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Speaker 1: Hello the Internet, and welcome to Season to thirty four,

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Speaker 1: Episode five of The Daily Like Guys, It's a production

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Speaker 1: of My Heart Radio. This is a podcast where we

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Speaker 1: take a deep dive into America's shared consciousness. It is Friday, April,

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Speaker 1: which of course means it's National Hairball Awareness Day. You

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Speaker 1: gotta be aware of the hairballs for the health of

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Speaker 1: your animal friends. You know, maybe groom if your cats

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Speaker 1: haven't coughing up a lot of hairballs, help out with

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Speaker 1: the grooming. I don't know my cats is Luckily you

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Speaker 1: don't have that issue. Um, but yeah, bring awareness because yeah,

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Speaker 1: these are not like pellets like an owl coughs up

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Speaker 1: after swallowing a rabbit hole. This is these are from

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Speaker 1: the grooming process. Yeah, and then you take because you know,

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Speaker 1: cats groom themselves and then they ingest their hair and

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Speaker 1: they either pass it, you know, the naturally, or they

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Speaker 1: cough them up as we all even see coughing up

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Speaker 1: a hairball. Um, yeah, I didn't. I didn't realize that

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Speaker 1: it could be. It could get so bad. That's that's

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Speaker 1: I'm blessed with cats who don't have this issue. So yeah,

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Speaker 1: please be aware of folks. Hair balls are out there.

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Speaker 1: You got the you got the short hair ones right

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Speaker 1: like the doctor sucking their coats as long as fun.

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Speaker 1: Oh they are well, oh my god, you see their

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Speaker 1: tails look like fucking like you thought a marching band

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Speaker 1: was coming through these plumes that's up in there. Um. Alright, well,

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Speaker 1: I'm Jack O'Brien a K I'll bite you with my

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Speaker 1: vampire straws. You've never bled this fast before. All I

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Speaker 1: wanted was to leave two holes, but you you stay

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Speaker 1: ached me. That is courtesy of t Z Burner. Um.

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Speaker 1: It's about the physiology of vampire teeth and the fact

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Speaker 1: that I I believed for a long time still kind

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Speaker 1: of believe that their teeth suck the blood through them. Um,

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Speaker 1: like reverse poisonous snake bites. Um, Miles and I both

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Speaker 1: believe that. Hey who's Miles. Uh well, I'm thrilled to

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Speaker 1: be joined. As always buy my co host, Mr Miles.

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Speaker 1: If you having cruisial problems, I feel bad for your son.

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Speaker 1: I got eighty eight keys, but eight playing one hit me. Okay.

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Speaker 1: Yesterday's guest Nicole was talking about her She was on

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Speaker 1: a Christian it's a piano show called eight eight and

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Speaker 1: the dude who was supposedly playing the piano. It was

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Speaker 1: pantomiming the whole time with a backage easier to staff

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Speaker 1: a position of guy. Who I just love that, Like

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Speaker 1: I would love to do a show because like I

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Speaker 1: feel like I could fake play a lot of instruments,

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Speaker 1: Like I can play a couple instruments, but like I

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Speaker 1: would love to pick up like a flute and just

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Speaker 1: do a fake flute solo hop on piano do on that.

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Speaker 1: I feel like I could sell it. Yeah, No, I

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Speaker 1: mean just watching you type. You're just finishing an email

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Speaker 1: before we started recording, and it was like watching you know,

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Speaker 1: somebody just jam out on the on the piano. You

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Speaker 1: had your eyes closed, you were standing up, using your

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Speaker 1: butt at times, elbows the Jimmy Hendrix of Maybs Beacons. Um, well,

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Speaker 1: we are thrilled to be joined in our third seat.

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Speaker 1: Oh yeah, and by the way, apologies for anybody who

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Speaker 1: got some audio issues on yesterday's episode up top. Uh

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Speaker 1: they have been fixed if you want to go redownload that.

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Speaker 1: Um yet, yeah, are audio just was not there for

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Speaker 1: like the first ten minutes. Um, it's we're good, We're

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Speaker 1: back and we're thrilled to be joining our third seat

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Speaker 1: by the extremely talented podcast host and digital activist who

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Speaker 1: you can hear on her brilliant podcast There Are No

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Speaker 1: Girls on the Internet. It's Bridget Tale. Oh. I love

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Speaker 1: the warm welcome, thank you for having me. I have

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Speaker 1: to tell you I once went to a Britney Spears

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Speaker 1: concert where when she played the song every time, she

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Speaker 1: was sitting at a piano. But then and there was

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Speaker 1: piano music playing, and that she was playing it, and

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Speaker 1: then she got up from the piano and the piano

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Speaker 1: music continued. Yeah, good, we don't care, you know, we

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Speaker 1: don't care. It's a show, you know, why not? That's

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Speaker 1: a I love when an artist wants to sit at

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Speaker 1: a piano like Axel Rose used to love to do that.

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Speaker 1: I think he didn't play like every once in a while,

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Speaker 1: but it was it was important for him to open

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Speaker 1: up the MTV Video Music Awards performance sitting at a piano.

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Speaker 1: You know. That was like, Oh, you thought I was

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Speaker 1: just a rock star. No, no, no, no, really, I'm

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Speaker 1: kind of a I'm a musician, a composer. I guess

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Speaker 1: you could say, just playing night. Yes, yeah, for sure.

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Speaker 1: Who are they emulating? Is that like an old Sinatra thing?

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Speaker 1: Or like Tony Bennett. You know that, because that's like

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Speaker 1: the thing where it's like, all right, we had enough

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Speaker 1: of that, enough a rocket, let's get let's get over

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Speaker 1: to this piano really quick, you know what I mean?

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Speaker 1: Spotlight because that's like a trope right for like music concerts,

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Speaker 1: and I know it obviously starts somewhere like is it Elvis?

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Speaker 1: M did Elvis? Remember I've never seen Elvis at a piano,

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Speaker 1: but I'm not a huge Elvis fan. So oh yeah, man, um,

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Speaker 1: that most famous one he did right before he died.

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Speaker 1: I don't like to acknowledge that he died. I actually

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Speaker 1: don't believe he did. So okay, my bad, My bad,

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Speaker 1: My bad. I forgot about that Men and Black, Men

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Speaker 1: and Black But yeah, he plays a Yeah, he plays piano.

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Speaker 1: You don't know that. M hmm. I mean, what's that

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Speaker 1: track he played right like one of the last concerts

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Speaker 1: he did. It's like a really iconic performance and everyone's like,

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Speaker 1: oh shit, this makes me think of Elton John Melody Okay,

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Speaker 1: chained melody. Oh yeah, and he's like, you know, you

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Speaker 1: could tell he looks he looks unhealthy as fuck in

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Speaker 1: that show is the last concert and he's ripping the piano.

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Speaker 1: Damn all right, Elvis. Um, I mean that that does

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Speaker 1: seem to play against type, right, you you typically want

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Speaker 1: to see the whole, the whole, Elvis. You want to

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Speaker 1: see the hip swiveling, the honey and the hips and

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Speaker 1: uh happening those days. So I mean it does give

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Speaker 1: you a chance to sit down, uh when when you're

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Speaker 1: maybe a rock star who who's past their physical prime,

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Speaker 1: you know, and just be like chilling. Um. Yeah, I

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Speaker 1: just wanted I just again, I think I do respect

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Speaker 1: the mid concert piano break. Yeah. I think Elton, John,

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Speaker 1: Stevie Wonder Like, those are the people who I think

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Speaker 1: of when I think of somebody at a concert just

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Speaker 1: destroying the room from behind a piano. Yeah. Well, I

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Speaker 1: mean yeah, because we think. I think the fun part

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Speaker 1: is when someone who is not known for playing keys

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Speaker 1: is like to get to the keys real quick. But Brittany, Brittany,

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Speaker 1: I love the Brittany that. That's an amazing Yeah, one

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Speaker 1: of the best concerts of my entire life. How old

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Speaker 1: were you? Oh? I was fully in my twenties that

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Speaker 1: long ago. Yeahs was it the Vegas Show? It was

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Speaker 1: Vegas And I'm looking back, you know, I know those shows.

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Speaker 1: Now we know that, like, perhaps those shows were not

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Speaker 1: as pleasant for her as they were for me and

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Speaker 1: the audience. But who she is? Dot keep appearing on

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Speaker 1: her right. You know. I saw this video of her

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Speaker 1: where she was performing in Vegas and she kept talking

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Speaker 1: about how she was sick and she didn't feel well.

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Speaker 1: And then you watched the documentary Framing Britney Spears and

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Speaker 1: she talks about how they forced her to perform when sick,

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Speaker 1: and those concerts have a whole new like very grim meeting. Now. Yeah,

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Speaker 1: not to bum everybody out, yeah, but I mean, like,

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Speaker 1: let's let's just you know, put some respect on on

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Speaker 1: her name and what the what she sacrificed so you

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Speaker 1: guys could see the best concerts you've ever seen. That's

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Speaker 1: why she had to play the fake piano. Okay, Bridget,

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Speaker 1: she would have played the real one, really played any

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Speaker 1: other day, but she was sick. She was doing the game. Yeah,

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Speaker 1: maybe you saw her flu game, like her greatest work

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Speaker 1: one of the anyway, Um, all right, well, Bridget, we're

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Speaker 1: going to get to know you a little bit better

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Speaker 1: in a moment. First, we're gonna tell her listeners a

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Speaker 1: couple of things. We're talking about Um, we're going to

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Speaker 1: talk about the Elon Musk ship in the context of

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Speaker 1: you know, online harassment of marginalized groups of people. Um,

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Speaker 1: and just generally it feels like Elon Musk has replaced

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Speaker 1: Trump as the thing that just takes up all the oxygen.

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Speaker 1: And everyone's like so fucking tired of hearing people talk

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Speaker 1: about Elon Musk. And then wait, what do you have

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Speaker 1: the fan people? Yeah, yeah, yeah, and then you have

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Speaker 1: the super fans. Um. So we'll talk about that. We'll

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Speaker 1: talk about Russia's uh neo knots, the raid on like

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Speaker 1: what what they claimed were neo Nazi journalists. Uh there,

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Speaker 1: the it appears to be a wildly unconvincing frame job. Um.

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Speaker 1: And so I just want to talk about that general

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Speaker 1: trend of like not even trying very hard when you lie, um,

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Speaker 1: and you know, draw draw line between that Trump even

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Speaker 1: even like like with a Simpsons ask like literal misshap

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Speaker 1: trying to frame someone like you literally got okay, wow,

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Speaker 1: not dealing with our a team here. Yeah, I gotta

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Speaker 1: get those sim sim cards. Oh whoops, Um, did you

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Speaker 1: see that? They More on that, More on that in

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Speaker 1: a moment. We'll dip back into the NPR well to

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Speaker 1: just look a little bit more into the history and

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Speaker 1: to the A S. M R. Of it all um,

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Speaker 1: and we might even get to some Broadway shows all

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Speaker 1: that plenty more. The first bridget we do like to

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Speaker 1: ask our guest, what is something from your search history?

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Speaker 1: A question that I googled recently is who closes the

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Speaker 1: bus door when the bus driver gets off the bus? Oh?

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Speaker 1: My god, think about it. I saw this TikTok that

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Speaker 1: asked that question, and I thought this podcast is over.

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Speaker 1: I mean medical care, is this podcast is over? That's

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Speaker 1: all we're talking about. I still haven't gotten to the

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Speaker 1: bottom of it. If anyone knows how how bus stores

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Speaker 1: get opened and closed when the driver is off the bus,

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Speaker 1: I would love to know. Yeah, is it a timer?

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Speaker 1: You know what I mean? Like when you're sitting an alarm,

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Speaker 1: Like you know, if you close up at like a

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Speaker 1: you know, retail gig, you're like, all right, we're gonna

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Speaker 1: bring the gate down, let me get the alarm up,

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Speaker 1: and you got like dirty seconds. I'd imagine it's much simpler,

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Speaker 1: Like they're like there's a fucking lever, you know, like

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Speaker 1: in a hook, or you can just pull this one

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Speaker 1: partner close, But I like the philosophical question, Yeah, who

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Speaker 1: closes the door for the bus driver? The superproducer Chris

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Speaker 1: was filling in for superproducer Justin has suggested they do

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Speaker 1: it through the window. Um, I'm not sure, like that

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Speaker 1: was that was the first thing that popped into my mind,

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Speaker 1: and like there there's that like smallest window drivers side

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Speaker 1: and like that, Like the first thing I picture when

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Speaker 1: you asked the question, was them like sliding out like

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Speaker 1: one limb at a time of that just being like dah,

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Speaker 1: and that's just like you you go to the bus

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Speaker 1: depot and see this horrible, shameful event. Um, but Chris,

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Speaker 1: if you have any proof of that or if that

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Speaker 1: was just an idle suggestion, let us know. I mean,

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Speaker 1: that's by far the simplest and most logical way to

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Speaker 1: do it. Like, Yeah, I opened the door and the

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Speaker 1: button that's right there, I just go on the other

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Speaker 1: side of the bus. I pressed that and then I

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Speaker 1: just closed the window and through the window I was

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Speaker 1: picturing them get like leaving through the window, like climbing

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Speaker 1: out right. Yeah, bring the airbrakes down, then alright, sled

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Speaker 1: out this fuck going through the emergency exit at the

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Speaker 1: back of the school bus. These are these were what

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Speaker 1: I was thinking of. But school bus windows, I feel

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Speaker 1: like are are kind of small, like I did. They're high,

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Speaker 1: they're high up there and small. They would have to

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Speaker 1: like reach all the way to that big swingy thing.

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Speaker 1: I haven't been on a school bus in many years,

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Speaker 1: but that's how my school bus worked. I mean, there's

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Speaker 1: I went. I went to YouTube, I said, bus driver

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Speaker 1: closing bus door, And there's a video called who closes

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Speaker 1: the school bus door when the driver gets off? And

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Speaker 1: then I just so we're not gonna watch it. Um,

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Speaker 1: this is one of those things I like having story

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Speaker 1: in the world. So you don't you don't want to know. No,

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Speaker 1: I mean I could, I could make this terrible for us,

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Speaker 1: but this guy on TikTok's just showing us. All right,

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Speaker 1: I'm gonna let Mr Neil demon streat this one because

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Speaker 1: he drives a bus with air. Break the bus driver,

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Speaker 1: it's closed. We're at a bus depot. They want to know.

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Speaker 1: How do you close the door with air when you

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Speaker 1: get off the bus. You flipped the switch here. It

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Speaker 1: takes the pressure off. Man. That sucks, all right? Parkour

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Speaker 1: long sticks or some ship. Oh yeah, you just released

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Speaker 1: the pressure and then there's no more pneumatic pressure in

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Speaker 1: the door, and then you can just close it like

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Speaker 1: that man. That guy looked like an idiot. I don't

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Speaker 1: think he didn't know what he was talking about. Of course,

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Speaker 1: I'm thinking it's something so complicated and it's like, oh,

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Speaker 1: the simple answer, it's just a switch. Yeah, damn it.

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Speaker 1: I'm like so mad, I am about to become a

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Speaker 1: Republican like that guy's a groom or on that answer.

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Speaker 1: I'm like, why am I so angry about this answer?

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Speaker 1: I think, Bridget, because you truly just my imagination went

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Speaker 1: off in a million directions as they can said it,

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Speaker 1: and I think I get it. I've got to i'ment

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Speaker 1: to the same process. This is why I googled it. Yeah,

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Speaker 1: what is something right overrated? Besides that guy's answer, which

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Speaker 1: was bullshit and a lie? Well, besides that guy's answer

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Speaker 1: that was bullshit and a lie to say Tesla's. I

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Speaker 1: know we're gonna talk about Elon Musk, but I felt

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Speaker 1: this way even before I knew what a crummy person

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Speaker 1: he is. So I think Tesla's are overrated, Like they

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Speaker 1: look weird every time I hear about them. I'm like, oh,

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Speaker 1: and I sound really fussy. I think they're overrated. And

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Speaker 1: also they're made by Elon Musk. So all right, so

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Speaker 1: this is a podcast where we use harsh language sometimes,

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Speaker 1: but you can't use the word crummy. I mean that's

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Speaker 1: too much, too much to use about. Actually, maybe let's

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Speaker 1: take a break really quick out Uh yeah, what a

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Speaker 1: fucking lithium they need to mind to put in those batteries.

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Speaker 1: I mean, there's so much there. There are so many

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Speaker 1: things like granted, yeah, the emissions are very different, but

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Speaker 1: like the process to get there is a very uh

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Speaker 1: chaotic resource extraction process. Yes. And I once read this

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Speaker 1: absolutely wild thing on Twitter where someone was reporting that

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Speaker 1: whatever the new version of Tesla is Um had this

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Speaker 1: glitch where I don't know, I'm not even sure if

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Speaker 1: it was a glitch, but it would, uh instead of

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Speaker 1: stopping at stop signs, it would like roll through them

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Speaker 1: at five miles an hour. And I was like, well,

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Speaker 1: that's obviously problematic because you could get pulled over, and

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Speaker 1: all of these Elon Musk stands were like, it's actually

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Speaker 1: safer sometimes to do a rolling stop, and I was like,

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Speaker 1: am i am I taking crazy pills? Like if a

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Speaker 1: cop sees you roll through a stop sign, they can

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Speaker 1: pull you over. It doesn't matter if Elon Musk thinks

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Speaker 1: it's safe or not. Like we were, the argument became

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Speaker 1: so strange or I was like, well, stopping is going

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Speaker 1: zero miles per hour. If something is going more than that,

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Speaker 1: you have not stopped. Am I right? Right? Most like

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Speaker 1: when I'm coming to a stop sign and the car

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Speaker 1: that I'm exchanging a stop with, like we're deciding who's

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Speaker 1: going to go first, Like the thing that tells you okay,

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Speaker 1: that is a full stop, they just hit the stop

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Speaker 1: is when it like stops and like you see it,

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Speaker 1: like you know, you can't rolling stop there like that.

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Speaker 1: That's very dangerous, Like you have to that. I feel

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Speaker 1: like you have to navigate that like your yourself. I

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Speaker 1: don't know, man, I stop, you know, why take a

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Speaker 1: full stop? Because that's a favorite bullshit reason to get

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Speaker 1: pulled over over. I've been pulled over so many times

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Speaker 1: for like the most like minute, like you know, just

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Speaker 1: like a fraction of a full stop when everybody's blowing.

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Speaker 1: I mean, people don't stop fully if that stop signs.

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Speaker 1: Let's be real, like especially in l A, like people

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Speaker 1: just it's like slowing down until you figure out who

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Speaker 1: you don't have to hit and keep going. That's why

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Speaker 1: I really am like, no, let's make sure they can

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Speaker 1: see that ship like pop, Like I stopped right and

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Speaker 1: then Yeah. My brother is a lawyer, and he once

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Speaker 1: told me that if you're ever driving in a situation

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Speaker 1: where you might not want to have an interaction with

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Speaker 1: the police, we will say, uh, you stop at a

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Speaker 1: stab sign. Make sure that you can feel the car

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Speaker 1: go backward a little bit, right, And that's exactly yeah,

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Speaker 1: that's yeah, right or whatever. You're like no, because you

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Speaker 1: know if you just slow and you're like, it's good enough,

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Speaker 1: and we're going no, no, no, no, And didn't you

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Speaker 1: mostly try and take somebody down who was like revealing

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Speaker 1: the environmental impact of Tesla one of his own employees. Yeah,

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Speaker 1: one of his employees. You like, wage such a champion

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Speaker 1: of free speech each Yeah, number one advocate, And I'm

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Speaker 1: glad he's going to Actually, you actually can't expect our

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Speaker 1: free speech if you're in the capacity of an employee

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Speaker 1: and you signed a contract and then you're doing dispiriting things.

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Speaker 1: Comp Okay, I'm sorry. So you can apply this energy

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Speaker 1: right when you get booted off of a fucking non

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Speaker 1: public utility, the website like Twitter. You get you get

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Speaker 1: that part right? So what well? Anyway? Uh? What is?

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Speaker 1: What's something you think is underrated? Bridget Oh? Something I

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Speaker 1: personally experienced as underrated this week was going to a

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Speaker 1: movie matinee show on a weekday by yourself. If you've ever,

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Speaker 1: if you're just like I'm done with this day, I

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Speaker 1: need a fucking break, go to a movie. I went

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Speaker 1: to a movie by myself randomly at three pm on Tuesday.

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Speaker 1: Highly recommend. Nobody else was in there. I had the

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Speaker 1: whole twee to myself. Highly recommend what you see right?

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Speaker 1: Oh that was. It was a tough decision. I saw

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Speaker 1: everything everywhere, all that want it was. Have y'all seen it? Yeeah? Yes,

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Speaker 1: it was something else. I definitely recommend it. If you

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Speaker 1: haven't seen it, definitely see it. Yeah yeah, oh no, yeah.

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Speaker 1: I Man, it's funny that you were mentioning that too,

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Speaker 1: because before I was waiting for my wife, her majesty

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Speaker 1: to get back in town to watch it together, and

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Speaker 1: part of me was like, man, I just need to

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Speaker 1: do to do me and just go like Saturday morning,

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Speaker 1: like at eleven am, like the early style matinee, but

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Speaker 1: I went to a theater. But oh man, that would

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Speaker 1: have been wild to see that by myself. Yeah, it was.

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Speaker 1: I highly recommend. Yeah, the audience, like is for it

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Speaker 1: was a big part of the experience because people really

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Speaker 1: fucking love that movie, and I don't know, I appreciate that.

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Speaker 1: I haven't been to a movie that resonated that much

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Speaker 1: with an audience. So I'm going to see it again

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Speaker 1: on Friday night to see if the experience is different

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Speaker 1: in a full year. Yeah. Uh damn, it's like time

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Speaker 1: twice in one week. There are also moments too, were

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Speaker 1: like watching it when you'll I was laughing at certain

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Speaker 1: things where I was the only person in the theater

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Speaker 1: who thought something was funny, and I'd be like and

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Speaker 1: like everyone's quiet, and I'm like what sorry. Then I

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Speaker 1: just then I looked over and then I was like,

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Speaker 1: I was not the only person that it was funny.

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Speaker 1: But I think that's the beauty of the film, like

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Speaker 1: it resonates in so many different ways for different people

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Speaker 1: at different times. Yeah. So I think that's t d

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Speaker 1: zs uh front runner for the best movie of the

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Speaker 1: year already, Like we we fun with that when you

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Speaker 1: were gone Jack Kis when he was guest hosting, he

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Speaker 1: told me it was the best film he'd seen in

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Speaker 1: fifteen years. Yeah. I saw him write that on Twitter.

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Speaker 1: I was like, okay, yeah, and he the way his

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Speaker 1: face changed when I asked him, I was like, oh,

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Speaker 1: did you He goes, yes, it was the best film

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Speaker 1: I've seen in fifteen years. I was like, oh this, okay,

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Speaker 1: we got something here. M hm um. I don't know what.

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Speaker 1: I didn't bother to ask what came out fifteen years ago,

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Speaker 1: but I just like that window of time. All right,

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Speaker 1: let's take a quick break and we'll be right back.

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Speaker 1: And we're back. Um and yeah, I feel like the

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Speaker 1: stuff that we we're dealing with. When Trump was in

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Speaker 1: office and during the rise of Trump, where everything was Trump,

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Speaker 1: he just took up all the oxygen. Like I'm starting

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Speaker 1: to see that ship. I'm starting to feel that ship

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Speaker 1: with Elon Musk, Like uh, like just the trying to

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Speaker 1: keep up with like his purchase of Twitter is Like

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Speaker 1: yesterday when I went to bed, everyone was like, no,

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Speaker 1: he's not actually gonna be able to do it because

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Speaker 1: of Tesla, And then like the day before that, it

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Speaker 1: was like he's definitely gonna do it, and now like

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Speaker 1: I wake up to people in my fucking timeline being like,

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Speaker 1: you gotta admit this joke by Elon Musk about buying

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Speaker 1: Twitter is pretty funny and it just fucking sucks. It's

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Speaker 1: it's awful. I mean, god no, just like it's like

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Speaker 1: I r L physical space ship posting, like I might

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Speaker 1: buy Twitter, and then like all of the cause all

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Speaker 1: of this fucking commotion and people like shi joke, dude,

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Speaker 1: sick joke. It looks already looked pretty pretty terrible, like

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Speaker 1: even in the last couple of days with him like

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Speaker 1: basically putting the focus on some female executives at the

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Speaker 1: company to try and out them or make it the

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Speaker 1: situation untenable, and a lot of people like, is he

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Speaker 1: trying to wiggle out of this buyout clause because he'd

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Speaker 1: have to pay people um and if they quit before

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Speaker 1: they're under different circumstances that might change the financial aspects

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Speaker 1: of it. But either way, like it, it's nothing about

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Speaker 1: it looks uh honorable. Yeah, And Miles, I'm so glad

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Speaker 1: that you brought that up. The employee, one of the

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Speaker 1: employees that he's been I has on a harassment campaign

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Speaker 1: against this week is a prominent woman of color at

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Speaker 1: at Twitter, and her role is really working to make

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Speaker 1: Twitter less hospitable to things like online harassment, disinformation, conspiracy theories,

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Speaker 1: and extremists and you know, hate speech. And so I

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Speaker 1: think that in attacking her specifically, he's doing two really

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Speaker 1: clear and important things. One, he's attacking a woman of

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Speaker 1: color because he knows that women of color online are

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Speaker 1: disproportionately targets for things like harassment, and so I think

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Speaker 1: that he is signaling to his followers like, harass this person.

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Speaker 1: And too, I think he's trying to make clear this

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Speaker 1: is what you can expect from how I will run Twitter.

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Speaker 1: I will, you know, I will. He's already showing us

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Speaker 1: who he is. He is someone who is okay harassing

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Speaker 1: women of color for just trying to do their jobs.

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Speaker 1: And so, um, I think those are two really important

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Speaker 1: things that we need to be super clear on. I also,

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Speaker 1: I kind of agree with you. I think that it

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Speaker 1: seems before that the ink is even dry on this deal.

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Speaker 1: He is behaving in these ways that all that that

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Speaker 1: would make a person observing question like are you trying

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Speaker 1: to tank this deal? What is going on? Yeah? I

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Speaker 1: mean so like there's this Reuters kind of opinion piece

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Speaker 1: that's basically saying like he's not gonna do it. He

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Speaker 1: always does ship like this where he you know, claims

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Speaker 1: he's going to I think he said that he was

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Speaker 1: going to uh set up a peanut ruttle brittle company

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Speaker 1: to take on Warren Buffett's iconic uh Sees candies. That

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Speaker 1: he changed his mind. Um, and like this kind of

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Speaker 1: a pinion piece on Routers is like, so this is

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Speaker 1: just more of the same ship. He also said he

424
00:24:49,240 --> 00:24:54,280
Speaker 1: was like cure world hunger. Um, I'm pretty sure he

425
00:24:54,280 --> 00:24:59,040
Speaker 1: hasn't done that. Uh. And but I I really think

426
00:25:00,280 --> 00:25:03,840
Speaker 1: like we need to recognize that there's a commonality between

427
00:25:03,920 --> 00:25:06,119
Speaker 1: him and Trump, not just in the way that they're dominating,

428
00:25:06,160 --> 00:25:09,879
Speaker 1: but also in the way that like this is the

429
00:25:10,000 --> 00:25:13,760
Speaker 1: number one currency for them is attention. And like the

430
00:25:14,680 --> 00:25:17,800
Speaker 1: this has given him more attention than he's ever had,

431
00:25:18,200 --> 00:25:20,840
Speaker 1: I guess, which is shocking because he's already had like

432
00:25:20,880 --> 00:25:25,080
Speaker 1: way too much. Um. And like he's not he's not

433
00:25:25,080 --> 00:25:28,879
Speaker 1: gonna let this go just because like you know, people

434
00:25:28,920 --> 00:25:31,399
Speaker 1: tell him it's a bad financial move. Like this is

435
00:25:32,600 --> 00:25:36,080
Speaker 1: has just made him like even more central to the

436
00:25:36,119 --> 00:25:38,639
Speaker 1: conversations people are having and he does not give a

437
00:25:38,680 --> 00:25:44,080
Speaker 1: funk if like those conversations are critical. It feels like, um,

438
00:25:44,160 --> 00:25:46,760
Speaker 1: but yeah, well yeah, And then I think he's in

439
00:25:46,800 --> 00:25:49,760
Speaker 1: some way he's found a way to or not someone

440
00:25:49,800 --> 00:25:53,679
Speaker 1: He's found a way to like stifle the conversation, just

441
00:25:53,720 --> 00:25:56,160
Speaker 1: like he can have his hand, you know, his finger

442
00:25:56,280 --> 00:25:59,680
Speaker 1: on the on the button. And I'm sure that there's

443
00:25:59,680 --> 00:26:01,760
Speaker 1: another element of that must feel good to him for

444
00:26:01,800 --> 00:26:04,919
Speaker 1: someone who like probably he's not she's not stupid. He

445
00:26:04,960 --> 00:26:07,680
Speaker 1: knows there are people who talk about him, but I'm

446
00:26:07,680 --> 00:26:09,520
Speaker 1: sure that there's something about that in the back of

447
00:26:09,560 --> 00:26:11,080
Speaker 1: his mind too. It's like, oh, wouldn't that be good?

448
00:26:11,080 --> 00:26:13,200
Speaker 1: Because then I can show them what's up too if

449
00:26:13,240 --> 00:26:15,240
Speaker 1: I run Twitter. There's just a lot of you can

450
00:26:15,280 --> 00:26:18,480
Speaker 1: tell that there isn't There's really nothing admirable about him

451
00:26:18,480 --> 00:26:20,040
Speaker 1: wanting to buy And we were talking about this in

452
00:26:20,119 --> 00:26:22,440
Speaker 1: yesterday's episode. It's like it's not even clear what he's

453
00:26:22,440 --> 00:26:24,320
Speaker 1: trying to do, even if we're a business, like how

454
00:26:24,320 --> 00:26:25,639
Speaker 1: he's even trying to run it, and even if it

455
00:26:25,680 --> 00:26:28,760
Speaker 1: were a business, So it has a lot of the

456
00:26:28,800 --> 00:26:33,479
Speaker 1: trappings of like impulsive, uh, you know, self centered person

457
00:26:33,800 --> 00:26:36,200
Speaker 1: thinking that this is a good idea without fully thinking

458
00:26:36,200 --> 00:26:39,160
Speaker 1: it through. But also it does appeal to him because

459
00:26:39,200 --> 00:26:42,720
Speaker 1: he he I think he really feels super powerful to

460
00:26:42,880 --> 00:26:45,400
Speaker 1: even have this thing happening around where people like, oh

461
00:26:45,440 --> 00:26:47,840
Speaker 1: my god, Ellen Musk is gonna buy Twitter, and that

462
00:26:48,119 --> 00:26:51,240
Speaker 1: for sure is also very energizing for him. I'm like,

463
00:26:51,359 --> 00:26:55,920
Speaker 1: I do think that an underrated like detail is that

464
00:26:56,440 --> 00:26:59,720
Speaker 1: he seems to be like openly a racist and white supremacist,

465
00:26:59,800 --> 00:27:03,600
Speaker 1: like not like his company had to pay a hundred

466
00:27:03,600 --> 00:27:06,360
Speaker 1: and thirty six million dollars to a black man who

467
00:27:06,400 --> 00:27:11,680
Speaker 1: was racially harassed at his uh like while working at

468
00:27:11,720 --> 00:27:15,879
Speaker 1: Tesla um. But also this detail Bridget that you pointed

469
00:27:15,880 --> 00:27:18,199
Speaker 1: out and your most recent episode of there are No

470
00:27:18,280 --> 00:27:21,760
Speaker 1: Girls on the Internet that black workers report being like

471
00:27:21,880 --> 00:27:26,440
Speaker 1: multiple workers for Tesla report being moved to the back

472
00:27:26,480 --> 00:27:29,120
Speaker 1: of the floor when he would visit, like to keep

473
00:27:29,160 --> 00:27:33,440
Speaker 1: them out of his sight like that, like we know

474
00:27:34,000 --> 00:27:36,399
Speaker 1: what the funk is going on here, like this is

475
00:27:36,920 --> 00:27:40,520
Speaker 1: not He's not quiet about it. Clearly people if that's

476
00:27:40,560 --> 00:27:43,960
Speaker 1: like a policy that happens. Yeah, And there was something

477
00:27:44,040 --> 00:27:47,359
Speaker 1: so heartbreaking about that that detail, because I think that

478
00:27:47,440 --> 00:27:49,880
Speaker 1: you're right, like I have no you know, I've never

479
00:27:49,880 --> 00:27:53,840
Speaker 1: met the Mark Zuckerberg's or the bezos Is of the world,

480
00:27:53,880 --> 00:27:57,520
Speaker 1: but there's something so and I'm sure they're awful. I

481
00:27:57,960 --> 00:28:00,480
Speaker 1: have a lot of complaints about the way they run

482
00:28:00,480 --> 00:28:04,960
Speaker 1: their platforms. However, there is something so visceral about that

483
00:28:05,040 --> 00:28:07,960
Speaker 1: detail and so personal where it's like, oh, when he

484
00:28:08,080 --> 00:28:11,399
Speaker 1: visits the visits the factory, y'all have to go. You

485
00:28:11,400 --> 00:28:14,520
Speaker 1: need to physically hide because he can't even stand and

486
00:28:14,720 --> 00:28:17,679
Speaker 1: to look at your black faces. There's something so And

487
00:28:17,720 --> 00:28:20,760
Speaker 1: then hearing this not just from one worker, but multiple workers.

488
00:28:20,800 --> 00:28:24,159
Speaker 1: And I also wanted to um mentioned the lawsuit that

489
00:28:24,200 --> 00:28:27,320
Speaker 1: you mentioned. In that lawsuit where that former black staff

490
00:28:27,359 --> 00:28:30,919
Speaker 1: or of Tesla was awarded millions of dollars. Tesla tried

491
00:28:30,960 --> 00:28:33,399
Speaker 1: to have the courts lower the amount of money they

492
00:28:33,440 --> 00:28:35,840
Speaker 1: had to pay him too, I think like seven hundred

493
00:28:35,920 --> 00:28:38,840
Speaker 1: thousand dollars, and the courts basically were like, no, you

494
00:28:38,880 --> 00:28:41,560
Speaker 1: need to pay him millions of dollars for what you've done.

495
00:28:41,600 --> 00:28:44,760
Speaker 1: This person talks about how he suffered post traumatic stress

496
00:28:44,800 --> 00:28:48,360
Speaker 1: disorder from the disgusting racist treatment that he suffered while

497
00:28:48,360 --> 00:28:51,920
Speaker 1: working at Tesla. So yeah, I just think that you

498
00:28:51,960 --> 00:28:55,840
Speaker 1: know when someone shows you who they are, it's important

499
00:28:55,880 --> 00:28:58,040
Speaker 1: to believe them. And I feel like Elon Musk goes

500
00:28:58,040 --> 00:29:00,200
Speaker 1: out of his way to make it very clear who

501
00:29:00,200 --> 00:29:04,000
Speaker 1: he is, and so people who ignore this are really

502
00:29:04,040 --> 00:29:05,920
Speaker 1: making a choice to ignore what I feel as so

503
00:29:06,040 --> 00:29:07,480
Speaker 1: plain in front of all of us, you know what

504
00:29:07,560 --> 00:29:12,000
Speaker 1: I mean? Right, yeah, and like to that. I don't

505
00:29:12,040 --> 00:29:13,720
Speaker 1: know if you were out Jack when we were talking

506
00:29:13,760 --> 00:29:17,120
Speaker 1: about that lawsuit, but you know, just the way that

507
00:29:18,280 --> 00:29:21,080
Speaker 1: there are many lawsuits. There are more than one. They're

508
00:29:21,120 --> 00:29:24,600
Speaker 1: more than a few black employees of Tesla, and like

509
00:29:24,760 --> 00:29:27,440
Speaker 1: it's awful, like even like to the thing of like

510
00:29:27,520 --> 00:29:30,720
Speaker 1: working out of sight, like they were referring to parts

511
00:29:30,720 --> 00:29:33,320
Speaker 1: of the plant as like the slave ship or the

512
00:29:33,480 --> 00:29:37,680
Speaker 1: dark side too for like that that's the culture that

513
00:29:38,080 --> 00:29:40,760
Speaker 1: they're like, that's just how they're allowed to cook over there.

514
00:29:41,080 --> 00:29:44,160
Speaker 1: And they even remember once that was that lawsuit you know,

515
00:29:44,320 --> 00:29:46,840
Speaker 1: was was being decided, they put out a blog post

516
00:29:46,880 --> 00:29:49,000
Speaker 1: over there like we've had over like we've you know,

517
00:29:49,080 --> 00:29:52,680
Speaker 1: the Department of Fair of of a Fair Employment has

518
00:29:52,800 --> 00:29:57,720
Speaker 1: investigated like fifth US fifty times and it's never found anything, Wow,

519
00:29:57,760 --> 00:30:00,360
Speaker 1: fifty times, huh only on the only to come by

520
00:30:00,400 --> 00:30:06,960
Speaker 1: her fifty times. And also in America where yeah, I'm

521
00:30:07,000 --> 00:30:09,360
Speaker 1: just guessing they're not gonna go out of their way

522
00:30:09,400 --> 00:30:14,080
Speaker 1: to slap the hand of the billionaire. Oh and and

523
00:30:14,080 --> 00:30:16,800
Speaker 1: and and like the agency who was also like that's

524
00:30:16,800 --> 00:30:23,240
Speaker 1: not precisely true, but okay, like that's why we're here

525
00:30:23,320 --> 00:30:27,160
Speaker 1: because they we found things right. Yeah. And then also,

526
00:30:27,320 --> 00:30:30,800
Speaker 1: you know, not only have people taken them to court

527
00:30:30,880 --> 00:30:35,240
Speaker 1: for racist treatment, also sexist harassment at their workplace. And

528
00:30:35,520 --> 00:30:37,000
Speaker 1: you know, when you look at the way that Elon

529
00:30:37,080 --> 00:30:42,040
Speaker 1: Musk tweets, which is often very kind of juvenile sexism,

530
00:30:42,080 --> 00:30:44,440
Speaker 1: you know, the kind of stuff that maybe you might

531
00:30:44,480 --> 00:30:46,240
Speaker 1: have thought was funny when you were in ninth grade

532
00:30:46,280 --> 00:30:49,840
Speaker 1: trying to be edgy. Um. I have no trouble believing

533
00:30:49,840 --> 00:30:53,320
Speaker 1: that this is a top down culture problem, that it's

534
00:30:53,400 --> 00:30:57,440
Speaker 1: you know, not only is it a pervasive racist, sexist culture,

535
00:30:57,800 --> 00:31:01,160
Speaker 1: but that that vibe almost from the top. And that

536
00:31:01,200 --> 00:31:03,360
Speaker 1: means Elon Musk. I think that seems very clear to me.

537
00:31:03,600 --> 00:31:07,400
Speaker 1: Oh yeah, oh yeah, it's it's I mean that that's

538
00:31:07,400 --> 00:31:10,960
Speaker 1: always the that's what's bringing all the creeps to the yard.

539
00:31:11,600 --> 00:31:14,600
Speaker 1: You know what I mean is Elon and they see

540
00:31:14,640 --> 00:31:16,040
Speaker 1: what he does, are like, oh, I want to move

541
00:31:16,120 --> 00:31:18,200
Speaker 1: like that and I can and you can already tell

542
00:31:18,240 --> 00:31:21,240
Speaker 1: based on what he thinks is appropriate or inappropriate, like perfect,

543
00:31:21,880 --> 00:31:24,640
Speaker 1: this person is going to tell me I'm being sexist

544
00:31:24,880 --> 00:31:29,720
Speaker 1: or racist. They know I'm joking, so this is perfect. Yeah,

545
00:31:29,760 --> 00:31:32,800
Speaker 1: And I can totally see how. You know, there's probably

546
00:31:32,840 --> 00:31:36,760
Speaker 1: a real interesting mixture of people who are really um

547
00:31:37,160 --> 00:31:40,480
Speaker 1: intrigued by the prospect of working on like really cool

548
00:31:40,600 --> 00:31:44,000
Speaker 1: technology and and like you know, furthering their own careers

549
00:31:44,000 --> 00:31:46,080
Speaker 1: and science and things like that. And then you mix

550
00:31:46,160 --> 00:31:47,720
Speaker 1: that with other people who are like completely like I

551
00:31:47,760 --> 00:31:49,920
Speaker 1: don't know, I like the fucking vibes here and they're

552
00:31:49,960 --> 00:31:54,120
Speaker 1: kind of weird. Yeah. I think there's like some like

553
00:31:54,160 --> 00:31:57,440
Speaker 1: the the tweet that that's somebody in my time. I

554
00:31:57,480 --> 00:32:00,160
Speaker 1: was like, god, admit it was funny. Was just him

555
00:32:00,160 --> 00:32:02,880
Speaker 1: being like, now next time, I'm gonna buy Coca Cola

556
00:32:02,920 --> 00:32:06,000
Speaker 1: and put the cocaine back. And I do not have

557
00:32:06,040 --> 00:32:09,920
Speaker 1: to admit that's funny. That's just a pop culture reference. Um,

558
00:32:10,280 --> 00:32:13,120
Speaker 1: But I do think it gets at like this appeal

559
00:32:13,240 --> 00:32:17,080
Speaker 1: that he has two people that it's it's like that

560
00:32:17,240 --> 00:32:20,160
Speaker 1: I'm Sandler movie Big Daddy, where like an idiot one

561
00:32:21,200 --> 00:32:26,440
Speaker 1: a bunch of money and like does Mr Deeds, Mr Deeds,

562
00:32:27,360 --> 00:32:31,560
Speaker 1: and and well I've never seen Mr Deeds big Daddy.

563
00:32:31,640 --> 00:32:34,080
Speaker 1: He adopts that, he adopts a kid, and he becomes

564
00:32:34,440 --> 00:32:39,120
Speaker 1: Dylan Sprouse. Dylan Sprouse. He also won a bunch of

565
00:32:39,120 --> 00:32:42,720
Speaker 1: money from a like getting hit by a cab I

566
00:32:42,760 --> 00:32:50,560
Speaker 1: think work. Yeah, okay, so but he stills but he's

567
00:32:51,120 --> 00:32:55,200
Speaker 1: like that. I think that's like part of the thing

568
00:32:55,320 --> 00:32:57,600
Speaker 1: is like this guy is an idiot, but he has

569
00:32:57,640 --> 00:33:00,960
Speaker 1: like all this money. Uh, he's winning. We can't say

570
00:33:00,960 --> 00:33:05,160
Speaker 1: shipped to him now. Um, And it's just I don't know,

571
00:33:05,400 --> 00:33:09,840
Speaker 1: it's truly a bummer. Um, it's shitty. Billy Madison. Yeah,

572
00:33:11,160 --> 00:33:17,520
Speaker 1: Billy Madison bought Twitter. Um. And there's like the stuff

573
00:33:17,520 --> 00:33:22,680
Speaker 1: that we're hoping will happen is not. Well the governmental

574
00:33:22,720 --> 00:33:26,160
Speaker 1: step in him, like make this a utility where you know,

575
00:33:26,520 --> 00:33:31,080
Speaker 1: recognize that this person is like a danger to um freedom,

576
00:33:31,920 --> 00:33:36,360
Speaker 1: and instead it's like we hope he decides not to

577
00:33:36,400 --> 00:33:39,840
Speaker 1: do it because it's a bad investment, Like that's where

578
00:33:39,880 --> 00:33:44,080
Speaker 1: we are, and it just feel it very I don't know.

579
00:33:44,400 --> 00:33:47,520
Speaker 1: It reminded me of this other like Russia story from

580
00:33:47,680 --> 00:33:53,440
Speaker 1: last week where Russia's Federal Security Service arrested a group

581
00:33:53,440 --> 00:33:56,840
Speaker 1: of six Russian neo Nazis who are plotting to assassinate

582
00:33:56,840 --> 00:34:01,440
Speaker 1: a Russian state TV talk show host. Um, but like

583
00:34:01,520 --> 00:34:04,800
Speaker 1: the neo Nazis in question, we're just like journalist critical

584
00:34:05,120 --> 00:34:10,040
Speaker 1: of the state TV. Uh. The person they were supposedly

585
00:34:10,040 --> 00:34:14,279
Speaker 1: trying to assassinate had once praised Hitler as a very

586
00:34:14,320 --> 00:34:21,239
Speaker 1: brave man uh and even produced an admiring documentary about Mussolini. Um.

587
00:34:21,280 --> 00:34:25,120
Speaker 1: So like it's it's a Nazi who they were supposedly

588
00:34:25,160 --> 00:34:28,399
Speaker 1: trying to assassinate, and like clearly the thing that they're

589
00:34:28,400 --> 00:34:33,640
Speaker 1: piste off about is that they're critical of state run TV.

590
00:34:33,800 --> 00:34:35,719
Speaker 1: But it reminded me of that just because it's like

591
00:34:36,440 --> 00:34:38,560
Speaker 1: this ship is now just being done out in the open.

592
00:34:38,760 --> 00:34:42,160
Speaker 1: It's just like the racist guy is going to take

593
00:34:42,200 --> 00:34:48,040
Speaker 1: over Twitter and like start and like let the Nazis

594
00:34:48,040 --> 00:34:51,560
Speaker 1: back on, and like there's not it's not a thing

595
00:34:51,600 --> 00:34:54,920
Speaker 1: where like there's an appeal to authority. It's just a

596
00:34:55,200 --> 00:34:59,239
Speaker 1: we're like hoping that it doesn't happen by some like

597
00:34:59,280 --> 00:35:02,040
Speaker 1: stroke able luck at this point, Yeah, where you're counting

598
00:35:02,080 --> 00:35:06,839
Speaker 1: on we hope a billionaire knows better. Oh I don't.

599
00:35:07,080 --> 00:35:09,560
Speaker 1: We'll see about that. I think The only thing that

600
00:35:09,640 --> 00:35:12,280
Speaker 1: could potentially act as a safeguard is that the EU

601
00:35:12,440 --> 00:35:15,160
Speaker 1: has been pretty forcefully said like if there's not real

602
00:35:15,520 --> 00:35:19,160
Speaker 1: moderation here, like we won't we're not gonna sunk within

603
00:35:19,239 --> 00:35:23,400
Speaker 1: the EU, like we'll ban it, right, So that's one potential.

604
00:35:23,440 --> 00:35:25,719
Speaker 1: I mean, there are these like little things where it's like, yeah,

605
00:35:25,719 --> 00:35:29,040
Speaker 1: you can't just go foot off the fucking break and

606
00:35:29,040 --> 00:35:31,719
Speaker 1: see what happens. I mean you can, but it's sure

607
00:35:31,760 --> 00:35:35,040
Speaker 1: it's certainly not going to help like Twitter as a company.

608
00:35:35,040 --> 00:35:36,880
Speaker 1: So that's why I think there's so many dimensions to

609
00:35:36,960 --> 00:35:38,560
Speaker 1: It's like do you really not give a funk? You

610
00:35:38,600 --> 00:35:42,000
Speaker 1: ready to billion dollars like to just like to fully

611
00:35:42,080 --> 00:35:45,480
Speaker 1: go into your absolutists like version of free speech and

612
00:35:45,520 --> 00:35:48,360
Speaker 1: see where that experiment goes. Are is this is it

613
00:35:48,400 --> 00:35:50,279
Speaker 1: going to be more long term? You're gonna try and

614
00:35:50,280 --> 00:35:53,440
Speaker 1: pick people off slowly and turn up the heat on

615
00:35:53,480 --> 00:35:56,560
Speaker 1: Twitter and sanitize it of all like the leftists or

616
00:35:56,600 --> 00:35:59,359
Speaker 1: people who are like advocating for equality, and like that's

617
00:35:59,400 --> 00:36:02,759
Speaker 1: the plan. I think that's it. I mean, I something

618
00:36:02,800 --> 00:36:04,600
Speaker 1: that I've really thought a lot about this week is

619
00:36:04,680 --> 00:36:08,440
Speaker 1: why Twitter? Why Twitter? Even before Elon Musk, Why was

620
00:36:08,480 --> 00:36:11,960
Speaker 1: Twitter this hotbed of sort of quote unquote culture wars

621
00:36:12,000 --> 00:36:14,319
Speaker 1: and all of that. And I think it's not a

622
00:36:14,360 --> 00:36:17,560
Speaker 1: coincidence that all of this has really imploded around Twitter.

623
00:36:18,000 --> 00:36:22,239
Speaker 1: I think that extremists, people on people on the far right,

624
00:36:22,480 --> 00:36:25,920
Speaker 1: they have watched people who traditionally are marginalized and don't

625
00:36:25,960 --> 00:36:29,160
Speaker 1: have a lot of institutional power or support use platforms

626
00:36:29,239 --> 00:36:32,720
Speaker 1: like Twitter to build movements and to democratize our ability

627
00:36:32,760 --> 00:36:35,040
Speaker 1: to have a platform in a voice. We've built things

628
00:36:35,080 --> 00:36:40,040
Speaker 1: like me to uh, black Lives Matter using these platforms, right,

629
00:36:40,080 --> 00:36:44,280
Speaker 1: We've been able to really like use them to to build,

630
00:36:44,360 --> 00:36:46,120
Speaker 1: to get some more power and to sort of be

631
00:36:46,200 --> 00:36:48,600
Speaker 1: part of the conversation in ways that we've always been

632
00:36:48,880 --> 00:36:52,040
Speaker 1: traditionally locked out of. And I think that they see

633
00:36:52,080 --> 00:36:54,960
Speaker 1: this medium as something they need to take back. I

634
00:36:55,000 --> 00:36:57,200
Speaker 1: think that they I think that they find that very

635
00:36:57,280 --> 00:36:59,520
Speaker 1: threatening to watch people who traditionally did not have a

636
00:36:59,520 --> 00:37:01,719
Speaker 1: lot of power or or a lot of voice use

637
00:37:01,800 --> 00:37:05,400
Speaker 1: these platforms to take back that power in that voice.

638
00:37:05,560 --> 00:37:07,440
Speaker 1: And I think that this is part and parcel of

639
00:37:07,440 --> 00:37:10,080
Speaker 1: a plan to make that harder, to make it to

640
00:37:10,200 --> 00:37:13,200
Speaker 1: tempt to go back to a time where we didn't

641
00:37:13,239 --> 00:37:15,000
Speaker 1: really have those kinds of voices are those kind of

642
00:37:15,040 --> 00:37:19,600
Speaker 1: platforms even if we built them ourselves. Mm hmm. Yeah.

643
00:37:19,640 --> 00:37:24,480
Speaker 1: I think that's a very good point and probably absolutely true.

644
00:37:24,560 --> 00:37:27,960
Speaker 1: If not, like, if it's not on a fucking flow

645
00:37:28,040 --> 00:37:30,920
Speaker 1: chart an elon Musk's office, it's definitely like somewhere in

646
00:37:30,960 --> 00:37:34,520
Speaker 1: his brain, you know, like that that's something that scares

647
00:37:34,600 --> 00:37:37,120
Speaker 1: him and makes him uncomfortable. Well yeah, and because I

648
00:37:37,160 --> 00:37:39,160
Speaker 1: think the source of a lot of headaches for him,

649
00:37:39,239 --> 00:37:42,200
Speaker 1: can you can draw a line to Twitter or like

650
00:37:42,280 --> 00:37:45,920
Speaker 1: these or or pings are discussed very energetically on Twitter.

651
00:37:46,760 --> 00:37:49,040
Speaker 1: Uh And I think again, like you're saying, bridget that

652
00:37:49,239 --> 00:37:52,200
Speaker 1: is it's freaky if you're like a you know, point

653
00:37:52,280 --> 00:37:54,319
Speaker 1: one percent or and you look out your window and

654
00:37:54,480 --> 00:37:56,800
Speaker 1: Twitter's outside, and you're like, damn, like they're able to

655
00:37:56,840 --> 00:37:59,560
Speaker 1: get together real fucking quick lunch over there. Like that's

656
00:38:00,400 --> 00:38:05,359
Speaker 1: not good for you know, my gash toly aims. But yeah,

657
00:38:05,400 --> 00:38:08,600
Speaker 1: I think that's where we see It's like what version

658
00:38:08,719 --> 00:38:12,919
Speaker 1: is it? Is it? This? Is it completely uh like aggressive?

659
00:38:13,040 --> 00:38:15,400
Speaker 1: And you know from day one the floodgates open? Is

660
00:38:15,440 --> 00:38:17,600
Speaker 1: it this version where it stealthily trying to make it

661
00:38:17,600 --> 00:38:20,239
Speaker 1: look like no, no no, Twitter is not changing, and it

662
00:38:20,320 --> 00:38:24,879
Speaker 1: is and it's much more you know, uh insidious and

663
00:38:25,080 --> 00:38:28,239
Speaker 1: you know, with a smile on its face. But yeah,

664
00:38:28,280 --> 00:38:30,359
Speaker 1: it's the other part of it. There's just so many

665
00:38:30,360 --> 00:38:32,560
Speaker 1: of these other dimensions, like how that you would respond

666
00:38:32,600 --> 00:38:35,040
Speaker 1: like how China, like he has so much, so much

667
00:38:35,080 --> 00:38:38,000
Speaker 1: business in China and they don't like Twitter. What happens

668
00:38:38,040 --> 00:38:40,200
Speaker 1: then when they see how like other people use it.

669
00:38:40,480 --> 00:38:43,120
Speaker 1: There are so many other dimensions to it. I'm just

670
00:38:43,160 --> 00:38:46,120
Speaker 1: so curious to know, like to begin to really see

671
00:38:46,120 --> 00:38:48,160
Speaker 1: it come together. But all of these things are possible,

672
00:38:48,200 --> 00:38:52,720
Speaker 1: and they're all real risks. I've heard the metaphor before

673
00:38:52,760 --> 00:38:55,359
Speaker 1: that like you don't notice the things are getting worse

674
00:38:55,440 --> 00:38:59,239
Speaker 1: because it's like a pot and a frog and a

675
00:38:59,280 --> 00:39:01,520
Speaker 1: pot of water that's like slowly getting hotter, and like

676
00:39:01,600 --> 00:39:05,480
Speaker 1: these are the moments where it like really hits me, like,

677
00:39:05,480 --> 00:39:09,040
Speaker 1: oh yeah, this is this is getting much hotter. It's

678
00:39:09,080 --> 00:39:15,120
Speaker 1: like uncomfortably, unhealthily hot right now. And if that's the case,

679
00:39:15,160 --> 00:39:18,040
Speaker 1: I mean, then it's really incumbent on people who are

680
00:39:18,120 --> 00:39:21,960
Speaker 1: using Twitter for good things or like not ship posting

681
00:39:22,000 --> 00:39:25,000
Speaker 1: and being racist to you know, maybe use the little

682
00:39:25,000 --> 00:39:27,080
Speaker 1: time we have left on Twitter to organize a way

683
00:39:27,080 --> 00:39:31,640
Speaker 1: to figure out like how to keep something like this alive. Um,

684
00:39:31,680 --> 00:39:34,160
Speaker 1: because it is powerful. I mean, like most people really

685
00:39:34,200 --> 00:39:36,600
Speaker 1: do use it for news, you know, not everyone is

686
00:39:36,680 --> 00:39:39,319
Speaker 1: using Twitter to communicate. Like a lot of people really

687
00:39:39,360 --> 00:39:41,080
Speaker 1: like Twitter because they're like I can't man, I can

688
00:39:41,120 --> 00:39:43,239
Speaker 1: just look up a city and just see what's going

689
00:39:43,320 --> 00:39:47,280
Speaker 1: off because people are talking about it. And yeah, it's

690
00:39:48,000 --> 00:39:51,840
Speaker 1: I don't know what early it's early days, but it's there.

691
00:39:52,719 --> 00:39:56,240
Speaker 1: The sky looks dark. I feel better about the EU band.

692
00:39:56,280 --> 00:39:59,000
Speaker 1: But you know they tried that with Mountain Dew and

693
00:39:59,040 --> 00:40:07,160
Speaker 1: it only made Mountain Do stronger. You know, God couldn't

694
00:40:07,160 --> 00:40:11,000
Speaker 1: stop me. If you strike me down, will become even

695
00:40:11,040 --> 00:40:13,960
Speaker 1: more powerful. Um. All right, let's take a quick break

696
00:40:13,960 --> 00:40:15,840
Speaker 1: and then we'll come back and talk about that Russia

697
00:40:15,880 --> 00:40:28,040
Speaker 1: story and we're back. Um. Yeah, So, like I said,

698
00:40:28,080 --> 00:40:30,719
Speaker 1: I was, I was just tying a line between the

699
00:40:30,719 --> 00:40:33,480
Speaker 1: Elam Musk and this Russia frame up because I do

700
00:40:33,600 --> 00:40:39,520
Speaker 1: feel like a lot of this sensibility um of Yeah,

701
00:40:39,560 --> 00:40:42,000
Speaker 1: we don't have to like try to be convincing in

702
00:40:42,000 --> 00:40:43,960
Speaker 1: our lie. We just like say the lie and then

703
00:40:44,000 --> 00:40:47,160
Speaker 1: stick with it and it doesn't matter. Like kind of

704
00:40:47,640 --> 00:40:52,160
Speaker 1: started in in Russia and like, first, you know, trum

705
00:40:52,320 --> 00:40:55,760
Speaker 1: Trump obviously was like the number one proprietor in America

706
00:40:56,040 --> 00:41:00,040
Speaker 1: of it. But um, this one, I mean people have

707
00:41:00,120 --> 00:41:02,360
Speaker 1: been people been doing this one for for a while.

708
00:41:02,400 --> 00:41:06,440
Speaker 1: I'd say, you know, the weapons of mass destruction man,

709
00:41:06,840 --> 00:41:10,799
Speaker 1: We're good, yeah, yellow cake man. But eventually they were like,

710
00:41:10,840 --> 00:41:17,120
Speaker 1: we didn't find any. Yeah. Um fuck Yeah. So Russia's

711
00:41:17,280 --> 00:41:21,480
Speaker 1: Federal Security Service FSB arrested a group of six Russian

712
00:41:21,960 --> 00:41:24,880
Speaker 1: what they're claiming are neo Nazis who are plotting to

713
00:41:24,960 --> 00:41:30,879
Speaker 1: assassinate a Russian state TV talk show host. Um and Yeah,

714
00:41:30,920 --> 00:41:34,000
Speaker 1: things just like seemed really fishy right off the bat,

715
00:41:34,320 --> 00:41:38,280
Speaker 1: starting with the fact that the supposed target of the

716
00:41:38,400 --> 00:41:43,879
Speaker 1: of their plot was this um state Russian state TV,

717
00:41:44,520 --> 00:41:51,080
Speaker 1: like you know host presenter person who has said has

718
00:41:51,080 --> 00:41:53,600
Speaker 1: praised Hitler as a very brave man and even produced

719
00:41:53,640 --> 00:41:59,759
Speaker 1: an admiring documentary about Mussolini. So yeah, because you know

720
00:42:00,080 --> 00:42:03,879
Speaker 1: that's we we always just like stick photos to our

721
00:42:03,920 --> 00:42:11,399
Speaker 1: computer speakers. Um. They also had three copies of the

722
00:42:11,440 --> 00:42:16,040
Speaker 1: Game of the sims um and and people were like,

723
00:42:16,600 --> 00:42:19,400
Speaker 1: what the fund is that doing there? That's so weird.

724
00:42:19,560 --> 00:42:26,320
Speaker 1: It's like three three like discs of the Sims portrait

725
00:42:26,360 --> 00:42:30,680
Speaker 1: of a portrait of Hitler to go to mind comp

726
00:42:31,120 --> 00:42:37,359
Speaker 1: and three copies of the SIMS expansion packs. So men,

727
00:42:37,800 --> 00:42:42,120
Speaker 1: the working theory is that someone, uh, you know, did

728
00:42:42,160 --> 00:42:46,040
Speaker 1: fabricate this evidence. And we're told they were told to

729
00:42:46,080 --> 00:42:50,560
Speaker 1: get three Sims, as in three Sims cards and SIM cards,

730
00:42:50,800 --> 00:43:00,600
Speaker 1: and they fucking missed the subtle and went. When the

731
00:43:00,680 --> 00:43:05,280
Speaker 1: Investigative Committee of the Russian Federation later posted a video

732
00:43:06,320 --> 00:43:09,919
Speaker 1: of the raid, they had blurred out the Sims um

733
00:43:10,440 --> 00:43:14,759
Speaker 1: the yeah, because it's it's like so it really does

734
00:43:15,760 --> 00:43:20,279
Speaker 1: like it's like the commander wasn't there, right, He's texting everybody, look,

735
00:43:20,760 --> 00:43:24,440
Speaker 1: get get a Swaska T shirt, get some like SS patches,

736
00:43:24,840 --> 00:43:28,360
Speaker 1: put up a picture Hitler. The three Sims do all that,

737
00:43:28,440 --> 00:43:31,640
Speaker 1: you know, make it look real shapey, right, and then

738
00:43:31,640 --> 00:43:33,360
Speaker 1: he just goes and like takes a picture. And the

739
00:43:33,400 --> 00:43:35,440
Speaker 1: guy's like, mother, He's like, what the fund is that?

740
00:43:35,520 --> 00:43:37,960
Speaker 1: What are those three games on the bed? And he's

741
00:43:38,000 --> 00:43:43,080
Speaker 1: like three Sims, Like because it really doesn't mean like

742
00:43:43,160 --> 00:43:45,120
Speaker 1: it's put out there as if it's like you have

743
00:43:45,239 --> 00:43:47,799
Speaker 1: to take a picture of this. This is relevant to

744
00:43:47,880 --> 00:43:49,480
Speaker 1: the case, you know what I mean. It's like he took.

745
00:43:49,800 --> 00:43:52,440
Speaker 1: It's like he said, and they had five soup ladles,

746
00:43:52,920 --> 00:43:54,919
Speaker 1: you know what I mean, Like that's not relevant. It's

747
00:43:54,960 --> 00:43:57,040
Speaker 1: in the house, But why put that ship there. It's

748
00:43:57,080 --> 00:44:00,000
Speaker 1: clear that the person's directive was take all the pictures,

749
00:44:00,160 --> 00:44:06,000
Speaker 1: including the three sims to uh just for for who?

750
00:44:06,040 --> 00:44:09,120
Speaker 1: For what? Again? I think this is all, like you're saying,

751
00:44:09,120 --> 00:44:12,160
Speaker 1: the low energy effort to just say, you see, there's

752
00:44:12,200 --> 00:44:15,960
Speaker 1: neo Nazis in Ukraine and they're coming after people in Russia,

753
00:44:16,040 --> 00:44:18,279
Speaker 1: and that's what all of this is about. That's why

754
00:44:18,480 --> 00:44:22,240
Speaker 1: we're there. Because we put out a swastika T shirt

755
00:44:23,440 --> 00:44:26,160
Speaker 1: really loosely taped photo of Hitler to a Bluetooth speaker

756
00:44:26,200 --> 00:44:30,120
Speaker 1: and three copies of the sims um and then the

757
00:44:30,160 --> 00:44:34,719
Speaker 1: target quote of the of the attack, who's just like

758
00:44:34,760 --> 00:44:38,000
Speaker 1: their wolf blitz er like some you know TV person,

759
00:44:38,200 --> 00:44:41,640
Speaker 1: except if people still like watched CNN. But he went

760
00:44:41,680 --> 00:44:44,640
Speaker 1: on TV and claimed the plot was all hatched by

761
00:44:45,239 --> 00:44:50,719
Speaker 1: Zelinsky um because Zelinsky wanted to be a presenter on

762
00:44:50,920 --> 00:44:56,960
Speaker 1: the state run channel but wasn't talented enough. We're doing

763
00:44:57,000 --> 00:45:00,160
Speaker 1: the old Donald Trump thing. Haters. You just ne they

764
00:45:00,200 --> 00:45:02,359
Speaker 1: were begging me for a job, and then I said no,

765
00:45:02,560 --> 00:45:06,960
Speaker 1: so that's where they lie. Now, Okay, that's I mean,

766
00:45:07,719 --> 00:45:14,760
Speaker 1: so that's that's pretty pretty questionable child logic at work there.

767
00:45:14,840 --> 00:45:19,080
Speaker 1: It would seem, um so like he was doing it

768
00:45:19,120 --> 00:45:23,480
Speaker 1: because he hates me, and uh he's like what he

769
00:45:23,480 --> 00:45:25,360
Speaker 1: he actually is on the record saying he wished he

770
00:45:25,400 --> 00:45:29,440
Speaker 1: was as handsome as me. So, um yeah, I have

771
00:45:29,520 --> 00:45:31,560
Speaker 1: some I have some texts where he's like asking me

772
00:45:31,600 --> 00:45:33,480
Speaker 1: for pointers, like on how to look like me. But

773
00:45:33,520 --> 00:45:36,239
Speaker 1: I like, I was like, I was like, seriously, dude,

774
00:45:36,280 --> 00:45:37,680
Speaker 1: we're like in a war, Like I can't do this

775
00:45:37,760 --> 00:45:42,239
Speaker 1: right now. Um, but yeah, tough times, tough times, Um

776
00:45:42,360 --> 00:45:45,399
Speaker 1: all right. I I just wanted to continue complaining about

777
00:45:45,480 --> 00:45:49,680
Speaker 1: MPR um for for because we didn't get all the

778
00:45:49,680 --> 00:45:53,000
Speaker 1: way through the story. Uh. Super producer Tricia did a

779
00:45:53,000 --> 00:45:56,800
Speaker 1: bunch of really good research along with super producer Becca

780
00:45:57,120 --> 00:46:03,000
Speaker 1: on just like, um you know where where this so bridge?

781
00:46:03,600 --> 00:46:06,520
Speaker 1: Like Basically, my point is like I listened to NPR

782
00:46:06,600 --> 00:46:08,680
Speaker 1: for the first time in a year and just found

783
00:46:08,760 --> 00:46:12,400
Speaker 1: the tone, which is I don't think it's changed, but

784
00:46:12,480 --> 00:46:16,799
Speaker 1: it just feels insane to me, Like it feels very

785
00:46:16,880 --> 00:46:20,600
Speaker 1: like gentle but like they're talking about like gentle mixed

786
00:46:20,600 --> 00:46:26,680
Speaker 1: with like board and whatever. And so then like the

787
00:46:26,800 --> 00:46:30,200
Speaker 1: Russians came in and you know, they're reporting on war crimes,

788
00:46:30,239 --> 00:46:31,960
Speaker 1: but they're doing it in like a way that's like

789
00:46:32,600 --> 00:46:36,359
Speaker 1: just feels so strange and basically feels like if we

790
00:46:36,440 --> 00:46:38,439
Speaker 1: if we were all hearing it again for the first time,

791
00:46:38,480 --> 00:46:41,000
Speaker 1: we would all be like, what the funk is happening

792
00:46:41,560 --> 00:46:45,919
Speaker 1: right now? Um. So we talked about that and like

793
00:46:46,360 --> 00:46:50,080
Speaker 1: some psychoanalysis on like neoliberals, like why this might be

794
00:46:50,880 --> 00:46:56,520
Speaker 1: might be happening, might be necessary for them right now? Um.

795
00:46:56,560 --> 00:46:59,439
Speaker 1: You know, super producer Tricia like did a deep dive

796
00:46:59,440 --> 00:47:04,080
Speaker 1: into like to the history of just basically what I've

797
00:47:04,080 --> 00:47:07,120
Speaker 1: heard described as like TV English, UM. But it's like

798
00:47:07,200 --> 00:47:11,200
Speaker 1: sort of the um accent lists is how it's often

799
00:47:11,239 --> 00:47:16,440
Speaker 1: described English that people speak with on UM TV. But

800
00:47:16,600 --> 00:47:22,440
Speaker 1: then you know, say, calling something accentless just uh, you know,

801
00:47:22,520 --> 00:47:26,960
Speaker 1: positioned yourself as thinking that a certain access, a certain

802
00:47:27,000 --> 00:47:31,879
Speaker 1: way of speaking American English doesn't have an accent. Basically, Um,

803
00:47:32,040 --> 00:47:38,600
Speaker 1: the presumed audience is an English monolingual speaker, UM. And

804
00:47:39,080 --> 00:47:42,719
Speaker 1: when the voice and language of the speaker this is

805
00:47:42,760 --> 00:47:45,040
Speaker 1: I'm just gonna read directly from what Triture wrote when

806
00:47:45,040 --> 00:47:47,000
Speaker 1: the voice and language of the speaker is intended to

807
00:47:47,040 --> 00:47:50,240
Speaker 1: not make the listener uncomfortable. The placidity of the MPR

808
00:47:50,360 --> 00:47:52,760
Speaker 1: voice also feeds into this. Like the rest of the media,

809
00:47:52,840 --> 00:47:54,880
Speaker 1: they want listeners to feel a certain amount of fear,

810
00:47:55,320 --> 00:47:58,399
Speaker 1: which will push them to keep listening and not uh

811
00:47:58,440 --> 00:48:00,600
Speaker 1: and not be too uncomfortable or in it. That will

812
00:48:00,600 --> 00:48:04,560
Speaker 1: make them feel like they're also experiencing the crisis. Um,

813
00:48:04,719 --> 00:48:08,680
Speaker 1: so they you know, they choose to speak like a

814
00:48:08,719 --> 00:48:12,640
Speaker 1: group of people who aren't affected by the crises. Uh,

815
00:48:12,800 --> 00:48:16,279
Speaker 1: they are, but they still like want to talk about it.

816
00:48:16,440 --> 00:48:19,120
Speaker 1: And the accent emulates people who like don't suffer the

817
00:48:19,160 --> 00:48:22,880
Speaker 1: human rights crises that and wars and disasters that NPR

818
00:48:23,120 --> 00:48:29,439
Speaker 1: reports on, and like. She found examples of people who

819
00:48:29,760 --> 00:48:33,880
Speaker 1: were prohibited from or just like their story wasn't accepted

820
00:48:33,920 --> 00:48:37,840
Speaker 1: to on NPR because they were told that they speak

821
00:48:38,560 --> 00:48:42,879
Speaker 1: too much with too much of an accent. Um. Hear

822
00:48:42,920 --> 00:48:44,919
Speaker 1: that a lot, a lot of people hear that a lot,

823
00:48:45,400 --> 00:48:48,560
Speaker 1: like some lovel you know, it's like, yeah, what what

824
00:48:48,760 --> 00:48:50,879
Speaker 1: is that voice exactly? I don't know if it's I mean,

825
00:48:50,880 --> 00:48:52,920
Speaker 1: at this point, it feels like this thing where it

826
00:48:53,000 --> 00:48:56,279
Speaker 1: naturally evolved, right where I get that there's just you know,

827
00:48:56,360 --> 00:48:59,759
Speaker 1: like in the radio announcer days, people all spoke like

828
00:49:00,080 --> 00:49:03,680
Speaker 1: this and the funk is that, And then we slowly

829
00:49:04,000 --> 00:49:07,680
Speaker 1: got into something a little less like you know, good evening,

830
00:49:07,840 --> 00:49:09,600
Speaker 1: rather here is the weather for today. I sound like

831
00:49:09,680 --> 00:49:14,040
Speaker 1: David Lynch doing the weather. Um. But you know, even now,

832
00:49:14,120 --> 00:49:16,200
Speaker 1: it's like then we had this like I think really

833
00:49:16,239 --> 00:49:18,280
Speaker 1: coming in and like the out of the eighties into

834
00:49:18,320 --> 00:49:20,759
Speaker 1: the nineties, like the real MPR voice that I feel

835
00:49:20,760 --> 00:49:22,600
Speaker 1: like like as a kid, I was like, oh wow,

836
00:49:22,760 --> 00:49:26,000
Speaker 1: that's the nice talk radio or whatever. It's less animated,

837
00:49:26,440 --> 00:49:29,000
Speaker 1: and it's it's weird, Like I'm not sure if they

838
00:49:29,000 --> 00:49:32,799
Speaker 1: even know they're doing it, you know, and I know

839
00:49:32,880 --> 00:49:35,160
Speaker 1: that they do on some level because it's part of

840
00:49:35,200 --> 00:49:37,880
Speaker 1: the aesthetic. But if it's like about to say, like

841
00:49:37,920 --> 00:49:39,840
Speaker 1: so to the points like we have to speak like

842
00:49:39,920 --> 00:49:42,000
Speaker 1: this in order to get people to fucking tune in,

843
00:49:42,120 --> 00:49:46,000
Speaker 1: I think it it's sort of it's just a function

844
00:49:46,040 --> 00:49:49,279
Speaker 1: of you know, that way of looking at things. Yeah,

845
00:49:49,320 --> 00:49:52,080
Speaker 1: I think I think it's interesting, not not necessarily as

846
00:49:52,120 --> 00:49:55,120
Speaker 1: like a critique of NPR, like going in and we're

847
00:49:55,160 --> 00:49:57,239
Speaker 1: going to catch them being like you have to talk

848
00:49:57,280 --> 00:50:01,520
Speaker 1: to them like children, because like you know, and even

849
00:50:01,520 --> 00:50:05,319
Speaker 1: if they are saying that like that's, um, I think

850
00:50:05,360 --> 00:50:09,440
Speaker 1: it's interesting about what it reveals about the listeners of

851
00:50:09,719 --> 00:50:14,360
Speaker 1: NPR more than anything. Yeah, I think that the listeners

852
00:50:14,360 --> 00:50:18,000
Speaker 1: of NPR. I mean, if you're if you're on the

853
00:50:18,120 --> 00:50:21,680
Speaker 1: left and you're where you're getting your audio news and

854
00:50:21,719 --> 00:50:25,279
Speaker 1: commentaries NPR, I do feel like that probably suggests that

855
00:50:25,320 --> 00:50:28,080
Speaker 1: you're a certain kind of person because there's so many

856
00:50:28,080 --> 00:50:31,440
Speaker 1: different places to get you know, news and commentary in

857
00:50:31,480 --> 00:50:33,440
Speaker 1: the audio format. If you're if you're if you're sticking

858
00:50:33,440 --> 00:50:37,359
Speaker 1: with NPR, I feel like perhaps you know, you're looking

859
00:50:37,400 --> 00:50:41,520
Speaker 1: for a certain kind of tone. I guess, um, it's

860
00:50:41,520 --> 00:50:43,760
Speaker 1: so funny that we're talking about this. When I first

861
00:50:43,760 --> 00:50:46,600
Speaker 1: started working as a podcaster and an end an audio,

862
00:50:47,320 --> 00:50:49,719
Speaker 1: I thought that I had to do that voice to

863
00:50:49,800 --> 00:50:52,360
Speaker 1: be taken seriously. When I go back and listen to

864
00:50:52,400 --> 00:50:54,919
Speaker 1: the early days of me on podcasts, I can tell

865
00:50:55,040 --> 00:50:58,239
Speaker 1: that I'm sort of I'm doing my NPR voice. You know,

866
00:50:58,360 --> 00:51:02,680
Speaker 1: it's very mono tone. You would think that I am

867
00:51:02,719 --> 00:51:05,480
Speaker 1: talking about things happening in a country where I have

868
00:51:05,600 --> 00:51:07,960
Speaker 1: never even visited, as opposed to my own country. I'm

869
00:51:07,960 --> 00:51:11,040
Speaker 1: talking about things that I have no real opinion on.

870
00:51:11,160 --> 00:51:15,040
Speaker 1: Here's just some very gently delivered information about what could

871
00:51:15,080 --> 00:51:18,440
Speaker 1: be happening somewhere hypothetically, you know. And so I think

872
00:51:18,480 --> 00:51:23,719
Speaker 1: that there was a time where NPR and I yeah,

873
00:51:23,800 --> 00:51:25,560
Speaker 1: no shade to NPR, but there was a time where

874
00:51:25,600 --> 00:51:29,400
Speaker 1: I think that they really were influential and how other

875
00:51:30,080 --> 00:51:33,520
Speaker 1: people did radio and did audio and did podcasting. I

876
00:51:33,800 --> 00:51:40,000
Speaker 1: will say, yeah, for sure, I think that's something. You know,

877
00:51:40,239 --> 00:51:44,839
Speaker 1: when producer Anna and I were like first starting the

878
00:51:45,160 --> 00:51:48,680
Speaker 1: l A How Stuff Works offices, like we talked about

879
00:51:48,719 --> 00:51:52,120
Speaker 1: like we wanted to steer away from the NPR aesthetic

880
00:51:52,200 --> 00:51:55,279
Speaker 1: because it was so pervasive, Like it was just like

881
00:51:55,360 --> 00:51:59,120
Speaker 1: so that's what people thought podcasts sounded like for for

882
00:51:59,160 --> 00:52:02,360
Speaker 1: a long time. Um, but that's so interesting describing it

883
00:52:02,400 --> 00:52:06,120
Speaker 1: as like even though you were describing America, you felt

884
00:52:06,280 --> 00:52:09,760
Speaker 1: pressure to like describe it like it was a country

885
00:52:09,760 --> 00:52:12,600
Speaker 1: where you've never been. Because that really like that was

886
00:52:12,680 --> 00:52:15,880
Speaker 1: kind of what we had landed on yesterday. Is that

887
00:52:15,960 --> 00:52:19,040
Speaker 1: like by doing this and like adding this tone of

888
00:52:19,719 --> 00:52:24,799
Speaker 1: um of like removed like I keep saying, it's like

889
00:52:24,920 --> 00:52:28,239
Speaker 1: feels like they're on xan X because they like feel

890
00:52:28,239 --> 00:52:34,200
Speaker 1: like they're like removed from the anxiety, Uh that you know,

891
00:52:34,320 --> 00:52:37,400
Speaker 1: the rest of the that they're talking about, like an anxious,

892
00:52:37,400 --> 00:52:41,960
Speaker 1: an anxiety provoking situation. Uh. They're describing it like with

893
00:52:42,320 --> 00:52:47,960
Speaker 1: the humanity and the emotion removed from it, and it's yeah,

894
00:52:48,080 --> 00:52:51,239
Speaker 1: it just feels like that has to be at some

895
00:52:51,400 --> 00:52:58,400
Speaker 1: level a conscious decision um that they're like, uh, perpetuating

896
00:52:58,440 --> 00:53:01,120
Speaker 1: because they just have seen at work and I think

897
00:53:01,320 --> 00:53:05,720
Speaker 1: they see it works so well because they're the NPR

898
00:53:05,840 --> 00:53:11,080
Speaker 1: listener wants wants to have be told about the story,

899
00:53:11,640 --> 00:53:14,920
Speaker 1: like be told about the problem, but then like not

900
00:53:15,120 --> 00:53:19,040
Speaker 1: feel bad about it. You can't confront you can't confront

901
00:53:19,080 --> 00:53:24,160
Speaker 1: the actual uncomfortable nous of the story. That's all it is.

902
00:53:24,320 --> 00:53:26,840
Speaker 1: It's it's too it's to tell you enough about the

903
00:53:26,880 --> 00:53:30,640
Speaker 1: story without informing you enough that you can actually begin

904
00:53:30,680 --> 00:53:33,759
Speaker 1: to empathize. Really, I think that's what it is. It

905
00:53:33,239 --> 00:53:36,360
Speaker 1: it really dules your ability to connect with the people

906
00:53:36,360 --> 00:53:38,160
Speaker 1: that are even being talked about in the story. Like

907
00:53:38,200 --> 00:53:40,360
Speaker 1: even that one where the woman was talking about she

908
00:53:40,520 --> 00:53:44,120
Speaker 1: was fleeing like artillery, like shelling from Russians and she

909
00:53:44,320 --> 00:53:47,000
Speaker 1: fled to her basement and was like, well, thank god,

910
00:53:47,080 --> 00:53:48,640
Speaker 1: she had a little bit of food. But it's just

911
00:53:48,680 --> 00:53:51,200
Speaker 1: done as like like we were saying, and you know

912
00:53:51,360 --> 00:53:53,440
Speaker 1: we're hearing her. You can hear in her voice she's

913
00:53:53,480 --> 00:53:55,960
Speaker 1: like she you can tell I don't speak Ukrainian, but

914
00:53:56,000 --> 00:53:58,360
Speaker 1: you can tell this person isn't speaking calmly about the

915
00:53:58,360 --> 00:54:01,799
Speaker 1: situation they were in. But the the translator's voices and

916
00:54:01,840 --> 00:54:03,640
Speaker 1: it's not that it has to be an acted out version,

917
00:54:03,680 --> 00:54:05,600
Speaker 1: but it comes in more like, thank god I had

918
00:54:05,640 --> 00:54:08,080
Speaker 1: potatoes and some extra oil in the house, and also

919
00:54:08,120 --> 00:54:09,840
Speaker 1: I had a count so I was able to get milk.

920
00:54:10,040 --> 00:54:14,400
Speaker 1: And you're like, that was electrifying compared to the to

921
00:54:14,480 --> 00:54:19,360
Speaker 1: the translator, but like and even like you know, you

922
00:54:19,400 --> 00:54:21,759
Speaker 1: go on NPRS page right now, there's there's stuff where

923
00:54:21,800 --> 00:54:25,120
Speaker 1: there's a headline says, why this economy maybe sturdier than

924
00:54:25,200 --> 00:54:28,600
Speaker 1: it looks. When I say, okay, maybe this has something

925
00:54:28,640 --> 00:54:30,840
Speaker 1: to do with the lived experience of people who are

926
00:54:30,840 --> 00:54:34,560
Speaker 1: working in the like as part of the economy, and

927
00:54:34,600 --> 00:54:37,000
Speaker 1: maybe there's some good news. All it's about his g

928
00:54:37,120 --> 00:54:40,120
Speaker 1: d P and ship. The word wage only shows up

929
00:54:40,200 --> 00:54:42,160
Speaker 1: once and it's not even and it's like it's it's

930
00:54:42,200 --> 00:54:45,200
Speaker 1: a quote about someone talking about like she also increased

931
00:54:45,280 --> 00:54:48,640
Speaker 1: or prices to offset rising costs of cotton, polyester, and spandex,

932
00:54:48,680 --> 00:54:52,320
Speaker 1: as well as higher wages for her employees. So now

933
00:54:52,640 --> 00:54:55,520
Speaker 1: the empathy isn't about there's no there's no need to

934
00:54:55,600 --> 00:54:58,080
Speaker 1: feel bad about anyone in this story or even to

935
00:54:58,160 --> 00:55:01,240
Speaker 1: tell people like in this version word wages as mentioned

936
00:55:01,280 --> 00:55:03,839
Speaker 1: in the context of like, man, people poor people ask

937
00:55:03,920 --> 00:55:08,080
Speaker 1: for too much money. Huh yeah. Not. Despite this, the

938
00:55:08,160 --> 00:55:11,480
Speaker 1: lived experience of your neighbors might be completely different to

939
00:55:11,520 --> 00:55:13,520
Speaker 1: some of these headlines about the economy. And I think

940
00:55:13,520 --> 00:55:16,040
Speaker 1: that's where because that's the uncomfortable part if you're going

941
00:55:16,080 --> 00:55:17,920
Speaker 1: to talk about the economy, like is it going to

942
00:55:18,000 --> 00:55:21,240
Speaker 1: be a real thing of like we spoke to working parents,

943
00:55:21,280 --> 00:55:23,520
Speaker 1: single parents, people who live here, people who live there

944
00:55:23,560 --> 00:55:26,840
Speaker 1: about what just what even though we're seeing this economy stuff,

945
00:55:26,840 --> 00:55:29,440
Speaker 1: what's it like for them? And even if when when

946
00:55:29,440 --> 00:55:31,600
Speaker 1: you get pieces like that, are we going to get

947
00:55:31,640 --> 00:55:33,919
Speaker 1: the like is it going to get to the point

948
00:55:33,920 --> 00:55:38,280
Speaker 1: where someone would listen to it and then be outraged? Right? Yeah?

949
00:55:38,360 --> 00:55:40,759
Speaker 1: And I think I mean I have to mention we

950
00:55:40,840 --> 00:55:44,440
Speaker 1: are seeing this interesting moment where NPR seems to be

951
00:55:44,520 --> 00:55:48,640
Speaker 1: kind of hemorrhaging young talent of color, like young audio talent,

952
00:55:49,200 --> 00:55:52,560
Speaker 1: and I have to wonder if there's something related there

953
00:55:52,600 --> 00:55:56,279
Speaker 1: that you know, people want. I feel like people get

954
00:55:56,320 --> 00:56:00,840
Speaker 1: into audio journalism because there's an intimacy to storytelling. You

955
00:56:00,880 --> 00:56:03,680
Speaker 1: can hear, you know, listening to that Ukrainian woman tell

956
00:56:03,680 --> 00:56:05,880
Speaker 1: her story, even if you don't speak the language, you

957
00:56:05,920 --> 00:56:08,200
Speaker 1: can hear it in her voice. And I think that's

958
00:56:08,239 --> 00:56:11,680
Speaker 1: what that's what draws people to audio storytelling in the

959
00:56:11,719 --> 00:56:14,920
Speaker 1: first place. And I think if you're someplace where the

960
00:56:15,200 --> 00:56:22,000
Speaker 1: entire vibe is not reflecting that humanity, that intimacy, that authenticity,

961
00:56:22,040 --> 00:56:24,640
Speaker 1: and that like truth through audio, it does seem to

962
00:56:24,680 --> 00:56:28,760
Speaker 1: be like a little bit of a disconnect. Yeah. Yeah,

963
00:56:29,480 --> 00:56:32,920
Speaker 1: I mean like we were you know, I was saying yesterday,

964
00:56:32,960 --> 00:56:34,880
Speaker 1: like you can mint a bitcoin with the amount of

965
00:56:34,920 --> 00:56:39,080
Speaker 1: like mental work and like pretzeling of themselves that is

966
00:56:39,160 --> 00:56:44,400
Speaker 1: required to achieve the cognitive dissonance required to still be

967
00:56:44,440 --> 00:56:48,279
Speaker 1: on board with like the mainstream media and like d

968
00:56:48,440 --> 00:56:52,120
Speaker 1: n C sort of narratives where like check on the

969
00:56:52,360 --> 00:56:56,000
Speaker 1: g d P every month because that's the thing that matters,

970
00:56:56,040 --> 00:56:58,359
Speaker 1: and we just like care about g d P and

971
00:56:58,400 --> 00:57:01,640
Speaker 1: stuff like that. And I just think that's that's coming

972
00:57:01,640 --> 00:57:04,719
Speaker 1: out in in this weird way. Uh and then I

973
00:57:04,719 --> 00:57:06,600
Speaker 1: also wanted to talk about so j m I, a

974
00:57:06,640 --> 00:57:10,640
Speaker 1: writer from Canada, says the same thing is happening on

975
00:57:10,719 --> 00:57:13,360
Speaker 1: the CBC and has always been happening on the CBC

976
00:57:13,960 --> 00:57:18,280
Speaker 1: um but he has an alternate explanation that they like

977
00:57:18,360 --> 00:57:24,080
Speaker 1: found out about uh HSMR or a SMR and are

978
00:57:24,120 --> 00:57:27,920
Speaker 1: are like because they like keep doing stories about like

979
00:57:27,960 --> 00:57:31,120
Speaker 1: they've done a lot of stories about as MR and

980
00:57:32,040 --> 00:57:34,560
Speaker 1: like it does seem to be His theory is they're

981
00:57:34,600 --> 00:57:37,360
Speaker 1: like ramping it up because they were like, oh yeah,

982
00:57:37,600 --> 00:57:41,480
Speaker 1: like this this makes people feel good. Oh yeah, morning

983
00:57:41,480 --> 00:57:44,920
Speaker 1: a Morning becomes eclectic on k c RW, I'm like,

984
00:57:45,080 --> 00:57:47,360
Speaker 1: I feel like I'm in the middle of yawning the

985
00:57:47,400 --> 00:57:50,520
Speaker 1: whole time I'm listening to it, Like the music is right,

986
00:57:50,560 --> 00:57:53,360
Speaker 1: but like they're like, Milvina, what's going on this weekend?

987
00:57:53,400 --> 00:57:55,440
Speaker 1: They're like, well, actually, I think, Jetty, there's going to

988
00:57:55,520 --> 00:58:00,160
Speaker 1: be a fantastic display of West African art. And You're like, uh,

989
00:58:00,240 --> 00:58:04,240
Speaker 1: huh huh, it's not it's I get it. It's it's soothing.

990
00:58:04,320 --> 00:58:08,600
Speaker 1: But I do find myself, you know, in a trance

991
00:58:08,640 --> 00:58:10,840
Speaker 1: to hearing it, but not even that I'm here, like listening,

992
00:58:10,840 --> 00:58:14,320
Speaker 1: it's like, oh, this is very like the it's that

993
00:58:15,640 --> 00:58:18,320
Speaker 1: that monotone that really, I don't know, it gets you.

994
00:58:18,560 --> 00:58:21,680
Speaker 1: Do you all remember that Saturday Night Live bit um

995
00:58:21,720 --> 00:58:27,080
Speaker 1: the Delicious. Yeah. Yeah. So that's the thing is that

996
00:58:27,360 --> 00:58:31,160
Speaker 1: I don't know if at that time, like they it

997
00:58:31,240 --> 00:58:33,520
Speaker 1: was some of their shows spoke like this, and it

998
00:58:33,600 --> 00:58:38,000
Speaker 1: was the ones about like you know, wine and leaves

999
00:58:38,120 --> 00:58:41,080
Speaker 1: and like foliage and ship, and then they had more

1000
00:58:41,880 --> 00:58:46,200
Speaker 1: more appropriate tone like when talking about news and war crimes.

1001
00:58:46,600 --> 00:58:50,480
Speaker 1: But now the whole thing is it's like listening to

1002
00:58:51,040 --> 00:58:56,400
Speaker 1: those characters do the news about the Russian invasion of Ukraine.

1003
00:58:57,080 --> 00:59:02,240
Speaker 1: Mm hmmm um, And it's very weird, it's very strange. Well,

1004
00:59:02,280 --> 00:59:05,960
Speaker 1: you know again, I think the effective thing about you know, uh,

1005
00:59:06,600 --> 00:59:10,320
Speaker 1: neoliberalism and these news things that are they are helping

1006
00:59:10,360 --> 00:59:12,400
Speaker 1: people kind of stay in this place, is that it

1007
00:59:12,480 --> 00:59:15,080
Speaker 1: helps people not stay in a place of comfort and

1008
00:59:15,120 --> 00:59:18,520
Speaker 1: not really want to do anything radical or or or

1009
00:59:18,560 --> 00:59:21,760
Speaker 1: have the mindset that there's a need for radical change,

1010
00:59:22,000 --> 00:59:23,920
Speaker 1: that's for sure. And I think it's the same thing

1011
00:59:23,960 --> 00:59:27,000
Speaker 1: like even with the uprisings, right, we've barely heard people

1012
00:59:27,240 --> 00:59:30,320
Speaker 1: from that were in the streets talking on TV. If ever,

1013
00:59:30,960 --> 00:59:33,200
Speaker 1: and if it was like find the angriest motherfucker you

1014
00:59:33,240 --> 00:59:36,200
Speaker 1: can find and put them on TV, don't don't get

1015
00:59:36,200 --> 00:59:38,560
Speaker 1: the people who are really there trying to say something.

1016
00:59:38,600 --> 00:59:40,280
Speaker 1: And we would always be like, why are they never

1017
00:59:40,400 --> 00:59:42,400
Speaker 1: talking to the people that are in the streets. It's

1018
00:59:42,440 --> 00:59:44,680
Speaker 1: always like somebody from like fifty feet away, a hundred

1019
00:59:44,680 --> 00:59:46,520
Speaker 1: feet away, like and now that you can see their

1020
00:59:46,520 --> 00:59:49,520
Speaker 1: gathering over here now and blah like doing it like

1021
00:59:49,600 --> 00:59:52,560
Speaker 1: they're calling a fucking horse race or some ship. But

1022
00:59:53,560 --> 00:59:55,920
Speaker 1: we're not. You're not doing us the service of hearing

1023
00:59:55,960 --> 00:59:59,160
Speaker 1: the people who decided to enter physical space why they

1024
00:59:59,160 --> 01:00:02,760
Speaker 1: are there really, rather than your commentary from a hundred

1025
01:00:02,880 --> 01:00:07,040
Speaker 1: thousand feet away and speculating and then basing, you know,

1026
01:00:07,080 --> 01:00:10,000
Speaker 1: being able to shape the entire narrative from there rather

1027
01:00:10,040 --> 01:00:12,400
Speaker 1: than hearing it from people's mouth. Well, I think that

1028
01:00:12,480 --> 01:00:15,400
Speaker 1: goes back to who is listening. As I said earlier,

1029
01:00:15,680 --> 01:00:18,920
Speaker 1: I think if you're in, if you're getting your commentary

1030
01:00:18,920 --> 01:00:21,760
Speaker 1: and your news and your news from MPR, I think

1031
01:00:21,760 --> 01:00:23,760
Speaker 1: that you're not looking for anything radical. I think that

1032
01:00:23,800 --> 01:00:27,160
Speaker 1: you're not looking to be moved into action or feeling

1033
01:00:27,240 --> 01:00:30,800
Speaker 1: discomfort or feeling bad or feeling complicit you know, heaven forbid,

1034
01:00:31,120 --> 01:00:33,080
Speaker 1: I think that if you're not and not again, not

1035
01:00:33,120 --> 01:00:35,320
Speaker 1: to disparage NPR listeners. I listen to some of their

1036
01:00:35,320 --> 01:00:38,720
Speaker 1: programming my parents. I grew up on public radio, you know,

1037
01:00:38,960 --> 01:00:41,320
Speaker 1: not to disparage them, but I think that what you're

1038
01:00:41,360 --> 01:00:46,919
Speaker 1: describing is perhaps not someone who is looking for that

1039
01:00:47,080 --> 01:00:50,240
Speaker 1: kind of you know, those kinds of feelings from their

1040
01:00:50,280 --> 01:00:52,560
Speaker 1: their commentary or their news. They're not looking to feel

1041
01:00:53,040 --> 01:00:58,040
Speaker 1: engaged in that way. I don't think. Yeah. So anyways,

1042
01:00:58,600 --> 01:01:02,440
Speaker 1: zi gang, if you if you feel the same way,

1043
01:01:02,480 --> 01:01:06,080
Speaker 1: if you hear like an NPR clip that has particularly egregious,

1044
01:01:06,360 --> 01:01:09,400
Speaker 1: hit me up. I'm I'm going to keep thinking about

1045
01:01:09,440 --> 01:01:13,000
Speaker 1: this and I'd love to you know, get get more

1046
01:01:13,080 --> 01:01:17,360
Speaker 1: evidence or you know, more more thoughts on it. So

1047
01:01:17,360 --> 01:01:18,960
Speaker 1: so it hit me up. You know what, maybe Jack,

1048
01:01:19,040 --> 01:01:21,400
Speaker 1: we might have to do an episode in that voice,

1049
01:01:21,480 --> 01:01:25,000
Speaker 1: just to see how the audience responds, and we'll say

1050
01:01:25,640 --> 01:01:29,880
Speaker 1: hello the Internet, Hello, and welcome to another episode of

1051
01:01:30,640 --> 01:01:34,640
Speaker 1: Dirt Dailies. Like, yeah, you're actually quite good at that

1052
01:01:34,840 --> 01:01:40,520
Speaker 1: for somebody who just likes it so much, Bridget, it's

1053
01:01:40,560 --> 01:01:44,480
Speaker 1: been such a pleasure having you on, uh the dailies,

1054
01:01:44,520 --> 01:01:48,600
Speaker 1: Like where can people find you, follow you, hear you

1055
01:01:48,640 --> 01:01:52,040
Speaker 1: all that good stuff. Well, I would be so honored

1056
01:01:52,120 --> 01:01:54,360
Speaker 1: and so please the folks checked out my podcast on

1057
01:01:54,400 --> 01:01:56,880
Speaker 1: this very net work. There are no girls on the internet.

1058
01:01:56,880 --> 01:01:59,960
Speaker 1: We've been talking about Elon Musk this week, so please

1059
01:02:00,080 --> 01:02:01,920
Speaker 1: check it out. You can find me on Twitter at

1060
01:02:01,920 --> 01:02:04,600
Speaker 1: Bridget Murray and you can find me on Instagram at

1061
01:02:04,600 --> 01:02:08,040
Speaker 1: Bridget Murray in d C. Yeah, yea. And is there

1062
01:02:08,160 --> 01:02:10,680
Speaker 1: a tweet or some of the work of social media

1063
01:02:10,720 --> 01:02:13,760
Speaker 1: you've been enjoying? Oh yes, this tweet from Brittany van Horn.

1064
01:02:14,320 --> 01:02:16,320
Speaker 1: If we want to if we want to raise the

1065
01:02:16,360 --> 01:02:18,200
Speaker 1: money to buy Twitter back and put it in the

1066
01:02:18,200 --> 01:02:20,080
Speaker 1: hands of the people, we're gonna have to put on

1067
01:02:20,120 --> 01:02:29,600
Speaker 1: the greatest talent show this town's ever so good. Hell yeah, Miles,

1068
01:02:29,600 --> 01:02:32,960
Speaker 1: Where can people find you? What's a tweet you've been enjoying? Man?

1069
01:02:33,000 --> 01:02:36,560
Speaker 1: You can find me on Twitter and Instagram at Miles

1070
01:02:36,720 --> 01:02:40,160
Speaker 1: of Gray. Also the other pod for Fiance, Also the

1071
01:02:40,240 --> 01:02:45,320
Speaker 1: basketball podcast Miles and Jack Got Mad boost these check

1072
01:02:45,400 --> 01:02:49,720
Speaker 1: that our We look, we're just speaking. We're just loving

1073
01:02:49,760 --> 01:02:54,680
Speaker 1: the loving the game of basketball, no hate oration. It's

1074
01:02:54,720 --> 01:02:58,200
Speaker 1: been very refreshing to have a place where I can

1075
01:02:58,400 --> 01:03:05,000
Speaker 1: go and just be excited about John Morant and uh

1076
01:03:05,320 --> 01:03:08,160
Speaker 1: my team the seventies sixers and not have to deal

1077
01:03:08,240 --> 01:03:12,480
Speaker 1: with um Bill Simmons talking about like how this guy's

1078
01:03:12,480 --> 01:03:15,920
Speaker 1: got no hoops a cute um and I'll that guy

1079
01:03:15,960 --> 01:03:23,680
Speaker 1: what uh funk? Jalen Green? Okay, okay, um, it's a

1080
01:03:23,720 --> 01:03:26,320
Speaker 1: great show. Go check it out, Go check it out.

1081
01:03:26,480 --> 01:03:28,040
Speaker 1: You know, do you get in or get out? But

1082
01:03:28,160 --> 01:03:29,680
Speaker 1: you know what, the bus is taken off and we

1083
01:03:29,800 --> 01:03:31,440
Speaker 1: love to have you with us. Okay. A tweet that

1084
01:03:31,480 --> 01:03:34,440
Speaker 1: I like first one from at not Funny L tweeted,

1085
01:03:34,760 --> 01:03:38,240
Speaker 1: my mother staring down at my open casket? Is that

1086
01:03:38,280 --> 01:03:43,520
Speaker 1: what you're wearing? And comb at win w y n

1087
01:03:43,640 --> 01:03:48,160
Speaker 1: n E tweeted, incense looks like skinny corn dog. Like

1088
01:03:52,040 --> 01:03:54,360
Speaker 1: It's like, yeah, it looks like the stick is like

1089
01:03:54,520 --> 01:03:59,960
Speaker 1: batter dipped. Look like that's so that's the same checkolog's

1090
01:04:00,160 --> 01:04:01,959
Speaker 1: we take a stip. We gotta dip it, we gotta

1091
01:04:02,040 --> 01:04:05,439
Speaker 1: dip it anyway, shout out to you. It does look

1092
01:04:05,480 --> 01:04:11,160
Speaker 1: like skinny corn dog. Skinny corn dog. Since it looks

1093
01:04:11,240 --> 01:04:13,920
Speaker 1: like skinny corn dog, it's the I think it's a

1094
01:04:14,000 --> 01:04:17,120
Speaker 1: bad grammar. That also makes this tweet so memorable for

1095
01:04:17,240 --> 01:04:19,880
Speaker 1: me throwing them one more. I think was just a

1096
01:04:19,960 --> 01:04:23,680
Speaker 1: good idea. At clumsy Ail, you tweeted, instead of leaving Twitter,

1097
01:04:23,720 --> 01:04:26,840
Speaker 1: we should all block Elon Musk. But I don't know

1098
01:04:26,880 --> 01:04:28,840
Speaker 1: if that'll help. Yeah, I don't think that would be

1099
01:04:28,880 --> 01:04:32,520
Speaker 1: a significant thing. I did lose a bunch of followers

1100
01:04:32,520 --> 01:04:36,280
Speaker 1: of the past couple of days who are principled people

1101
01:04:36,400 --> 01:04:38,959
Speaker 1: who have decided to leave Twitter. But please come back.

1102
01:04:39,360 --> 01:04:44,600
Speaker 1: I miss you. Um, that's true. That's how I got No,

1103
01:04:44,680 --> 01:04:46,720
Speaker 1: I got lost all my followers. I think they were

1104
01:04:46,720 --> 01:04:50,040
Speaker 1: all bots. Yeah, yeah, you went to my mom. It

1105
01:04:50,120 --> 01:04:53,040
Speaker 1: was crazy to see. Yeah, my one follower my mom.

1106
01:04:53,080 --> 01:04:55,920
Speaker 1: Shout out to you, Mom. I appreciate you buying those bots.

1107
01:04:55,960 --> 01:05:00,720
Speaker 1: You're good mom, getting me get me the ten k Um,

1108
01:05:00,760 --> 01:05:04,560
Speaker 1: a twenty four year old Virgin, tweeted, women be dating

1109
01:05:04,560 --> 01:05:07,000
Speaker 1: men that are nimble and then act all surprised when

1110
01:05:07,000 --> 01:05:12,520
Speaker 1: he jumps over a candlestick? Is that about you, Jack?

1111
01:05:13,880 --> 01:05:20,440
Speaker 1: You know? Guiltiest charge um? And then and then uh

1112
01:05:20,720 --> 01:05:25,560
Speaker 1: will at Mary Will Uh tweeted it finally happened. My

1113
01:05:25,600 --> 01:05:30,000
Speaker 1: photos app generated the saddest video possible. And it's like,

1114
01:05:30,480 --> 01:05:33,720
Speaker 1: you know how your photo app will like just set

1115
01:05:33,840 --> 01:05:37,120
Speaker 1: set something up for you do a little surprise. Uh,

1116
01:05:37,160 --> 01:05:41,040
Speaker 1: and it says tasty bites over the years, and it's

1117
01:05:41,080 --> 01:05:44,320
Speaker 1: like all these pictures of the most depressing meals that

1118
01:05:44,640 --> 01:05:46,439
Speaker 1: I think he had taken pictures of in the first

1119
01:05:46,440 --> 01:05:49,000
Speaker 1: place because they were so depressing, looking like it's like

1120
01:05:49,040 --> 01:05:52,920
Speaker 1: a kid's meal of like macaroni and cheese and stuff.

1121
01:05:52,960 --> 01:05:55,600
Speaker 1: And it's like set to those weird classical piece of music.

1122
01:05:55,920 --> 01:05:59,120
Speaker 1: Um so I don't know it's worth watching. It really

1123
01:05:59,120 --> 01:06:04,960
Speaker 1: resonated with me because those, um, those like algorithmically generated

1124
01:06:04,960 --> 01:06:10,680
Speaker 1: photo SLAD shows always very strange first ballot podcasts at

1125
01:06:10,720 --> 01:06:15,080
Speaker 1: the John Morant dunc an Extreme Slow Motion to Stretch

1126
01:06:15,200 --> 01:06:19,280
Speaker 1: My Hands part one and it's the perfect treatment of that,

1127
01:06:19,440 --> 01:06:23,840
Speaker 1: so highly recommend that. And then Ordinary at Ordinary also

1128
01:06:23,920 --> 01:06:28,120
Speaker 1: tweeted brain cactus me okay, brain, touch it me. But

1129
01:06:28,200 --> 01:06:32,400
Speaker 1: it's sharp, brain, I know. But how sharp? And that is?

1130
01:06:33,760 --> 01:06:35,800
Speaker 1: That is the exact dialect that goes on every time

1131
01:06:35,840 --> 01:06:38,840
Speaker 1: I see a cactus. Oh yeah, I cannot stop myself

1132
01:06:39,000 --> 01:06:42,840
Speaker 1: always surprised. Um. So you can find me liking tweets

1133
01:06:42,920 --> 01:06:46,280
Speaker 1: like that on Twitter at Jack Underscore O'Brien. You can

1134
01:06:46,320 --> 01:06:48,880
Speaker 1: find us on Twitter at daily Zeykeeist were at the

1135
01:06:49,000 --> 01:06:51,880
Speaker 1: Daily Zycheist on Instagram. We have a Facebook fan page

1136
01:06:51,880 --> 01:06:55,080
Speaker 1: on a website, Daily zycheist dot com where we post

1137
01:06:55,120 --> 01:06:57,800
Speaker 1: our episodes on our footnotes where we link off to

1138
01:06:57,800 --> 01:07:00,520
Speaker 1: the information that we talked about in today's episode, as

1139
01:07:00,520 --> 01:07:03,280
Speaker 1: well as a song that we think you might enjoy. Miles,

1140
01:07:03,480 --> 01:07:06,520
Speaker 1: what song do we think people might enjoy? Oh? Um, Well,

1141
01:07:06,560 --> 01:07:08,720
Speaker 1: this is gonna be a great track from the artist

1142
01:07:08,840 --> 01:07:13,240
Speaker 1: Lucy h really new the new new single called Almost Blue.

1143
01:07:14,040 --> 01:07:16,800
Speaker 1: The vocal chopped samples on here with the with the

1144
01:07:16,880 --> 01:07:20,640
Speaker 1: really nice familiar sort of pop R and B instrumental bed.

1145
01:07:21,040 --> 01:07:23,360
Speaker 1: We'll probably bring all of your neighbors to your yard

1146
01:07:23,400 --> 01:07:25,880
Speaker 1: because they're going to think there's some kind of cookout happening.

1147
01:07:25,880 --> 01:07:29,360
Speaker 1: How maybe some other kind of event. So slap this one,

1148
01:07:29,480 --> 01:07:32,800
Speaker 1: bump this in your civic This is Lucy with almost Blue.

1149
01:07:33,040 --> 01:07:36,520
Speaker 1: There go. Um all right, well, The Daily zyke is

1150
01:07:36,560 --> 01:07:38,440
Speaker 1: a production by Her Radio. For more podcast from my

1151
01:07:38,480 --> 01:07:40,800
Speaker 1: Her Radio, visit the Her Radio app, Apple podcast, or

1152
01:07:40,800 --> 01:07:42,840
Speaker 1: wherever you listen to your favorite shows. That's gonna do

1153
01:07:42,920 --> 01:07:45,760
Speaker 1: it for us this morning. But we're back this afternoon

1154
01:07:45,800 --> 01:07:48,080
Speaker 1: to tell you what's trending, and we'll talk to you all.

1155
01:07:48,160 --> 01:07:55,520
Speaker 1: Then Bye bye,