like

1001
00:51:26,360 --> 00:51:28,799
Speaker 5: he put out his tickets for his tour, and I

1002
00:51:28,840 --> 00:51:30,920
Speaker 5: was like, I'm not even gonna bother, Like there's no

1003
00:51:30,960 --> 00:51:33,480
Speaker 5: way I'm getting those tickets, Like I might.

1004
00:51:33,400 --> 00:51:36,000
Speaker 3: As well just sleep in that day when.

1005
00:51:35,800 --> 00:51:38,680
Speaker 5: They go on sale at eight am, which is early

1006
00:51:38,760 --> 00:51:44,560
Speaker 5: for me. But yeah, it's it's concert tickets have gotten ridiculous.

1007
00:51:44,120 --> 00:51:46,160
Speaker 3: And it is not fun.

1008
00:51:46,800 --> 00:51:50,480
Speaker 1: Hopefully the Swifties can help us out with this and organize.

1009
00:51:50,480 --> 00:51:53,200
Speaker 1: I know they are a very powerful unified for us,

1010
00:51:53,239 --> 00:51:55,680
Speaker 1: as is Taylor Swift. I don't know if y'all saw

1011
00:51:55,760 --> 00:51:59,720
Speaker 1: but Taylor Swift. On Tuesday, she posted a short Instagram

1012
00:51:59,719 --> 00:52:02,800
Speaker 1: post to her two hundred and seventy two million followers

1013
00:52:02,880 --> 00:52:06,120
Speaker 1: asking them to get registered to vote, and according to

1014
00:52:06,400 --> 00:52:10,440
Speaker 1: vote dot org, the nonpartisan voter registration nonprofit, they got

1015
00:52:10,600 --> 00:52:15,120
Speaker 1: more than thirty five thousand new registrations And yeah, so

1016
00:52:15,200 --> 00:52:17,840
Speaker 1: she she had a They had a twenty three percent

1017
00:52:17,960 --> 00:52:21,799
Speaker 1: jump over voter registration Day last year because of the

1018
00:52:21,840 --> 00:52:25,520
Speaker 1: power of Taylor Swift. So when Taylor Swift speaks, people listen.

1019
00:52:25,920 --> 00:52:29,759
Speaker 1: When the Swifties speaks, Joe Biden listens. We gotta think

1020
00:52:29,800 --> 00:52:32,000
Speaker 1: of like what else we want the Swifties to advocate

1021
00:52:32,040 --> 00:52:35,280
Speaker 1: for and be like we need universal healthcare swifties.

1022
00:52:34,880 --> 00:52:35,359
Speaker 2: Get on it.

1023
00:52:37,000 --> 00:52:41,879
Speaker 5: I do think that fandom and is the rallying sort

1024
00:52:41,880 --> 00:52:43,080
Speaker 5: of force of the future.

1025
00:52:43,160 --> 00:52:43,719
Speaker 3: Apparently.

1026
00:52:45,760 --> 00:52:50,319
Speaker 5: Contemporary political situation that I find fascinating is that whole

1027
00:52:50,320 --> 00:52:53,560
Speaker 5: thing when all the K pop stands were like managed

1028
00:52:53,600 --> 00:52:57,120
Speaker 5: to mess up the Trump speech that it was supposed

1029
00:52:57,120 --> 00:53:00,280
Speaker 5: to happen in like twenty twenty. I think or canzing

1030
00:53:00,360 --> 00:53:05,439
Speaker 5: young people through the power of fandom being obsessed with.

1031
00:53:05,320 --> 00:53:06,919
Speaker 3: A particular celebrity thought.

1032
00:53:06,920 --> 00:53:09,840
Speaker 5: It is so powerful and I'm so glad that that

1033
00:53:10,080 --> 00:53:11,440
Speaker 5: energy is being used.

1034
00:53:11,200 --> 00:53:15,080
Speaker 3: For good right now. And yeah, we'll see what happens

1035
00:53:15,280 --> 00:53:15,960
Speaker 3: in the future.

1036
00:53:16,840 --> 00:53:19,600
Speaker 2: We love it, Joey, Thank you for being here. A

1037
00:53:19,640 --> 00:53:22,400
Speaker 2: pleasure as always, of course, and as.

1038
00:53:22,280 --> 00:53:24,560
Speaker 1: Always, listeners, thanks for hanging out with us. If you

1039
00:53:24,600 --> 00:53:27,480
Speaker 1: want more and free content, check out our Patreon at

1040
00:53:27,520 --> 00:53:29,640
Speaker 1: patreon dot com, slash Tangody and we will.

1041
00:53:29,480 --> 00:53:30,279
Speaker 2: See you real soon.

1042
00:53:33,360 --> 00:53:35,480
Speaker 1: If you're looking for ways to support the show, check

1043
00:53:35,480 --> 00:53:38,080
Speaker 1: out our mark store at tenggody dot com slash Store.

1044
00:53:39,280 --> 00:53:41,279
Speaker 1: Got a story about an interesting thing in tech, or

1045
00:53:41,400 --> 00:53:43,239
Speaker 1: just want to say hi, You can reach us at

1046
00:53:43,280 --> 00:53:46,000
Speaker 1: Hello at tegody dot com. You can also find transcripts

1047
00:53:46,000 --> 00:53:48,440
Speaker 1: for today's episode at tengody dot com. There Are No

1048
00:53:48,520 --> 00:53:50,560
Speaker 1: Girls on the Internet was created by me Bridget Todd.

1049
00:53:50,960 --> 00:53:54,160
Speaker 1: It's a production of iHeartRadio and Unboss Creative, edited by

1050
00:53:54,200 --> 00:53:58,280
Speaker 1: Joey pat Jonathan Strickland is our executive producer. Tari Harrison

1051
00:53:58,360 --> 00:54:01,120
Speaker 1: is our producer and sound engineer. Michael Amado is our

1052
00:54:01,160 --> 00:54:04,200
Speaker 1: contributing producer. I'm your host, Bridget Todd. If you want

1053
00:54:04,200 --> 00:54:06,640
Speaker 1: to help us grow, rate and review us on Apple Podcasts.

1054
00:54:07,400 --> 00:54:10,200
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1055
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Speaker 1: Apple Podcasts, or wherever you get your podcasts.