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Speaker 1: Welcome to Brief Recess. I'm Michael Foote.

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Speaker 2: I'm a listen albranch.

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Speaker 1: Today we're going to talk about the Knicks one and

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Speaker 1: NYC went straight to jail. Things that make us cry,

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Speaker 1: Haiti in the World Cup and in the customs line

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Speaker 1: at the airport, the UFC fight on the front lawn

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Speaker 1: of the Way, secret situation room recording regarding the Epstein files. Whoops,

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Speaker 1: wasn't me? We have an interview with the New York

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Speaker 1: twelve district congressional candidate Laura Dunn, and we're going to

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Speaker 1: answer all your questions from the DMS and read all

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Speaker 1: the wild reviews you leave. So stick around every time.

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Speaker 1: Every time I eat a croissant, it's it's Russian roulette

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Speaker 1: on where the crumbs are going to go?

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Speaker 2: Well, I will tell you if you had, I know.

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Speaker 1: You would, but you're not always around.

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Speaker 2: I'm not always unfortunately for you. How are you friends?

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Speaker 2: How you been?

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Speaker 1: I don't know if you heard? But the next one, no,

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Speaker 1: I don't know.

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Speaker 2: Are you sure?

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Speaker 1: I don't know if you saw the sixty three people

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Speaker 1: who got arrested and the ten people who got shot

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Speaker 1: and the guy who was standing on a bus railing lines.

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Speaker 2: Your neighbor Chris just hoovering up the cooke. He was

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Speaker 2: so excited.

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Speaker 1: I don't know if you saw this town painted ballow

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Speaker 1: An orange.

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Speaker 2: So I will tell you my brother lost his fucking mind.

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Speaker 2: I'm sure I have a clip. I've asked him for

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Speaker 2: permission to show it. He said, yes, he looks crazy.

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Speaker 2: I have never seen him this way, and his feeling

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Speaker 2: is that, you know, yeah, born in britt New Yorker.

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Speaker 2: None of his teams ever win. He's a big Mets fan,

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Speaker 2: a big Knicks fan, and they never win. So this

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Speaker 2: was yeah, so the baby's all outfitted in Nicks for.

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Speaker 1: The straight people who are always like, I don't get

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Speaker 1: why you guys need a pride parade. DM me from

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Speaker 1: that parade on Thursday when this episode drops, because that's

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Speaker 1: your straight pride parade. Okay, that's what you got. And

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Speaker 1: you know it's so important to straight people this next thing.

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Speaker 1: And I'm going to prove it to you really quick.

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Speaker 2: CJ.

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Speaker 1: How many years has it been?

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Speaker 3: Thank you?

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Speaker 1: Thank you? That's how important it is. First eight people,

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Speaker 1: they know they did Marsha P. Johnson. That's what I

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Speaker 1: know in fifty three years is what they know. This

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Speaker 1: is their pride.

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Speaker 2: I mean as somebody who is not a sporty person,

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Speaker 2: even though I said old options in my Haitian World

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Speaker 2: Cup jersey. But but I was, like I told Michael,

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Speaker 2: I was away with some friends over the weekend. I

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Speaker 2: was scrap booking and there was a there was a

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Speaker 2: bar in our hotel and we went down and I

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Speaker 2: watched the last fifteen minutes and it was very exciting. Yes,

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Speaker 2: it was exciting, and I'm very happy for the people

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Speaker 2: who are are happy, like my brother and CJ, who

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Speaker 2: told us that he collapsed on the floor in his

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Speaker 2: living room and cried.

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Speaker 1: I was planking in his own home. Thought they lost

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Speaker 1: because I was crying. CJ, Are you like a cryer?

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Speaker 1: Do you cry? Often? Only when my team hasn't want

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Speaker 1: because some because some people are like criers, they'll cry

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Speaker 1: like all the time. Brad cried when Pikachu left Ash

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Speaker 1: and that was it, and like then I know what

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Speaker 1: that means. Yeah, it's a Pokemon thing. When he was

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Speaker 1: a kid, he cried when Pikachu left Ash. She was

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Speaker 1: a child and that was it. What do you mean

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Speaker 1: It's like hasn't been since he hasn't cried. I think

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Speaker 1: maybe when his grandparents died and it really he's not

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Speaker 1: a crier?

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Speaker 2: Are you a crier? Oh?

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Speaker 1: My god? All the time? All the time for just

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Speaker 1: no reason? Sometimes okay, and I love it. I really

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Speaker 1: am like.

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Speaker 2: No, no, no, no, it's fine. I just I I

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Speaker 2: definitely don't cry as much as I used to.

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Speaker 1: Yeah, when I'm a set or frustrated or excited or happy.

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Speaker 1: It's just like how my body expresses an intense emotion. Okay,

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Speaker 1: So like I'll be crying because I'm just like this

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Speaker 1: is the coolest thing ever, not because of any distress.

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Speaker 1: So people oftentimes misinterpret my tears. It's like this person's not.

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Speaker 2: Okay, I can't. I'm trying to remember, like, yeah, I

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Speaker 2: do cry, but I don't feel like I cry all

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Speaker 2: the time. However, the other day, I'm.

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Speaker 1: Trying to think of a time when I saw you cry.

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Speaker 2: Oh no, you can't do my dad's wake I was crying.

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Speaker 2: Oh yeah, yeah, I'm trying to think. I don't think

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Speaker 2: i've cried. Really, does I stuffed the feelings down?

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Speaker 1: Just raise catholic.

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Speaker 2: I'm Catholic, I'm patient. I stuff the feelings down, That's

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Speaker 2: what it is.

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Speaker 1: Let's get into a sidebar on grief, please perceed.

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Speaker 2: This is not grief, though, the other day, so Haiti

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Speaker 2: has not been in the World Cup since nineteen seventy three,

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Speaker 2: I think, and again I don't really care about sports,

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Speaker 2: but I care about this. This is about pride point

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Speaker 2: oh for sure, for sure, for sure, and we need this,

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Speaker 2: we need we need some good and this is a

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Speaker 2: very good thing. And I also know if my dad

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Speaker 2: was alive, he would lose his mind, right, thank you.

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Speaker 2: And so the other day they were playing Scotland and

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Speaker 2: I got weepy when they were playing the national anthem,

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Speaker 2: the Haitian national anthem, which I had practiced, and now

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Speaker 2: I know. And it's hard, it's hard. It's a very well.

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Speaker 2: My French is not sad, very French. My French is

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Speaker 2: not that good.

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Speaker 1: I imagine it's in French.

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Speaker 2: It's in French.

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Speaker 1: I'm gonna go out on a limit. It's probably in French.

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Speaker 2: It's in French. There is also a creole version. And

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Speaker 2: when I was saying to my mom, I'm like, I

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Speaker 2: don't I don't know this, and she was like annoyed

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Speaker 2: with me, She's like, why don't you know it? I'm like,

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Speaker 2: did you teach me why I know the punge of

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Speaker 2: allegiance in America, but I didn't, so she was annoyed

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Speaker 2: with me. But now I know it.

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Speaker 1: My mom is always horrified if I tell her that

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Speaker 1: I got like a parking ticket and didn't pay it immediately.

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Speaker 2: I always forget to pay my parking tickets. Come knocking

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Speaker 2: on my door, they send me, they send me, and

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Speaker 2: I keep on saying, oh, I have to remember to

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Speaker 2: pay it, and then I put it to the side.

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Speaker 2: It's a bright orange envelope. Well that's when I that's

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Speaker 2: when I really pay it. I'm like, oh wait, it's

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Speaker 2: the orange envelope is here.

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Speaker 1: I'm always like, how bad does it have to get

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Speaker 1: in New York City for them to come drag me away?

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Speaker 2: They're made, They've They've reached out to me. Hey, Melissa,

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Speaker 2: we know they say things like we know sometimes we

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Speaker 2: get busy.

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Speaker 1: Hey girl, you up, what are you doing? I had

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Speaker 1: a neighbor in my old building downstairs from Chris was

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Speaker 1: this hilarious Polish woman who I won't say her name,

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Speaker 1: but it's like a very Polish name, Megda.

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Speaker 2: Yeah.

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Speaker 1: Yeah, I got it close to Magda.

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Speaker 2: Yeah.

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Speaker 1: But she always this is someone did I tell you

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Speaker 1: her cat was like attacking people.

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Speaker 2: Yes, yeah, I remember. Oh my god.

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Speaker 1: I don't know if we told this story on the show.

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Speaker 1: But basically, there was this this other older woman in

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Speaker 1: the and her home health aid. I ran into her

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Speaker 1: on the street and I was like, how you doing

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Speaker 1: and she was like, oh, I don't go to that

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Speaker 1: building anymore because Magda's cat attacked me. And she lifted

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Speaker 1: up her skirt on the street and her legs it

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Speaker 1: looked like Freddy Krueger gouch mar.

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Speaker 2: It was like shaving her legs.

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Speaker 1: So anyway, the people came and booted Magda's car once

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Speaker 1: right in front of the building, and I asked her.

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Speaker 1: I was like, wow, they booted your car. She's like, yeah,

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Speaker 1: they do it if you have over five hundred dollars

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Speaker 1: in parking tickets.

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Speaker 2: Okay, I've never gotten there.

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Speaker 1: I was like, damn girl.

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Speaker 2: CJJ raised his hand, Wow, really is it? Are you forgetting?

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Speaker 1: Or I was in college in the Bronx.

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Speaker 2: Oh that doesn't count. It doesn't count.

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Speaker 1: My car actually got towed, and I thought stolen. If

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Speaker 1: someone tows my carm, like keep it, keep it.

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Speaker 2: I wouldn't do that.

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Speaker 1: I would I would be like I'm going to leave

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Speaker 1: it there for a couple of weeks so I don't

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Speaker 1: get parking tickets, and then.

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Speaker 2: They charge you. They charge you per day.

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Speaker 1: Do they Yes? Is it more than the ticket? Yes? Okay,

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Speaker 1: all right, well all right, never mind, I'm going to

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Speaker 1: go get it. But they don't. They don't tell it.

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Speaker 2: Have you what's your problem?

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Speaker 1: I was going to ask you, have you been through

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Speaker 1: customs recently? Because I just went through customs. I just

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Speaker 1: flew back into the country because there was a group

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Speaker 1: of a plan full of Haitians.

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Speaker 2: I texted you, Michael texted me about this.

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Speaker 1: Planeful of Haitians got off right in front of me

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Speaker 1: in the customs line. And I don't have global entry.

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Speaker 2: I don't.

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Speaker 1: Everyone's zombie. I get that answer all the time. Everyone

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Speaker 1: zombie about it.

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Speaker 2: I just got it. I'm so I'm not being superior.

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Speaker 2: I'm surprised you don't have it.

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Speaker 1: I don't have it because I don't want to go

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Speaker 1: to the airport for that extra interview.

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Speaker 2: Michael, I did it, and I also felt the same

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Speaker 2: way two minutes.

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Speaker 1: But to get to the airport, it was a pain

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Speaker 1: in the ass.

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Speaker 2: See yeahs and nothing good ever happens at Liguardia.

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Speaker 1: And people thank you, and people are like, oh, you

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Speaker 1: could do it when you're flying back in, Yeah, you can.

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Speaker 1: When I'm flying back in.

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Speaker 2: Now you just want to go home.

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Speaker 1: I feel like, no, I hear you. I feel like

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Speaker 1: I did it. I got run over by the Knicks parade,

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Speaker 1: So who did it? And ran?

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Speaker 2: Just ridden hard.

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Speaker 1: I'm looking like, who did it?

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Speaker 2: In ran?

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Speaker 1: It's forty miles a rough highway.

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Speaker 2: What were the Haitians like?

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Speaker 1: So by the time, I honestly don't feel like I'm

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Speaker 1: allowed to say what the Haitians were like in mine,

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Speaker 1: but I will imagine, but I will say by the

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Speaker 1: time I got to the custom sky he said, he

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Speaker 1: looked at me. I'm not kidding. He said, I'm going

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Speaker 1: on break after this. He said, you are my last person, okay,

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Speaker 1: And he said do you have anything in your bags

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Speaker 1: that you need to declare? And I said no, no,

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Speaker 1: He said, go leave here immediately. He did not look

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Speaker 1: at my passport, which I was like, doesn't someone need

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Speaker 1: to know I'm back in the country, Like, don't think

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Speaker 1: I'm like an immigration learn I'm thinking, have I ever had

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Speaker 1: a client who never got stamped like that? Just happened

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Speaker 1: to me, never got the customs of border protection, never

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Speaker 1: documented me returning.

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Speaker 2: To tell you and I love my people. I do.

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Speaker 2: I clearly you've been on a lot of flights back

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Speaker 2: from Haiti. Yes, and I get it. And dealing with

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Speaker 2: Haitian people, I mean, being Haitian is not for the week, right,

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Speaker 2: growing up in a Haitian household, nobody can hurt my feelings.

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Speaker 2: My feelings cannot be hurt. So yeah, poor guy, Oh no,

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Speaker 2: he'll be okay.

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Speaker 1: Then, yeah, let's get into an algorithm is showing. Did

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Speaker 1: you see the people doing like wheelie motorbike, motorbike motorcross

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Speaker 1: crossroads on lawn.

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Speaker 2: No, I did not see that, but you know what

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Speaker 2: I did see. I did see it. A couple of

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Speaker 2: people come to blows peoples cuffs on the white and

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Speaker 2: not the people in the cage, the random people. And

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Speaker 2: the thing about it is like, you know, I think

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Speaker 2: when you see like a fight in a movie, right

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Speaker 2: or a show, it's like very like dramatic and boom

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Speaker 2: and but when people are real people are fighting, it's

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Speaker 2: like like cats fighting with each other. It's kind of.

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Speaker 1: Like people that choreography. No, not at all. There's always

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Speaker 1: one move that like you know, that person's embarrassed because

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Speaker 1: they kind of like did like a weird flick with

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Speaker 1: their wrists. Were they made like the noise.

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Speaker 2: Or like I think it's really funny where people, real

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Speaker 2: people are fighting and they're not fighting with like their

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Speaker 2: fists out there. Yes, it's more like.

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Speaker 1: Or the or the wife always comes up and behind

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Speaker 1: and it's like you stop it. It gets them with

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Speaker 1: a broom handle or something.

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Speaker 2: There's always real weird flick.

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Speaker 1: So you better not. It's like that's not going to

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Speaker 1: stop them. They're rolling around on the ground. Oh my god. Yeah,

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Speaker 1: So Trump spend sixty million on the on this fight

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Speaker 1: on the lawn, right, we did six my healthcare. My

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Speaker 1: deductible went up so that he could have a UFC

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Speaker 1: fight on his front lawn.

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Speaker 2: So CJ, tell me tell us again what you said,

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Speaker 2: like what you're feeling of why he did this. It's

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Speaker 2: like what.

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Speaker 1: It's like a twelve year old boy got a wish

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Speaker 1: from a genie and wanted to become president.

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Speaker 2: And he just wanted to have an mma by and

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Speaker 2: I'll bet you like a giant probably like a giant

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Speaker 2: Sam's Club cake with a really thick layer of frosting.

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Speaker 1: You know those really long heroes we got we they

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Speaker 1: slice them because the Italian hero.

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Speaker 2: Island. I just notified, I don't can we get lower

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Speaker 2: than this? Like how much lower can it get? Right?

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Speaker 2: Forget all the terrible policies that are coming through, Forget

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Speaker 2: all of.

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Speaker 1: That, forgot the Epstein files, forget.

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Speaker 2: It, but this is just at its core, it is

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Speaker 2: like the trashiest it's so fucking trashy.

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Speaker 1: Well. I was like, how are we going to literally

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Speaker 1: distract from the New York Times Epstein files, Like there

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Speaker 1: was this huge article in New York Times magazine last week.

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Speaker 2: You know what, and I missed it.

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Speaker 1: I read the whole thing.

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Speaker 2: How bad is that?

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Speaker 1: It is so bad? It's Maggie Haberman and it's so bad.

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Speaker 1: It documents basically how the Trump administration, his cabinet of

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Speaker 1: like six eight people, including JD. Vance, used the Situation

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Speaker 1: Room to figure out what to do last year. Remember,

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Speaker 1: there was like the New York article. It was like

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Speaker 1: his poem to Jeffrey Epstein. It was like his birthday

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Speaker 1: card and it was on the cover of the New Yorker. Yes, yes,

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Speaker 1: I think it was The New Yorker. Fact check me

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Speaker 1: on that. But basically when that came out last summer,

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Speaker 1: everyone started talking about Epstein. It was so clear that

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Speaker 1: Trump was very much involved in the Epstein files, that

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Speaker 1: there was a cover up, that everyone was involved in

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Speaker 1: the cover up, that he was using the government to

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Speaker 1: cover up what was in the files, and Pam Bondi

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Speaker 1: was involved. And so his cabinet met in the Situation Room,

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Speaker 1: the room for Warfare, and meant to discuss how they

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Speaker 1: were going to handle this, whether they should get in

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Speaker 1: front of the release of the files, whether they need to.

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Speaker 2: Well, here's what I'm thinking. The reason why they met

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Speaker 2: the situation room where we talk about war because I

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Speaker 2: think that they believe that they are at war against

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Speaker 2: the media, do you know what I'm saying? So, like,

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Speaker 2: how are we going to strategize, How are we going

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Speaker 2: to get in front of this? How can we make

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Speaker 2: this go up?

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Speaker 1: Can we protect the president?

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Speaker 2: How do we protect this.

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Speaker 1: R we're trying to do? And so the article was

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Speaker 1: basically like they fumbled it at every turn, Like there

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Speaker 1: was no no outcome from that meeting.

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Speaker 2: That was Michael. They fumble at every turn for everything,

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Speaker 2: nothing is going well.

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Speaker 1: But it got even more met up because including the

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Speaker 1: meeting to talk about how to not fumble got fumbled

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Speaker 1: because there might have been a recording of that meeting

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Speaker 1: in the situation room and everyone's talking.

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Speaker 2: About it, the Trump did it.

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Speaker 1: They're terrified that there's going to be a clip that

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Speaker 1: gets dropped of them talking about what to do.

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Speaker 2: Yeah, I hope.

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Speaker 1: So so they're running around the chickens with chickens with

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Speaker 1: their heads cut off right today while we're recording. So

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Speaker 1: I'm like, I can't wait for that recording to drop.

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Speaker 1: I'm going to eat it up. We're going to play

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Speaker 1: it on the show.

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Speaker 2: Oh yeah, I just how does this?

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Speaker 1: And well they're talking about they're like, well, which part

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Speaker 1: of the meeting is going to drop? Which means many

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Speaker 1: parts of the meeting were a problem. They're trying to

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Speaker 1: figure they're trying to figure out what to do if

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Speaker 1: which part of the meeting drops, which means there were

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Speaker 1: multiple parts of the meeting really problem matter.

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Speaker 2: Right that that they are worried about. So we need

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Speaker 2: to try and get in front of they're doing planning

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Speaker 2: part A.

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Speaker 1: Right, Yeah, the plan A or f right Now, there's

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Speaker 1: probably a recording of this meeting about what to do

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Speaker 1: about the recording and the meeting put that on, put

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Speaker 1: that Sometimes I just.

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Speaker 2: Where are we? Where are you? What's happening? What did

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Speaker 2: what did we do to deserve this?

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Speaker 1: A part of me is like, should I have just

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Speaker 1: gone back on that plane with those Haitians? Got turned

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Speaker 1: around at customs and border protections and I'm a celebrity.

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Speaker 1: Get me out of here, Get me to port a Prince.

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Speaker 1: Welcome back to brief Rests. This is under oath where

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Speaker 1: we take a deep dive into a topic with a special.

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Speaker 2: Guest, and today we're really excited to welcome Laura Dunn.

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Speaker 2: Laura is an award winning civil rights attorney, a former educator,

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Speaker 2: and a nationally recognized advocate for survivors. She played a

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Speaker 2: key role in drafting and passing the twenty thirteen reauthorization

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Speaker 2: of the Violence Against Women Act. She is a current

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Speaker 2: member of the New York State Bar Association and is

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Speaker 2: currently running for Congress to restore accountability, uphold the rule

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Speaker 2: of law, and ensure government works for the people, not

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Speaker 2: the powerful. Laura, thank you so much for coming, Welcome

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Speaker 2: to being here.

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Speaker 3: Thank you guys for having me on. This is a

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Speaker 3: great group to have this discussion with.

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Speaker 1: We met actually last week during the Courier News event.

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Speaker 1: There was a debate and I got to moderate it

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Speaker 1: along with a group of other political influencers. It was

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Speaker 1: really fun. Yeah, we got to meet you. It was great.

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Speaker 1: What did you think of that event?

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Speaker 3: I was very happy to be on sta agent some

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Speaker 3: of you know, there's three debates for NY twelve. I

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Speaker 3: was actually robbed of the stage the first time. I

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Speaker 3: hit five percent in the largest pole that's the requirement,

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Speaker 3: and then the news agency decided to run their own

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Speaker 3: pole that was a fraction of the size, and they

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Speaker 3: disqualified me, didn't invite me on I know. And when

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Speaker 3: I looked up who owned them, I was not surprised

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Speaker 3: to see four private equity companies, including black Rocks. So ikes,

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Speaker 3: here we are.

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Speaker 2: I mean, private equity is ruining everything everything they touch. Yeah, yeah,

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Speaker 2: that's really frustrating.

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Speaker 1: So this was like one of the few debates who

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Speaker 1: actually got to be a part of Yes, which is

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Speaker 1: so messed up. It is because, let me tell you,

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Speaker 1: she ate them up. Laura gobbled them up, and it

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Speaker 1: was it was fierce Yes. And I was like, I

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Speaker 1: got to get Laura on the show because she really did,

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Speaker 1: Like you were incredible. So I just had fun listening

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Speaker 1: to you because you really like it's I mean, it's

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Speaker 1: tell as old as time, right, Like there was like

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Speaker 1: the NEPO Baby, the it was like the white men

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Speaker 1: got their big pitch and their moment, and you had

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Speaker 1: the actual substance and credentials and the resume, and you

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Speaker 1: were polished and brilliant and we're saying all the right

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Speaker 1: things that everyone really needed to hear. But then of

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Speaker 1: course weren't included in many of the debates.

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Speaker 3: Well, and that's why, because no one owns me. And

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Speaker 3: that's the challenge in this race, right we have super

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Speaker 3: packs behind to the candidates who are very part of

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Speaker 3: the establishment. Michael Bloomberg's backing Michael Lasher. He's a billionaire.

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Speaker 3: He controls a lot of the media in New York City.

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Speaker 3: We also had Alex Borez, who used to work for

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Speaker 3: Palanteer hugely problematic, made his fortune off working for that

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Speaker 3: company during all the issues with Ice during the Trump administration,

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Speaker 3: actually cashed out to live in the house he is

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Speaker 3: in now and he says he's a champion, but he's

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Speaker 3: taking money from Menthropics. So it kind of feels like

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Speaker 3: he's just switching AI lords and signing us up for

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Speaker 3: a different program. And it's really hard when you see

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Speaker 3: what's going on and you know the voters don't. And

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Speaker 3: that's why I was so wound up for that debate.

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Speaker 3: I'm like, if I only get one, I'm going to

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Speaker 3: make a count and sounds like you did. Yeah, hopefully.

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Speaker 2: How many people are in the race?

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Speaker 3: Eight total? So people have been very frustrated because people

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Speaker 3: were in and out of this race from the beginning,

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Speaker 3: and it was really also part of the challenge that

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Speaker 3: people came in, soaked up a lot of media attention

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Speaker 3: and then just dropped out out of nowhere. People who

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Speaker 3: actually found raised really well over a million dropped out

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Speaker 3: of nowhere, and it's because they were frustrated with the

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Speaker 3: working of the system. It was very clear who was

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Speaker 3: going to be endorsed by all the Democratic clubs. It

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Speaker 3: was very clear that that was going to create lots

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Speaker 3: of problems down the line for field operations. And what

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Speaker 3: I always try to point out to people is when

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Speaker 3: they're frustrated, like why didn't you raise more money? Why

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Speaker 3: weren't you on every stage, I'm like, I didn't give up.

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Speaker 3: I'm right here if that's what you want from someone

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Speaker 3: in Congress who gives up and tosses in the towel, Like,

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Speaker 3: that's why you have the leaders you have. If you

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Speaker 3: want someone who fights no matter what they're given, then

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Speaker 3: you want to pick me when you go into thet.

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Speaker 1: I also feel like in New York, we're always talking

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Speaker 1: about how progressive New York is, right, but I think

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Speaker 1: when these races come around, we really realize how antiquated

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Speaker 1: a lot of our systems are. How you know, we

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Speaker 1: really are going to be a reflection of the rest

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Speaker 1: of the country many times, Like, sure, we may be

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Speaker 1: very socially progressive, but at the end of the day,

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Speaker 1: I think what we're seeing in the New York twelve

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Speaker 1: race right now is that the deepest pockets are the

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Speaker 1: ones that are going the furthest in the polls, right.

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Speaker 3: Yeah, And it's been really frustrating. So there's, you know,

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Speaker 3: all these groups that target certain types of political candidates.

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Speaker 3: Right there's the women's groups, the queer groups, the union groups,

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Speaker 3: and I will say all the women's groups donated to men,

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Speaker 3: all the lgbt g Q groups excuse me, donated to

440
00:21:47,480 --> 00:21:50,440
Speaker 3: cis gender men. And there's two queer women in this race,

441
00:21:50,480 --> 00:21:53,080
Speaker 3: which is like, really, we were livid, you know, when

442
00:21:53,440 --> 00:21:56,399
Speaker 3: into our community and we've turned away. And of course

443
00:21:56,440 --> 00:21:59,199
Speaker 3: the unions picked people who have never been union members.

444
00:21:59,240 --> 00:22:01,679
Speaker 3: I've been a teacher. I was part of United Teachers

445
00:22:01,680 --> 00:22:03,840
Speaker 3: of New Orleans, and that means I was in post

446
00:22:03,880 --> 00:22:06,680
Speaker 3: coatrada in New Orleans the first year of the schools reopened,

447
00:22:06,880 --> 00:22:10,000
Speaker 3: working alongside a bunch of teachers who have been disenfranchised

448
00:22:10,000 --> 00:22:12,480
Speaker 3: for three years while the government figured out what to do,

449
00:22:13,080 --> 00:22:15,280
Speaker 3: and we marched together and we fought for what was

450
00:22:15,359 --> 00:22:17,840
Speaker 3: right for our kids. And when I taught on Chicago's

451
00:22:17,840 --> 00:22:20,800
Speaker 3: North Side, which was largely immigrant and refugee, I was

452
00:22:20,800 --> 00:22:24,280
Speaker 3: at a public charter and it was deeply problematic and

453
00:22:24,320 --> 00:22:26,720
Speaker 3: the way it was engaging with some of the teachers

454
00:22:26,720 --> 00:22:29,680
Speaker 3: who were highly qualified and female and weren't getting promoted

455
00:22:30,080 --> 00:22:33,280
Speaker 3: and underqualified men were. So we unionized and I fought

456
00:22:33,280 --> 00:22:36,440
Speaker 3: the administration. So when you come in with these credentials

457
00:22:36,440 --> 00:22:39,760
Speaker 3: of I've actually fought for LGBTQ plus rights through Title

458
00:22:39,840 --> 00:22:43,320
Speaker 3: nine cases, I've actually fought for women's rights, and then

459
00:22:43,320 --> 00:22:45,840
Speaker 3: they're like, sorry, it's not your turn, Like what is

460
00:22:45,840 --> 00:22:48,320
Speaker 3: this turn? Thing like isn't it the best leader?

461
00:22:48,440 --> 00:22:50,399
Speaker 2: That's what I thought it was. Sarah. Let me ask

462
00:22:50,480 --> 00:22:53,480
Speaker 2: you this. You said something interesting that you you know,

463
00:22:54,000 --> 00:22:55,719
Speaker 2: you went to the queer groups and you went to

464
00:22:55,800 --> 00:22:58,960
Speaker 2: the groups for women who and they supported the men

465
00:22:59,080 --> 00:23:02,080
Speaker 2: and the sister. Why do you think that is? What

466
00:23:02,640 --> 00:23:04,800
Speaker 2: do you think? I mean? I don't want to put

467
00:23:04,800 --> 00:23:07,000
Speaker 2: person in tell me, tell me what why you think

468
00:23:07,040 --> 00:23:07,399
Speaker 2: that is?

469
00:23:07,560 --> 00:23:11,240
Speaker 3: It's a few different things. Like I think career politicians

470
00:23:11,240 --> 00:23:13,400
Speaker 3: are the worst leaders in the entire world because they've

471
00:23:13,440 --> 00:23:15,679
Speaker 3: never done anything real right now, I've never started business,

472
00:23:15,680 --> 00:23:17,879
Speaker 3: They've never been at a school, like, they don't have

473
00:23:17,920 --> 00:23:20,680
Speaker 3: real world experience. They're in a little bubble and they're

474
00:23:20,880 --> 00:23:23,560
Speaker 3: raised up to be exactly who above them wanted them

475
00:23:23,600 --> 00:23:25,840
Speaker 3: to be, and so they're just kind of parroting the system.

476
00:23:26,240 --> 00:23:28,120
Speaker 3: But when you run, people are like, well, we didn't

477
00:23:28,119 --> 00:23:29,880
Speaker 3: see you. You weren't part of these clubs. You weren't

478
00:23:29,960 --> 00:23:32,320
Speaker 3: yet a lawmaker. And I'm like, yeah, I didn't want

479
00:23:32,359 --> 00:23:34,080
Speaker 3: to be. I was in a courtroom, I was getting

480
00:23:34,080 --> 00:23:36,600
Speaker 3: a legal education, I was working my executive NBA, And

481
00:23:36,640 --> 00:23:39,480
Speaker 3: why you start like, I was building these life experiences

482
00:23:39,520 --> 00:23:42,080
Speaker 3: that helped me see from a better perspective than most

483
00:23:42,080 --> 00:23:44,600
Speaker 3: of the people. But these are two men that got

484
00:23:44,640 --> 00:23:46,879
Speaker 3: in line a long time ago. Numerous people were like

485
00:23:46,920 --> 00:23:49,520
Speaker 3: I watched them grow up, and this is kind of

486
00:23:49,560 --> 00:23:52,640
Speaker 3: what they were raised for. And it's so painful when

487
00:23:52,680 --> 00:23:55,040
Speaker 3: people walk up and say I want a woman leader,

488
00:23:55,160 --> 00:23:58,159
Speaker 3: like run again. It's like you keep getting women leaders,

489
00:23:58,200 --> 00:24:00,880
Speaker 3: Like look at District three. We just has election there.

490
00:24:01,119 --> 00:24:03,600
Speaker 3: That's the quote unquote gay district in your health's kitchen,

491
00:24:03,920 --> 00:24:06,440
Speaker 3: and there's three amazing women and then one guy, and

492
00:24:06,480 --> 00:24:09,160
Speaker 3: he won by a landslide, even though Mom Donnie even

493
00:24:09,280 --> 00:24:11,560
Speaker 3: endorsed one of the women. And it was kind of

494
00:24:11,640 --> 00:24:14,440
Speaker 3: eye opening to me because I had heard more from

495
00:24:14,440 --> 00:24:17,119
Speaker 3: the Hell's Kitchen Dems that they wanted women leaders than

496
00:24:17,160 --> 00:24:19,879
Speaker 3: anywhere else. But they were like, oh, he was loyal,

497
00:24:19,960 --> 00:24:22,240
Speaker 3: he's been here the longest. It's like, if you're only

498
00:24:22,280 --> 00:24:24,679
Speaker 3: going to vote for the people that you see the most,

499
00:24:24,960 --> 00:24:27,000
Speaker 3: and you want everyone to get in line, that's fine,

500
00:24:27,160 --> 00:24:30,040
Speaker 3: say so, say that this is the requirement for you

501
00:24:30,119 --> 00:24:32,360
Speaker 3: to have office. But if you're going to be open

502
00:24:32,400 --> 00:24:34,680
Speaker 3: to other types of leaders, give people credit for being

503
00:24:34,720 --> 00:24:37,000
Speaker 3: in courtrooms, like I was already working on the hill,

504
00:24:37,040 --> 00:24:39,159
Speaker 3: which no one else in this race did like you

505
00:24:39,200 --> 00:24:41,959
Speaker 3: have to have open credentials to have more variety of leaders.

506
00:24:42,080 --> 00:24:45,640
Speaker 1: And it's like that meme of Carrie Bradshaw where it's

507
00:24:45,680 --> 00:24:48,679
Speaker 1: like you say you want complicated female characters, but you

508
00:24:48,720 --> 00:24:51,880
Speaker 1: couldn't handle her, like you couldn't just handle Carry Bradshaw

509
00:24:52,000 --> 00:24:55,159
Speaker 1: or Lena Dunham's character and girls and people couldn't handle it,

510
00:24:55,200 --> 00:24:57,680
Speaker 1: and everyone's like, we want complex female leads, and it's

511
00:24:57,720 --> 00:25:00,720
Speaker 1: like you literally are still hung up on Big and Carrie,

512
00:25:00,880 --> 00:25:05,480
Speaker 1: like it's been twenty years, right, Yeah, But I want

513
00:25:05,520 --> 00:25:08,480
Speaker 1: to talk about you know, Epstein has been in the

514
00:25:08,560 --> 00:25:10,480
Speaker 1: news a lot, and you have talked a lot about

515
00:25:10,480 --> 00:25:14,600
Speaker 1: sexual violence in your campaign, so I wanted to bring

516
00:25:14,640 --> 00:25:16,360
Speaker 1: you on the show. And I know you've been a

517
00:25:16,359 --> 00:25:19,160
Speaker 1: civil rights attorney for a long time before you run,

518
00:25:20,119 --> 00:25:21,879
Speaker 1: So I just wanted to talk about that, your hopes

519
00:25:21,880 --> 00:25:26,680
Speaker 1: for New York twelve, how these issues are really important

520
00:25:26,680 --> 00:25:29,840
Speaker 1: to you, and why if you want to take it

521
00:25:29,920 --> 00:25:30,760
Speaker 1: from there.

522
00:25:31,000 --> 00:25:34,359
Speaker 3: So I call myself the accountability candidate. My platform is

523
00:25:34,440 --> 00:25:36,560
Speaker 3: very clear that I want term limits, that's both for

524
00:25:36,640 --> 00:25:39,600
Speaker 3: Congress and the Supreme Court. I want to end insider trading,

525
00:25:39,680 --> 00:25:43,119
Speaker 3: no more making millions off of public office, ethical standards

526
00:25:43,160 --> 00:25:45,240
Speaker 3: for the Supreme Court. So we know it's politically corrupt

527
00:25:45,320 --> 00:25:48,440
Speaker 3: right now. But to your point, there's all this other corruption,

528
00:25:48,600 --> 00:25:52,040
Speaker 3: right I try to keep everything in threes because we're litigators, people, memories,

529
00:25:53,600 --> 00:25:59,680
Speaker 3: court exactly. But Epstein, that scandal just really breaks my heart.

530
00:26:00,119 --> 00:26:02,919
Speaker 3: Republic about being a campus sexual salt survivor. That's actually

531
00:26:02,960 --> 00:26:05,720
Speaker 3: how I found my way into politics. I never wanted

532
00:26:05,720 --> 00:26:07,960
Speaker 3: this path, but this was the right path to make change.

533
00:26:08,440 --> 00:26:11,119
Speaker 3: So when I experienced sexual violence, I turned around shared

534
00:26:11,119 --> 00:26:13,320
Speaker 3: my name, face story at a time when everyone was

535
00:26:13,320 --> 00:26:16,919
Speaker 3: still Jane Doe. That allowed me this amazing platform that

536
00:26:16,920 --> 00:26:19,959
Speaker 3: got the attention of President Obama, and I advocated in

537
00:26:20,000 --> 00:26:23,399
Speaker 3: Congress in both Republican and Democrat offices for two years

538
00:26:23,400 --> 00:26:25,920
Speaker 3: as a law student, sharing my rape story over and

539
00:26:26,000 --> 00:26:29,240
Speaker 3: over and over to pass the twenty thirteen Violence Against

540
00:26:29,240 --> 00:26:31,440
Speaker 3: Women Act. It took everything I had. I remember I

541
00:26:31,480 --> 00:26:35,640
Speaker 3: once hunted down Senator Al Franken. He was ignoring our requests,

542
00:26:35,640 --> 00:26:37,200
Speaker 3: he was not being supportive. He was part of the

543
00:26:37,240 --> 00:26:39,840
Speaker 3: Senate Judiciary. I found him on the stairwell and just

544
00:26:39,880 --> 00:26:41,399
Speaker 3: called out to him in front of a group of

545
00:26:41,440 --> 00:26:43,560
Speaker 3: thirty people in front of him and was like, you

546
00:26:43,600 --> 00:26:48,440
Speaker 3: have ignored this bill, So it really required me to

547
00:26:48,480 --> 00:26:50,359
Speaker 3: step up. And that's why I no, federal law and

548
00:26:50,359 --> 00:26:52,560
Speaker 3: policy is so important, and I also know what it takes.

549
00:26:52,800 --> 00:26:55,120
Speaker 3: So when you look at the Epstein files that happened

550
00:26:55,240 --> 00:26:57,879
Speaker 3: in NY twelve, and none of the men are talking

551
00:26:57,920 --> 00:27:00,879
Speaker 3: about that, and that should signal everything for one of

552
00:27:00,920 --> 00:27:04,440
Speaker 3: the biggest scandals. That shows that there's foreign influence, foreign money,

553
00:27:04,760 --> 00:27:08,040
Speaker 3: and really obviously despicable crimes and horrors that were being committed.

554
00:27:08,320 --> 00:27:11,200
Speaker 3: And yet it's not in anyone's radar. That's the Epstein

555
00:27:11,200 --> 00:27:15,199
Speaker 3: class filtering money and picking your candidate for them. I

556
00:27:15,280 --> 00:27:17,720
Speaker 3: know both myself and the other woman in this race,

557
00:27:18,040 --> 00:27:20,680
Speaker 3: we would not tolerate this. We are from the communities

558
00:27:20,680 --> 00:27:22,479
Speaker 3: that have been harded by general violence. We're not going

559
00:27:22,520 --> 00:27:25,280
Speaker 3: to stand it. And I'm very honored that Epstein survivors

560
00:27:25,280 --> 00:27:27,920
Speaker 3: have come been there when I put the petitions to

561
00:27:27,920 --> 00:27:30,200
Speaker 3: get on the ballot in, they were there hugging me

562
00:27:30,280 --> 00:27:32,840
Speaker 3: and saying we need a survivor. So I want to

563
00:27:32,840 --> 00:27:35,000
Speaker 3: be let loose on Congress. I want to tear it up.

564
00:27:35,240 --> 00:27:37,360
Speaker 3: I want to call these names out. I really admire

565
00:27:37,359 --> 00:27:39,040
Speaker 3: all the people who have been listing the names of

566
00:27:39,080 --> 00:27:41,920
Speaker 3: the perpetrators that are these files. But it's not enough.

567
00:27:41,960 --> 00:27:43,840
Speaker 3: We have to rebuild the DOJ and we have to

568
00:27:43,840 --> 00:27:46,320
Speaker 3: make a commitment because it will show us exactly what's

569
00:27:46,359 --> 00:27:49,359
Speaker 3: been happening to our elections. I don't think Donald Trump

570
00:27:49,600 --> 00:27:52,280
Speaker 3: won by accident. I think he won by intention and

571
00:27:52,320 --> 00:27:54,280
Speaker 3: will know more when we get into the Epstein files

572
00:27:54,280 --> 00:27:56,240
Speaker 3: about where the money is coming from, who is behind

573
00:27:56,280 --> 00:27:56,920
Speaker 3: these plans?

574
00:27:57,520 --> 00:28:00,480
Speaker 1: Oh my god, gosh, that's you know.

575
00:28:00,560 --> 00:28:03,760
Speaker 2: I just I always more and more I ask myself,

576
00:28:03,840 --> 00:28:06,639
Speaker 2: you know, how did we get here? Why are we

577
00:28:06,720 --> 00:28:10,600
Speaker 2: in this space? Why are the lives of women and

578
00:28:10,760 --> 00:28:16,280
Speaker 2: children and victims of sexual assault not taken seriously? They're

579
00:28:16,560 --> 00:28:19,720
Speaker 2: they're not important. But we love our guns, you know,

580
00:28:20,040 --> 00:28:23,120
Speaker 2: And and it just seems to me that that's happening

581
00:28:23,160 --> 00:28:25,840
Speaker 2: more and more. It feels like it's getting worse, and

582
00:28:25,880 --> 00:28:31,080
Speaker 2: it's harder and harder for me personally to I want

583
00:28:31,080 --> 00:28:34,400
Speaker 2: to remain engaged, but sometimes it feels like too much.

584
00:28:34,960 --> 00:28:36,920
Speaker 2: It feels like a lot. It feels like a lot.

585
00:28:37,040 --> 00:28:39,720
Speaker 2: But I also know that if I don't remain engaged,

586
00:28:39,760 --> 00:28:41,800
Speaker 2: then it's never going to change, which is why we

587
00:28:41,880 --> 00:28:45,920
Speaker 2: have people like you. But yeah, it's frustrating. It's frustrating,

588
00:28:45,920 --> 00:28:47,880
Speaker 2: and it must be really frustrating for you to be

589
00:28:47,960 --> 00:28:50,600
Speaker 2: in this position. You're running for office and you're listening

590
00:28:50,600 --> 00:28:52,560
Speaker 2: to all these stories and you're getting these sort of

591
00:28:53,080 --> 00:28:56,520
Speaker 2: roadblocks because you're not a part of what the old

592
00:28:56,600 --> 00:28:59,600
Speaker 2: boys that works the system. Yeah yeah, yeah, yeah.

593
00:28:59,640 --> 00:29:01,440
Speaker 3: Well the good news is I've never been part of

594
00:29:01,440 --> 00:29:03,640
Speaker 3: the system, so I'm actually like kind of used to it,

595
00:29:03,800 --> 00:29:06,520
Speaker 3: and I think it helps bring out like the true

596
00:29:06,720 --> 00:29:09,360
Speaker 3: nature of who I am and why I fight. So

597
00:29:09,560 --> 00:29:12,000
Speaker 3: no matter the outcome of this particular race, I'm obviously

598
00:29:12,040 --> 00:29:14,440
Speaker 3: fighting to the end. I hit five percent, thirty percent

599
00:29:14,440 --> 00:29:18,080
Speaker 3: are undecided. It's a race literally anyone could win. But

600
00:29:18,080 --> 00:29:20,000
Speaker 3: no matter what happens, like, I know who I am

601
00:29:20,080 --> 00:29:21,800
Speaker 3: and I've grounded in that, and it's gained a lot

602
00:29:21,840 --> 00:29:24,040
Speaker 3: of respect on the ground. So people who may be

603
00:29:24,160 --> 00:29:26,040
Speaker 3: looking at them men saying they have a leg up,

604
00:29:26,480 --> 00:29:28,720
Speaker 3: they know that I'm right behind them. So I don't

605
00:29:28,720 --> 00:29:31,840
Speaker 3: think it's over. But to your point about being overwhelmed,

606
00:29:32,320 --> 00:29:34,640
Speaker 3: I guess one of the weirder parts of my platform

607
00:29:35,040 --> 00:29:38,680
Speaker 3: that I've talked about is being pro psychedelics and why

608
00:29:38,680 --> 00:29:41,920
Speaker 3: that topic. It's because it focuses on healing. So there

609
00:29:42,080 --> 00:29:45,640
Speaker 3: is so much unwellness in our society. We have lived

610
00:29:45,640 --> 00:29:48,480
Speaker 3: through COVID, we have had political unrest.

611
00:29:48,680 --> 00:29:52,320
Speaker 1: Us all the time. How we are not over COVID. No,

612
00:29:52,480 --> 00:29:55,280
Speaker 1: we just went right back to work. We picked up

613
00:29:55,680 --> 00:29:58,360
Speaker 1: that dusty pen off the desk where we left it

614
00:29:58,400 --> 00:30:01,840
Speaker 1: two years earlier, that we plugged the computer back end.

615
00:30:02,520 --> 00:30:05,320
Speaker 1: And I know someone they left their laptop charger at

616
00:30:05,320 --> 00:30:07,280
Speaker 1: the office and just went back and just plugged their

617
00:30:07,360 --> 00:30:10,680
Speaker 1: laptop back in a year later, and we have not

618
00:30:10,840 --> 00:30:11,880
Speaker 1: and we've just not looked at it.

619
00:30:11,880 --> 00:30:13,000
Speaker 3: We've talked about it, no doubt.

620
00:30:13,440 --> 00:30:17,000
Speaker 2: Yeah, I mean that was it was a very traumatic experience,

621
00:30:17,080 --> 00:30:20,720
Speaker 2: and I don't think that we've given it the gravitas

622
00:30:20,760 --> 00:30:23,560
Speaker 2: that it deserves, right, I mean, because especially when you

623
00:30:23,600 --> 00:30:26,600
Speaker 2: think back in the very beginning, for me, anyway, I

624
00:30:26,640 --> 00:30:28,640
Speaker 2: was convinced we were all going to die, right Like

625
00:30:29,080 --> 00:30:32,880
Speaker 2: I was convinced that we were living the stand by

626
00:30:32,880 --> 00:30:35,080
Speaker 2: Stephen King, Like that's what I felt like was going

627
00:30:35,120 --> 00:30:39,320
Speaker 2: to happen. I was worried about everybody, and I was afraid.

628
00:30:41,000 --> 00:30:45,000
Speaker 2: And I don't think that any of us really sat

629
00:30:45,120 --> 00:30:48,400
Speaker 2: back to really reflect on what we went through. And

630
00:30:48,440 --> 00:30:50,280
Speaker 2: like Michael said, we just sort of went back to work.

631
00:30:50,320 --> 00:30:53,160
Speaker 2: I went back to work and my calendar was still

632
00:30:53,720 --> 00:30:58,000
Speaker 2: on March from March of twenty twenty and I went

633
00:30:58,080 --> 00:31:00,560
Speaker 2: back in like twenty twenty two when I was like, well,

634
00:31:00,880 --> 00:31:04,280
Speaker 2: just I'm the calendar.

635
00:31:04,680 --> 00:31:06,760
Speaker 1: I love psychedelics and I talk about this on the

636
00:31:06,760 --> 00:31:09,960
Speaker 1: Shawl that I'm a post pandemic. Had a really hard

637
00:31:10,000 --> 00:31:13,120
Speaker 1: time going back to work, going back to the courtroom,

638
00:31:13,200 --> 00:31:16,080
Speaker 1: going back to walking down the street and seeing other

639
00:31:16,080 --> 00:31:21,600
Speaker 1: people's faces, like it really was emotionally difficult for me.

640
00:31:21,640 --> 00:31:23,160
Speaker 1: And Melissa was there for me through and through the

641
00:31:23,160 --> 00:31:25,760
Speaker 1: whole time. But I went to ketamine therapy and like

642
00:31:25,840 --> 00:31:27,840
Speaker 1: my insurance paid for it. Like it was a full,

643
00:31:28,520 --> 00:31:31,280
Speaker 1: you know, above word experience. I wasn't in a warehouse

644
00:31:31,320 --> 00:31:36,080
Speaker 1: in Bushwick, but it really helped me. It really helped

645
00:31:36,120 --> 00:31:37,640
Speaker 1: me get to a place where I could do things

646
00:31:37,680 --> 00:31:41,680
Speaker 1: like launch a podcast or you know, get out there

647
00:31:41,680 --> 00:31:44,400
Speaker 1: on social media. I wouldn't have been able to do

648
00:31:44,480 --> 00:31:45,800
Speaker 1: without that. It was so healing.

649
00:31:45,960 --> 00:31:49,080
Speaker 3: I really admire that you're talking about that people need

650
00:31:49,120 --> 00:31:51,000
Speaker 3: to know that this is available to them, and certain

651
00:31:51,040 --> 00:31:53,480
Speaker 3: types are legal. I have done the more not so

652
00:31:53,560 --> 00:31:58,160
Speaker 3: legal types. I'm DMA to heal from PTSD and psilocybin,

653
00:31:58,320 --> 00:32:01,200
Speaker 3: and now I do kambu, which is totally an Amazon

654
00:32:01,280 --> 00:32:02,040
Speaker 3: Frog poison.

655
00:32:02,440 --> 00:32:02,800
Speaker 2: Cool.

656
00:32:02,960 --> 00:32:06,200
Speaker 3: Yeah, it makes you violently also not super cool, but

657
00:32:06,600 --> 00:32:10,000
Speaker 3: for twenty minutes you're purging and then afterwards people have visions.

658
00:32:10,040 --> 00:32:11,959
Speaker 3: I have not had the benefit of those visions, but

659
00:32:12,000 --> 00:32:15,040
Speaker 3: it definitely physically clears the vessel.

660
00:32:16,040 --> 00:32:17,160
Speaker 1: Wow, I've never heard of this.

661
00:32:17,160 --> 00:32:19,240
Speaker 2: It is so fat Again, Michael and I talk about

662
00:32:19,280 --> 00:32:21,880
Speaker 2: this all the time, Like, I grew up in a

663
00:32:21,920 --> 00:32:27,160
Speaker 2: household where you know, my mother equated marijuana to crack cocaine, right,

664
00:32:27,280 --> 00:32:29,480
Speaker 2: So it's the same. It was. It was the same.

665
00:32:29,720 --> 00:32:32,840
Speaker 2: It was the same. And so this idea that you

666
00:32:32,880 --> 00:32:37,320
Speaker 2: could use psychedelics as a as a as a means

667
00:32:37,320 --> 00:32:43,040
Speaker 2: of healing from trauma is it's so it's weird to

668
00:32:43,080 --> 00:32:46,520
Speaker 2: me because I can't imagine it, and I will admit

669
00:32:46,560 --> 00:32:49,320
Speaker 2: I'm also I think a little bit afraid of what

670
00:32:49,440 --> 00:32:52,760
Speaker 2: am I going to remember? What am I going to discover?

671
00:32:52,920 --> 00:32:55,240
Speaker 1: When I tell people I've done ketamine therapy, that is

672
00:32:55,280 --> 00:32:57,840
Speaker 1: the thing. The number one thing they say to me

673
00:32:58,360 --> 00:33:01,920
Speaker 1: is I'm afraid of what I'm going to learn about myself. Yes, yeah,

674
00:33:02,080 --> 00:33:05,000
Speaker 1: that is Honestly, the only resistance people tell me when

675
00:33:05,000 --> 00:33:07,000
Speaker 1: I'm like, oh, you should try it. I only had

676
00:33:07,000 --> 00:33:11,320
Speaker 1: positive experiences crowd a lot, but like it was a healing,

677
00:33:11,640 --> 00:33:14,920
Speaker 1: interesting journey, And what they say to me is, I'm

678
00:33:14,960 --> 00:33:17,920
Speaker 1: afraid of how it will change my life, whether they'll

679
00:33:18,000 --> 00:33:20,960
Speaker 1: learn that their relationship with someone is wrong for them,

680
00:33:21,360 --> 00:33:24,520
Speaker 1: or their job or dynamic that they're in. They're afraid

681
00:33:24,560 --> 00:33:27,840
Speaker 1: of facing the change, is what I notice when I

682
00:33:27,880 --> 00:33:28,520
Speaker 1: talk to people.

683
00:33:28,560 --> 00:33:30,960
Speaker 3: Well, that's even happening right now, right people want to

684
00:33:31,000 --> 00:33:33,720
Speaker 3: go back to what was and it can't happen. You

685
00:33:33,760 --> 00:33:36,120
Speaker 3: have to be bold and brave and realize that there's

686
00:33:36,120 --> 00:33:38,120
Speaker 3: something new and it actually could be better. And that's

687
00:33:38,160 --> 00:33:41,280
Speaker 3: the best part of it. Right. So my experience, the

688
00:33:41,280 --> 00:33:43,160
Speaker 3: reason I kind of brought it up in response to

689
00:33:43,360 --> 00:33:46,600
Speaker 3: your comment is I now kind of almost have like

690
00:33:46,640 --> 00:33:50,200
Speaker 3: a divine perspective where it's almost humorous what we as

691
00:33:50,240 --> 00:33:52,800
Speaker 3: humans choose to do, because we really have the power

692
00:33:53,000 --> 00:33:55,760
Speaker 3: to choose any way, to rewant, to have any policy

693
00:33:55,800 --> 00:33:58,440
Speaker 3: we want, and yet we keep getting stuck in this fight.

694
00:33:58,800 --> 00:34:00,160
Speaker 3: Do people deserve healthcare?

695
00:34:00,280 --> 00:34:00,400
Speaker 2: Like?

696
00:34:00,520 --> 00:34:02,880
Speaker 3: Are we still fighting about that? Really?

697
00:34:03,000 --> 00:34:03,080
Speaker 2: Like?

698
00:34:03,120 --> 00:34:05,840
Speaker 3: Because I think the younger generations don't have a question.

699
00:34:05,880 --> 00:34:08,960
Speaker 3: We're like, yes, human beings deserve to live and to

700
00:34:09,000 --> 00:34:10,839
Speaker 3: live well and not to struggle and not to die

701
00:34:10,880 --> 00:34:14,080
Speaker 3: in the streets. So it's very interesting that we're kind

702
00:34:14,080 --> 00:34:16,560
Speaker 3: of stuck in this place. But I think we can

703
00:34:16,600 --> 00:34:18,880
Speaker 3: get past it, and it's just a choice. And so

704
00:34:19,080 --> 00:34:21,960
Speaker 3: when all these horrors are kind of playing one by

705
00:34:22,000 --> 00:34:25,000
Speaker 3: one rapidly, I'm definitely furious. And I'm sure you saw

706
00:34:25,040 --> 00:34:27,480
Speaker 3: some of that power come out in the debate. Lawyers,

707
00:34:27,520 --> 00:34:29,680
Speaker 3: I think learn how to channel it and we just come.

708
00:34:30,880 --> 00:34:33,480
Speaker 1: Katie Kirk and Don Lemon were in the green room like.

709
00:34:35,760 --> 00:34:37,520
Speaker 2: Gags. They were like to.

710
00:34:38,080 --> 00:34:41,920
Speaker 1: Katie Kirk, like, do snaps in the green room because

711
00:34:41,960 --> 00:34:46,240
Speaker 1: we're hearing what's going on on the stage was hilarious.

712
00:34:46,920 --> 00:34:48,560
Speaker 3: Yeah, it was.

713
00:34:48,560 --> 00:34:51,080
Speaker 1: Because what Laura was saying, like she really was eating

714
00:34:51,080 --> 00:34:53,879
Speaker 1: them alive, because a lot of what they were saying

715
00:34:54,000 --> 00:34:55,480
Speaker 1: was just like political bullshit.

716
00:34:55,600 --> 00:34:59,120
Speaker 2: It's sort of that was the pivoting, and that's sort

717
00:34:59,120 --> 00:35:02,399
Speaker 2: of going in circles that words right, and.

718
00:35:02,560 --> 00:35:04,560
Speaker 1: Alex Bars said that everyone on the stage had a

719
00:35:04,600 --> 00:35:07,120
Speaker 1: super pack and Laura was like, I would love to

720
00:35:07,120 --> 00:35:07,879
Speaker 1: meet my super pa.

721
00:35:09,320 --> 00:35:12,000
Speaker 3: It's not doing a great job if it's out there.

722
00:35:12,360 --> 00:35:15,759
Speaker 1: She was like, wait a minute, Yeah, this is the

723
00:35:15,760 --> 00:35:16,520
Speaker 1: first time heard.

724
00:35:16,719 --> 00:35:18,759
Speaker 3: Yeah, well that's what happens when people get off their

725
00:35:18,760 --> 00:35:21,719
Speaker 3: talking points. I say crazy things, and lawyers we go

726
00:35:21,840 --> 00:35:22,160
Speaker 3: right in.

727
00:35:22,440 --> 00:35:22,520
Speaker 2: Uh.

728
00:35:22,600 --> 00:35:24,920
Speaker 3: There was actually a forum earlier that week on Monday

729
00:35:24,920 --> 00:35:27,640
Speaker 3: with Michael Lasher and me, and he had the first question.

730
00:35:27,719 --> 00:35:29,960
Speaker 3: It was about the definition of anti Semitism from the

731
00:35:30,000 --> 00:35:33,799
Speaker 3: Holocaust Remembrance Organization that New York had adopted, and the

732
00:35:33,880 --> 00:35:36,959
Speaker 3: mom Donnie had kind of struck down and they were saying,

733
00:35:37,000 --> 00:35:39,279
Speaker 3: you know, what's your position on this definition. He was like,

734
00:35:39,360 --> 00:35:41,440
Speaker 3: I don't want to answer. This divides us more than

735
00:35:41,480 --> 00:35:43,799
Speaker 3: anything else, and he dodged it. Then it came to

736
00:35:43,840 --> 00:35:45,840
Speaker 3: me and I was like, this is the lawyer training.

737
00:35:45,920 --> 00:35:47,839
Speaker 3: I am ready. And I was like, isn't it a

738
00:35:47,840 --> 00:35:51,279
Speaker 3: shame when politicians dodge hard questions? And everyone was like

739
00:35:52,640 --> 00:35:54,279
Speaker 3: and I was like, lawyers don't get to do that.

740
00:35:54,320 --> 00:35:57,719
Speaker 3: We literally walk into court to answer these questions. I'm

741
00:35:57,719 --> 00:35:59,759
Speaker 3: not afraid to take a stand. I don't even care

742
00:35:59,800 --> 00:36:02,480
Speaker 3: the consequence of taking the stand because I've thought deeply

743
00:36:02,480 --> 00:36:04,520
Speaker 3: about it, researched it, and I know what a stand

744
00:36:04,520 --> 00:36:06,839
Speaker 3: for and I will pay the price for them. And

745
00:36:07,160 --> 00:36:10,360
Speaker 3: you know, I saw Jack Shlasberg kind of wiggle woggle

746
00:36:10,440 --> 00:36:14,120
Speaker 3: on you know, Israel Palestine and try to be progressive

747
00:36:14,120 --> 00:36:16,360
Speaker 3: but also pro Israel, and he just flip popped and

748
00:36:16,360 --> 00:36:19,000
Speaker 3: made everyone mad and he dropped ten points. And it's like,

749
00:36:19,040 --> 00:36:20,960
Speaker 3: you can't make everyone happy, and the fact that you

750
00:36:21,000 --> 00:36:23,719
Speaker 3: don't know that means you're not ready for office. You

751
00:36:23,800 --> 00:36:25,759
Speaker 3: have to take your stand. You have to know what

752
00:36:25,760 --> 00:36:28,040
Speaker 3: you're about and just know that there's a price tag

753
00:36:28,080 --> 00:36:30,879
Speaker 3: for it, and that's okay. If someone wants a different leader,

754
00:36:30,960 --> 00:36:33,080
Speaker 3: they will find a different leader. And your time is

755
00:36:33,120 --> 00:36:37,600
Speaker 3: not now. So I have enjoyed the few opportunities have

756
00:36:37,640 --> 00:36:39,879
Speaker 3: had to really jab at these men who have come

757
00:36:39,960 --> 00:36:42,480
Speaker 3: up there, and it's just the four of them on stage.

758
00:36:42,480 --> 00:36:44,800
Speaker 3: No one's throwing any punches, no one's getting into the

759
00:36:44,920 --> 00:36:47,399
Speaker 3: tough issues. So I'm glad they started inviting the.

760
00:36:47,320 --> 00:36:51,279
Speaker 1: Women politically aligned. Trying not to piss off anybody. What

761
00:36:51,360 --> 00:36:54,240
Speaker 1: do you say? I'm so fucking sick of talking about Ai,

762
00:36:54,600 --> 00:36:56,719
Speaker 1: but I do feel like we have to have I

763
00:36:56,840 --> 00:36:57,879
Speaker 1: heard AI one more time.

764
00:36:57,920 --> 00:37:01,000
Speaker 2: I'm gonna right, but it's a they're going to It's

765
00:37:01,080 --> 00:37:03,080
Speaker 2: not just the fruit. It's like really important.

766
00:37:03,400 --> 00:37:06,000
Speaker 1: It's really important, and I know it's come up a

767
00:37:06,000 --> 00:37:07,880
Speaker 1: lot in this race. It's not just like, what do

768
00:37:07,880 --> 00:37:10,520
Speaker 1: you think about AI? AM not like some Silicon Valley

769
00:37:10,520 --> 00:37:13,960
Speaker 1: tech bro I do feel like it has been one

770
00:37:13,960 --> 00:37:16,920
Speaker 1: of the top three things that has come up randomly

771
00:37:17,040 --> 00:37:21,000
Speaker 1: in this New York twelve congressional race. Take it away,

772
00:37:21,080 --> 00:37:22,400
Speaker 1: Laura tell us.

773
00:37:24,840 --> 00:37:27,719
Speaker 3: So if it makes you less annoyed, you could say

774
00:37:27,760 --> 00:37:31,040
Speaker 3: big tech generally, right, it's AI is just one issue.

775
00:37:31,080 --> 00:37:31,239
Speaker 1: Right.

776
00:37:31,280 --> 00:37:33,480
Speaker 3: We have crypto in there, we have quantum computing, we

777
00:37:33,520 --> 00:37:36,200
Speaker 3: already have social media. And I have talked about Section

778
00:37:36,239 --> 00:37:39,279
Speaker 3: two thirty, the immunity given to big tech companies that

779
00:37:39,360 --> 00:37:42,040
Speaker 3: allows them to do many things that newspapers cannot do,

780
00:37:42,120 --> 00:37:46,800
Speaker 3: such as spread misinformation, tailor algorithms to create more political division.

781
00:37:47,320 --> 00:37:48,759
Speaker 3: And I think we need to get rid of that,

782
00:37:49,120 --> 00:37:50,920
Speaker 3: and that I think would solve a lot of our

783
00:37:50,960 --> 00:37:53,719
Speaker 3: problems right now. But I think AI is such a

784
00:37:53,760 --> 00:37:57,120
Speaker 3: big thing because it's replacing people's jobs. Right, college students

785
00:37:57,160 --> 00:37:59,520
Speaker 3: can't get an entry level job. We're scared for our

786
00:37:59,560 --> 00:38:02,120
Speaker 3: kids who are falling in love with AIS are being

787
00:38:02,120 --> 00:38:04,839
Speaker 3: told how to commit suicide, or god knows what else

788
00:38:04,880 --> 00:38:08,000
Speaker 3: is happening. We also have AIS undressing women and harassing

789
00:38:08,080 --> 00:38:11,200
Speaker 3: them in ways that we have never imagined before. It's

790
00:38:11,239 --> 00:38:14,319
Speaker 3: the boogeyman that's out there. And Alex Brez did a

791
00:38:14,320 --> 00:38:16,560
Speaker 3: state law that kind of reined that in. It's the

792
00:38:16,560 --> 00:38:19,080
Speaker 3: only state. New York is the only state that's really

793
00:38:19,200 --> 00:38:21,520
Speaker 3: kind of tackled the issue. But they did it because

794
00:38:21,560 --> 00:38:24,279
Speaker 3: the thorough government wasn't why is that because of all

795
00:38:24,320 --> 00:38:28,279
Speaker 3: the money going in to deter it. So he did that,

796
00:38:28,400 --> 00:38:30,839
Speaker 3: and now he has AI money coming in. And when

797
00:38:30,880 --> 00:38:32,719
Speaker 3: I was on stage, I pointed out that there was

798
00:38:32,800 --> 00:38:36,200
Speaker 3: four different AI consumer protection bills that he alone voted

799
00:38:36,239 --> 00:38:39,840
Speaker 3: against as this quote unquote AI Champion, which really raises

800
00:38:40,000 --> 00:38:43,400
Speaker 3: questions and I really believe is a trojan horse. I

801
00:38:43,400 --> 00:38:45,759
Speaker 3: think he was sent to look like a hero when

802
00:38:45,760 --> 00:38:47,920
Speaker 3: he's not. He's just going to set up a specific

803
00:38:48,000 --> 00:38:51,840
Speaker 3: AI company Anthropic over that appallenteer and it's just marketing

804
00:38:51,880 --> 00:38:55,759
Speaker 3: and thropics the less evil. But AI can't be reined in, like,

805
00:38:55,920 --> 00:38:57,840
Speaker 3: let's not be fooled. We can say it can, but

806
00:38:57,920 --> 00:38:58,440
Speaker 3: it can't.

807
00:38:58,520 --> 00:38:59,040
Speaker 2: Can't.

808
00:38:59,280 --> 00:39:02,240
Speaker 3: Know it add quantum computing that's coming in five years.

809
00:39:03,000 --> 00:39:05,480
Speaker 3: We are We're in trouble. And I think the hardest

810
00:39:05,480 --> 00:39:08,360
Speaker 3: thing that I've ever said, which did not win many favors,

811
00:39:08,400 --> 00:39:10,960
Speaker 3: but I said it. I meant it was during the

812
00:39:11,040 --> 00:39:14,560
Speaker 3: UFT the Teachers' Union endorsement, they were asking about AI

813
00:39:14,640 --> 00:39:17,200
Speaker 3: and education, and I'm a former teacher, and I said,

814
00:39:17,200 --> 00:39:19,640
Speaker 3: the research is actually showing that more screen time and

815
00:39:19,760 --> 00:39:23,120
Speaker 3: use of AI is impeding cognitive development. We literally have

816
00:39:23,160 --> 00:39:27,360
Speaker 3: generations that are less academically successful. This is not okay,

817
00:39:27,400 --> 00:39:29,520
Speaker 3: and so we have to have moretoriums. I hate to

818
00:39:29,560 --> 00:39:32,280
Speaker 3: say it. We can't just implement and see what happens.

819
00:39:32,320 --> 00:39:35,080
Speaker 3: We can experiment on children. And I don't think they

820
00:39:35,160 --> 00:39:39,960
Speaker 3: liked that answer. Here we are, but I mean that answer.

821
00:39:40,120 --> 00:39:42,920
Speaker 3: AI is not for everywhere and everything. Maybe it shouldn't

822
00:39:42,960 --> 00:39:46,319
Speaker 3: belong in, for example, wars. We really want to give

823
00:39:46,520 --> 00:39:50,239
Speaker 3: lethal ability to a technology we can't control and just

824
00:39:50,320 --> 00:39:53,680
Speaker 3: see what happens. Not me. So I think we can

825
00:39:53,680 --> 00:39:56,080
Speaker 3: put guardrails around it. I really want to adopt the

826
00:39:56,120 --> 00:39:58,520
Speaker 3: precautionary principle, which is what we have in Europe, which

827
00:39:58,520 --> 00:40:02,080
Speaker 3: says you can't put something into the consumer population until

828
00:40:02,080 --> 00:40:05,360
Speaker 3: you've proven it safe. So you can put regulations around it.

829
00:40:05,360 --> 00:40:08,360
Speaker 3: You can have ethical standards. We can have a whole requirement.

830
00:40:08,440 --> 00:40:10,040
Speaker 3: This is what we do with drugs, right, they have

831
00:40:10,080 --> 00:40:11,920
Speaker 3: to be approved before they go out. We could do

832
00:40:11,960 --> 00:40:14,080
Speaker 3: something similar and that way we find out where it's

833
00:40:14,120 --> 00:40:16,799
Speaker 3: okay and we have them investing in research. Does it

834
00:40:16,840 --> 00:40:20,160
Speaker 3: in pea cognitive development? Does it not? And until we

835
00:40:20,239 --> 00:40:23,080
Speaker 3: have people who are willing to tell corporations that are

836
00:40:23,239 --> 00:40:27,440
Speaker 3: getting trillion dollar valuations, no, we're going to be stuck

837
00:40:27,520 --> 00:40:30,680
Speaker 3: with whatever the latest innovation is, no matter the consequence

838
00:40:30,719 --> 00:40:31,320
Speaker 3: to our children.

839
00:40:31,560 --> 00:40:33,480
Speaker 1: I hate AI so much, and I'll go on the

840
00:40:33,480 --> 00:40:35,520
Speaker 1: record with that. I fucking hate AI.

841
00:40:35,719 --> 00:40:38,880
Speaker 2: I am so sick of that spoken like lear.

842
00:40:39,400 --> 00:40:41,960
Speaker 1: I have tried it. I think it's dumb, it is

843
00:40:42,040 --> 00:40:46,040
Speaker 1: not smarter. I hate it. I've tried using it for

844
00:40:46,160 --> 00:40:50,840
Speaker 1: like legal briefs or for emotion or whatever. And the

845
00:40:51,000 --> 00:40:53,319
Speaker 1: tea about my legal briefs and my motion is that

846
00:40:53,360 --> 00:40:57,120
Speaker 1: they're from me to you. Yeah, So once I start

847
00:40:57,160 --> 00:41:01,000
Speaker 1: pumping that into AI, it's not written as me I

848
00:41:01,239 --> 00:41:06,239
Speaker 1: like a stylized motion her mother was beheaded. A. I

849
00:41:06,280 --> 00:41:08,680
Speaker 1: is not going to say that when I put that in,

850
00:41:08,760 --> 00:41:12,279
Speaker 1: like help me draft this legal motion or like my

851
00:41:12,640 --> 00:41:16,480
Speaker 1: asylum argument, I'll say that, but a A I will

852
00:41:16,480 --> 00:41:21,959
Speaker 1: say respondents parents suffered extreme hardship, like it will say,

853
00:41:22,000 --> 00:41:24,080
Speaker 1: like some sort of guard.

854
00:41:23,920 --> 00:41:27,480
Speaker 2: Water down word salad. Yeah, So I don't know.

855
00:41:27,600 --> 00:41:28,040
Speaker 1: I hate it.

856
00:41:28,080 --> 00:41:28,759
Speaker 2: I think it's dumb.

857
00:41:28,760 --> 00:41:31,520
Speaker 1: I don't think it applies to everything, and I think

858
00:41:31,560 --> 00:41:34,120
Speaker 1: it's over hyped and it's gonna bubble that's going to burst.

859
00:41:34,320 --> 00:41:35,640
Speaker 1: Judge also on the record with that.

860
00:41:35,719 --> 00:41:37,840
Speaker 3: Yeah, judges are kicking it out of the courtroom. People

861
00:41:37,960 --> 00:41:40,239
Speaker 3: coming with their AI lawyers and judges are like, get

862
00:41:40,280 --> 00:41:40,800
Speaker 3: it out.

863
00:41:41,080 --> 00:41:45,040
Speaker 2: It's not gonna I had this a conversation with my

864
00:41:45,360 --> 00:41:48,280
Speaker 2: primary care physician a few months back, and she wanted

865
00:41:48,280 --> 00:41:51,719
Speaker 2: me to know that they were under the doctors were

866
00:41:51,800 --> 00:41:55,160
Speaker 2: under pressure to use AI for the note taking, and

867
00:41:55,200 --> 00:41:58,319
Speaker 2: she's a pretty old school doctor and she was psch.

868
00:41:58,440 --> 00:42:03,000
Speaker 2: I refused, and she wanted me to know that they

869
00:42:03,080 --> 00:42:06,759
Speaker 2: must tell you that they're using it, and if I

870
00:42:06,800 --> 00:42:08,960
Speaker 2: find out that they've used it and they haven't told me,

871
00:42:09,280 --> 00:42:12,759
Speaker 2: I can bring charges up against them. Right. But her

872
00:42:12,880 --> 00:42:16,279
Speaker 2: worry is, you know, she says, people come to her,

873
00:42:17,000 --> 00:42:20,000
Speaker 2: she's their physician, and they tell her intimate things about

874
00:42:20,040 --> 00:42:21,799
Speaker 2: what's going on in their lives, things are going on

875
00:42:21,880 --> 00:42:25,040
Speaker 2: with their health, and she is deeply uncomfortable with the

876
00:42:25,080 --> 00:42:29,680
Speaker 2: idea of whatever AI turns into having that information.

877
00:42:30,040 --> 00:42:32,680
Speaker 3: Yeah, and it'll hear your voice and you know, AI

878
00:42:32,760 --> 00:42:35,319
Speaker 3: can mimic voices like I don't want to find out

879
00:42:35,360 --> 00:42:38,359
Speaker 3: where the end of the story goes, but I'm with you.

880
00:42:38,640 --> 00:42:42,240
Speaker 3: And a positive example of AI though, is like breast cancer,

881
00:42:42,960 --> 00:42:46,680
Speaker 3: the detection you still need human oversight, right, but using

882
00:42:46,920 --> 00:42:49,399
Speaker 3: a machine is actually more accurate than humans. So that's

883
00:42:49,440 --> 00:42:51,960
Speaker 3: a great example where the research is showing it's better

884
00:42:52,640 --> 00:42:55,240
Speaker 3: and it doesn't I think, inherently replace anything.

885
00:42:56,760 --> 00:42:57,040
Speaker 2: Yeah.

886
00:42:57,640 --> 00:43:00,319
Speaker 3: So that's the balance. You know, people act like it's

887
00:43:00,360 --> 00:43:03,040
Speaker 3: all in, all out, and it's like we have.

888
00:43:03,080 --> 00:43:05,239
Speaker 2: A balance to most things, right, and we just have

889
00:43:05,320 --> 00:43:10,520
Speaker 2: to find that what's going to do no harm as

890
00:43:10,520 --> 00:43:11,800
Speaker 2: little as harm as possible.

891
00:43:11,920 --> 00:43:15,640
Speaker 1: Absolutely, yes, So where are we in this race?

892
00:43:16,000 --> 00:43:18,360
Speaker 3: Well, again, I want to thank you guys for having

893
00:43:18,360 --> 00:43:20,320
Speaker 3: me on. It's so important that we have new media.

894
00:43:20,440 --> 00:43:24,400
Speaker 3: We know that traditional media is dying, right, monopoly is

895
00:43:24,480 --> 00:43:28,000
Speaker 3: we can literally there's like spreadsheets now of like three

896
00:43:28,040 --> 00:43:31,520
Speaker 3: companies that own or three different owners for fifty companies.

897
00:43:32,440 --> 00:43:35,680
Speaker 1: There's about to be another Selder about to merger.

898
00:43:35,760 --> 00:43:38,640
Speaker 3: Yeah, goodness, that's just approved. I don't know how Elizabeth

899
00:43:38,680 --> 00:43:40,920
Speaker 3: Warren is handling this right. She's been calling for the

900
00:43:40,920 --> 00:43:43,120
Speaker 3: breaking up monopolies for so long. That's why I backed

901
00:43:43,120 --> 00:43:48,560
Speaker 3: her for presidential run back in twenty sixteen. It's it's

902
00:43:48,640 --> 00:43:51,799
Speaker 3: deeply problematic what is happening with our media, and I've

903
00:43:51,840 --> 00:43:54,239
Speaker 3: seen a lack of critical thinking about the candidates that

904
00:43:54,320 --> 00:43:57,279
Speaker 3: are offered, a lack of expiration. One of the things

905
00:43:57,280 --> 00:43:59,120
Speaker 3: I brought up on the debate stage was a racist

906
00:43:59,120 --> 00:44:03,360
Speaker 3: cartoon that Michael helped distribute in white neighborhoods, going after

907
00:44:03,640 --> 00:44:07,040
Speaker 3: Reverend Al Sharpton. And it was a horrific graphic and

908
00:44:07,080 --> 00:44:08,879
Speaker 3: we found it because even though it's been talked about

909
00:44:08,920 --> 00:44:11,520
Speaker 3: once or twice, no one's shown the image. And it

910
00:44:11,600 --> 00:44:15,359
Speaker 3: was to impede a Latino mayoral candidate. It was meant

911
00:44:15,440 --> 00:44:19,000
Speaker 3: to have him lose. And so I am very concerned

912
00:44:19,000 --> 00:44:21,399
Speaker 3: when I see black and brown communities saying, oh, maybe

913
00:44:21,440 --> 00:44:24,279
Speaker 3: Mike is the choice. It's like, if it's convenient for him,

914
00:44:24,400 --> 00:44:25,960
Speaker 3: then sure he'll show up for you. If it's not,

915
00:44:26,680 --> 00:44:29,440
Speaker 3: then you're going to be used as fodder. And you

916
00:44:29,440 --> 00:44:31,560
Speaker 3: should know that about your candidates, who has always stood

917
00:44:31,760 --> 00:44:34,640
Speaker 3: for the communities, not come only when they need something,

918
00:44:35,280 --> 00:44:38,759
Speaker 3: so I have tried to be the vocal advocate, and

919
00:44:39,040 --> 00:44:40,799
Speaker 3: people like you have helped lift me up and I

920
00:44:40,840 --> 00:44:44,080
Speaker 3: really appreciate that giving me this opportunity. I want people

921
00:44:44,120 --> 00:44:46,279
Speaker 3: to really think as they go to vote for n

922
00:44:46,400 --> 00:44:50,520
Speaker 3: Y twelve, who do you want? I have heard from

923
00:44:50,520 --> 00:44:53,080
Speaker 3: many people who do they think is going to win?

924
00:44:53,640 --> 00:44:56,080
Speaker 3: Just different than who do you want? And we need

925
00:44:56,120 --> 00:44:58,799
Speaker 3: to start voting who do you want? Because we saw

926
00:44:59,000 --> 00:45:02,959
Speaker 3: this amazing shift with Mom Donnie versus Cuomo, Cole Old Guard.

927
00:45:03,120 --> 00:45:05,359
Speaker 3: It was the big money, it was the billionaires. It

928
00:45:05,400 --> 00:45:08,920
Speaker 3: was this ugly attitude of I will take what I want,

929
00:45:09,440 --> 00:45:13,239
Speaker 3: no one can stop me, and we won. I love

930
00:45:13,280 --> 00:45:14,960
Speaker 3: that a door knocked for Mayor mont Donnie and he

931
00:45:15,000 --> 00:45:17,000
Speaker 3: has yet to choose a candidate. I hope he'll choose me.

932
00:45:17,160 --> 00:45:17,760
Speaker 1: That's day.

933
00:45:19,080 --> 00:45:19,319
Speaker 2: Well.

934
00:45:19,360 --> 00:45:21,399
Speaker 3: And it might be smart that he doesn't say who

935
00:45:21,400 --> 00:45:24,200
Speaker 3: he wants to move for, because he's not super super loved.

936
00:45:24,480 --> 00:45:27,319
Speaker 3: It was a fifty to fifty split in twelve. He's

937
00:45:27,360 --> 00:45:32,279
Speaker 3: loved everywhere else, but it's a high Jewish population and

938
00:45:32,320 --> 00:45:34,840
Speaker 3: people were I think rightly upset with his use of

939
00:45:34,880 --> 00:45:37,480
Speaker 3: anti fada and things at the beginning. I think he's

940
00:45:37,520 --> 00:45:41,439
Speaker 3: worked really hard to try to correct missteps and errors

941
00:45:41,480 --> 00:45:45,160
Speaker 3: that have stoked some anti Semitism. But I understand people

942
00:45:45,200 --> 00:45:48,920
Speaker 3: who are very upset. It's maybe one of the quickest

943
00:45:48,960 --> 00:45:50,840
Speaker 3: questions I get asked on the street is like Mandannie

944
00:45:50,880 --> 00:45:52,640
Speaker 3: or Cuomo? And I was like, Mom Donnie, and people

945
00:45:52,600 --> 00:45:56,280
Speaker 3: will walk away and starve away. But Cuomo's actually harassed

946
00:45:56,560 --> 00:45:59,440
Speaker 3: Charlotte Bennett, who is someone who interned for me, and

947
00:45:59,560 --> 00:46:03,080
Speaker 3: I was the first phone call she made after that incident,

948
00:46:03,080 --> 00:46:04,840
Speaker 3: and she said, I think I have to sue my boss.

949
00:46:04,840 --> 00:46:07,120
Speaker 3: I didn't know she worked for Cuomo, but she called

950
00:46:07,120 --> 00:46:08,919
Speaker 3: me to get a referral and I gave her one.

951
00:46:09,120 --> 00:46:11,799
Speaker 3: So I'm never going to vote for that man. I'm

952
00:46:11,840 --> 00:46:13,840
Speaker 3: so glad he's nowhere in the city from what I

953
00:46:13,880 --> 00:46:16,480
Speaker 3: can tell. But he thought about entering this race, and

954
00:46:16,640 --> 00:46:18,480
Speaker 3: some part of me kind of wish he did so

955
00:46:18,560 --> 00:46:20,840
Speaker 3: I had someone to punch against, because that was the

956
00:46:20,840 --> 00:46:23,200
Speaker 3: beauty the Mom Donnie race. There was someone to punch against.

957
00:46:23,239 --> 00:46:25,960
Speaker 3: There was a bad guy this one. I think everyone

958
00:46:26,200 --> 00:46:29,560
Speaker 3: is generally a pretty good Democrat, right, and it's different

959
00:46:29,640 --> 00:46:32,160
Speaker 3: levels of experience, And so why I'm saying, Picky, you

960
00:46:32,200 --> 00:46:34,560
Speaker 3: really want to lead? Who is the new voice, who

961
00:46:34,600 --> 00:46:36,360
Speaker 3: is saying the things you haven't heard, Who is the

962
00:46:36,360 --> 00:46:38,600
Speaker 3: person that's going to fight the battles versus look away,

963
00:46:39,120 --> 00:46:42,080
Speaker 3: and then vote for them because when thirty percent or undecided,

964
00:46:42,080 --> 00:46:45,480
Speaker 3: that swings an entire race. So don't how anyone out

965
00:46:45,840 --> 00:46:49,440
Speaker 3: take your time eight candidates, just research all of them. Yeah,

966
00:46:49,480 --> 00:46:50,040
Speaker 3: takes a minute.

967
00:46:50,120 --> 00:46:53,600
Speaker 2: I actually really love what you're saying about choose stop

968
00:46:53,680 --> 00:46:56,880
Speaker 2: thinking so much about who's going to win, because I

969
00:46:57,360 --> 00:46:59,120
Speaker 2: have been guilty of thinking the same people as well.

970
00:46:59,120 --> 00:47:01,640
Speaker 2: I could do this, but is my vote wasted?

971
00:47:01,760 --> 00:47:01,960
Speaker 3: Right?

972
00:47:02,320 --> 00:47:05,640
Speaker 2: But this notion of vote for the person who you

973
00:47:05,719 --> 00:47:07,719
Speaker 2: really want in the job, vote for the person that

974
00:47:07,760 --> 00:47:10,440
Speaker 2: you think will do their best. If more of us

975
00:47:10,520 --> 00:47:13,760
Speaker 2: think that way, the shift that we're hoping will happen.

976
00:47:13,840 --> 00:47:16,239
Speaker 2: I think will eventually happen. It might take some time,

977
00:47:16,480 --> 00:47:20,759
Speaker 2: but it's a better way to think about it.

978
00:47:20,960 --> 00:47:24,160
Speaker 3: A vote is a message to the establishment of where

979
00:47:24,320 --> 00:47:27,279
Speaker 3: the current is going, right, and NY twelve really is

980
00:47:27,520 --> 00:47:30,600
Speaker 3: the district that everyone in the country watches. It's Manhattan.

981
00:47:30,640 --> 00:47:33,160
Speaker 3: It's where all the new innovation ideas come from. So

982
00:47:33,200 --> 00:47:35,800
Speaker 3: we're way too much money and power have been consolidated.

983
00:47:36,160 --> 00:47:40,360
Speaker 3: So even a significant shift like towards a non establishment candidate,

984
00:47:40,680 --> 00:47:43,279
Speaker 3: says a lot to any establishment candidate that would win

985
00:47:43,440 --> 00:47:46,520
Speaker 3: to maybe be more progressive than they're inclined to be,

986
00:47:46,600 --> 00:47:49,879
Speaker 3: which is good. We want a representative who's understanding where

987
00:47:49,920 --> 00:47:52,840
Speaker 3: the current is going and not just you know, standing

988
00:47:52,880 --> 00:47:56,040
Speaker 3: by for example, Hquem Jeffries. It absolutely killed me. I

989
00:47:56,040 --> 00:47:57,799
Speaker 3: didn't have time in the debate to make all the

990
00:47:57,840 --> 00:48:01,000
Speaker 3: points I wanted, but him Jeffries, has come out saying

991
00:48:01,080 --> 00:48:04,880
Speaker 3: impeaching Donald Trump is no longer the priority. It's now affordability.

992
00:48:05,360 --> 00:48:07,440
Speaker 3: And they're related, you know, like we can't have someone

993
00:48:07,520 --> 00:48:10,400
Speaker 3: stealing one point eight billion dollars from IRS and then

994
00:48:10,480 --> 00:48:13,520
Speaker 3: pretend like that's not going to affect the taxpayer, So

995
00:48:13,880 --> 00:48:17,080
Speaker 3: it's related. But the minute that came out, Michael Lasher

996
00:48:17,200 --> 00:48:20,200
Speaker 3: was in a forum for ninety second Street Why, and

997
00:48:20,239 --> 00:48:24,360
Speaker 3: he said, it is a fantasy world. It is impossible.

998
00:48:25,000 --> 00:48:27,680
Speaker 3: There's no world that exists in which we can impeach

999
00:48:27,760 --> 00:48:30,520
Speaker 3: Donald Trump. And I was shocked. I've listened to him

1000
00:48:30,520 --> 00:48:32,160
Speaker 3: in every debate and I was like, where is this

1001
00:48:32,200 --> 00:48:34,680
Speaker 3: coming from? And then I saw Hikin Jeffreys and I

1002
00:48:34,719 --> 00:48:38,000
Speaker 3: was like, oh, so you you have abandoned your principles

1003
00:48:38,040 --> 00:48:41,040
Speaker 3: that you've said in every single forum because someone said

1004
00:48:41,040 --> 00:48:43,160
Speaker 3: it's not our priority, and so you just shifted on

1005
00:48:43,200 --> 00:48:45,360
Speaker 3: a dime. You didn't listen to what the people on

1006
00:48:45,400 --> 00:48:48,600
Speaker 3: the ground said, because if you did, everyone wants him out,

1007
00:48:48,680 --> 00:48:50,480
Speaker 3: Like especially after what he did with the NIXT game.

1008
00:48:50,560 --> 00:48:51,800
Speaker 3: I mean he's gone now.

1009
00:48:54,920 --> 00:48:56,440
Speaker 2: He's like, where's your moral compass?

1010
00:48:56,680 --> 00:49:00,640
Speaker 1: Right? Well, thank you for joining us, Laura. Early voting

1011
00:49:00,680 --> 00:49:03,000
Speaker 1: is happening now if you're listening to this on Thursday

1012
00:49:03,120 --> 00:49:06,680
Speaker 1: or watching it on YouTube, and the election is on Tuesday,

1013
00:49:06,920 --> 00:49:10,840
Speaker 1: June twenty third, So get to the polls, vote for

1014
00:49:10,880 --> 00:49:11,680
Speaker 1: who you care about.

1015
00:49:12,160 --> 00:49:15,080
Speaker 2: Laura. Where can people find you on social night you

1016
00:49:15,120 --> 00:49:16,000
Speaker 2: look into the camera link.

1017
00:49:16,040 --> 00:49:18,600
Speaker 3: Thank ye. So Lourdne for Congress dot com is the

1018
00:49:18,640 --> 00:49:22,160
Speaker 3: home base, and Loura Done for Congress is TikTok. It's

1019
00:49:22,200 --> 00:49:25,520
Speaker 3: LinkedIn Facebook. The only one that's different is of course

1020
00:49:25,560 --> 00:49:27,560
Speaker 3: Twitter and X. I'm sorry I'm still on there. It's

1021
00:49:27,560 --> 00:49:31,080
Speaker 3: a political necessary Loura Done Ny twelve, But I would

1022
00:49:31,120 --> 00:49:33,720
Speaker 3: love to have you follow, like shoot me a message.

1023
00:49:33,719 --> 00:49:36,280
Speaker 3: I actually do respond to everyone who asks me questions

1024
00:49:36,320 --> 00:49:37,879
Speaker 3: because I want you to know who you're voting for

1025
00:49:38,000 --> 00:49:39,080
Speaker 3: and what my values are.

1026
00:49:39,400 --> 00:49:41,200
Speaker 2: Thank you so much, Thank you so much, Thank you

1027
00:49:41,200 --> 00:49:42,240
Speaker 2: for coming coming.

1028
00:49:42,480 --> 00:49:43,360
Speaker 3: Course, thank you guys.

1029
00:49:46,840 --> 00:49:48,600
Speaker 1: This is Tales from the Dams. We're going to talk

1030
00:49:48,719 --> 00:49:51,799
Speaker 1: about all the weird, wild, freaky, dky things you send

1031
00:49:51,800 --> 00:49:54,400
Speaker 1: me in my DMS. You email it to brief Recess

1032
00:49:54,480 --> 00:49:57,480
Speaker 1: at exactly Wrightmedia dot com, or you send them to Melissa,

1033
00:49:57,960 --> 00:49:59,759
Speaker 1: whatever you want to do. We're reading it on the

1034
00:49:59,760 --> 00:50:02,799
Speaker 1: show and it's getting sick and twisted and I love it.

1035
00:50:02,800 --> 00:50:04,280
Speaker 1: Sure is, so Melissa.

1036
00:50:04,640 --> 00:50:08,680
Speaker 2: Who am I? What I always say? Friends? Well, Michael

1037
00:50:08,840 --> 00:50:12,280
Speaker 2: is a lawyer. He's not your lawyer, so you probably

1038
00:50:12,320 --> 00:50:15,880
Speaker 2: should find your own. By the way, speaking of that,

1039
00:50:16,719 --> 00:50:21,080
Speaker 2: somebody quoted that to me where in Kate may I

1040
00:50:21,120 --> 00:50:21,839
Speaker 2: love that? I know?

1041
00:50:22,120 --> 00:50:22,680
Speaker 1: I love that.

1042
00:50:22,719 --> 00:50:23,000
Speaker 2: I know.

1043
00:50:23,200 --> 00:50:27,120
Speaker 1: Not this show getting traction, not this not people liking

1044
00:50:27,160 --> 00:50:31,279
Speaker 1: this show, not that being on my twenty twenty six

1045
00:50:31,320 --> 00:50:33,600
Speaker 1: Bingo card that was not on there. But here we are.

1046
00:50:34,480 --> 00:50:37,399
Speaker 1: You know what, not many people believed in us.

1047
00:50:37,640 --> 00:50:38,520
Speaker 2: We believed in us.

1048
00:50:38,600 --> 00:50:41,880
Speaker 1: Yeah, be the change you wish to see at the

1049
00:50:41,880 --> 00:50:43,080
Speaker 1: bottom of the trappy fountain.

1050
00:50:43,600 --> 00:50:47,440
Speaker 2: Totally random things. Did you see? My mom commented on Magalie.

1051
00:50:48,280 --> 00:50:50,960
Speaker 1: She is using ten nine words. She's getting in there

1052
00:50:51,280 --> 00:50:52,680
Speaker 1: she is respond.

1053
00:50:52,480 --> 00:50:54,320
Speaker 2: I'm like, thanks, mom, you welcome.

1054
00:50:56,600 --> 00:50:59,000
Speaker 1: Oh my god. Okay. The one thing I don't want

1055
00:50:59,040 --> 00:51:03,120
Speaker 1: you guys to send us medical prognoses because someone someone

1056
00:51:03,200 --> 00:51:05,800
Speaker 1: sent me a mental illness prognosis.

1057
00:51:05,960 --> 00:51:06,920
Speaker 2: What what do you got.

1058
00:51:07,160 --> 00:51:08,320
Speaker 1: Telling me I'm bipolar?

1059
00:51:08,480 --> 00:51:08,759
Speaker 2: Are you?

1060
00:51:09,560 --> 00:51:10,319
Speaker 1: I don't think so?

1061
00:51:11,600 --> 00:51:17,080
Speaker 2: Should you ask somebody not a medical professional why? I'm curious, though,

1062
00:51:17,320 --> 00:51:22,239
Speaker 2: what is it? What behaviors? Hey, friends, what behaviors.

1063
00:51:22,600 --> 00:51:24,560
Speaker 1: Having them do exactly what I don't want.

1064
00:51:24,840 --> 00:51:27,200
Speaker 2: But I'm curious, Like I would never have said that

1065
00:51:27,280 --> 00:51:29,960
Speaker 2: about you. So I'm wondering what it is that they're

1066
00:51:30,000 --> 00:51:33,839
Speaker 2: looking at. And they're like, he's he's bipolar.

1067
00:51:34,160 --> 00:51:35,000
Speaker 1: Man's bipolar.

1068
00:51:35,120 --> 00:51:37,080
Speaker 2: He's bipolar. It's like the person who told me that

1069
00:51:37,120 --> 00:51:39,440
Speaker 2: I was jaundice.

1070
00:51:40,920 --> 00:51:43,160
Speaker 1: You're like, I'm actually just black.

1071
00:51:43,280 --> 00:51:44,120
Speaker 2: I'm just brown.

1072
00:51:44,239 --> 00:51:45,480
Speaker 1: I'm just a black woman.

1073
00:51:45,800 --> 00:51:48,080
Speaker 2: That's all that it is. Thank you.

1074
00:51:48,400 --> 00:51:50,960
Speaker 1: Okay. So this is from the sixty Minutes episode This

1075
00:51:51,000 --> 00:51:55,040
Speaker 1: is a fun show review. Mike Alvoord fifty five says, Actually, guys,

1076
00:51:55,080 --> 00:51:59,000
Speaker 1: nobody is watching CBS News or sixty Minutes. CBS is

1077
00:51:59,000 --> 00:52:01,640
Speaker 1: full of partisan active and not journalists. Did you not

1078
00:52:01,719 --> 00:52:05,120
Speaker 1: think this would catch up to you eventually? No, I didn't.

1079
00:52:05,520 --> 00:52:06,840
Speaker 1: This is the first I thought about it.

1080
00:52:06,960 --> 00:52:12,040
Speaker 2: He's not talking to you, oh, talking to CBS. He's

1081
00:52:12,040 --> 00:52:12,440
Speaker 2: talking to.

1082
00:52:12,840 --> 00:52:15,839
Speaker 1: It's like, wow, yeah, I am really part of isant.

1083
00:52:15,840 --> 00:52:18,200
Speaker 1: Actually I'm not a journalist, so it did catch up

1084
00:52:18,239 --> 00:52:18,400
Speaker 1: to me.

1085
00:52:19,400 --> 00:52:21,560
Speaker 2: No, he's not talking I don't Okay, thanks, I don't

1086
00:52:21,560 --> 00:52:23,239
Speaker 2: think that Mike is talking to you. I think he's

1087
00:52:23,280 --> 00:52:29,239
Speaker 2: talking to CBS. I used to watch CBS in the

1088
00:52:29,239 --> 00:52:32,560
Speaker 2: morning every day, and we've and we switched, which is

1089
00:52:33,520 --> 00:52:35,320
Speaker 2: and I have a family member who works on that show.

1090
00:52:35,400 --> 00:52:40,239
Speaker 2: So oh yeah, but you gotta do something, you gotta

1091
00:52:40,280 --> 00:52:42,520
Speaker 2: stand for something. I get scruples from somewhere.

1092
00:52:42,719 --> 00:52:45,840
Speaker 1: Scruples from somewhere. Katie Kirk gave me your number. She

1093
00:52:45,960 --> 00:52:46,600
Speaker 1: was in CBS.

1094
00:52:46,640 --> 00:52:48,280
Speaker 2: Who she she was on NBC?

1095
00:52:48,600 --> 00:52:48,880
Speaker 1: NBC.

1096
00:52:49,040 --> 00:52:51,080
Speaker 2: Okay, okay, okay, okay, one day.

1097
00:52:51,560 --> 00:52:53,160
Speaker 1: One day, you'll tell me a Katie Kirk story.

1098
00:52:53,800 --> 00:52:56,200
Speaker 2: Is a Magley Joel Melissa's story.

1099
00:52:56,480 --> 00:52:58,640
Speaker 1: Okay, for one more reason, you should just tell me.

1100
00:52:59,560 --> 00:53:02,279
Speaker 2: Okay. When I decided to have weight loss surgery, I

1101
00:53:02,320 --> 00:53:04,920
Speaker 2: did not want to tell my parents because they were

1102
00:53:04,920 --> 00:53:06,440
Speaker 2: going to be in my ear about it. And then

1103
00:53:06,560 --> 00:53:09,800
Speaker 2: finally my brother said to me, if you don't tell them.

1104
00:53:10,320 --> 00:53:11,239
Speaker 2: I'm going to tell them.

1105
00:53:11,360 --> 00:53:13,600
Speaker 1: Did he give you a deadline? Yeah?

1106
00:53:14,160 --> 00:53:18,200
Speaker 2: So the week of I show up at my parents'

1107
00:53:18,200 --> 00:53:20,000
Speaker 2: house late at night and my mom is like, what

1108
00:53:20,000 --> 00:53:22,120
Speaker 2: are you doing here? And I was like nothing.

1109
00:53:22,320 --> 00:53:24,480
Speaker 1: You're like, I'm on a deadline Joey gave me.

1110
00:53:24,800 --> 00:53:28,040
Speaker 2: I said nothing. Where's where's Pop? And she was like

1111
00:53:28,080 --> 00:53:30,319
Speaker 2: he's in the room and I said okay. So I

1112
00:53:30,360 --> 00:53:32,800
Speaker 2: went back there and my dad was like half asleep,

1113
00:53:32,840 --> 00:53:35,239
Speaker 2: and I was like hey. He was like, what's the matter.

1114
00:53:35,320 --> 00:53:36,799
Speaker 2: I was like nothing, I wanted to talk to you

1115
00:53:36,880 --> 00:53:40,000
Speaker 2: with mom. So I turn around to call my mom

1116
00:53:40,080 --> 00:53:41,239
Speaker 2: and she's right here.

1117
00:53:42,400 --> 00:53:47,000
Speaker 1: Like I bumped intown, like like alien, like right here.

1118
00:53:47,560 --> 00:53:50,080
Speaker 2: So I go on to say whatever, I'm going to

1119
00:53:50,120 --> 00:53:52,680
Speaker 2: have weight loss surgery and they're like, oh my god.

1120
00:53:52,840 --> 00:53:59,279
Speaker 2: And then my dad said to me Lisa. He's like,

1121
00:53:59,400 --> 00:54:05,280
Speaker 2: I look it Al Roker and he says Al Roker

1122
00:54:05,800 --> 00:54:10,440
Speaker 2: the weather man on Good Morning America. This is important, okay,

1123
00:54:10,520 --> 00:54:14,000
Speaker 2: And my mom says, Joel. That's my dad's name is Joel.

1124
00:54:14,920 --> 00:54:18,680
Speaker 2: I woka sit back, Good Morning, I met you go

1125
00:54:19,920 --> 00:54:21,440
Speaker 2: I woke on East Today Show.

1126
00:54:23,239 --> 00:54:25,320
Speaker 1: I meanwhile, You're like, I'm trying to make an important

1127
00:54:25,360 --> 00:54:26,080
Speaker 1: life announcement.

1128
00:54:26,480 --> 00:54:29,000
Speaker 2: And when I tell you this went back and forth

1129
00:54:29,040 --> 00:54:31,799
Speaker 2: for like three minutes, and I'm sitting here and my

1130
00:54:31,920 --> 00:54:34,920
Speaker 2: mom is like, I woke her today, show get your

1131
00:54:34,920 --> 00:54:40,040
Speaker 2: correc Matt Lawe and go. And then my dad's like,

1132
00:54:41,120 --> 00:54:42,120
Speaker 2: you're right, you know what.

1133
00:54:42,880 --> 00:54:46,400
Speaker 1: Minutes later. There was another part of that story though,

1134
00:54:46,440 --> 00:54:48,360
Speaker 1: that you haven't told yet, and I want you to.

1135
00:54:48,480 --> 00:54:49,480
Speaker 1: I want you to say it.

1136
00:54:49,880 --> 00:54:52,399
Speaker 2: Oh right now, I'll say so. One of the things

1137
00:54:52,400 --> 00:54:55,320
Speaker 2: that I really wanted to make sure was that I

1138
00:54:55,360 --> 00:54:57,719
Speaker 2: didn't want them to tell anybody because I wasn't ready

1139
00:54:57,880 --> 00:55:01,880
Speaker 2: to say anything. And I and I said, I don't

1140
00:55:01,880 --> 00:55:04,839
Speaker 2: want you to tell people. Mom, don't because my mom

1141
00:55:04,920 --> 00:55:08,880
Speaker 2: will tell her sisters everything. Mom, I don't want you

1142
00:55:08,920 --> 00:55:09,600
Speaker 2: to tell anybody.

1143
00:55:09,640 --> 00:55:13,400
Speaker 1: And my miss is actually her microphone she uses to

1144
00:55:13,440 --> 00:55:14,840
Speaker 1: tell the whole sam everybody.

1145
00:55:15,760 --> 00:55:18,640
Speaker 2: Yeah, so and she was like no, no, no, I'm

1146
00:55:18,680 --> 00:55:20,160
Speaker 2: not going to say anything. And then I was like

1147
00:55:20,200 --> 00:55:24,000
Speaker 2: all right, and then my dad was very offended. Yeah,

1148
00:55:24,040 --> 00:55:25,759
Speaker 2: he was just like what do you mean? And then

1149
00:55:25,760 --> 00:55:28,160
Speaker 2: my mom went to go do something and I was like, Dad,

1150
00:55:28,560 --> 00:55:31,279
Speaker 2: I'm not talking to you, I'm talking to mom. Oh, mummy,

1151
00:55:31,360 --> 00:55:34,840
Speaker 2: use something else. Yeah, because my mom can't she cannot

1152
00:55:34,920 --> 00:55:36,960
Speaker 2: keep It was like, oh yeah, he was like, oh

1153
00:55:37,000 --> 00:55:39,239
Speaker 2: for sure, for sure, you really needed to tell her that.

1154
00:55:39,320 --> 00:55:39,719
Speaker 1: Thank you.

1155
00:55:39,840 --> 00:55:41,319
Speaker 2: He was like, but it didn't matter because she told

1156
00:55:41,320 --> 00:55:46,359
Speaker 2: an told everybody anyway she did. I was really I

1157
00:55:46,360 --> 00:55:47,080
Speaker 2: had to track her down.

1158
00:55:47,120 --> 00:55:50,600
Speaker 1: She was on vacationing the tea. Okay, okay, do you

1159
00:55:50,680 --> 00:55:53,479
Speaker 1: want to read this one from Natalie Castle. It's about Ted,

1160
00:55:53,560 --> 00:55:59,040
Speaker 1: your neighbor, neighbor. A lot of people messaged me about

1161
00:55:59,080 --> 00:55:59,799
Speaker 1: your neighbor Ted.

1162
00:56:00,080 --> 00:56:02,600
Speaker 2: The best thing about it was that Katie sent us

1163
00:56:02,600 --> 00:56:04,640
Speaker 2: a text message. I'll share it with you guys if

1164
00:56:04,640 --> 00:56:06,759
Speaker 2: you want. And she was like, has Ted said fire

1165
00:56:06,840 --> 00:56:13,560
Speaker 2: to the rain lately? Dead? Okay? This is from Natalie

1166
00:56:13,640 --> 00:56:16,799
Speaker 2: Castle in ninety five. You're always having a bad fucking day.

1167
00:56:16,880 --> 00:56:19,360
Speaker 2: Ted is relatable in that regard.

1168
00:56:20,640 --> 00:56:25,120
Speaker 1: For Ted. Okay. From the Alex Murder Murder Conviction Overturned episode,

1169
00:56:25,360 --> 00:56:29,320
Speaker 1: Cisco says, longtime, your first time commenter, Welcome to the DMS.

1170
00:56:29,800 --> 00:56:32,440
Speaker 1: To complicate things more, I have an internal monologue but

1171
00:56:32,560 --> 00:56:37,719
Speaker 1: can't visualize. It's called a fantasia, and when I close

1172
00:56:37,840 --> 00:56:41,719
Speaker 1: my eyes, it feels like talking to someone in a

1173
00:56:41,800 --> 00:56:43,040
Speaker 1: dark room.

1174
00:56:43,760 --> 00:56:44,200
Speaker 2: Wow.

1175
00:56:44,719 --> 00:56:45,799
Speaker 1: Oh that's so cool.

1176
00:56:45,920 --> 00:56:47,600
Speaker 2: I got a lot of people who were upset with

1177
00:56:47,640 --> 00:56:49,680
Speaker 2: me when we were talking about the people who don't

1178
00:56:49,719 --> 00:56:52,719
Speaker 2: have an internal model, okay, and they wanted me to

1179
00:56:53,200 --> 00:56:57,000
Speaker 2: know that just because you don't have an internal monologue

1180
00:56:57,040 --> 00:56:59,359
Speaker 2: doesn't mean you have a moral compass. And I wasn't

1181
00:56:59,360 --> 00:57:01,960
Speaker 2: sure that's what I was saying. We were also processing

1182
00:57:02,000 --> 00:57:04,359
Speaker 2: in real time, correct, I was because it was hard

1183
00:57:04,400 --> 00:57:06,000
Speaker 2: to understand. I'm like, well, if you don't have an

1184
00:57:06,000 --> 00:57:09,759
Speaker 2: inner monologue, what's going on? So people were saying that

1185
00:57:09,840 --> 00:57:13,400
Speaker 2: they see images, they do other things, but they don't

1186
00:57:13,600 --> 00:57:15,640
Speaker 2: they're just not yapping to themselves all day like that.

1187
00:57:15,760 --> 00:57:19,280
Speaker 2: I think that that is an inner monologue, right, maybe yeh,

1188
00:57:19,320 --> 00:57:22,640
Speaker 2: there's images in your head. I think it's like, it's

1189
00:57:22,720 --> 00:57:26,040
Speaker 2: kind of the same thing, take a nuanced kind of trum.

1190
00:57:26,280 --> 00:57:30,280
Speaker 2: I was concerned that people with no inner monologue but

1191
00:57:30,320 --> 00:57:33,440
Speaker 2: there's nothing going on, and I was wrong, And I'm sorry.

1192
00:57:33,600 --> 00:57:37,200
Speaker 1: All right, we'll do a quick email question. I'll read

1193
00:57:37,280 --> 00:57:41,160
Speaker 1: number one. Sorry, Highbury Precess love your podcast. Last month,

1194
00:57:41,240 --> 00:57:43,440
Speaker 1: I was called for jury duty at the US District

1195
00:57:43,480 --> 00:57:45,880
Speaker 1: Court for Southern New York. I was not part of

1196
00:57:45,880 --> 00:57:49,360
Speaker 1: the jury, but did spend three days in the wider

1197
00:57:49,400 --> 00:57:52,919
Speaker 1: process involves a lot of waiting around, Yes, forced into

1198
00:57:52,920 --> 00:57:56,000
Speaker 1: a new form of existence without any electronic devices. I

1199
00:57:56,120 --> 00:57:59,720
Speaker 1: noticed that all the female attorneys, almost all of them

1200
00:57:59,720 --> 00:58:03,400
Speaker 1: wore heels. I assume most of these women have some

1201
00:58:03,440 --> 00:58:06,920
Speaker 1: comfortable sneakers stashed somewhere in the building, though I acknowledge

1202
00:58:06,920 --> 00:58:10,320
Speaker 1: they're wonderfully loud on those shiny marble floors. Anyway, I

1203
00:58:10,320 --> 00:58:13,280
Speaker 1: found myself wondering why so few female lawyers were in

1204
00:58:13,360 --> 00:58:17,920
Speaker 1: cute dress professional flats. Our female attorneys still expected to

1205
00:58:17,920 --> 00:58:22,160
Speaker 1: wear high heels, and many work situations are flats quietly

1206
00:58:22,200 --> 00:58:22,840
Speaker 1: frowned upon.

1207
00:58:23,080 --> 00:58:24,800
Speaker 2: That's a good question. That's a good question. I don't know.

1208
00:58:25,280 --> 00:58:29,480
Speaker 1: I think that tell us about just like professional women attire,

1209
00:58:30,480 --> 00:58:31,560
Speaker 1: I meanspective.

1210
00:58:31,560 --> 00:58:35,160
Speaker 2: I think it depends, and I think it depends on

1211
00:58:36,600 --> 00:58:38,760
Speaker 2: the environment that you're working in. Right. There are some

1212
00:58:38,920 --> 00:58:42,520
Speaker 2: work environments that are just casual, and then there are

1213
00:58:42,560 --> 00:58:44,280
Speaker 2: some that are not as much. So, if you work

1214
00:58:44,320 --> 00:58:47,920
Speaker 2: in a really corporate space, I can imagine that you

1215
00:58:48,040 --> 00:58:50,280
Speaker 2: have to get more dressed up. If you don't, then

1216
00:58:50,440 --> 00:58:55,840
Speaker 2: you don't. It's more like work casual. Right. Yeah, I

1217
00:58:55,920 --> 00:58:59,240
Speaker 2: also think, and I'm going to try and work this out,

1218
00:58:59,240 --> 00:59:01,800
Speaker 2: because I've talked about this with some friends, is that

1219
00:59:02,800 --> 00:59:08,040
Speaker 2: I find that as somebody who's an older person in

1220
00:59:08,080 --> 00:59:11,760
Speaker 2: the workplace and I look at my much younger colleagues

1221
00:59:13,200 --> 00:59:16,920
Speaker 2: and they are not dressed up right. They there were like,

1222
00:59:16,960 --> 00:59:19,120
Speaker 2: it's it's not that they look bad. They don't look bad.

1223
00:59:19,600 --> 00:59:21,400
Speaker 1: My t shirt that says Daddy's little.

1224
00:59:21,160 --> 00:59:25,000
Speaker 2: Meatball, right, yeah, it's so, it's and I think that

1225
00:59:25,320 --> 00:59:30,680
Speaker 2: I have been trained to look a certain way when

1226
00:59:30,720 --> 00:59:33,200
Speaker 2: I get to work, right, and it's and it's not

1227
00:59:33,400 --> 00:59:35,880
Speaker 2: good or bad, it's just but it is something that

1228
00:59:35,920 --> 00:59:39,440
Speaker 2: I've noticed, like I would never leave the house if

1229
00:59:39,440 --> 00:59:42,320
Speaker 2: my stuff wasn't ironed right, that's just right, ye. And

1230
00:59:42,360 --> 00:59:44,560
Speaker 2: I find that And this is something that I talked

1231
00:59:44,600 --> 00:59:46,640
Speaker 2: to with KP about all the time. I'm like, what

1232
00:59:46,640 --> 00:59:47,080
Speaker 2: are you doing?

1233
00:59:47,200 --> 00:59:48,960
Speaker 1: My mom taught me how to iron, Like I had

1234
00:59:49,000 --> 00:59:50,880
Speaker 1: to iron my shirts for when I was a waiter

1235
00:59:52,280 --> 00:59:55,360
Speaker 1: for the legal profession. When we were in law school,

1236
00:59:55,560 --> 00:59:58,200
Speaker 1: women had to wear tights if they were going and

1237
00:59:58,240 --> 01:00:00,920
Speaker 1: they had like a meeting with all of us because

1238
01:00:00,920 --> 01:00:03,960
Speaker 1: the legal profession is still very conservative. Like when I

1239
01:00:04,040 --> 01:00:08,360
Speaker 1: was working for judges, internships, clerkships, whatever, you were not

1240
01:00:08,440 --> 01:00:10,480
Speaker 1: allowed to step foot in the courtroom if you were

1241
01:00:10,480 --> 01:00:12,840
Speaker 1: not wearing a tie in jacket. And that is still

1242
01:00:12,880 --> 01:00:16,480
Speaker 1: true today. I bring ties and jackets for clients if

1243
01:00:16,520 --> 01:00:18,880
Speaker 1: they don't have them. I don't think I've ever seen

1244
01:00:18,920 --> 01:00:21,520
Speaker 1: a lawyer not in a tie in jacket in a courtroom,

1245
01:00:21,600 --> 01:00:24,320
Speaker 1: and it's almost like going on stage in a costume.

1246
01:00:25,040 --> 01:00:28,000
Speaker 1: So but I do remember we had like a it's

1247
01:00:28,040 --> 01:00:30,680
Speaker 1: called trial advocacy. It's basically where you learn how to

1248
01:00:30,720 --> 01:00:33,080
Speaker 1: do an opening statement in law school and you're all

1249
01:00:33,080 --> 01:00:38,480
Speaker 1: like practicing, and this like very southern Louisiana attorney. She

1250
01:00:38,560 --> 01:00:42,840
Speaker 1: came and was an older woman, and she basically explained

1251
01:00:42,880 --> 01:00:46,400
Speaker 1: to the whole class, ladies, you have to wear tights.

1252
01:00:46,440 --> 01:00:48,880
Speaker 1: You cannot wear a skirt or a dress, doesn't matter

1253
01:00:48,920 --> 01:00:51,920
Speaker 1: how long it is, you must wear tights and heels.

1254
01:00:52,680 --> 01:00:56,240
Speaker 1: So I do think that there is a very conservative

1255
01:00:56,320 --> 01:00:59,880
Speaker 1: wardrobe that lawyers are wearing a because of the profession.

1256
01:01:00,320 --> 01:01:03,880
Speaker 1: Be we're trying to look neutral to a jury. Like

1257
01:01:04,040 --> 01:01:07,080
Speaker 1: I'm not wearing anything crazy. I'm just trying to dress

1258
01:01:07,200 --> 01:01:11,040
Speaker 1: nice and proper in court because for me, I'm like,

1259
01:01:11,120 --> 01:01:13,920
Speaker 1: this trial is not about me and my wardrobe. It's

1260
01:01:13,920 --> 01:01:17,479
Speaker 1: about just looking presentable. Like, I don't think I would

1261
01:01:17,480 --> 01:01:20,120
Speaker 1: wear this tie to court, Okay, I would wear like

1262
01:01:20,120 --> 01:01:23,040
Speaker 1: a navy suit. It was a really important here navy suit,

1263
01:01:23,280 --> 01:01:24,160
Speaker 1: more neutral tie.

1264
01:01:24,280 --> 01:01:27,440
Speaker 2: Okay, Because I've seen you, yeah, go to court, come

1265
01:01:27,480 --> 01:01:29,360
Speaker 2: back from court, and I've seen what you're wearing, and

1266
01:01:29,400 --> 01:01:34,720
Speaker 2: you always look great. But I wonder what do you

1267
01:01:34,840 --> 01:01:38,120
Speaker 2: think the judges might think of the cut of the suit,

1268
01:01:38,200 --> 01:01:41,000
Speaker 2: because the cut of your suit's take like a little bit. Yeah,

1269
01:01:41,000 --> 01:01:45,680
Speaker 2: they're like not bagging right, and traditionally it's because it's

1270
01:01:45,720 --> 01:01:47,680
Speaker 2: like a traditional see, yeah.

1271
01:01:47,520 --> 01:01:49,280
Speaker 1: There are different kinds of cuts. I wear like a

1272
01:01:49,320 --> 01:01:50,280
Speaker 1: soho fit.

1273
01:01:51,160 --> 01:01:54,120
Speaker 2: Yeah, So do you think that that has an impact

1274
01:01:54,920 --> 01:01:56,520
Speaker 2: that people are looking at you and their disay.

1275
01:01:56,520 --> 01:01:59,040
Speaker 1: They've never gotten any like feedback on But I think

1276
01:01:59,080 --> 01:02:01,640
Speaker 1: as long as your dressed like presentable for court is

1277
01:02:01,720 --> 01:02:03,760
Speaker 1: usually what I start it going for.

1278
01:02:04,400 --> 01:02:08,160
Speaker 2: So to go back to what this person asked us,

1279
01:02:09,600 --> 01:02:15,680
Speaker 2: what do we think that courts might think about flat shoes?

1280
01:02:17,520 --> 01:02:19,920
Speaker 2: Flat shoes? And I also wonder what they would think

1281
01:02:19,960 --> 01:02:24,360
Speaker 2: about ultra high shoes like the super sexy stilettos, right,

1282
01:02:24,480 --> 01:02:28,080
Speaker 2: like is that fowned upon? Also, I don't know these

1283
01:02:28,120 --> 01:02:30,720
Speaker 2: are limitations that are placed on what right these are

1284
01:02:30,800 --> 01:02:32,160
Speaker 2: limitations that are placed on women.

1285
01:02:32,240 --> 01:02:34,640
Speaker 1: There's an episode of Good Fight, Good Wife episode of

1286
01:02:34,680 --> 01:02:37,560
Speaker 1: the Good Wife where Alicia was wearing a pants suit

1287
01:02:37,800 --> 01:02:40,240
Speaker 1: not a skirt suit, and a judge said something to her.

1288
01:02:41,080 --> 01:02:45,760
Speaker 1: So I do think there are like instances where judges like,

1289
01:02:45,840 --> 01:02:48,080
Speaker 1: I can't imagine that was like just for TV. I'm

1290
01:02:48,080 --> 01:02:49,760
Speaker 1: sure that's happened in real life.

1291
01:02:49,600 --> 01:02:54,040
Speaker 2: When you are in court and you are and there's

1292
01:02:54,080 --> 01:02:57,960
Speaker 2: an attorney who's a woman suit and heels. Is it

1293
01:02:58,000 --> 01:03:00,280
Speaker 2: a dress suit or is it pants suit?

1294
01:03:00,680 --> 01:03:01,240
Speaker 1: Dress?

1295
01:03:01,280 --> 01:03:01,840
Speaker 2: Always?

1296
01:03:02,360 --> 01:03:05,640
Speaker 1: Oh, I'm like really focused not on outfits.

1297
01:03:05,800 --> 01:03:07,760
Speaker 2: I understand. No, I understanding.

1298
01:03:07,880 --> 01:03:10,920
Speaker 1: I would say for the most part, yes, okay, I

1299
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Speaker 1: don't recall a pants suit.

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Speaker 2: I'm going to ask because I have some women in

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Speaker 2: my life. Yeah, our attorneys and I will ask Jim,

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Speaker 2: let's ask. Let's circle back. It's interesting question. Actually, right,

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Speaker 2: these are things because there could be a multitude of

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Speaker 2: reasons why you prefer to wear flats.

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Speaker 1: Now I'm going to get in my head because I

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Speaker 1: have a trial this week. Now, I'm like, what the

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Speaker 1: hell am I gonna wear? This is pref recess. Thank

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Speaker 1: you for watching. I'll see you in court, not me.

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Speaker 1: This has been an Exactly Right production recorded at iHeart Studios,

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Speaker 1: posted by me, Michael Foote.

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Speaker 2: And me Melissa Malbranch. Our producer is CJ. Ferroni.

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Speaker 1: This episode was edited by Nicholas Galucci.

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Speaker 2: Our associate producer is Christina Chamberlain and our guest booker

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Speaker 2: is Patria Cottner.

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Speaker 1: Our theme song was composed by Tom Brye Vocal with

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Speaker 1: artwork from Charlotte Delarue and a Lilac, with photography by

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Speaker 1: Brad Obono.

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Speaker 2: Brief Recess is executive produced by Karen Kilgareff, Georgia hart Stark,

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Speaker 2: and Danielle Kramer.

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Speaker 1: You can find me on Instagram at Department of Redundancy

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01:04:10,200 --> 01:04:12,920
Speaker 1: Department or on TikTok at Michael foot.

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01:04:12,760 --> 01:04:15,640
Speaker 2: And I'm on both Instagram and TikTok as Melissa Malbranch.

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Speaker 1: Got legal questions, reach out at Brief Recess at exactlyrightmedia

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Speaker 1: dot com. Listen to Brief Recess on the iHeartRadio app,

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01:04:23,240 --> 01:04:26,280
Speaker 1: Apple Podcasts or wherever you get your podcasts, and of

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01:04:26,360 --> 01:04:29,280
Speaker 1: course we're a podcast with video. Search for Brief Recess

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Speaker 1: on YouTube