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Speaker 1: Hello the Internet, and welcome to this episode of The

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Speaker 1: Weekly Zeitgeist. These are some of our favorite segments from

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Speaker 1: this week, all edited together into one NonStop infotainment laugh stravaganza. Yeah, So,

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Speaker 1: without further ado, here is the Weekly Zeitgeist. What is

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Speaker 1: something from your search history that is revealing about who

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Speaker 1: you are?

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Speaker 2: I yesterday was looking up the public pool hours in

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Speaker 2: New York because I'm a huge, huge, huge advocate of

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Speaker 2: going to the public pools in New York City because

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Speaker 2: everybody's like, I mean, itw gross the public pools, like

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Speaker 2: I'd rather go to a hotel, and I'm like, okay,

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Speaker 2: but the pools are run by the city and have

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Speaker 2: like really intense guidelines about how clean they have to be.

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Speaker 2: And you know who doesn't have those guidelines any hotel.

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Speaker 2: I don't know if any hotel pools are getting cleaned.

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Speaker 2: And the way that the public pools in New York

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Speaker 2: are so I'm a huge fan freezing cold if you

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Speaker 2: live they're super They're like because they're like cooling centers,

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Speaker 2: like they're four people, especially if you don't have air

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Speaker 2: conditioning in the summer. They're also the location of a

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Speaker 2: lot of the free lunches that get you know, for students,

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Speaker 2: so in the summer you're not in school, that's where

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Speaker 2: they do it. I love, love, love the public pools,

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Speaker 2: but I was I've never gone early enough to know

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Speaker 2: what time they opened, so I was like, I guess

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Speaker 2: I should find out. And it's eleven, which I think

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Speaker 2: is a little close for me, so I don't know

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Speaker 2: if I'll ever get there at opening, but noon feels.

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Speaker 3: Right right, right right. Did you grow up in New York?

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Speaker 4: In New York?

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Speaker 2: No, Yeah, I grew up in Maryland. But I've been

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Speaker 2: here for sixteen or seventeen years, which is crazy because

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Speaker 2: I'm twenty.

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Speaker 3: God so much just kidding.

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Speaker 4: I would never want to be twenty again, my god.

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Speaker 5: Oh yeah, some of the most chaotic times in my

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Speaker 5: life because like La, the pools in La are just

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Speaker 5: because of the ambient heat, not always like super but

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Speaker 5: you definitely cool off.

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Speaker 3: But then we also have like all those like splash parks.

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Speaker 5: Now we're just basically equivalent like an open fire hydrant, yeah,

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Speaker 5: a like foam ground area to make it sae yeah

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Speaker 5: for kids.

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Speaker 4: I love the public pools in LA though, too. I

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Speaker 4: used to go swim in those when I lived there.

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Speaker 4: They're the best.

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Speaker 3: I love the proofs.

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Speaker 4: I guess that's that's something about me. I love pools.

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Speaker 1: It's I've talked before and hear about how my first

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Speaker 1: job out of college was as a pool boy at

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Speaker 1: the Soho House, the roof deck of the Soho House

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Speaker 1: when that had just opened, and I was in charge

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Speaker 1: of just to your point about them not having regulations,

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Speaker 1: I was in charge of like the chlorine levels.

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Speaker 3: Also.

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Speaker 1: Yeah, they were like like there was Oh no. I

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Speaker 1: had somebody who like knew more about it, who checked

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Speaker 1: with me every once in a while, but I was

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Speaker 1: like doing the pH testing and yeah, and I was

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Speaker 1: in no way equipped to do that. I had to

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Speaker 1: like pull a drowning kid out of the pool one

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Speaker 1: time I there. I was there during the blackout of

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Speaker 1: whatever year that was, yeah, two thousand and three, and

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Speaker 1: everybody like came to that pool. It was a tiny pool.

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Speaker 1: It was like halfway between a pool and a bath tub.

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Speaker 4: Yeah, it's like the size of a couch.

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Speaker 1: But everyone thought it would be a cool place to

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Speaker 1: hang out. And it was like milky by the end

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Speaker 1: of it. Because I didn't know what I was doing.

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Speaker 1: They just like put whoever's up there in charge of

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Speaker 1: like the chlorine levels.

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Speaker 5: Yeah, because like on the other side, like in Vegas,

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Speaker 5: their pools, Like if you open your eyes under the water,

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Speaker 5: it will just strip like membranes from your like eyeballs, so.

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Speaker 1: Your eyes turns like five shades, Like, yeah, you just

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Speaker 1: have white walker eyes open them underwater. What is what's

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Speaker 1: something that you think is overrated?

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Speaker 6: I think that Wes Anderson is overrated?

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Speaker 7: What the job for saying? What exactly about less Anderson?

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Speaker 6: I think, Look, I he just tells the same quirky

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Speaker 6: little story over and over again. Granted I have not

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Speaker 6: seen Asteroid City yet, so maybe this one will just

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Speaker 6: blow me away and I will be excited again. To

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Speaker 6: be clear, there was a time period where I did

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Speaker 6: like his work, but I don't know, Maybe I think

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Speaker 6: it's just like too repetitive. I don't know. And but like, yeah,

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Speaker 6: I get it, like he's an a tour so he's

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Speaker 6: going to have a distinct style that he kind of

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Speaker 6: just keeps recycling over and over. But like, I don't know,

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Speaker 6: I just like find his quirky little quirkiness a bit

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Speaker 6: tiresome these days.

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Speaker 7: What era.

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Speaker 6: I would say, Well, the for me was fantastic mister Fox.

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Speaker 6: Hell yeah, that's probably my favorite of his and leading

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Speaker 6: up to but then like after that, I felt like

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Speaker 6: there was just a declose moon Rise Kingdom. I think

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Speaker 6: that one was like, okay, fine, and then and then

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Speaker 6: again another controversial take here, but I thought that Isle

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Speaker 6: of Dogs was speaking of toilets.

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Speaker 7: Yeah, oh gosh, I think that's totally fair. I okay,

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Speaker 7: here's my experience watching almost every was Anderson film. She

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Speaker 7: was like, gosh, that's really pretty Ohen Wilson. He's always delightful.

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Speaker 7: Costume should get credit. Wow, the fits are fitting. That

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Speaker 7: movie was that. I'll never watch it again and don't

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Speaker 7: revisit Wes Anderson films. They're like very beautiful. I feel

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Speaker 7: like they have just en a story to avoid being

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Speaker 7: music in pieces, you know what I mean. You've seen

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Speaker 7: a movie in the museum.

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Speaker 6: Yeah right, but it's like, tell me the plot of

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Speaker 6: any Wes Anderson movie. You can't like, I can't do it, Like,

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Speaker 6: I don't like, they just don't stick with me. I

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Speaker 6: feel like it's just like you see a frame and

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Speaker 6: you're like, wow, look at all that headroom. That's nice,

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Speaker 6: and look at this misan sen whoo and then you're like,

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Speaker 6: but what was the plot and also why did I

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Speaker 6: watch it?

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Speaker 1: Yeah, feel like he is going to be the least

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Speaker 1: likely filmmaker too for you to be like, Oh, he

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Speaker 1: really surprised me on this one. This is this is not.

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Speaker 1: I did not see this one coming. I think his

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Speaker 1: like French Dispatch, was his attempt to do something different,

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Speaker 1: and I think it's like it's it's definitely my least

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Speaker 1: favorite of his movies.

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Speaker 6: I skipped it. I couldn't be bothered.

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Speaker 1: Yeah, but it's it also seems like I don't see

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Speaker 1: that many people like Riding for that one usually, Like

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Speaker 1: I feel like his movies are some people really like it,

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Speaker 1: some people really hate it, and you know, it's it's

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Speaker 1: kind of random, Like I really like Grand Budapest Hotel,

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Speaker 1: but I don't like a lot of the ones around that,

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Speaker 1: and that's kind of the only later era one that

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Speaker 1: I really enjoy. But a lot of people like really

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Speaker 1: love The Life Aquatic. I've never really connected with that

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Speaker 1: one either, But yeah, French Dispatch felt like people were like, huh,

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Speaker 1: we're we're not going with you on this one. There

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Speaker 1: are some really good performances in it. Yeah, I don't know,

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Speaker 1: I like part of me wants to see the Asteroid

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Speaker 1: City one because I don't know, it just looks like

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Speaker 1: the he's instead of trying to do something different, He's like,

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Speaker 1: I'm going to do the same so hard.

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Speaker 6: Oh you didn't like it when I tried something new,

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Speaker 6: Well fine, I'll do the thing again. Yeah.

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Speaker 1: How about if Wes Anderson tried to make a Wes

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Speaker 1: Anderson movie. He like got jealous of all the people

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Speaker 1: being like on social media being like what if your

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Speaker 1: day was a Wes Anderson movie?

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Speaker 7: And like wild to me that he was upset about that,

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Speaker 7: Like I was really trying to.

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Speaker 1: Was he upset about that? Yeah?

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Speaker 7: Oh wow, Yeah he came out he was like I

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Speaker 7: would never look at those and people realize it's like

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Speaker 7: people are just homaging.

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Speaker 3: You felt like that.

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Speaker 7: I think that the highest form of flattery is like

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Speaker 7: the entire Internet got together and was like, I think

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Speaker 7: your aesthetic is so utterly charming. I'm gonna place myself

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Speaker 7: inside of it.

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Speaker 4: It was I really liked to meet.

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Speaker 7: I thought it was cute, disappointing court your fan base, please.

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Speaker 7: I think it's this is the best ap para social

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Speaker 7: relationship can be. Is just to say hey, guys, I

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Speaker 7: see you and I liked what you did and thank

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Speaker 7: you and then just move on.

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Speaker 1: Yeah.

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Speaker 8: I don't know.

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Speaker 1: I wonder if it's also like you. It would just

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Speaker 1: be like he's worried. It would like fuck him up

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Speaker 1: a little bit to see everybody's like version of him,

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Speaker 1: the way that like seeing someone do an impression of

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Speaker 1: you can be a little unnerving for the first time.

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Speaker 7: You know, that is fair that Okay, maybe, or.

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Speaker 1: Maybe he's just an asshole. I couldn't possibly imagine a

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Speaker 1: universe where that's true.

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Speaker 7: That's from Wes Anderson. That's got his quote directly. So okay,

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Speaker 7: So Wes Anderson said about the memes, I'm very good

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Speaker 7: at protecting myself from seeing all that stuff. If somebody

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Speaker 7: sends me something like that, I'll immediately erase it and

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Speaker 7: say please, sorry, do not send me things of people

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Speaker 7: doing me, because I do not want to look at

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Speaker 7: it thinking.

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Speaker 6: Is that what I do?

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Speaker 7: Is that what I mean? I don't want to see

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Speaker 7: too much of someone else thinking about what I try

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Speaker 7: to be, because God knows, I could then start doing it.

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Speaker 7: So to your point, Jack, this is a form of

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Speaker 7: self protection. And now I dismissed love his fans.

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Speaker 1: Yeah, okay, all right. Also he does betray in that quote,

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Speaker 1: like a little bit of like a thing I always

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Speaker 1: suspect about anybody who got famous before like a certain

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Speaker 1: point like that they just like don't know how technology works,

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Speaker 1: because like if someone sends me something, I erase it, like,

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Speaker 1: what do you mean you RaSE it the link that

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Speaker 1: they sent to you?

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Speaker 6: They delete it from Internet dot com.

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Speaker 1: Oh man, what's something you think is underrated? Teresa?

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Speaker 9: Okay, there's this really cool taco spot right around where

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Speaker 9: I live. It's like my neighborhood. But it's just a

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Speaker 9: guy who sells tacos in front of his house, and

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Speaker 9: he's really cool and it's underrated obviously because you guys.

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Speaker 4: Don't know about it.

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Speaker 9: But I want to kind of out because I love

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Speaker 9: this so much. Literally, I feel like it's like I

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Speaker 9: don't want to say I manifested it, because obviously this

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Speaker 9: man is an individual person who has his own life

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Speaker 9: and needs. But I was thinking right before I move, like, oh,

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Speaker 9: it would be really cool to just I think I

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Speaker 9: was just having existential dreams about you can't tell, like

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Speaker 9: what's my future and livelihood?

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Speaker 4: So it's like what if I just.

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Speaker 9: Like opened a little restaurant in my garage. But that

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Speaker 9: was mostly like I don't actually want to do it,

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Speaker 9: but I was just thinking the idea of like, let's

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Speaker 9: just go back to It reminds me of like Taiwan,

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Speaker 9: where people just have these little eateries and you know

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Speaker 9: your neighborhood and you enjoy your community and it's nice

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Speaker 9: and and it doesn't have to be you know, a

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Speaker 9: Chipotle or bought by Facebook. But then, like the first

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Speaker 9: week I lived here, I saw a sign that was

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Speaker 9: just like handwritten I just like in Spanish, I said,

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Speaker 9: like Tacos Fierness East Abado, like Fridays and Saturdays. And

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Speaker 9: my first thought was like, oh, that must be good

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Speaker 9: because if it's a handwritten sign, it's not advertised.

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Speaker 4: He's only doing it up two days of the week.

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Speaker 1: Just go sheer love of the game.

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Speaker 9: Yeah, but Friday comes around, I'm like, oh, I can't wait.

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Speaker 9: First time I go. And he said it was the

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Speaker 9: first time he was doing it too, So oh, mine

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Speaker 9: line's coincided.

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Speaker 5: Yeah, and so and did You're like I made you

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Speaker 5: do this, Like I've never heard of tacos before.

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Speaker 9: Yesterday He's like, I just spun tuously appeared, but no,

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Speaker 9: he like started this little business in front of his

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Speaker 9: house and he's so good. He just like starts cooking

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Speaker 9: in the afternoon on Fridays, and then around five he

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Speaker 9: started telling it like I was trying to buy it,

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Speaker 9: like at like two, and he was like it's.

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Speaker 3: Not ready yet.

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Speaker 9: And then now, but they're so good and it's so cute,

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Speaker 9: and he's been doing it now for the last couple

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Speaker 9: of weeks every Friday Saturday, and there's like a crowd,

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Speaker 9: and he started here's by Papa's Talk Tacos Papa Jose,

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Speaker 9: And like every week I go there, there's like a

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Speaker 9: new sign now, like he's like adding more marketing. Like

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Speaker 9: now there's a sign down the street along like the

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Speaker 9: you know the main street, that has an little arrow

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Speaker 9: that says tacos. And then the other day there was

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Speaker 9: one that you could scan the QR code and follow him. Oh,

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Speaker 9: Tacos Papa Jose.

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Speaker 1: It's actually brilliant marketing strategy. Could you actually give him

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Speaker 1: my number? I actually want to reach out to him

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Speaker 1: about getting his brand online. That's it. That's really like

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Speaker 1: a cool thing because I feel like the lemonade stand model,

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Speaker 1: like you you never hear that applied anything else. It's

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Speaker 1: just like kids trying their first taking their first whack

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Speaker 1: at capitalism.

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Speaker 4: It's like very and they don't know it's because they're cute.

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Speaker 9: That's why they're selling it.

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Speaker 1: Yeah, right, right, But like if you're good at making stuff,

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Speaker 1: why not do a little talk.

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Speaker 9: It's so good and it's like like it's homemade and

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Speaker 9: there's like, you know, people sitting around. There's usually like

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Speaker 9: a TV and his family's hanging out, so it's like

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Speaker 9: really nice. But also like the first weekend, I think

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Speaker 9: there was a graduation, so a lot of people were coming.

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Speaker 9: But also he just said he I asked them how

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Speaker 9: we advertised, and he just said he was posting on Facebook.

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Speaker 9: So I mean, whatever, fuck it, Zuckerberg, But like that's

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Speaker 9: kind of nice. I don't know, there was something really

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Speaker 9: like sweet about just like it's good and he's just

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Speaker 9: urgently trying to do it that way. But in my mind,

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Speaker 9: I'm like, oh my god, what if this is the

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Speaker 9: next sting type funk because that's how you hear about

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Speaker 9: these like huge eateries. They always start from.

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Speaker 3: Just okay, So then maybe you need to get in

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Speaker 3: as an investor.

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Speaker 1: Yeah, ground investor. This is how you get the Wilding's

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Speaker 1: name after you.

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Speaker 3: Yeah you do. You can stand up and it's gonna.

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Speaker 9: Be called Taco's.

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Speaker 4: Mama Teresa.

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Speaker 3: I did a leverage buy out. I got chased this

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Speaker 3: outside of town. It's all mine now.

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Speaker 1: This idiot made the mistake of showing me his process

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Speaker 1: for making.

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Speaker 3: Meary recipe true capitalists.

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Speaker 4: They're also only two dollars nevery good.

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Speaker 3: That's the other thing.

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Speaker 9: I'm like, oh so so near Salazar, but I'm like

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Speaker 9: this place that's great. Yeah.

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Speaker 5: I love like I love local food, local eateries. It's

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Speaker 5: it's so funny when you meet people like I don't know,

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Speaker 5: maybe it's just being an Angelina, like I've never grown

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Speaker 5: up with like the fear of street food. And also

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Speaker 5: maybe just like in Japan to in Asia, like they're

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Speaker 5: just like in Japan they're called Yatai's where they're just

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Speaker 5: like fucking people just throw up a tent and ship

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Speaker 5: and a grill.

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Speaker 3: Yeah, like they're serving outside of a train. Yeah yeah. Yeah.

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Speaker 3: So like it's it's always funny me.

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Speaker 5: People are like, I don't know about that. I'm like,

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Speaker 5: you have clearly not felt the love of street food.

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Speaker 4: That I will so you can't get stick of you.

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Speaker 9: Like when I went back to time, wanted, I hadn't

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Speaker 9: been for a while, and I just like late, I

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Speaker 9: got something that probably had been out for hours. I

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Speaker 9: was like, I'm going to be like, yeah, you gotta

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Speaker 9: know how to be a little savvy about what time

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Speaker 9: and where which stands are going to.

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Speaker 3: But I like to just say, yeah, it's because you've

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Speaker 3: been out of country too long. Yeah it was. It

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Speaker 3: wasn't their fault.

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Speaker 9: It was you, wasn't They were like, why would you

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Speaker 9: buy this meat thingless?

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Speaker 3: It was clearly a shoe on a stick. I don't know.

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Speaker 5: I thought it was like a gag, like a fun shape.

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Speaker 1: All right, let's take a quick break and we'll come

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Speaker 1: back and talk about cocaine, and we're back and back

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Speaker 1: in our crack days. I worked on an article about

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Speaker 1: like cognitive biases that affect our ability to understand money,

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Speaker 1: and like the piece really like zoomed in on examples

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Speaker 1: of how traditional media interacts with a brain that was

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Speaker 1: designed millions of years ago for an animal that was

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Speaker 1: trying to survive the food chain, and like our brain

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Speaker 1: is designed to process like fairly simple visual stimuli in

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Speaker 1: a pretty straightforward way. That tree has fruit on it.

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Speaker 1: Remember that tree. And then you know, the point in

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Speaker 1: the article was like if you only show the person

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Speaker 1: who won the lottery on TV and not the you know,

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Speaker 1: billions of people who lose the lottery every day, it

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Speaker 1: creates a imprint of like that's the fruit tree, that's

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Speaker 1: that's the place to go, and like that is so basic.

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Speaker 1: That's such a basic thing that just feels like so

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Speaker 1: quaint and antiqu antiquated compared to the modern world that

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Speaker 1: we're existing in, where the increasing use of AI to

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Speaker 1: create intentionally false stories, use of like technology really seems

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Speaker 1: to be accelerating things to in some cases like make

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Speaker 1: them worse or at least there's a feeling that that

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Speaker 1: is the case in like day to day our day

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Speaker 1: to day lives. And so we wanted to talk about

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Speaker 1: kind of all the ways that the modern world is

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Speaker 1: sort of this fun house mirror that our brand's ability

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Speaker 1: to interact with it like just warps and stretches, and

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Speaker 1: it's it's not going well. It seems like based on

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Speaker 1: some of these statistics that you pulled, Jason.

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Speaker 8: Well, I wanted to pull some stance because when we

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Speaker 8: talk about like people being anxious or depressed or whatever.

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Speaker 8: These days, it's not just talking about vibes like you

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Speaker 8: can look at the statistics. So, suicide rates been climbing

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Speaker 8: in the USA for the last twenty years. Around two

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Speaker 8: thousand is when most of these trends started to skew higher.

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Speaker 8: That is a distinctly American phenomenon. Most other countries suicide

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Speaker 8: rates have been steadily following. This is an American thing,

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Speaker 8: but there's a large number they call deaths of despair

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Speaker 8: where they want together suicide, alcohol debts, drug related deaths,

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Speaker 8: and all of that has skewed up since two thousand

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Speaker 8: and then since around twenty ten has started to like

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Speaker 8: most of them have kind of started to spike. Now

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Speaker 8: part of you you mentioned like the deaths of the

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Speaker 8: drug overdose deaths. Some of that is separately just the

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Speaker 8: opioid epidemic and fentanyl, but also some of those overdoses

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Speaker 8: are intentional, but if there's no note left behind, they

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Speaker 8: just put it down as overdose because of course, how

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Speaker 8: do you know, so that's and so. And then anxiety

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Speaker 8: and depression both have been rising up specifically among the

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Speaker 8: youth again going back to around two thousand and nine

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Speaker 8: twenty ten. Now there's two ways people interpret this that

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Speaker 8: are controversial. You can either say that these things have

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Speaker 8: been going up in the internet era and then have

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Speaker 8: accelerated in the smartphone era. Or you can say, well,

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Speaker 8: these things have gone up since nine to eleven and

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Speaker 8: accelerated since the financial crisis of two thousand and eight.

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Speaker 8: When we start talking about how the media and smartphones,

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Speaker 8: all those things make people more anxious, this obsess people

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Speaker 8: because the response is always, well, we're not anxious because

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Speaker 8: of phones. We're anxious because the world is on fire.

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Speaker 8: Our assertion is not that there are no problems in

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Speaker 8: the world. Our assertion, or at least mine, is that

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Speaker 8: the way media, the media environment is one of those problems.

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Speaker 8: It's one of those things that make things worse.

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Speaker 1: Yeah, I think there's a lot of things, like all

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Speaker 1: the things that you were saying, like the world is

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Speaker 1: on fire nine to eleven, the economic collapse, and then

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Speaker 1: also having devices in our hands feeding us a steady

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Speaker 1: stream of media that's like specifically tailored to us and

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Speaker 1: specifically based on preferences of what makes us angriest or

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Speaker 1: most frightened. Like those things can't be good and yeah,

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Speaker 1: I think there's miles you pulled to Al Jazeera story

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Speaker 1: about like outrage headlines increasing well because.

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Speaker 5: I mean, yeah again, like we're there's so many facets

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Speaker 5: of how we end up with bad vibes. The bad

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Speaker 5: vibes decades uh trademarked, but yeah, like I think one

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Speaker 5: of them is, you know, like this is some version

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Speaker 5: of like mean world syndrome where a lot of your

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Speaker 5: media diet are just giving you sort of an over

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Speaker 5: emphasis on the terrible things that are happening, which can

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Speaker 5: just lead to like being more cynical or just being

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Speaker 5: like what the fuck is going on? And yeah, like

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Speaker 5: with Al Jazeera, they analyze like headlines like well, like

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Speaker 5: tens of thousands of headlines from twenty to twenty nineteen

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Speaker 5: just to see what the emotional charge of was of

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Speaker 5: some of these headlines, and they've noticed that things have

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Speaker 5: just gotten more and more increasingly negative since the year

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Speaker 5: two thousand, like you know, headlines that say like quote,

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Speaker 5: Brazil prison riot leaves nine dead rather than things like

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Speaker 5: a new lens restores vision and brings relief.

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Speaker 3: And we're seeing just that sort of that.

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Speaker 5: Rise in those kinds of headlines be equally sort of

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Speaker 5: distributed between the right and left, but there is there

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Speaker 5: is an edge on the right, like with conservative media

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Speaker 5: definitely having those you know, a bigger emphasis on the

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Speaker 5: fear based kind of headline. And I feel the same

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Speaker 5: way too, like because reading as much news as I do,

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Speaker 5: or we have to making this show like that absolutely

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Speaker 5: has an effect on me.

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Speaker 3: But then you kind of have to.

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Speaker 5: Take a step back and like, what are the statistics

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Speaker 5: saying you're actually getting something completely different?

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Speaker 1: Yeah?

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Speaker 8: Yeah, what the headlines? And again note that there's the

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Speaker 8: year two thousand again when going back to the origin

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Speaker 8: of that, what was driven by that was the death

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Speaker 8: of news being a print medium versus news being an

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Speaker 8: online medium because again with newspaper headlines, like of course

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Speaker 8: once pon a time they had to sell papers that

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Speaker 8: now individual stories have to get clicked on. Yeah, and

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Speaker 8: very very quickly, just through ab testing. Again there's no

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Speaker 8: conspiracy here. Just through trancking user behavior, they figured out

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Speaker 8: that the more emotionally charge i mean, we saw this cracked,

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Speaker 8: the more emotionally charged headline gets clicked. So now every

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Speaker 8: individual headline because you know, once upon a time you'd

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Speaker 8: have a newspaper with a big headline across the top.

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Speaker 8: You know, Nixon goes to jail whatever. I don't think

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Speaker 8: Nixon never actually went to the other Yeah, yeah, it

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Speaker 8: doesn't matter.

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Speaker 1: Would have sold papers and it would have been a

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Speaker 1: headline in the modern.

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Speaker 8: Are and then a lot of the other headlines would

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Speaker 8: be very boring and straightforward city council votes to do whatever. Well, now,

439
00:22:26,119 --> 00:22:28,240
Speaker 8: if you want people to click on that boring city

440
00:22:28,280 --> 00:22:31,399
Speaker 8: council story, if it's your job as a journalist get

441
00:22:31,440 --> 00:22:33,280
Speaker 8: people to click, there's got to be an angle on

442
00:22:33,359 --> 00:22:37,080
Speaker 8: there that's going to get people mad. And so beyond

443
00:22:37,080 --> 00:22:41,119
Speaker 8: the examples you gave here, you have the news, you know,

444
00:22:41,160 --> 00:22:43,440
Speaker 8: the actual news organization's gathering news. But then you have

445
00:22:43,560 --> 00:22:47,600
Speaker 8: the aggregators of the content like Coffington Post, BuzzFeed, Vox,

446
00:22:47,640 --> 00:22:49,800
Speaker 8: all of these sites that basically would take the headline

447
00:22:49,840 --> 00:22:52,239
Speaker 8: and then do a little blog post about it, and

448
00:22:52,400 --> 00:22:56,320
Speaker 8: those titles would be things like, you know, if you're

449
00:22:56,320 --> 00:22:59,600
Speaker 8: not paying attention to this, you're not angry enough, or

450
00:22:59,760 --> 00:23:02,119
Speaker 8: this clip is going to leave you outraged when you

451
00:23:02,160 --> 00:23:06,320
Speaker 8: see how they treated this disabled man at McDonald's, you're

452
00:23:06,359 --> 00:23:08,919
Speaker 8: going to be furious, Like literally putting the emotion in

453
00:23:09,000 --> 00:23:14,320
Speaker 8: the headline. If you're not mad, You're not a good person, right,

454
00:23:14,400 --> 00:23:16,880
Speaker 8: and making that part of the ethos of the time

455
00:23:16,960 --> 00:23:18,760
Speaker 8: that it's like, if you want to be a good

456
00:23:18,840 --> 00:23:21,240
Speaker 8: person who cares about the world, you must be angry

457
00:23:21,600 --> 00:23:23,880
Speaker 8: all the time because there's so much there's so much

458
00:23:23,920 --> 00:23:27,480
Speaker 8: injustice or whatever. Never Mind that that doesn't help that

459
00:23:27,520 --> 00:23:30,040
Speaker 8: person in the video. Never Mind that you're watching a

460
00:23:30,080 --> 00:23:33,879
Speaker 8: clip from three years ago and everyone has forgotten about it.

461
00:23:33,880 --> 00:23:35,720
Speaker 8: It doesn't matter. It has bubbled up on the Reddit

462
00:23:35,800 --> 00:23:39,200
Speaker 8: and now everybody's mad again to no effect, Like it's

463
00:23:39,200 --> 00:23:41,399
Speaker 8: not motivating you to help this person.

464
00:23:42,080 --> 00:23:46,680
Speaker 1: Yeah. What one old, outdated technology I think we're underrating

465
00:23:46,760 --> 00:23:49,679
Speaker 1: is newsies. These headlines are doing. You know, newsies just

466
00:23:49,760 --> 00:23:52,359
Speaker 1: used to yell at you to read the newspaper and

467
00:23:52,400 --> 00:23:55,520
Speaker 1: people would just listen because they're scared of the newsies.

468
00:23:55,960 --> 00:23:58,360
Speaker 1: But now they have to scare us with the actual

469
00:23:58,480 --> 00:24:02,040
Speaker 1: content of the headline, and then I think, you know,

470
00:24:02,080 --> 00:24:05,679
Speaker 1: we We've also talked recently about how the number of

471
00:24:05,720 --> 00:24:10,280
Speaker 1: people who identify with a religion or involved in a religion,

472
00:24:10,560 --> 00:24:14,520
Speaker 1: and the number of people who have access to or

473
00:24:14,600 --> 00:24:20,000
Speaker 1: regular contact with a community like both are just on

474
00:24:20,080 --> 00:24:23,800
Speaker 1: an all time low and going lower. And so I

475
00:24:23,840 --> 00:24:29,359
Speaker 1: think that there's a broad kind of you can call

476
00:24:29,400 --> 00:24:33,280
Speaker 1: it spiritual or like broadly psychological level more than ever

477
00:24:33,359 --> 00:24:39,399
Speaker 1: before where we don't have access to answering some of

478
00:24:39,440 --> 00:24:42,879
Speaker 1: the big questions. And so, like we speculated in past

479
00:24:43,280 --> 00:24:46,879
Speaker 1: one of these like kind of broad episodes about the

480
00:24:46,920 --> 00:24:51,160
Speaker 1: idea that like maybe stand culture is coming from that

481
00:24:51,280 --> 00:24:55,240
Speaker 1: this need to sublimate ourselves to something higher and like

482
00:24:55,320 --> 00:25:00,199
Speaker 1: some mythical like godhead figure or like leader person like

483
00:25:00,240 --> 00:25:03,760
Speaker 1: because we're not getting that anywhere else, and so like

484
00:25:03,840 --> 00:25:07,240
Speaker 1: we get stand culture or the stories of the movies

485
00:25:07,240 --> 00:25:09,439
Speaker 1: that make an imprint on us when we're very young,

486
00:25:09,760 --> 00:25:13,160
Speaker 1: like Star Wars or you know, Harry Potter, the Matrix,

487
00:25:13,200 --> 00:25:19,600
Speaker 1: Like these are our mythical stories that we have chosen

488
00:25:19,640 --> 00:25:24,399
Speaker 1: to kind of put ourselves like derive our meaning from.

489
00:25:24,960 --> 00:25:30,080
Speaker 1: And that actually made a lot of sense of how

490
00:25:30,119 --> 00:25:33,960
Speaker 1: people react, like how Star Wars fans or like fandoms

491
00:25:34,480 --> 00:25:38,680
Speaker 1: react like there is a religious war when something happens

492
00:25:38,760 --> 00:25:42,359
Speaker 1: that doesn't cohere to the dogma that they were raised on.

493
00:25:42,720 --> 00:25:45,199
Speaker 1: But I think there's a lot of like kind of

494
00:25:45,600 --> 00:25:51,320
Speaker 1: grasping for meaning as technology has isolated us from one

495
00:25:51,359 --> 00:25:55,399
Speaker 1: another and from the communities that used to allow people

496
00:25:55,440 --> 00:26:00,040
Speaker 1: to sort of dissolve their sense of self into like

497
00:26:00,080 --> 00:26:04,600
Speaker 1: a broader, less kind of self centered way of viewing

498
00:26:04,600 --> 00:26:07,400
Speaker 1: the world. And I mean, yeah, we were talking about

499
00:26:07,440 --> 00:26:12,320
Speaker 1: like consumer culture as like kind of another example of

500
00:26:12,359 --> 00:26:15,639
Speaker 1: where we see this. I mean with with I guess

501
00:26:16,080 --> 00:26:20,040
Speaker 1: stand culture is one example of that, but consumerism people

502
00:26:20,080 --> 00:26:23,600
Speaker 1: have become like very serious consumers, like to like on

503
00:26:23,640 --> 00:26:26,840
Speaker 1: a deep, deeply personal level.

504
00:26:27,000 --> 00:26:29,600
Speaker 5: I feel like yeah, because I mean, like to your point,

505
00:26:29,640 --> 00:26:32,400
Speaker 5: I mean, I don't you know, the lack of religion

506
00:26:32,520 --> 00:26:35,680
Speaker 5: or I think the sense of community more than like finding.

507
00:26:35,800 --> 00:26:37,879
Speaker 5: I mean, people are finding meaning in other things, but

508
00:26:37,920 --> 00:26:40,479
Speaker 5: I don't know how many people are explicitly like I

509
00:26:40,560 --> 00:26:43,399
Speaker 5: just at least something that kind of explains everything. And

510
00:26:43,480 --> 00:26:46,159
Speaker 5: I think the way we pivot to that is just

511
00:26:46,200 --> 00:26:48,439
Speaker 5: to find, like you say, like, because we feel so

512
00:26:48,520 --> 00:26:51,320
Speaker 5: isolated where we want to find community in these other

513
00:26:51,359 --> 00:26:53,800
Speaker 5: ways that like are interesting to us because I'm not

514
00:26:53,920 --> 00:26:57,639
Speaker 5: interested in religion, Yeah, but I'm interested in Arsenal Football club,

515
00:26:58,359 --> 00:27:02,240
Speaker 5: and that is the closest I begin to devote myself

516
00:27:02,320 --> 00:27:04,680
Speaker 5: to something that's like part like there's a group, there's

517
00:27:04,720 --> 00:27:07,240
Speaker 5: like a in group where I'm trying to be like

518
00:27:07,320 --> 00:27:11,399
Speaker 5: identify with these other supporters. I go through the religious

519
00:27:11,800 --> 00:27:15,119
Speaker 5: ceremonies of like watching the matches and getting very emotional

520
00:27:15,160 --> 00:27:17,840
Speaker 5: as I watch them, and be very like emotionally moved

521
00:27:17,880 --> 00:27:20,119
Speaker 5: when things go up or down, and so like, I

522
00:27:20,440 --> 00:27:23,720
Speaker 5: find that like most people have like a topic where

523
00:27:23,760 --> 00:27:26,760
Speaker 5: they will bring that sort of level of like devotion to,

524
00:27:27,200 --> 00:27:28,879
Speaker 5: you know, like what they're paying attention to and what

525
00:27:28,880 --> 00:27:31,800
Speaker 5: they're willing to debate people on, et cetera. Because yeah,

526
00:27:31,840 --> 00:27:34,480
Speaker 5: like we're all we're all just trying to find something

527
00:27:34,520 --> 00:27:37,399
Speaker 5: that like feels good and helps us feel connected at

528
00:27:37,440 --> 00:27:38,879
Speaker 5: the end of the day at least certainly that I

529
00:27:38,880 --> 00:27:41,160
Speaker 5: can speak for myself in that very narrow example.

530
00:27:42,200 --> 00:27:44,080
Speaker 8: Yes, this is something else where you can tract and

531
00:27:44,119 --> 00:27:47,280
Speaker 8: statistics like the average number of friends and close friends

532
00:27:47,280 --> 00:27:50,200
Speaker 8: a person has again has been dropping since the nineties,

533
00:27:51,119 --> 00:27:54,680
Speaker 8: and it is just the people used to meet their

534
00:27:54,720 --> 00:27:57,680
Speaker 8: friends at church, They used to meet their friends at

535
00:27:57,680 --> 00:27:59,560
Speaker 8: the office, and now a lot of people work at home,

536
00:28:00,119 --> 00:28:03,920
Speaker 8: you know. And that's the thing where we can sit

537
00:28:03,920 --> 00:28:05,879
Speaker 8: here and talk about as like a mystical thing like

538
00:28:05,920 --> 00:28:08,719
Speaker 8: there's no sense of unity or community or whatever, but

539
00:28:09,240 --> 00:28:11,600
Speaker 8: from just a practical point of view, having a friend

540
00:28:11,600 --> 00:28:13,879
Speaker 8: who will give you a ride to the airport, or

541
00:28:13,880 --> 00:28:16,720
Speaker 8: who will help you move or you know, like just

542
00:28:16,800 --> 00:28:19,199
Speaker 8: as in a practical manner. We that's part of what

543
00:28:19,760 --> 00:28:22,120
Speaker 8: people don't get this. It's part of what a church provided.

544
00:28:22,280 --> 00:28:24,720
Speaker 8: Like the church when one person got sick and couldn't work,

545
00:28:24,760 --> 00:28:26,600
Speaker 8: the other members of the church would bring food to

546
00:28:26,640 --> 00:28:29,040
Speaker 8: their house. They would come help them clean like that

547
00:28:29,200 --> 00:28:31,160
Speaker 8: was and you did it because it's like, hey, we

548
00:28:31,240 --> 00:28:34,760
Speaker 8: all are Baptists or whatever, and we are all on

549
00:28:34,800 --> 00:28:38,320
Speaker 8: the same team. And it was That's something that is

550
00:28:39,160 --> 00:28:42,440
Speaker 8: humans do everywhere that you find humans as we organize

551
00:28:42,440 --> 00:28:44,600
Speaker 8: and get together, but we usually have to have something

552
00:28:44,640 --> 00:28:49,480
Speaker 8: to rally around, a symbol or something a tree, this

553
00:28:49,600 --> 00:28:53,040
Speaker 8: tree si, we all yeah, whatever it is, you know.

554
00:28:54,520 --> 00:28:57,280
Speaker 8: And unfortunately that also makes us go to war with

555
00:28:57,320 --> 00:28:59,200
Speaker 8: one another. If you see somebody in a Red Sox

556
00:28:59,280 --> 00:29:01,840
Speaker 8: Jersey Yankee fan and then it's like, all right, let

557
00:29:02,240 --> 00:29:05,160
Speaker 8: let's go punch that guy. But when you talk about

558
00:29:05,240 --> 00:29:08,840
Speaker 8: and there's a term that is for the modern situation,

559
00:29:08,960 --> 00:29:13,200
Speaker 8: which is atomization, where you've adomized people to where now

560
00:29:13,320 --> 00:29:15,080
Speaker 8: if you need a ride to the airport, you're going

561
00:29:15,160 --> 00:29:18,800
Speaker 8: to you know, pay for an uber and so many

562
00:29:18,800 --> 00:29:21,120
Speaker 8: of these things that used to be stuff that friends

563
00:29:21,120 --> 00:29:23,400
Speaker 8: would do. It's like, well, now it's a corporation doing

564
00:29:23,440 --> 00:29:27,880
Speaker 8: it for you. And I'm not saying that the friends

565
00:29:28,000 --> 00:29:32,040
Speaker 8: you know purely online aren't your real friends, but it's

566
00:29:32,080 --> 00:29:34,120
Speaker 8: a different type of friendship. If it's somebody who you

567
00:29:34,240 --> 00:29:36,600
Speaker 8: can't call when you've broken your leg you need somebody

568
00:29:36,600 --> 00:29:40,040
Speaker 8: to go get groceries for you, or vice versa. If

569
00:29:40,080 --> 00:29:42,600
Speaker 8: you're not the person that like, you feel obligator to

570
00:29:42,640 --> 00:29:44,760
Speaker 8: do that because they're my friend, like like they depend

571
00:29:44,880 --> 00:29:48,080
Speaker 8: on me. It means something to be needed, to be

572
00:29:48,160 --> 00:29:51,320
Speaker 8: dependent on, Like to get in a situation where nobody

573
00:29:51,320 --> 00:29:54,840
Speaker 8: depends on you, and like I don't have children or whatever,

574
00:29:54,880 --> 00:29:57,120
Speaker 8: but like I don't have friends where that friend's gonna

575
00:29:57,160 --> 00:29:58,920
Speaker 8: call me in the middle of I said, hey, I

576
00:29:58,920 --> 00:30:01,200
Speaker 8: need you to come bail me in it. Like that

577
00:30:01,240 --> 00:30:03,880
Speaker 8: sucks in the moment, but knowing that somebody needs you

578
00:30:04,640 --> 00:30:07,800
Speaker 8: is what keeps you going When you're that isolated from

579
00:30:07,840 --> 00:30:11,880
Speaker 8: real life connections. It's too easy to just drift away.

580
00:30:12,320 --> 00:30:15,680
Speaker 8: Humans need to be needed. Do we need that actual

581
00:30:15,760 --> 00:30:16,840
Speaker 8: in real life connection?

582
00:30:17,200 --> 00:30:20,040
Speaker 5: Which is interesting too because I see this like on

583
00:30:20,120 --> 00:30:23,960
Speaker 5: TikTok more and more of people posting like these strategies

584
00:30:24,160 --> 00:30:27,680
Speaker 5: that come off as like the most manipulative, sort of

585
00:30:27,680 --> 00:30:30,240
Speaker 5: like sadistic things where they talk about it's like you

586
00:30:30,360 --> 00:30:32,640
Speaker 5: got to be needed, and that's how you do It's

587
00:30:32,680 --> 00:30:35,200
Speaker 5: how you develop even deeper relationships. I do this thing

588
00:30:35,240 --> 00:30:39,479
Speaker 5: with my wife where I unhook the chain from the

589
00:30:39,520 --> 00:30:44,280
Speaker 5: toilet handle so she'll need and when the toilet isn't working,

590
00:30:44,600 --> 00:30:47,080
Speaker 5: she will then associate me with someone who can come

591
00:30:47,160 --> 00:30:49,800
Speaker 5: and solve a problem, and then that helps create a

592
00:30:49,840 --> 00:30:50,520
Speaker 5: deeper love.

593
00:30:50,600 --> 00:30:53,840
Speaker 3: And you're like, oh my god, and people are like really.

594
00:30:53,720 --> 00:30:57,120
Speaker 5: Like I mean, that's a kind of fringe element of TikTok,

595
00:30:57,200 --> 00:30:58,880
Speaker 5: But more and more people are taking these sort of

596
00:30:58,880 --> 00:31:03,040
Speaker 5: things and sort of finding to like manufacture these kinds

597
00:31:03,080 --> 00:31:06,840
Speaker 5: of connections because they aren't happening like normally either, and

598
00:31:06,880 --> 00:31:09,479
Speaker 5: you're kind of like this sounds like sociopathic. But on

599
00:31:09,520 --> 00:31:11,720
Speaker 5: the other side of it, you can see people sort

600
00:31:11,720 --> 00:31:14,719
Speaker 5: of like yearning for like, yeah, how do I cultivate

601
00:31:14,840 --> 00:31:15,680
Speaker 5: a deeper connection?

602
00:31:15,760 --> 00:31:17,680
Speaker 3: Do I need to sort of gaslight this person?

603
00:31:17,680 --> 00:31:20,440
Speaker 5: And then thinking that the toilet never works and I'm

604
00:31:20,040 --> 00:31:24,040
Speaker 5: the like magical fixer of that. But again, like you

605
00:31:24,040 --> 00:31:27,719
Speaker 5: see it expressed in so many ways of that there

606
00:31:27,840 --> 00:31:30,360
Speaker 5: is this deeper human thing lacking.

607
00:31:30,560 --> 00:31:33,040
Speaker 8: Yeah work, I mean then a system from it's always

608
00:31:33,080 --> 00:31:36,280
Speaker 8: sunny in Philadelphia, right right if you don't know that

609
00:31:36,320 --> 00:31:37,120
Speaker 8: reference right.

610
00:31:38,280 --> 00:31:43,360
Speaker 1: About but a strange like when one of your human

611
00:31:43,360 --> 00:31:47,920
Speaker 1: interactions most common human interactions is like an uber driver,

612
00:31:48,120 --> 00:31:50,560
Speaker 1: like a person a stranger you can put on quiet

613
00:31:50,600 --> 00:31:53,840
Speaker 1: mode like when when you're having a conversation with them.

614
00:31:53,920 --> 00:31:56,440
Speaker 1: Then it makes sense to me that that sort of

615
00:31:57,320 --> 00:31:59,560
Speaker 1: manipulation and viewing other people as a means to an

616
00:31:59,640 --> 00:32:04,320
Speaker 1: end bleed into how you view like other other parts

617
00:32:04,320 --> 00:32:08,120
Speaker 1: of your life. Right if everything's just sort of a

618
00:32:08,120 --> 00:32:14,440
Speaker 1: transactional and I mean they talk about this new sort

619
00:32:14,440 --> 00:32:18,560
Speaker 1: of information and also like just day to day economy

620
00:32:18,560 --> 00:32:24,400
Speaker 1: as being a way to reduce the friction of that

621
00:32:24,800 --> 00:32:26,680
Speaker 1: like got in the way of some of our consumer

622
00:32:26,800 --> 00:32:31,320
Speaker 1: like spending habits, and like friction in many cases seems

623
00:32:31,320 --> 00:32:34,720
Speaker 1: to be human interaction. So I think one thing we're

624
00:32:34,760 --> 00:32:39,080
Speaker 1: going to say overall human interaction good. Find ways to

625
00:32:39,120 --> 00:32:42,239
Speaker 1: be part of a community, you know, preferably one that

626
00:32:42,520 --> 00:32:45,200
Speaker 1: needs you and gives you meaning.

627
00:32:45,360 --> 00:32:48,280
Speaker 8: Miles The next time you go on TikTok, like there's

628
00:32:48,320 --> 00:32:51,120
Speaker 8: a meta narrative in that video you saw, because that

629
00:32:51,200 --> 00:32:55,960
Speaker 8: algorithm floated up to you a video where the actual

630
00:32:56,640 --> 00:33:01,800
Speaker 8: message was people are crazy out there and relationships are

631
00:33:01,800 --> 00:33:04,440
Speaker 8: weird and toxic these days. You would be shocked at

632
00:33:04,480 --> 00:33:08,440
Speaker 8: what percentage of the feed is some subtle message, some

633
00:33:08,480 --> 00:33:11,360
Speaker 8: subtle version of out there is dangerous.

634
00:33:12,000 --> 00:33:12,160
Speaker 6: Right.

635
00:33:12,320 --> 00:33:16,880
Speaker 8: Guys are sexist, women are crazy, their standards are super high.

636
00:33:17,480 --> 00:33:20,240
Speaker 8: You'll be accused of sexual harassment if you ever try

637
00:33:20,280 --> 00:33:23,160
Speaker 8: to talk to a woman in any setting. And there's

638
00:33:23,200 --> 00:33:27,120
Speaker 8: this meta message of the only safe place is at

639
00:33:27,160 --> 00:33:28,920
Speaker 8: home looking at a screen.

640
00:33:29,320 --> 00:33:32,720
Speaker 1: Yeah, women out there and sees people who aren't there,

641
00:33:33,640 --> 00:33:36,280
Speaker 1: just as you mentioned as a video like it's a

642
00:33:36,280 --> 00:33:40,720
Speaker 1: person having a mental health episode. That was everywhere for

643
00:33:40,960 --> 00:33:44,920
Speaker 1: like a week, and I never would have seen thirty

644
00:33:45,280 --> 00:33:47,440
Speaker 1: you know, twenty maybe like ten years ago.

645
00:33:47,720 --> 00:33:49,880
Speaker 8: You know, there was a time when that wouldn't have

646
00:33:49,920 --> 00:33:52,160
Speaker 8: even shown up in like the police boughter and your

647
00:33:52,200 --> 00:33:54,520
Speaker 8: local paper. It was a non event. Somebody threw a

648
00:33:54,560 --> 00:33:56,400
Speaker 8: fit on it, but because it was captured on camera.

649
00:33:56,440 --> 00:33:59,480
Speaker 8: But the message is it's scary to find there's crazy

650
00:33:59,520 --> 00:34:02,880
Speaker 8: people out of there, and any conservative news like you

651
00:34:02,920 --> 00:34:05,920
Speaker 8: if you look at the comments on any conservative news outlet.

652
00:34:05,920 --> 00:34:09,520
Speaker 8: It's like, well, I won't even drive through this city,

653
00:34:09,640 --> 00:34:13,759
Speaker 8: like it's just mac It's like, no, it's not. I've

654
00:34:13,840 --> 00:34:16,600
Speaker 8: been there. It's people walking around and shopping and eating

655
00:34:16,640 --> 00:34:18,799
Speaker 8: in the restaurants. Bit It's like no, from from their

656
00:34:18,840 --> 00:34:22,640
Speaker 8: point of view, it's just cars on fire, smashed windows.

657
00:34:22,680 --> 00:34:25,480
Speaker 8: Like if you are a white person, the minorities will

658
00:34:25,480 --> 00:34:27,359
Speaker 8: just drag you off the street because they all it's

659
00:34:27,400 --> 00:34:31,160
Speaker 8: Antifa and the Black Lives Matter. It's like, you've got

660
00:34:31,160 --> 00:34:35,320
Speaker 8: such a weird view of the world, but it's all

661
00:34:36,120 --> 00:34:38,920
Speaker 8: you're only safe at home. Like you have people living

662
00:34:38,960 --> 00:34:42,520
Speaker 8: in the middle of whatever, Oklahoma or Montana, someplace where

663
00:34:42,560 --> 00:34:45,759
Speaker 8: they haven't had a violent crime, and you know, like

664
00:34:45,800 --> 00:34:48,520
Speaker 8: in six months, where they've got cameras all over the

665
00:34:48,520 --> 00:34:51,080
Speaker 8: outside of their house and they've got a shotgun under

666
00:34:51,120 --> 00:34:53,840
Speaker 8: their bed because they're sure that at any moment a

667
00:34:53,920 --> 00:34:56,120
Speaker 8: gang of twenty five guys is going to come try

668
00:34:56,120 --> 00:34:58,160
Speaker 8: to take over their house because it's something they saw

669
00:34:58,239 --> 00:35:00,480
Speaker 8: on the news. It's like, well, you know, in like

670
00:35:00,520 --> 00:35:03,880
Speaker 8: in Portland and the Walgreens, they'll just have like twenty

671
00:35:03,920 --> 00:35:06,840
Speaker 8: five looters show up and steal everything that could happen

672
00:35:06,880 --> 00:35:10,439
Speaker 8: to me at any time here in North Dakota. Right,

673
00:35:10,680 --> 00:35:13,720
Speaker 8: It's like, and you see when you see their fear

674
00:35:13,760 --> 00:35:18,360
Speaker 8: and how irrational it is from the outside, your fear

675
00:35:18,440 --> 00:35:21,120
Speaker 8: also looks like that to someone else, Like we all

676
00:35:21,239 --> 00:35:23,680
Speaker 8: have been put into kind of a little a little box,

677
00:35:23,719 --> 00:35:24,720
Speaker 8: a little fear box.

678
00:35:25,040 --> 00:35:27,040
Speaker 5: Well, I think, like to your point, like especially about

679
00:35:27,040 --> 00:35:30,480
Speaker 5: like I think of things like reddit, right, and the

680
00:35:30,560 --> 00:35:33,720
Speaker 5: subreddit public freak Out. There's like a subreddit called public

681
00:35:33,760 --> 00:35:36,799
Speaker 5: freakout that's really popular and it's mostly a lot of

682
00:35:36,800 --> 00:35:39,040
Speaker 5: people just having some kind of like mental health crisis

683
00:35:39,120 --> 00:35:41,040
Speaker 5: or something like that, or just some wild thing that's

684
00:35:41,080 --> 00:35:43,719
Speaker 5: going on. But when you think about like when you're

685
00:35:43,800 --> 00:35:46,279
Speaker 5: like a kid, I remember being like, oh, what's the

686
00:35:46,360 --> 00:35:48,520
Speaker 5: ocean like? Or I'm trying to like, you know, draw

687
00:35:48,560 --> 00:35:51,840
Speaker 5: on experiences I have. Most of them are like media

688
00:35:51,880 --> 00:35:54,719
Speaker 5: reference to memories I have, like of a movie or

689
00:35:54,719 --> 00:35:57,279
Speaker 5: something I saw on TV that was forming even my

690
00:35:57,400 --> 00:36:00,480
Speaker 5: own concept of what something was. And now that we

691
00:36:00,560 --> 00:36:04,440
Speaker 5: have like video that's like IROL type sort of video

692
00:36:04,560 --> 00:36:07,680
Speaker 5: from cameras that sort of that ups the stakes even

693
00:36:07,719 --> 00:36:10,239
Speaker 5: more where people begin to associate Well, I did see

694
00:36:10,239 --> 00:36:12,480
Speaker 5: this one clip of this thing happening in this place

695
00:36:12,560 --> 00:36:14,840
Speaker 5: now that is exactly what is going to happen to me,

696
00:36:14,880 --> 00:36:17,960
Speaker 5: and has this effect of just ramping up these fears

697
00:36:18,440 --> 00:36:20,440
Speaker 5: and like a good like you know, an example of

698
00:36:20,480 --> 00:36:23,200
Speaker 5: this is, like you're saying, Jason, like, especially on conservative news,

699
00:36:23,200 --> 00:36:26,440
Speaker 5: the way they portray certain cities and what quote unquote

700
00:36:26,520 --> 00:36:29,520
Speaker 5: crime waves are happening. That has this effect on us

701
00:36:29,560 --> 00:36:32,399
Speaker 5: just as human beings, where the more we're put into

702
00:36:32,480 --> 00:36:36,360
Speaker 5: a fear state, the more malleable we become. And also

703
00:36:36,600 --> 00:36:39,600
Speaker 5: it we inch closer and closer to being in a

704
00:36:39,640 --> 00:36:43,799
Speaker 5: mindset or a mind state where solving things violently is

705
00:36:43,880 --> 00:36:48,080
Speaker 5: acceptable because we see just how fucked up and like

706
00:36:48,239 --> 00:36:51,319
Speaker 5: agro and violent the world is, and just looking at

707
00:36:51,360 --> 00:36:53,120
Speaker 5: all of those things feeding on each other, it's like,

708
00:36:53,200 --> 00:36:55,799
Speaker 5: at some point for me, like I realized that the

709
00:36:55,840 --> 00:36:58,080
Speaker 5: way to even break that kind of cycle was first

710
00:36:58,120 --> 00:37:00,839
Speaker 5: just to have awareness because a lot of the time,

711
00:37:00,880 --> 00:37:02,520
Speaker 5: if I am getting caught up on what I read

712
00:37:02,560 --> 00:37:06,880
Speaker 5: in the headlines, it it feeds on like, you know,

713
00:37:06,920 --> 00:37:10,000
Speaker 5: I start ruminating on things that aren't actually necessarily helpful

714
00:37:10,000 --> 00:37:12,520
Speaker 5: to me because it's also not the reality. Because we

715
00:37:12,560 --> 00:37:14,800
Speaker 5: talk about the quote unquote crime waves that were that

716
00:37:14,840 --> 00:37:16,759
Speaker 5: everyone wanted to talk about in the last year that

717
00:37:16,880 --> 00:37:21,440
Speaker 5: just didn't exist, and it's it's much easier to be like, Okay,

718
00:37:21,480 --> 00:37:23,719
Speaker 5: I know I'm seeing a lot of like over emphasis

719
00:37:23,719 --> 00:37:27,719
Speaker 5: on these like visually really like you know, uh, provocative

720
00:37:27,719 --> 00:37:30,600
Speaker 5: images and videos. But that's not actually, that's not that's

721
00:37:30,640 --> 00:37:33,680
Speaker 5: not the most accurate depiction on what on what is happening.

722
00:37:34,040 --> 00:37:39,360
Speaker 1: Yeah, And it's specifically like designed that way, specifically based

723
00:37:39,400 --> 00:37:43,719
Speaker 1: on like it's nothing is based on reality as much

724
00:37:43,719 --> 00:37:47,319
Speaker 1: as it's based on what is going to feed. Like

725
00:37:47,360 --> 00:37:49,680
Speaker 1: nobody was sitting back and being like, what we're going

726
00:37:49,680 --> 00:37:53,120
Speaker 1: to make up a crime wave? It was that people's

727
00:37:53,680 --> 00:37:57,839
Speaker 1: like that that was the story that made people have

728
00:37:58,040 --> 00:38:02,399
Speaker 1: the most scared reaction, and therefore they clicked on it,

729
00:38:02,520 --> 00:38:05,560
Speaker 1: and therefore they got more of it, and the media

730
00:38:05,880 --> 00:38:08,799
Speaker 1: you know, keeps feeding them. All Right, let's let's take

731
00:38:08,920 --> 00:38:13,120
Speaker 1: a quick break and we'll come back. We'll talk about climate,

732
00:38:13,280 --> 00:38:16,800
Speaker 1: which I think plays into this in a bunch of ways.

733
00:38:17,000 --> 00:38:20,880
Speaker 1: And also just you know, are there solutions like what

734
00:38:21,560 --> 00:38:22,640
Speaker 1: can we do?

735
00:38:23,320 --> 00:38:23,520
Speaker 7: No?

736
00:38:24,880 --> 00:38:39,160
Speaker 1: Then nothing and we're back. And so the latest Mission

737
00:38:39,160 --> 00:38:43,000
Speaker 1: Impossible dropped last night or two nights ago. It's getting

738
00:38:43,040 --> 00:38:47,640
Speaker 1: great reviews. It does indeed seem to be about Ethan

739
00:38:47,760 --> 00:38:52,240
Speaker 1: Hunt battling a self aware AI program known as the Entity,

740
00:38:52,960 --> 00:38:57,000
Speaker 1: which I don't know this like he might as well

741
00:38:57,440 --> 00:39:03,759
Speaker 1: from my perspective, like that is as dramatically impactful as

742
00:39:03,880 --> 00:39:07,720
Speaker 1: like he's battling a wizard this time. It's just like, Okay,

743
00:39:07,960 --> 00:39:12,759
Speaker 1: well that doesn't really make sense to me or like

744
00:39:12,920 --> 00:39:15,279
Speaker 1: does It's not like really a thing, and that does.

745
00:39:15,360 --> 00:39:17,439
Speaker 1: When people are critical of the movie, they seem to say,

746
00:39:17,480 --> 00:39:19,960
Speaker 1: like all the stuff about AI kind of drags a

747
00:39:19,960 --> 00:39:26,440
Speaker 1: little bit, but and visually it is depicted as basically

748
00:39:26,480 --> 00:39:29,920
Speaker 1: an evil screensaver from nineteen ninety nine, like it's just

749
00:39:30,680 --> 00:39:35,520
Speaker 1: the black circle with with like white dots of light.

750
00:39:36,000 --> 00:39:40,400
Speaker 1: Three hundred million dollar movie, by the way, but it can. So.

751
00:39:40,440 --> 00:39:44,200
Speaker 1: The main claim that the movie makes about this AI,

752
00:39:44,520 --> 00:39:47,960
Speaker 1: and I guess AI in general, is that the program

753
00:39:48,040 --> 00:39:52,319
Speaker 1: can also see the future, like very specifically through its

754
00:39:52,360 --> 00:39:56,520
Speaker 1: predictive technology. And that's like based on what we're seeing

755
00:39:56,760 --> 00:40:01,880
Speaker 1: in news headlines like the you know, deep learning teaching

756
00:40:01,920 --> 00:40:04,960
Speaker 1: computers to predict the future is like a headline I

757
00:40:04,960 --> 00:40:08,440
Speaker 1: feel like I've seen a hundred times spooky Artificial intelligence

758
00:40:08,480 --> 00:40:10,880
Speaker 1: can accurately predict the future, and it's about to be

759
00:40:10,960 --> 00:40:14,880
Speaker 1: asked more questions. AI can now predict crime before it

760
00:40:14,960 --> 00:40:17,680
Speaker 1: happens as well, we'll get into in a moment.

761
00:40:18,080 --> 00:40:21,879
Speaker 6: And you mean like that movie Minority Report. Also, yeah,

762
00:40:22,120 --> 00:40:26,160
Speaker 6: Tom Cruise Cruise, Yeah, he's he. I feel like his

763
00:40:26,320 --> 00:40:30,440
Speaker 6: sense of reality is probably more blurred by the movies

764
00:40:30,480 --> 00:40:32,879
Speaker 6: he's in than any other movie star.

765
00:40:33,760 --> 00:40:34,959
Speaker 4: Well, yeah, because he has.

766
00:40:34,840 --> 00:40:38,319
Speaker 7: An entire organization blurring his reality. Yeah, before he hits

767
00:40:38,360 --> 00:40:41,439
Speaker 7: set and then you're in that magical landscape where he's

768
00:40:41,440 --> 00:40:44,560
Speaker 7: made himself king. Yeah. I mean that that guy's not

769
00:40:44,560 --> 00:40:45,479
Speaker 7: living on planet Earth.

770
00:40:45,680 --> 00:40:46,480
Speaker 3: He doesn't need too.

771
00:40:47,160 --> 00:40:50,719
Speaker 1: Yeah. The this movie actually was like written, it was

772
00:40:50,760 --> 00:40:53,560
Speaker 1: supposed to come out like years ago, but the production

773
00:40:53,920 --> 00:40:58,480
Speaker 1: famously shut down due to the coronavirus outbreak, which, according

774
00:40:58,520 --> 00:41:01,120
Speaker 1: to reports in February twenty two, when he was putting

775
00:41:01,120 --> 00:41:05,960
Speaker 1: a real damper on offshore location shoots. Wow, gave us

776
00:41:06,000 --> 00:41:09,120
Speaker 1: the Tom Cruise thing where it was clear that he

777
00:41:09,160 --> 00:41:13,239
Speaker 1: thought he was the last barrier between like the end

778
00:41:13,280 --> 00:41:17,040
Speaker 1: of the world and you know, coronavirus just like killing

779
00:41:17,080 --> 00:41:20,359
Speaker 1: everyone where he was like shouting at everyone. But first

780
00:41:20,360 --> 00:41:23,040
Speaker 1: of all, I just want to say too, Ai, speaking

781
00:41:23,320 --> 00:41:26,200
Speaker 1: of I'd like to issue a big where were you

782
00:41:26,280 --> 00:41:28,880
Speaker 1: on that one? Dipshit to the AI on predicting the

783
00:41:28,920 --> 00:41:33,160
Speaker 1: global pandemic, Like you couldn't We couldn't see that one coming.

784
00:41:33,239 --> 00:41:36,200
Speaker 1: A lot of people saw it coming, people mere people

785
00:41:36,440 --> 00:41:40,640
Speaker 1: saw it coming. But yeah, the whole predicting the future

786
00:41:40,680 --> 00:41:46,239
Speaker 1: thing seems to be vastly overstated. Like there's a so

787
00:41:46,320 --> 00:41:49,680
Speaker 1: the MI T researchers who had created a computer that

788
00:41:49,760 --> 00:41:50,800
Speaker 1: could supposedly lose.

789
00:41:51,160 --> 00:41:56,680
Speaker 6: Mission Impossible Technology Mission Impossible Technology am I technology.

790
00:41:57,120 --> 00:42:03,120
Speaker 1: Yes, yeah, they are loosely associated. But it was basically

791
00:42:03,200 --> 00:42:06,600
Speaker 1: like they were predicting. They would show the computer a

792
00:42:06,640 --> 00:42:12,040
Speaker 1: picture and then the computer would predict, like what would

793
00:42:12,120 --> 00:42:15,360
Speaker 1: happen for the next one point five seconds in that picture?

794
00:42:16,200 --> 00:42:19,400
Speaker 1: And like that it was like someone walking across the

795
00:42:19,400 --> 00:42:21,640
Speaker 1: golf course and they were like, that thing's about to

796
00:42:21,719 --> 00:42:25,400
Speaker 1: keep walking across that golf course. They were like, holy shit,

797
00:42:25,680 --> 00:42:30,560
Speaker 1: you guys. Or like one was a wave crashing, they

798
00:42:30,560 --> 00:42:34,640
Speaker 1: were like, I think it's gonna keep crashing. Call me crazy,

799
00:42:35,239 --> 00:42:39,480
Speaker 1: and they were like, fucking a, do you think it's brilliant?

800
00:42:39,800 --> 00:42:46,800
Speaker 1: Thing's magical and yeah, and then like MIT Mission Possible

801
00:42:46,800 --> 00:42:49,840
Speaker 1: Technology also developed an algorithm that could predict how people

802
00:42:49,880 --> 00:42:52,520
Speaker 1: will greet each other and got a lot of cool

803
00:42:52,520 --> 00:42:55,560
Speaker 1: headlines for that. It was trained on YouTube videos and

804
00:42:55,600 --> 00:42:59,680
Speaker 1: reruns of the Office and Desperate Housewives. Amazing, and it

805
00:42:59,800 --> 00:43:03,399
Speaker 1: was only right just over forty three percent of the time.

806
00:43:03,920 --> 00:43:06,200
Speaker 7: We never greet each other like we do ones for Housewives.

807
00:43:06,280 --> 00:43:08,319
Speaker 7: I wish we did, but like, I can't just walk

808
00:43:08,400 --> 00:43:10,160
Speaker 7: up to my enemy and slap them across the face.

809
00:43:10,200 --> 00:43:13,880
Speaker 1: It's not reality, I know, and that sucks. And hopefully

810
00:43:13,880 --> 00:43:17,680
Speaker 1: we'll get to that world soon. That's my future that

811
00:43:17,719 --> 00:43:21,320
Speaker 1: I'm hopeful for. But so one second away from the greeting,

812
00:43:21,360 --> 00:43:23,439
Speaker 1: they could only predict it forty three percent at a time.

813
00:43:23,760 --> 00:43:27,520
Speaker 1: So this is what I'm always wondering, Like, what how

814
00:43:27,560 --> 00:43:31,120
Speaker 1: does that compare to humans? Humans making the same prediction

815
00:43:31,440 --> 00:43:34,960
Speaker 1: were right seventy one percent of the time. Oh so

816
00:43:36,160 --> 00:43:39,439
Speaker 1: much better than this AI that everyone did. You guys

817
00:43:39,440 --> 00:43:42,280
Speaker 1: ever see the sixty minutes where they like this sixty

818
00:43:42,280 --> 00:43:44,560
Speaker 1: minutes about AI. I think it came out like back

819
00:43:44,600 --> 00:43:49,719
Speaker 1: in March or April, and like Scott, I think it's

820
00:43:49,800 --> 00:43:53,000
Speaker 1: Scott Pelly, like one of the old journalists on sixty minutes,

821
00:43:53,120 --> 00:43:56,640
Speaker 1: is just like okay, like write a speech for me

822
00:43:56,760 --> 00:44:00,000
Speaker 1: about this, and then he seems to be blown away,

823
00:44:00,200 --> 00:44:03,600
Speaker 1: like the amount of text it produces, like he's like

824
00:44:03,680 --> 00:44:07,719
Speaker 1: that just rolled a whole speech in four seconds, Like

825
00:44:08,200 --> 00:44:13,480
Speaker 1: he's it's like he's never seen a computer before. But

826
00:44:14,520 --> 00:44:17,960
Speaker 1: I do think we're at a weird place where people

827
00:44:18,040 --> 00:44:21,719
Speaker 1: will you can just be like magic AI is bad

828
00:44:21,760 --> 00:44:25,520
Speaker 1: guy in movie, and everyone's like, yep, that makes sense,

829
00:44:25,760 --> 00:44:28,480
Speaker 1: because like we we should be afraid of AI, but

830
00:44:28,600 --> 00:44:32,160
Speaker 1: people don't really know why necessarily we should be, and

831
00:44:32,239 --> 00:44:35,799
Speaker 1: so we just you know, like it's the same thing

832
00:44:35,840 --> 00:44:39,520
Speaker 1: that happens with all our conspiracy theories, and you know,

833
00:44:39,680 --> 00:44:42,319
Speaker 1: we should be scared about the pandemic, we should be

834
00:44:42,560 --> 00:44:46,040
Speaker 1: scared about the government's response to the pandemic, but people

835
00:44:46,239 --> 00:44:50,000
Speaker 1: create like vast conspiracy theories just to make sure they're

836
00:44:50,040 --> 00:44:54,160
Speaker 1: like scared about it for nonsensical reasons. It's like we

837
00:44:54,560 --> 00:44:57,839
Speaker 1: need that like cognitive dissonance transference happening, and I feel

838
00:44:57,840 --> 00:45:00,520
Speaker 1: like we're starting to see that with AI, Like AI

839
00:45:00,640 --> 00:45:02,839
Speaker 1: is going to be magic and tell us everything that

840
00:45:02,880 --> 00:45:05,000
Speaker 1: could happen to us for the rest of our lives.

841
00:45:05,160 --> 00:45:10,920
Speaker 1: And that's that's not the scary thing about AI.

842
00:45:10,280 --> 00:45:14,680
Speaker 6: Right, The scary thing is like Skynet. And that's the thing.

843
00:45:14,719 --> 00:45:19,160
Speaker 6: Like movies have been having AI as the villain for

844
00:45:19,239 --> 00:45:23,640
Speaker 6: like decades now, and I feel like I don't know

845
00:45:23,680 --> 00:45:27,080
Speaker 6: what my point is gonna be. But remember Terminator one.

846
00:45:27,640 --> 00:45:30,719
Speaker 6: I remember the Matrix from nineteen ninety nine, over twenty

847
00:45:30,840 --> 00:45:34,520
Speaker 6: years ago. Like, I just think it's funny that AI,

848
00:45:34,719 --> 00:45:41,160
Speaker 6: I guess, hasn't evolved very much in movies. Yeah, I

849
00:45:41,160 --> 00:45:44,200
Speaker 6: don't know, No, I mean for real, like we've been

850
00:45:44,239 --> 00:45:45,400
Speaker 6: knowing tho is what I'm saying.

851
00:45:45,960 --> 00:45:50,520
Speaker 7: Yeah, And I think it's interesting. You know, movies, by

852
00:45:50,560 --> 00:45:54,080
Speaker 7: their very nature have to heighten and dramatize in order

853
00:45:54,200 --> 00:45:57,680
Speaker 7: to effectively bring home their messages, particularly if we're looking

854
00:45:57,719 --> 00:46:02,960
Speaker 7: at genre films, and the AI has always been like,

855
00:46:03,520 --> 00:46:06,200
Speaker 7: you know, turns into a cop and now it's hunting you,

856
00:46:06,520 --> 00:46:11,440
Speaker 7: or you know, it takes away your freedom of choice.

857
00:46:11,719 --> 00:46:16,520
Speaker 7: You know, if we look at the matrix, Yes, what's

858
00:46:16,520 --> 00:46:20,839
Speaker 7: the other one that report a minority report, Like they're

859
00:46:21,480 --> 00:46:23,280
Speaker 7: saying that crime.

860
00:46:23,320 --> 00:46:25,399
Speaker 1: And it's said in the future. It's like a sci

861
00:46:25,440 --> 00:46:30,200
Speaker 1: fi movie where sorry, mission impossible is supposed to be.

862
00:46:30,680 --> 00:46:33,440
Speaker 1: Like even though they can take masks off that make

863
00:46:33,480 --> 00:46:37,040
Speaker 1: them look exactly like the other person like you wouldn't

864
00:46:37,200 --> 00:46:42,160
Speaker 1: see Tom Cruise fighting robots necessarily, or like, no, you

865
00:46:42,200 --> 00:46:46,960
Speaker 1: know that that feels like it's a step into this

866
00:46:47,120 --> 00:46:48,720
Speaker 1: is ship that can actually happen.

867
00:46:49,360 --> 00:46:53,279
Speaker 7: Yeah, yeah, and I appreciate the grounding. I think we

868
00:46:53,600 --> 00:46:57,080
Speaker 7: got there because it's so much more tactile in this moment.

869
00:46:57,200 --> 00:47:00,960
Speaker 7: I think between if you think about your grocery store

870
00:47:00,960 --> 00:47:04,560
Speaker 7: workers who have been concerned about self checkout for like

871
00:47:04,680 --> 00:47:07,279
Speaker 7: over a decade, a lot of those stories are unionized

872
00:47:07,320 --> 00:47:11,160
Speaker 7: and have actively been like, hey, you're taking jobs from

873
00:47:11,280 --> 00:47:14,719
Speaker 7: like checkout counter people, some of whom are elderly, and

874
00:47:14,800 --> 00:47:16,640
Speaker 7: this is like the last place they can work and

875
00:47:16,680 --> 00:47:21,239
Speaker 7: make money consistently. To the writers and actors who may

876
00:47:21,480 --> 00:47:24,160
Speaker 7: be on strike by the time this comes out, and

877
00:47:24,280 --> 00:47:30,120
Speaker 7: there feared that not only could AIBS to take their job,

878
00:47:30,200 --> 00:47:33,800
Speaker 7: but I mean for performers, can my face be doing

879
00:47:33,880 --> 00:47:37,960
Speaker 7: things long, long, long after I'm dead and what will

880
00:47:38,000 --> 00:47:42,800
Speaker 7: that look like? I think, as we're sort of confronting

881
00:47:42,800 --> 00:47:47,160
Speaker 7: these things, AI is a really freaking dope tool. I'm

882
00:47:47,200 --> 00:47:50,239
Speaker 7: so much more concerned about these executives who are like,

883
00:47:50,600 --> 00:47:52,719
Speaker 7: oh great, now I don't have to pay people. Did

884
00:47:52,760 --> 00:47:54,760
Speaker 7: you guys see the on nine article that was written

885
00:47:54,760 --> 00:47:57,080
Speaker 7: by AI. They came out a couple days ago. They

886
00:47:57,120 --> 00:47:58,880
Speaker 7: have Internet in a tangle.

887
00:47:59,320 --> 00:48:04,759
Speaker 1: Yeah, this is like I've ever since I've been you know,

888
00:48:05,360 --> 00:48:09,080
Speaker 1: working on the Internet, creating trying to create like unique

889
00:48:09,360 --> 00:48:13,200
Speaker 1: interesting content. There's also been this push to just flood

890
00:48:13,239 --> 00:48:17,399
Speaker 1: the zone with shit. To quote Steve Bannon, like we

891
00:48:17,400 --> 00:48:20,200
Speaker 1: we used to like crack cracked zoned by a company

892
00:48:20,200 --> 00:48:25,160
Speaker 1: that was like also just destroying Google's search results with

893
00:48:25,440 --> 00:48:29,640
Speaker 1: just like fake articles like answers to questions and stuff.

894
00:48:29,640 --> 00:48:31,279
Speaker 1: And they were like trying to get us to like

895
00:48:31,840 --> 00:48:34,360
Speaker 1: do that. Just like there was like scale, how do

896
00:48:34,400 --> 00:48:37,879
Speaker 1: we scale? And like that's been you know that that

897
00:48:38,000 --> 00:48:43,160
Speaker 1: intersection of tech and media has always been scary because

898
00:48:43,239 --> 00:48:46,719
Speaker 1: it's very easy for them to just create ninety nine

899
00:48:46,760 --> 00:48:52,160
Speaker 1: million articles using technology now that like yeah, pass like

900
00:48:52,520 --> 00:48:54,560
Speaker 1: a little bit like you have to like read a

901
00:48:54,600 --> 00:48:57,600
Speaker 1: paragraph to be like wait this this wasn't written by

902
00:48:57,600 --> 00:48:58,759
Speaker 1: a human, wasn't. Yeah.

903
00:48:58,960 --> 00:49:03,200
Speaker 7: So article was like ranking the Star Wars movies in

904
00:49:03,320 --> 00:49:07,279
Speaker 7: like chronological order, I think, yeah, And they got the

905
00:49:07,600 --> 00:49:10,440
Speaker 7: dates wrong on many of them. Sometimes they weren't even

906
00:49:10,440 --> 00:49:14,800
Speaker 7: listed in chronological order. The way they were dated. The

907
00:49:14,840 --> 00:49:18,200
Speaker 7: information in individual movies was in corect. It was just

908
00:49:18,920 --> 00:49:22,960
Speaker 7: error filled, like no logical saying editor would have been

909
00:49:23,000 --> 00:49:26,520
Speaker 7: like and publish. And what's crazy is I don't know

910
00:49:26,600 --> 00:49:29,759
Speaker 7: his entire union that's actively been like, hey, we do

911
00:49:29,800 --> 00:49:31,879
Speaker 7: not want this. It does not make sense to ask

912
00:49:32,080 --> 00:49:36,080
Speaker 7: an AI program that cannot consistently write fact checked articles

913
00:49:36,600 --> 00:49:40,120
Speaker 7: to be publishing these and then asking somebody an editor

914
00:49:40,160 --> 00:49:44,200
Speaker 7: to like go through and essentially rewrite this incorrect work

915
00:49:44,239 --> 00:49:47,799
Speaker 7: that isn't benefiting anyone, because who needs this list? We

916
00:49:47,920 --> 00:49:50,640
Speaker 7: have twenty seven thousand of this very specific Well, this

917
00:49:50,760 --> 00:49:53,879
Speaker 7: is dumb uh and it's wild that, you know. I'm

918
00:49:53,920 --> 00:49:58,640
Speaker 7: glad the Internet roasted the editor in chief pretty intently.

919
00:49:58,680 --> 00:50:00,960
Speaker 7: I'm really hoping that brings them back to the table

920
00:50:01,040 --> 00:50:03,960
Speaker 7: and there can be working discussions about how this company

921
00:50:04,000 --> 00:50:06,440
Speaker 7: decides to use AI and the future. But it's that

922
00:50:06,520 --> 00:50:09,239
Speaker 7: kind of stupid shit that's like really draining, I think

923
00:50:09,239 --> 00:50:11,760
Speaker 7: on workers across job titles.

924
00:50:11,840 --> 00:50:12,880
Speaker 4: It's just like, what are.

925
00:50:12,719 --> 00:50:15,080
Speaker 7: We what are you trying? You just want to force

926
00:50:15,120 --> 00:50:17,680
Speaker 7: people out of work and that's not a logical thing

927
00:50:17,719 --> 00:50:19,560
Speaker 7: for you to do to yourself.

928
00:50:19,960 --> 00:50:21,520
Speaker 4: You mean the product money.

929
00:50:21,320 --> 00:50:24,600
Speaker 1: Yeah, to your point, the product sucks, like the product

930
00:50:24,719 --> 00:50:27,080
Speaker 1: like the AI as bad as it's bad at its

931
00:50:27,080 --> 00:50:30,279
Speaker 1: fucking job, like with regards to like the self checkout thing,

932
00:50:30,680 --> 00:50:34,200
Speaker 1: that the AI like can't stop people from stealing stuff,

933
00:50:34,239 --> 00:50:36,440
Speaker 1: and so the companies are like losing massive amounts of

934
00:50:36,440 --> 00:50:39,839
Speaker 1: money on theft, and then in order to combat that,

935
00:50:39,840 --> 00:50:43,080
Speaker 1: they're just like making claims that like everyone's shoplifting when

936
00:50:43,120 --> 00:50:46,400
Speaker 1: it's just like no, like you just put a like

937
00:50:47,600 --> 00:50:51,719
Speaker 1: inadequate program like as the thing in charge of like

938
00:50:51,760 --> 00:50:55,319
Speaker 1: making sure people can't steal stuff or like that they

939
00:50:55,320 --> 00:50:57,840
Speaker 1: don't want to steal stuff, and it's just not going

940
00:50:57,880 --> 00:50:59,760
Speaker 1: to it's not going to work.

941
00:51:00,320 --> 00:51:03,000
Speaker 7: But they made it way too easy because when I

942
00:51:03,040 --> 00:51:04,840
Speaker 7: was in college, we would for sure bring up like

943
00:51:04,880 --> 00:51:08,080
Speaker 7: a full roast chicken as like some griefs man, we're

944
00:51:08,120 --> 00:51:13,040
Speaker 7: good stop no uh, And there's personators is the possible

945
00:51:13,080 --> 00:51:14,760
Speaker 7: way you could get like that used to be somebody's

946
00:51:14,880 --> 00:51:17,320
Speaker 7: job to scan and bag your stuff. There's no possible

947
00:51:17,360 --> 00:51:19,160
Speaker 7: way to get around. So that's what I'm saying though,

948
00:51:19,200 --> 00:51:21,640
Speaker 7: like none of these things are thought out. They just

949
00:51:21,680 --> 00:51:24,640
Speaker 7: see a way to potentially preserve money without looking at

950
00:51:24,680 --> 00:51:25,840
Speaker 7: the long term.

951
00:51:25,640 --> 00:51:28,200
Speaker 6: Costs, and then they still have to hire someone to

952
00:51:28,320 --> 00:51:33,359
Speaker 6: monitor the self checkout area, so it's like, well, how

953
00:51:33,440 --> 00:51:37,080
Speaker 6: much money are you actually saving, mister grocery.

954
00:51:37,239 --> 00:51:40,759
Speaker 1: Yeah, big Grocery, which are now owned by just like

955
00:51:40,800 --> 00:51:43,920
Speaker 1: two companies in all of America. But yeah, like so

956
00:51:44,280 --> 00:51:49,520
Speaker 1: they've also been using it in like predictive crime fighting technology.

957
00:51:49,640 --> 00:51:52,440
Speaker 1: But of course, first of all, the data that it's

958
00:51:52,480 --> 00:51:57,160
Speaker 1: being fed is from police data, so it's you know,

959
00:51:57,640 --> 00:52:02,320
Speaker 1: using the it's not predicting. It's predicting like where police

960
00:52:02,480 --> 00:52:06,520
Speaker 1: are spending their time is essentially which is in low

961
00:52:06,560 --> 00:52:11,319
Speaker 1: income and you know, non white neighborhoods, And it's just

962
00:52:11,640 --> 00:52:17,480
Speaker 1: complete bullshit. There's one great anecdote where Chicago's predictive policing software,

963
00:52:17,520 --> 00:52:20,359
Speaker 1: created by the Illinois Institute of Technology, compiled a list

964
00:52:20,400 --> 00:52:22,720
Speaker 1: of people most likely to be involved in a violent

965
00:52:22,800 --> 00:52:26,960
Speaker 1: crime and they're, oh, no, a AI, baby, check out

966
00:52:26,960 --> 00:52:30,520
Speaker 1: this because it was generated by AI, you can trust this.

967
00:52:30,880 --> 00:52:33,719
Speaker 1: And then an investigation later found that the software is

968
00:52:33,760 --> 00:52:37,880
Speaker 1: list of future criminals included every single person arrested or

969
00:52:37,960 --> 00:52:42,560
Speaker 1: fingerprinted in Chicago since twenty thirteen. WHOA, So it was

970
00:52:42,680 --> 00:52:46,560
Speaker 1: just like copying off of another like data size A

971
00:52:46,800 --> 00:52:47,480
Speaker 1: I can do.

972
00:52:47,480 --> 00:52:52,160
Speaker 7: Is it can gather and redistribute information using keywords that

973
00:52:52,920 --> 00:52:57,239
Speaker 7: the person using it inputs, which means it's logically going

974
00:52:57,280 --> 00:52:59,719
Speaker 7: to be flawed because it's not understanding the words, it's

975
00:52:59,760 --> 00:53:02,080
Speaker 7: just organizing them in a way that it thinks make

976
00:53:02,160 --> 00:53:06,800
Speaker 7: sense to you. It's on a thinking machine. Yeah, the

977
00:53:06,880 --> 00:53:09,400
Speaker 7: technology is not there yet, and people are way too

978
00:53:09,480 --> 00:53:12,040
Speaker 7: eager to jump into it and in a way that

979
00:53:12,080 --> 00:53:15,080
Speaker 7: would almost assuredly collapse society, which is why it's insane

980
00:53:15,120 --> 00:53:17,239
Speaker 7: to me that we're still having to like explain this

981
00:53:17,320 --> 00:53:20,120
Speaker 7: to people to be like they're like, did you see

982
00:53:20,120 --> 00:53:23,480
Speaker 7: the article from was it the Hollywood Reporter that came

983
00:53:23,520 --> 00:53:26,279
Speaker 7: out about the executives and how they're choosing to fight

984
00:53:26,320 --> 00:53:26,840
Speaker 7: the unions.

985
00:53:27,200 --> 00:53:28,880
Speaker 1: Yeah, by just waiting them out.

986
00:53:29,239 --> 00:53:33,520
Speaker 7: Yeah, essentially, And the key part that's resonated with me

987
00:53:33,680 --> 00:53:36,040
Speaker 7: was like, this is a necessary evil.

988
00:53:36,680 --> 00:53:36,919
Speaker 1: Yeah.

989
00:53:37,000 --> 00:53:39,360
Speaker 7: It was the verbatim words from this quote story. So

990
00:53:39,440 --> 00:53:42,200
Speaker 7: we're pretty sure this is a scare tactic to get

991
00:53:42,239 --> 00:53:46,160
Speaker 7: sagged to not strike and them saying, hey, we'll wade out.

992
00:53:46,200 --> 00:53:48,520
Speaker 7: The writers will wait out the actors as well. But

993
00:53:49,040 --> 00:53:52,000
Speaker 7: I think what's really happened is they fired up the

994
00:53:52,040 --> 00:53:55,920
Speaker 7: base of unions to be like, excuse me, a necessary

995
00:53:56,040 --> 00:54:00,360
Speaker 7: evil is not destroying the beautiful industry can be that

996
00:54:00,400 --> 00:54:04,040
Speaker 7: people have tried to create here for literally over a century.

997
00:54:04,480 --> 00:54:07,520
Speaker 7: It's nonsensical. I just I can't understand the end game

998
00:54:08,040 --> 00:54:10,960
Speaker 7: other than I guess forty people will be a little

999
00:54:11,000 --> 00:54:11,719
Speaker 7: bit wealthier.

1000
00:54:12,239 --> 00:54:14,439
Speaker 1: Yeah, that's all it is. Yeah, I don't think it's

1001
00:54:14,440 --> 00:54:17,120
Speaker 1: going to cause society to collapse. It'll just accelerate the

1002
00:54:17,160 --> 00:54:21,320
Speaker 1: thing that's already happening, which is just like grotesque inequality

1003
00:54:21,480 --> 00:54:24,960
Speaker 1: like gets worse and like they're able to hire fewer

1004
00:54:25,000 --> 00:54:29,600
Speaker 1: people to do jobs. And also the other thing that

1005
00:54:29,600 --> 00:54:32,040
Speaker 1: that seems to be happening is like the quality of

1006
00:54:32,120 --> 00:54:36,760
Speaker 1: everything is getting worse, and like that's going to keep happening,

1007
00:54:36,920 --> 00:54:39,040
Speaker 1: you know, like TV shows, movies.

1008
00:54:38,800 --> 00:54:42,719
Speaker 7: Or But to my point, isn't that like if we

1009
00:54:42,760 --> 00:54:45,880
Speaker 7: can track revolutions based off the price of bread, right, Like,

1010
00:54:45,920 --> 00:54:48,200
Speaker 7: so when people can no longer afford bread, that's when

1011
00:54:48,239 --> 00:54:50,440
Speaker 7: they riot in the streets and take out leaders and

1012
00:54:50,520 --> 00:54:54,120
Speaker 7: get very serious about their actions because everybody's base staple

1013
00:54:54,160 --> 00:54:59,280
Speaker 7: for survival. Then we have a fairly largely the entertainment

1014
00:54:59,280 --> 00:55:01,560
Speaker 7: community is huge, which I know some people think this

1015
00:55:01,640 --> 00:55:04,720
Speaker 7: is like a very small or elite space, but it's ginormous,

1016
00:55:04,760 --> 00:55:06,600
Speaker 7: and most of the people working in it are like

1017
00:55:06,760 --> 00:55:08,160
Speaker 7: working class people.

1018
00:55:08,560 --> 00:55:09,239
Speaker 1: And so if you.

1019
00:55:09,239 --> 00:55:12,959
Speaker 7: Eliminate everyone who I mean, because essentially, what when AI

1020
00:55:13,080 --> 00:55:17,719
Speaker 7: gets good enough, when it's actually usable, it will eliminate

1021
00:55:17,760 --> 00:55:22,440
Speaker 7: everybody who is of average talent. Right. What you do

1022
00:55:22,560 --> 00:55:25,800
Speaker 7: is you write pretty cute Hallmark stories and you're pretty

1023
00:55:25,800 --> 00:55:29,000
Speaker 7: good at that, and they're successful enough to get commercials

1024
00:55:29,000 --> 00:55:31,480
Speaker 7: into air frequently. Think you can probably buy a house,

1025
00:55:31,520 --> 00:55:33,080
Speaker 7: and you can fut your kids and send them to college,

1026
00:55:33,080 --> 00:55:35,439
Speaker 7: and you can have a very comfortable life. If AI

1027
00:55:35,560 --> 00:55:38,920
Speaker 7: can do that job, then you're wiping out hundreds of

1028
00:55:38,920 --> 00:55:41,600
Speaker 7: thousands of jobs, and that is really really bad news

1029
00:55:41,600 --> 00:55:45,360
Speaker 7: for like Los Angeles, the county. I just to me,

1030
00:55:45,560 --> 00:55:47,759
Speaker 7: I know, it's like a small first step, but to me,

1031
00:55:47,880 --> 00:55:53,640
Speaker 7: like the dominoes seem large and looming absolutely like probable,

1032
00:55:53,840 --> 00:55:57,479
Speaker 7: like if things are not stopped immediately. And I really

1033
00:55:57,480 --> 00:56:00,480
Speaker 7: think that that's the takeaway from the WGA strike in

1034
00:56:00,680 --> 00:56:04,279
Speaker 7: and I really do hope SAG joints because it's not

1035
00:56:04,320 --> 00:56:06,040
Speaker 7: just going to stop at the entertainment industry. It's going

1036
00:56:06,120 --> 00:56:07,880
Speaker 7: to continue to all out to it, like we are

1037
00:56:08,400 --> 00:56:11,520
Speaker 7: one American workforce and we're all about to be impacted

1038
00:56:11,520 --> 00:56:11,920
Speaker 7: by this ship.

1039
00:56:11,960 --> 00:56:15,600
Speaker 1: It's great, all right, that's gonna do it. For this

1040
00:56:15,760 --> 00:56:20,560
Speaker 1: week's weekly Zeitgeist, Please like and review the show if

1041
00:56:20,600 --> 00:56:24,759
Speaker 1: you like, the show means the world to Miles. He

1042
00:56:24,960 --> 00:56:28,880
Speaker 1: needs your validation, folks. I hope you're having a great

1043
00:56:28,920 --> 00:57:12,520
Speaker 1: weekend and I will talk to him Monday. By spe