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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 uh NonStop

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

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Speaker 1: is the Weekly Zeitgeist. We are thrilled to have in

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Speaker 1: the studio two wonderful podcasters as well as co authors.

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Speaker 1: Maybe you know them from their podcast By the Book,

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Speaker 1: maybe you've heard about their book How to Be Fine,

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Speaker 1: What we learned from Living by the Rules and fifty

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Speaker 1: self help books and if you like self help books,

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Speaker 1: great great topics to talk about because I think all

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Speaker 1: of us we look in there and say, does this

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Speaker 1: stuff work? What if I really followed to the letter

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Speaker 1: of the law? Guess what they did that? And also

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Speaker 1: you can hear them on the latest show for Romance

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Speaker 1: road Test again trying out different kinds of advice, seeing

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Speaker 1: what the what the results are. Please welcome to the microphones.

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Speaker 1: We have Kristin Mineser and Geletta Greenberg. Hello, are so

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Speaker 1: excited to be here. Thank you for thank you for

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Speaker 1: happy to have you. We feel like we should sing,

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Speaker 1: but we're not gonna. That's no pressure. Don't like that

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Speaker 1: is such a good singer, by the way. She just

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Speaker 1: come up with, like, you know, a song from our

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Speaker 1: youth and and then make podcasting lyrics about it on

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Speaker 1: the fly. Linda, you got you got, you got some pipes. No,

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Speaker 1: he's being modest. She has a beautiful boy. Okay, what's

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Speaker 1: your karaoke song? What's like your number one karaoke? What's

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Speaker 1: your go to? Oh? That's hard. I'm always good to

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Speaker 1: do nine to five because people get impressed if you

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Speaker 1: can keep up with all of like the fast lyrics,

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Speaker 1: which I usually can depending on my level of inebriation. Okay, yeah, yeah,

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Speaker 1: those are chops right there. It's the end of the

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Speaker 1: world as we know it. For the other fast lyrics

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Speaker 1: to wow, yeah, TikTok is hard. Also, oh yeah it

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Speaker 1: does go. What about you, Christian? Do you have a

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Speaker 1: Do you have a go to? Absolutely? My go to

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Speaker 1: is always Raspberry Bray by my hometown hero Prince. He's

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Speaker 1: from my hometown Minneapolis. One thing I really like about

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Speaker 1: that song is you can kind of talk half of

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Speaker 1: it instead of singing. Yeah, not a good singer. I

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Speaker 1: can just you know, talking time at five and dime.

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Speaker 1: Mr McGhee hear that Wow whoa yeah, expert singer ripped

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Speaker 1: out in swag. Oh wait, so where are you both

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Speaker 1: coming to us from? Are you in Minneapolis or what

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Speaker 1: cities are we in collectively? Right now? We are both

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Speaker 1: in Brooklyn, not too far apart from each other, but

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Speaker 1: in our respective homes. Okay, fantastic, shout out Brooklyn man,

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Speaker 1: we've had yesterday or on Friday's episode two, we have

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Speaker 1: some people from seven Brooklyn in the house and also beca.

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Speaker 1: We look we're a national international podcast obviously, um, but

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Speaker 1: we're out here, and so tell us a little bit

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Speaker 1: about your newest show, because, like, as someone who I

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Speaker 1: you know, I used to read a lot of self

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Speaker 1: help books, like in college, because you know, I thought

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Speaker 1: that would make up for never going to therapy. It

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Speaker 1: turns out therapy is more effective than self help books

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Speaker 1: in most instances. But when I saw the premise of this,

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Speaker 1: I'm like, okay, what I like you. I'm like you,

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Speaker 1: You're You're in my similar mindset of like, let's test

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Speaker 1: the advice, let's see what is actionable. Give us a

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Speaker 1: little bit of a taste of what's going on with

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Speaker 1: the new show. Yeah, so Romance road Test, we rather

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Speaker 1: than reading full self help books cover to cover four

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Speaker 1: fifty pages of how to improve your life. We just

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Speaker 1: snack on short articles, tech talk videos, uh, YouTube videos

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Speaker 1: and so on that are dispensing relationship hacks, things that

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Speaker 1: we find in women's magazines and so on, and we

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Speaker 1: apply them to our relationships. So everything from do something

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Speaker 1: terrifying together, to assemble flat pack furniture, to get closer

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Speaker 1: with your partner, introduce each other to your hobbies, read

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Speaker 1: smut to each other. We do all of the things.

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Speaker 1: Sex every day for a week, yes, all of that,

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Speaker 1: grooming each other, grooming each other, Oh, yes, you don't

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Speaker 1: have to. And then you get to eavesdrop on it

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Speaker 1: because it's kind of an audio reality show, so we

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Speaker 1: tape ourselves laughing, crying, and fighting through every one of

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Speaker 1: these hackszing, is there is there one like? Because like

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Speaker 1: you typically this is kind of like the stuff you

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Speaker 1: focused on was like taking knowledge or self help things

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Speaker 1: or relationship advice. What's been like the most surprising thing

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Speaker 1: that you're like, this is the this will never work

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Speaker 1: and you're like, oh they were right about that. Damn

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Speaker 1: that really worked. I mean I don't want to speak

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Speaker 1: for you, Kristen, but I'm going to but I would

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Speaker 1: say trying to I would say trying something terrifying together

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Speaker 1: was was a surprising thrill, shall I say, like it

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Speaker 1: was definitely something I went into reluctantly and was like,

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Speaker 1: this will not work. But like you know, when your

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Speaker 1: nerves are are up, like your endorphins are up, and

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Speaker 1: then you guys are like bonded and like jittery together

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Speaker 1: and it's like yeah, right, yeah. It supposedly simulates a

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Speaker 1: lot of the same feelings you have when you're first

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Speaker 1: falling in love with someone. The uncertainty, the where do

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Speaker 1: we stand? We're not on firm ground, what's happening here?

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Speaker 1: And then also the shared trauma of surviving that terrifying

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Speaker 1: ps trauma. One of the only hacks that we did

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Speaker 1: that both Joe Lenta and her partner and I and

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Speaker 1: my partner. It was one of the only ones that

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Speaker 1: we all universally felt was great and so and that's relative, right,

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Speaker 1: because for me, something terrifying would be to, you know,

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Speaker 1: go to a Lulu Lemon opening butterfing, like, how do

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Speaker 1: you like? What are the parameters? Like if someone who's

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Speaker 1: listening right now says, what, what's this sort of sliding

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Speaker 1: scale to say this is terrifying, this is adequately terrifying

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Speaker 1: to improvement. I was gonna be my question, what is

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Speaker 1: the terrifying thing if it's just for us? It was

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Speaker 1: just like what we could agree on as a couple, Like,

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Speaker 1: because you know, even, yeah, the stuff that terrifies you

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Speaker 1: may not necessarily terrify your partner, but you gotta find

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Speaker 1: like a bit of a middle ground and like, it

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Speaker 1: doesn't have to be too extreme as long as it

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Speaker 1: makes both of you a little hesitant, right, Like go

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Speaker 1: to like a mattress store and cut off the tags.

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Speaker 1: Who yeah, just thrill apparently a federal offense. Yeah. Wait,

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Speaker 1: so do you mind if I ask what you both did,

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Speaker 1: respectively as your terrifying events. Yeah, so my husband and

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Speaker 1: I did something that on the outside probably just looked cute,

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Speaker 1: but on the coast side was so scream inducing that

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Speaker 1: half of the audio from that episode is just me

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Speaker 1: screaming the whole time. It was us writing a tandem

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Speaker 1: bicycle together, and and I'm literally screaming at the top

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Speaker 1: of my lungs through half this episode. And Dean, when

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Speaker 1: he gets very tense, he just goes silent. So it's

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Speaker 1: just him saying nothing and me screaming the whole time. Wait,

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Speaker 1: so are you are you not comfortable on a bike?

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Speaker 1: What what made a terrifying with the idea that the

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Speaker 1: two of you have to in tandem keep the bike

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Speaker 1: up right? Well, I am not a super confident bike

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Speaker 1: rider in the city, like I can ride a bike

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Speaker 1: like maybe on the beach. But I've been in bike accidents.

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Speaker 1: I've been hit by bikes before, I've been injured by bikes.

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Speaker 1: And meanwhile, my husband, he's just a little bit too

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Speaker 1: much of a thrill seeker on bikes. And just a

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Speaker 1: few weeks before we did this, he was in the

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Speaker 1: e r because he had a mountain biking accident. So

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Speaker 1: the last thing I want to do is get on

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Speaker 1: a bike with somebody who's so reckless that he gets

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Speaker 1: into mountain biking accidents. And the last thing he wants

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Speaker 1: to get on a bike with somebody who's too scared

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Speaker 1: to ride about and and so it was terrifying for

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Speaker 1: both of us. Okay, what about you, Gilanta. I mean,

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Speaker 1: mine was like very heteronormative, but my husband and I

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Speaker 1: I drove us to the beach it and normally, even

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Speaker 1: though we're both like very good drivers. He's the one

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Speaker 1: that tends to drive, especially in the city. I'm like,

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Speaker 1: I'll drive out of the city, no prob. But he

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Speaker 1: tends to do the city driving. And so just him

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Speaker 1: sort of giving up that control and like letting me

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Speaker 1: have it and me sort of getting my my sea

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Speaker 1: legs or like my city driving legs. Again, it was

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Speaker 1: definitely terrifying. Like I tend to be like maybe a

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Speaker 1: little overly cautious, which will get you like honk dat

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Speaker 1: and like you know, there was lots of yelling, but

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Speaker 1: in the end we couldn't believe we made it, and

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Speaker 1: like we were definitely on a high nice and I think, yeah, actually,

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Speaker 1: the more I ask, I'm like, wait, the real exercise here,

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Speaker 1: I think for somebody trying to figure out what is

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Speaker 1: a good activity is more to be open enough with

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Speaker 1: yourself to be like, what are my vulnerabilities actually, because

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Speaker 1: that those will probably lead to more trying activities that

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Speaker 1: will only enrich the relationship for sure. What is something

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Speaker 1: from your search history? Oh, search history right now? Um gosh.

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Speaker 1: I have been looking into something called empathic discipline, which

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Speaker 1: is an an approach to creating stronger teacher student trust

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Speaker 1: and relationships um with the goal of decreasing racial disparities

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Speaker 1: in school discipline like suspensions, expulsions, detentions, things like that.

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Speaker 1: And there's some really interesting research done by an amazing

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Speaker 1: psychologist named Jason Okana Fua who finds that and the

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Speaker 1: research found that when you trained teachers to use empathic

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Speaker 1: approaches to students, when you train teachers to really focus

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Speaker 1: on building trusting relationships and avoiding labeling students and really

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Speaker 1: thinking about how important a teacher student relationship is to

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Speaker 1: helping students success, what happens is suspensions drop, and specifically

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Speaker 1: racial disparities in dispension in suspensions decrease as well. So

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Speaker 1: it's like this really interesting approach to decreasing bias that

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Speaker 1: doesn't actually target bias. So it's it's like kind of

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Speaker 1: this Ninja or maybe more like Judo. It's like this

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Speaker 1: this move of getting at the consequences of bias without

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Speaker 1: actually trying to tackle the bias itself. So I've been

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Speaker 1: I've been researching that, just focusing on building empathy, like

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Speaker 1: with teachers having empathy with their students across the board,

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Speaker 1: and the idea that like just by having a like

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Speaker 1: an actual relationship with student will probably be like, oh, yeah,

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Speaker 1: I respect you because I trust to you. So if

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Speaker 1: you're telling me that I'm less likely to act out

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Speaker 1: versus me being like, oh, here comes this fucking asshole

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Speaker 1: who just wants to say I'm a bad influence all

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Speaker 1: the time. That's exactly it. So what this researcher found

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Speaker 1: was that a lot of like bias interventions think of

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Speaker 1: it as this one way street, which is like the

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Speaker 1: teacher express and bias towards the student. But what Jason

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Speaker 1: o'kana fua found, Dr okana Fua, is that it's actually

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Speaker 1: like an interactive experience. So exactly as you point out, Miles, like,

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Speaker 1: the teacher is maybe having certain stereotypes about students, and

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Speaker 1: the student senses that, and they are primed to act

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Speaker 1: out because they don't trust the teacher and they're expecting

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Speaker 1: to be treated in a particular way, and so that

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Speaker 1: might even create them to act out more and then

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Speaker 1: fulfill the teacher's stereotype, which just creates this like endless

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Speaker 1: and then the teachers like and I was right about them,

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Speaker 1: and then you nailed it. Yeah, So this approach is

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Speaker 1: really designed to interrupt that bad cycle and help teachers

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Speaker 1: really understand how important it is too for the students

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Speaker 1: to feel respected and for the teacher to respect the

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Speaker 1: students and to rate that bond, so that exactly like

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Speaker 1: when a problem arises, the student like, as you point out,

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Speaker 1: is like, oh, okay, maybe the teacher's right, maybe I

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Speaker 1: do need to kind of shift things around. And I

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Speaker 1: know that they tried. I know that they respect me,

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Speaker 1: and so it creates the foundation for a relationship that

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Speaker 1: then causes students to feel more respected and behave better right,

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Speaker 1: And it seems like it's just something really good teachers naturally,

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Speaker 1: do you know, like I think of like teachers I've had.

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Speaker 1: I've had teachers who have like written me off, and

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Speaker 1: I'm like, and I hated being in their classroom because

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Speaker 1: they're going to be like the second. I have one

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Speaker 1: teacher who like, if anybody laughed at any time, she

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Speaker 1: was like, Miles, what are you doing or something because

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Speaker 1: she thought I was distracting the class and liked, I

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Speaker 1: don't even sit on that side of the classroom, what

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Speaker 1: the are you talking about? And it all I was.

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Speaker 1: It was always very tense. And then I had other

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Speaker 1: teachers who knew I was. I could be disruptive, but

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Speaker 1: like would come at me into like, hey, look I

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Speaker 1: know you got you get excited, you want to talk

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Speaker 1: to your friends, but like just help me out and

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Speaker 1: just kind of like cool it when you do it,

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Speaker 1: and that approach all like I was, all, he's more

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Speaker 1: respectful with those teachers who are like, hey, I get it,

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Speaker 1: you know, like I get you. But and I was like, okay,

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Speaker 1: versus like here he goes the loud kid again, throwing

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Speaker 1: up gang signs, ruining our class picture, and I'm like,

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Speaker 1: get back in your thunderbird already at least yeah, I mean.

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Speaker 1: One thing that was super interesting to me about this

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Speaker 1: research was that when he when this. When the psychologist

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Speaker 1: recruited teachers for the study, he didn't actually tell them

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Speaker 1: that they were doing that. He was like doing an

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Speaker 1: intervention with them. What he told them was he was

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Speaker 1: they were being recruited to kind of reflect and review

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Speaker 1: best practices in teaching right and review. And so they

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Speaker 1: were given this material that talked about how important trusting

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Speaker 1: relationships are and how important it is to not label

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Speaker 1: a student or assume that that the teacher knows why

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Speaker 1: a student is behaving that way, and to instead look

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Speaker 1: for maybe situational reasons that a student is having that way,

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Speaker 1: rather than fix it to like some kind of essential

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Speaker 1: aspect of that student. And so they were yeah, so exactly,

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Speaker 1: they were kind of they were told that they were

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Speaker 1: just reviewing best practices and and then they reviewed things

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Speaker 1: like how how students felt when they felt respected and

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Speaker 1: how that helped them learn. And yeah, I mean the

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Speaker 1: results were pretty spectacular in terms of actually like changing

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Speaker 1: the dynamic. It's wild how much we ask of our

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Speaker 1: teachers too already, right, like because on top of you know,

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Speaker 1: the many teachers who listen to this show, again, thank

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Speaker 1: you so much. I'll continue to retweet your wish lists,

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Speaker 1: but the added sort of task of like, yeah, look,

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Speaker 1: some kids are not supported at home and are going

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Speaker 1: to come in here. And then also we also need

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Speaker 1: you to have these skills to be able to make

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Speaker 1: sure that they can navigate life because they're not going

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Speaker 1: to be through this like chaotic sequence of like not

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Speaker 1: trusting people in authority positions and what that turns into

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Speaker 1: an adulthood. Just just how much we ask that's right,

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Speaker 1: very a thank teacher when you see them, because that's

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Speaker 1: why I'm so grateful, because I think of the teachers

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Speaker 1: who actually tried to understand me rather than just kind

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Speaker 1: of be like this guy's that disrupted an assholes, Like

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Speaker 1: thank you, and that helped me be more interested in

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Speaker 1: like school at the end of the day rather than

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Speaker 1: like feeling like I was going to a place where

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Speaker 1: people were just going to be like, you're bad. That's

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Speaker 1: so dope though, that that you've that the study found

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Speaker 1: that the training, like it is changeable. It's not a

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Speaker 1: fixed problem. It's it's something where training teachers to you know,

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Speaker 1: just focus on this this part of their relationships with students,

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Speaker 1: it like makes makes an impact. Is that is that

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Speaker 1: something that's like generalizable to healthcare and you know other

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Speaker 1: places is at the empathic discipline kind of being being adopted.

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Speaker 1: Law enforcement said, I don't know, it's a really it's

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Speaker 1: a really interesting question. I mean I think what that

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Speaker 1: like if if you zoom out a little bit, I

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Speaker 1: think what this approach shows is that if you if

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Speaker 1: you want to address people's biases, one thing that can

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Speaker 1: work that we see in this education research is enhancing

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Speaker 1: their other values, like boosting their commitment to values like

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Speaker 1: trusting relationships and respect and mutual understanding and avoiding labeling,

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Speaker 1: and so if you kind of boost and like amplify

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Speaker 1: those values, then that can override these automatic responses that

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Speaker 1: that we might have toward one another. So it kind

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Speaker 1: of like, yeah, it's almost it's like it's like, I

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Speaker 1: don't know, like a vitamin, like a kind of ster

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Speaker 1: like you you give your other values steroids, and then

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Speaker 1: it kind of like over this metaphor is falling apart. Sorry, Okay,

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Speaker 1: we're a steroids. We're both on cycles right now. So

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Speaker 1: you do a hit a balco straight in the empathy zone,

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Speaker 1: everyone is completely juice. Yeah, So but no, it's true

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Speaker 1: and bigger. My heart was enlarged. Also, heart only grew

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Speaker 1: three sizes that day, ship Broy. Yeah, I'm glad that

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Speaker 1: you I'm glad you mentioned policing because yes, there there

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Speaker 1: is also really interesting work done in policing that I

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Speaker 1: that I talked about in my book. Actually that looks

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Speaker 1: at like how you change police behavior basically, like how

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Speaker 1: you actually get police to behave in respectful, kind humane

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Speaker 1: ways rather than just avoid like breaking the law and

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Speaker 1: avoid just like criminal behavior and that Yeah, and I

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Speaker 1: think you know, in that case, it's a lot about

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Speaker 1: creating incentives, like we talk about you know, I was

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Speaker 1: just at a meeting actually here in Minneapolis talking about

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Speaker 1: improving police behavior and accountability, and everyone focuses primarily on

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Speaker 1: accountability and correct punishment for you know, for failure, we

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Speaker 1: need more guardrails, more guardrails kind of thing, man, exactly.

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Speaker 1: And that's like, really, it's totally important. I mean, it

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Speaker 1: creates like a floor below which you cannot go in

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Speaker 1: terms of bad behavior. But I think we miss something

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Speaker 1: when we talk about this, because culture is not just

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Speaker 1: what you punish, but it's also what you reward. And

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Speaker 1: I think if we if we just talk about punishment

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Speaker 1: without talking about what we're actually trying to reward and

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Speaker 1: incentivize and like the kind of behavior we actually want,

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Speaker 1: then we only kind of have half the half the story. Yeah,

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Speaker 1: And even in like that guardrail metaphor, it's like, if

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Speaker 1: I think of a cop as a bowler, like do

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Speaker 1: you want the guys like, yeah, put the bumpers up

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Speaker 1: because I'm sloppy as shit, or someone who's like there's

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Speaker 1: a there's someone in need I know how to like

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Speaker 1: solve it. Let me just bowl of strike here. I

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Speaker 1: don't need guardrails because I'm focused on a different version,

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Speaker 1: which is like I'm out of control. How do you

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Speaker 1: contain that? Hm? I want that guy who said who

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Speaker 1: do you think you are? I am? That's metaphor. But yeah, Jack,

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Speaker 1: to your question about values, I mean like if you

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Speaker 1: can generalize that the education work to policing, I mean

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Speaker 1: I think that you can create incentive structures. In fact,

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Speaker 1: there's a there's a small group in l A, the

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Speaker 1: Community Safety Partnership that um there was just an independent

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Speaker 1: evaluation of this particular police program which was designed around

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Speaker 1: changing incentive. So officers were rewarded for building relationships instead

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Speaker 1: of making arrests, and so the value was in the relationship.

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Speaker 1: That's what they were actually being rewarded for. And the

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Speaker 1: analysis that came out of this of that program found

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Speaker 1: that it did change police behavior actually, and it also

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Speaker 1: dicused violent crime and that's very cool. Shout out to

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Speaker 1: l A is that that was an l A p D.

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Speaker 1: It was believe it, Yes, it was l A p D.

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Speaker 1: It was a small group that's currently headed by a

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Speaker 1: Mode of ting Gardis, Deputy Chief of Mod of Tingartis,

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Speaker 1: And it was like a small pilot program that started

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Speaker 1: in in Watts And I want to say two thousand

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Speaker 1: eleven with like forty officers that were tasked with creating

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Speaker 1: relationships and were rewarded on the basis of whether they

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Speaker 1: created relationships with the community. That's very cool. What's uh,

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Speaker 1: what's something you think is underrated? Definitely? Uh, Jordan Peele's

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Speaker 1: new movie. Nope, I feel like it's underrated. I think

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Speaker 1: that movie is super dope. I was in the theater

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Speaker 1: doing finger Guns the whole time, and so many parts

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Speaker 1: of it because they had so many like cool like

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Speaker 1: mergings of of influences and genres and styles. I was like, Oh,

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Speaker 1: this movie is great. But at the same time, when

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Speaker 1: the lights went up, I could audibly hear people talking

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Speaker 1: about like I don't know about this one? What's going

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Speaker 1: on with this one? And I'm I'm just in my

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Speaker 1: seat seething because I'm like, Yo, it's not supposed to

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Speaker 1: be get Out, it's not supposed to be us. It's

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Speaker 1: a whole different movie. Enjoyed the movie for what it is.

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Speaker 1: Let go of your expectations. Get into it. Brother. They're like,

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Speaker 1: what it means Black Cowboy's Search and Ship. It's like, yeah,

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Speaker 1: I'm you know, so I've been seeing a whole lot

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Speaker 1: of mixed reviews about it from various sources, but I

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Speaker 1: love the movie. I think people should go see that

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Speaker 1: movie for sure, right right right absolutely. I'm waiting to go,

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Speaker 1: uh maybe in the next couple of weekends or something.

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Speaker 1: I seem supposed to go with my wife, but that's

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Speaker 1: like burning a hole in my pocket if I had

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Speaker 1: a ticket, Like, please let me go to see this one. Yeah,

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Speaker 1: I can't wait. And it really has been device wild.

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Speaker 1: I was telling a group of friends and people were

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Speaker 1: splitting that group and people who were like even like

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Speaker 1: I know it's a different film. It's like I'm just

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Speaker 1: singing like could it have been better? Even as a

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Speaker 1: genre thing? I was like, Okay, you know, I just

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Speaker 1: want to talk to people who are like I saw

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Speaker 1: people immediately and hate mode, like fresh out of the

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Speaker 1: theater seat like nope, like nope, truly. Yeah it was

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Speaker 1: so craty. I didn't expect that, you know, but I

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Speaker 1: enjoyed the movie, so jokes on him. Yeah, it's so enjoyable.

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Speaker 1: There's so much good stuff in it. Like I can

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Speaker 1: see a criticism that it's like not as coherent as

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Speaker 1: his other ones, because like there's just like a lot

390
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Speaker 1: of cool ideas, but also like doesn't need to be

391
00:22:37,240 --> 00:22:40,680
Speaker 1: cod here and he's like an artist, you know, he's

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Speaker 1: putting things out there. But yeah, I agree like it.

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Speaker 1: People after the movie, like while walking down the escalator

394
00:22:49,680 --> 00:22:53,359
Speaker 1: were we're like, I didn't know what he was saying

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Speaker 1: the time. I couldn't understand him. So wait the character, Yeah,

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Speaker 1: what are we talking about? You? Oh? No, like literally

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Speaker 1: I cannot oh wow doing that one? Yeah, what dialect

398
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Speaker 1: was that? Oh my god? Oh? I mean I think

399
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Speaker 1: he's a good actor, but I didn't. I didn't know

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Speaker 1: what he was saying. But that movie is great. Everybody

401
00:23:21,080 --> 00:23:24,280
Speaker 1: should go check it out. What else is out in movies?

402
00:23:24,359 --> 00:23:26,760
Speaker 1: I feel like they stopped releasing movies after Top Gun

403
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Speaker 1: came out. There, we did it. You were good until

404
00:23:30,200 --> 00:23:34,119
Speaker 1: Milpe there was there was just a like article about

405
00:23:34,160 --> 00:23:37,800
Speaker 1: how what do you call that? August is like very

406
00:23:37,840 --> 00:23:40,960
Speaker 1: not much going on in August. Wait, wait you know

407
00:23:41,000 --> 00:23:44,480
Speaker 1: what I saw? I saw Bullet Train is out? Oh yeah,

408
00:23:44,560 --> 00:23:47,160
Speaker 1: bullet train came out? I did. I did see that.

409
00:23:47,160 --> 00:23:52,160
Speaker 1: That was okay, Yeah that it was aggressively okay, Yeah, yeah,

410
00:23:52,520 --> 00:23:56,480
Speaker 1: hey that's a perfect description. Is definitely aggressively Okay, extra

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Speaker 1: I don't know about how do y'all feel about Brad

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Speaker 1: Pitt's acting in general? Like what what? Like he's like

413
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Speaker 1: a vibe He's not an actor. He's like a vibes dealer. Word,

414
00:24:08,200 --> 00:24:11,200
Speaker 1: We're on the same page. To me, I'm never like, damn,

415
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Speaker 1: Brad Pitt fuckingbodied that role. I'm like, Brad Pitt has

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Speaker 1: He contains multitudes and it just depends which one he

417
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Speaker 1: pulls out of his back. My thing is like, yeah,

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Speaker 1: Brad Pitt did not ruin this good movie. Tight, Yeah,

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Speaker 1: And I don't mind. It's just like and I'm like, cool, Yeah,

420
00:24:30,920 --> 00:24:33,560
Speaker 1: he really is himself, you know, like we could be

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Speaker 1: in the eighteen hundreds, we could be in the future. Yeah,

422
00:24:36,400 --> 00:24:41,760
Speaker 1: you could traveler and snatch. I'm like, yeah, he said,

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Speaker 1: you know Brad Pitt with with an accent. But I'm

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Speaker 1: brad exactly exactly? Is he eating throughout this like that?

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Speaker 1: That is one of the things that I usually need

426
00:24:52,119 --> 00:24:54,480
Speaker 1: him to be doing. I do remember some eating. I

427
00:24:54,920 --> 00:24:58,000
Speaker 1: definitely remember some drinking of water. He definitely drinking. He

428
00:24:58,119 --> 00:25:00,879
Speaker 1: was staying hydrated. He like of things in his mouth.

429
00:25:01,119 --> 00:25:04,600
Speaker 1: That's another one that's super divisive to people who love

430
00:25:04,680 --> 00:25:07,840
Speaker 1: it or hate it. My mom was like, I love

431
00:25:07,960 --> 00:25:12,040
Speaker 1: that ship. Wait while big her and Steve Hernandez tough

432
00:25:12,119 --> 00:25:14,000
Speaker 1: Guy of the Year, I saw him tweet he said

433
00:25:14,000 --> 00:25:20,080
Speaker 1: he walked out of Bullet Oh yeah, Steve her name,

434
00:25:20,160 --> 00:25:22,240
Speaker 1: he tweeted. I had to retweet that with the tough

435
00:25:22,240 --> 00:25:29,160
Speaker 1: guy gift because I was like, alright, they do. There

436
00:25:29,160 --> 00:25:31,480
Speaker 1: are a lot of things that get wrapped up very

437
00:25:31,680 --> 00:25:34,080
Speaker 1: neatly in that movie. I could I could see somebody

438
00:25:34,119 --> 00:25:37,240
Speaker 1: like not digging that. But like walk out movie, Like

439
00:25:37,280 --> 00:25:39,280
Speaker 1: the last movie I walked out of was like that

440
00:25:40,359 --> 00:25:43,560
Speaker 1: Johnny Knoxville movie where he was like in the Special Olympics,

441
00:25:43,600 --> 00:25:49,320
Speaker 1: like yeah, like like like like but like this ship

442
00:25:49,440 --> 00:25:54,120
Speaker 1: is fucked up. I gotta go. Yeah, I can't be here.

443
00:25:54,200 --> 00:25:58,439
Speaker 1: But than that, like like remember after the fact too,

444
00:25:58,520 --> 00:26:00,960
Speaker 1: they were trying to like really act like they were

445
00:26:00,960 --> 00:26:03,080
Speaker 1: doing everybody is solid. They're like, yeah, but these people

446
00:26:03,160 --> 00:26:05,600
Speaker 1: like now they got little careers going through like they

447
00:26:05,600 --> 00:26:08,840
Speaker 1: were doing press for the show. Yeah you're not. You're

448
00:26:08,880 --> 00:26:11,680
Speaker 1: not like don't don't like lay your head at night

449
00:26:11,720 --> 00:26:13,800
Speaker 1: on your big pillow. If I'm an ally and like

450
00:26:15,040 --> 00:26:19,280
Speaker 1: better representation, no, come on now. But yeah, the Bullet

451
00:26:19,280 --> 00:26:21,359
Speaker 1: Train thing, I feel like it looks so campy that

452
00:26:21,400 --> 00:26:23,359
Speaker 1: I can tell like you you might either be piste

453
00:26:23,359 --> 00:26:26,119
Speaker 1: off because it's so camp or you can accept that

454
00:26:26,240 --> 00:26:27,840
Speaker 1: and be like, I don't know, fine funcket it was,

455
00:26:28,600 --> 00:26:34,359
Speaker 1: you know, it's airplane movie, but yeah, yeah, for sure. Sorry,

456
00:26:34,359 --> 00:26:37,359
Speaker 1: what is something you think is overrated? Switch it up

457
00:26:37,840 --> 00:26:41,560
Speaker 1: your lawn, your grass, get rid of it? Oh my god?

458
00:26:41,760 --> 00:26:46,400
Speaker 1: Why is it still everywhere? My car? My my car?

459
00:26:46,680 --> 00:26:51,440
Speaker 1: Why did I say my car the other most American thing. Well,

460
00:26:51,520 --> 00:26:53,720
Speaker 1: it's just making me sad that I said that, because

461
00:26:53,760 --> 00:26:57,600
Speaker 1: I really just met my desk. That means that I

462
00:26:57,640 --> 00:27:01,199
Speaker 1: feel like I'm in a moving veha goal Behy. In

463
00:27:01,359 --> 00:27:05,120
Speaker 1: the screen, you do have one of those little uh

464
00:27:05,600 --> 00:27:09,399
Speaker 1: Fisher Price like steering wheel things, and you've been hitting

465
00:27:09,480 --> 00:27:12,320
Speaker 1: the gum beet beat every time you want to start talking,

466
00:27:12,520 --> 00:27:17,720
Speaker 1: So that Fisher Price steering wheel you've had to turn

467
00:27:17,760 --> 00:27:22,560
Speaker 1: signal on the entire recording, though, So I would ask, anyways,

468
00:27:25,160 --> 00:27:28,320
Speaker 1: get rid of your lawn falls. What the hell? It's

469
00:27:28,359 --> 00:27:33,880
Speaker 1: a d five degrees in some places people are mowing

470
00:27:34,400 --> 00:27:42,040
Speaker 1: dead yellow grass, kicking up dust. Just go to nice

471
00:27:42,359 --> 00:27:45,080
Speaker 1: drought proof plants if you like the plants in the

472
00:27:45,119 --> 00:27:48,200
Speaker 1: front the lawn ship. I mean this is that there's

473
00:27:48,240 --> 00:27:52,080
Speaker 1: just like an article about how like how the in

474
00:27:52,440 --> 00:27:57,880
Speaker 1: like northern Mexico, like there's really really severe water rationing

475
00:27:57,920 --> 00:28:01,320
Speaker 1: happening to combat drought. But mean while just over the border,

476
00:28:01,400 --> 00:28:04,679
Speaker 1: like in Laredo, Texas, they're using like there's something like

477
00:28:04,760 --> 00:28:08,320
Speaker 1: ten million gallons a day or something on fucking like

478
00:28:08,320 --> 00:28:10,480
Speaker 1: like lawns and stuff. And I'm sure, like l A

479
00:28:10,720 --> 00:28:14,040
Speaker 1: every drought area that has lawns has some absurd number

480
00:28:14,040 --> 00:28:17,960
Speaker 1: they're wasting just purely on watering grass. But it feels

481
00:28:18,000 --> 00:28:20,200
Speaker 1: like one of the easiest I mean, like I get

482
00:28:20,240 --> 00:28:22,440
Speaker 1: that there's so many things that we obviously need to

483
00:28:22,520 --> 00:28:25,240
Speaker 1: lean on, like changing our energy mix and much bigger

484
00:28:25,280 --> 00:28:27,480
Speaker 1: ideas and things like that to save the planet. But

485
00:28:27,600 --> 00:28:29,199
Speaker 1: I like, the more I look at them, like I

486
00:28:29,280 --> 00:28:32,480
Speaker 1: don't need to see fucking grass all the fucking time,

487
00:28:32,760 --> 00:28:36,600
Speaker 1: Like in a place that's a desert, there are succulents

488
00:28:36,680 --> 00:28:40,160
Speaker 1: that look like grass. You don't need to do this.

489
00:28:40,280 --> 00:28:45,760
Speaker 1: And also the causes of some wildfires have been lawn

490
00:28:45,760 --> 00:28:52,080
Speaker 1: mowers on dead, dry grass that shoots sparks and catch fire,

491
00:28:51,800 --> 00:28:53,840
Speaker 1: and like, what are you doing? I put my friction

492
00:28:53,920 --> 00:29:01,280
Speaker 1: machine over this fuel pile in highways. I don't understand

493
00:29:01,360 --> 00:29:04,720
Speaker 1: what happened. Wildfires are job creators are That's what you

494
00:29:04,760 --> 00:29:10,360
Speaker 1: have to understand. For prison labor. You sounds like a

495
00:29:10,400 --> 00:29:15,080
Speaker 1: warden right now. It's actually a really great employment opportunity

496
00:29:15,120 --> 00:29:21,280
Speaker 1: for our chattel slate prison uh uh teammates. No, I

497
00:29:21,320 --> 00:29:23,640
Speaker 1: get it. I've been hired for arson and I've done it,

498
00:29:23,680 --> 00:29:29,600
Speaker 1: but my heart was not in it. It just was not.

499
00:29:30,560 --> 00:29:32,640
Speaker 1: That's why it warms my heart to see the golf

500
00:29:32,800 --> 00:29:35,960
Speaker 1: the golf courses where activists have been filling up the

501
00:29:36,000 --> 00:29:41,280
Speaker 1: holes with cement. Although I will say, just turn up

502
00:29:41,320 --> 00:29:43,640
Speaker 1: the green, don't fill up the holes of cement, because

503
00:29:43,680 --> 00:29:46,080
Speaker 1: the whole like they moved the hole every day, so

504
00:29:46,120 --> 00:29:49,400
Speaker 1: you can just like that's easy. Yeah, they can just

505
00:29:49,440 --> 00:29:52,080
Speaker 1: poke that shut out. But I love the love, the

506
00:29:52,120 --> 00:29:55,840
Speaker 1: effort and the symbolism is great. It's just like that's

507
00:29:55,880 --> 00:30:00,200
Speaker 1: probably didn't funk with them too bad, But no, because

508
00:30:00,200 --> 00:30:03,200
Speaker 1: they're so precious about their little grass, the little fairway grass.

509
00:30:03,240 --> 00:30:05,720
Speaker 1: They got the little things that like comb it and

510
00:30:05,800 --> 00:30:08,360
Speaker 1: like primp it. After you hit the ball off of

511
00:30:08,440 --> 00:30:11,760
Speaker 1: the grass, they're like it's gonna be smooth, right, Like

512
00:30:11,960 --> 00:30:14,600
Speaker 1: what was what's the movie where they're like tunneling out

513
00:30:14,640 --> 00:30:16,760
Speaker 1: of prison and they're like taking the dirt with him

514
00:30:16,800 --> 00:30:24,760
Speaker 1: out into the yard, right, uh, great escape. Yeah, he's

515
00:30:24,840 --> 00:30:27,840
Speaker 1: like letting the dirt loose through his pant leg. Oh

516
00:30:27,960 --> 00:30:30,240
Speaker 1: yeah yeah yeah. And then they lampooned that and naked

517
00:30:30,280 --> 00:30:32,280
Speaker 1: gun too when they're trying to escape and he's just

518
00:30:32,320 --> 00:30:34,400
Speaker 1: like sitting on a fucking mountain. I'm like, did you

519
00:30:34,440 --> 00:30:37,040
Speaker 1: do a similar thing but with like grass killer on

520
00:30:37,040 --> 00:30:40,280
Speaker 1: a golf course, Like we're big pants, you're like four,

521
00:30:40,520 --> 00:30:42,320
Speaker 1: and they're like a bunch of ships coming out to

522
00:30:42,280 --> 00:30:45,160
Speaker 1: the bottom that guy's pants and spilling you and eat

523
00:30:45,200 --> 00:30:55,840
Speaker 1: the rich on the fairway are still on lines? Yeah, yeah, yeah,

524
00:30:56,000 --> 00:30:57,760
Speaker 1: we had to we had to take a sharp right

525
00:30:57,800 --> 00:31:00,360
Speaker 1: turn into the gulf the country cliff real quick. Speaking

526
00:31:00,400 --> 00:31:04,720
Speaker 1: of grass Listen, now, now that I'm employed, there are

527
00:31:04,800 --> 00:31:06,960
Speaker 1: all these freelance jobs I have to say no to,

528
00:31:07,720 --> 00:31:10,120
Speaker 1: And that's where these are coming from. And this is

529
00:31:10,160 --> 00:31:13,720
Speaker 1: coming from like ten fifteen years into your future for

530
00:31:13,760 --> 00:31:16,320
Speaker 1: the rest of America, because I was I was back

531
00:31:16,320 --> 00:31:19,960
Speaker 1: East and everything's green back there, just by accident, like

532
00:31:20,000 --> 00:31:24,920
Speaker 1: there's grass growing places, like because what else is gonna happen.

533
00:31:25,040 --> 00:31:28,400
Speaker 1: Of course grass is gonna grow there, but yeah we are.

534
00:31:28,400 --> 00:31:32,080
Speaker 1: We're into the drought that's coming for all of us.

535
00:31:32,240 --> 00:31:35,720
Speaker 1: And the only things that are green are golf courses

536
00:31:36,000 --> 00:31:40,280
Speaker 1: and like a handful of huge like agribusiness. There's like

537
00:31:40,360 --> 00:31:45,240
Speaker 1: twenty five states that don't need grass. Yea Miss Union

538
00:31:45,680 --> 00:31:47,959
Speaker 1: never had like I look, I love a field for

539
00:31:48,040 --> 00:31:50,800
Speaker 1: like sport, but you know, the turf is getting pretty good,

540
00:31:51,480 --> 00:31:57,080
Speaker 1: you know. Yeah. This is also because outside my window

541
00:31:57,840 --> 00:32:02,040
Speaker 1: while I'm trying to podcast, there is these huge John

542
00:32:02,120 --> 00:32:07,760
Speaker 1: Deer's over this like ted by ted patch. It doesn't

543
00:32:07,800 --> 00:32:12,920
Speaker 1: make any sense, and there's so much gn essentially, there's

544
00:32:13,000 --> 00:32:15,880
Speaker 1: so much des they are they do donuts, they're having

545
00:32:15,880 --> 00:32:18,040
Speaker 1: a blast. I feel for these guys. I get it.

546
00:32:18,040 --> 00:32:21,680
Speaker 1: It's a good time, but it sucks. And so that's

547
00:32:21,720 --> 00:32:25,640
Speaker 1: where my underrated comes in, which is what yeah, what

548
00:32:25,760 --> 00:32:32,040
Speaker 1: is your under it? These are dark chocolate almonds, uh huh,

549
00:32:33,280 --> 00:32:36,760
Speaker 1: And yeah, I like, how you good? You know, we

550
00:32:36,840 --> 00:32:39,120
Speaker 1: gotta we gotta get off the fucking lawn business to

551
00:32:39,320 --> 00:32:42,200
Speaker 1: one of the most water intensive products in this in

552
00:32:42,280 --> 00:32:45,000
Speaker 1: the fucking state, the actual one of the biggest reasons

553
00:32:45,000 --> 00:32:50,440
Speaker 1: the California's experiencing drought because the almond industry intensive enough

554
00:32:51,400 --> 00:32:54,560
Speaker 1: cocoa beans. That's what I'm saying, the lawn so I

555
00:32:54,560 --> 00:32:56,680
Speaker 1: can have more of these chocolate covered almonds at a

556
00:32:56,680 --> 00:33:00,840
Speaker 1: reduced price. This brings me to my underrated mentioned, which

557
00:33:00,880 --> 00:33:06,400
Speaker 1: is hypocrisy. It's really the cure for heart disease in

558
00:33:06,440 --> 00:33:11,320
Speaker 1: this nation. Try it out. It will keep you alive

559
00:33:12,000 --> 00:33:14,480
Speaker 1: so long. Wait, but let me see those almonds again.

560
00:33:14,480 --> 00:33:19,320
Speaker 1: They're they're good. Yeah, each one. I just I taste

561
00:33:19,360 --> 00:33:25,000
Speaker 1: gallons of water in the chocolate goodness. You're like each

562
00:33:25,120 --> 00:33:28,440
Speaker 1: with each almond. That's one last child thirty years from

563
00:33:28,480 --> 00:33:30,720
Speaker 1: now that will know the feeling of grass under their

564
00:33:30,760 --> 00:33:39,800
Speaker 1: bare feet. I know what a shower is? Do you

565
00:33:39,800 --> 00:33:42,440
Speaker 1: ever think about that? Like those are like these are

566
00:33:42,600 --> 00:33:45,400
Speaker 1: really weird small details that is going to go missing

567
00:33:45,840 --> 00:33:49,360
Speaker 1: from from kids, like honestly grass right, Like I'm out

568
00:33:49,360 --> 00:33:51,960
Speaker 1: here really thinking looking at my own and like what

569
00:33:52,000 --> 00:33:55,120
Speaker 1: the fucking grass necessary? Oh my god. We already live

570
00:33:55,160 --> 00:33:57,320
Speaker 1: in the era where most people don't know what I

571
00:33:57,360 --> 00:34:02,280
Speaker 1: mean by a real university experience or like what it's

572
00:34:02,320 --> 00:34:06,760
Speaker 1: like to have campus life, right, you know, and like

573
00:34:06,800 --> 00:34:09,920
Speaker 1: there's so many things like you don't think about like

574
00:34:09,960 --> 00:34:12,440
Speaker 1: fifty years from now or something. With the water shortages

575
00:34:12,480 --> 00:34:16,440
Speaker 1: and stuff, you think like, you know, immediate like pools,

576
00:34:17,520 --> 00:34:21,200
Speaker 1: you know, sprinklers, water bottles, and you don't think like, oh, yeah,

577
00:34:21,239 --> 00:34:23,359
Speaker 1: we might not be able to produce almonds anymore because

578
00:34:23,360 --> 00:34:27,480
Speaker 1: it's just so water intensive, or we do because they

579
00:34:27,520 --> 00:34:30,480
Speaker 1: have an outsized influence in the state legislature and they're like,

580
00:34:30,600 --> 00:34:33,799
Speaker 1: I'm sorry, man, if only you guys had more lobbyists. Right,

581
00:34:33,800 --> 00:34:35,960
Speaker 1: It's like when you it's like when you look at

582
00:34:36,000 --> 00:34:39,520
Speaker 1: like corn politics and then it's like, oh, yeah, that's

583
00:34:39,600 --> 00:34:43,520
Speaker 1: my batteries and my advil and like my window sill.

584
00:34:44,840 --> 00:34:48,000
Speaker 1: You know, like you know that astro turf you use

585
00:34:48,040 --> 00:34:50,839
Speaker 1: on your lawn is actually made from recycled almonds. They

586
00:34:50,920 --> 00:34:55,280
Speaker 1: just made too many almonds, so they've turned it into

587
00:34:55,640 --> 00:35:02,840
Speaker 1: it's an almond base. You about this little heart salve

588
00:35:02,920 --> 00:35:06,799
Speaker 1: that I call hypocrisy, Get on board. You gotta, well,

589
00:35:06,840 --> 00:35:09,520
Speaker 1: you gotta sip from it every now and then. You

590
00:35:09,640 --> 00:35:11,960
Speaker 1: simply must. We'll see because when you get when you

591
00:35:12,000 --> 00:35:14,480
Speaker 1: get drunk off it, that's when it's it's problems. But

592
00:35:14,520 --> 00:35:18,120
Speaker 1: every now and then it's like it's a quick little taste.

593
00:35:18,440 --> 00:35:24,600
Speaker 1: I knew you'd get it. Yeah, shout out Blue Diamond Almonds. Uh,

594
00:35:25,080 --> 00:35:28,239
Speaker 1: inaugural sponsor of the podcast. All right, let's take a

595
00:35:28,280 --> 00:35:41,240
Speaker 1: quick break. We'll be right back, and we're back, and

596
00:35:42,000 --> 00:35:46,520
Speaker 1: Liz Cheney, as predicted, defeated in her primary race against

597
00:35:47,160 --> 00:35:50,120
Speaker 1: someone whose name I have not committed to memory. But

598
00:35:50,360 --> 00:35:52,520
Speaker 1: I mean there's just like really really no need to

599
00:35:52,640 --> 00:35:55,160
Speaker 1: It's not it's not that important. The most you need

600
00:35:55,200 --> 00:35:58,120
Speaker 1: to know is that this woman, Harriet Hagman, had one

601
00:35:58,160 --> 00:36:02,000
Speaker 1: of the worst looking like fashion choices I've ever seen.

602
00:36:02,120 --> 00:36:05,840
Speaker 1: Like it really has this like quilt coat that's baffling.

603
00:36:06,320 --> 00:36:11,040
Speaker 1: But anyway, sound baffling almost it would work very well,

604
00:36:11,719 --> 00:36:14,200
Speaker 1: it really would it really would. You know. It's you know,

605
00:36:14,280 --> 00:36:17,760
Speaker 1: got her own magna swag, her own swagga. But yeah,

606
00:36:17,880 --> 00:36:21,160
Speaker 1: she one handle. I think with sixty of the vote.

607
00:36:21,200 --> 00:36:23,440
Speaker 1: She got six percent of the vote, So you know,

608
00:36:23,520 --> 00:36:26,360
Speaker 1: I think if you turn on like CNN or MSNBC,

609
00:36:26,640 --> 00:36:28,520
Speaker 1: some are like being like, hey, you know, it's like

610
00:36:28,560 --> 00:36:31,680
Speaker 1: almost treeing her like a fallen hero. But come on, y'all, like,

611
00:36:31,800 --> 00:36:34,760
Speaker 1: does she deserve an applause? Like she helped elevate Trump.

612
00:36:35,000 --> 00:36:37,719
Speaker 1: She voted for night, she voted with him of the

613
00:36:37,760 --> 00:36:41,640
Speaker 1: time and only found a backbone after January six, presumably

614
00:36:42,280 --> 00:36:45,040
Speaker 1: because she hoped that an electoral defeat would be a

615
00:36:45,080 --> 00:36:47,080
Speaker 1: tidy way to get him out the way, which is

616
00:36:47,120 --> 00:36:49,760
Speaker 1: I just feel like that's the That's the most charity

617
00:36:49,880 --> 00:36:51,960
Speaker 1: I could give her. So I'll give her, you know what,

618
00:36:52,000 --> 00:36:55,880
Speaker 1: I'll give her one point because she did draw the

619
00:36:55,960 --> 00:36:58,680
Speaker 1: line at election theft, but not at things like restricting

620
00:36:58,840 --> 00:37:02,040
Speaker 1: like healthcare or lgbt Q rights or voting rights or

621
00:37:02,120 --> 00:37:05,760
Speaker 1: human rights like that. So there it is. But really

622
00:37:05,880 --> 00:37:08,000
Speaker 1: what this says is that this is this is pretty

623
00:37:08,080 --> 00:37:11,040
Speaker 1: much the as many people saying, it's the purge of

624
00:37:11,200 --> 00:37:13,840
Speaker 1: anybody who went against Trump, and the House is pretty

625
00:37:13,880 --> 00:37:16,719
Speaker 1: much gone off without a itch. Eight out of town.

626
00:37:17,360 --> 00:37:20,040
Speaker 1: So yeah, and you said there's two left and they're

627
00:37:20,080 --> 00:37:23,200
Speaker 1: hanging on by technicalities. Yeah, like one like there's a

628
00:37:23,640 --> 00:37:25,879
Speaker 1: it's just like the way the district is set. It's

629
00:37:25,880 --> 00:37:28,080
Speaker 1: just it's like a it's an eventuality. I think the

630
00:37:28,120 --> 00:37:30,960
Speaker 1: other is a friend of Kevin McCarthy, and Kevin McCarthy

631
00:37:31,040 --> 00:37:34,960
Speaker 1: like begged Trump to not like name him to peek

632
00:37:35,000 --> 00:37:40,839
Speaker 1: out a win. Yeah, no, seriously, So you know it's

633
00:37:40,880 --> 00:37:44,359
Speaker 1: it's her her speech when she conceded, was sort of like,

634
00:37:44,680 --> 00:37:47,160
Speaker 1: you know, I could have won this race, but I

635
00:37:47,160 --> 00:37:51,200
Speaker 1: didn't want to throw the whole boot. Okay, I only

636
00:37:51,239 --> 00:37:53,319
Speaker 1: wanted to lick the tip a little bit a few

637
00:37:53,400 --> 00:37:56,400
Speaker 1: years ago, and then I drew the line there, and

638
00:37:56,440 --> 00:37:58,600
Speaker 1: that's why I got smashed by somebody who was willing

639
00:37:58,640 --> 00:38:02,600
Speaker 1: to regurgitate any amount of nonsense. So, you know, this

640
00:38:02,960 --> 00:38:04,640
Speaker 1: makes this is probably know, obviously the end of the

641
00:38:04,719 --> 00:38:07,120
Speaker 1: road for her as a congress person at the moment.

642
00:38:07,120 --> 00:38:09,239
Speaker 1: But there's already a lot of talk and you know

643
00:38:09,280 --> 00:38:12,400
Speaker 1: saying like, yeah, I might think about running for president too.

644
00:38:12,600 --> 00:38:14,719
Speaker 1: And there's like a new leadership pack that she's like

645
00:38:14,760 --> 00:38:17,920
Speaker 1: shifting her money into. It's called like the Great Task

646
00:38:18,080 --> 00:38:25,719
Speaker 1: or some ship, very cryptic there, it's something it's some

647
00:38:25,760 --> 00:38:29,440
Speaker 1: ship like that, very very very honest. So and then

648
00:38:29,440 --> 00:38:31,239
Speaker 1: a lot of people think, like, you know that that

649
00:38:31,360 --> 00:38:34,520
Speaker 1: may that maybe her ultimate aim is to just be

650
00:38:34,920 --> 00:38:38,279
Speaker 1: a permanent thorn in Trump's side. But yeah, I mean

651
00:38:38,520 --> 00:38:44,000
Speaker 1: her as a presidential candidate feels very like the wet

652
00:38:44,080 --> 00:38:48,120
Speaker 1: dream of like CNN Sienna loves that ship. Oh yeah,

653
00:38:48,160 --> 00:38:52,320
Speaker 1: idea of like, first of all, she's you know, got legacy,

654
00:38:52,600 --> 00:38:55,320
Speaker 1: she's got the nepotism thing going. She has like a

655
00:38:56,040 --> 00:38:59,239
Speaker 1: you know what, when the national news cycle was like, well,

656
00:38:59,320 --> 00:39:03,080
Speaker 1: Jeb Bush is going to be the nominee type sh like,

657
00:39:03,400 --> 00:39:06,080
Speaker 1: I feel like that. I could see her getting a

658
00:39:06,080 --> 00:39:09,239
Speaker 1: lot of attention that way. And if she can somehow

659
00:39:09,440 --> 00:39:12,640
Speaker 1: rip off the band aid for you know, get getting

660
00:39:12,640 --> 00:39:16,520
Speaker 1: people's mind around third parties, I would be all about that.

661
00:39:16,719 --> 00:39:18,879
Speaker 1: Who knows, I mean, it looks like a good pedigree. Though,

662
00:39:18,880 --> 00:39:20,840
Speaker 1: you know her dad, her dad actually knows how to

663
00:39:20,840 --> 00:39:25,360
Speaker 1: steal an election. That's true. Look out. I mean that's

664
00:39:25,200 --> 00:39:28,239
Speaker 1: a that's a feathering about Florida. Yeah, you know what

665
00:39:28,320 --> 00:39:31,480
Speaker 1: I mean. But yeah, we'll see what I don't know.

666
00:39:31,520 --> 00:39:33,640
Speaker 1: I mean, Amy, what do you think you see her

667
00:39:33,760 --> 00:39:37,080
Speaker 1: being serious, like having a serious political career after a

668
00:39:37,080 --> 00:39:40,840
Speaker 1: lot of people think, no, man, I think she's done.

669
00:39:41,000 --> 00:39:43,359
Speaker 1: I think she also knows that she's done. It's it's

670
00:39:43,360 --> 00:39:45,279
Speaker 1: like that scene at the end of Black Panther Where

671
00:39:45,760 --> 00:39:47,640
Speaker 1: to talk at the end, just like, you know what,

672
00:39:47,680 --> 00:39:49,840
Speaker 1: I can kind of see things your way now, it

673
00:39:50,239 --> 00:39:53,920
Speaker 1: still doesn't erase everything that the villain has done the

674
00:39:53,920 --> 00:39:57,239
Speaker 1: whole movie, you know what I mean. This Cheney is

675
00:39:57,280 --> 00:40:01,560
Speaker 1: a very staunch conservative and when we're thinking about what's

676
00:40:01,560 --> 00:40:04,520
Speaker 1: good for the country, actually forget what's good for the country,

677
00:40:04,719 --> 00:40:07,799
Speaker 1: think about where the polls are, the national polls, and

678
00:40:07,840 --> 00:40:10,480
Speaker 1: what people actually want. She's one of those people that's

679
00:40:10,520 --> 00:40:15,839
Speaker 1: voted regularly against what nationally people in America usually want

680
00:40:15,880 --> 00:40:18,600
Speaker 1: for this country. And on top of that, if you

681
00:40:18,680 --> 00:40:21,440
Speaker 1: want to just for a second, talk about her position

682
00:40:21,440 --> 00:40:25,120
Speaker 1: on waterboarding. He she doesn't think that waterboarding is actually tortured.

683
00:40:25,640 --> 00:40:28,000
Speaker 1: She's on record saying that it's not torture and that

684
00:40:28,120 --> 00:40:32,919
Speaker 1: it's an interrogative interrogation technique that works, and to this day,

685
00:40:33,000 --> 00:40:35,680
Speaker 1: to this day, she still thinks that that's why, in

686
00:40:35,760 --> 00:40:38,120
Speaker 1: the end we were able to get been leaded. Never

687
00:40:38,160 --> 00:40:40,920
Speaker 1: mind the fact that the CIA, the CIA themselves had

688
00:40:40,960 --> 00:40:46,160
Speaker 1: their own fact finding agency that produced like a six thousand,

689
00:40:46,400 --> 00:40:50,560
Speaker 1: seven hundred page report that Indian concluded that there is

690
00:40:50,560 --> 00:40:53,640
Speaker 1: no evidence saying that any information obtained by any of

691
00:40:53,680 --> 00:40:57,760
Speaker 1: those two interrogation techniques if you want to torture, nothing

692
00:40:57,800 --> 00:41:00,719
Speaker 1: obtained by torture helped us get and let him. But

693
00:41:00,760 --> 00:41:02,239
Speaker 1: that doesn't matter, you know what I mean. She's still

694
00:41:02,280 --> 00:41:06,640
Speaker 1: in that realm of conservative where her her position matters

695
00:41:06,680 --> 00:41:09,960
Speaker 1: more than the truth when it comes to actually hurting

696
00:41:10,080 --> 00:41:14,080
Speaker 1: people and hurting the country. I don't know, man, I'm

697
00:41:14,160 --> 00:41:16,879
Speaker 1: kind of glad to see her go. Yeah, it's nice

698
00:41:16,920 --> 00:41:19,880
Speaker 1: that she at the very end grew up conscious, but

699
00:41:20,000 --> 00:41:23,279
Speaker 1: we would have loved to see that conscious. But what

700
00:41:23,440 --> 00:41:27,200
Speaker 1: I think I'm more worried about is where the Conservative

701
00:41:27,239 --> 00:41:31,160
Speaker 1: and Republican Party is going, because I think this, in

702
00:41:31,520 --> 00:41:34,720
Speaker 1: my opinion, what was at stake was what Trump's power.

703
00:41:34,840 --> 00:41:36,840
Speaker 1: I think a lot of people were talking about Trump

704
00:41:36,880 --> 00:41:40,239
Speaker 1: as being this tangential figure in the Republican Party. Now

705
00:41:40,560 --> 00:41:42,600
Speaker 1: he's sort of out of the way, he's quieter, he's

706
00:41:42,600 --> 00:41:45,360
Speaker 1: off Twitter, he doesn't have that reach. I think he

707
00:41:45,440 --> 00:41:49,600
Speaker 1: proved a lot of people wrong by getting Liz Cheney totally.

708
00:41:50,560 --> 00:41:52,640
Speaker 1: You know, it's it's insane, the margin that she was

709
00:41:52,680 --> 00:41:55,400
Speaker 1: beat out by man like just that's insane, incumbent. I

710
00:41:55,440 --> 00:41:58,799
Speaker 1: don't think that's ever happened before ever. So I think

711
00:41:59,160 --> 00:42:02,279
Speaker 1: it's not a good sign if you're someone who's worried

712
00:42:02,320 --> 00:42:06,520
Speaker 1: about Trump's power. And at the same time, uh, knowing

713
00:42:06,680 --> 00:42:09,879
Speaker 1: now that the Republican Party is is a party that's

714
00:42:09,920 --> 00:42:13,879
Speaker 1: loyal to a person, it's it's gonna get hair from here.

715
00:42:14,000 --> 00:42:16,319
Speaker 1: Is a lot of people are like, Bro, I think

716
00:42:16,360 --> 00:42:19,160
Speaker 1: these some of these people think this motherfucker's Jesus. The

717
00:42:19,160 --> 00:42:21,680
Speaker 1: way some of these avangelicals we're talking to, it's like

718
00:42:21,840 --> 00:42:25,960
Speaker 1: he's redefining religion for some people, with like their adherence

719
00:42:26,040 --> 00:42:29,040
Speaker 1: to everything that he says. I mean, I think one

720
00:42:29,080 --> 00:42:31,560
Speaker 1: of the reasons why they're really energized to is like

721
00:42:31,680 --> 00:42:34,840
Speaker 1: the Republicans, it's easier to be like this motherfucker's a

722
00:42:34,880 --> 00:42:39,399
Speaker 1: trader and turn out against them while being upset like what,

723
00:42:39,480 --> 00:42:41,960
Speaker 1: you know, Democrats being in power. But for sure, I

724
00:42:42,000 --> 00:42:44,960
Speaker 1: mean like it it shows that that grievance vote was

725
00:42:45,120 --> 00:42:47,600
Speaker 1: very potent there. But I don't know, you know, she

726
00:42:47,800 --> 00:42:49,840
Speaker 1: maybe she'll spoil the party. I don't know. It's like

727
00:42:49,840 --> 00:42:51,680
Speaker 1: I don't know who she takes. It's like those people

728
00:42:51,719 --> 00:42:53,640
Speaker 1: who might be like I can't get with Trump, It's like,

729
00:42:53,640 --> 00:42:56,120
Speaker 1: well don't. I don't know if those are votes for

730
00:42:56,160 --> 00:43:00,480
Speaker 1: anybody else but him anyway, But yeah. I recently ran

731
00:43:00,560 --> 00:43:05,160
Speaker 1: a piece in Slate about the line between extremism and

732
00:43:05,280 --> 00:43:09,160
Speaker 1: mainstream Republican politics shrinking right, and so I talked to

733
00:43:09,680 --> 00:43:12,839
Speaker 1: a research fellow at the Sufian Center, which is like

734
00:43:12,880 --> 00:43:17,360
Speaker 1: this far right not not far. They they investigate extremism

735
00:43:17,360 --> 00:43:21,440
Speaker 1: wherever it comes from, and they found that that line

736
00:43:21,680 --> 00:43:24,840
Speaker 1: that's you know, the distance that a person has to

737
00:43:24,920 --> 00:43:32,600
Speaker 1: travel to find crazy conspiracies and violent rhetoric has virtually disappeared.

738
00:43:32,960 --> 00:43:34,960
Speaker 1: And now if you go online and you're looking for

739
00:43:35,080 --> 00:43:39,640
Speaker 1: just running the mill conservative ideas, you're pretty much guaranteed

740
00:43:39,960 --> 00:43:42,319
Speaker 1: to be funneled into one of these corners of the

741
00:43:42,320 --> 00:43:46,279
Speaker 1: Internet where you're bounty encounter some of the most hardcore ship,

742
00:43:46,719 --> 00:43:50,080
Speaker 1: you know what I mean. And so this, I think,

743
00:43:50,840 --> 00:43:53,680
Speaker 1: like the whole this chainey thing is just it's like

744
00:43:53,719 --> 00:43:57,320
Speaker 1: a symptom of a bigger problem, which is that the

745
00:43:57,320 --> 00:44:01,480
Speaker 1: the person who was online looking for conservative ideas now

746
00:44:02,080 --> 00:44:06,960
Speaker 1: is just being thrashed with so much of this crazy

747
00:44:07,040 --> 00:44:10,879
Speaker 1: extremist ship. And I'm not talking about just like extremism

748
00:44:10,920 --> 00:44:14,400
Speaker 1: on like abortion or you know, I'm talking about we

749
00:44:14,480 --> 00:44:16,480
Speaker 1: got to burn it down, you know what I mean,

750
00:44:16,760 --> 00:44:22,000
Speaker 1: like accelerationist. Yeah, it's insane. So I think that distinction

751
00:44:22,000 --> 00:44:25,120
Speaker 1: is important between like what Republican ideas are and like

752
00:44:25,200 --> 00:44:27,879
Speaker 1: the the extremism ship that this group is talking about.

753
00:44:27,880 --> 00:44:32,319
Speaker 1: When they're for example, trying to kind of tear all

754
00:44:32,320 --> 00:44:35,160
Speaker 1: of the institutions apart, tear trust away from these two

755
00:44:35,239 --> 00:44:38,800
Speaker 1: institutions so that people feel helpless and working with the system,

756
00:44:39,000 --> 00:44:42,359
Speaker 1: so they start looking for solutions outside the system. And

757
00:44:42,400 --> 00:44:45,440
Speaker 1: those solutions are not going to be peaceful. Right now,

758
00:44:45,480 --> 00:44:50,080
Speaker 1: we're talking about subverting the will of American democracy, the

759
00:44:50,080 --> 00:44:52,480
Speaker 1: will of your neighbor. Now you're just trying to enforce

760
00:44:52,560 --> 00:44:54,879
Speaker 1: it by force. And so what does that look like?

761
00:44:54,960 --> 00:44:57,480
Speaker 1: It looks like the dude going and setting his car

762
00:44:57,520 --> 00:45:00,200
Speaker 1: on fire in front of the in Washington. Do you

763
00:45:00,200 --> 00:45:02,840
Speaker 1: see and we're talking about the dude who tried to

764
00:45:02,880 --> 00:45:06,920
Speaker 1: blast through a bulletproof glass and in an FBI building

765
00:45:06,920 --> 00:45:10,080
Speaker 1: in Cincinnati with a nailgun. You know, That's what that

766
00:45:10,120 --> 00:45:13,080
Speaker 1: looks like. And so I think it's it's not looking good.

767
00:45:13,160 --> 00:45:16,319
Speaker 1: It's not looking good. But do you think like he

768
00:45:16,640 --> 00:45:22,480
Speaker 1: is more electorally viable than like what people are giving

769
00:45:22,560 --> 00:45:24,960
Speaker 1: him credit? Like it it seems to me like he

770
00:45:25,840 --> 00:45:31,520
Speaker 1: is the presumptive, presumptive, like winner of not even the

771
00:45:31,640 --> 00:45:35,880
Speaker 1: nominee primary. I don't like he's gonna he's gonna be

772
00:45:35,960 --> 00:45:39,840
Speaker 1: the nominee. Like I feel like the amount of energy

773
00:45:39,960 --> 00:45:43,960
Speaker 1: we're seeing out here and like unprecedented wins and you know,

774
00:45:44,120 --> 00:45:47,400
Speaker 1: granted as Wyoming or whatever the funk, but like it

775
00:45:47,520 --> 00:45:53,080
Speaker 1: just feels like the people are once again sleeping on

776
00:45:53,239 --> 00:45:56,800
Speaker 1: the fact that Trump is going to be the president

777
00:45:56,840 --> 00:46:01,000
Speaker 1: again barring some manner of like I don't know charges

778
00:46:01,040 --> 00:46:05,560
Speaker 1: against him, which is also very unlikely. I feel like,

779
00:46:05,840 --> 00:46:10,160
Speaker 1: I don't know, man, it's bleak bleak terms, and like

780
00:46:10,239 --> 00:46:13,160
Speaker 1: what does a Trump presidency look like? Yeah, but I

781
00:46:13,200 --> 00:46:15,080
Speaker 1: don't know. I mean, that's why that's why it's close

782
00:46:15,120 --> 00:46:17,040
Speaker 1: to pick. Gotta pay attention to these mid terms, man,

783
00:46:17,080 --> 00:46:21,000
Speaker 1: that's you'll see what a how much people are like,

784
00:46:21,040 --> 00:46:23,320
Speaker 1: oh do I have to vote to keep my rights

785
00:46:23,440 --> 00:46:25,080
Speaker 1: for the first Like do I need to go get

786
00:46:25,080 --> 00:46:27,800
Speaker 1: out to do that? Will they do that? Are people

787
00:46:28,160 --> 00:46:32,040
Speaker 1: connected enough to what the stakes are? Is by virtue

788
00:46:32,080 --> 00:46:35,040
Speaker 1: of all of the talk in like d C really

789
00:46:35,080 --> 00:46:37,120
Speaker 1: centering around like what's going on with Trump? Like is

790
00:46:37,160 --> 00:46:38,840
Speaker 1: he going to jail? Is he getting indicted? Is he

791
00:46:38,840 --> 00:46:43,640
Speaker 1: getting be charged? Definitely good for like the media energy machine.

792
00:46:44,360 --> 00:46:46,680
Speaker 1: But then like when I do see people like Eric

793
00:46:46,680 --> 00:46:50,120
Speaker 1: Trump being like these people were like fighting over giving

794
00:46:50,160 --> 00:46:52,000
Speaker 1: me dinner. You gotta see that. I'm like that did

795
00:46:52,040 --> 00:46:56,040
Speaker 1: ship didn't happen? Full? Shut up? Like, it's not like that, okay,

796
00:46:56,080 --> 00:46:58,640
Speaker 1: but I do understand that it is. This is the

797
00:46:58,719 --> 00:47:02,759
Speaker 1: absolute position Fox Trump, the right wing loves to be in,

798
00:47:02,880 --> 00:47:05,080
Speaker 1: is to get into like we got they they're coming

799
00:47:05,120 --> 00:47:09,400
Speaker 1: for us mode. But you know, again, seeing how like

800
00:47:09,440 --> 00:47:13,560
Speaker 1: ill equipped Republicans are when asked to comment on everything

801
00:47:13,760 --> 00:47:16,319
Speaker 1: are like about this situation, then you're like, damn, my god,

802
00:47:16,400 --> 00:47:19,319
Speaker 1: I'm sure these people would again rather be trying to say, like,

803
00:47:19,560 --> 00:47:24,239
Speaker 1: actually following gas prices is bad for Americans, because that

804
00:47:24,320 --> 00:47:29,400
Speaker 1: was like, you know, I think the lesson from sixteen

805
00:47:30,160 --> 00:47:33,880
Speaker 1: when Hillary lost was that elections aren't one by energizing

806
00:47:33,920 --> 00:47:36,080
Speaker 1: your base. The elections are one by getting the other

807
00:47:36,120 --> 00:47:39,160
Speaker 1: side to not show up, you know, right. That was

808
00:47:39,200 --> 00:47:42,919
Speaker 1: the issue with Hillary. It's not that Trump's support got

809
00:47:42,960 --> 00:47:46,520
Speaker 1: him over the edge. It was that, but also Hillary

810
00:47:46,520 --> 00:47:50,040
Speaker 1: supporters didn't show up, you know, partly because of you know,

811
00:47:50,120 --> 00:47:53,080
Speaker 1: her her emails and the FBI opening and investigation just

812
00:47:53,760 --> 00:47:56,320
Speaker 1: literally the same month of the election. But at the

813
00:47:56,360 --> 00:47:58,719
Speaker 1: same time it's it's you know, I think we need

814
00:47:58,760 --> 00:48:02,200
Speaker 1: to be thinking about that moving forward a little bit more,

815
00:48:02,640 --> 00:48:07,160
Speaker 1: because what is it that's going to get Democrats out

816
00:48:07,400 --> 00:48:10,160
Speaker 1: and to vote. I think the problem is right. We

817
00:48:10,200 --> 00:48:12,319
Speaker 1: always talk about it. I just saw a headline it's like,

818
00:48:12,360 --> 00:48:14,959
Speaker 1: what can Joe Biden do to bring out the youth

819
00:48:15,040 --> 00:48:18,400
Speaker 1: vote or you know, like what has to act happen?

820
00:48:18,480 --> 00:48:21,520
Speaker 1: And it sounds like this thing where the youth vote

821
00:48:21,640 --> 00:48:24,520
Speaker 1: is this thing that like it's like, through this alchemy

822
00:48:24,640 --> 00:48:28,040
Speaker 1: we can energize them. What is the secret recipe? When

823
00:48:28,080 --> 00:48:31,520
Speaker 1: really it's about can it's not about the youth vote

824
00:48:31,640 --> 00:48:35,680
Speaker 1: waking up? It's about can the party actually appeal to people?

825
00:48:35,719 --> 00:48:37,680
Speaker 1: Stop putting it in the in the hands of like

826
00:48:37,719 --> 00:48:39,560
Speaker 1: can the youth vote wake up? It's like are you

827
00:48:39,600 --> 00:48:43,480
Speaker 1: even are you even espousing policies that interest people? Like,

828
00:48:43,640 --> 00:48:46,080
Speaker 1: can you even connect with them? It's not that you're

829
00:48:46,120 --> 00:48:49,160
Speaker 1: trying to prod this like dead fucking body on the

830
00:48:49,160 --> 00:48:51,080
Speaker 1: side of the road, like hey, come on, man, wake up.

831
00:48:51,520 --> 00:48:53,640
Speaker 1: It's about can you even put something in the air

832
00:48:53,719 --> 00:48:56,080
Speaker 1: that people like, Oh, that's a direction that I believe

833
00:48:56,120 --> 00:48:57,799
Speaker 1: in that we can go for because a lot of

834
00:48:57,800 --> 00:48:59,920
Speaker 1: times people, you know, here a lot of political talk

835
00:49:00,120 --> 00:49:02,880
Speaker 1: like this's a bunch of bullshit. Case in point, sucking

836
00:49:02,960 --> 00:49:06,800
Speaker 1: Andrew Yang recently out here talking about his third Party

837
00:49:07,120 --> 00:49:10,799
Speaker 1: on CNN, and he this guy thinks he's so big brain.

838
00:49:10,960 --> 00:49:13,359
Speaker 1: He's like, no, man, it's the fucking it's about. It's

839
00:49:13,360 --> 00:49:17,000
Speaker 1: about going forward, man, it's about progress. Okay, I know

840
00:49:17,080 --> 00:49:20,279
Speaker 1: I progressed means something very specific to me. But when

841
00:49:20,320 --> 00:49:23,360
Speaker 1: he was asked by Jim Accost on CNN, this, dude,

842
00:49:24,080 --> 00:49:27,000
Speaker 1: oh my, it's so really you gotta listen to this.

843
00:49:27,080 --> 00:49:29,880
Speaker 1: But like, this is what happens when your people pleasing

844
00:49:29,960 --> 00:49:32,080
Speaker 1: part of your brain is completely blown out because you

845
00:49:32,080 --> 00:49:33,920
Speaker 1: don't even know what to do it, Like, how can

846
00:49:33,960 --> 00:49:37,840
Speaker 1: I please anybody? These things have taken over my body? Okay,

847
00:49:37,840 --> 00:49:41,120
Speaker 1: here we go. Please please show us, show us the

848
00:49:41,120 --> 00:49:47,279
Speaker 1: way Andrew on both sides to come up with policy. Yeah,

849
00:49:47,320 --> 00:49:49,799
Speaker 1: but Andrew, you're gonna have to have policy positions at

850
00:49:49,840 --> 00:49:52,600
Speaker 1: some point. How does the Forward Party feel about ro

851
00:49:52,760 --> 00:49:57,840
Speaker 1: versus wage should have been overturned? Well, I personally I

852
00:49:57,920 --> 00:50:01,560
Speaker 1: don't think that women's reproductive rights are fundamental human rights.

853
00:50:01,719 --> 00:50:04,880
Speaker 1: But the Forward Party has not left or right. But

854
00:50:05,000 --> 00:50:08,520
Speaker 1: Forward stands on even the most divisive and contentious issues.

855
00:50:08,680 --> 00:50:15,120
Speaker 1: Don't have to. You can't just say, well, you know

856
00:50:15,160 --> 00:50:16,719
Speaker 1: this is a hot button issue, so I'm not going

857
00:50:16,760 --> 00:50:18,759
Speaker 1: to take a position on you. You know you want

858
00:50:18,760 --> 00:50:20,200
Speaker 1: to run the country, you're gonna have to make some

859
00:50:20,239 --> 00:50:24,360
Speaker 1: hard decisions. Andrew. Again, the Forward Party is about that

860
00:50:24,440 --> 00:50:27,240
Speaker 1: common sense consensus majority of view, which is very clear

861
00:50:27,520 --> 00:50:31,600
Speaker 1: on abortion, it's clear about guns, what about change, It's

862
00:50:31,600 --> 00:50:33,520
Speaker 1: actually clear on just about every issue under the sun.

863
00:50:34,920 --> 00:50:38,560
Speaker 1: To buy because of the nature of our systems, should

864
00:50:38,560 --> 00:50:41,920
Speaker 1: eighteen year olds be able to buy air fifteens? Again,

865
00:50:41,960 --> 00:50:46,840
Speaker 1: the common sense consensus. There should be some rules around

866
00:50:46,920 --> 00:50:49,920
Speaker 1: background checks and access to firearms. But we're not getting

867
00:50:49,920 --> 00:50:52,440
Speaker 1: any of these things, Jim, because the two party system

868
00:50:52,480 --> 00:50:55,719
Speaker 1: does not need to deliver. Okay, it doesn't even sound

869
00:50:55,719 --> 00:50:58,480
Speaker 1: like you can deliver on even having a take on ship.

870
00:50:58,920 --> 00:51:03,719
Speaker 1: This is the So the idea that he's pitching is

871
00:51:03,920 --> 00:51:08,120
Speaker 1: a third party. That is, the center is to the center,

872
00:51:08,640 --> 00:51:13,480
Speaker 1: and that is based on this talking point that was

873
00:51:13,560 --> 00:51:17,960
Speaker 1: created by the Republicans, that is, the Democrats are too

874
00:51:18,000 --> 00:51:21,360
Speaker 1: far to the left, too extreme, except they're not extreme

875
00:51:21,400 --> 00:51:26,960
Speaker 1: about literally anything like then there's not an extreme left

876
00:51:27,320 --> 00:51:31,440
Speaker 1: position that is occupied by the Democratic Party. So like

877
00:51:31,560 --> 00:51:36,360
Speaker 1: anytime you try and ask, like the this new idea

878
00:51:36,400 --> 00:51:40,600
Speaker 1: for a third party to like articulate how their position

879
00:51:40,760 --> 00:51:45,120
Speaker 1: is different from the Democrats in any way they can't

880
00:51:45,200 --> 00:51:48,080
Speaker 1: because the Democrats are the center's party. But the issue

881
00:51:48,120 --> 00:51:51,160
Speaker 1: is we don't have a party that is to the

882
00:51:51,239 --> 00:51:54,640
Speaker 1: left or like he says left or right beforeward. Okay,

883
00:51:54,640 --> 00:51:59,000
Speaker 1: so you're talking progress, right, that's I think that's a

884
00:51:59,080 --> 00:52:03,080
Speaker 1: rap sor if that's you're saying, because we're talking progress. Inherently,

885
00:52:03,400 --> 00:52:06,800
Speaker 1: we're talking about disrupting the status quo, and you should

886
00:52:06,840 --> 00:52:09,560
Speaker 1: be able to articulate things like rather than falling back

887
00:52:09,560 --> 00:52:12,280
Speaker 1: on a tidy talking point like well they're coming since consensus.

888
00:52:12,400 --> 00:52:15,680
Speaker 1: Well if your party represents that, then fucking say that, right,

889
00:52:16,000 --> 00:52:18,040
Speaker 1: And what I just at the problem, it's like you

890
00:52:18,120 --> 00:52:19,960
Speaker 1: just there needs to be a party. It's like, Okay,

891
00:52:19,960 --> 00:52:21,960
Speaker 1: we're not gonna fucking waffles, like we need to go

892
00:52:22,160 --> 00:52:26,040
Speaker 1: hard part, Like we go hard. We're not mincing words

893
00:52:26,080 --> 00:52:29,080
Speaker 1: about ship like and that. That's what the Republicans are

894
00:52:29,160 --> 00:52:31,879
Speaker 1: right now. But they're just going hard for fucking autocracy

895
00:52:31,960 --> 00:52:37,120
Speaker 1: and the fucking crystal fascism. Well, right, there's there's a

896
00:52:37,719 --> 00:52:41,719
Speaker 1: like whole middle, like fuzzy middle part that is like

897
00:52:41,800 --> 00:52:47,600
Speaker 1: traditional Democrats and traditional like Republicans, and then there is

898
00:52:48,080 --> 00:52:52,520
Speaker 1: like a fascist thing that is what like Mega has

899
00:52:52,560 --> 00:52:56,719
Speaker 1: become and that's it. That's the entirety of like American

900
00:52:57,280 --> 00:53:01,960
Speaker 1: political thought. Like those are your options. Nobody has articulated

901
00:53:02,040 --> 00:53:05,520
Speaker 1: anything else other than you know, like a handful of

902
00:53:05,600 --> 00:53:09,680
Speaker 1: people who are not candidates unless you yourself are like

903
00:53:09,800 --> 00:53:13,239
Speaker 1: reading like about like actually educating yourself and like socialism

904
00:53:13,239 --> 00:53:15,200
Speaker 1: and things like that. I mean, yeah, there are there

905
00:53:15,200 --> 00:53:17,799
Speaker 1: are many ways to look at, you know, how our

906
00:53:17,840 --> 00:53:21,160
Speaker 1: country is operating. But I think because the ones that

907
00:53:21,200 --> 00:53:22,719
Speaker 1: like you're saying, those are the ones that are most

908
00:53:22,760 --> 00:53:26,239
Speaker 1: readily available and overly represented for people are just like

909
00:53:26,320 --> 00:53:30,440
Speaker 1: let me click on this news site. Right, What do

910
00:53:30,640 --> 00:53:34,719
Speaker 1: you guys think about like preferential voting? You know, when

911
00:53:34,760 --> 00:53:38,760
Speaker 1: you like assigned a party in number and you say, okay,

912
00:53:38,840 --> 00:53:43,960
Speaker 1: I kind of like I'll give Democrats to three Republicans

913
00:53:43,960 --> 00:53:45,920
Speaker 1: at two in the Green Party one and you just

914
00:53:46,000 --> 00:53:48,200
Speaker 1: like they calculated that way. I think they do that

915
00:53:48,239 --> 00:53:52,280
Speaker 1: in other countries. Yeah, you do that. I mean anything

916
00:53:52,360 --> 00:53:55,040
Speaker 1: better than the two party system that we have right now,

917
00:53:55,080 --> 00:53:58,560
Speaker 1: Like that the current like winner take all thing, and

918
00:53:58,880 --> 00:54:05,680
Speaker 1: the current like entrenched Republican Democrat are not you know

919
00:54:05,840 --> 00:54:09,320
Speaker 1: that like they make it impossible for a third party,

920
00:54:09,400 --> 00:54:11,959
Speaker 1: So like, yeah, that that would be great I feel

921
00:54:12,000 --> 00:54:16,880
Speaker 1: like the only way we see any third party is

922
00:54:16,880 --> 00:54:21,680
Speaker 1: it is if Trump is prevented from being the Republican nominee,

923
00:54:21,719 --> 00:54:25,440
Speaker 1: then like comes through as a third party candidate and

924
00:54:26,000 --> 00:54:30,759
Speaker 1: like something extreme and accidental and you know, something that

925
00:54:31,160 --> 00:54:33,920
Speaker 1: neither of the two major parties can deal with because

926
00:54:34,000 --> 00:54:37,799
Speaker 1: right now, like there's so the whole that they are

927
00:54:37,960 --> 00:54:42,080
Speaker 1: the entire system Republican Democratic Party. So like there, you

928
00:54:42,120 --> 00:54:45,839
Speaker 1: can't you really can't do anything unless you already like

929
00:54:45,960 --> 00:54:50,000
Speaker 1: have built in a majority of like you know, just

930
00:54:50,320 --> 00:54:53,560
Speaker 1: insane numbers or energy or or something like that. I mean,

931
00:54:53,560 --> 00:54:56,080
Speaker 1: I feel like the energy right now is with fucking

932
00:54:56,160 --> 00:55:00,640
Speaker 1: organized labor. Right That's something that is becoming a increasingly

933
00:55:01,480 --> 00:55:04,280
Speaker 1: more at the front of mind for American people, especially

934
00:55:04,280 --> 00:55:07,239
Speaker 1: working people, and we see a lot of people who

935
00:55:07,320 --> 00:55:10,920
Speaker 1: are you know, fighting to try and get equitable wages

936
00:55:11,040 --> 00:55:13,760
Speaker 1: and benefits and things like that. And again we always,

937
00:55:13,800 --> 00:55:15,680
Speaker 1: you know, you always see like, oh, these are these

938
00:55:15,680 --> 00:55:18,120
Speaker 1: talking points work when you're like, hey man, you should

939
00:55:18,160 --> 00:55:20,759
Speaker 1: be able to fucking live off a one job and

940
00:55:20,760 --> 00:55:24,000
Speaker 1: ship like that. But again the issue is you always

941
00:55:24,160 --> 00:55:26,160
Speaker 1: you're always gonna go up against the donor class, which

942
00:55:26,160 --> 00:55:27,719
Speaker 1: are the people who cut the checks for the people

943
00:55:27,760 --> 00:55:29,640
Speaker 1: whose vote you're trying to get, and they're like, hey, man,

944
00:55:29,680 --> 00:55:32,000
Speaker 1: don't don't talk that ship like you're gonna fucking raise

945
00:55:32,080 --> 00:55:36,279
Speaker 1: my taxes. Man, funk out of here. Fucking I'll wreck

946
00:55:36,360 --> 00:55:39,879
Speaker 1: your whole ship with fucking with attack ads. Come on, now,

947
00:55:41,560 --> 00:55:44,720
Speaker 1: you know what I You know, I kind of hate

948
00:55:44,840 --> 00:55:47,640
Speaker 1: the way that it's set up right now because it

949
00:55:47,920 --> 00:55:50,680
Speaker 1: will split the vote like crazy. You know what I

950
00:55:50,680 --> 00:55:53,240
Speaker 1: mean by splitting the vote, like if we have people

951
00:55:53,280 --> 00:55:55,200
Speaker 1: who are going to be looking at this long list

952
00:55:55,239 --> 00:55:58,200
Speaker 1: of parties and they're going to be thinking, oh, well,

953
00:55:58,239 --> 00:56:00,000
Speaker 1: I kind of I'm not sure if I'm gonna go

954
00:56:00,160 --> 00:56:03,040
Speaker 1: left or super left or even more left, then that

955
00:56:03,800 --> 00:56:06,239
Speaker 1: that will split the vote. So I'm Egyptian and I

956
00:56:06,280 --> 00:56:09,759
Speaker 1: was paying really close attention, and I think it was

957
00:56:10,239 --> 00:56:13,360
Speaker 1: twelve when you just had like the first democratic election

958
00:56:13,440 --> 00:56:15,960
Speaker 1: ever in its history, right, going all the way back

959
00:56:16,000 --> 00:56:19,000
Speaker 1: to Phonic times even, And the way that they did

960
00:56:19,080 --> 00:56:21,200
Speaker 1: their election was kind of like what we do here

961
00:56:21,200 --> 00:56:24,080
Speaker 1: where everybody is invited to make their own parties, right,

962
00:56:24,360 --> 00:56:27,480
Speaker 1: But there were these two existing parties that were already

963
00:56:27,600 --> 00:56:30,040
Speaker 1: they had already a ton of support. I'm talking about

964
00:56:30,040 --> 00:56:33,840
Speaker 1: the Muslim Brotherhood, which is like the theocratic conservative party.

965
00:56:33,880 --> 00:56:35,879
Speaker 1: But then they also had the military which is sort

966
00:56:35,880 --> 00:56:38,200
Speaker 1: of the old regime, which was also like a super

967
00:56:38,239 --> 00:56:42,360
Speaker 1: hardcore conservative party. So everybody who wanted to vote progressive

968
00:56:42,560 --> 00:56:45,200
Speaker 1: or liberal, which when I was down there and was

969
00:56:45,239 --> 00:56:49,040
Speaker 1: interviewing people into her square was most people, right. Nobody

970
00:56:49,080 --> 00:56:52,520
Speaker 1: wanted the Muslim Brotherhood and nobody wanted the old government

971
00:56:52,520 --> 00:56:55,640
Speaker 1: that they just revolted against, and so they were just

972
00:56:55,800 --> 00:56:57,960
Speaker 1: during argue over like who was the better of these

973
00:56:58,000 --> 00:57:01,480
Speaker 1: three different liberal party ease, and so what happened in

974
00:57:01,480 --> 00:57:07,279
Speaker 1: the end, the Conservatives voted for the Muslim group, the

975
00:57:07,360 --> 00:57:10,560
Speaker 1: Muslim Brotherhood. The military people voted for the military group,

976
00:57:10,920 --> 00:57:12,680
Speaker 1: and they were all in line there was, they had

977
00:57:12,719 --> 00:57:15,440
Speaker 1: their support, and then all the people voted for Liberals,

978
00:57:15,440 --> 00:57:17,240
Speaker 1: which if you added up all those tallies they would

979
00:57:17,240 --> 00:57:20,480
Speaker 1: have won. They weren't even on the runoff. They weren't

980
00:57:20,480 --> 00:57:22,600
Speaker 1: even in the top two, you know what I mean.

981
00:57:22,960 --> 00:57:25,800
Speaker 1: It was like split between a hundred different parties in Canada.

982
00:57:25,960 --> 00:57:29,000
Speaker 1: So yeah, exactly, yeah, And so all of the people

983
00:57:29,040 --> 00:57:31,160
Speaker 1: that I when I was there, when they were talking

984
00:57:31,200 --> 00:57:33,360
Speaker 1: about who are you gonna vote for this person or

985
00:57:33,400 --> 00:57:35,840
Speaker 1: that person, neither of them were ever hurt from again,

986
00:57:35,920 --> 00:57:38,240
Speaker 1: you know, because they didn't have that kind of support

987
00:57:38,520 --> 00:57:41,720
Speaker 1: to compete with the government or compete with I'm playing

988
00:57:41,760 --> 00:57:44,240
Speaker 1: at the government, compete with the military, or compete with

989
00:57:44,880 --> 00:57:48,800
Speaker 1: the Muslim brotherhood. So I'm almost like, I think we

990
00:57:48,840 --> 00:57:50,520
Speaker 1: need to make up our mind. Do we want just

991
00:57:50,600 --> 00:57:53,120
Speaker 1: the two parties. Are we gonna vote fascism yes or no?

992
00:57:53,880 --> 00:57:57,240
Speaker 1: Or do we want that kind of tiered system where

993
00:57:57,280 --> 00:57:59,800
Speaker 1: we can say I'm gonna give this one three points,

994
00:57:59,840 --> 00:58:02,280
Speaker 1: this on two points, this from five points, and that

995
00:58:02,360 --> 00:58:04,960
Speaker 1: way there's sort of at least like a second choice,

996
00:58:05,400 --> 00:58:08,920
Speaker 1: you know. Yeah, it's like and at the end of

997
00:58:08,920 --> 00:58:11,320
Speaker 1: the day, like whenever I think of I'm like, yeah,

998
00:58:11,360 --> 00:58:13,360
Speaker 1: that would work. And then I'm like, but the second

999
00:58:13,480 --> 00:58:16,000
Speaker 1: you give people the option to take a bite out

1000
00:58:16,040 --> 00:58:19,720
Speaker 1: of a corporation's ass, and that's popular, Like the amount

1001
00:58:19,720 --> 00:58:23,080
Speaker 1: of money that's spent to like defeat policies like that,

1002
00:58:23,160 --> 00:58:25,280
Speaker 1: I'm like, what's first, Like, do we just need to

1003
00:58:25,320 --> 00:58:28,280
Speaker 1: get the money out of politics first? You know, to

1004
00:58:28,440 --> 00:58:32,320
Speaker 1: even to even have some semblance of a process that

1005
00:58:32,520 --> 00:58:35,800
Speaker 1: isn't completely tampered with by moneyed interest, but on some

1006
00:58:35,920 --> 00:58:38,600
Speaker 1: level it always we always be because you know, our

1007
00:58:38,640 --> 00:58:41,040
Speaker 1: reliance on like the media and things like that. But

1008
00:58:41,960 --> 00:58:44,520
Speaker 1: it's uh, it's yeah, a complex problem. And yeah, at

1009
00:58:44,520 --> 00:58:46,320
Speaker 1: the moment, I think we're just stuck with, Hey, you

1010
00:58:46,320 --> 00:58:49,560
Speaker 1: want which old guy you want? You want like kind

1011
00:58:49,600 --> 00:58:52,560
Speaker 1: of oh yeah, exactly pick a old guy. Which one

1012
00:58:52,600 --> 00:58:54,760
Speaker 1: you want? The one who's like, you know, kind of

1013
00:58:54,880 --> 00:58:59,000
Speaker 1: chill or the one who's definitely a fascist? Uh? And

1014
00:58:59,040 --> 00:59:02,760
Speaker 1: then you're like, what about like someone fascist or fascist? Light?

1015
00:59:02,840 --> 00:59:07,200
Speaker 1: Pick one? Right, exactly, right, sugar free fascist. Citizens United

1016
00:59:07,240 --> 00:59:09,640
Speaker 1: has been like a flashpoint on the left that I've

1017
00:59:09,640 --> 00:59:12,840
Speaker 1: seen at least some people rallying behind. I know the

1018
00:59:12,840 --> 00:59:16,320
Speaker 1: Bernie Sanders crowd was very in favor of repealing that.

1019
00:59:17,240 --> 00:59:21,200
Speaker 1: I would love to see more energy behind that. I

1020
00:59:21,280 --> 00:59:23,880
Speaker 1: think you're right, I think and I do some some

1021
00:59:23,920 --> 00:59:26,920
Speaker 1: of my own monitoring of the right wing extremists, and

1022
00:59:26,960 --> 00:59:29,720
Speaker 1: they hate money in politics just as much as a

1023
00:59:29,720 --> 00:59:33,520
Speaker 1: Bernie Sanders supporter would, you know. And in fact, they

1024
00:59:33,560 --> 00:59:36,680
Speaker 1: some of them love Trump so much because they see

1025
00:59:36,760 --> 00:59:39,800
Speaker 1: him as the anti establishment candidate. And right now they're

1026
00:59:39,800 --> 00:59:42,479
Speaker 1: doing a victory lap over this Cheney because they see

1027
00:59:42,560 --> 00:59:49,040
Speaker 1: him as old as the as the person that can

1028
00:59:49,080 --> 00:59:52,160
Speaker 1: get rid of some of these establishment types, you know.

1029
00:59:52,800 --> 00:59:55,160
Speaker 1: So it's I think one of the tweets that I

1030
00:59:55,160 --> 00:59:58,440
Speaker 1: saw from like this hardcore right person was, you know,

1031
00:59:58,480 --> 01:00:01,720
Speaker 1: because of Trump, we won't have a bush or a

1032
01:00:01,800 --> 01:00:06,680
Speaker 1: chainey in politics right now, right, and and that they

1033
01:00:06,920 --> 01:00:10,440
Speaker 1: see him as like that that kind of politics Vanquisher.

1034
01:00:10,720 --> 01:00:13,400
Speaker 1: And so I think if we can find a way

1035
01:00:13,440 --> 01:00:17,640
Speaker 1: to bring that to the forefront, I think that would

1036
01:00:17,640 --> 01:00:20,120
Speaker 1: be a strong united I think you're one. I'll think

1037
01:00:20,160 --> 01:00:21,959
Speaker 1: it's just the one. It's like the answer to every

1038
01:00:22,000 --> 01:00:24,600
Speaker 1: question we have, you know, Like we talk about like, well,

1039
01:00:24,600 --> 01:00:26,480
Speaker 1: how come it still being so hard for the unit,

1040
01:00:26,560 --> 01:00:28,840
Speaker 1: like this Starbucks union push right now, It's like, well,

1041
01:00:29,040 --> 01:00:32,400
Speaker 1: the fucking and like the National Labor Relations Board is

1042
01:00:32,480 --> 01:00:36,400
Speaker 1: severely underfunded and they can't keep up with helping like

1043
01:00:36,560 --> 01:00:39,880
Speaker 1: workers organized, when like that's the federal agency tasked with it.

1044
01:00:40,200 --> 01:00:43,520
Speaker 1: And you get why people will drag their heels as

1045
01:00:43,560 --> 01:00:46,520
Speaker 1: representatives of Congress to not fund certain things because of

1046
01:00:46,520 --> 01:00:49,080
Speaker 1: how how the money flows. And I'm like, it answers

1047
01:00:49,120 --> 01:00:51,400
Speaker 1: so many questions. And I remember when I was working

1048
01:00:51,400 --> 01:00:53,840
Speaker 1: in politics, I was like, damn, it's this fucking just

1049
01:00:54,680 --> 01:00:57,640
Speaker 1: in front of your face forward. It's like this motherfucker

1050
01:00:57,720 --> 01:01:00,960
Speaker 1: signs your biggest check, so now all of your fucking

1051
01:01:01,080 --> 01:01:05,200
Speaker 1: energy goes into protecting this person's fucking business interests. And

1052
01:01:05,240 --> 01:01:07,320
Speaker 1: then like, meanwhile, you said, go you glad hand in

1053
01:01:07,360 --> 01:01:08,960
Speaker 1: your district and be like, yeah, man, we'll build this

1054
01:01:09,000 --> 01:01:12,080
Speaker 1: community center and ship, but no, you're not. You're gonna

1055
01:01:12,080 --> 01:01:14,040
Speaker 1: go because you've been paid to like vote a certain

1056
01:01:14,080 --> 01:01:16,400
Speaker 1: way on these like like ten bills every year that

1057
01:01:16,440 --> 01:01:18,360
Speaker 1: really matter most of your donors. And then you fucking

1058
01:01:18,400 --> 01:01:20,360
Speaker 1: go on with it and you don't, and you you

1059
01:01:20,560 --> 01:01:23,440
Speaker 1: you save your time from having to actually fundraise like

1060
01:01:23,480 --> 01:01:27,960
Speaker 1: small dollar donations because lobbyists come in with huge packaged

1061
01:01:28,240 --> 01:01:32,160
Speaker 1: donations from other moneyed interests. And now you're like, oh, Ship,

1062
01:01:32,320 --> 01:01:34,800
Speaker 1: I'm set. I got more. Note who's gonna try and

1063
01:01:34,840 --> 01:01:37,480
Speaker 1: step to me in a primary? I'll blow them out

1064
01:01:37,520 --> 01:01:39,720
Speaker 1: with the amount of cash I have because I'm backed

1065
01:01:39,720 --> 01:01:41,919
Speaker 1: by all this money. And I think that's the one

1066
01:01:42,120 --> 01:01:44,400
Speaker 1: that's the only that's like I feel like without that

1067
01:01:44,520 --> 01:01:48,000
Speaker 1: piece being taken out, there's absolutely no fucking way. Because

1068
01:01:48,000 --> 01:01:50,360
Speaker 1: they are they're always able to put their fingers and ship,

1069
01:01:51,160 --> 01:01:53,200
Speaker 1: let's take a quick break, we'll come back, We'll we'll

1070
01:01:53,280 --> 01:02:04,920
Speaker 1: keep talking about this and what's happening with Starbucks and

1071
01:02:04,960 --> 01:02:08,640
Speaker 1: we're back. I just want to touch briefly. I'm Burger King.

1072
01:02:09,560 --> 01:02:12,440
Speaker 1: They're just like there. I just feel like they're creepy,

1073
01:02:12,880 --> 01:02:16,720
Speaker 1: you know, like the Burger King mascot guy that's creepy.

1074
01:02:17,000 --> 01:02:20,160
Speaker 1: He's creepy. I'm still adjusting. He was gonna say just

1075
01:02:20,280 --> 01:02:23,120
Speaker 1: a word for him. I don't think he's as scary

1076
01:02:23,160 --> 01:02:28,040
Speaker 1: as their original Ronald McDonald bell. Oh yeah, I mean yeah, Okay,

1077
01:02:28,040 --> 01:02:33,160
Speaker 1: clowns are like clowns are always fucking scary plastic head kings. Yeah,

1078
01:02:33,280 --> 01:02:36,560
Speaker 1: but he's like because he's like a mixture of like

1079
01:02:36,560 --> 01:02:39,840
Speaker 1: like like a guy fox mask and like that Dura

1080
01:02:39,960 --> 01:02:44,880
Speaker 1: Cell family from the nineties commercials, all those super exaggerated

1081
01:02:44,880 --> 01:02:48,040
Speaker 1: facial features. White family, Like, hey, we're the Dura Cell people.

1082
01:02:48,600 --> 01:02:50,640
Speaker 1: That's what the Burger King got. Like he's definitely their

1083
01:02:50,680 --> 01:02:53,200
Speaker 1: cousin or some ship. But Burger King. They're back at

1084
01:02:53,200 --> 01:02:56,480
Speaker 1: it again, freaking out their customers. They sent a mass

1085
01:02:56,600 --> 01:03:00,600
Speaker 1: email with a blank receipt for an order, like where

1086
01:03:00,600 --> 01:03:02,920
Speaker 1: it just says thanks for ordering from Burger King, your

1087
01:03:03,000 --> 01:03:04,800
Speaker 1: order would be ready in place that like with all

1088
01:03:04,800 --> 01:03:07,280
Speaker 1: this blank stuff, so like it didn't really have any details,

1089
01:03:07,280 --> 01:03:09,320
Speaker 1: but it said thanks for ordering, and a lot of

1090
01:03:09,360 --> 01:03:12,040
Speaker 1: people were They're like, oh, fuck, did someone hack my ship?

1091
01:03:12,600 --> 01:03:15,480
Speaker 1: And it's like doing what all people do when they

1092
01:03:15,680 --> 01:03:18,000
Speaker 1: immediately get their hands on a hacked account, which is

1093
01:03:18,000 --> 01:03:22,360
Speaker 1: by Burger King. And the Burger King later claimed that

1094
01:03:22,440 --> 01:03:25,200
Speaker 1: this was simply they said, oh, we don't they're being

1095
01:03:25,360 --> 01:03:28,200
Speaker 1: coy and then said it's just the result of internal

1096
01:03:28,280 --> 01:03:31,520
Speaker 1: of an internal processing era. People were just sort of like,

1097
01:03:31,840 --> 01:03:35,480
Speaker 1: I don't I've never created a Burger King account, so

1098
01:03:36,440 --> 01:03:38,520
Speaker 1: what how do you even have my Like what what

1099
01:03:38,720 --> 01:03:41,240
Speaker 1: is this? So would that piece a side? A lot

1100
01:03:41,240 --> 01:03:44,200
Speaker 1: of people are like, wait, they're also owned by Restaurant

1101
01:03:44,240 --> 01:03:47,479
Speaker 1: Brands International And if if you're remember in Canada, Tim

1102
01:03:47,760 --> 01:03:53,640
Speaker 1: Timmy's Tim Horton's massive data breeds or like all this

1103
01:03:53,760 --> 01:03:58,920
Speaker 1: sensitive information like leaked and like even the Privacy Commissioner

1104
01:03:58,920 --> 01:04:02,840
Speaker 1: in Canada said, like this quote crossed the line for

1105
01:04:03,280 --> 01:04:05,600
Speaker 1: like how much like of this information that came out?

1106
01:04:05,840 --> 01:04:08,520
Speaker 1: And at the time Tim like Hortons, You're like, please

1107
01:04:08,600 --> 01:04:12,880
Speaker 1: don't sue us. How about we give you a coffee

1108
01:04:12,880 --> 01:04:18,160
Speaker 1: and a doughnut? Okay, no, maybe, And you know, people

1109
01:04:18,280 --> 01:04:23,240
Speaker 1: weren't too happy about that either, but bad your data loss.

1110
01:04:23,600 --> 01:04:27,120
Speaker 1: I know someone completely started three credit cards and max

1111
01:04:27,200 --> 01:04:30,080
Speaker 1: them out already with your fake information. Would you like

1112
01:04:30,120 --> 01:04:34,200
Speaker 1: a crueler or an ice coffee? This coffee is only

1113
01:04:34,280 --> 01:04:39,200
Speaker 1: slightly burned slightly, but like you know, this is like

1114
01:04:39,200 --> 01:04:42,080
Speaker 1: a thing that people were like, okay, whatever, what the

1115
01:04:42,080 --> 01:04:44,160
Speaker 1: fund is going on? Like this is kind of heart

1116
01:04:44,160 --> 01:04:48,040
Speaker 1: and Parcel with burger kings, like weird creep marketing, and

1117
01:04:48,440 --> 01:04:49,760
Speaker 1: a lot of people are like, this has to be

1118
01:04:49,800 --> 01:04:52,240
Speaker 1: part of like some kind of like elaborate scheme because

1119
01:04:52,280 --> 01:04:53,720
Speaker 1: in the past, like this is what they've been in

1120
01:04:53,720 --> 01:04:59,160
Speaker 1: the past. In ten, they made a commercial specifically designed

1121
01:04:59,240 --> 01:05:03,880
Speaker 1: to hide a Google Home device, so to the point

1122
01:05:03,920 --> 01:05:07,040
Speaker 1: where Google had to, like the said from this article quote,

1123
01:05:07,080 --> 01:05:09,200
Speaker 1: you were discovered that by asking okay, Google, what is

1124
01:05:09,200 --> 01:05:13,240
Speaker 1: the whopper burger? Like the like the speakers would then

1125
01:05:13,280 --> 01:05:15,280
Speaker 1: do all this other stuff and Google had to interview

1126
01:05:15,360 --> 01:05:17,600
Speaker 1: and be like, we had to stop this prompt like

1127
01:05:17,800 --> 01:05:21,160
Speaker 1: from the from the our products, like understanding this prompt

1128
01:05:21,160 --> 01:05:24,000
Speaker 1: because it's just causing too much chaos. And that was

1129
01:05:24,080 --> 01:05:28,960
Speaker 1: that we thought. And then in apparently they had to

1130
01:05:29,040 --> 01:05:32,040
Speaker 1: settle of eight and a half million dollar like class

1131
01:05:32,080 --> 01:05:38,280
Speaker 1: action lawsuit over junk facts ads like facsimile machines, facts is.

1132
01:05:38,640 --> 01:05:42,720
Speaker 1: They were ascending in the year of our Lord ten

1133
01:05:43,600 --> 01:05:46,600
Speaker 1: facts is to fucking people. I don't say that I

1134
01:05:46,640 --> 01:05:48,880
Speaker 1: worked at a place that got facts is still it

1135
01:05:49,000 --> 01:05:51,760
Speaker 1: was a it was a theater company, and we would

1136
01:05:51,840 --> 01:05:57,360
Speaker 1: get spam from people like that, right, and every day

1137
01:05:57,400 --> 01:05:59,400
Speaker 1: we get at least like five facts is and it

1138
01:05:59,440 --> 01:06:05,360
Speaker 1: was like twelve or something, and people had fax machines

1139
01:06:05,440 --> 01:06:09,360
Speaker 1: and it got like converted into an email and would

1140
01:06:09,360 --> 01:06:12,320
Speaker 1: get sent to like like one of the admins. Or

1141
01:06:12,360 --> 01:06:14,960
Speaker 1: you're like or like I remember working in office like

1142
01:06:15,600 --> 01:06:18,760
Speaker 1: where the big networkings. Your ox machine was also a

1143
01:06:18,800 --> 01:06:20,920
Speaker 1: fax machine. And then every now and then you look

1144
01:06:20,960 --> 01:06:23,160
Speaker 1: in the printing tray and then like faxes had come

1145
01:06:23,200 --> 01:06:25,960
Speaker 1: in and you're like, what the I am not interested

1146
01:06:26,000 --> 01:06:31,040
Speaker 1: in a reverse mortgage on my car? What? But the

1147
01:06:31,080 --> 01:06:33,880
Speaker 1: people that were the members of that class action lawsuit,

1148
01:06:34,080 --> 01:06:37,280
Speaker 1: we're getting up to five dollars per facts that they received,

1149
01:06:37,680 --> 01:06:40,360
Speaker 1: and they could get a maximum of four grand back

1150
01:06:40,400 --> 01:06:43,400
Speaker 1: in that eight and a half millions. Oh now, I

1151
01:06:43,440 --> 01:06:45,040
Speaker 1: really wish I would have gotten one of those things,

1152
01:06:45,840 --> 01:06:47,959
Speaker 1: of these facts. I know where my five hundred bucks

1153
01:06:48,200 --> 01:06:50,880
Speaker 1: you know people are making money from getting like coming

1154
01:06:50,920 --> 01:06:56,240
Speaker 1: after the spam text people, Oh they loved me. If

1155
01:06:56,240 --> 01:06:59,680
Speaker 1: you're if your game speed, Sorry to completely derail this,

1156
01:06:59,720 --> 01:07:02,520
Speaker 1: but like if you're on the do not Call registry

1157
01:07:02,600 --> 01:07:06,320
Speaker 1: and someone is like hitting you up, if you can

1158
01:07:06,360 --> 01:07:09,880
Speaker 1: find out who the actual entity is behind that call,

1159
01:07:10,160 --> 01:07:12,800
Speaker 1: you can typically just be like here's a form letter

1160
01:07:12,880 --> 01:07:16,080
Speaker 1: that sounds lawyery, and they'll they'll st they'll try and

1161
01:07:16,080 --> 01:07:23,000
Speaker 1: settle with you. About thirty calls a day, I'm not exaggerating.

1162
01:07:23,040 --> 01:07:24,560
Speaker 1: If you're on the and if and it takes it

1163
01:07:24,600 --> 01:07:26,280
Speaker 1: takes energy. Though, like a lot of people say, like

1164
01:07:26,400 --> 01:07:28,120
Speaker 1: you have to have the time to be like what

1165
01:07:28,280 --> 01:07:30,920
Speaker 1: is this company? Who runs it? Can I get an email?

1166
01:07:31,400 --> 01:07:34,320
Speaker 1: Because it's different than like if you're getting scammed, right,

1167
01:07:34,320 --> 01:07:36,600
Speaker 1: if someone's calling you and being like hello, I'm from

1168
01:07:36,880 --> 01:07:40,440
Speaker 1: Windows XP security, that's a different thing. But like when

1169
01:07:40,440 --> 01:07:43,040
Speaker 1: you get the ones that's like hey your auto warranty.

1170
01:07:43,160 --> 01:07:46,680
Speaker 1: If you can find out who's sending yeah, you can

1171
01:07:46,680 --> 01:07:49,640
Speaker 1: get you can get some money. You know that sounds

1172
01:07:49,640 --> 01:07:52,480
Speaker 1: like an episode of Get Rich Nick? Yeah, right is yeah,

1173
01:07:52,600 --> 01:07:55,360
Speaker 1: just just be like the just bawling off of complaints

1174
01:07:55,360 --> 01:07:57,520
Speaker 1: from being on the do not call this another thing.

1175
01:07:57,600 --> 01:07:59,880
Speaker 1: I just want to add lastly, in two thousand nine,

1176
01:08:00,120 --> 01:08:04,880
Speaker 1: Working also made a Facebook app that remember Facebook apps, Damn,

1177
01:08:05,440 --> 01:08:09,920
Speaker 1: let's wait, what do you remember? They're like building I remember.

1178
01:08:09,960 --> 01:08:12,320
Speaker 1: I was just sorry that I haven't used in so long.

1179
01:08:12,600 --> 01:08:14,720
Speaker 1: It's believable that you wouldn't remember. And I'm like, hey,

1180
01:08:14,800 --> 01:08:16,400
Speaker 1: I know i've been. I just went I just went

1181
01:08:16,439 --> 01:08:19,800
Speaker 1: back in my brain and went. This app basically said

1182
01:08:19,920 --> 01:08:25,559
Speaker 1: if you delete ten Facebook friends, you get a free whopper. Sorry,

1183
01:08:25,640 --> 01:08:27,840
Speaker 1: well you're out. I'm getting this whopper. That's fine, bro,

1184
01:08:27,920 --> 01:08:30,240
Speaker 1: get your give a ship. I won't be precious about that.

1185
01:08:30,360 --> 01:08:33,559
Speaker 1: Gets your free fucking whopper. But then after they were

1186
01:08:33,560 --> 01:08:36,200
Speaker 1: doing it like it would also send a message though,

1187
01:08:36,240 --> 01:08:39,719
Speaker 1: like if the person got deleted, this app from Burking

1188
01:08:39,760 --> 01:08:42,880
Speaker 1: would let them know their friendship was quote valued at

1189
01:08:42,960 --> 01:08:46,519
Speaker 1: less than one tenth of a whopper. Oh why just

1190
01:08:46,680 --> 01:08:49,120
Speaker 1: like dunk on them and then Facebook shut the ship

1191
01:08:49,280 --> 01:08:53,400
Speaker 1: in after ten days? That's how does that like as

1192
01:08:53,439 --> 01:08:57,719
Speaker 1: a business decision, this is like that part is bad marketing.

1193
01:08:57,960 --> 01:09:02,639
Speaker 1: Now now he's doing okay for Burger King, like bad business?

1194
01:09:02,880 --> 01:09:05,280
Speaker 1: Why why not refer people to burger King and get

1195
01:09:05,280 --> 01:09:08,400
Speaker 1: ten percent off your next whopper as opposed to just

1196
01:09:08,840 --> 01:09:15,880
Speaker 1: tell them they're worth and then we'll we'll message them,

1197
01:09:15,880 --> 01:09:18,960
Speaker 1: which is I'm sure we'll put you into their hearts

1198
01:09:18,960 --> 01:09:20,840
Speaker 1: in a positive way. And when they did like an

1199
01:09:20,840 --> 01:09:24,439
Speaker 1: announcement of what happened about twenty thou people took them

1200
01:09:24,520 --> 01:09:26,800
Speaker 1: up like on the deleting the ten people, but then

1201
01:09:27,120 --> 01:09:28,960
Speaker 1: in seeing that, they were like, yeah, but they also

1202
01:09:29,000 --> 01:09:31,760
Speaker 1: created two hundred thousand people who are like pissed up,

1203
01:09:32,240 --> 01:09:34,800
Speaker 1: like Burger King or like what the funk was that

1204
01:09:34,880 --> 01:09:37,639
Speaker 1: burger King? But pe'll get into fights with our friends.

1205
01:09:37,920 --> 01:09:39,880
Speaker 1: I mean, yeah, look the things will do for a

1206
01:09:39,920 --> 01:09:43,160
Speaker 1: free burging. I get it. Things feel good. All right,

1207
01:09:43,479 --> 01:09:47,839
Speaker 1: that's gonna do it for this week's weekly Zeitgeys, please

1208
01:09:47,960 --> 01:09:51,280
Speaker 1: like and review the show. If you like the show,

1209
01:09:51,880 --> 01:09:56,280
Speaker 1: uh means the world to Miles. He needs your validation. Folks.

1210
01:09:56,880 --> 01:09:59,920
Speaker 1: I hope you're having a great weekend and I will

1211
01:10:00,000 --> 01:10:32,160
Speaker 1: talk to you Monday. Bye.