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Speaker 1: It's one thing if you show up to a party

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Speaker 1: and there's a few people there who were awful. It

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Speaker 1: is quite another if you show up to the party

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Speaker 1: and the host is awful. There are no girls on

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Speaker 1: the Internet. As a production of iHeartRadio and Unbossed Creative,

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Speaker 1: I'm Bridge Tad and this is there are no girls

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Speaker 1: on the Internet. Okay, So Mike. For folks who listen

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Speaker 1: to the newscast, they might recall that we do a

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Speaker 1: little segment from time to time all about Elon Musk

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Speaker 1: and Twitter.

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Speaker 2: Yeah, that's right.

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Speaker 3: Were doing it like every week for a while because

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Speaker 3: it was just like one dumb thing after another, NonStop.

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Speaker 1: Yeah, And I've kind of been, I don't know if

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Speaker 1: you've noticed, kind of been lessening the amount of times

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Speaker 1: I talk about Elon Musk or trying to, I guess

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Speaker 1: if I'm going to be keep it really real, trying

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Speaker 1: to lessen the amount of times I talk about Elon

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Speaker 1: Musk on the podcast.

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Speaker 3: It has been a while since we've I've heard about

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Speaker 3: Elon on here. What's the deal, Bridget, I don't know.

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Speaker 3: I think it just got to be a little bit

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Speaker 3: too much, you know. I still plan on doing those

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Speaker 3: segments on the newscast, But it just felt like every

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Speaker 3: day he was doing something infuriating and it was taking

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Speaker 3: up a lot of room from other things that we

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Speaker 3: could be diving into. Honestly, I think if I talked

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Speaker 3: about every instance of Elon Musk doing something infuriating or objectionable,

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Speaker 3: it would be all we talked about on this podcast.

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Speaker 3: And listen, there are many good tech podcasts out there

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Speaker 3: that are dedicated to solely covering Elon Musk and solely

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Speaker 3: covering his tenure at Twitter. Their good podcasts recommend them.

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Speaker 3: That is not my ministry. I do not want to.

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Speaker 1: Publish an Elon Musk themed podcast, but if I were

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Speaker 1: to cover everything that he says and does, I absolutely

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Speaker 1: would find myself doing that.

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Speaker 3: Yeah, that makes sense. I mean, he's somebody who is

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Speaker 3: in the news a lot, doing stupid things a lotten

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Speaker 3: Those stupid things have implications and harm for the sorts

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Speaker 3: of people that we try to elevate on this podcast.

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Speaker 3: So yeah, it would just take up all of the

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Speaker 3: damn space.

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Speaker 1: But there's actually a lot going on with Elon and

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Speaker 1: Twitter right now, so I thought we might be overdue

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Speaker 1: on an update. So consider this a super sized version

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Speaker 1: of our news roundup segment.

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Speaker 2: What's Elon done? Now?

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Speaker 4: Okay, so here's what's going on.

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Speaker 1: First of all, I have to start by sort of

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Speaker 1: giving you a bit of context, which is that Elon

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Speaker 1: Musk has been trafficking in hate for a very long time.

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Speaker 4: This is not new for him.

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Speaker 1: I don't necessarily feel like it got enough attention when

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Speaker 1: he was first and talks to buy Twitter way back when.

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Speaker 1: But the whole reason that he said that he wanted

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Speaker 1: to buy Twitter in the first place was rooted in transphobia.

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Speaker 1: According to his own text messages revealed in court, he

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Speaker 1: didn't like that Twitter had rules against dead naming and

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Speaker 1: misgendering trans people, and it prompted his interest in buying

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Speaker 1: the platform initially to turn it into some kind of

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Speaker 1: so called quote free speech utopia.

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Speaker 4: So let's be.

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Speaker 1: Really really clear about who he is and who he

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Speaker 1: has always been. I feel like a lot of folks,

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Speaker 1: even folks that I respect, in tech journalism tech media,

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Speaker 1: really kind of sold this false narrative that, oh, Elon

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Speaker 1: is a genius. If he's doing these hateful things, if

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Speaker 1: he's tweeting sexist, transphobic, racist things, he must be playing

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Speaker 1: three dimensional chests this must be some genius move. We

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Speaker 1: don't understand either that or they did not cover this

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Speaker 1: aspect of who he is at all. Only now do

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Speaker 1: I think we're starting to see, Please places really catch

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Speaker 1: up and cover him thoughtfully and accurately to who he is,

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Speaker 1: what he says, and the things that he does. But

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Speaker 1: for a long time, I don't think that was the case.

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Speaker 1: So I just want to root this whole conversation in

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Speaker 1: that reality that this is.

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Speaker 4: None of this is new. This is who he is.

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Speaker 1: This is who he's always been, and he's always shown

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Speaker 1: himself to be this kind of person, and we ought

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Speaker 1: to believe him.

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Speaker 4: That this is who he is.

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Speaker 3: Yeah, he does a very good job acting the role

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Speaker 3: of a fun party boy genius who's trying to do

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Speaker 3: good in the world. And I think that's like really

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Speaker 3: appealing and captivating to people. And maybe that's why so

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Speaker 3: many people are like not only eager to take him

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Speaker 3: at his word, but almost like trying to actively erase

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Speaker 3: these things that he says with his words, you know,

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Speaker 3: like trying to wanting to buy Twitter because he didn't

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Speaker 3: like its policies against trans people as just like one example.

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Speaker 4: Oh yeah, I mean the word that I would use

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Speaker 4: is launder.

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Speaker 1: I have to say that a lot of my colleagues

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Speaker 1: who make content about technology have done the dirty business

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Speaker 1: of laundering his bad behavior and making it more palatable.

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Speaker 1: And I have a lot of suspen as to why

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Speaker 1: that was. But I think that one a lot of

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Speaker 1: these places just don't have the range, right Like, if

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Speaker 1: you don't have the range to dive into the way

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Speaker 1: that things like transphobia, sexism, racism are impacting not just

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Speaker 1: who he is as a person, but his business and

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Speaker 1: financial moves, moves that impact all of us, you might

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Speaker 1: be less inclined to have that inform your reporting about him,

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Speaker 1: even though it is absolutely unequivocally part of the story

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Speaker 1: of how he runs businesses. You know, this is someone

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Speaker 1: who has been accused of mistreating his workers along racial lines,

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Speaker 1: around along gender lines, right Like, this is absolutely part

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Speaker 1: and parcel to how he runs businesses. So if you're

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Speaker 1: somebody who makes media or writes or covers about technology

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Speaker 1: and you're leaving that out, well you're leaving out a

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Speaker 1: huge relevant part of the story.

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Speaker 2: Yeah.

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Speaker 3: I think the idea that people don't have the range

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Speaker 3: to cover the implications of his hateful statements is really

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Speaker 3: interesting because I think he counts on a similar thing

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Speaker 3: regarding his a lot of his technical statements.

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Speaker 2: I feel it's.

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Speaker 3: Almost a meme at this point that it's easy to

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Speaker 3: think Elon Musk is a genius until he says something

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Speaker 3: about a domain that you happen to know something about,

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Speaker 3: and I feel it feels like there's a lot of

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Speaker 3: parallels with what you were just talking about, where journalists

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Speaker 3: maybe don't have the range to really contextualize the impact

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Speaker 3: of his transphobic or racist or anti semitic statements. Similarly,

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Speaker 3: people just take him at his word that he's a

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Speaker 3: tech genius who will revolutionize social media and create the

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Speaker 3: new everything app that users have been clamoring for, which

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Speaker 3: doesn't seem to be working out super great.

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Speaker 1: I think never underestimate how much people will believe you

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Speaker 1: when you are a wealthy white guy who says you're

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Speaker 1: a genius and Mike to your point about buying Twitter

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Speaker 1: and like revolutionizing it, if I were to get into

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Speaker 1: the depths of it, we would be here for hours.

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Speaker 1: But let me just say this as somebody who has

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Speaker 1: studied social media worked at social media companies ben in

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Speaker 1: the space for a long time. Ben In rooms with

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Speaker 1: people who are way smarter than I am, who have

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Speaker 1: been working at this for many, many years, longer than

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Speaker 1: I have, and we all cannot agree on how to

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Speaker 1: do this right. Like the what we're going to talk

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Speaker 1: about today, content moderation and how you keep hate off

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Speaker 1: of platforms is very complicated. It's very complex. There's not

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Speaker 1: like one simple answer. Smart people learned, people accomplished. People

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Speaker 1: have been arguing about it since there was social media.

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Speaker 4: The hubris that.

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Speaker 1: It takes to walk in and be like, well, I

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Speaker 1: can do this, it like it fills me with such

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Speaker 1: a deep rage and to.

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Speaker 4: Have people be like, maybe he can do it.

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Speaker 1: He has never done this before, and there's no background

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Speaker 1: in it, and people who have been doing it for

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Speaker 1: like decades haven't been able to figure it out. And

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Speaker 1: it's not really an easy thing. But I don't know,

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Speaker 1: maybe he's a genius and he can figure it out.

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Speaker 3: He's so obviously not up to the task of figuring

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Speaker 3: out social media these like really difficult, abstract, high level problems.

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Speaker 3: I remember one of the first things he did when

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Speaker 3: he took over Twitter was, uh, you know, fire a

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Speaker 3: bunch of people, and then the engineers who were left.

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Speaker 3: I forget the exact details, but it was like they

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Speaker 3: had to meet with him and show him like how

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Speaker 3: many lines of code they were writing each week, which

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Speaker 3: is the craziest metric by which to judge engineers.

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Speaker 1: Yes, but that's the thinking of someone who doesn't know

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Speaker 1: what they're doing of like, well, just obviously more equals good, right,

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Speaker 1: Like that's the only that's the only way my brain

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Speaker 1: can understand this is.

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Speaker 4: Like, like that has to be the way it works, right.

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Speaker 3: Yeah, right, more code equals better, right, Like obviously, Yeah,

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Speaker 3: That's that's always what engineers are saying.

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Speaker 1: It's like if a caveman was run in Twitter.

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Speaker 4: Okay, so Elon Musk.

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Speaker 1: He tweets and does misogynistic things, racist things, transphobic things,

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Speaker 1: and has trafficked in anti semitism before too a lot

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Speaker 1: of times. In the past it's been this brand of

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Speaker 1: kind of wink wink nod nod anti semitism, like dog whistles,

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Speaker 1: but last week he engaged in pretty overt anti semitism.

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Speaker 1: Musk posted to Twitter, you have said the actual truth

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Speaker 1: in response to a post that claimed that Jewish people

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Speaker 1: support quote dialectical hatred against whites.

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Speaker 3: I feel like the word dialectical is having a renaissance.

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Speaker 3: Maybe people have been talking about dialecticals this whole time

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Speaker 3: and I've just been laid to the party.

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Speaker 4: Well, I kind of get what you mean that.

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Speaker 1: It might be one of those words that people who

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Speaker 1: are trying to make their terrible, messed up opinions sound

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Speaker 1: like high art and like high falutin. There are a

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Speaker 1: couple of words like that that I've definitely heard in

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Speaker 1: college classes where it's like, oh, you are just trying

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Speaker 1: to make your horrible opinion sound refined?

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Speaker 4: Is that sort of what you mean?

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Speaker 2: That is kind of what I mean.

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Speaker 3: It feels like one of these words that like you

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Speaker 3: just kind of sprinkle it in and it adds an

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Speaker 3: air of authority or learnedness. It's like I'm referencing nineteenth

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Speaker 3: century philosophers. Clearly what I'm saying isn't dumb, but like,

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Speaker 3: what is it actually adding?

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Speaker 4: Right?

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Speaker 1: Like my flavor of anti Semitism is actually very learned?

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Speaker 4: Right?

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Speaker 3: Like you know, he in this quote that you just read,

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Speaker 3: he said that they were supporting dialectical hatred against whites.

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Speaker 3: What is the word dialectical really adding in that sentence

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Speaker 3: other than connotations of you know, I'm someone who's read philosophy.

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Speaker 3: This is a learned take, not just hate.

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Speaker 4: Totally agree.

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Speaker 1: So this kind of feels like yet another tipping point

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Speaker 1: for the platform. I think I've said that before on

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Speaker 1: the podcast, that like, oh, this is a new low,

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Speaker 1: this is a new low. But no, this is a

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Speaker 1: really this is a real new low. I think it

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Speaker 1: feels like a new low in a situation that was

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Speaker 1: already not so great. Elon Musk's remarks drew widespread condemnation.

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Speaker 1: The White House even weighed in saying it is unacceptable

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Speaker 1: to repeat the hideous lie behind the most fatal act

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Speaker 1: of anti Semitism in American history at any time, let

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Speaker 1: alone one month after the deadliest day for the Jewish

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Speaker 1: people since the Holocaust. This is from White House spokesperson

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Speaker 1: Andrew Bates in a statement. A little side note here,

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Speaker 1: which is that the White House putting out this statement

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Speaker 1: is one thing. But you know, the reality is that

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Speaker 1: the American government is pretty deeply entangled with Elon Musk

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Speaker 1: right now to communications and technology infrastructure. In addition to

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Speaker 1: owning and tanking Twitter and also Tesla, Musk runs the

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Speaker 1: high speed satellite internet provider Starlink. That's been a major

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Speaker 1: factor in both the war and Ukraine and the conflict

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Speaker 1: in Gaza. And right now there's over a billion dollars

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Speaker 1: worth of Elon Musk's SpaceX technology about to launch Pentagon

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Speaker 1: tech into space, and so, you know, I agree with

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Speaker 1: this statement. However, the reality is that American civic infrastructure

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Speaker 1: and public infrastructure remains pretty entangled with and reliant on

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Speaker 1: in a lot of ways Elon Musk, and so yeah,

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Speaker 1: it sounds great, but what can they really do when

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Speaker 1: that is the case.

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Speaker 3: Yeah, and not just our civic infrastructure are military infrastructure, right,

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Speaker 3: Like we should definitely link to Ronan Pharaoh's piece in

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Speaker 3: the show notes about how star Link has been kind

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Speaker 3: of instrumental in Ukraine's war against Russia and how awkward

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Speaker 3: a position that has put the Pentagon into of you

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Speaker 3: know this this military ally in a life and death

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Speaker 3: conflict being so dependent on Starlink, which is a private

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Speaker 3: company owned by this mercurial.

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Speaker 2: Guy.

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Speaker 1: And I think that's the thing, like at the very

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Speaker 1: like base level, do you really want like if you

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Speaker 1: see the way that Elon Musk tweets if you've ever

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Speaker 1: seen him on the Joe Rogan Show, which it needs

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Speaker 1: to be part of my job to watch Joe Rogan podcasts,

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Speaker 1: and I have seen him on those podcasts. You would say, like,

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Speaker 1: this is not somebody that we want deeply entangled in

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Speaker 1: like life or deay military operations, right, Like, it's just

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Speaker 1: that simple. And I think that it really does mirror

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Speaker 1: the relationship that a lot of us myself unfortunately very

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Speaker 1: much included, have with Elon Musk's Twitter, right, Like, we

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Speaker 1: hate it for lots of really valid reasons, but in

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Speaker 1: other ways, you know, leaving Twitter outright can feel really hard,

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Speaker 1: especially given that it doesn't really feel like there's one

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Speaker 1: place that has a merge to replace it necessarily. It's

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Speaker 1: certainly the way that I feel. You know, I don't

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Speaker 1: like Elon Musk. I don't like the idea that every

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Speaker 1: day that I'm showing up on this platform, I am

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Speaker 1: essentially complicit in his reign over this technology. Like, I

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Speaker 1: don't like that. I don't like my personal individual role

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Speaker 1: in that dynamic. I want to stop using it. However,

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Speaker 1: it has also become such a big part of my

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Speaker 1: own media diet, right It's it's how I collect stories

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Speaker 1: for the podcasts and perspective for the podcast and it's

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Speaker 1: also just hard to give up on those days where

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Speaker 1: I felt like Twitter was the place that you could

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Speaker 1: find legitimate community and build real political power and social

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Speaker 1: power and like lead to actual change. But these days, no,

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Speaker 1: I don't feel that way on the platform at all.

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Speaker 1: I think I shared this on the Patreon episode that

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Speaker 1: we did a while back about my decision whether to

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Speaker 1: stay on Twitter or leave Twitter. But not that long ago,

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Speaker 1: I was called a straight up racial slur on Twitter

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Speaker 1: and it's been a while since that kind of thing

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Speaker 1: has happened, And it was a racial slur that I

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Speaker 1: had never heard before in my thirty out of years

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Speaker 1: as a black woman on this planet.

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Speaker 4: I had to look it up on Urban Dictionaire.

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Speaker 1: And I was like, oh, they're like coming out with

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Speaker 1: new racial slurs on Twitter now, who knew? But like, so,

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Speaker 1: like the vibes are not good, right, I'll be the

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Speaker 1: first person to admit that, But where would we go, Like,

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Speaker 1: I don't think that we have anything right now that

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Speaker 1: would actually be a replacement for it.

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Speaker 3: And it's a real catch twenty two because I think

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Speaker 3: exactly that feeling is what keeps people there and perpetuates

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Speaker 3: its status as like the place that people are.

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Speaker 1: Absolutely and I won't need to say, like, that's not

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Speaker 1: unique to Twitter. I think Facebook did the same thing,

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Speaker 1: where it's like this is where my friends are, this

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Speaker 1: is how I remember my friend's birthdays, Like this is

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Speaker 1: how I go to events, That's how I find out

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Speaker 1: about events. Platforms intentionally make you feel like your entire

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Speaker 1: world is on their platforms. What's that much easier for

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Speaker 1: you to be like, I'm out. I don't want this,

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Speaker 1: because it means that breaking up with that platform is

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Speaker 1: going to feel like breaking up with your friends, your community,

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Speaker 1: how you remember birthdays, how you keep track of people

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Speaker 1: in your that you went to school with, how you

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Speaker 1: keep track of events happening in your local community, all

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Speaker 1: of that right, and so that's by design. However, the

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Speaker 1: White House actually announced today that they were joining the

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Speaker 1: Twitter alternative Threads, which we talked about on the podcast before.

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Speaker 1: I think you and I both tried it briefly. I

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Speaker 1: haven't logged it in a while. Maybe it's pop it

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Speaker 1: over there, or I need to like dip back in.

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Speaker 1: Maybe I will. And I do think that Biden's campaign

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Speaker 1: being on threads will cause a lot of journalists and

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Speaker 1: media makers. The folks who made up a big contingent

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Speaker 1: of like what kept Twitter moving to be spending more

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Speaker 1: time on thread. So that's I thought that was kind

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Speaker 1: of an interesting kind of We'll see about this whole situation.

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Speaker 5: Let's take a quick break.

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Speaker 4: And are back.

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Speaker 1: So the White House was not the only place fed

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Speaker 1: up with Elon Musk's antics. On November eighth, Media Matters

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Speaker 1: staffer Eric Hananok published a report showing Nazi content on

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Speaker 1: Twitter alongside advertisements for major brands. Hananochi rights as ex

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Speaker 1: owner Elon Musk continues his descent into white nationalists and

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Speaker 1: anti Semitic conspiracy theories. His social media platform has been

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Speaker 1: placing ads for major brands like Apple, Bravo, IBM, Oracle,

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Speaker 1: Exfinity next to content that house Adolf Hitler and his

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Speaker 1: Nazi party. The company's placements come after CEO Linda Yakarino

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Speaker 1: claimed that brands are protected from the risk of being

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Speaker 1: next to toxic posts on the platform. We also saw

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Speaker 1: one hundred and seventy one rabbis, leaders of Jewish organizations, artists, activists,

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Speaker 1: and academics publish a letter pressuring brands to stop advertising

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Speaker 1: on Twitter, saying Elon Musk is spreading the kind of

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Speaker 1: antisemitism that leads to massacres, and advertisers are funding the

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Speaker 1: platform that allows him to spread his ideology to hundreds

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Speaker 1: of millions of people.

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Speaker 3: Yeah, I can imagine that that group of Rabbis didn't

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Speaker 3: love seeing all that Nazi content, you know.

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Speaker 1: No, absolutely, And so these companies actually did start suspending

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Speaker 1: their advertising from Twitter, first IBM, then Apple, Warner Brothers, Lionsgate, Discovery, Paramount,

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Speaker 1: and Sony have all left too. Now, this is kind

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Speaker 1: of a huge deal. According to The Washington Post, Apple

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Speaker 1: was Twitter's biggest ad buyer during the first quarter of

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Speaker 1: twenty twenty two, an ad by amounting to forty eight

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Speaker 1: million dollars in Q one meant that Apple accounted for

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Speaker 1: a whopping four percent of Twitter's total revenue for the quarter.

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Speaker 1: So that's like a non trivial amount of revenue. So

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Speaker 1: if they lose Apple, they could be losing a big

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Speaker 1: chunk of their money.

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Speaker 3: Yeah, that's a big chunk. It's interesting that Apple spent

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Speaker 3: forty eight million dollars in a single quarter advertising on Twitter.

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Speaker 2: That's kind of mind blowing.

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Speaker 1: And as the Media Matters piece points out, this comes

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Speaker 1: after Twitter's maybe kind of sort of question mark CEO

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Speaker 1: Linda Yacarino had been talking a very big game about

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Speaker 1: wooling back advertisers and brands, promising them that their ads

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Speaker 1: will not be showing up next to Nazi content, which

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Speaker 1: I gotta be honest, that's like such a sad promise.

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Speaker 1: First of all, it's not like there's not Nazi content.

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Speaker 1: It's like, yeah, we all know there's Nazi content on

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Speaker 1: this platform, but we can let's.

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Speaker 4: Just start from there.

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Speaker 1: We all know that it's not your ads will be

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Speaker 1: seen by lots of people, or your ads will perform well,

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Speaker 1: it's just there will not be a literal picture of

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Speaker 1: Adolf Hitler next to it. And they can't even deliver

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Speaker 1: on that.

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Speaker 3: Like very sad When you say it like that, it's

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Speaker 3: it is very sad. It's such a such a low

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Speaker 3: bar that they're still failing to hit.

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Speaker 1: Another thing to note here is that one of the

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Speaker 1: brands that is pulling their advertising is Comcast. Comcast owns

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Speaker 1: Bravo and NBC, and Linda Yakarino was formerly in a

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Speaker 1: high up advertising executive at NBC, So if she's not

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Speaker 1: even able to confidently woo back her where she worked

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Speaker 1: most recently before she was at Twitter. She's not even

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Speaker 1: able to woo back them as an advertiser. That is

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Speaker 1: really telling me something that like something is deeply wrong

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Speaker 1: and advertisers are not happy.

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Speaker 2: Yeah, understandably so, and it's I mean, it's bad.

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Speaker 1: The Media Matters report, which will put in the show notes,

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Speaker 1: is pretty damning. It has all of these screenshots of

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Speaker 1: brand tweets like advertisements next to like to roll over

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Speaker 1: Nazi posts, like actual pictures end quotes of Hitler. So

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Speaker 1: but that'll be next to like an ad for an

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Speaker 1: Apple product or like an ad inviting you to hang

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Speaker 1: out with the Real Housewives at bravocon right, Like, it's

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Speaker 1: a very weird switch.

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Speaker 4: We'll throw it in the show notes. Very damning.

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Speaker 1: So this is not really anything new for social media platforms,

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Speaker 1: especially ones that rely on user generated content. I used

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Speaker 1: to work for a platform called Medium, and when we

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Speaker 1: were be hyping up the platform to potential people to

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Speaker 1: partner with us, we've been one of the ways that

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Speaker 1: we would do it is by showing people how like

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Speaker 1: if they had a serious op ed and they ran

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Speaker 1: it at like a traditional media website, it might be

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Speaker 1: running alongside those awful like sponsor those scammy sponsored ads

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Speaker 1: that you see at the bottom of websites. It will

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Speaker 1: be like, you won't believe how terrible the actress that

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Speaker 1: played Jam on The Brady Bunch looks now with like

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Speaker 1: an unflattering picture of her, or like, here's what your

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Speaker 1: doctor doesn't want you to know about belly fat next

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Speaker 1: to like a picture of like a stomach spilling out

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Speaker 1: over some tight jeans.

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Speaker 4: You know what I'm talking about?

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Speaker 3: Those ass Oh those ads are so terrible and they're

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Speaker 3: so obvious, but they're also so good at like enticing

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Speaker 3: me to want to click on them, Like I don't

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Speaker 3: I never click on them because I try to never

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Speaker 3: click on I don't know shit that people are trying

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Speaker 3: to like pay money to get me to click on

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Speaker 3: It just feels wrong. But there's some of them are

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Speaker 3: so good at like appealing to my basest interest of

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Speaker 3: like what does jan from the Brady Bunch look like?

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Speaker 2: Now?

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Speaker 1: Like that short is an unflattering picture of her? What

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Speaker 1: a terrible angle her mouth is open? Let's just see

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Speaker 1: So ads showing up to this kind of problematic content

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Speaker 1: online is not new, and brands have always had to

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Speaker 1: navigate that for like as long as they've been advertising online.

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Speaker 1: But what is new and specific and unique to Twitter

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Speaker 1: is that you don't usually have the owner who has

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Speaker 1: made himself this like very visible person and on the

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Speaker 1: platform endorsing those same kind of problematic views.

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Speaker 4: Like it's one thing if you show up.

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Speaker 1: To a party and there's a few people there who

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Speaker 1: are awful. It is quite another if you show up

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Speaker 1: to the party and the host is awful, and that

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Speaker 1: awful host is also high fiving and like hyping up

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Speaker 1: all of the awful people at the party. It's a

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Speaker 1: totally different thing. And I think that that's what brands

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Speaker 1: are responding to in this moment.

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Speaker 3: That is such a good analogy. Why would a person

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Speaker 3: want to stay at this party?

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Speaker 4: You would leave?

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Speaker 1: You would be like, oh, I have to get out

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Speaker 1: of here, right. I've been at parties like that, not

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Speaker 1: with Nazis, but with other like other less objectionable forces,

439
00:23:43,080 --> 00:23:44,160
Speaker 1: and you know what you do?

440
00:23:44,200 --> 00:23:44,680
Speaker 4: You leave.

441
00:23:44,760 --> 00:23:47,639
Speaker 1: That's what these brands are doing. These big companies like

442
00:23:47,680 --> 00:23:50,440
Speaker 1: your ibms and your apples can really set the tone

443
00:23:50,480 --> 00:23:53,240
Speaker 1: for the space, and so if they're pausing will it

444
00:23:53,240 --> 00:23:56,120
Speaker 1: can create a domino effect where other companies will get

445
00:23:56,119 --> 00:23:59,960
Speaker 1: the idea and pause as well. So after these advertisers left.

446
00:24:00,320 --> 00:24:03,240
Speaker 1: Elon Musk took responsibility for his tweets and the way

447
00:24:03,280 --> 00:24:06,760
Speaker 1: that they had normalized hate on the platform. Oh wait, sorry,

448
00:24:06,840 --> 00:24:09,439
Speaker 1: I misreading that. What he actually did is what he

449
00:24:09,520 --> 00:24:12,400
Speaker 1: always does, which was tweet a million tweets and then

450
00:24:12,440 --> 00:24:16,280
Speaker 1: threaten a lawsuit. He tweeted the split second the court

451
00:24:16,320 --> 00:24:19,920
Speaker 1: opens on Monday, X Corp will be filing a thermonuclear

452
00:24:20,040 --> 00:24:23,280
Speaker 1: lawsuit against Media Matters and all those who colluded in

453
00:24:23,320 --> 00:24:25,320
Speaker 1: this fraudulent attack on our company.

454
00:24:26,800 --> 00:24:29,919
Speaker 3: I'm sure they're terrified a thermonuclear lawsuit.

455
00:24:30,840 --> 00:24:33,640
Speaker 1: Also, a second note, does this not sound like something

456
00:24:33,760 --> 00:24:37,159
Speaker 1: a supervillain would tweet? Like this is giving lex Luthor,

457
00:24:37,240 --> 00:24:38,320
Speaker 1: it's giving supervillain?

458
00:24:38,320 --> 00:24:38,719
Speaker 4: Am I am?

459
00:24:38,760 --> 00:24:39,119
Speaker 5: I wrong?

460
00:24:39,440 --> 00:24:45,400
Speaker 3: It's definitely giving supervillain threatening a lawsuit thermonuclear. It's intense,

461
00:24:46,160 --> 00:24:48,920
Speaker 3: and it's X Corp. Who's gonna do this? Like that's

462
00:24:48,960 --> 00:24:51,280
Speaker 3: the name of a super villain's company.

463
00:24:51,200 --> 00:24:51,639
Speaker 2: X Corp.

464
00:24:51,840 --> 00:24:54,120
Speaker 3: Yes, it doesn't even have like a like a real name.

465
00:24:54,200 --> 00:24:55,680
Speaker 4: It's just X a normal name.

466
00:24:56,040 --> 00:24:57,720
Speaker 2: It's like such a not normal name.

467
00:25:00,640 --> 00:25:01,840
Speaker 4: Okay, So I actually have.

468
00:25:01,840 --> 00:25:04,199
Speaker 1: To give Elon a little bit of credit here because

469
00:25:04,560 --> 00:25:08,800
Speaker 1: he actually tweeted something and then followed through on it,

470
00:25:08,840 --> 00:25:10,679
Speaker 1: which for him, you know, you never know. He tweets

471
00:25:10,720 --> 00:25:12,600
Speaker 1: all kinds of stuff and like it doesn't come to fruition.

472
00:25:12,720 --> 00:25:14,600
Speaker 1: But here he tweeted that there was going to be

473
00:25:14,600 --> 00:25:17,520
Speaker 1: a lawsuit, and there is a lawsuit because earlier today

474
00:25:17,800 --> 00:25:21,400
Speaker 1: we're recording this. On Monday, he actually did file the lawsuit.

475
00:25:21,760 --> 00:25:24,840
Speaker 1: In it, he accused Media Matters of defaming Twitter, saying

476
00:25:24,920 --> 00:25:30,119
Speaker 1: that they quote manufactured or contrived the screenshots in their report,

477
00:25:30,320 --> 00:25:33,640
Speaker 1: and that Media Matters had not found the ads as claimed,

478
00:25:33,880 --> 00:25:38,200
Speaker 1: but rather quote created these pairings in secrecy. The suit

479
00:25:38,280 --> 00:25:41,560
Speaker 1: specifically names the individual Media Matter staffer who wrote the report,

480
00:25:41,720 --> 00:25:46,359
Speaker 1: Eric Hananok. In the lawsuit, Twitter's again maybe CEO Linda

481
00:25:46,400 --> 00:25:49,639
Speaker 1: Yakermino responded to the Media Matters support confirming that the

482
00:25:49,680 --> 00:25:53,000
Speaker 1: screenshots were real, like in a literal sense. She tweeted,

483
00:25:54,000 --> 00:25:56,439
Speaker 1: if you know me, you know I'm committed to truth

484
00:25:56,520 --> 00:25:57,280
Speaker 1: and fairness.

485
00:25:57,600 --> 00:25:58,560
Speaker 4: So here's the truth.

486
00:25:59,000 --> 00:26:01,680
Speaker 1: Not a single author and tick user on x saw

487
00:26:01,720 --> 00:26:05,960
Speaker 1: IBM's Comcasts or Oracles ads next to the content and

488
00:26:06,080 --> 00:26:09,560
Speaker 1: Media Matters article. Only two users saw Apple's ad next

489
00:26:09,600 --> 00:26:12,520
Speaker 1: to the content, at least one of which was Media Matters.

490
00:26:12,880 --> 00:26:17,119
Speaker 1: Data wins over manipulation and allegations, don't be manipulated. Stand

491
00:26:17,160 --> 00:26:20,959
Speaker 1: with X, which, first of all, I feel like that

492
00:26:21,119 --> 00:26:23,879
Speaker 1: is the tweet of somebody who is perhaps a little

493
00:26:23,880 --> 00:26:27,119
Speaker 1: bit unaware of how little goodwill people have for Twitter.

494
00:26:27,160 --> 00:26:29,720
Speaker 1: And also Elon Musk right now, like other than the

495
00:26:29,880 --> 00:26:34,360
Speaker 1: deepest Elon Musk fanboys who out there is like, yeah,

496
00:26:34,880 --> 00:26:38,439
Speaker 1: X is part of my identity, Like I need to

497
00:26:38,560 --> 00:26:41,120
Speaker 1: align with them. I need to like that is part

498
00:26:41,119 --> 00:26:44,200
Speaker 1: of who I am aligning with this platform.

499
00:26:44,560 --> 00:26:49,080
Speaker 3: Yeah, with X, I'm part of X. It's like such

500
00:26:49,080 --> 00:26:50,440
Speaker 3: an uninspiring name.

501
00:26:50,920 --> 00:26:51,199
Speaker 4: I know.

502
00:26:52,080 --> 00:26:53,840
Speaker 1: I just don't think it's how most people feel about

503
00:26:53,880 --> 00:26:57,160
Speaker 1: social media platforms. Even when we were having conversations about

504
00:26:57,200 --> 00:27:01,720
Speaker 1: potentially banning TikTok, people who were, you know, prolific TikTokers,

505
00:27:02,520 --> 00:27:06,040
Speaker 1: they weren't saying like, I stand with TikTok like they was.

506
00:27:06,200 --> 00:27:09,760
Speaker 1: It wasn't like a you know, thing that they were

507
00:27:09,760 --> 00:27:12,120
Speaker 1: making part of their identity. A lot of those folks

508
00:27:12,160 --> 00:27:13,879
Speaker 1: that I talked to were like, oh, I'll be the

509
00:27:13,880 --> 00:27:14,840
Speaker 1: first person to tell.

510
00:27:14,720 --> 00:27:16,919
Speaker 4: You about the problems on TikTok. Oh, I've been talking

511
00:27:16,960 --> 00:27:19,000
Speaker 4: about X y Z issues with TikTok.

512
00:27:19,359 --> 00:27:21,840
Speaker 1: I think this idea of like you need Like, I

513
00:27:21,840 --> 00:27:24,240
Speaker 1: don't know a lot of people who would have this

514
00:27:24,359 --> 00:27:27,879
Speaker 1: level of brand loyalty to a social media platform that

515
00:27:27,960 --> 00:27:30,320
Speaker 1: she is like conjuring up in this tweet.

516
00:27:30,920 --> 00:27:34,960
Speaker 3: That's actually a really interesting observation because yeah, I don't either.

517
00:27:35,000 --> 00:27:38,879
Speaker 3: It seems nuts, but that's absolutely what she's doing, you know,

518
00:27:39,160 --> 00:27:46,360
Speaker 3: like promoting Twitter or X as like an identity thing,

519
00:27:46,560 --> 00:27:50,159
Speaker 3: like you're either with us or against us, stand with X.

520
00:27:51,080 --> 00:27:52,560
Speaker 2: Yeah, that's kind of wild.

521
00:27:53,080 --> 00:27:56,200
Speaker 1: Yeah, I just don't think that's how social media platforms fit.

522
00:27:56,520 --> 00:27:59,280
Speaker 1: I don't think that's how people think about social media platforms.

523
00:27:59,600 --> 00:28:02,600
Speaker 1: I think that, you know, not that long ago, Elon

524
00:28:02,680 --> 00:28:06,359
Speaker 1: Musk was behaving in an incredibly hostile manner toward people

525
00:28:06,440 --> 00:28:09,000
Speaker 1: who use Twitter, and now to turn around and be like, oh,

526
00:28:09,040 --> 00:28:10,800
Speaker 1: we want you to stand with us. It's like, it's

527
00:28:10,800 --> 00:28:12,840
Speaker 1: not really how it works. And even if that wasn't

528
00:28:12,840 --> 00:28:14,199
Speaker 1: the case, I don't think. I don't think that's how

529
00:28:14,200 --> 00:28:16,880
Speaker 1: people think about social media platforms in general.

530
00:28:16,960 --> 00:28:17,480
Speaker 4: Full stap.

531
00:28:18,000 --> 00:28:22,280
Speaker 3: It's really interesting that that's how she phrased it, Like

532
00:28:22,720 --> 00:28:25,000
Speaker 3: it kind of suggested that's how they think about it,

533
00:28:25,080 --> 00:28:31,000
Speaker 3: that maybe they're not thinking about X as a social

534
00:28:31,000 --> 00:28:34,600
Speaker 3: media platform. Maybe they're thinking about it as like an

535
00:28:34,600 --> 00:28:39,440
Speaker 3: in group or a club of their people who want

536
00:28:39,480 --> 00:28:45,240
Speaker 3: to be there, reading Elon's in name tweets, entering their

537
00:28:45,280 --> 00:28:47,920
Speaker 3: banking information so they can bank there, using it for

538
00:28:48,000 --> 00:28:51,160
Speaker 3: video calls, all the stuff that they talk about wanting

539
00:28:51,200 --> 00:28:51,760
Speaker 3: to do with it.

540
00:28:52,240 --> 00:28:53,680
Speaker 2: Maybe that's how they view it.

541
00:28:54,040 --> 00:28:57,720
Speaker 1: I think there are a small faction of people for

542
00:28:57,760 --> 00:29:01,160
Speaker 1: whom that is the case, Like I think it's Elon

543
00:29:01,320 --> 00:29:06,920
Speaker 1: Musk fanboys, probably some like aspiring tech thought leader types

544
00:29:07,400 --> 00:29:11,680
Speaker 1: who have kind of bought in. But listen, you need

545
00:29:11,760 --> 00:29:14,840
Speaker 1: more than that small faction of people to run a

546
00:29:14,840 --> 00:29:19,959
Speaker 1: successful company. You can't just like build out this like

547
00:29:20,040 --> 00:29:24,560
Speaker 1: small in group of people who will always agree with

548
00:29:24,600 --> 00:29:28,560
Speaker 1: what you say to build your company a company like Twitter,

549
00:29:28,600 --> 00:29:31,400
Speaker 1: that's just like knocking. It's not going to be a

550
00:29:31,680 --> 00:29:33,680
Speaker 1: fruitful and sustainable way to build a.

551
00:29:33,600 --> 00:29:37,960
Speaker 3: Platform, certainly not financially sustainable. But maybe that's not what

552
00:29:38,000 --> 00:29:42,520
Speaker 3: they care about. Maybe Elon just wants his fanboys to

553
00:29:42,640 --> 00:29:45,760
Speaker 3: stand with X. Stand with X is the craziest thing

554
00:29:45,840 --> 00:29:50,000
Speaker 3: that I've heard all week long. It's like patriotic sounding

555
00:29:50,600 --> 00:29:54,400
Speaker 3: incitement for people to stand with X, Like come on,

556
00:29:54,520 --> 00:29:55,400
Speaker 3: get over yourself.

557
00:29:56,360 --> 00:29:58,560
Speaker 1: I mean, we are talking about Elon Musk, the same

558
00:29:58,600 --> 00:30:01,880
Speaker 1: person who launched an AI chatbot to tell him how

559
00:30:01,920 --> 00:30:05,280
Speaker 1: funny he is and how much everybody likes him, how

560
00:30:05,360 --> 00:30:07,920
Speaker 1: much everybody thinks he's so funny on social media.

561
00:30:08,120 --> 00:30:10,560
Speaker 4: That's what we're talking about, So keep that in mind.

562
00:30:10,960 --> 00:30:11,680
Speaker 2: Yeah.

563
00:30:12,160 --> 00:30:15,960
Speaker 3: Also, the same guy who had Twitter's engineers changed the

564
00:30:15,960 --> 00:30:19,720
Speaker 3: algorithm to boost his tweets, like specifically.

565
00:30:20,280 --> 00:30:23,280
Speaker 1: Yeah, the same guy who thinks that his genetics are

566
00:30:23,320 --> 00:30:26,680
Speaker 1: like superior to other people's genetics, and so he has

567
00:30:26,680 --> 00:30:29,560
Speaker 1: as many children as he can to spread his super

568
00:30:29,680 --> 00:30:32,240
Speaker 1: genetics to as many people as he can to repopulate

569
00:30:32,280 --> 00:30:34,680
Speaker 1: the earth within his image.

570
00:30:35,040 --> 00:30:39,800
Speaker 3: Oh okay, that's we got to bring it back. We

571
00:30:39,800 --> 00:30:42,080
Speaker 3: could be here all night and it's going from bad

572
00:30:42,120 --> 00:30:45,960
Speaker 3: to worse. You were talking about his lawsuit against Media Matters.

573
00:30:46,600 --> 00:30:49,720
Speaker 1: Yes, okay, So here's my thing about this lawsuit. Musk's

574
00:30:49,720 --> 00:30:53,840
Speaker 1: suit is saying that Media Matters has manufactured those images

575
00:30:53,840 --> 00:30:56,800
Speaker 1: in the report, but Yacharino has already confirmed in her

576
00:30:56,800 --> 00:30:59,880
Speaker 1: tweet that they are real in a literal sense. The

577
00:31:00,200 --> 00:31:02,240
Speaker 1: only thing that makes sense that they could be arguing

578
00:31:02,360 --> 00:31:05,240
Speaker 1: is that they're saying that Media Matters is like using

579
00:31:05,240 --> 00:31:07,960
Speaker 1: a dummy Twitter account that they have where they have

580
00:31:08,120 --> 00:31:11,360
Speaker 1: followed or engaged with accounts that post Nazi stuff on

581
00:31:11,400 --> 00:31:14,400
Speaker 1: the platform, and that is why they are seeing those

582
00:31:14,560 --> 00:31:17,440
Speaker 1: kinds of tweets in their Twitter feeds next to ads

583
00:31:17,440 --> 00:31:20,520
Speaker 1: for Apple and IBM, Like they followed a bunch of

584
00:31:20,600 --> 00:31:24,160
Speaker 1: Nazi accounts, they followed, they followed our advertisers, and now

585
00:31:24,200 --> 00:31:28,680
Speaker 1: they're just like getting those images. So like manufactured, I

586
00:31:28,680 --> 00:31:31,760
Speaker 1: think is a bit strong, but what they're arguing is

587
00:31:31,800 --> 00:31:35,800
Speaker 1: that the typical Twitter user probably would not be seeing

588
00:31:35,880 --> 00:31:39,680
Speaker 1: those tweets next to those brands advertisings. But as a

589
00:31:39,720 --> 00:31:42,640
Speaker 1: really good piece for tech Crunch points out, Twitter, by

590
00:31:42,640 --> 00:31:45,960
Speaker 1: their own admission in the suit, was aware that these

591
00:31:46,000 --> 00:31:49,440
Speaker 1: accounts posted Nazi content and allowed them to do that

592
00:31:49,800 --> 00:31:52,840
Speaker 1: and allowed them to continue making money through Twitter's revenue

593
00:31:52,840 --> 00:31:56,400
Speaker 1: program until Media Matters pointed it out with the report.

594
00:31:56,840 --> 00:31:59,560
Speaker 1: The piece reads, the lawsuit says that these accounts were

595
00:31:59,760 --> 00:32:02,680
Speaker 1: no to produce extreme fringe content, yet they were not

596
00:32:02,800 --> 00:32:06,360
Speaker 1: demonetized until after Media Matters pointed them out. So x

597
00:32:06,440 --> 00:32:09,520
Speaker 1: knew they were extreme, but did not demonetize them. That

598
00:32:09,680 --> 00:32:11,840
Speaker 1: is what the lawsuit expressly states.

599
00:32:12,080 --> 00:32:14,600
Speaker 2: Okay, hold on, so two things here.

600
00:32:15,760 --> 00:32:20,200
Speaker 3: Their defense was the only reason that those ads had

601
00:32:20,480 --> 00:32:23,480
Speaker 3: Nazi imagery next to them was because we thought the

602
00:32:23,520 --> 00:32:27,240
Speaker 3: account wanted to see Nazi imagery, right, Like that's their

603
00:32:27,280 --> 00:32:31,920
Speaker 3: defense there, Yeah more or less. Yeah, yeah, okay, cool,

604
00:32:33,800 --> 00:32:35,360
Speaker 3: probably not a great So again.

605
00:32:35,560 --> 00:32:40,440
Speaker 1: No dispute that Nazi imagery is like available for people

606
00:32:40,480 --> 00:32:40,880
Speaker 1: to see.

607
00:32:41,400 --> 00:32:45,760
Speaker 3: Yeah, but they're disputing that non Nazis would see it.

608
00:32:45,800 --> 00:32:48,880
Speaker 3: They're like, no, no, we only show Nazi stuff to Nazis.

609
00:32:50,040 --> 00:32:50,280
Speaker 4: Yeah.

610
00:32:50,280 --> 00:32:51,920
Speaker 1: Basically they're saying like you would have to be a

611
00:32:52,000 --> 00:32:56,000
Speaker 1: Nazi who also follows like IBM and Apple to see

612
00:32:56,040 --> 00:32:57,200
Speaker 1: this content, which, like.

613
00:32:58,040 --> 00:33:00,680
Speaker 4: That's probably not a ton of people. But I don't

614
00:33:00,720 --> 00:33:01,400
Speaker 4: think that's.

615
00:33:01,160 --> 00:33:07,080
Speaker 1: Some like wild scenario that like media matters quote manufactured.

616
00:33:07,600 --> 00:33:07,800
Speaker 2: Yeah.

617
00:33:08,320 --> 00:33:12,480
Speaker 3: The whole idea here is that people who believe in

618
00:33:12,520 --> 00:33:18,480
Speaker 3: a free society should be actively trying the thwart Nazis,

619
00:33:18,800 --> 00:33:21,360
Speaker 3: not serve content to them that they want to see.

620
00:33:22,320 --> 00:33:25,120
Speaker 3: That seems to be a point that is missed. But

621
00:33:25,480 --> 00:33:28,440
Speaker 3: the other thing that you just said, these accounts that

622
00:33:28,440 --> 00:33:31,880
Speaker 3: were producing the Nazi material in question in the report,

623
00:33:32,400 --> 00:33:35,479
Speaker 3: they were monetized. They were like getting paid to produce

624
00:33:35,520 --> 00:33:36,760
Speaker 3: this material for Twitter.

625
00:33:37,240 --> 00:33:39,360
Speaker 1: Well that all depends, do you think Elon is actually

626
00:33:39,440 --> 00:33:43,320
Speaker 1: mailing out checks. But yes, they were, Like they were

627
00:33:43,400 --> 00:33:46,120
Speaker 1: monetized according to this report.

628
00:33:46,160 --> 00:33:46,440
Speaker 4: They were.

629
00:33:46,840 --> 00:33:50,640
Speaker 1: They via Twitter's revenue starting program. They were eligible to

630
00:33:50,640 --> 00:33:53,600
Speaker 1: make money. Whether not Elon pays up or not or

631
00:33:53,680 --> 00:33:56,480
Speaker 1: is doing funny math on that, I cannot say, but like, yeah,

632
00:33:56,480 --> 00:33:59,719
Speaker 1: they were able until this report was published, they were monetized.

633
00:33:59,840 --> 00:34:02,760
Speaker 1: It was not until Media Matters published this report that

634
00:34:02,800 --> 00:34:04,240
Speaker 1: Twitter demonetized them.

635
00:34:04,760 --> 00:34:07,560
Speaker 2: How is that not the top line of this report?

636
00:34:07,680 --> 00:34:26,799
Speaker 5: Like, ugh, more after a quick break, let's get right

637
00:34:26,840 --> 00:34:27,399
Speaker 5: back into it.

638
00:34:28,920 --> 00:34:32,719
Speaker 1: So we're talking about the thermonuclear lawsuit that Elon Musk

639
00:34:32,760 --> 00:34:36,360
Speaker 1: filed against Media Matters for their report showing ads next

640
00:34:36,360 --> 00:34:40,160
Speaker 1: to Nazi content on Twitter. Musk and Twitter CEO Lindia

641
00:34:40,200 --> 00:34:43,879
Speaker 1: Parrino are saying that no actual users saw ads next

642
00:34:43,920 --> 00:34:46,319
Speaker 1: to the content, which they do not dispute is on

643
00:34:46,360 --> 00:34:49,560
Speaker 1: the platform notably, but they say that Media Matters is

644
00:34:49,640 --> 00:34:52,760
Speaker 1: only seeing it because they followed or searched a bunch

645
00:34:52,760 --> 00:34:55,960
Speaker 1: of Nazi content themselves. They're arguing that this is Media

646
00:34:56,040 --> 00:35:00,480
Speaker 1: Matters quote manufacturing the content, which they say is fraud

647
00:35:01,200 --> 00:35:06,600
Speaker 1: pretty dubious disinformation. Researcher doctor Carolyn Orbueno actually made a

648
00:35:06,640 --> 00:35:09,760
Speaker 1: really good point about all of this on Twitter, saying

649
00:35:09,760 --> 00:35:12,600
Speaker 1: that what Media Matters has actually done is reveal what's

650
00:35:12,640 --> 00:35:16,000
Speaker 1: known as a data void on Twitter. She said the

651
00:35:16,080 --> 00:35:18,680
Speaker 1: issue at the heart of Elon Musk's lawsuit against Media

652
00:35:18,719 --> 00:35:22,000
Speaker 1: Matters is who is responsible for data voids when they're discovered.

653
00:35:22,360 --> 00:35:25,200
Speaker 1: Media Matters identified a bunch of many data voids on

654
00:35:25,239 --> 00:35:28,680
Speaker 1: Twitter where problematic content lives, and then reported on it

655
00:35:28,800 --> 00:35:31,560
Speaker 1: rather than exploiting them. When you search for an obscure

656
00:35:31,640 --> 00:35:34,400
Speaker 1: or rarely used hashtag or set of keywords like what

657
00:35:34,520 --> 00:35:36,759
Speaker 1: Media Matters did and what a lot of people are

658
00:35:36,760 --> 00:35:39,479
Speaker 1: doing now on Twitter, you will often stumble upon data

659
00:35:39,520 --> 00:35:43,080
Speaker 1: voids or informational dark spaces. That is not fraud. This

660
00:35:43,239 --> 00:35:46,759
Speaker 1: is a well known phenomena. Data voids or informational dark

661
00:35:46,800 --> 00:35:52,000
Speaker 1: spaces are extremely vulnerable to manipulation and exploitation, often by extremists.

662
00:35:52,280 --> 00:35:55,239
Speaker 1: It's not fraud when someone searches for and identifies a

663
00:35:55,320 --> 00:35:58,920
Speaker 1: data void. In this case, Media Matters use the platform's

664
00:35:58,960 --> 00:36:02,720
Speaker 1: own search function to identify ads that Twitter itself placed

665
00:36:02,760 --> 00:36:05,759
Speaker 1: on the platforms. Twitter could have removed ads from these

666
00:36:05,760 --> 00:36:09,879
Speaker 1: search terms, but they didn't listen. As somebody who has

667
00:36:10,000 --> 00:36:12,640
Speaker 1: done the kind of work that Media Matters is doing

668
00:36:12,640 --> 00:36:15,160
Speaker 1: with the support in a kind of way, like gathering

669
00:36:15,320 --> 00:36:19,040
Speaker 1: content that breaks social media platforms as stated terms of

670
00:36:19,080 --> 00:36:22,160
Speaker 1: service and user agreements. Twitter really ought to be thanking

671
00:36:22,239 --> 00:36:25,120
Speaker 1: Media Matters for doing what should be their jobs or

672
00:36:25,120 --> 00:36:27,319
Speaker 1: the jobs of their trust and safety teams. I'm sure

673
00:36:27,360 --> 00:36:29,920
Speaker 1: it's like one person, if they have anybody there at all,

674
00:36:30,040 --> 00:36:33,759
Speaker 1: and doing that unpaid. Might I add right, like being like, hey,

675
00:36:34,480 --> 00:36:37,400
Speaker 1: this is your terms of service. Here's a bunch of

676
00:36:37,520 --> 00:36:41,600
Speaker 1: content that you are monetized that, per your terms of service,

677
00:36:41,719 --> 00:36:45,000
Speaker 1: should not be monetized. That is actually a favor that

678
00:36:45,360 --> 00:36:48,200
Speaker 1: Media Matters is doing to Twitter. They honestly should be

679
00:36:48,640 --> 00:36:51,080
Speaker 1: doing it themselves, but they're not doing it. So like

680
00:36:51,520 --> 00:36:53,759
Speaker 1: it's just such thankless work. And I feel like in

681
00:36:53,800 --> 00:36:57,879
Speaker 1: a different world that work would not be punished by

682
00:36:57,920 --> 00:37:00,640
Speaker 1: a lawsuit. It would actually be you would be thanked

683
00:37:00,680 --> 00:37:03,719
Speaker 1: for it, and in another world thanks for it by

684
00:37:03,920 --> 00:37:05,120
Speaker 1: being given fucking money.

685
00:37:05,719 --> 00:37:09,320
Speaker 2: Yeah, that would be a different world for sure.

686
00:37:09,520 --> 00:37:12,480
Speaker 1: As ridiculous as all of this is, even more ridiculously

687
00:37:12,920 --> 00:37:17,280
Speaker 1: Texas Attorney General Ken Paxton, do you remember Ken Paxton?

688
00:37:17,440 --> 00:37:20,279
Speaker 2: I do? Yeah, He's like, what do you remember about him.

689
00:37:20,600 --> 00:37:26,000
Speaker 3: Uh, he's risen to national clown prominence as the attorney

690
00:37:26,080 --> 00:37:30,480
Speaker 3: general in Texas who was indicted by his own party,

691
00:37:30,840 --> 00:37:35,319
Speaker 3: that party being Republicans in Texas for corruption. He was

692
00:37:35,760 --> 00:37:42,640
Speaker 3: it's not a party known for I don't know, throwing

693
00:37:42,680 --> 00:37:46,680
Speaker 3: out its own like his party was in control of

694
00:37:46,960 --> 00:37:50,800
Speaker 3: the legislature in Congress and they indicted him for corruption

695
00:37:51,480 --> 00:37:56,000
Speaker 3: and somehow he beat it. And we were talking about

696
00:37:56,000 --> 00:37:59,360
Speaker 3: his some previous little stunt of his right, Yeah.

697
00:37:59,120 --> 00:38:01,000
Speaker 1: His last the last time that we talked about him

698
00:38:01,000 --> 00:38:03,399
Speaker 1: on the podcast, he was doing a little stunt where

699
00:38:03,400 --> 00:38:08,319
Speaker 1: he was suing the platform YELP because YELP was accurately,

700
00:38:09,000 --> 00:38:14,319
Speaker 1: per his own office, accurately describing crisis pregnancy centers on

701
00:38:14,440 --> 00:38:16,960
Speaker 1: their platform. And so he was like, I'm gonna sue

702
00:38:17,000 --> 00:38:21,280
Speaker 1: them because this is Texas. So Texas Attorney General Ken Paxton,

703
00:38:21,360 --> 00:38:23,560
Speaker 1: don't worry because he is on the case. He is

704
00:38:23,560 --> 00:38:26,400
Speaker 1: going to open up an investigation into media matters for

705
00:38:26,560 --> 00:38:31,040
Speaker 1: potential fraudulent activity himself only having been recently as in

706
00:38:31,120 --> 00:38:34,360
Speaker 1: like a few months ago, cleared up corruption and problem

707
00:38:34,560 --> 00:38:35,640
Speaker 1: activity himself.

708
00:38:35,880 --> 00:38:37,080
Speaker 4: Keep that in mind, he.

709
00:38:37,080 --> 00:38:39,480
Speaker 3: Says he's just the guy to go after them. He

710
00:38:40,040 --> 00:38:42,400
Speaker 3: if there's one thing he knows. It's fraudulent activity.

711
00:38:43,600 --> 00:38:46,880
Speaker 1: He was like, oh, oh, frauds and scams. That's my

712
00:38:47,040 --> 00:38:48,640
Speaker 1: forte baby, I'm on it.

713
00:38:51,920 --> 00:38:52,440
Speaker 4: He said.

714
00:38:52,840 --> 00:38:55,279
Speaker 1: We are examining the issue closely to ensure that the

715
00:38:55,280 --> 00:38:58,520
Speaker 1: public has not been deceived by the schemes of radical

716
00:38:58,600 --> 00:39:01,239
Speaker 1: left being organizations who would like nothing more than to

717
00:39:01,280 --> 00:39:04,600
Speaker 1: limit freedom by reducing participation in the public square.

718
00:39:05,120 --> 00:39:07,040
Speaker 2: Oh my god, so yeah.

719
00:39:06,880 --> 00:39:09,960
Speaker 1: I mean, like, it doesn't surprise me that he's pulling

720
00:39:10,000 --> 00:39:12,439
Speaker 1: a little stunt sticking up for Elon Musk game, Reckon,

721
00:39:12,520 --> 00:39:15,600
Speaker 1: that's game. Like He's like, oh, scams and stunts, scams

722
00:39:15,600 --> 00:39:17,239
Speaker 1: and stunts, right or right, right, let's do this.

723
00:39:17,760 --> 00:39:20,239
Speaker 3: Is there some sort of like Texas connection here that

724
00:39:20,320 --> 00:39:23,520
Speaker 3: I don't know about. I don't know, like I'm giving

725
00:39:23,560 --> 00:39:26,560
Speaker 3: him too much credit. I guess it's not like that

726
00:39:26,960 --> 00:39:29,760
Speaker 3: kind of legitimate thing. It's it's a little stunt.

727
00:39:29,960 --> 00:39:31,200
Speaker 4: Yeah, it's a little stunt.

728
00:39:31,480 --> 00:39:34,160
Speaker 1: So Twitter assuming Media Matters for defamation, saying that they

729
00:39:34,200 --> 00:39:37,520
Speaker 1: lost revenue when the brands left the platform. However, most

730
00:39:37,560 --> 00:39:40,280
Speaker 1: of these brands did not say it was media matters

731
00:39:40,320 --> 00:39:45,080
Speaker 1: as report as the reason why they left. Lionsgate specifically

732
00:39:45,120 --> 00:39:47,920
Speaker 1: said that it was Elon Musk's anti Semitic tweet was

733
00:39:47,920 --> 00:39:50,480
Speaker 1: the reason why they left. So this is really just

734
00:39:50,520 --> 00:39:54,280
Speaker 1: like classic Elon blaming everyone else for his own behavior

735
00:39:54,320 --> 00:39:56,719
Speaker 1: when that behavior causes a problem. He did the same

736
00:39:56,719 --> 00:39:58,839
Speaker 1: thing earlier this year when he launched a lawsuit against

737
00:39:58,840 --> 00:40:01,680
Speaker 1: the Center for Countering Digital Hey for publishing a report

738
00:40:01,719 --> 00:40:05,040
Speaker 1: about how hate speech was flourishing on the platform since

739
00:40:05,120 --> 00:40:08,160
Speaker 1: Musk took over. Like, this is just not how good

740
00:40:08,280 --> 00:40:11,719
Speaker 1: leaders lead, Like blaming everyone and passing the buck to

741
00:40:11,760 --> 00:40:13,000
Speaker 1: avoid responsibility.

742
00:40:13,480 --> 00:40:20,000
Speaker 3: Yeah, I mean, just continuously suing every organization that talks

743
00:40:20,040 --> 00:40:23,520
Speaker 3: about rampant hate speech on Twitter kind of gives the

744
00:40:23,520 --> 00:40:27,800
Speaker 3: impression that he's not really that concerned with hate speech

745
00:40:27,840 --> 00:40:28,360
Speaker 3: on Twitter.

746
00:40:28,880 --> 00:40:31,399
Speaker 1: No, And I think that's what bugs me so much

747
00:40:31,400 --> 00:40:35,280
Speaker 1: about it. When Linda Yakarino is talking about like, oh, brands,

748
00:40:35,320 --> 00:40:38,279
Speaker 1: like it's safe to be here, your content won't be

749
00:40:38,320 --> 00:40:42,799
Speaker 1: next to Nazi pictures, It's like that's the only way

750
00:40:42,840 --> 00:40:47,120
Speaker 1: they can conceptualize how a platform can be can feel

751
00:40:47,120 --> 00:40:50,080
Speaker 1: healthy is that if brands feel good to show up there.

752
00:40:50,120 --> 00:40:53,239
Speaker 1: I just think it's like the wrong metric, and it

753
00:40:53,320 --> 00:40:59,279
Speaker 1: really makes me wonder if they meaningfully care what the

754
00:40:59,360 --> 00:41:02,239
Speaker 1: platform is like, do they really care that hate speeches there?

755
00:41:02,239 --> 00:41:05,200
Speaker 1: Do they really care that, like, you know, there are

756
00:41:05,239 --> 00:41:09,000
Speaker 1: slurs and conspiracy theories and anti semitism, Like I would argue, no,

757
00:41:09,160 --> 00:41:11,640
Speaker 1: I think the only thing they care about is our

758
00:41:11,719 --> 00:41:14,960
Speaker 1: brands there, because they're ninety percent of our revenue. And

759
00:41:15,040 --> 00:41:17,480
Speaker 1: speaking of Linda Yakarno, you know, we've talked about her

760
00:41:17,520 --> 00:41:20,080
Speaker 1: a lot on the podcast. I'm kind of fascinated by

761
00:41:20,120 --> 00:41:21,920
Speaker 1: her in a lot of ways. I see her as

762
00:41:21,920 --> 00:41:26,600
Speaker 1: this sort of very intriguing figure. Forbes actually reported that

763
00:41:26,920 --> 00:41:32,120
Speaker 1: Lindiakrino's advertising colleagues have been texting her trying to be like, honey,

764
00:41:32,120 --> 00:41:34,719
Speaker 1: you need to get out of Twitter to save her

765
00:41:34,719 --> 00:41:37,520
Speaker 1: own reputation, because they are worried that she's going to

766
00:41:37,600 --> 00:41:41,160
Speaker 1: tank her own personal brand by being associated with an

767
00:41:41,160 --> 00:41:45,200
Speaker 1: anti Semite, racist, misogynist like Elon Musk.

768
00:41:45,640 --> 00:41:47,279
Speaker 4: Marketing industry veteran.

769
00:41:47,160 --> 00:41:50,320
Speaker 1: Luke Pascalis said that he texted Linda Yakrino, and he

770
00:41:50,400 --> 00:41:54,480
Speaker 1: told CNN she thinks quitting is failing. She believes that

771
00:41:54,520 --> 00:41:56,719
Speaker 1: she can mother Elon Musk into someone who could be

772
00:41:56,760 --> 00:42:00,880
Speaker 1: respected by the advertising community, and that chip has definitely sailed,

773
00:42:01,160 --> 00:42:03,120
Speaker 1: But she's not going to come off the mechanical bull

774
00:42:03,400 --> 00:42:05,319
Speaker 1: without all of us telling her it's time to go.

775
00:42:05,680 --> 00:42:07,640
Speaker 1: And I believe that there's been a ground swell of

776
00:42:07,640 --> 00:42:10,520
Speaker 1: a lot of people, such as myself, saying save yourself.

777
00:42:11,000 --> 00:42:15,040
Speaker 3: So I'm curious, like, did you know who Linda Yakarino

778
00:42:15,360 --> 00:42:18,200
Speaker 3: was before she became CEO of Twitter? Was she like

779
00:42:18,239 --> 00:42:21,160
Speaker 3: a known person that people knew about?

780
00:42:21,520 --> 00:42:22,600
Speaker 4: I knew who she was.

781
00:42:22,880 --> 00:42:25,800
Speaker 1: I think that she was definitely a known high level

782
00:42:25,840 --> 00:42:28,960
Speaker 1: figure in media advertising, like she was a big wig

783
00:42:28,960 --> 00:42:32,880
Speaker 1: at NBC, But I don't know that like your average

784
00:42:32,920 --> 00:42:35,200
Speaker 1: person and be like, oh, Linda Yakarino, of course. Also,

785
00:42:35,239 --> 00:42:38,080
Speaker 1: she's someone who is like speaks publicly a lot, Like

786
00:42:38,120 --> 00:42:39,960
Speaker 1: That's how I knew of her. Was like, she's someone

787
00:42:39,960 --> 00:42:42,720
Speaker 1: who like would go to conferences and like in public

788
00:42:42,840 --> 00:42:44,279
Speaker 1: speaking a lot.

789
00:42:44,560 --> 00:42:45,879
Speaker 2: Yeah, I guess that makes sense.

790
00:42:46,640 --> 00:42:49,000
Speaker 3: I had never heard of her before she took over

791
00:42:49,320 --> 00:42:55,239
Speaker 3: as CEO at Twitter, And I'm continuously puzzled by I

792
00:42:55,239 --> 00:42:58,120
Speaker 3: guess the benefit of doubt that people give her, or

793
00:42:58,200 --> 00:43:00,919
Speaker 3: like the good will that people seem to have towards her,

794
00:43:01,480 --> 00:43:05,200
Speaker 3: because like I only knew her as coming in to

795
00:43:05,600 --> 00:43:11,920
Speaker 3: try to whitewash the tanking Twitter brand as Elon like

796
00:43:12,480 --> 00:43:15,759
Speaker 3: rode the sinking ship down. Every statement she makes just

797
00:43:15,800 --> 00:43:20,720
Speaker 3: seems like sad, like, oh there's you know, don't worry,

798
00:43:20,719 --> 00:43:24,440
Speaker 3: there's ninety percent less Nazi stuff now.

799
00:43:24,600 --> 00:43:28,480
Speaker 1: Yeah, I mean, I give Linda Yacharino no goodwill.

800
00:43:29,320 --> 00:43:32,040
Speaker 4: We said this when when she first was announced. If

801
00:43:32,080 --> 00:43:33,879
Speaker 4: in this day and age, you.

802
00:43:33,840 --> 00:43:38,160
Speaker 1: Are willingly deciding to leave your job and to sign

803
00:43:38,239 --> 00:43:42,520
Speaker 1: up to work alongside Elon Muskat Twitter, you know exactly

804
00:43:42,560 --> 00:43:46,240
Speaker 1: what you're getting into you like, there is no world

805
00:43:46,320 --> 00:43:47,120
Speaker 1: where you can be like.

806
00:43:47,120 --> 00:43:49,600
Speaker 4: I didn't know or I thought I could fix him.

807
00:43:50,320 --> 00:43:53,560
Speaker 4: You knew, we all saw you made a choice.

808
00:43:53,920 --> 00:43:57,560
Speaker 1: I'm just really curious what her inner monologue is like

809
00:43:58,520 --> 00:44:02,560
Speaker 1: and how she feels about how it's going. Her tweets

810
00:44:02,560 --> 00:44:06,320
Speaker 1: are absurd, like when Elon Musk is like tweeting anti

811
00:44:06,320 --> 00:44:09,600
Speaker 1: Semitic stuff and it's like making headlines. She'll literally be

812
00:44:09,600 --> 00:44:15,799
Speaker 1: tweeting like does anyone like beverages? I love beverages, not that,

813
00:44:16,000 --> 00:44:18,040
Speaker 1: but basically that, you know what I mean, Like the

814
00:44:18,080 --> 00:44:21,160
Speaker 1: most inane stuff, And it's it's just like it's hard

815
00:44:21,200 --> 00:44:23,280
Speaker 1: to not I don't know, maybe it's maybe I'm alone

816
00:44:23,280 --> 00:44:25,320
Speaker 1: in this. It's hard for me to not be fascinated

817
00:44:25,320 --> 00:44:25,640
Speaker 1: by her.

818
00:44:26,080 --> 00:44:29,879
Speaker 3: Yeah, you're you're not alone there, I guess, I guess

819
00:44:29,880 --> 00:44:33,520
Speaker 3: I get it. You know, I also find her interesting.

820
00:44:33,560 --> 00:44:35,879
Speaker 3: I don't really know why though to that.

821
00:44:35,840 --> 00:44:38,360
Speaker 1: Point, you know, lawsuit, don't no lawsuit. This is all

822
00:44:38,440 --> 00:44:41,360
Speaker 1: bad for Twitter's economic outlook, all of the verification in

823
00:44:41,400 --> 00:44:45,320
Speaker 1: Twitter Blue subscriptions are not really paying off. Advertising is

824
00:44:45,360 --> 00:44:49,040
Speaker 1: still ninety percent of Twitter's revenue model. According to tech Crunch.

825
00:44:49,080 --> 00:44:52,080
Speaker 1: Before any of this even happened, Twitter's ad revenues were

826
00:44:52,120 --> 00:44:55,600
Speaker 1: already forecasted to be declining by fifty four point four

827
00:44:55,640 --> 00:44:58,360
Speaker 1: percent from twenty twenty two to twenty twenty three, a

828
00:44:58,400 --> 00:45:02,600
Speaker 1: pretty sizeable drop. But I wanted to add that for context.

829
00:45:03,160 --> 00:45:07,200
Speaker 1: But I actually don't think that like how much money

830
00:45:07,239 --> 00:45:11,120
Speaker 1: Twitter is making for how or whether it can wo

831
00:45:11,239 --> 00:45:14,279
Speaker 1: brands and keep brands like is the ultimate sign of

832
00:45:14,320 --> 00:45:16,680
Speaker 1: health for the platform. And I really want to caution

833
00:45:16,840 --> 00:45:19,440
Speaker 1: folks about making it seem like those are the only

834
00:45:19,560 --> 00:45:22,960
Speaker 1: metrics that matter, because the real marker of the health

835
00:45:23,000 --> 00:45:24,840
Speaker 1: of a platform, in my book, is whether or not

836
00:45:24,880 --> 00:45:27,440
Speaker 1: people who can actually show up there and whether it

837
00:45:27,440 --> 00:45:30,080
Speaker 1: feels good when they do, right, Like, are you able

838
00:45:30,120 --> 00:45:32,920
Speaker 1: to use the platform to find accurate and timely relevant

839
00:45:32,920 --> 00:45:35,360
Speaker 1: information about what's going on in the world. Can you

840
00:45:35,400 --> 00:45:38,360
Speaker 1: find community there? Like do you feel relatively safe showing

841
00:45:38,440 --> 00:45:41,120
Speaker 1: up there? These are things that make an online space

842
00:45:41,160 --> 00:45:43,560
Speaker 1: worth showing up to. And it feels like more and

843
00:45:43,640 --> 00:45:46,920
Speaker 1: more that space in Twitter is gone and perhaps not

844
00:45:46,960 --> 00:45:51,279
Speaker 1: coming back. But we all deserve to have healthy digital platforms,

845
00:45:51,320 --> 00:45:54,080
Speaker 1: Like I truly believe that this is something that we

846
00:45:54,239 --> 00:45:56,880
Speaker 1: deserve and should be able to expect from our digital

847
00:45:56,920 --> 00:45:57,840
Speaker 1: media landscape.

848
00:45:58,560 --> 00:46:03,759
Speaker 3: Yeah, it's it's what people want, you know, community information,

849
00:46:06,600 --> 00:46:08,480
Speaker 3: not to see a bunch of Hitler stuff.

850
00:46:09,840 --> 00:46:14,719
Speaker 1: Yeah, baseline not Hitler stuff like that's like, can we

851
00:46:14,760 --> 00:46:15,440
Speaker 1: get that?

852
00:46:15,440 --> 00:46:18,920
Speaker 4: That would be great, that would be good, Like we.

853
00:46:19,040 --> 00:46:20,000
Speaker 2: Joked, but you were saying.

854
00:46:20,200 --> 00:46:21,840
Speaker 3: A couple of weeks ago, somebody like called you a

855
00:46:21,960 --> 00:46:25,000
Speaker 3: racial slur, like not cool, not.

856
00:46:25,040 --> 00:46:28,120
Speaker 1: Just a racial slur, a brand new racial slur that

857
00:46:28,160 --> 00:46:30,319
Speaker 1: I had never heard before. I was like, I think

858
00:46:30,360 --> 00:46:32,239
Speaker 1: this is a racial slur. I had to google it

859
00:46:32,239 --> 00:46:34,120
Speaker 1: and I was like, oh wow, I got a new one.

860
00:46:34,680 --> 00:46:37,800
Speaker 3: Who knew it was a new one, not an antiquated one.

861
00:46:38,120 --> 00:46:40,000
Speaker 3: They're coming up with new ones now.

862
00:46:39,880 --> 00:46:41,799
Speaker 1: They're coming up with new ones and they're doing it

863
00:46:41,840 --> 00:46:45,000
Speaker 1: on Twitter, so I want to know, like, how are

864
00:46:45,040 --> 00:46:46,880
Speaker 1: you feeling about being on Twitter?

865
00:46:46,920 --> 00:46:48,279
Speaker 4: I did a whole kind of like.

866
00:46:48,719 --> 00:46:52,640
Speaker 1: Emotional deep dive about my wrestling with my choice to

867
00:46:52,680 --> 00:46:55,560
Speaker 1: stay or leave the platform. But tell me how you're feeling,

868
00:46:55,600 --> 00:46:57,480
Speaker 1: Like are you on Twitter?

869
00:46:57,600 --> 00:46:59,400
Speaker 4: Have you left Twitter? Are you still on? But like

870
00:46:59,520 --> 00:47:01,600
Speaker 4: using it? Last? Let us know? I really want to know.

871
00:47:01,640 --> 00:47:03,759
Speaker 1: You can hit us up at hello at tangoity dot

872
00:47:03,760 --> 00:47:10,520
Speaker 1: com and thanks so much for listening. Got a story

873
00:47:10,520 --> 00:47:12,400
Speaker 1: about an interesting thing in tech, or just want to

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00:47:12,440 --> 00:47:14,800
Speaker 1: say hi. You can reach us at hello at tangody

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Speaker 1: dot com. You can also find transcripts for today's episode

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Speaker 1: at tengody dot com. There Are No Girls on the

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Speaker 1: Internet was created by me Bridget Todd. It's a production

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Speaker 1: of iHeartRadio and Unbossed.

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Speaker 5: Creative.

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Speaker 1: Jonathan Strickland is our executive producer. Tari Harrison is our

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Speaker 1: producer and sound engineer. Michael Almado is our contributing producer.

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Speaker 1: I'm your host, Bridget Todd. If you want to help

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Speaker 1: us grow, rate and review us on Apple podcasts. For

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Speaker 1: more podcasts from iHeartRadio, check out the iHeartRadio app, Apple Podcasts,

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Speaker 1: or wherever you get your podcasts,