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

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

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Speaker 1: from this week, all edited together into one NonStop infotainment

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Speaker 1: laugh stravaganza. Uh yeah, So, without further ado, here is

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Speaker 1: the Weekly Zeitgeist. It in the brilliant and hilarious nick

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Speaker 1: that ray. You all came in with the song should

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Speaker 1: I have a song? I mean, might as well you

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Speaker 1: post your score in the air like you just don't care.

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Speaker 1: Come mon, tell me watch the word A word? All? Hey,

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Speaker 1: there it did? Uh wait, what happened with a word? All?

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Speaker 1: While I was gone, I heard this did switch on?

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Speaker 1: What happened? Somebody's got switched ownership? I lost one of

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Speaker 1: my two one of the times that I got to

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Speaker 1: got it in two guesses off of my record. Absolute bullshit.

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Speaker 1: I don't know how it happened, But it's really kind

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Speaker 1: of the main thing that people are talking about, is

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Speaker 1: that indignity that I faced. Yeah, that's kind of the

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Speaker 1: main news that you missed, Miles. It's what t DZ

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Speaker 1: has been about for the past couple of weeks. They're

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Speaker 1: doing quadrill Now, what's that quard? That's bad for me?

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Speaker 1: That's because they not only not only is it for

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Speaker 1: like you're you're playing wordle on four grids and like that.

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Speaker 1: That adds a complexity and makes it a little bit

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Speaker 1: more difficult. But then you also have like practice games

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Speaker 1: that you can just like go and play like so

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Speaker 1: you can just play it all day. It's yeah, I

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Speaker 1: the it is the one a day is sort of good. Yes,

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Speaker 1: the one day of it all? Yeah, quartal seems life ruining.

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Speaker 1: I'm gonna try to yeah, irresponsible, down right and irresponsible.

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Speaker 1: I will not allow it. Nick, are you you play

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Speaker 1: word I I do. I like to call it words

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Speaker 1: without friends. I think that you know, a lot of

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Speaker 1: these people will post their scores on the internet, and

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Speaker 1: I think that's a little too much. What I do

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Speaker 1: is I I go out and I etched my scores

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Speaker 1: into the dirt caked faces of the forgotten. That's what

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Speaker 1: I do. Yes, if I'm gonna be obnoxious about it,

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Speaker 1: I'm going full throttle much more curse it and uh

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Speaker 1: hunting way to share your uh yeah yeah, no, I

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Speaker 1: share every time I get it, get it in two

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Speaker 1: guesses an act like That's just what I do every time,

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Speaker 1: and usually like with a cocky gift or something like

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Speaker 1: the Jude rolling a strike and saying, who do you

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Speaker 1: think you are? I am like that, it's obnoxious. It's

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Speaker 1: the one place where I have cultivated my image to

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Speaker 1: be the most obnoxious piece of ship that I can imagine.

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Speaker 1: Why are people posting it in five or People are

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Speaker 1: like I, I'm not that good at it and I'm

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Speaker 1: telling everybody about it. I don't know, man, people people

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Speaker 1: have their own strap, their own posting needs. I get

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Speaker 1: all funked up in their own kind of way. I

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Speaker 1: don't know, but it's not for us to trying to

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Speaker 1: figure out. I'm not a psycho exactly, you know. I

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Speaker 1: just let them make me look good. That's what I'm

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Speaker 1: That's what I'm the only post If I don't get it,

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Speaker 1: there you go. I've definitely seen that, all right, Nick,

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Speaker 1: and that we're we're gonna stop that. I know people

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Speaker 1: like word all has to be so annoying to people

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Speaker 1: who just like aren't into it, don't give a shit

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Speaker 1: about it, and I love hearing about it. Yeah, that's

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Speaker 1: very convincing. What is something from your search history? This

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Speaker 1: is kind of embarrassing, but I was looking at the

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Speaker 1: last thing just now that I searched and it was

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Speaker 1: best glue for wine corks. I've been collecting thousands of

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Speaker 1: wine corks from friends and family for years, and I'm

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Speaker 1: trying to make a big mosaic out of them. I

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Speaker 1: like to do a lot of big paintings, and my

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Speaker 1: sort of doing art is one of the ways I

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Speaker 1: cope with the really painful and difficult work that we

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Speaker 1: do around the country with with people who are confined

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Speaker 1: in jail cells all over the country, and the work

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Speaker 1: can be really difficult and stressful, and one of the

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Speaker 1: ways I just personally cope is making art. And I

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Speaker 1: now have been asking everyone I know to collect wine

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Speaker 1: corks for me, and I have thousands and thousands of them,

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Speaker 1: but I have no idea how to actually make them

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Speaker 1: into anything. So I was trying to figure out how

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Speaker 1: to actually glue them together. What do you think? What

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Speaker 1: do you mean? What are we talking? You're like you

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Speaker 1: would paint each one and sort of mosaic get out,

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Speaker 1: or you're trying to use the natural graphics on the

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Speaker 1: cork to inform how you get your image, or would

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Speaker 1: you know walk walk me through this process. I've been painting.

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Speaker 1: I paint each one and make them into sort of

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Speaker 1: a colorful mosaic, usually depicting like some poem that I

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Speaker 1: like or so um aspect of the work that we do.

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Speaker 1: So yeah, it's maybe not the best use of my time,

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Speaker 1: but I think the consensus seems to be a glue gun. Okay, okay,

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Speaker 1: all right, there we go, glue gun when doubt it

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Speaker 1: does feel like the glue gun is always is always

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Speaker 1: a good option. Like, is there anything that a glue

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Speaker 1: gun does not glue like, does not work on? Is

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Speaker 1: my question? I mean, something that you need to guarantee,

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Speaker 1: like structural integrity of you know, like crafting. I'm sure

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Speaker 1: it's fine, but do you you know, do you repair

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Speaker 1: a baby's high chair, you know, with a glue gun?

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Speaker 1: I don't know about that one. I do, but I

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Speaker 1: mean that's just me just because I'm I'm wild with

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Speaker 1: a glue gun. Do you remember when you're old enough

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Speaker 1: to use a glue gun that felt like a like

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Speaker 1: the first like driver's license you get as a child,

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Speaker 1: where it's like, man, you can't funk with this glue

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Speaker 1: gun because that metal tip will burn the ship out

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Speaker 1: of you. And then at a certain point it's like

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Speaker 1: you are acknowledged as a child who is responsible enough

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Speaker 1: to use a glue gun. And I felt that was,

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Speaker 1: I don't know, a big point turn point for me.

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Speaker 1: I keep that thing on me, man, the the gluegn

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Speaker 1: I got it holstered, ready to go at all times.

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Speaker 1: You never know when you might need to make a

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Speaker 1: cool little uh doll out of corn husks or something. Yeah, exactly.

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Speaker 1: So can you speak a little bit about the work

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Speaker 1: that you do the like while you're like what you

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Speaker 1: were actually out in l A doing. Yeah. We we

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Speaker 1: are civil rights lawyers and advocates and and storytellers and

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Speaker 1: and experts about the criminal punishment system in this country,

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Speaker 1: and the bulk of our work over the last few

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Speaker 1: years has been suing cities and counties and states and

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Speaker 1: judges and prosecutors, sheriffs, police over sort of the rampant,

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Speaker 1: unconstitutional like conduct that they engage in every single day

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Speaker 1: all over the country. So, for example, as you and

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Speaker 1: I are talking right now, there are four hundred to

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Speaker 1: five hundred thousand people depending on how you count, in

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Speaker 1: cages in this country, solely because they can't afford to

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Speaker 1: pay a cash payment to get out. These are people

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Speaker 1: who are presumptively innocent they're waiting trial, they're supposed to

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Speaker 1: be presumed innocent, and because their families don't have enough

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Speaker 1: cash to keep them with their kids and their schools

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Speaker 1: and their homes and their families and their jobs and

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Speaker 1: their churches and their community, they're stuck in a cage.

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Speaker 1: And so we have filed lawsuits all over the country.

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Speaker 1: Last year I argued a case that we brought in

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Speaker 1: California that's struck down the money bail system in California

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Speaker 1: as we know it on behalf of our client Kindeth Humphrey.

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Speaker 1: And so we've been doing a lot of work with

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Speaker 1: people who have been directly harmed by the prisoner jail

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Speaker 1: system in California, advocates, public defenders, organizers, crime survivors, and

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Speaker 1: others to try to figure out, like how to reshape

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Speaker 1: the pre trial system in California, And we do similar

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Speaker 1: work all over the country, basically trying to resensitize our

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Speaker 1: society to the extraordinary and senseless violence that the criminal

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Speaker 1: punishment bureaucracy just inflicts on people with absolutely no evidence

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Speaker 1: that it does any good or makes anyone any safer, right,

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Speaker 1: And that seems to be the biggest thing that whether

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Speaker 1: it's like overtly being debated or subconsciously being debated. That's

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Speaker 1: SEMs to be the thing that many people are having

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Speaker 1: a reckoning with, especially in California, is the idea of like,

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Speaker 1: I just feel like maybe we just need to be

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Speaker 1: cruel to people, so I read less stories about shoplifting

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Speaker 1: or that you know, there's no acknowledgment, you know, like

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Speaker 1: the work that it takes to try and go up

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Speaker 1: against something like the prison industrial complex, and you know

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Speaker 1: what what that entails. Well, a really basic thing that

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Speaker 1: a lot of people just don't seem to understand is

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Speaker 1: that if police and prisons and prosecutors made people safer,

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Speaker 1: then the U. S would have the safest society and

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Speaker 1: the history of the world. I mean, we cage people

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Speaker 1: at rates that are five to ten times every other

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Speaker 1: comparable country. We cage people. We cage Black people at

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Speaker 1: a rate six times out of South Africa at the

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Speaker 1: height of apartheid. So if human caging and punishment and

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Speaker 1: police and surveillance and batons and tasers and guns, if

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Speaker 1: all that stuff made people safer, we would have an

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Speaker 1: extraordinarily safe society. And yet we spend by far the

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Speaker 1: most money on armed the government bureaucrats of any country

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Speaker 1: in the world, and those armed government bureaucrats specifically target

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Speaker 1: very poor people in communities all over this country, and

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Speaker 1: they have a terrible track record of improving public safety.

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Speaker 1: And so I think it's it's a really important thing

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Speaker 1: to keep pointing out to people that essentially every other

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Speaker 1: society in the world has figured out ways of having

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Speaker 1: lower levels of violence with lower expenditures on things like handcuffs,

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Speaker 1: cages and prosecutors and cops. Right, yeah, because I think

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Speaker 1: in our way of thinking, it's like, well, what's the problem,

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Speaker 1: all right, spend money on it, rather than taking a

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Speaker 1: little bit of a wider view, like well, what's driving crime?

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Speaker 1: Because that's the one thing I always see absent with

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Speaker 1: a lot of reporting around things like crime rates going up.

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Speaker 1: It's like crimes up, man, it's out of control, and

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Speaker 1: we got to get rid of these d a s.

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Speaker 1: And it's never I've I've yet to read like a

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Speaker 1: or here a real sincere analysis of what cry even

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Speaker 1: is in this country. And I think that's a huge

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Speaker 1: blind spot. I think a lot of people have as well.

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Speaker 1: In the discourse. There's a lot of powerful people who

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Speaker 1: also are making a lot of money. Who I want

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Speaker 1: you asking questions like, well, shouldn't we just be having

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Speaker 1: shouldn't we just be spending more money on more technology

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Speaker 1: for cops and more stuff for prosecutors and more prison beds?

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Speaker 1: And you know that will help the union, the correction

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Speaker 1: officers union, right, But they don't want you asking are

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Speaker 1: things like should we pay attention to the research that

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Speaker 1: shows that like having a stable place to live and

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Speaker 1: having healthcare and mental health treatment, having good schools, having

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Speaker 1: less inequality, having less starvation and poverty, those are actually

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Speaker 1: the things that are correlated with violence and harm. But

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Speaker 1: they don't want you asking those questions because that solution

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Speaker 1: to so called violent crime would actually require deep investments

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Speaker 1: in changing the levels of inequality in our society, and

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Speaker 1: that's not something that most of the powerful politicians who

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Speaker 1: control these narratives are actually interested in doing. Right. What

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Speaker 1: is something you think is overrated? Okay, I say this

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Speaker 1: ever since I was a baby, I've been a night

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Speaker 1: Oh I'm born. I am genetically wired as a nocturnal creature.

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Speaker 1: I think being an early bird is overrated, overvalued. I

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Speaker 1: think yes, it's easier too, It's easier to sort of

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Speaker 1: succeed in suciety society if you like, look at me,

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Speaker 1: if I'd actually gotten any sleep, I could say that properly.

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Speaker 1: It's easier to succeed in society if you're like an

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Speaker 1: early riser. I do get up. I'm exhausted all the time.

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Speaker 1: But there's something to be said. I am so fun.

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Speaker 1: I was so fun at a slumber party. I am

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Speaker 1: so fun from the hour from like eleven to three,

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Speaker 1: Like there's something, there's a magic witching hour, and and

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Speaker 1: it's not something you choose, it's just in your blood.

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Speaker 1: And like I think there's a real arrogance to like

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Speaker 1: just genetic early risers. Right, that's I'm I kind of

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Speaker 1: feel the same. I can be like dead the whole

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Speaker 1: day and then suddenly like find a burst of energy

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Speaker 1: like a ten PM. That's right, because it's fun. Then

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Speaker 1: it's a fun time then because it's still okay. Wait,

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Speaker 1: so is it fun because you're like everyone's asleep except us,

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Speaker 1: or is it that you're like, I love sleep so

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Speaker 1: fun the morning, I think I think I'm in my

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Speaker 1: best spirits. Late at night I have the most creat

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Speaker 1: like my creative juices are going the most. I feel happiest.

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Speaker 1: I think I feel like kind of mischievous, Like it's

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Speaker 1: when I'm at my best, and I think the world

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Speaker 1: like doesn't value that. Right, Can you go help all

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Speaker 1: those people who gave entrusted you with their secrets. That's right.

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Speaker 1: I gotta go. I gotta go. I have to deal

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Speaker 1: with the body. I gotta exactly I've got, I've got

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Speaker 1: all my ammonia in my car. I gotta go to

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Speaker 1: different times. Damn, that sounds that sounds like he has

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Speaker 1: some experience. Well, I always say, because I had like

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Speaker 1: a I had like a explosion at my house and

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Speaker 1: from a fireplace, and so I went like late at

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Speaker 1: night to home to home depot. I was told like

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Speaker 1: ammonia was going to help get off of the walls

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Speaker 1: and stuff. And the guy it was like just me

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Speaker 1: at eleven pm, like but like the Eagle Rock home

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Speaker 1: depot and the guy know. I was like, hey, do

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Speaker 1: you know where the ammonia is? The guy don't work there.

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Speaker 1: He looked like he was like eighteen. He looked at

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Speaker 1: me and goes, just make sure you use enough to

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Speaker 1: knock him out. I was like what And then I

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Speaker 1: asked that. I was like whoa, And I said I

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Speaker 1: started laughing. I was like, what if I was here

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Speaker 1: for that? And he goes, hey, I didn't see anything.

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Speaker 1: I didn't see anything. That guy's the vault. That guy.

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Speaker 1: That's the sort of fun interaction you don't have when

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Speaker 1: you go into home depot in the morning. They're not

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Speaker 1: gonna be like fun and flirty and be like we're

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Speaker 1: both serial killers. They're gonna be over there just like

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Speaker 1: leave me alone. You know, it's fun flirt serial killer interactions.

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Speaker 1: Journal entry that night, Journal, I finally met her. He

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Speaker 1: understands me, this blonde woman with a high pitched voice.

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Speaker 1: Finally I felt like neo, the one. She's finally came

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Speaker 1: looking for the ammonia a murder. The downside of that,

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Speaker 1: the only the only other people you find buying ammonia

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Speaker 1: in the middle of the night at home depot are

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Speaker 1: probably using it to clean up a mess. Everyone's cleaning

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Speaker 1: up a mass of some kind. You can, I say,

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Speaker 1: one more interaction I had at the home depot and

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Speaker 1: then I checked out. This is what you get at

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Speaker 1: midnight at the home depot. I was checking out and

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Speaker 1: the woman I was like, how are you doing to

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Speaker 1: the security guard? Is this lady? And She's like not good.

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Speaker 1: She goes my coworker. He just called me. He's like

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Speaker 1: stuck somewhere. He's in a car. There's a bunny running

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Speaker 1: around in his car, just like pissing and ship eating

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Speaker 1: the seeds everywhere, and he didn't have anything to clean

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Speaker 1: it up. And I told him, I'm not driving an

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Speaker 1: hour to clean up the bunny ship. And I'm like, wait, what,

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Speaker 1: Like there's some dude, like just some random bunny, Like,

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Speaker 1: what is happening of this? Maybe maybe this was just

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Speaker 1: a figment of my imagination. Maybe I was just like

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Speaker 1: tripping on ayahuasca and I never went to home depotemonia. Yeah,

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Speaker 1: that's what happened. That's what happens. If you're a night

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Speaker 1: all you get jewels like that? Yeah, Greg, what something

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Speaker 1: you think is underrated? Underrated? Okay, here, I'm going out

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Speaker 1: on a limb. Here, I'm gonna say buttered noodles. You know,

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Speaker 1: I think I think everybody wants to give a lot.

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Speaker 1: You know, you give credit to the you know, a

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Speaker 1: marinara or or a vodka sauce or a carbonara. You know,

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Speaker 1: that's where that's your go to in your head when

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Speaker 1: you're thinking about pasta. But when you just take a

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Speaker 1: little bit of butter, maybe throwing some grilled onions. If

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Speaker 1: you're making like a bone in chicken, you add a

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Speaker 1: little small into that top with some parmesan. That's that's

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Speaker 1: like really good food. That's like really easy to do

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Speaker 1: and isn't a whole it's not a whole headache in

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Speaker 1: the kitchen. You can just kind of like toss it

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Speaker 1: together and suddenly that's a that's a top quality side

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Speaker 1: dish or hole dish rights Controversially, no, it is kind

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Speaker 1: of controversial. It's like not controversial with young children. I

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Speaker 1: think young children love a buttered noodle. It really I

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Speaker 1: I think of it as like too bland for me.

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Speaker 1: I'm a real I'm a real tomato bitch. I love sauce,

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Speaker 1: I love tomato salsa. But yeah, I've never been into

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Speaker 1: the buttered noodles because it tastes too much like noodles

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Speaker 1: to me and not not enough. Like I don't know

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Speaker 1: what I have associated pasta with, which is the marinara sauce.

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Speaker 1: But maybe that's the key to the greatness of butter noodles.

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Speaker 1: It's like this is the pace of the dish, right,

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Speaker 1: Like technically you're showing up for spaghetti and you've associated

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Speaker 1: it with the marinera on top. But the noodle should

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Speaker 1: be the highlight of that dish. And as to get

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Speaker 1: more into like like I've recently really gotten into ramen

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Speaker 1: and I'm like reading recipes on how to make it

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Speaker 1: from scratch and stuff, and like there's so much technique

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Speaker 1: in a noodle and create like crafting it. You know,

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Speaker 1: what kind of flower, what kind of grind on that flower?

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Speaker 1: How long are you mixing it at? What temperature that

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Speaker 1: I think if you get a quality noodle and you're

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Speaker 1: just tasting which is a little bit of butter, you're

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Speaker 1: really putting that noodle like on a pedestal and asking

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Speaker 1: people to taste just that noodle. And I can see,

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Speaker 1: I can see where that would be, like you know,

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Speaker 1: this is the highlight, like really experience and enjoy this

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Speaker 1: part of the dish that typically you're just trying to

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Speaker 1: get through. Okay, see it, are you putting high quality

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Speaker 1: like noodle in into a butter noodle dish? No, I'm

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Speaker 1: saying you get you get some egg noodles and then

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Speaker 1: you just you just get some like relled onions. You

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Speaker 1: fix that suddenly parmesan on top, and you've got you've

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Speaker 1: got something more than just butter noodle. I think, okay,

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Speaker 1: all right, I think I think, yeah, alright. But controversial

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Speaker 1: will be hearing from our listeners, maybe more than any

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Speaker 1: guest we've ever had. But all right, let's take a

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Speaker 1: quick break. We'll come back. We'll talk about inflation and

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Speaker 1: bountime staff. And we are back and Elon Musk. Let's

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Speaker 1: talk about Elon Musk really quick. He has had a

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Speaker 1: wild couple of weeks. He's had to pretend to donate

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Speaker 1: billions of dollars to himself in a move to distract

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Speaker 1: people from another story that came out that his neural

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Speaker 1: link company was basically unethically experimenting on monkeys or many

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Speaker 1: were dying after He's like, with this brain ship in him,

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Speaker 1: Oh it's un old suffering, I don't know whatever. And

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Speaker 1: now we're hearing about a lawsuit from some of his

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Speaker 1: black employees in a Fremont, California factory claiming that you know,

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Speaker 1: the workplace is a racist hell escape and be surprised,

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Speaker 1: and they're like, oh wow, really, the the guy who

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Speaker 1: the boy with emeralds in his pocket from apartheid South Africa,

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Speaker 1: letting race, anti black racism, cooking his facilities. I don't know.

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Speaker 1: I mean, obviously he doesn't run HR, but it's his company.

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Speaker 1: So you're gonna have to understand. We'll have to, you know,

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Speaker 1: look into that a little bit more so. This lawsuit

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Speaker 1: has been following three It's like comes after a three

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Speaker 1: year investigation into Tesla, and it alleges that black and

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Speaker 1: African American employees at the company's Fremont plant are quote

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Speaker 1: segregated to the lowest levels, meaning in some places, black

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Speaker 1: employees are meant to scrub the floors on their hands

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Speaker 1: and knees where employees who are not black did not

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Speaker 1: have to do that kind of labor. Also being subjected

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Speaker 1: to some of like the hardest physical labor within the plant. Quote.

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Speaker 1: This is from an MP article that goes on and

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Speaker 1: say quote. The lawsuit describes multiple instances of racist language

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Speaker 1: and drawings towards black employees, penalizing black employees more harshly

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Speaker 1: than white employees, and denying black employees career advancement opportunities

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Speaker 1: and equal pay for work similar to that of other employees.

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Speaker 1: When they say racist language and drawings, we're talking about

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Speaker 1: graffiti that was like fucking all over the place, according

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Speaker 1: to this lawsuit, like everywhere the bathroom stalls, workbenches, lunch

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Speaker 1: tables with things like KKK Hangman's nooses, go back to Africa,

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Speaker 1: using the N word in all kinds of ways that

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Speaker 1: you can imagine. And this is on top of, like

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Speaker 1: they said, of being such a segregated environment that the

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Speaker 1: some of these racist co workers had given nicknames to

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Speaker 1: the parts of the factor where most of the black

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Speaker 1: employees were working. Every day, they would refer to some

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Speaker 1: parts of the factory is quote, the slave ship or

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Speaker 1: the plantation in addition to other slayers. One black worker

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Speaker 1: quote heard these racial sluryers as often as fifty two

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Speaker 1: a hundred times a day. It's a very very fucked

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Speaker 1: up story. And sadly this is the first time this

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Speaker 1: ship has happened, because another former employee was just awarded

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Speaker 1: by a judge almost a hundred forty million dollars for

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Speaker 1: the racism that they had to endure at Tesla. And

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Speaker 1: like in their defense, Tesla just posted to their blog

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Speaker 1: with this rebuttal that essentially said it like we've been

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Speaker 1: investigated like fifty times for racial discrimination and not once

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Speaker 1: did they find us to be acting in violation of

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Speaker 1: the law, and it's like I'm sorry fifty times. Uh,

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Speaker 1: that's so insane. It's like it's like when my parents,

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Speaker 1: like I was sneaking out of house all the time

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Speaker 1: as a kid, but I never got caught. It doesn't

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Speaker 1: mean I wasn't sneaking out of the house. Means I

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Speaker 1: wasn't getting caught. Like insane, it's a very yeah, I

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Speaker 1: mean that like that, I don't think I guess they

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Speaker 1: think that's a good defense. Although like even like the

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Speaker 1: like labor Board was sort of like a lot of

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00:21:59,000 --> 00:22:02,560
Speaker 1: even their internal like investigations aren't compliant with like the

394
00:22:02,600 --> 00:22:06,800
Speaker 1: actual law. So you know, it's like most organizations that

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00:22:07,080 --> 00:22:15,720
Speaker 1: investigate themselves where they're sort of like yeah, let me look, okay, yeah, yeah,

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00:22:17,119 --> 00:22:22,919
Speaker 1: it's yeah. So the this Elon Musk nonsense continues, and

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Speaker 1: then not to mention that this week too, he was

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Speaker 1: like he's like ship posting like Hitler memes talking about

399
00:22:28,520 --> 00:22:30,840
Speaker 1: Trudeau because of like you know, I'm trying to hold

400
00:22:30,920 --> 00:22:34,920
Speaker 1: up crypto payments to the racist convoy. And it was

401
00:22:34,960 --> 00:22:37,320
Speaker 1: like it was like a meme of Hitler that said, like, hey,

402
00:22:37,359 --> 00:22:40,000
Speaker 1: don't compare to me. Me to him, I had a budget,

403
00:22:40,520 --> 00:22:47,760
Speaker 1: and it's like, what are you God? The Gremlin? I hate?

404
00:22:48,640 --> 00:22:52,600
Speaker 1: Gremlin is a bad name. Yeah, come on, leave GisMo alone.

405
00:22:52,680 --> 00:22:56,320
Speaker 1: He leave GisMo. Yeah. It's like even the moment I

406
00:22:56,359 --> 00:22:59,960
Speaker 1: ever heard his name, like the last his name literally

407
00:23:00,080 --> 00:23:02,879
Speaker 1: sounds like a Batman villain, like he doesn't you know

408
00:23:02,880 --> 00:23:04,480
Speaker 1: what I mean, It's like this, they're no good can

409
00:23:04,520 --> 00:23:09,160
Speaker 1: come from somebody named Elon Musk? Are you kidding me? Yeah?

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Speaker 1: That the name is too too many hard consonants sounds

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Speaker 1: and that feels like like a it sounds like a

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00:23:15,680 --> 00:23:19,680
Speaker 1: swear word already. Yeah right, m m. But yeah, I

413
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Speaker 1: mean I think it's just funny because he's as he

414
00:23:22,320 --> 00:23:24,560
Speaker 1: you know, goes more and more like openly you're like

415
00:23:24,680 --> 00:23:27,320
Speaker 1: right wing, like what his like fans are going to

416
00:23:27,400 --> 00:23:29,520
Speaker 1: be like are they also going to be like yeah, man,

417
00:23:29,720 --> 00:23:32,840
Speaker 1: fucking the Holocaust didn't happen. But like, we gotta have

418
00:23:32,920 --> 00:23:37,600
Speaker 1: electric cars. We really need to think about, Like is

419
00:23:37,640 --> 00:23:41,959
Speaker 1: that the then the weird byproduct of Elon Musk? Like

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00:23:42,080 --> 00:23:45,399
Speaker 1: I don't, right, It's such a conundrum to me because

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00:23:45,440 --> 00:23:50,520
Speaker 1: it's like I we need like that type of technology

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Speaker 1: electric or like some some alternative to you know, burning

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Speaker 1: fossil fuels and and all that kind of stuff. So

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Speaker 1: I'm like, yeah, I like the cars, sounds good to me,

425
00:24:01,000 --> 00:24:03,960
Speaker 1: but the main like the one of the biggest manufacturers

426
00:24:04,560 --> 00:24:10,200
Speaker 1: of them is a like just a piss pot, piss pot,

427
00:24:10,480 --> 00:24:14,600
Speaker 1: a chamber pot of a humane as we say back

428
00:24:14,600 --> 00:24:18,520
Speaker 1: in Victorian English. It also always boggles my mind when

429
00:24:18,520 --> 00:24:21,520
Speaker 1: people have the they considered these types of people they're

430
00:24:21,560 --> 00:24:24,320
Speaker 1: like heroes and will go to battle for them no

431
00:24:24,359 --> 00:24:27,639
Speaker 1: matter what. We're like, what this do you think if

432
00:24:27,680 --> 00:24:29,520
Speaker 1: you were in a real world scenario where you met

433
00:24:29,520 --> 00:24:31,840
Speaker 1: this person, that they would even give any type of

434
00:24:31,840 --> 00:24:34,600
Speaker 1: shit about you. It's like so wild to me that

435
00:24:34,640 --> 00:24:36,679
Speaker 1: they put them on a pedestal when I'm like, they

436
00:24:36,720 --> 00:24:39,040
Speaker 1: would literally step on your neck if they had a chance,

437
00:24:39,119 --> 00:24:42,480
Speaker 1: Like it's crazy. I mean, it's the people have. You know,

438
00:24:42,480 --> 00:24:45,080
Speaker 1: everyone has these odd para social relationships, and the ones

439
00:24:45,119 --> 00:24:47,919
Speaker 1: with like billionaires are like really confounding to me because

440
00:24:48,119 --> 00:24:51,159
Speaker 1: they're like they they're actually like the root cause of

441
00:24:51,200 --> 00:24:54,639
Speaker 1: all the chaos and instability, instability that you're feeling down

442
00:24:54,680 --> 00:24:57,080
Speaker 1: on the other end of like the socio economic ladder,

443
00:24:57,240 --> 00:25:00,800
Speaker 1: like but you're so your anger that you're actually using

444
00:25:00,840 --> 00:25:05,320
Speaker 1: to defend Elon Musk. You're you're it's completely misdirected, and

445
00:25:05,359 --> 00:25:08,240
Speaker 1: I get for a lot of people, he's like, he

446
00:25:08,280 --> 00:25:12,359
Speaker 1: feels like this fucking like fantasy story of like a

447
00:25:12,400 --> 00:25:15,400
Speaker 1: guy who likes science, who like is now like this,

448
00:25:15,720 --> 00:25:19,080
Speaker 1: you know, like shitty version of what's the dude from

449
00:25:19,280 --> 00:25:22,480
Speaker 1: Iron Man? You know what I mean? Yeah, he's like

450
00:25:22,520 --> 00:25:24,600
Speaker 1: Tony Stark. He's like the new like you know, his

451
00:25:24,640 --> 00:25:28,800
Speaker 1: own hair plugged version of Tony Stark. And in that sense,

452
00:25:28,840 --> 00:25:31,480
Speaker 1: you know, like no shade. I remember the old photos

453
00:25:31,520 --> 00:25:33,600
Speaker 1: of you when PayPal came out in two thousand, very

454
00:25:33,600 --> 00:25:36,160
Speaker 1: different hairline. But that's the glow up that we can

455
00:25:36,200 --> 00:25:40,000
Speaker 1: experience with billions of dollars, so one day, one day,

456
00:25:40,200 --> 00:25:43,320
Speaker 1: And that's why I defend him for my right. Honestly,

457
00:25:43,359 --> 00:25:46,679
Speaker 1: I'm starting to see a correlation between people becoming worse

458
00:25:46,800 --> 00:25:48,959
Speaker 1: humans when they get hair plugs. It's like it's like

459
00:25:49,000 --> 00:25:54,119
Speaker 1: infecting their brain, right, I mean, okay, So Jeremy Piven,

460
00:25:55,800 --> 00:25:58,440
Speaker 1: you know hair that the plugs, the plugs took him

461
00:25:58,440 --> 00:26:01,000
Speaker 1: to an interesting path. Although he's been pretty quiet, I

462
00:26:01,320 --> 00:26:06,480
Speaker 1: feel who else I do think that well, Antonio banderis

463
00:26:06,720 --> 00:26:08,600
Speaker 1: see that's people don't know about his plugs. Wait, I

464
00:26:08,600 --> 00:26:11,879
Speaker 1: didn't know. Yeah, hang on a second, well that you

465
00:26:11,920 --> 00:26:13,200
Speaker 1: need a lot if you're going to be a cat.

466
00:26:13,480 --> 00:26:20,880
Speaker 1: Sorry to reference deep got a puss in booth? Anybody,

467
00:26:21,240 --> 00:26:26,480
Speaker 1: all right? I got you? What about Billy Zane? I mean,

468
00:26:26,560 --> 00:26:31,000
Speaker 1: he's just he's the best. So oh yeah, how did

469
00:26:31,000 --> 00:26:34,760
Speaker 1: his plugs look? They look good? Well, well, I don't

470
00:26:34,800 --> 00:26:37,080
Speaker 1: even know if he's using them anymore. Maybe you got

471
00:26:37,280 --> 00:26:41,760
Speaker 1: can you take them out? Maybe you never had them?

472
00:26:41,960 --> 00:26:45,560
Speaker 1: I don't know. Maybe I'm wrong about Zane. And it's

473
00:26:45,840 --> 00:26:49,160
Speaker 1: also wearing two pays or plugs. I think he's wearing

474
00:26:49,200 --> 00:26:54,760
Speaker 1: a whole new face right face off. Speaking of Nicolas Cage,

475
00:26:54,800 --> 00:26:57,639
Speaker 1: I feel like has plugs. Oh yeah, yeah yeah, I

476
00:26:57,640 --> 00:27:00,320
Speaker 1: mean he's tried. He was kind of like back in

477
00:27:00,320 --> 00:27:04,000
Speaker 1: those nineties films and his hair looked different every film,

478
00:27:04,040 --> 00:27:07,840
Speaker 1: and like nobody really just asked about it. They're like, yeah, yeah, yeah, yeah,

479
00:27:07,840 --> 00:27:10,720
Speaker 1: he looks great. He looks great. You're like, now, did

480
00:27:10,840 --> 00:27:12,840
Speaker 1: they have the hair the same hair and makeup person

481
00:27:12,960 --> 00:27:17,120
Speaker 1: on this other film? Maybe not, but yeah, shout out

482
00:27:17,160 --> 00:27:19,600
Speaker 1: to Billy Zane because you say Billy Zane is a

483
00:27:19,640 --> 00:27:22,480
Speaker 1: cool guy. Still, I mean, I don't know him personally,

484
00:27:22,720 --> 00:27:28,440
Speaker 1: but based on his performance in Titanic m hm. And

485
00:27:28,560 --> 00:27:33,320
Speaker 1: yes he is the villain, but isn't the iceberg actually

486
00:27:33,400 --> 00:27:38,920
Speaker 1: the villain? I would say Billy's ad is my point.

487
00:27:39,520 --> 00:27:43,879
Speaker 1: Someone said that he had some kind of disorder that

488
00:27:44,040 --> 00:27:46,160
Speaker 1: made him bald and I'm just reading a Reddit thread,

489
00:27:46,200 --> 00:27:48,359
Speaker 1: so don't believe anything you're reading right now, And then

490
00:27:48,359 --> 00:27:49,879
Speaker 1: someone said no. In an interview, he said, it's just

491
00:27:49,880 --> 00:27:53,760
Speaker 1: male pattern Baldin has started when he was twenty five. Okay, okay, cool,

492
00:27:54,240 --> 00:27:59,959
Speaker 1: thank you, he aggressive Reddit user yeah for defending Billy's

493
00:28:00,000 --> 00:28:02,800
Speaker 1: as lack of hair and the root causes m But yeah,

494
00:28:02,960 --> 00:28:06,080
Speaker 1: shout out to UH for the people who got plugs

495
00:28:06,119 --> 00:28:10,080
Speaker 1: and went positive with it. We need you, yeah, we

496
00:28:10,119 --> 00:28:13,760
Speaker 1: need you more than ever. Alright, well, let's talk about

497
00:28:14,040 --> 00:28:17,919
Speaker 1: something else dangerous to do. Driving high for some people.

498
00:28:18,480 --> 00:28:22,960
Speaker 1: For me, yeah, but mostly because I when I was

499
00:28:23,040 --> 00:28:26,639
Speaker 1: the type of high person that would drive seven miles

500
00:28:26,680 --> 00:28:30,719
Speaker 1: per hour tops and feel like I was speeding and

501
00:28:30,760 --> 00:28:34,040
Speaker 1: also that everyone's looking at me. But you know, I

502
00:28:34,119 --> 00:28:37,479
Speaker 1: also know I have some good friends who have been

503
00:28:37,560 --> 00:28:40,720
Speaker 1: using weed since middle school as like a d D

504
00:28:40,880 --> 00:28:45,880
Speaker 1: medication and like cased their GMAT like just high out

505
00:28:45,880 --> 00:28:49,640
Speaker 1: of their mind, because like they are better at stuff

506
00:28:49,840 --> 00:28:53,520
Speaker 1: when they're high, So it really depends. That's the hard

507
00:28:53,560 --> 00:28:56,000
Speaker 1: bit about trying. You know, as like more and more

508
00:28:56,000 --> 00:28:59,600
Speaker 1: states legalized recreational cannabis, you know the thing all law

509
00:28:59,720 --> 00:29:02,080
Speaker 1: force it's like, well, how do we pull people the

510
00:29:02,240 --> 00:29:05,479
Speaker 1: funk over for being high while driving? That's like the

511
00:29:05,520 --> 00:29:08,840
Speaker 1: fucking white whale that law enforcement is searching for. And

512
00:29:08,880 --> 00:29:10,560
Speaker 1: I think in general a lot of people too, even

513
00:29:10,560 --> 00:29:13,479
Speaker 1: like stoners, say, look, if there was a way for

514
00:29:13,520 --> 00:29:15,920
Speaker 1: you to actually be like, hey man, you're too high

515
00:29:16,000 --> 00:29:18,080
Speaker 1: to drive, because people would be like, I've been so

516
00:29:18,160 --> 00:29:20,400
Speaker 1: high I shouldn't drive. Most people just don't. But if

517
00:29:20,400 --> 00:29:23,360
Speaker 1: there was a way to say, verifiably this person is

518
00:29:23,400 --> 00:29:25,400
Speaker 1: too high to drive, we've proved it with this test

519
00:29:25,440 --> 00:29:28,120
Speaker 1: that doesn't rely on you know, some guys stepdad from

520
00:29:28,160 --> 00:29:31,480
Speaker 1: the seventies being an asshole, then maybe this would be

521
00:29:31,520 --> 00:29:34,200
Speaker 1: like a fair application of the law. But as it stands,

522
00:29:34,240 --> 00:29:36,760
Speaker 1: we just have things like blood tests that will measure

523
00:29:36,760 --> 00:29:39,160
Speaker 1: like the amount of nanograms of t S in your blood.

524
00:29:39,480 --> 00:29:42,360
Speaker 1: But since THC is fat soluble, it's not like alcohol,

525
00:29:42,400 --> 00:29:45,040
Speaker 1: which is water soluble, that ship can stay in your

526
00:29:45,080 --> 00:29:47,680
Speaker 1: system for weeks or maybe just a couple of days

527
00:29:47,760 --> 00:29:50,680
Speaker 1: or hours, depending on your biology. So that's not really

528
00:29:50,720 --> 00:29:52,680
Speaker 1: a good way to measure it. And also it only

529
00:29:52,720 --> 00:29:54,800
Speaker 1: measures like how much th HC is in your blood,

530
00:29:54,800 --> 00:29:58,560
Speaker 1: it doesn't necessarily measure how impaired you might be. And

531
00:29:58,600 --> 00:30:03,640
Speaker 1: then you know, standards variety tests wield pretty wildly inconsistent

532
00:30:03,760 --> 00:30:07,160
Speaker 1: results because you know, some like you're saying, some people

533
00:30:07,280 --> 00:30:10,200
Speaker 1: are completely fucked up, can be completely sucked up. Some

534
00:30:10,240 --> 00:30:13,600
Speaker 1: people are normal, and some people have fucking super strength somehow.

535
00:30:13,960 --> 00:30:16,720
Speaker 1: So the need for something that can measure someone's cognitive

536
00:30:16,760 --> 00:30:21,280
Speaker 1: impairment that isn't like rife with cultural biases or discriminatory

537
00:30:21,360 --> 00:30:24,080
Speaker 1: leanings of a police officer is like critical to have

538
00:30:24,120 --> 00:30:26,760
Speaker 1: a balanced application of the law. So a few states

539
00:30:27,280 --> 00:30:29,840
Speaker 1: again have said, well, maybe the blood tests the same thing,

540
00:30:29,880 --> 00:30:32,160
Speaker 1: but even cops are like, that's not even close, Like

541
00:30:32,240 --> 00:30:35,080
Speaker 1: this person looks sober and then their blood said one thing,

542
00:30:35,240 --> 00:30:37,880
Speaker 1: Like that doesn't even feel right even for the police.

543
00:30:37,920 --> 00:30:41,280
Speaker 1: So there's a device called cognitive You, which is being

544
00:30:41,360 --> 00:30:44,400
Speaker 1: touted as the solution to this problem and was first

545
00:30:44,480 --> 00:30:47,360
Speaker 1: is developed as like a test for cognitive decline in

546
00:30:47,400 --> 00:30:49,920
Speaker 1: aging people, just to see like okay, we can begin

547
00:30:50,000 --> 00:30:52,440
Speaker 1: to see like their reaction time, like their ability to

548
00:30:52,560 --> 00:30:54,720
Speaker 1: tract things with their eyes. And that's where I was

549
00:30:54,760 --> 00:30:57,480
Speaker 1: familiar with it from you making me take it after

550
00:30:57,560 --> 00:31:00,920
Speaker 1: a couple of slow recordings, right, I don't like jack,

551
00:31:00,960 --> 00:31:02,600
Speaker 1: come on now, which one of these is not a

552
00:31:02,640 --> 00:31:07,040
Speaker 1: real word? So that's what this like whole this machine does.

553
00:31:07,080 --> 00:31:08,920
Speaker 1: It like looks like a little laptop and it has

554
00:31:08,960 --> 00:31:11,280
Speaker 1: like a jog wheel in the center of it, so

555
00:31:11,360 --> 00:31:14,880
Speaker 1: it'll do things like ask questions like literally which shape

556
00:31:14,920 --> 00:31:17,080
Speaker 1: is different and show you like a few different shapes,

557
00:31:17,160 --> 00:31:19,320
Speaker 1: so you have to discern which is different or like

558
00:31:19,480 --> 00:31:22,440
Speaker 1: which word is real? And you have to rotate the

559
00:31:22,520 --> 00:31:24,720
Speaker 1: knob to like select the answer, and if you take

560
00:31:24,760 --> 00:31:27,520
Speaker 1: too long, the test will just move on and like

561
00:31:27,680 --> 00:31:30,280
Speaker 1: record that as like a non answer or just begin

562
00:31:30,320 --> 00:31:32,840
Speaker 1: to calculate what you're impairing. That's where I started having

563
00:31:32,880 --> 00:31:35,240
Speaker 1: a panic attack. That part where it was like it'll

564
00:31:35,320 --> 00:31:39,680
Speaker 1: just move on. As you're going to the radio literally

565
00:31:39,720 --> 00:31:43,680
Speaker 1: hearing this the knobs and the moving on, I can't

566
00:31:43,720 --> 00:31:46,280
Speaker 1: smoke pot because I am the full panic attack. Like

567
00:31:46,280 --> 00:31:48,160
Speaker 1: I go right to Middle Earth, I go right to

568
00:31:48,400 --> 00:31:51,840
Speaker 1: like me. If you don't hold onto my hand, I

569
00:31:51,840 --> 00:31:53,560
Speaker 1: will slip to Middle Earth. Or if I don't call,

570
00:31:53,680 --> 00:31:56,440
Speaker 1: I'm like such a buzz kill, and everyone's like, I

571
00:31:56,520 --> 00:31:58,640
Speaker 1: want to see you high. It's like not if you

572
00:31:58,640 --> 00:32:02,520
Speaker 1: want to have a good time. You even hearing that

573
00:32:03,640 --> 00:32:07,080
Speaker 1: literally cripples me with panic. Oh and it's and it

574
00:32:07,120 --> 00:32:10,200
Speaker 1: has like many different things, like little ways to make

575
00:32:10,240 --> 00:32:13,600
Speaker 1: the test harder, Like the wheel will be harder to rotate,

576
00:32:13,680 --> 00:32:16,640
Speaker 1: they say, as if it was in peanut butter like

577
00:32:17,240 --> 00:32:20,000
Speaker 1: so just to like fully begin to like take advantage

578
00:32:20,000 --> 00:32:21,360
Speaker 1: of like, oh, is this thrown them off because the

579
00:32:21,360 --> 00:32:23,560
Speaker 1: wheel moves a little bit slower than the first questions,

580
00:32:24,160 --> 00:32:27,440
Speaker 1: Then this one seems like super well too, to see

581
00:32:27,480 --> 00:32:30,520
Speaker 1: how well they respond to visual stimuli, they make like

582
00:32:30,560 --> 00:32:33,800
Speaker 1: these flashing frantic dots, and it will instruct you stay

583
00:32:33,840 --> 00:32:36,560
Speaker 1: on the bright dots. And you have like a green

584
00:32:36,640 --> 00:32:39,920
Speaker 1: wedge that you can hover over, like with the rotating knobs,

585
00:32:40,240 --> 00:32:41,840
Speaker 1: and you have to like put it over the white

586
00:32:41,880 --> 00:32:45,160
Speaker 1: twinkling like dots, and but don't mistake them for the

587
00:32:45,200 --> 00:32:48,600
Speaker 1: gray ones around it. And again these are things that

588
00:32:48,640 --> 00:32:51,440
Speaker 1: are just meant to slowly see your reaction time and

589
00:32:51,480 --> 00:32:54,200
Speaker 1: things like this. So to test this, like how well

590
00:32:54,240 --> 00:32:57,840
Speaker 1: this machine worked on this wired article. They're like they

591
00:32:57,920 --> 00:33:00,280
Speaker 1: these people got together in Colorado, a group of like

592
00:33:00,360 --> 00:33:03,000
Speaker 1: cops from New York who were trained in something called

593
00:33:03,480 --> 00:33:07,600
Speaker 1: their drug Recognition Experts, which just sounds like like the

594
00:33:07,640 --> 00:33:12,560
Speaker 1: most annoying parents kind of thing, like, Oh, we're trained

595
00:33:12,560 --> 00:33:16,920
Speaker 1: to recognize when someone's drugged out, you know, Like oh yeah,

596
00:33:16,960 --> 00:33:19,160
Speaker 1: they right. They write those like lists that are like,

597
00:33:19,200 --> 00:33:22,400
Speaker 1: here's what to look for if your kids like smoking pot,

598
00:33:22,920 --> 00:33:25,120
Speaker 1: put a UV lead on their tongue to see that.

599
00:33:26,120 --> 00:33:29,479
Speaker 1: Like it's like literally ship like that. So the cops

600
00:33:29,520 --> 00:33:31,479
Speaker 1: they did, they did their thing where like they were

601
00:33:31,480 --> 00:33:33,520
Speaker 1: looking at the same group of stoners, like a bunch

602
00:33:33,560 --> 00:33:37,120
Speaker 1: of stoners volunteered for this, and they used their you know,

603
00:33:37,240 --> 00:33:40,080
Speaker 1: skills to figure out which who was high from there

604
00:33:40,360 --> 00:33:42,000
Speaker 1: and then a lot of and then a also the

605
00:33:42,040 --> 00:33:45,400
Speaker 1: people use the cognitive view machine and the results were

606
00:33:45,920 --> 00:33:51,400
Speaker 1: mixed because it cannabis effects everybody so differently. The cops

607
00:33:51,440 --> 00:33:53,240
Speaker 1: attended to be when they actually looked at the data,

608
00:33:53,280 --> 00:33:56,440
Speaker 1: they were more lenient in their assessment than the fucking

609
00:33:56,480 --> 00:33:59,760
Speaker 1: machine was. Like, and a lot of the people the

610
00:34:00,000 --> 00:34:02,719
Speaker 1: owners involved, they're like like it just seemed like like

611
00:34:02,760 --> 00:34:05,400
Speaker 1: the cops are actually an easier experience for me to

612
00:34:05,440 --> 00:34:08,200
Speaker 1: deal with than like the machine that felt like made

613
00:34:08,200 --> 00:34:10,759
Speaker 1: me feel like I was completely failing at like like

614
00:34:10,920 --> 00:34:14,520
Speaker 1: basic motor skills. But the thing that is sort of

615
00:34:14,560 --> 00:34:18,319
Speaker 1: also tricky with this about smokers, like like stowners, they

616
00:34:18,320 --> 00:34:21,439
Speaker 1: think they drive better when they're high, or at least

617
00:34:21,440 --> 00:34:24,759
Speaker 1: they say they're more focused and aware, which I think

618
00:34:24,800 --> 00:34:27,880
Speaker 1: anyone who smokes, we had just heard that refrain very consistent,

619
00:34:27,960 --> 00:34:31,120
Speaker 1: like dude, I don't drive faster, I drive slower, like

620
00:34:31,160 --> 00:34:34,960
Speaker 1: I'm more aware, and you know that that's a that's

621
00:34:35,000 --> 00:34:36,920
Speaker 1: not the best sentiment to have when it comes to

622
00:34:37,000 --> 00:34:38,960
Speaker 1: roads safety. And like now when I smoke this ship

623
00:34:39,200 --> 00:34:41,719
Speaker 1: and I go slow mo, I'm a better driver. But

624
00:34:41,800 --> 00:34:45,400
Speaker 1: then you looked at this test and some people with

625
00:34:45,480 --> 00:34:49,640
Speaker 1: the Cognitiview machine, they were like outliers who performed better

626
00:34:50,040 --> 00:34:53,719
Speaker 1: after smoking. So that was really fucking up. Like the

627
00:34:53,719 --> 00:34:57,760
Speaker 1: administrators are being like fuck Like this guy looked stoned

628
00:34:57,880 --> 00:35:01,520
Speaker 1: off his face and he was like killing he was

629
00:35:01,560 --> 00:35:05,600
Speaker 1: crushing the scores. Like even for like sober like genius people,

630
00:35:05,600 --> 00:35:07,440
Speaker 1: we've used to like kind of get an average of

631
00:35:07,440 --> 00:35:11,640
Speaker 1: how people respond. So all that to say is it's

632
00:35:11,680 --> 00:35:15,240
Speaker 1: still a very very tricky thing to figure out because

633
00:35:15,280 --> 00:35:18,719
Speaker 1: there's really no one way too, you know, discern what

634
00:35:18,920 --> 00:35:22,320
Speaker 1: someone's level of impairment is. Just hearing about that machine,

635
00:35:22,360 --> 00:35:25,239
Speaker 1: it reminds me of going to the eye doctor and

636
00:35:25,239 --> 00:35:26,600
Speaker 1: when you have to look at that thing and they're

637
00:35:26,600 --> 00:35:29,480
Speaker 1: like click every time you see the squiggly line, you

638
00:35:29,520 --> 00:35:32,280
Speaker 1: know that, And it's like, I just am so panicked

639
00:35:32,280 --> 00:35:34,920
Speaker 1: about seeing the squiggly line that I feel like it

640
00:35:35,120 --> 00:35:37,840
Speaker 1: just the test always says that I can't see anything

641
00:35:37,880 --> 00:35:42,319
Speaker 1: because I'm so panicking and clicking. Yeah, whoever came up

642
00:35:42,360 --> 00:35:46,560
Speaker 1: with that, this this stoned driving thing. It feels like

643
00:35:46,640 --> 00:35:50,839
Speaker 1: they just want everyone to fail, right, well, yeah, And

644
00:35:50,880 --> 00:35:52,880
Speaker 1: I think that's the hard part is like even law

645
00:35:53,040 --> 00:35:56,520
Speaker 1: enforcement and like other like district attorneys are like, dude,

646
00:35:56,520 --> 00:35:59,359
Speaker 1: we don't have anything good to really be able to

647
00:35:59,440 --> 00:36:03,680
Speaker 1: figure this out. And that's why they're scrambling to figure

648
00:36:03,680 --> 00:36:04,799
Speaker 1: this out because I mean, I think at the end

649
00:36:04,840 --> 00:36:06,799
Speaker 1: of the day, like everyone's so into this idea of

650
00:36:06,800 --> 00:36:09,880
Speaker 1: impairment and it and I mean not that everyone's so

651
00:36:09,920 --> 00:36:12,880
Speaker 1: into it, but like with things like alcohol, it's pretty straightforward.

652
00:36:13,280 --> 00:36:17,319
Speaker 1: But with some substances such as this, you know, some

653
00:36:17,360 --> 00:36:21,440
Speaker 1: people end up becoming fucking superman after smoking. So it's like,

654
00:36:21,600 --> 00:36:24,279
Speaker 1: how do you weed? Well? What what is what is

655
00:36:24,320 --> 00:36:27,800
Speaker 1: the way to to even keep people safe? Like and

656
00:36:27,920 --> 00:36:30,239
Speaker 1: let's just trust Stoner's like, hey man, I get it, dude,

657
00:36:30,280 --> 00:36:33,200
Speaker 1: you get it right, Like if if the person is

658
00:36:33,800 --> 00:36:38,360
Speaker 1: good at this test after after smoking and like getting

659
00:36:38,400 --> 00:36:42,759
Speaker 1: pulled over like you, probably I wouldn't feel that bad

660
00:36:42,880 --> 00:36:46,640
Speaker 1: letting them drive even if they were out like super high,

661
00:36:46,760 --> 00:36:50,120
Speaker 1: because clearly they have their ship together, Like that's what.

662
00:36:50,920 --> 00:36:53,920
Speaker 1: And then if you're wouldn't be good at this test,

663
00:36:53,960 --> 00:36:58,560
Speaker 1: like this test sounds bad enough to me to like

664
00:36:58,680 --> 00:37:02,720
Speaker 1: if I smoked weed, I would never drive ever again

665
00:37:02,840 --> 00:37:05,640
Speaker 1: just take your license based on the cognit. But I

666
00:37:05,760 --> 00:37:09,279
Speaker 1: just I'd stop driving. I'd give away my license and

667
00:37:09,560 --> 00:37:11,600
Speaker 1: on the off chance that I would get pulled over

668
00:37:12,200 --> 00:37:17,319
Speaker 1: it from you again at the grove. Yeah, but yeah,

669
00:37:17,520 --> 00:37:20,439
Speaker 1: I think it's it. You know, we're yet to figure

670
00:37:20,480 --> 00:37:22,600
Speaker 1: out the best one. And I even, like colloquially someone

671
00:37:22,600 --> 00:37:24,200
Speaker 1: who smokes a lot, I'm like, I don't really know

672
00:37:24,320 --> 00:37:27,880
Speaker 1: how because like my balance is good. You know. Sometimes

673
00:37:27,920 --> 00:37:29,960
Speaker 1: I ask people like, you know, count to thirty in

674
00:37:29,960 --> 00:37:32,080
Speaker 1: your head, Like I know, like I have a pretty

675
00:37:32,080 --> 00:37:35,720
Speaker 1: good internal clock, So I'm not sure, Like it's there's

676
00:37:35,760 --> 00:37:38,560
Speaker 1: no real uniform way to do this, unless it should

677
00:37:38,600 --> 00:37:42,759
Speaker 1: just make this publicly available and everybody can go, like,

678
00:37:43,600 --> 00:37:47,600
Speaker 1: get get high at the DMV, then take this test

679
00:37:47,880 --> 00:37:52,680
Speaker 1: and you can get a I'm an okay Stone driver license.

680
00:37:54,560 --> 00:38:01,800
Speaker 1: I would fail immediately Stone Stone Driver's license. But Miles

681
00:38:01,840 --> 00:38:06,000
Speaker 1: could test his luck. Yeah, I because I do. I mean,

682
00:38:06,719 --> 00:38:08,480
Speaker 1: I think a lot of a lot of people get

683
00:38:08,560 --> 00:38:10,799
Speaker 1: high and play video games, you know what I mean.

684
00:38:11,000 --> 00:38:15,400
Speaker 1: And I'm killing it out there, so I don't my

685
00:38:15,440 --> 00:38:18,000
Speaker 1: great another video game to play while I'm high, say

686
00:38:18,120 --> 00:38:22,600
Speaker 1: less officer. But yeah, it's not there. Uh, they're they're

687
00:38:22,600 --> 00:38:25,600
Speaker 1: still having trouble. And you know, I think as long

688
00:38:25,800 --> 00:38:29,120
Speaker 1: as we have the you know, carcial system as it is,

689
00:38:29,160 --> 00:38:32,080
Speaker 1: they're they're gonna do their damnedest to try and find

690
00:38:32,120 --> 00:38:33,880
Speaker 1: a way to make it like like this is it.

691
00:38:33,880 --> 00:38:36,839
Speaker 1: It's the most infallible test ever And they're not like

692
00:38:36,920 --> 00:38:40,360
Speaker 1: penning this too. A rise in like fatal car accidents

693
00:38:40,360 --> 00:38:43,359
Speaker 1: tied to people driving Stone. Right. It's just like in

694
00:38:43,440 --> 00:38:47,120
Speaker 1: Washington they did initially right after legalization, they said, oh

695
00:38:47,160 --> 00:38:49,200
Speaker 1: my god, look at all these like these like twice

696
00:38:49,239 --> 00:38:51,800
Speaker 1: as many people are testing with THHC and these like

697
00:38:51,920 --> 00:38:54,360
Speaker 1: terrible car accidents. But again that goes back to the

698
00:38:54,400 --> 00:38:57,120
Speaker 1: thing of like that doesn't mean that they were stoned

699
00:38:57,200 --> 00:38:59,759
Speaker 1: when they were driving. Some person could have smoked three

700
00:38:59,800 --> 00:39:02,880
Speaker 1: days before and had like a certain amount of nanograms

701
00:39:02,880 --> 00:39:05,799
Speaker 1: of THHC in their blood, So that's not straightforward. And

702
00:39:05,800 --> 00:39:08,200
Speaker 1: even then they said fatal car crashes were actually on

703
00:39:08,239 --> 00:39:10,560
Speaker 1: a decline in that period where they were even looking

704
00:39:10,600 --> 00:39:12,279
Speaker 1: at it. It just meant that now that you were

705
00:39:12,280 --> 00:39:15,280
Speaker 1: looking for it, you have more data to suggest maybe

706
00:39:15,360 --> 00:39:18,839
Speaker 1: more people use cannabis. But does that mean the same thing?

707
00:39:19,000 --> 00:39:21,719
Speaker 1: Not always, And I think that's what makes it so tricky. Yeah,

708
00:39:21,920 --> 00:39:24,080
Speaker 1: some people are a way where drivers if you are

709
00:39:24,120 --> 00:39:26,960
Speaker 1: one of those people, don't, don't drive. But then also

710
00:39:27,000 --> 00:39:29,200
Speaker 1: a fewer people are like doing those have you ever

711
00:39:29,280 --> 00:39:31,719
Speaker 1: seen have you seen those like dash cam videos of

712
00:39:31,760 --> 00:39:35,120
Speaker 1: people like having shootouts on the highway, like because like

713
00:39:35,200 --> 00:39:37,719
Speaker 1: because of road rage incidents. Oh I saw that guy

714
00:39:37,760 --> 00:39:39,760
Speaker 1: who like pulled a gun out of his center console

715
00:39:39,880 --> 00:39:42,120
Speaker 1: was like not just like firing at a guy who

716
00:39:42,160 --> 00:39:45,000
Speaker 1: was also firing at him as he drove by. Like

717
00:39:45,080 --> 00:39:50,640
Speaker 1: it was fucking yeah, I need that America America. It's like,

718
00:39:50,840 --> 00:39:52,480
Speaker 1: it's weird because even as I saw him, like, oh,

719
00:39:52,480 --> 00:39:54,080
Speaker 1: he's going for his gun, I'm like, oh, he's shooting

720
00:39:54,239 --> 00:39:55,719
Speaker 1: out of his car window, and I was like, this

721
00:39:55,800 --> 00:39:59,120
Speaker 1: is normal. Yeah. Yeah. And then there was that road

722
00:39:59,200 --> 00:40:03,080
Speaker 1: rage incident recently where somebody worked for like the I

723
00:40:03,080 --> 00:40:07,000
Speaker 1: think it was the Florida State GOP was shot and

724
00:40:07,080 --> 00:40:12,560
Speaker 1: killed after he basically got into an argument with somebody

725
00:40:12,600 --> 00:40:15,960
Speaker 1: in a Prius and they GOP guys in a in

726
00:40:16,000 --> 00:40:21,000
Speaker 1: a larger SUV type car, came back, rammed him and

727
00:40:21,040 --> 00:40:24,120
Speaker 1: then started firing his gun at the guy in the prius,

728
00:40:24,200 --> 00:40:26,680
Speaker 1: and the guy in the prius just took him out.

729
00:40:26,760 --> 00:40:30,160
Speaker 1: But oh my god, that also sounds like somebody who

730
00:40:30,239 --> 00:40:34,880
Speaker 1: maybe you should have tried smoky weed. Yeah, oh sorry.

731
00:40:34,920 --> 00:40:37,359
Speaker 1: And the other detail of that is he had done

732
00:40:37,440 --> 00:40:39,880
Speaker 1: the GOP guy who got killed had done the exact

733
00:40:39,960 --> 00:40:46,560
Speaker 1: same thing the year before. What I'd imagine, like, Yo,

734
00:40:46,640 --> 00:40:49,560
Speaker 1: anybody who's that reckless with their road rage, I'm like,

735
00:40:50,000 --> 00:40:53,120
Speaker 1: keep an eye on them. The most I do when

736
00:40:53,160 --> 00:40:55,600
Speaker 1: I'm getting road rages with my windows rolled up, go

737
00:40:55,920 --> 00:41:01,520
Speaker 1: what the fuck right? I assume I'm gonna lose a

738
00:41:01,680 --> 00:41:06,360
Speaker 1: fight with anybody so I and you never know who's

739
00:41:06,440 --> 00:41:08,560
Speaker 1: just looking like just give me, give me a reason,

740
00:41:08,719 --> 00:41:13,360
Speaker 1: you know what I mean, So give me that um

741
00:41:13,400 --> 00:41:17,520
Speaker 1: so um so. I I try to just just put

742
00:41:17,800 --> 00:41:21,000
Speaker 1: down and deal with it. Yeah. Yeah, I like to

743
00:41:21,000 --> 00:41:25,560
Speaker 1: be very approving of them. Great, awesome job that SMAR

744
00:41:25,880 --> 00:41:30,279
Speaker 1: reverse psychology. Yep, you nailed it. I am a piece

745
00:41:30,280 --> 00:41:33,720
Speaker 1: of sh I do that with rolls on like Twitter.

746
00:41:33,880 --> 00:41:36,760
Speaker 1: I I remember people would sometimes people would be angry,

747
00:41:36,800 --> 00:41:39,120
Speaker 1: like if I would win, like at midnight, you would

748
00:41:39,120 --> 00:41:41,600
Speaker 1: get an extramunt of like I hate her face, why

749
00:41:41,600 --> 00:41:43,520
Speaker 1: did she win? You know, and like so that I

750
00:41:43,520 --> 00:41:46,080
Speaker 1: would always just reply, think because they would at you,

751
00:41:46,080 --> 00:41:47,799
Speaker 1: you know, so I would just right back and right

752
00:41:47,880 --> 00:41:51,439
Speaker 1: thank you with an exclamation point, and like nobody knew

753
00:41:51,480 --> 00:41:53,840
Speaker 1: what to do. I wouldn't engage. I would never reply again.

754
00:41:53,960 --> 00:41:56,680
Speaker 1: I wouldn't. I think people were so confused. It's like, yeah,

755
00:41:56,680 --> 00:41:58,520
Speaker 1: obviously I saw it, so just right back thank you.

756
00:41:58,840 --> 00:42:00,840
Speaker 1: Some of them would that replying to be like no,

757
00:42:00,960 --> 00:42:04,040
Speaker 1: I mean, you know, your fist is okay. I just

758
00:42:04,200 --> 00:42:07,000
Speaker 1: I just really like to see it. Yeah, I just

759
00:42:07,239 --> 00:42:09,719
Speaker 1: like Nick and I thought Nickson was pretty funny, but

760
00:42:09,760 --> 00:42:16,200
Speaker 1: you're okay to it was Yeah, yeah, that is just

761
00:42:16,239 --> 00:42:18,279
Speaker 1: it really is. I think it's the best way to

762
00:42:18,320 --> 00:42:22,920
Speaker 1: deal with the troll. Thank you. Oh yeah, there was.

763
00:42:23,000 --> 00:42:24,759
Speaker 1: So there was like an epic one. I feel like

764
00:42:24,760 --> 00:42:26,799
Speaker 1: a couple of years ago, may've been Sarah Silverman where

765
00:42:26,800 --> 00:42:28,840
Speaker 1: they're like, hey, man, sounds like you're going through some stuff,

766
00:42:28,880 --> 00:42:31,560
Speaker 1: and like a few replies later, the person just broke down.

767
00:42:31,560 --> 00:42:32,960
Speaker 1: I was like, hey, you know, to be honest, I

768
00:42:32,960 --> 00:42:36,040
Speaker 1: am kind of going through a rough spot. Nobody really

769
00:42:36,800 --> 00:42:42,000
Speaker 1: I haven't really thought about it like that. And you're like, see,

770
00:42:42,719 --> 00:42:48,239
Speaker 1: everyone's hurting. Everybody's hurting. Mm hmm. Has that great r

771
00:42:48,480 --> 00:42:57,240
Speaker 1: M song says everybody's hurting, everybody's hurting. Everybody's hurting most

772
00:42:57,280 --> 00:43:02,280
Speaker 1: of the time. All right, let's take a quick break.

773
00:43:02,320 --> 00:43:05,840
Speaker 1: We'll come back and talk about early two thousand's officially

774
00:43:05,920 --> 00:43:18,799
Speaker 1: coming back. And we're back, and actually, Alec, the thing

775
00:43:18,840 --> 00:43:21,680
Speaker 1: that made me think about this is you had pointed

776
00:43:21,719 --> 00:43:26,640
Speaker 1: out that Erica Adams is trying to get drill rap

777
00:43:26,800 --> 00:43:32,880
Speaker 1: videos banned from social media after some rappers were killed

778
00:43:33,080 --> 00:43:35,600
Speaker 1: in New York recently, and like it's a it's become

779
00:43:35,640 --> 00:43:38,400
Speaker 1: a high profile news story, and you I think I

780
00:43:38,520 --> 00:43:41,440
Speaker 1: had a tweet to the effect of, you know, Adams

781
00:43:41,520 --> 00:43:46,000
Speaker 1: is also planning on banning the opera because uh, you know,

782
00:43:46,280 --> 00:43:49,360
Speaker 1: people who engage in wage theft and tax evasion like

783
00:43:49,440 --> 00:43:53,880
Speaker 1: tends to go there. And so this guy DJ is

784
00:43:53,960 --> 00:43:57,440
Speaker 1: serious on Twitter and the lest you doubt his journalistic

785
00:43:57,440 --> 00:44:01,279
Speaker 1: Bonafide's came at you and was like, like, you can't

786
00:44:01,280 --> 00:44:03,120
Speaker 1: be serious. You think like we're gonna be able to

787
00:44:03,120 --> 00:44:07,359
Speaker 1: solve those problems, like the things that you know we've

788
00:44:07,400 --> 00:44:12,040
Speaker 1: been talking about on this podcast, like wage theft, caging humans,

789
00:44:12,080 --> 00:44:14,400
Speaker 1: lack of funding for schools and programs that invest in

790
00:44:14,400 --> 00:44:20,200
Speaker 1: the humanity of underserved communities. He dismissed as like, you know,

791
00:44:20,320 --> 00:44:24,680
Speaker 1: unrealistic or childish. And then and just like cloud chasing,

792
00:44:24,840 --> 00:44:28,120
Speaker 1: I guess and I actually a couple of weeks ago,

793
00:44:28,200 --> 00:44:30,600
Speaker 1: we had somebody on the show and we were like

794
00:44:30,680 --> 00:44:33,799
Speaker 1: they made some point to the effect of like that

795
00:44:33,840 --> 00:44:36,759
Speaker 1: the system is is fucked up, and you know that

796
00:44:36,960 --> 00:44:39,680
Speaker 1: kind of aligned with what we've been talking about, and

797
00:44:39,719 --> 00:44:41,680
Speaker 1: then like stopped him was like, I I know it

798
00:44:41,760 --> 00:44:45,600
Speaker 1: sounds childish, and I I think that's something that like

799
00:44:45,760 --> 00:44:49,759
Speaker 1: I also internalized at a certain point, is like just

800
00:44:50,440 --> 00:44:54,560
Speaker 1: like pointing out these very basic problems is like idealistic

801
00:44:54,719 --> 00:44:58,560
Speaker 1: and childish and like not something like the realistic people

802
00:44:58,680 --> 00:45:02,719
Speaker 1: are out here pointing out individual like acts of violence.

803
00:45:02,760 --> 00:45:04,440
Speaker 1: Like when you go to the guy who you are

804
00:45:04,520 --> 00:45:07,680
Speaker 1: arguing with on Twitter's thread, he like has these posts

805
00:45:07,719 --> 00:45:11,400
Speaker 1: of like like a video of a murder happening, and

806
00:45:11,440 --> 00:45:13,520
Speaker 1: it's like the bronx is out of control and like

807
00:45:13,640 --> 00:45:18,600
Speaker 1: so he's the the serious one while arguing for the

808
00:45:18,640 --> 00:45:23,000
Speaker 1: banning of rap music on social media, Like do you

809
00:45:23,080 --> 00:45:26,200
Speaker 1: do you run up against that a lot, like just

810
00:45:26,400 --> 00:45:30,520
Speaker 1: sort of the you're being unrealistic or childish all the time.

811
00:45:30,600 --> 00:45:32,640
Speaker 1: I mean, I think he's maybe a bad example because

812
00:45:32,640 --> 00:45:35,480
Speaker 1: he's not really a serious person because you know, like

813
00:45:36,280 --> 00:45:38,719
Speaker 1: he he really showed who he was not, just with

814
00:45:38,760 --> 00:45:40,440
Speaker 1: all the insults he was hurling at me as I

815
00:45:40,480 --> 00:45:43,480
Speaker 1: was trying to just like have a reasonable like debate.

816
00:45:43,600 --> 00:45:47,000
Speaker 1: But like he then said that Eric Adams is also

817
00:45:47,040 --> 00:45:49,640
Speaker 1: trying to address all these root causes, and then he

818
00:45:49,719 --> 00:45:53,280
Speaker 1: excited to Adams's crime plan, which is literally the exact opposite,

819
00:45:53,320 --> 00:45:56,160
Speaker 1: Like you know, Adams is trying to beef up uh

820
00:45:56,239 --> 00:45:58,920
Speaker 1: you know, rollback bail reform and beef up cops and

821
00:45:58,960 --> 00:46:02,279
Speaker 1: all this stuff. And not addressing things like healthcare and

822
00:46:02,360 --> 00:46:04,960
Speaker 1: housing and inequality, and so you know, this guy is

823
00:46:04,960 --> 00:46:06,880
Speaker 1: not a serious person. But I think what was really

824
00:46:06,880 --> 00:46:09,759
Speaker 1: revealing about the exchange, and which I do see a lot,

825
00:46:10,480 --> 00:46:15,080
Speaker 1: is politicians and sort of very comfortable people are constantly

826
00:46:15,120 --> 00:46:18,359
Speaker 1: trying to just to distract us from having the real

827
00:46:18,440 --> 00:46:24,440
Speaker 1: conversation about structural inequalities in our society, about divestment from

828
00:46:24,640 --> 00:46:29,480
Speaker 1: safe places to live and systems of care. And what

829
00:46:29,520 --> 00:46:32,680
Speaker 1: they want us to do is focus on like bad

830
00:46:32,760 --> 00:46:37,040
Speaker 1: individual bad apples, or well, this week, the problem is music,

831
00:46:37,440 --> 00:46:40,680
Speaker 1: so like we don't have to confront poverty and inequality

832
00:46:41,000 --> 00:46:45,279
Speaker 1: and deprivation and loneliness and and toxic masculinity and all

833
00:46:45,320 --> 00:46:47,840
Speaker 1: these other things that are sort of big social structural

834
00:46:47,920 --> 00:46:49,960
Speaker 1: problems all way, if you do is banned this type

835
00:46:49,960 --> 00:46:53,080
Speaker 1: of rap music, and tomorrow it's going to be all

836
00:46:53,120 --> 00:46:54,720
Speaker 1: we have to do is get rid of bail reform.

837
00:46:54,760 --> 00:46:55,920
Speaker 1: And the next day it's going to be all we

838
00:46:56,000 --> 00:46:57,560
Speaker 1: have to do is get rid of this district attorney

839
00:46:57,560 --> 00:47:00,320
Speaker 1: in Los Angeles, because everything was so much better the

840
00:47:00,400 --> 00:47:03,080
Speaker 1: last thirty years before we had this district attorney, right,

841
00:47:03,280 --> 00:47:05,960
Speaker 1: And every single day they point to some other little

842
00:47:06,000 --> 00:47:09,239
Speaker 1: thing that is not fixing the deeper structural problems in

843
00:47:09,239 --> 00:47:12,160
Speaker 1: our society. And to me, that kind of argument is

844
00:47:12,160 --> 00:47:14,640
Speaker 1: just such a joke. It's hard to even engage with

845
00:47:14,719 --> 00:47:16,799
Speaker 1: someone seriously about it. But there are a lot of

846
00:47:16,800 --> 00:47:19,279
Speaker 1: well meaning people that get trapped up in this, and

847
00:47:19,280 --> 00:47:22,360
Speaker 1: so I think it's important sometimes to treat this is

848
00:47:22,360 --> 00:47:24,560
Speaker 1: a serious argument and to point out sort of why

849
00:47:24,560 --> 00:47:28,200
Speaker 1: it's so flawed. Yeah, it's it's it's again. It's so

850
00:47:28,280 --> 00:47:33,319
Speaker 1: much easier to just say to to ignore like all

851
00:47:33,360 --> 00:47:35,520
Speaker 1: of the root causes like you're talking about, and just

852
00:47:35,600 --> 00:47:37,839
Speaker 1: turn it into this thing of like this like very

853
00:47:37,960 --> 00:47:42,000
Speaker 1: understandable evil that exists somewhere and it's this this drill wrap.

854
00:47:42,120 --> 00:47:45,120
Speaker 1: I mean that dishes are too violent and that's what's

855
00:47:45,160 --> 00:47:50,000
Speaker 1: causing all of this chaos. But again, people like the

856
00:47:50,040 --> 00:47:52,279
Speaker 1: example of people always fail to like really think about

857
00:47:52,320 --> 00:47:54,399
Speaker 1: two is like, well then how come you know what

858
00:47:54,400 --> 00:47:56,600
Speaker 1: what about why is there not a drill scene in

859
00:47:56,680 --> 00:47:59,080
Speaker 1: Beverly Hills? You know, why is there not a drill

860
00:47:59,120 --> 00:48:02,040
Speaker 1: scene in these more affluent areas? And what would happen then?

861
00:48:02,080 --> 00:48:04,640
Speaker 1: Would that would those people suddenly be overtaken by the

862
00:48:04,719 --> 00:48:07,960
Speaker 1: demonic drill music? And then begin killing each other or

863
00:48:08,040 --> 00:48:12,480
Speaker 1: is it about the outcomes that people are offered based

864
00:48:12,520 --> 00:48:14,759
Speaker 1: on their their place in this and like in this

865
00:48:14,800 --> 00:48:16,440
Speaker 1: sort of cast system that we have in the in

866
00:48:16,440 --> 00:48:19,479
Speaker 1: the country, and rather than saying, like you know, when

867
00:48:19,480 --> 00:48:23,680
Speaker 1: people are deprived and desperate, we we begin to do

868
00:48:23,840 --> 00:48:28,560
Speaker 1: things that have to ensure our survival and to distill

869
00:48:28,600 --> 00:48:32,440
Speaker 1: it too well, these lyrics are too hot. Again. Everything

870
00:48:32,560 --> 00:48:35,640
Speaker 1: is just sort of about avoiding the real solution to something,

871
00:48:35,680 --> 00:48:38,040
Speaker 1: which is we need to address rampant inequality. We need

872
00:48:38,080 --> 00:48:41,319
Speaker 1: to address this stuff. The the greed of the wealthy

873
00:48:41,440 --> 00:48:45,040
Speaker 1: has only exacerbated these things. But again, I think that's

874
00:48:45,120 --> 00:48:47,799
Speaker 1: much easier for people who probably feel that, you know,

875
00:48:47,880 --> 00:48:51,120
Speaker 1: their livelihood or something is at risk with some kind

876
00:48:51,120 --> 00:48:55,000
Speaker 1: of increased equality in society. I think those kinds of

877
00:48:55,040 --> 00:48:57,799
Speaker 1: explanations help those people wrap their minds around it, because like, well,

878
00:48:57,840 --> 00:48:59,880
Speaker 1: certainly it's not this other thing that I've been completely

879
00:49:00,000 --> 00:49:03,200
Speaker 1: earning a blind eye to my whole life, drill music.

880
00:49:03,760 --> 00:49:06,560
Speaker 1: And if you think about yeah, I believe drill music

881
00:49:06,640 --> 00:49:09,360
Speaker 1: was around, uh even in the sixties, you know what

882
00:49:09,400 --> 00:49:13,239
Speaker 1: I mean, Like what why is it always just like changing, Uh,

883
00:49:13,280 --> 00:49:16,440
Speaker 1: this evolving sort of like fake target that you know,

884
00:49:16,520 --> 00:49:19,600
Speaker 1: allows people just to avoid again, like always avoiding the

885
00:49:19,920 --> 00:49:22,239
Speaker 1: part of the conversation, which is, yeah, we have to

886
00:49:22,360 --> 00:49:25,160
Speaker 1: we have to fundamentally change a lot of things. And

887
00:49:25,280 --> 00:49:27,400
Speaker 1: there's something about this guy that I just wanted to

888
00:49:27,520 --> 00:49:32,319
Speaker 1: underline because he's a Pulitzer Center grantee, which I don't

889
00:49:32,360 --> 00:49:34,680
Speaker 1: really know what that means, but it sounds impressive, and

890
00:49:34,760 --> 00:49:38,799
Speaker 1: like he has a picture, like his Twitter header is

891
00:49:38,840 --> 00:49:41,480
Speaker 1: like a picture of him like doing war reporting and

892
00:49:41,560 --> 00:49:45,040
Speaker 1: like being on the ground and like being there for

893
00:49:45,280 --> 00:49:48,000
Speaker 1: violence happening in other countries, and then he has this

894
00:49:48,080 --> 00:49:50,640
Speaker 1: post of like a video of somebody being murdered. And

895
00:49:51,360 --> 00:49:55,760
Speaker 1: the degree to which like it's ingrained in our values

896
00:49:55,800 --> 00:49:59,320
Speaker 1: and the values that I like grew up with, where

897
00:49:59,400 --> 00:50:02,640
Speaker 1: like the you know, action movies are about the police

898
00:50:02,840 --> 00:50:06,000
Speaker 1: and like doing like real serious things and like serious

899
00:50:06,040 --> 00:50:09,920
Speaker 1: people taking care of serious problems, and like that that

900
00:50:10,080 --> 00:50:15,839
Speaker 1: sort of idea that you're serious because you were kind

901
00:50:15,840 --> 00:50:21,919
Speaker 1: of focusing on the like very short term like cause

902
00:50:21,960 --> 00:50:25,480
Speaker 1: and effect of like violent conflict like that that is

903
00:50:26,239 --> 00:50:30,240
Speaker 1: the serious thing to do, and then actually talking about

904
00:50:30,280 --> 00:50:33,919
Speaker 1: structural issues is like the not serious thing like that.

905
00:50:34,320 --> 00:50:38,120
Speaker 1: I don't know, it's just especially now with social media,

906
00:50:38,480 --> 00:50:42,080
Speaker 1: which I feel nine years old every time I complain

907
00:50:42,120 --> 00:50:47,080
Speaker 1: about social media. But like it is so like every

908
00:50:47,120 --> 00:50:50,359
Speaker 1: aspect of this value system of like you know, being

909
00:50:50,400 --> 00:50:54,879
Speaker 1: able to over index whatever problem you want to exaggerate,

910
00:50:55,480 --> 00:50:59,880
Speaker 1: is like so deeply ingrained in like how how we

911
00:51:00,040 --> 00:51:03,520
Speaker 1: communicate and get information that I'm I don't know, Like,

912
00:51:03,640 --> 00:51:07,439
Speaker 1: I is there anything that makes you feel hopeful out

913
00:51:07,920 --> 00:51:11,920
Speaker 1: like about the struggle that you're kind of engaged? I

914
00:51:11,960 --> 00:51:15,920
Speaker 1: think it's easy to feel hopeless because the problems in

915
00:51:15,920 --> 00:51:19,360
Speaker 1: front of us seems so daunting and and you've got

916
00:51:19,800 --> 00:51:23,480
Speaker 1: very powerful interests who not only are controlling how all

917
00:51:23,600 --> 00:51:26,000
Speaker 1: this money is being spent all these policies, but they're

918
00:51:26,000 --> 00:51:29,920
Speaker 1: also you know, the ones who own the media system

919
00:51:30,000 --> 00:51:32,000
Speaker 1: in which these discussions are being had. But at the

920
00:51:32,040 --> 00:51:36,520
Speaker 1: same time, there's a whole new generation of people that

921
00:51:36,640 --> 00:51:40,680
Speaker 1: are seeing through this stuff, that are having conversations that

922
00:51:40,719 --> 00:51:43,120
Speaker 1: we just weren't having ten years ago. And you know,

923
00:51:43,120 --> 00:51:45,880
Speaker 1: when I was a younger lawyer just starting out in

924
00:51:45,920 --> 00:51:48,120
Speaker 1: this space, there was really no one talking about the

925
00:51:48,200 --> 00:51:51,719
Speaker 1: need to shrink the size of the com punishment bureocracy,

926
00:51:51,800 --> 00:51:54,920
Speaker 1: to take money away from police departments, to invest in

927
00:51:54,920 --> 00:51:57,799
Speaker 1: in communities of care, no one in in sort of

928
00:51:57,800 --> 00:52:00,480
Speaker 1: these elite spaces. That is obviously that people in these

929
00:52:00,480 --> 00:52:02,680
Speaker 1: communities that are directly targeted. I've been talking about this,

930
00:52:02,760 --> 00:52:06,759
Speaker 1: you know, from the very beginning, but there's a I

931
00:52:06,800 --> 00:52:09,719
Speaker 1: think one of the reasons we've seen this incredible pushback

932
00:52:09,760 --> 00:52:13,480
Speaker 1: from the police and from these media interests and is

933
00:52:13,600 --> 00:52:17,480
Speaker 1: precisely because they were threatened by a lot of the

934
00:52:17,680 --> 00:52:20,680
Speaker 1: growing social movement to change the way our society thinks

935
00:52:20,719 --> 00:52:23,480
Speaker 1: about its investment priorities. And so I think that is

936
00:52:23,520 --> 00:52:26,840
Speaker 1: a positive. We We are definitely seeing a movement of

937
00:52:26,840 --> 00:52:29,320
Speaker 1: people led by the people that are most targeted by

938
00:52:29,920 --> 00:52:34,200
Speaker 1: these systems of of human caging and surveillance and brutality

939
00:52:34,239 --> 00:52:38,759
Speaker 1: and violence, and that's encouraging. And we're in a reactionary

940
00:52:38,760 --> 00:52:42,239
Speaker 1: backlash right now, but the thing that it's reacting to

941
00:52:42,520 --> 00:52:44,759
Speaker 1: is is a very encouraging set of developments. And I

942
00:52:44,800 --> 00:52:47,799
Speaker 1: think it's very very important that anyone interested in this

943
00:52:48,560 --> 00:52:50,640
Speaker 1: comes together with other people who are interested in it

944
00:52:50,840 --> 00:52:53,719
Speaker 1: and starts getting involved in their own community, whether it's

945
00:52:53,719 --> 00:52:56,640
Speaker 1: in mutual aid, whether it's in bail funds, whether it's

946
00:52:56,680 --> 00:53:02,280
Speaker 1: in organizing around environmental issue, health issues, housing issues, criminal

947
00:53:02,320 --> 00:53:07,480
Speaker 1: punishment system issues, mutual aid like efforts, immigration issues. There's

948
00:53:07,520 --> 00:53:10,520
Speaker 1: so many ways to plug in that, you know, around

949
00:53:10,520 --> 00:53:14,279
Speaker 1: something that you're personally really passionate about. That all are

950
00:53:14,480 --> 00:53:17,560
Speaker 1: sort of factoring into us building the systems of care

951
00:53:17,640 --> 00:53:20,040
Speaker 1: that we need that are going to replace this horrific

952
00:53:20,040 --> 00:53:23,520
Speaker 1: system of violence. And I think that's all positive. Yeah,

953
00:53:23,520 --> 00:53:26,279
Speaker 1: I mean yeah, Like to your point, it's clear that

954
00:53:27,239 --> 00:53:31,719
Speaker 1: the that like a moment of clarity for people over

955
00:53:31,840 --> 00:53:34,319
Speaker 1: in the summer of where many people are just like,

956
00:53:34,360 --> 00:53:37,920
Speaker 1: hold on, yeah, is this the right thing? Is this

957
00:53:38,120 --> 00:53:41,040
Speaker 1: the way we get out of this that scared the

958
00:53:41,080 --> 00:53:44,680
Speaker 1: ship out of law enforcement clearly because we've seen them

959
00:53:44,719 --> 00:53:48,439
Speaker 1: pour every single thing they can into countering the sort

960
00:53:48,440 --> 00:53:51,000
Speaker 1: of clarity that something that many people are beginning to

961
00:53:51,120 --> 00:53:53,040
Speaker 1: arrive to, which is sort of like, yeah, I'm not

962
00:53:53,080 --> 00:53:55,560
Speaker 1: sure that this partial system is the way that we

963
00:53:55,719 --> 00:53:58,920
Speaker 1: solve things. It sounds like we need to actually help

964
00:53:59,080 --> 00:54:03,760
Speaker 1: people rather than solving the failures of our capitalist, capitalist

965
00:54:03,840 --> 00:54:07,880
Speaker 1: society by just investing more and punishing the poor. I

966
00:54:07,920 --> 00:54:10,480
Speaker 1: think people are begin to be like, that doesn't quite connect.

967
00:54:10,520 --> 00:54:13,399
Speaker 1: And yet when you see them this all in thing

968
00:54:13,440 --> 00:54:16,000
Speaker 1: of like man, the shoplifting, this that that that that's

969
00:54:16,040 --> 00:54:19,239
Speaker 1: the drill music. It does. You can tell that they're

970
00:54:19,239 --> 00:54:21,640
Speaker 1: in a much different posture than before, when I think

971
00:54:21,640 --> 00:54:24,520
Speaker 1: people were just much more willing to accept whatever the

972
00:54:24,600 --> 00:54:26,440
Speaker 1: local news said and just be like yeah, I mean

973
00:54:26,440 --> 00:54:28,960
Speaker 1: if that's the cops say, yeah, go ahead. And now

974
00:54:29,000 --> 00:54:33,000
Speaker 1: I think with story after story about abuses that occur

975
00:54:33,120 --> 00:54:36,360
Speaker 1: in those in the legal system, it's it's hard to

976
00:54:36,520 --> 00:54:38,759
Speaker 1: I don't know how you counter that, aside from just

977
00:54:39,200 --> 00:54:42,920
Speaker 1: going further into your bad habits of stoking more fear

978
00:54:43,480 --> 00:54:46,719
Speaker 1: without really being able to like present the people with

979
00:54:46,760 --> 00:54:50,160
Speaker 1: actual winds that law enforcement has been behind, you know,

980
00:54:50,239 --> 00:54:52,160
Speaker 1: like they're not out here being like, hey, you know

981
00:54:52,239 --> 00:54:55,200
Speaker 1: what we revamped. We turned half of our force into

982
00:54:55,239 --> 00:54:58,120
Speaker 1: like first responders for people who are in need of

983
00:54:58,160 --> 00:55:00,960
Speaker 1: like a mental health intervene, shin and things like that.

984
00:55:01,080 --> 00:55:03,319
Speaker 1: And look at the crime it's gone down. Baby, every

985
00:55:03,400 --> 00:55:05,680
Speaker 1: You could leave a bike out and nobody's gonna steal

986
00:55:05,680 --> 00:55:08,040
Speaker 1: it because they're just unable to do that, because that

987
00:55:08,440 --> 00:55:10,960
Speaker 1: the way the system works for them is no, we

988
00:55:11,000 --> 00:55:13,280
Speaker 1: just have to keep brutalizing poor people. That's the only

989
00:55:13,320 --> 00:55:17,000
Speaker 1: thing this thing is set up to do. So we're

990
00:55:17,040 --> 00:55:18,799
Speaker 1: just gonna turn up the heat on that, and I

991
00:55:18,800 --> 00:55:21,319
Speaker 1: think it has this effective on one side a lot

992
00:55:21,360 --> 00:55:23,239
Speaker 1: of people. Really. I see it all the time people

993
00:55:23,280 --> 00:55:25,000
Speaker 1: I used to go to high school with on Instagram

994
00:55:25,040 --> 00:55:27,360
Speaker 1: who are like looking at taking a picture of a

995
00:55:27,440 --> 00:55:29,520
Speaker 1: dumpster that has graffiti on it, and you can tell

996
00:55:29,520 --> 00:55:32,200
Speaker 1: how like cop brained they are because they're like, oh,

997
00:55:32,239 --> 00:55:35,120
Speaker 1: my gosh, do I need to get a gun now? Yeah,

998
00:55:35,200 --> 00:55:38,360
Speaker 1: there's there's graffiti on this dumpster behind my office building.

999
00:55:38,760 --> 00:55:40,680
Speaker 1: And I see, this is what's happening right now because

1000
00:55:40,680 --> 00:55:43,719
Speaker 1: people are running just out here doing whatever they want

1001
00:55:43,760 --> 00:55:46,360
Speaker 1: because there's no law enforcement, while many others are just

1002
00:55:46,360 --> 00:55:48,960
Speaker 1: sort of like no, no, I All I see actually

1003
00:55:49,040 --> 00:55:52,320
Speaker 1: is a lot of pain suffering that has gone unaddressed,

1004
00:55:52,680 --> 00:55:56,440
Speaker 1: and that to me is a more pressing concern than oh,

1005
00:55:56,600 --> 00:55:58,719
Speaker 1: do we have to lock up you know, the mock

1006
00:55:58,840 --> 00:56:03,879
Speaker 1: three razors, the fucking pharmacy, and so yeah, like I yes,

1007
00:56:04,160 --> 00:56:07,319
Speaker 1: with all the with all the momentum, clearly that you know,

1008
00:56:07,400 --> 00:56:10,400
Speaker 1: this narrative that's been introduced by you know, the powers

1009
00:56:10,400 --> 00:56:13,200
Speaker 1: that be in law enforcement, et cetera, there is like

1010
00:56:13,640 --> 00:56:16,480
Speaker 1: there's just that little bit of clarity that you're beginning

1011
00:56:16,480 --> 00:56:18,840
Speaker 1: to see a lot of like people sort of step

1012
00:56:18,880 --> 00:56:23,560
Speaker 1: into as it relates to like what's actually playing our country.

1013
00:56:23,640 --> 00:56:26,640
Speaker 1: I mean, I I think it's worth talking about the

1014
00:56:26,640 --> 00:56:30,759
Speaker 1: the convoy that's happened up in Canada because like they

1015
00:56:31,000 --> 00:56:36,640
Speaker 1: without anyout any coherent worldview other than like sort of

1016
00:56:36,680 --> 00:56:39,840
Speaker 1: an underlying white supremacy that everybody seems to be on

1017
00:56:39,880 --> 00:56:45,560
Speaker 1: board with. They were pretty successful and like making everyone's

1018
00:56:45,640 --> 00:56:49,200
Speaker 1: lives miserable and like grinding everything to a halt for

1019
00:56:49,200 --> 00:56:51,360
Speaker 1: for a number of days. And they definitely have the

1020
00:56:51,360 --> 00:56:57,600
Speaker 1: built in advantage of the police also being on board

1021
00:56:57,640 --> 00:57:00,399
Speaker 1: with the fact that they're waving Nazi flags. I feel

1022
00:57:00,400 --> 00:57:04,040
Speaker 1: like if you replace those flags with Black Lives Matter flags,

1023
00:57:04,320 --> 00:57:07,440
Speaker 1: we're we're dealing with a whole different situation. But so,

1024
00:57:07,560 --> 00:57:10,160
Speaker 1: I mean, the latest in this story is that Trudeau

1025
00:57:10,680 --> 00:57:14,879
Speaker 1: is invoking the Emergencies Act, which is the Canadian Act

1026
00:57:15,000 --> 00:57:19,919
Speaker 1: that was used to suppress people's rights during World War

1027
00:57:20,000 --> 00:57:24,280
Speaker 1: One world War two in internment camps, and then in

1028
00:57:25,280 --> 00:57:28,240
Speaker 1: they reshaped the War Act like give it a little

1029
00:57:28,240 --> 00:57:32,640
Speaker 1: bit more congressional oversight, but it's it's a fair it's

1030
00:57:32,680 --> 00:57:37,680
Speaker 1: a pretty problematic, like and scary use of force that

1031
00:57:37,760 --> 00:57:41,800
Speaker 1: the government is like kind of coming in and using

1032
00:57:41,960 --> 00:57:45,720
Speaker 1: or like invoking I guess, and I'm just like wondering,

1033
00:57:46,760 --> 00:57:50,880
Speaker 1: I don't know, do like is there any part like

1034
00:57:51,000 --> 00:57:56,280
Speaker 1: the movement for Progress and social justice? Like should we

1035
00:57:56,360 --> 00:58:01,480
Speaker 1: be looking at like these sorts of actions that actually

1036
00:58:01,520 --> 00:58:04,840
Speaker 1: like fucking disrupt an entire city, Like this is not

1037
00:58:04,920 --> 00:58:07,720
Speaker 1: a well thought out plan, but it's just something that's

1038
00:58:07,720 --> 00:58:11,040
Speaker 1: happening in the news. And I'm just like wondering without

1039
00:58:11,160 --> 00:58:16,760
Speaker 1: them having any coherent argument or complaint, they are succeeding.

1040
00:58:17,040 --> 00:58:20,640
Speaker 1: Like if what if a you know, the movement to

1041
00:58:21,720 --> 00:58:25,560
Speaker 1: end wage theft, like did something like this a thing

1042
00:58:25,640 --> 00:58:30,080
Speaker 1: that actually affects more truckers than the six percent of

1043
00:58:30,120 --> 00:58:36,480
Speaker 1: the anti vaxor truckers in in Canada? Like why why

1044
00:58:36,520 --> 00:58:39,160
Speaker 1: don't we see more things like that? Should we see

1045
00:58:39,160 --> 00:58:43,720
Speaker 1: more things like that where it's like a very disruptive, um,

1046
00:58:44,480 --> 00:58:49,680
Speaker 1: you know, behavior like this? Absolutely, I mean this is

1047
00:58:50,160 --> 00:58:55,600
Speaker 1: why you've seen states, particularly conservative states across the country

1048
00:58:56,800 --> 00:59:01,480
Speaker 1: criminalized to extraordinary degree the kinds of direct actions. So

1049
00:59:01,520 --> 00:59:03,680
Speaker 1: now if you did this in a number of states

1050
00:59:03,680 --> 00:59:07,120
Speaker 1: in the US, you could be hit with huge felony charges,

1051
00:59:07,320 --> 00:59:09,800
Speaker 1: go to prison for life, you'd be called a terrorist.

1052
00:59:10,040 --> 00:59:13,360
Speaker 1: The federal government can prosecute. You know, they just prosecuted

1053
00:59:14,200 --> 00:59:18,280
Speaker 1: two women in Iowa for you know, disrupting climate infrastructure,

1054
00:59:18,320 --> 00:59:23,160
Speaker 1: and they prosecuted them as terrorists. And this is when,

1055
00:59:23,240 --> 00:59:26,480
Speaker 1: when it's being done on the left wing side, all

1056
00:59:26,520 --> 00:59:30,360
Speaker 1: of the incredible bureaucratic apparatus of state violence is a

1057
00:59:30,440 --> 00:59:33,160
Speaker 1: arraign against you, and you're called a terrorist, whether it's

1058
00:59:33,360 --> 00:59:36,720
Speaker 1: people who are trying to disrupt animal agriculture or or

1059
00:59:37,520 --> 00:59:40,840
Speaker 1: you know, toxic fossil fuel infrastructure. And there's a really

1060
00:59:41,240 --> 00:59:43,919
Speaker 1: interesting and thought provoking new book called How to Blow

1061
00:59:44,000 --> 00:59:49,640
Speaker 1: Up a Pipeline by Swedish climate activists and philosopher, which essentially,

1062
00:59:49,880 --> 00:59:52,479
Speaker 1: you know, makes the case that you just made, Jack,

1063
00:59:52,960 --> 00:59:55,400
Speaker 1: but makes it really beautifully. It's really fun and short

1064
00:59:55,480 --> 00:59:58,200
Speaker 1: read even more beautifully than I just made it. I

1065
00:59:58,200 --> 01:00:01,800
Speaker 1: thought it really now, but well obviously not as stuttering

1066
01:00:01,920 --> 01:00:05,080
Speaker 1: and uh and pauses that thought. I thought I really

1067
01:00:05,160 --> 01:00:09,680
Speaker 1: nailed it. Yeah, sorry, notice it's a it's a I

1068
01:00:09,720 --> 01:00:11,600
Speaker 1: think you should send him some notes and maybe the

1069
01:00:11,600 --> 01:00:14,160
Speaker 1: next version of the book can be can be a

1070
01:00:14,200 --> 01:00:18,280
Speaker 1: little bit more eloquent. But How to Glop of Pipeline

1071
01:00:18,320 --> 01:00:22,120
Speaker 1: is a really inspiring read about the need for direct

1072
01:00:22,160 --> 01:00:27,480
Speaker 1: action on the level that actually confronts the enormity of

1073
01:00:27,520 --> 01:00:32,160
Speaker 1: the ecological disaster and collapse that we're about to confront

1074
01:00:32,280 --> 01:00:36,560
Speaker 1: as a sort of a global world. And and you know,

1075
01:00:36,960 --> 01:00:40,800
Speaker 1: the more that starts to happen, the more repression we're

1076
01:00:40,800 --> 01:00:43,600
Speaker 1: going to see, the more things like what true Joe

1077
01:00:43,680 --> 01:00:47,840
Speaker 1: just did are going to be arrayed against anyone remotely

1078
01:00:47,880 --> 01:00:51,640
Speaker 1: pushing environmental or social justice. And it's going to be very,

1079
01:00:51,760 --> 01:00:55,920
Speaker 1: very scary, especially as significant migration of hundreds and millions

1080
01:00:55,920 --> 01:00:59,680
Speaker 1: of people starts to become sort of the monthly norm.

1081
01:00:59,760 --> 01:01:04,520
Speaker 1: Right the Yeah, I guess any anything that somebody is

1082
01:01:04,640 --> 01:01:08,680
Speaker 1: learning from this should be taken with a like like,

1083
01:01:08,760 --> 01:01:11,080
Speaker 1: I think it has been allowed to go on this

1084
01:01:11,200 --> 01:01:15,560
Speaker 1: long because it doesn't have any coherent like agenda or

1085
01:01:15,760 --> 01:01:19,880
Speaker 1: argument that is like picking up steam with anybody that

1086
01:01:19,880 --> 01:01:22,640
Speaker 1: that I can tell other than just white supremacy. Like,

1087
01:01:23,280 --> 01:01:26,080
Speaker 1: so I feel like they're like, yeah, sure, they hang out,

1088
01:01:26,360 --> 01:01:29,160
Speaker 1: you know, but take a picture there. Their examples were

1089
01:01:29,200 --> 01:01:33,640
Speaker 1: the Ottawa police were letting the truckers the these convoy

1090
01:01:33,720 --> 01:01:36,959
Speaker 1: protesters take selfies in the back of their squad car

1091
01:01:37,240 --> 01:01:41,240
Speaker 1: and then so that they could spread misinformation that they

1092
01:01:41,240 --> 01:01:44,640
Speaker 1: had been arrested to like get people outraged, but of

1093
01:01:44,680 --> 01:01:47,600
Speaker 1: course the place weren't arresting. Yeah. Well, I mean it's

1094
01:01:47,600 --> 01:01:49,200
Speaker 1: telling when you're in the back of a squad car

1095
01:01:49,280 --> 01:01:51,680
Speaker 1: with no handcuffs on, when you're when you're looking out

1096
01:01:51,680 --> 01:01:54,280
Speaker 1: to that and they're like, help, no, that's that's not

1097
01:01:54,440 --> 01:01:57,080
Speaker 1: what's happening there. And you know it's funny too, like

1098
01:01:57,120 --> 01:01:59,280
Speaker 1: they talk a lot about, you know, they don't want

1099
01:01:59,280 --> 01:02:01,000
Speaker 1: to send in the middle terry or they don't want

1100
01:02:01,040 --> 01:02:03,720
Speaker 1: to really start you know, rounding people up like they

1101
01:02:03,720 --> 01:02:08,280
Speaker 1: would uh, you know, protests that would have involved disenfranchised

1102
01:02:08,280 --> 01:02:12,280
Speaker 1: people of color, First Nations people, But you know, there's

1103
01:02:12,320 --> 01:02:15,320
Speaker 1: been this insistence that they're they're don't want this imagery

1104
01:02:15,360 --> 01:02:21,800
Speaker 1: of people actually being suppressed and being brutalized by the state,

1105
01:02:22,200 --> 01:02:24,160
Speaker 1: And I you know, part of me is like, well,

1106
01:02:24,200 --> 01:02:28,160
Speaker 1: that's really just for them, because most people who are protesting,

1107
01:02:28,600 --> 01:02:30,880
Speaker 1: they don't need to be brutalized by the police at

1108
01:02:30,880 --> 01:02:33,840
Speaker 1: a protest to get in touch with their oppression. Most

1109
01:02:33,840 --> 01:02:37,200
Speaker 1: people already are. Whereas this serves a very much visual

1110
01:02:37,360 --> 01:02:39,920
Speaker 1: narrative to be like you see, even because if what

1111
01:02:40,000 --> 01:02:43,080
Speaker 1: we're talking about is total vaporware and bullshit. But if

1112
01:02:43,080 --> 01:02:45,120
Speaker 1: they get out here and start arresting us, then we

1113
01:02:45,160 --> 01:02:48,760
Speaker 1: can add a little bit more emotional energy to this

1114
01:02:49,280 --> 01:02:52,080
Speaker 1: to help, you know, kind of build some momentum, because

1115
01:02:52,120 --> 01:02:53,560
Speaker 1: at the end of the day, like you're saying, it's

1116
01:02:53,600 --> 01:02:57,320
Speaker 1: not many people are confused, you know, especially if you're

1117
01:02:57,320 --> 01:03:00,840
Speaker 1: outside of this anti vax truck or con void world

1118
01:03:00,880 --> 01:03:03,680
Speaker 1: where they're like, what are these fucking people doing? Like

1119
01:03:04,160 --> 01:03:07,880
Speaker 1: this is nonsense, But you know, they're very much in

1120
01:03:08,440 --> 01:03:11,760
Speaker 1: the in pursuit of those visuals to help sort of

1121
01:03:11,800 --> 01:03:15,840
Speaker 1: solidify or validate their sort of victim narrative, which is

1122
01:03:15,920 --> 01:03:19,080
Speaker 1: just truly not there, especially not when you're hugging the

1123
01:03:19,120 --> 01:03:22,360
Speaker 1: police when they're supposed to be clearing you out. I mean, like,

1124
01:03:23,080 --> 01:03:24,880
Speaker 1: and I think that's the other part. Two. It's very

1125
01:03:24,880 --> 01:03:27,960
Speaker 1: hard for people who you know, have somewhat of a

1126
01:03:28,120 --> 01:03:30,880
Speaker 1: brain to look at that and go, that's weird. They

1127
01:03:31,000 --> 01:03:35,320
Speaker 1: hug those protesters, but are firing rubber bullets straight into

1128
01:03:35,360 --> 01:03:38,040
Speaker 1: the eyes of the other people, and they're not. They

1129
01:03:38,080 --> 01:03:44,840
Speaker 1: weren't holding up global commerce. All right, that's gonna do

1130
01:03:44,920 --> 01:03:49,200
Speaker 1: it for this week's Weekly Zeitguys, Please like and review

1131
01:03:49,240 --> 01:03:53,280
Speaker 1: the show. If you like the show, uh means the

1132
01:03:53,280 --> 01:03:57,480
Speaker 1: world to Miles. He he needs your validation. Folks. I

1133
01:03:57,520 --> 01:04:00,640
Speaker 1: hope you're having a great weekend and I will talk

1134
01:04:00,680 --> 01:04:41,480
Speaker 1: to you Monday. By