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Speaker 1: I think I'm most disappointed in Elon. I think divorce

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Speaker 1: is an option when your spouse wants to kill you. Yeah.

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Speaker 1: I was offered forty million dollars which included an NDA

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Speaker 1: and non discouragement into eternity, which I declined.

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Speaker 2: So, if you've ever wondered about the inner workings of

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Speaker 2: the Mega movement, what actually happens on the group chats?

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Speaker 2: Who's on the group chats? How coordinated is the Mega

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Speaker 2: Movement coming out of the White House, in the political

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Speaker 2: operation to influencers, to right wing media. While I've got

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Speaker 2: the perfect guest for you, Ashley Saint Clair. She spent

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Speaker 2: post to a decade in this movement and now she

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Speaker 2: is speaking out against the thing that she works so

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Speaker 2: hard to advance. This is Gavin.

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Speaker 1: Newsom and this is Ashley Saint Clair. Thanks for having me, guvnor.

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Speaker 2: So, Ashley, it's so interesting. Just a lot of clips

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Speaker 2: out there about you, a lot of energy of you know,

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Speaker 2: a lot of conversations and uh, and it's in you know,

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Speaker 2: not I think a lot of you know, feigning praise,

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Speaker 2: not criticism necessarily, but but you're playing to an audience, right,

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Speaker 2: You're sort of emerging out of this MAGA sort of

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Speaker 2: you know, influence space, this surround sound that a lot

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Speaker 2: of us are on the receiving end of, including myself.

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Speaker 2: So I have some intimate appreciation, uh for what they produce,

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Speaker 2: but I have little knowledge for how they produce it.

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Speaker 2: And so I'm fascinated by this opportunity. I'm very grateful

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Speaker 2: for you be willing to share just your insights without

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Speaker 2: you know, and I'm not looking to tear anybody down,

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Speaker 2: but just to understand the ecosystem that you came out

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Speaker 2: of and why you're coming out of that ecosystem and

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Speaker 2: what all of this represents to you. So maybe the

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Speaker 2: best way to start is really for you to introduce

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Speaker 2: yourself in the context of this journey to our audience.

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Speaker 1: I have to preface this too by saying apologies, because

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Speaker 1: I am almost positive I have probably cyberbullied you in

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Speaker 1: my MAGAAE because it's like a prerequisite to being in MAGA,

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Speaker 1: because you're a very popular figure for us to cyberbully.

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Speaker 1: But I got my start very young as soon as

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Speaker 1: I when I started college. Right before I started college,

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Speaker 1: there was a Trump rally on my campus, so I

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Speaker 1: was immediately going to that and seeing this energy around it.

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Speaker 1: And then I joined college. I had a bit more

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Speaker 1: of a cerebral side because I was homeschooled in high school,

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Speaker 1: so I enjoyed the more political aspects of the Young

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Speaker 1: Americans for Liberty groups that were built on free speech

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Speaker 1: and personal liberties, and then very quickly got involved in

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Speaker 1: the Turning Point apparatus and tweeting into the ether about

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Speaker 1: these conservatisms, these magaisms, and it just snowballed from there.

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Speaker 1: All of a sudden, I'm invited to as a special

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Speaker 1: guest to my first Turning Point event. I have Charlie

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Speaker 1: Kirk saying, you know, you're doing a good job, and

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Speaker 1: I'm getting praised from downtow and as like a very broken,

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Speaker 1: insecure girl who was looking for some sort of belonging

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Speaker 1: who didn't have that in high school. That was really

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Speaker 1: attractive to me in a harmful way. And then I

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Speaker 1: just I got caught up. I made a lot of

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Speaker 1: very wrong decisions about who I surrounded myself with and

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Speaker 1: the places that I got validation from, which ended up

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Speaker 1: being MAGA and this influencer culture. And very shortly afterwards,

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Speaker 1: you're in this environment in which they tell you don't

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Speaker 1: need school you don't need college, only listen to you know, truth,

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Speaker 1: social and Twitter and all of this, and you're sequestered

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Speaker 1: from information. You're told not to trust your professors or

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Speaker 1: these points of authority. And I dropped out and just

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Speaker 1: made this my entire identity. So then it's when you leave.

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Speaker 1: I often say it's not just changing your political beliefs

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Speaker 1: and saying, oh, I'm not as fiscally conservative now, or

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Speaker 1: I'm more socially liberal. You're blowing up your entire life

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Speaker 1: because your your social community, your finances, everything is is

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Speaker 1: structured in this way. So it's indistinguishable from a cult

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Speaker 1: in that aspect.

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Speaker 2: Yeah, I mean, listening to describe it, I mean you

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Speaker 2: by definition start thinking in those terms. But let me

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Speaker 2: unpack this a little bit. I mean this notion of belonging.

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Speaker 2: I think it's fascinating in this sense of belonging, this identity.

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Speaker 2: And so you you describe a Trump rally, I mean,

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Speaker 2: was it really that moment? Was it just watching that energy,

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Speaker 2: the crowd, this community that inspired you or were you

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Speaker 2: naturally prone? Were you, you know, what was your politics

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Speaker 2: sort of leaning in that direction? Were you frustrated with

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Speaker 2: the status quo? Uh? And you you know, how did

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Speaker 2: how did how did sort of that? How did Trump

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Speaker 2: ignite in you? Or what was it that ignited?

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Speaker 1: It was more of this contrarian take. I always liked

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Speaker 1: being a contrarian. And all of the heads of the

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Speaker 1: philosophy department and I went for philosophy at that time,

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Speaker 1: had signed a petition to ban Trump from campus. And

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Speaker 1: in my head, I'm like, oh, that's antithetical to everything

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Speaker 1: philosophy is about. But in retrospect, they were right, because

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Speaker 1: this rhetoric was going down a very dangerous and violent path.

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Speaker 1: But in my head at that time as this, you know,

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Speaker 1: I hadn't quite turned eighteen yet. I went to this

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Speaker 1: rally at seventeen years old, and I turned eighteen right

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Speaker 1: before I started, and it was, you know, to me,

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Speaker 1: I'm like, wow, there's all this energy and people like

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Speaker 1: me and this is fun. And I didn't have any

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Speaker 1: of that in high school. I didn't go to prom,

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Speaker 1: I didn't do any of that. So it was this

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Speaker 1: validation very quickly that I had never really experienced before.

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Speaker 2: And were you I'm just curious, were your parents in

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Speaker 2: political were you political necessarily or just you just had

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Speaker 2: that little contrary and beat.

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Speaker 1: So we moved from South Florida, which was a lot

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Speaker 1: more diverse, and all my families from New York, from

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Speaker 1: Queens and other areas that are more diverse. But throughout

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Speaker 1: my life we also moved to very rural areas such

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Speaker 1: as Alabama and Montana, and so while I wasn't necessarily

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Speaker 1: getting very conservative viewpoints at home, I was surrounded by it.

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Speaker 1: Like in Montana, the most unique sentence ever. My only

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Speaker 1: friend there was a female Mennonite lumberjack. And so it's

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Speaker 1: like it's a town of two hundred and fifty people.

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Speaker 1: And so I wasn't really exposed to varying viewpoints outside

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Speaker 1: of the Internet.

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Speaker 2: Right, And so you're you're you have this moment they're

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Speaker 2: trying to silence Trump, You're like, this is wrong. You

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Speaker 2: you buy down. And by the way, and there's you know,

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Speaker 2: you were quick to say maybe they were right, but

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Speaker 2: maybe they weren't right. And that's a deeper conversation we

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Speaker 2: can have about this notion of free speech and sort

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Speaker 2: of the origin story of a little bit of what

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Speaker 2: you know sort of has created this movement out of

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Speaker 2: anger and frustration of quote unquote being canceled and not

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Speaker 2: having necessarily those platforms that others, frankly it oftentimes take

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Speaker 2: for granted. But I'm curious. You know, you talk about

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Speaker 2: going feeling some identity energy. You're homeschooled. Now all of

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Speaker 2: a sudden, there's a community that's trying to pull you in.

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Speaker 2: Is it just pull you in on the basis of

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Speaker 2: just the joy of being the contrary and the joy

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Speaker 2: of expressing yourself fully and the sort of diversity of

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Speaker 2: opinion was what was the thing that sort of attracted.

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Speaker 1: Sort of It's also just having friends, you know, because

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Speaker 1: when you're in such an isolated community, like in the

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Speaker 1: middle of nowhere, Montana, and then you're here and you're

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Speaker 1: being invited as a special guest to Turning Point, and

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Speaker 1: you feel like you're all of a sudden, not this

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Speaker 1: you know, little small girl. You're important and people care

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Speaker 1: what you have to say. That's really validating in a

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Speaker 1: harmful way.

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Speaker 2: And so you talk about Turning Point, I mean that

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Speaker 2: was a turning point for you. I mean, was that

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Speaker 2: organization you know, that was sort of the beginning of

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Speaker 2: the organization right when Charlie.

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Speaker 1: Was It was very early on, and it was very

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Speaker 1: campus oriented and again simultaneously, part of it coincides with

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Speaker 1: the content, right, because you're also posting online and there's

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Speaker 1: these stories going up on Fox News of professors who

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Speaker 1: say something that's a little too woke, and so you're

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Speaker 1: going to school, but you're viewing it through this content

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Speaker 1: brain of ooh, am I going to get one, ooh,

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Speaker 1: I can't trust them, and so it really bastardizes your

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Speaker 1: experience in academia because you're viewing it through this, like

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Speaker 1: Charlie Kirk turning point content brain that is really harmful.

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Speaker 2: And when you were with Charlie, I mean, did what

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Speaker 2: you know, it's interesting we started this podcast with Charlie

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Speaker 2: and you know, obviously tragic what happened to him. And

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Speaker 2: I'm interested in look forward to your thoughts about where

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Speaker 2: the movement is today. But what aspects of that movement?

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Speaker 2: What was it about Charlie in the beginning of that

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Speaker 2: movement that you really may not have identified with necessarily

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Speaker 2: on the substance, but just the style that there was

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Speaker 2: something here that he was doing that no one else

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Speaker 2: was necessarily doing. What was you know, success leaves clues

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Speaker 2: and he was successful at organizing the campus is I'm

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Speaker 2: curious what examples were cues did you see or clues

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Speaker 2: early on of this sort of genesis of success.

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Speaker 1: He articulated himself well, but also when you're capitalism brained,

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Speaker 1: you view any mode of success or ambition as a

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Speaker 1: moral good. So ambition and success was equated with morality

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Speaker 1: in my head. So I'm like, Wow, he's so young

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Speaker 1: and successful, and that could be me too. All I

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Speaker 1: need to do is drop out of school and keep

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Speaker 1: fighting the good fight. And so I think that's But

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Speaker 1: Charlie at times was also encouraging, you know, at times

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Speaker 1: when I had tough times in Republican politics, and so

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Speaker 1: he had this softer side that was captivating to people

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Speaker 1: who were going through a lot. And I don't think

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Speaker 1: he was quite aware of the way in which his

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Speaker 1: organization was and has been used by people much bigger,

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Speaker 1: with a lot more money than him, to utilize it

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Speaker 1: for their own agenda and mobilize this sort of rhetoric

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Speaker 1: across America.

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Speaker 2: So, Ashley, how old were you at the time, I

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Speaker 2: mean your young twenties this time.

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Speaker 1: Or twenty seven? Well now I'm twenty seven now I was.

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Speaker 1: This happened right away when I was eighteen going on

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Speaker 1: college campuses. I went to my first turning point event

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Speaker 1: like nineteen twenty and so it was very early on.

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Speaker 2: And so was this I mean, did this become a

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Speaker 2: profession then for you? I mean you morphed in all

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Speaker 2: of a sudden. What was the first opportunity to monetize

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Speaker 2: where you realize, wait a second, I'm getting paid for this.

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Speaker 1: So it was actually I had had like normal jobs

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Speaker 1: working in campaigns and cleaning up bad data and volunteering.

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Speaker 1: But I dated a man who was ten years my senior,

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Speaker 1: and I met him at the Young Women's Leadership Conference

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Speaker 1: and within a month of meeting him, he's like, moved

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Speaker 1: to Tampa with me. You can just do maga influencing.

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Speaker 1: He was this big influencer guy DC Dreno, and he's like,

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Speaker 1: here's how you do it. Here's the sign you hold

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Speaker 1: up outside of the iced attention set. This will go viral.

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Speaker 1: Here's the shirts you can sell, the flags you can sell.

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Speaker 1: And that's when I started learning how to monetize activism

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Speaker 1: and learn that it's it's an industry.

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Speaker 2: It's interesting, and you made the point earlier and you're

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Speaker 2: reinforcing it now. I mean the connection between the movement

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Speaker 2: and the medium, which is the media and the clips

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Speaker 2: and the virality in the ability quote unquote influence substantively

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Speaker 2: and breakthrough. And so that's interesting. So he sort of

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Speaker 2: he designed in your mind. Yeah, and so you see

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Speaker 2: you're out there and you're feeling a sense of community connection, relationships.

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Speaker 1: But also fear because what that boyfriend of mine had

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Speaker 1: drove into my head was there were a few times

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Speaker 1: I found myself in controversy for you know, stepping out

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Speaker 1: a line, for having a more reasonable take on reproductive

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Speaker 1: rights or immigration, and he drove into my head he said,

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Speaker 1: never cross the base. Never cross the base, and that's

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Speaker 1: very much prolific throughout MAGA. You're not supposed to do that.

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Speaker 1: So so while it was these good feelings, it was

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Speaker 1: also very quickly a feeling of fear of stepping out

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Speaker 1: of line and staying within the talking points. And you

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Speaker 1: know you're going to get canceled now you've dropped out

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Speaker 1: of school, you'll lose your income, you're moving to a

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Speaker 1: place far, far away from home, and so so the

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Speaker 1: fear aspect took took a fact very early on as well.

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Speaker 2: It's interesting and I want to unpack that as well. Particularly,

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Speaker 2: you know, what is the base with the basis, whatever

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Speaker 2: Trump says it is because he seems to shape shift

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Speaker 2: often on issues, and with it, the base seems to

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Speaker 2: move along with him. I guess it's just waiting for

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Speaker 2: that cue. But I'm curious, just back to your first paycheck.

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Speaker 2: Do you remember where you actually, you know, someone said

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Speaker 2: here's a thousand bucks or you know, how did it?

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Speaker 2: How was what was the what was the formal relationship

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Speaker 2: and role to someone that can write a check?

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Speaker 1: The boss believe it was just an Instagram message or

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Speaker 1: Twitter DM that was like I'll pay you to retweet

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Speaker 1: this or post this, and then I got, you know,

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Speaker 1: other ones for wearing the T shirts or the deals

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Speaker 1: for hey, make your own T shirts, antisocialist social club,

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Speaker 1: all of the I believe I also had one that

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Speaker 1: set up May California, America. Again, there were a few

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Speaker 1: of those, but it was just through dms and here's

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Speaker 1: a PayPal and I'm like, oh, look at this very quickly, you.

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Speaker 2: Know, because I've gotten to know some of these folks,

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Speaker 2: and you know, I sort of an interesting history and

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Speaker 2: relationship to a little bit of the Trump passed and

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Speaker 2: which I'm unpacked modestly here on the podcast. But I'm curious.

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Speaker 2: You know, how much of it for you was real

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Speaker 2: versus performative? How much of it was substance versus style? Meaning?

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Speaker 2: Were these true believers that you were surrounded by, or

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Speaker 2: performers that were just trying to sort of, you know,

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Speaker 2: own the Libs, own that governor in California and just

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Speaker 2: don't you know, don't California, Maya, Montana or mon Texas.

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Speaker 2: I mean, what, you know, what was it about what

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Speaker 2: we're against or but what we're for? Give me a

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Speaker 2: sense of you know, who were the early influences for you?

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Speaker 2: Was it a sense of deep sincerity conviction?

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Speaker 1: For me? It started out that way. And I think

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Speaker 1: most of these people would tell you that they are

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Speaker 1: true believers, but they're performed. They really are performers who

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Speaker 1: have gotten so deep and their views have oscillated so

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Speaker 1: much within what's acceptable within the base that they're just

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Speaker 1: deeply broken and insecure people who lack any real sense

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Speaker 1: of identity. What was fascinating is when you go to

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Speaker 1: events or you go to the bar with these people, afterwards,

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Speaker 1: they can't talk about anything else, like it's they're only

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Speaker 1: talking about do you see what Joe Biden did? Did

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Speaker 1: you see this like it's they're not their shells of

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Speaker 1: human beings who are wearing this Maga costume and it's

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Speaker 1: become their entire identity. Nobody's nobody's really talking about things,

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Speaker 1: and so I do believe that they're all performers. I

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Speaker 1: believe Maga has the deepest issues with identity that I've

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Speaker 1: ever had the displeasure of interacting with.

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Speaker 2: And again, identity on the basis of just who I

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Speaker 2: mean as individuals, yes, who that yeah, sort of, and

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Speaker 2: they're in the process of becoming and discovering who they are,

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Speaker 2: but they put this mask on.

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Speaker 1: They've never had the opportunity to become because they've been

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Speaker 1: plucked and told what to be, and so they don't

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Speaker 1: ever have that opportunity of becoming. And now with this

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Speaker 1: age of the Internet, it's very hard to have that rebirth,

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Speaker 1: to have that reinvention because you have this permanent digital

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Speaker 1: footprint of you being a racist online. So it's very

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Speaker 1: hard to have a rebirth after that. So they're kind

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Speaker 1: of stuck in that as well.

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Speaker 2: It's interesting, so is this so with your own experience

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Speaker 2: and you know a little bit of with Charlie Kirk

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Speaker 2: and turning point USA you're starting to you know, ex

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Speaker 2: boyfriend and you know, learning how to put ship post

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Speaker 2: as we say, and you know, putting on you know

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Speaker 2: literally physically, you know, showing up with signs and T shirts,

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Speaker 2: et cetera. Is it a loose confederation or has it

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Speaker 2: evolved or devolved? Is it organized? Is it you know,

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Speaker 2: is it become radically different than it was three four

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Speaker 2: years ago? Trump one point zero versus Trump two point zero.

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Speaker 2: Are there sort of central key figures that are organizing

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Speaker 2: and sharing down a vision or is it again a

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Speaker 2: bottom up but within the dear leader's frame? How would

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Speaker 2: you describe the confederation or lack thereof the brand mega.

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Speaker 1: So a lot of people will say, you know, they

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Speaker 1: were duped by Trump and it's really evolved from what

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Speaker 1: it was years ago. But what I would say to

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Speaker 1: that is it it did evolve into the form that

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Speaker 1: people warned us it was going to evolve into. Yes,

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Speaker 1: it has changed, but it changed into what I would

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Speaker 1: say now is like this final form of this or

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Speaker 1: tyrianism that we were warned that it was going to

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Speaker 1: evolve into. It was a natural evolution of the things

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Speaker 1: that were being prepped Originally. Yeah, it was more open tent,

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Speaker 1: it was a little more Okay, we don't hate trans

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Speaker 1: and gay people. Okay, we we love our token block conservatives.

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Speaker 1: And then it really once they gained more of a

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Speaker 1: foothold of power, you saw that section off. And I

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Speaker 1: do believe that was by design.

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Speaker 2: In design Where I mean, is is this Trump power? Yeah?

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Speaker 2: And the tech for power and that power lies where

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Speaker 2: is it Trump himself? Is it Junior? Is it where?

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Speaker 2: I mean? Who? You know? We can and we'll jump

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Speaker 2: into some names and James more the contemporary names and

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Speaker 2: the political operation. But early on, where did you see

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Speaker 2: the power reside?

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Speaker 1: You know, four five six years ago, four or five

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Speaker 1: six years ago, the power was really with Trump. And

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Speaker 1: I do believe that Trump as a figure was co

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Speaker 1: opted by the Stephen Millers of the world and the

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Speaker 1: people who are really financially invested and ideologically invested in

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Speaker 1: their own vision for America. And now we're seeing it

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Speaker 1: being co opted further by the tech oligarchs and all

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Speaker 1: of this. That it's the power is really consolidating among this.

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Speaker 1: I mean, you have Jeff Bezos who won't say a

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Speaker 1: bad thing about Trump now, so they're really aligning with

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Speaker 1: where they see this power Trump was years ago just

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Speaker 1: a figure that they realized we can co opt this

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Speaker 1: guy for our own agenda.

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Speaker 2: And early on who are who are those early figures

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Speaker 2: and what were what was What was the agenda when

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Speaker 2: you first started. I mean, obviously you talk about I mean,

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Speaker 2: there's issues of reproductive rights, you talk about some those

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Speaker 2: I think there's these are contrarian issues and just you know,

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Speaker 2: anti obviously the elites and you know, all those the

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Speaker 2: Biden and Harris and Obama types myself imagine California included.

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Speaker 2: But what I mean, what was the uniting construct in

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Speaker 2: the beginning of your experience with Maga.

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Speaker 1: The uniting construct was mostly these magaisms of free speech

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Speaker 1: and holding the elites accountable, But there was also, particularly

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Speaker 1: within the right wing online sphere, there was a lot

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Speaker 1: of gendered issues. It was very anti feminism. It was

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Speaker 1: the birthplace in the foundations of the Andrew Tates of

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Speaker 1: the world. And what we're seeing now that has really

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Speaker 1: evolved very anti feminism, very anti me too, like why

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Speaker 1: are you just hating on the white guy type of stuff,

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Speaker 1: and they would utilize people like me, And I remember

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Speaker 1: there was a very large MAGA figure when I first

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Speaker 1: started blowing up online who came to me and said

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Speaker 1: you should speak on this issue. I think it was

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Speaker 1: a lead of Battle Angel or whatever. They were mad

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Speaker 1: that bre Larsen had said something against white men, straight

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Speaker 1: white men, and so very early on I was co

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Speaker 1: opted to speak on these issues regarding men because it

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Speaker 1: was better for it to come from a woman like me,

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Speaker 1: and so that was very pertinent early on was.

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Speaker 2: And it's interesting you say co opted, meaning at the

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Speaker 2: time you didn't feel co opted though, right, No.

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Speaker 1: I thought they were coming to me because I was

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Speaker 1: so such a special snowflake, and so it was smart

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Speaker 1: and I was like, I've been chosen, and you know,

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Speaker 1: I called the pygmisms like I just so wanted to

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Speaker 1: be picked and heard, and so in that moment you

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Speaker 1: don't feel but in retrospect, I'm like, wow, I was

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Speaker 1: I was used by these people for something really, really

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Speaker 1: harmful that I'm scared we're not going to be able

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Speaker 1: to undo.

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Speaker 2: Did you what was it? Do you remember the post

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Speaker 2: that really where you felt like you're now deep inside this,

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Speaker 2: like now you're actually even surprised you how viral a

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Speaker 2: statement was or an issue was something that for you

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Speaker 2: became more indelible and a consciousness of how powerful this

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Speaker 2: movement is and how powerful even your voice would become.

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Speaker 1: So for a while, I was like mostly a ship poster.

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Speaker 1: I would pretend to be serious at times, but it

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Speaker 1: wasn't really until I was with Elon that I would

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Speaker 1: see some of these effects of my words or effects

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Speaker 1: of Elon himself, that I'm like, this is actually really consequential.

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Speaker 1: And it sounds not even stupid to say, oh, you

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Speaker 1: didn't realize till then that your actions had so many consequences.

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Speaker 1: And that's something that I've really had to unpack and

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Speaker 1: unpack the harm that I did for nearly a decade

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Speaker 1: in this movement, saying things in the communities that I

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Speaker 1: hurt women, minorities, the trans community. I just didn't even consider.

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Speaker 1: I was completely unempathetic to how my words and actions

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Speaker 1: impacted other people. And I've had to do a lot

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Speaker 1: of work making amends for that and really saying, hey,

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Speaker 1: here's where I went wrong, here's where I was lacking,

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Speaker 1: and trying to understand why I made those decisions.

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Speaker 2: So it's interesting in it, and I don't want to

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Speaker 2: over index our time on Elon, but as someone that

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Speaker 2: knew Elon, you know, back in the day, and seeing

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Speaker 2: him radically change from the person I remember back in

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Speaker 2: early two thousands, particularly politically.

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Speaker 1: Yeah, I would say he probably didn't change. People just

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Speaker 1: weren't listening to the stories, particularly of women that he

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Speaker 1: was involved with, because when you do read the words

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Speaker 1: that his first wife, Justine wrote, it was always there.

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Speaker 1: We just ignored it.

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Speaker 2: Yeah, No, well I appreciate that. But he came into

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Speaker 2: the movement it seems a little later, obviously. I mean,

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Speaker 2: he wasn't necessarily part of Team Trump and MAGA as

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Speaker 2: it's described, despite some of those political leanings as you suggest,

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Speaker 2: and those values what you know, you describe what a DM.

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Speaker 2: That's how he reached out to you, just because he

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Speaker 2: was impressed with some of the stuff you were posting.

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Speaker 1: Yeah. I was at the Babylon b which he had

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Speaker 1: in affinity for at that time, and he ended up

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Speaker 1: dming me and then we met at Twitter headquarters what

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Speaker 1: have you. But even in his private conversations with me,

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Speaker 1: that's another instance of co opting. I really do believe

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Speaker 1: that he finds these populist movements, whether in the United

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Speaker 1: States or the UK or Germany, and he realizes that

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Speaker 1: They're very easy to co opt and manipulate for his

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Speaker 1: own agenda of basically digitizing these governments and getting an

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Speaker 1: insurmountable amount of data. And you know, that's one conversation

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Speaker 1: I did want to have with you and just ask

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Speaker 1: you because California was kind of at the forefront of

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Speaker 1: this and allowed for a lot of these Silicon Valley

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Speaker 1: and these tech companies to fester under California. And I

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Speaker 1: guess the question I have for you is, like, Silicon

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Speaker 1: Valley didn't just build software, It's built something that are

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Speaker 1: the civilizational scale experiment that is unreasonably safe. And so why,

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Speaker 1: at least in California was innovation considered like this sufficient

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Speaker 1: excuse and capitalism considered this sufficient excuse and justification to

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Speaker 1: expose the public to such risk. And the most important

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Speaker 1: question I have for you is did California become so

432
00:24:21,840 --> 00:24:26,560
Speaker 1: economically dependent on Silicon Valley that it lost the ability

433
00:24:26,600 --> 00:24:31,080
Speaker 1: to act as an independent watchdog for these organizations? And

434
00:24:31,119 --> 00:24:34,359
Speaker 1: why was so much of this allowed to be built?

435
00:24:34,440 --> 00:24:36,320
Speaker 1: And are there any regrets that you have?

436
00:24:36,960 --> 00:24:39,080
Speaker 2: Yeah, no, Look, I think it's a fair question, but

437
00:24:39,320 --> 00:24:43,800
Speaker 2: I think it lacks any context. California is the dominant

438
00:24:43,880 --> 00:24:49,520
Speaker 2: leader in privacy, dominant leader in regulation large leguage relates

439
00:24:49,560 --> 00:24:52,400
Speaker 2: to AI, we led the nation the first safety measures

440
00:24:52,400 --> 00:24:55,119
Speaker 2: for a large language models, frontier models. We created a

441
00:24:55,160 --> 00:25:00,560
Speaker 2: Privacy Council six seven years ago, statewide council that focused

442
00:25:00,560 --> 00:25:04,520
Speaker 2: on data privacy, first first state to advance. In fact,

443
00:25:04,640 --> 00:25:08,320
Speaker 2: Connecticut just backed into a similar framework that California laid

444
00:25:08,320 --> 00:25:10,800
Speaker 2: out as relates to the Delete Act, which California did

445
00:25:10,800 --> 00:25:13,919
Speaker 2: as relates to our own data and having control over it.

446
00:25:13,960 --> 00:25:17,000
Speaker 2: We led the nation as it relates to child protections,

447
00:25:17,000 --> 00:25:19,679
Speaker 2: but we were sued by these same companies. We're in

448
00:25:19,680 --> 00:25:23,760
Speaker 2: litigation and half dozen lawsuits, but we've led the nation

449
00:25:23,920 --> 00:25:25,440
Speaker 2: in every one of these categories.

450
00:25:26,040 --> 00:25:28,439
Speaker 1: Good you guys have and you've done great work in

451
00:25:28,520 --> 00:25:33,520
Speaker 1: terms of passing laws that help victims seek justice after

452
00:25:33,560 --> 00:25:37,359
Speaker 1: the harm occurs. But I guess what gets me is

453
00:25:38,800 --> 00:25:41,320
Speaker 1: there was also a lot of conditions that were able

454
00:25:41,359 --> 00:25:46,680
Speaker 1: to be created before the harm was done. And how

455
00:25:47,000 --> 00:25:49,479
Speaker 1: do we intervene before the harm is done? Instead of

456
00:25:49,920 --> 00:25:52,719
Speaker 1: placing this burden on victims now to prove the harm

457
00:25:52,880 --> 00:25:57,920
Speaker 1: after these products are deployed, instead of telling these companies

458
00:25:57,960 --> 00:26:01,040
Speaker 1: to stop and placing a really hard stop on these

459
00:26:01,040 --> 00:26:04,120
Speaker 1: technology companies before they prove safety.

460
00:26:04,680 --> 00:26:06,399
Speaker 2: Yeah, and I'm.

461
00:26:06,240 --> 00:26:08,000
Speaker 1: Seeing that in the EU too. You know, I have

462
00:26:08,119 --> 00:26:11,720
Speaker 1: these conversations internationally about the harm and it's like, why

463
00:26:11,720 --> 00:26:14,919
Speaker 1: don't we just turn the spigot off? Like is it

464
00:26:15,000 --> 00:26:17,720
Speaker 1: because they're so powerful? Is it because they have so

465
00:26:17,840 --> 00:26:20,639
Speaker 1: much force behind them? Like? Why can't we turn the

466
00:26:20,680 --> 00:26:23,639
Speaker 1: spigot off until they prove that it's reasonably safe, just

467
00:26:23,680 --> 00:26:27,239
Speaker 1: like any other company, Like if a pharmaceutical company has

468
00:26:27,280 --> 00:26:28,879
Speaker 1: a drug, we make sure it's safe first.

469
00:26:29,600 --> 00:26:33,720
Speaker 2: There's no there's no question that the collective we and

470
00:26:33,840 --> 00:26:36,720
Speaker 2: this well before I was even governor. As it relates

471
00:26:36,720 --> 00:26:39,720
Speaker 2: to social media in its arms, we failed on that.

472
00:26:39,800 --> 00:26:42,159
Speaker 2: I had Tristan harris On and others that have been

473
00:26:42,200 --> 00:26:44,919
Speaker 2: real leaders in this calling this out. We've talked a

474
00:26:44,960 --> 00:26:48,280
Speaker 2: lot about it extensively, not only on this platform but

475
00:26:48,720 --> 00:26:52,119
Speaker 2: substantively in terms of our legislative efforts in the state

476
00:26:52,400 --> 00:26:55,159
Speaker 2: to not make the same mistakes with AI. And so

477
00:26:55,240 --> 00:26:59,000
Speaker 2: what you just described are the lessons that we've learned

478
00:26:59,359 --> 00:27:03,360
Speaker 2: as it relates to adopting safety measures and transparency measures

479
00:27:03,520 --> 00:27:06,440
Speaker 2: as it relates to AI. In what's happening in terms

480
00:27:06,480 --> 00:27:08,760
Speaker 2: of how all this is going to be supercharged as

481
00:27:08,760 --> 00:27:11,879
Speaker 2: it relates to deep fakes, as it relates to privacy,

482
00:27:12,119 --> 00:27:14,960
Speaker 2: as it relates to child protection. You're talking to. Governor

483
00:27:14,960 --> 00:27:16,600
Speaker 2: has more receipts than any other governor in the United

484
00:27:16,640 --> 00:27:19,040
Speaker 2: States of America. We've done more than anyone else. Is

485
00:27:19,080 --> 00:27:21,000
Speaker 2: it good enough? No, That's why this year we're going

486
00:27:21,080 --> 00:27:23,600
Speaker 2: to ban social media for everyone under sixteen. Will be

487
00:27:23,640 --> 00:27:26,280
Speaker 2: the first large scale a jurisdiction to do that again

488
00:27:26,359 --> 00:27:29,160
Speaker 2: in the home state of this and we imagine that's

489
00:27:29,160 --> 00:27:32,520
Speaker 2: going to happen all across the United States because California moves,

490
00:27:32,600 --> 00:27:34,879
Speaker 2: we tend to see movement all across the country. So

491
00:27:35,440 --> 00:27:39,840
Speaker 2: not perfect, but no one, but best in class.

492
00:27:39,320 --> 00:27:42,680
Speaker 1: Biorelatively, California is one of the only states doing it.

493
00:27:42,760 --> 00:27:45,560
Speaker 1: And California is in such a weird position because while

494
00:27:45,560 --> 00:27:49,680
Speaker 1: they're one of the only states doing this legislation, there's

495
00:27:49,680 --> 00:27:53,320
Speaker 1: also been so much festering within California that it's been

496
00:27:53,359 --> 00:27:55,879
Speaker 1: built here, and so what is the answer to that.

497
00:27:56,640 --> 00:27:58,720
Speaker 2: It's interesting just you know, back to Elon, I mean,

498
00:27:58,720 --> 00:28:02,320
Speaker 2: we've been battling battling on these issues around deep fakes,

499
00:28:02,600 --> 00:28:05,520
Speaker 2: around election you know, just the integrity of our elections,

500
00:28:06,440 --> 00:28:08,919
Speaker 2: and you know, you can look at his you know,

501
00:28:09,080 --> 00:28:12,560
Speaker 2: just the sewage of tweets that he's put out condemning our,

502
00:28:12,640 --> 00:28:15,119
Speaker 2: our leadership, and that including by the way, where you

503
00:28:15,160 --> 00:28:17,760
Speaker 2: and I are aligned as it relates to what happened

504
00:28:17,760 --> 00:28:20,399
Speaker 2: to you and the litigation. And I appreciate your in

505
00:28:20,480 --> 00:28:24,600
Speaker 2: litigation against x Ai, but but you may have seen

506
00:28:25,359 --> 00:28:28,919
Speaker 2: what was happening to you and others. California led and

507
00:28:28,960 --> 00:28:32,359
Speaker 2: I directed our ag our attorney general to go after

508
00:28:32,840 --> 00:28:34,800
Speaker 2: groc and they actually stood down. I think it was

509
00:28:34,840 --> 00:28:39,400
Speaker 2: a combination of your lawsuit UH and our investigation UH.

510
00:28:39,440 --> 00:28:41,800
Speaker 2: And I think it was within a few hours after

511
00:28:41,840 --> 00:28:44,800
Speaker 2: we posted that we're doing the investigation, and after a

512
00:28:44,880 --> 00:28:48,600
Speaker 2: few days of what you did that, Elon finally acted

513
00:28:48,640 --> 00:28:54,240
Speaker 2: like you know that. So now look, I think you're right,

514
00:28:54,600 --> 00:28:56,680
Speaker 2: but but I also think mean in terms of just

515
00:28:56,800 --> 00:29:01,160
Speaker 2: the larger meta frame. But but California as a specific

516
00:29:01,200 --> 00:29:05,720
Speaker 2: example has a lot of credibility at least in trying

517
00:29:05,760 --> 00:29:09,360
Speaker 2: to balance those things as it relates to the influence. Uh,

518
00:29:09,400 --> 00:29:11,440
Speaker 2: the influence is usually on the back end. Ashley. It's

519
00:29:11,480 --> 00:29:15,880
Speaker 2: interesting we're passing these laws, I'm signing these laws, but

520
00:29:15,960 --> 00:29:19,680
Speaker 2: they're litigating and what they're using is the courts now

521
00:29:20,360 --> 00:29:24,320
Speaker 2: to slow down the progress. And it's interesting where they

522
00:29:24,320 --> 00:29:28,240
Speaker 2: don't have the throw with the legislature or maybe the governor.

523
00:29:28,240 --> 00:29:30,520
Speaker 2: We'll see what happens to the next governor. Uh, they're

524
00:29:30,640 --> 00:29:36,680
Speaker 2: counting on the slow system of adjudication with a third

525
00:29:36,720 --> 00:29:40,280
Speaker 2: branch and yeah, and time is uh, that's you know,

526
00:29:40,400 --> 00:29:41,120
Speaker 2: that's their ally.

527
00:29:41,880 --> 00:29:45,520
Speaker 1: Yes, especially through I mean they're the way in which

528
00:29:45,520 --> 00:29:48,040
Speaker 1: they've co opted the judicial system to just tie all

529
00:29:48,080 --> 00:29:51,040
Speaker 1: of this up. How do we fix that? I guess

530
00:29:51,040 --> 00:29:54,000
Speaker 1: you're a better person, Well, how do we fix that?

531
00:29:54,040 --> 00:29:56,160
Speaker 2: How do we get win?

532
00:29:56,520 --> 00:29:57,040
Speaker 1: Stop that?

533
00:29:57,280 --> 00:29:59,560
Speaker 2: You've got to be ruthless and winning. You can't be

534
00:29:59,640 --> 00:30:01,680
Speaker 2: winning arguments. You got to win power. You got to

535
00:30:01,680 --> 00:30:03,400
Speaker 2: get power back. You got to take back the United

536
00:30:03,440 --> 00:30:06,120
Speaker 2: States Senate, not just the House of Representatives, so you

537
00:30:06,120 --> 00:30:08,760
Speaker 2: have oversight in these federal appointees. We've got to take

538
00:30:08,800 --> 00:30:11,480
Speaker 2: back state houses so that we have governors that are

539
00:30:11,480 --> 00:30:15,400
Speaker 2: appointing judges at the state level, particularly in states like California,

540
00:30:15,440 --> 00:30:18,680
Speaker 2: that I have outsized role in regulation that reflect the

541
00:30:19,280 --> 00:30:22,240
Speaker 2: broader values that I think you and I share in

542
00:30:22,280 --> 00:30:22,880
Speaker 2: this respect.

543
00:30:22,920 --> 00:30:26,320
Speaker 1: So I love that approach too, especially you know if

544
00:30:26,360 --> 00:30:28,680
Speaker 1: we take it back to the beginning of the conversation too,

545
00:30:28,800 --> 00:30:33,680
Speaker 1: with the philosophy professors signing that petition to ban Trump right,

546
00:30:33,760 --> 00:30:36,920
Speaker 1: and whether or not that's that's too hard. I think

547
00:30:37,880 --> 00:30:40,200
Speaker 1: right now we're at a point where we can't ask

548
00:30:40,280 --> 00:30:42,600
Speaker 1: if it's if it's too much, or if we need

549
00:30:42,640 --> 00:30:48,440
Speaker 1: to be centrist or moderate, because they're not, as you're aware,

550
00:30:48,520 --> 00:30:52,880
Speaker 1: they're fighting very hard and very dirty, to a point

551
00:30:52,880 --> 00:30:54,400
Speaker 1: that I don't know that we're going to be able

552
00:30:54,400 --> 00:30:58,680
Speaker 1: to take that back. And so I hope that nobody

553
00:30:58,680 --> 00:31:03,520
Speaker 1: gets stuck within this point of like oscillating between playcating

554
00:31:03,560 --> 00:31:06,840
Speaker 1: both sides and just sticking to the gutting instinct of

555
00:31:07,240 --> 00:31:09,320
Speaker 1: what is right? Is this wrong? And if it is,

556
00:31:09,400 --> 00:31:11,920
Speaker 1: we need to fight back with every force that we

557
00:31:12,000 --> 00:31:15,120
Speaker 1: have instead of placating people who have who have been

558
00:31:15,120 --> 00:31:16,479
Speaker 1: a part of a lot of harm.

559
00:31:17,120 --> 00:31:20,680
Speaker 2: I tend to agree with you, and we manifested, quite

560
00:31:20,720 --> 00:31:25,560
Speaker 2: literally a frame that I think is appropriate to reference Prop.

561
00:31:25,600 --> 00:31:29,400
Speaker 2: Fifty fighting fire with fire. We did redistricting, you know,

562
00:31:29,440 --> 00:31:32,719
Speaker 2: and I agree with you our way back into powers

563
00:31:32,760 --> 00:31:35,920
Speaker 2: through the fight, not necessarily through the center. But that said,

564
00:31:36,800 --> 00:31:38,840
Speaker 2: you know, I also think and the reason I started

565
00:31:38,840 --> 00:31:41,480
Speaker 2: this podcast with guys like Bannon and Kirk and people

566
00:31:41,520 --> 00:31:44,040
Speaker 2: I deeply disagree with, and you know, having people on

567
00:31:44,080 --> 00:31:46,200
Speaker 2: there that have been attacking me and doing everything to

568
00:31:46,240 --> 00:31:50,040
Speaker 2: take me down, not professionally but personally. But I you know,

569
00:31:50,040 --> 00:31:52,640
Speaker 2: I still believe divorce is not an option. That's the

570
00:31:52,680 --> 00:31:55,040
Speaker 2: framework of this podcast. That we have to live together

571
00:31:55,360 --> 00:31:58,440
Speaker 2: and advance together across our differences. And you know that's

572
00:31:58,560 --> 00:32:00,480
Speaker 2: you know, back to sort of my comment. It's about

573
00:32:00,840 --> 00:32:03,080
Speaker 2: you know, Trump, but you know I'll still talk to

574
00:32:03,160 --> 00:32:05,680
Speaker 2: him open hand, not a closed fist. At the same time,

575
00:32:06,120 --> 00:32:08,840
Speaker 2: you know, we'll do Prop fifty of you know, we've

576
00:32:08,840 --> 00:32:12,400
Speaker 2: had sixty three or four lawsuits against Trump. We're going

577
00:32:12,480 --> 00:32:16,360
Speaker 2: to go hard back in terms of love that of

578
00:32:16,400 --> 00:32:20,080
Speaker 2: you know, pushing back against you know, all this bes.

579
00:32:20,400 --> 00:32:22,560
Speaker 1: Though I would disagree. I think divorce is an option

580
00:32:22,600 --> 00:32:26,440
Speaker 1: when your spouse wants to kill you. I think that's

581
00:32:26,440 --> 00:32:27,720
Speaker 1: what That's absolutely not.

582
00:32:29,040 --> 00:32:31,360
Speaker 2: Yeah, well, you know, and I just so that's why

583
00:32:31,360 --> 00:32:33,000
Speaker 2: I want to unpack with you a little bit more,

584
00:32:33,040 --> 00:32:36,360
Speaker 2: because I just you know, everyone wants to be loved,

585
00:32:36,440 --> 00:32:38,239
Speaker 2: Everyone needs to be loved. We all want to be

586
00:32:38,440 --> 00:32:41,840
Speaker 2: you know, the old frame protected, connected, respected, and we

587
00:32:41,960 --> 00:32:43,800
Speaker 2: want to be respect No one wants to be talked

588
00:32:43,800 --> 00:32:45,360
Speaker 2: down to a past too. We want to be part

589
00:32:45,360 --> 00:32:48,600
Speaker 2: of something bigger than ourselves. And and so you know this,

590
00:32:49,080 --> 00:32:51,200
Speaker 2: I think all that matters, that sense of belonging, and

591
00:32:51,240 --> 00:32:53,640
Speaker 2: I get that at a Trump rally, people feel connected

592
00:32:53,640 --> 00:32:55,880
Speaker 2: to something bigger than themselves. You talk in terms of

593
00:32:55,920 --> 00:32:59,200
Speaker 2: relationships and friends. You know that relationship you know with

594
00:32:59,280 --> 00:33:03,520
Speaker 2: Elon led to a beautiful child. It's and that's life

595
00:33:03,920 --> 00:33:06,200
Speaker 2: and we all live it. And I don't want to

596
00:33:06,240 --> 00:33:09,000
Speaker 2: go that we breathe the same air. Nonsense, except we do,

597
00:33:09,400 --> 00:33:10,640
Speaker 2: and so well, some.

598
00:33:10,520 --> 00:33:13,600
Speaker 1: People breathe air that is polluted by data centers, you know,

599
00:33:14,960 --> 00:33:18,440
Speaker 1: So we don't breed the same air. Actually, some people's

600
00:33:18,480 --> 00:33:20,560
Speaker 1: air is being polluted by Mega corporation.

601
00:33:21,440 --> 00:33:23,040
Speaker 2: I get it, and we got to call that out.

602
00:33:23,040 --> 00:33:26,280
Speaker 2: You're talking to the fiercest environmentalists in the country right here.

603
00:33:27,040 --> 00:33:30,400
Speaker 2: Despite the fact that I believe in a transition that works,

604
00:33:30,440 --> 00:33:33,840
Speaker 2: we're getting That's another subject, about the fact that I

605
00:33:33,920 --> 00:33:35,800
Speaker 2: drove here today and so yes, I went to the

606
00:33:35,800 --> 00:33:39,440
Speaker 2: gas station. Forgive me. So I'm hardly a purist, and sometimes.

607
00:33:39,000 --> 00:33:43,480
Speaker 1: I probably feel a little more cynical than some about

608
00:33:43,560 --> 00:33:47,400
Speaker 1: MAGA but it's because I saw them when they were alone.

609
00:33:47,440 --> 00:33:49,680
Speaker 1: I saw them when they were drunk. I saw the

610
00:33:49,680 --> 00:33:54,800
Speaker 1: things that they did and they said. And I don't

611
00:33:54,960 --> 00:33:58,720
Speaker 1: think a lot of these people, particularly in power, are

612
00:33:58,800 --> 00:34:01,800
Speaker 1: interested in some unif fight front. I don't. And we

613
00:34:02,200 --> 00:34:05,960
Speaker 1: have to consider if you're letting the barbarians into the.

614
00:34:05,920 --> 00:34:10,520
Speaker 2: Gate and let me into the gate. I had zero followers.

615
00:34:10,560 --> 00:34:13,960
Speaker 2: Actually you can appreciate this as an influencer. I had

616
00:34:14,200 --> 00:34:19,080
Speaker 2: zero when I when Charlie platformed me, when Ben platformed me,

617
00:34:19,840 --> 00:34:24,000
Speaker 2: when all of these guys, you know, Ben and others. Yeah,

618
00:34:24,160 --> 00:34:27,160
Speaker 2: I'm not platforming anyone. They already have huge platforms. I

619
00:34:27,280 --> 00:34:30,120
Speaker 2: just you know, I can't just turning our back doesn't

620
00:34:30,160 --> 00:34:33,040
Speaker 2: mean they turn off. And I think, you know, trying

621
00:34:33,040 --> 00:34:36,319
Speaker 2: to understand what motivates people, trying to understand, you know,

622
00:34:36,400 --> 00:34:40,040
Speaker 2: the why, what's the burning why allows us to be

623
00:34:40,080 --> 00:34:43,320
Speaker 2: able to position ourselves and you know, and and fight

624
00:34:43,400 --> 00:34:45,880
Speaker 2: back in a different way with a deeper sense of understanding.

625
00:34:45,920 --> 00:34:48,000
Speaker 2: You got to know your enemy, as they say, but

626
00:34:48,080 --> 00:34:50,080
Speaker 2: you also have to understand, you know, I come from

627
00:34:50,080 --> 00:34:53,480
Speaker 2: the prison, not everyone's an enemy that underneath all of it.

628
00:34:53,560 --> 00:34:56,640
Speaker 2: I don't know. I just I find I'm a little

629
00:34:56,640 --> 00:35:00,000
Speaker 2: bit more hopeful, and I appreciate you're a little more

630
00:35:01,440 --> 00:35:02,560
Speaker 2: I'm optimistic.

631
00:35:02,680 --> 00:35:06,160
Speaker 1: I'm optimistic that we can fight back, but I realize

632
00:35:06,480 --> 00:35:09,640
Speaker 1: that the optimism has to be based on a really

633
00:35:09,680 --> 00:35:12,520
Speaker 1: difficult fight where a lot of people are going to

634
00:35:12,600 --> 00:35:16,239
Speaker 1: have to make material sacrifices. You know, I don't want

635
00:35:16,239 --> 00:35:18,480
Speaker 1: to hear about how much money someone made anymore. I

636
00:35:18,480 --> 00:35:20,680
Speaker 1: want to know about the money they turned down. I

637
00:35:20,719 --> 00:35:23,840
Speaker 1: want to know what they've sacrificed, and not enough people

638
00:35:23,880 --> 00:35:26,200
Speaker 1: talk about that. I want to hear what people regret,

639
00:35:26,360 --> 00:35:28,680
Speaker 1: you know, I want to know what you regret as

640
00:35:28,719 --> 00:35:33,720
Speaker 1: governor things that you could have done differently, or because

641
00:35:33,719 --> 00:35:36,879
Speaker 1: as we're building the system that aggregates humanity, I think

642
00:35:36,920 --> 00:35:39,680
Speaker 1: it's just as important that we speak about the regrets

643
00:35:40,120 --> 00:35:43,440
Speaker 1: so that whatever they're building knows what to avoid. And

644
00:35:43,520 --> 00:35:47,080
Speaker 1: if nobody's nobody's being honest about that, that's going to

645
00:35:47,120 --> 00:35:50,520
Speaker 1: be incredibly difficult to overcome.

646
00:35:51,160 --> 00:35:53,520
Speaker 2: I I agree with you on that, and we can

647
00:35:53,600 --> 00:35:56,120
Speaker 2: we can go back to my one thousand page COVID

648
00:35:56,160 --> 00:35:57,720
Speaker 2: report and we can do that list.

649
00:35:58,560 --> 00:36:00,680
Speaker 1: And he's got all his way on a list.

650
00:36:00,960 --> 00:36:03,719
Speaker 2: I love how much you know you're with no well,

651
00:36:03,760 --> 00:36:05,920
Speaker 2: that's why we put so I couldn't agree with you more.

652
00:36:05,920 --> 00:36:07,359
Speaker 2: You got to own up. You got to and as

653
00:36:07,360 --> 00:36:09,120
Speaker 2: the hell, I wrote a whole book on on that

654
00:36:09,160 --> 00:36:11,080
Speaker 2: and you and but that's what you're doing right now.

655
00:36:11,120 --> 00:36:14,160
Speaker 2: And I appreciate that you're just being honest and transparent

656
00:36:15,200 --> 00:36:18,160
Speaker 2: and you know, and and you're not dream of regretting.

657
00:36:18,239 --> 00:36:20,719
Speaker 2: I mean the fact that you're willing to confront you know.

658
00:36:21,920 --> 00:36:23,759
Speaker 2: You know, it's well known that you, you know, wrote

659
00:36:23,920 --> 00:36:26,680
Speaker 2: a children's book that you regret writing, and the sort

660
00:36:26,719 --> 00:36:29,759
Speaker 2: of anti trans children book, and and and but also

661
00:36:29,800 --> 00:36:31,600
Speaker 2: the things you posted, and so I want to talk

662
00:36:31,600 --> 00:36:33,520
Speaker 2: to just a little bit more about that because you

663
00:36:33,520 --> 00:36:37,359
Speaker 2: know right now, you know, I'm here, you know, stone

664
00:36:37,480 --> 00:36:40,720
Speaker 2: throw away where I first learned about this person, Laura Lumer.

665
00:36:41,280 --> 00:36:44,399
Speaker 2: She was dressed up in a costume. She jumped over

666
00:36:44,440 --> 00:36:47,239
Speaker 2: the fence here at the Governor's mansion and she, you know,

667
00:36:47,560 --> 00:36:49,680
Speaker 2: she broke, you know, sort of that barrier of privacy.

668
00:36:49,719 --> 00:36:52,200
Speaker 2: And she did it online and you know, got a

669
00:36:52,239 --> 00:36:55,839
Speaker 2: bunch of followers, and she's a I'm no fan of hers.

670
00:36:55,920 --> 00:36:58,000
Speaker 2: I don't know over adeeming quality. I thought she was.

671
00:36:58,719 --> 00:37:00,719
Speaker 2: I was a little embarrassed for I thought she needed

672
00:37:00,719 --> 00:37:03,440
Speaker 2: a little help, but that was the beginning and then

673
00:37:03,440 --> 00:37:05,960
Speaker 2: she blew up. Now she's a damn in as seems

674
00:37:05,960 --> 00:37:08,359
Speaker 2: like real influence with Trump, and I'm trying to sort

675
00:37:08,400 --> 00:37:10,840
Speaker 2: of unpacked. I mean, that's to me madness that she

676
00:37:11,200 --> 00:37:14,000
Speaker 2: somehow has the ear of the president. But you know,

677
00:37:14,160 --> 00:37:16,040
Speaker 2: you have all these folks in this sort of right

678
00:37:16,040 --> 00:37:18,759
Speaker 2: wing influence spare. You got the ones like Laura that

679
00:37:18,800 --> 00:37:21,319
Speaker 2: people seem to know about, Candice Owens that people seem

680
00:37:21,360 --> 00:37:24,560
Speaker 2: to know about. Obviously, Tucker Carlson people know about. But

681
00:37:24,640 --> 00:37:28,200
Speaker 2: you have also these other characters. This Jack I can't

682
00:37:28,200 --> 00:37:31,839
Speaker 2: even remember his name, you know, Pasobic. I mean, these

683
00:37:31,840 --> 00:37:33,960
Speaker 2: are the guys and this Mike guy shure Up, whatever

684
00:37:33,960 --> 00:37:36,719
Speaker 2: the hell his name is. Yeah, these guys, I mean,

685
00:37:36,719 --> 00:37:40,319
Speaker 2: these are the Pizzagate guys. I mean literally, these are

686
00:37:40,320 --> 00:37:43,920
Speaker 2: the people that were talking about sexual predators and they

687
00:37:43,960 --> 00:37:47,319
Speaker 2: were They did nothing when you were being unmasked on

688
00:37:47,400 --> 00:37:48,360
Speaker 2: Grock the.

689
00:37:48,440 --> 00:37:51,560
Speaker 1: Same they did not, especially these people who claim to

690
00:37:51,600 --> 00:37:53,920
Speaker 1: care about women and children. And the only time they

691
00:37:53,920 --> 00:37:57,560
Speaker 1: claim that is when they're targeting the trans community. Yeah,

692
00:37:57,640 --> 00:38:00,239
Speaker 1: and a section of the population that's less than one

693
00:38:00,280 --> 00:38:03,400
Speaker 1: percent of the population. And what I can say, especially

694
00:38:03,440 --> 00:38:05,759
Speaker 1: as the Democrats try to navigate and they say, well,

695
00:38:05,800 --> 00:38:08,840
Speaker 1: maybe we went too far on the trans issue. No,

696
00:38:08,960 --> 00:38:11,759
Speaker 1: you didn't, because these people are targeting less than one

697
00:38:11,800 --> 00:38:16,560
Speaker 1: percent of the population, and that's really cruel and evil.

698
00:38:16,680 --> 00:38:18,920
Speaker 1: And if we ignore that cruelty that they've done to

699
00:38:19,000 --> 00:38:21,719
Speaker 1: this very marginalized group of people, it's going to be

700
00:38:21,719 --> 00:38:23,719
Speaker 1: done to you. But what I can say about these

701
00:38:23,760 --> 00:38:27,719
Speaker 1: influencers is we fixate on the caricatures and not the

702
00:38:27,760 --> 00:38:30,440
Speaker 1: system in the architecture that has allowed them to prosper.

703
00:38:30,600 --> 00:38:33,799
Speaker 1: And that is Twitter, that is X and it is

704
00:38:33,880 --> 00:38:37,000
Speaker 1: being manipulated in a way that I believe is really

705
00:38:37,120 --> 00:38:40,640
Speaker 1: dangerous to the future of our democracy and elections. That

706
00:38:40,719 --> 00:38:43,640
Speaker 1: we don't have transparency into how this data is being

707
00:38:43,680 --> 00:38:48,160
Speaker 1: analyzed for elections, which people are being boosted in this algorithm,

708
00:38:48,160 --> 00:38:51,240
Speaker 1: which people are You know that these characters are able

709
00:38:51,239 --> 00:38:55,040
Speaker 1: to amass millions of followers despite being previously banned everywhere,

710
00:38:55,480 --> 00:38:59,080
Speaker 1: and that is what needs to be fixated on. And

711
00:38:59,160 --> 00:39:02,040
Speaker 1: so often the caricature of these people on the right

712
00:39:02,080 --> 00:39:06,279
Speaker 1: get the headlines as opposed to governing the infrastructure that's

713
00:39:06,320 --> 00:39:09,080
Speaker 1: allowing this, and that is really important.

714
00:39:09,239 --> 00:39:12,839
Speaker 2: I love what you're saying, and I don't I don't

715
00:39:12,880 --> 00:39:15,319
Speaker 2: want to lose this thread, but I do want to

716
00:39:15,360 --> 00:39:18,759
Speaker 2: sort of illuminate that their component parts. These guys are

717
00:39:18,800 --> 00:39:21,560
Speaker 2: knitting these things together. This guy Jack and Mike and

718
00:39:21,600 --> 00:39:23,719
Speaker 2: these others that people don't know about it, and these

719
00:39:23,760 --> 00:39:27,080
Speaker 2: are so these are the influencers that are dialing up

720
00:39:27,120 --> 00:39:30,520
Speaker 2: the rage, dialing up the anger. They were dialing you up, right,

721
00:39:30,560 --> 00:39:35,360
Speaker 2: they were sort of building your platform and they're still

722
00:39:35,360 --> 00:39:37,560
Speaker 2: at it, right. I mean, these guys are you know,

723
00:39:37,680 --> 00:39:41,160
Speaker 2: they're part of you know, these guys you've described, and

724
00:39:41,200 --> 00:39:44,239
Speaker 2: I'd love to you illuminate further. These are folks on

725
00:39:44,320 --> 00:39:49,359
Speaker 2: group chats consistently trying to help weaponize grievance. They've got

726
00:39:49,400 --> 00:39:54,080
Speaker 2: the president's right hand person, potentially James Blair, the political operation.

727
00:39:53,719 --> 00:39:56,280
Speaker 1: No, potentially James Blair is in these group chats. Members

728
00:39:56,320 --> 00:39:58,800
Speaker 1: of the administration are in these group chats. They operate

729
00:39:58,840 --> 00:40:01,399
Speaker 1: through group chats and have for many years, in which

730
00:40:01,400 --> 00:40:05,319
Speaker 1: they coordinate these messaging campaigns on what they're going to

731
00:40:05,360 --> 00:40:07,879
Speaker 1: respond to, how they're going to respond to it or

732
00:40:08,040 --> 00:40:12,600
Speaker 1: not respond to it. It is incredibly coordinated and sophisticated

733
00:40:12,640 --> 00:40:15,400
Speaker 1: in the way in which they coordinate this via group chats,

734
00:40:15,480 --> 00:40:21,440
Speaker 1: via signal, via calls with the administration and members of

735
00:40:21,480 --> 00:40:26,360
Speaker 1: the campaign. So it is and again this primarily festers

736
00:40:26,120 --> 00:40:27,040
Speaker 1: on Twitter.

737
00:40:28,239 --> 00:40:30,680
Speaker 2: And back to that then, so the idea that Elon

738
00:40:30,840 --> 00:40:34,520
Speaker 2: has Twitter, idea that Elon ran one of the largest

739
00:40:34,520 --> 00:40:37,759
Speaker 2: super PACs in US history America Pack, idea that he

740
00:40:37,920 --> 00:40:42,160
Speaker 2: invested hundreds of millions of dollars that we know of directly,

741
00:40:43,400 --> 00:40:46,880
Speaker 2: that he ran their field campaign a big part of it,

742
00:40:46,920 --> 00:40:49,839
Speaker 2: and that data collection, the fact that we do have

743
00:40:49,880 --> 00:40:52,319
Speaker 2: someone as powerful as him was about to be exponentially

744
00:40:52,320 --> 00:40:55,880
Speaker 2: more powerful when this IPO Starlink, which you know, I

745
00:40:55,920 --> 00:40:58,879
Speaker 2: call a Starlink IPO more than a SpaceX IPO. That's

746
00:40:58,880 --> 00:41:00,960
Speaker 2: the one profitable side of it at least, you know,

747
00:41:01,080 --> 00:41:03,640
Speaker 2: And it's amazing that Rocket company you want to ask

748
00:41:03,640 --> 00:41:06,520
Speaker 2: to acknowledge that, butrox part But.

749
00:41:06,480 --> 00:41:08,279
Speaker 1: Even that, why do we acknowledge it? Why is it?

750
00:41:08,719 --> 00:41:11,759
Speaker 1: You know? I used to think the same way. I'm like,

751
00:41:11,800 --> 00:41:14,600
Speaker 1: it's it's beautiful to go to the moon, to Mars

752
00:41:14,640 --> 00:41:18,400
Speaker 1: and expand consciousness and you get involved in this Elon Moscovital.

753
00:41:18,880 --> 00:41:20,640
Speaker 1: But at the same time, it's like, why don't we

754
00:41:20,719 --> 00:41:23,439
Speaker 1: leave the moon alone? Why do we need the moon,

755
00:41:23,520 --> 00:41:25,840
Speaker 1: you know, Like why do we have to bastardize something

756
00:41:25,960 --> 00:41:29,160
Speaker 1: so beautiful that everyone can look up and see something

757
00:41:29,719 --> 00:41:32,640
Speaker 1: so pure? You know? My older son, he says, Mama,

758
00:41:32,760 --> 00:41:34,640
Speaker 1: if you're ever not with me, just look at the

759
00:41:34,640 --> 00:41:35,640
Speaker 1: moon and I'll be there.

760
00:41:36,880 --> 00:41:39,359
Speaker 2: Philosophy coming.

761
00:41:40,560 --> 00:41:44,000
Speaker 1: It's so pure and something that every human can look

762
00:41:44,040 --> 00:41:46,040
Speaker 1: at and see something so pure. And it's like, I

763
00:41:46,040 --> 00:41:47,920
Speaker 1: don't want to look at the moon and think of

764
00:41:48,000 --> 00:41:50,040
Speaker 1: American colonialism. I don't.

765
00:41:50,520 --> 00:41:52,600
Speaker 2: Well, he was supposed to be skipping it to Mars,

766
00:41:52,600 --> 00:41:54,359
Speaker 2: but it seems that I don't want to look at Mars.

767
00:41:54,440 --> 00:41:57,040
Speaker 1: You think of that either. I don't want American colonialism

768
00:41:57,080 --> 00:42:00,560
Speaker 1: on Mars. And it's like why if we just accepted that, yes,

769
00:42:00,640 --> 00:42:04,360
Speaker 1: let's let's expand, Like do we deserve to expand we

770
00:42:04,440 --> 00:42:06,640
Speaker 1: haven't even taken care of what we have now? Like

771
00:42:06,719 --> 00:42:08,920
Speaker 1: why do we deserve? Do we have the credit score

772
00:42:09,000 --> 00:42:09,479
Speaker 1: for the moon?

773
00:42:09,520 --> 00:42:13,480
Speaker 2: Do I know? I'm in California? Go west, young man,

774
00:42:13,560 --> 00:42:16,120
Speaker 2: Go west. This notion of the frontier, that's you know,

775
00:42:16,200 --> 00:42:19,640
Speaker 2: that's part of the rugged individualism the history of our country,

776
00:42:19,640 --> 00:42:21,239
Speaker 2: and I think a big part of who we are

777
00:42:21,280 --> 00:42:22,080
Speaker 2: as a species.

778
00:42:22,360 --> 00:42:24,680
Speaker 1: Maybe we can go to Mars speakers and then leave

779
00:42:24,800 --> 00:42:27,839
Speaker 1: Earth alone. So that's all of the life here is untouched.

780
00:42:27,920 --> 00:42:30,000
Speaker 1: You know, there's not other life on the other planets,

781
00:42:30,000 --> 00:42:33,680
Speaker 1: So maybe we just put our diabolical species there are

782
00:42:33,960 --> 00:42:36,600
Speaker 1: and it'll be okay, and then we leave Earth alone.

783
00:42:36,880 --> 00:42:38,480
Speaker 1: But you know it's it's some.

784
00:42:39,000 --> 00:42:42,440
Speaker 2: But the power of these algorithms, the power that Elon

785
00:42:42,920 --> 00:42:47,480
Speaker 2: himself has to dialing uprage, to determining what we see,

786
00:42:47,920 --> 00:42:52,080
Speaker 2: what we hear, how we think, who we vote for.

787
00:42:52,760 --> 00:42:56,520
Speaker 2: That seems disproportionate the power of James Blair to connect

788
00:42:56,600 --> 00:43:00,360
Speaker 2: and coordinate with all these influencers, to have the daily messages.

789
00:43:00,400 --> 00:43:03,160
Speaker 2: You see it weaponized on Fox, the primetime line up there,

790
00:43:03,320 --> 00:43:05,759
Speaker 2: which is Pravda. You see it on the right all

791
00:43:06,120 --> 00:43:08,400
Speaker 2: all cross the right wing spear. I watched a New

792
00:43:08,480 --> 00:43:11,720
Speaker 2: York Post, the California Post, the Daily all this stuff,

793
00:43:12,160 --> 00:43:15,400
Speaker 2: this stuff and just the connective tissue, and you were

794
00:43:15,480 --> 00:43:19,080
Speaker 2: part of all that. I mean, we're not overstating this.

795
00:43:19,520 --> 00:43:22,120
Speaker 1: No, No, I wasn't part of that. I saw it,

796
00:43:22,200 --> 00:43:25,160
Speaker 1: and you're not being hyperbolic, and I don't I don't

797
00:43:25,200 --> 00:43:28,680
Speaker 1: think there's an underdiscussed aspect of this as well. Yes,

798
00:43:29,120 --> 00:43:32,880
Speaker 1: they have the power to influence what you think who

799
00:43:33,000 --> 00:43:35,600
Speaker 1: you think about. But they also have the data on

800
00:43:35,640 --> 00:43:38,120
Speaker 1: what's going to be the most useful and the best

801
00:43:38,200 --> 00:43:41,759
Speaker 1: way to exploit that. If Cambridge Analytica was bad, this

802
00:43:41,800 --> 00:43:45,800
Speaker 1: is Cambridge Analytica on meth amphetamines and steroids at this point.

803
00:43:46,280 --> 00:43:49,160
Speaker 1: And so it's the how they know exactly how you think.

804
00:43:49,200 --> 00:43:53,120
Speaker 1: They're creating this behavioral inference model, that they know exactly

805
00:43:53,160 --> 00:43:56,600
Speaker 1: which part of you to exploit, which vulnerability. It is

806
00:43:56,719 --> 00:43:59,680
Speaker 1: like being in an abusive relationship where they know exactly

807
00:43:59,719 --> 00:44:03,960
Speaker 1: where you're vulnerable and how to exploit that vulnerability to

808
00:44:04,640 --> 00:44:06,160
Speaker 1: make you act in a certain way.

809
00:44:07,000 --> 00:44:12,279
Speaker 2: So what I mean is there any Do you see

810
00:44:12,280 --> 00:44:14,919
Speaker 2: anything on the left that's comparable or you don't want

811
00:44:14,960 --> 00:44:16,839
Speaker 2: to see anything on the left that's comparable, but.

812
00:44:16,800 --> 00:44:19,799
Speaker 1: Do you No, I don't want to see anything comparable.

813
00:44:19,960 --> 00:44:22,720
Speaker 1: And that's what really terrifies me is when I speak

814
00:44:22,719 --> 00:44:25,319
Speaker 1: about these things, I see people on the left and

815
00:44:25,360 --> 00:44:28,160
Speaker 1: the democratic side saying we need this, and no, you don't.

816
00:44:28,200 --> 00:44:33,440
Speaker 1: It's ontologically evil to have such unfettered capitalism and the

817
00:44:33,800 --> 00:44:37,960
Speaker 1: effects of citizens United so prolific that we don't have

818
00:44:38,040 --> 00:44:41,239
Speaker 1: these disclosure laws. No, the left needs to be going

819
00:44:41,280 --> 00:44:44,719
Speaker 1: hard and making sure that you cannot post anything, you

820
00:44:44,760 --> 00:44:48,280
Speaker 1: cannot be paid to post anything, whether it's an opinion,

821
00:44:48,400 --> 00:44:52,520
Speaker 1: an idea, a philosophy that you like. We're so without

822
00:44:52,920 --> 00:44:57,000
Speaker 1: disclosing that, and that's what needs to change, rather than

823
00:44:57,040 --> 00:45:01,120
Speaker 1: building this evil apparatus for yourselves. I think that's if

824
00:45:01,160 --> 00:45:02,839
Speaker 1: I think it's bad on the right, it's also bad

825
00:45:02,840 --> 00:45:05,600
Speaker 1: on the left. But you can stop them from doing

826
00:45:05,680 --> 00:45:07,600
Speaker 1: it with laws and regulations.

827
00:45:07,880 --> 00:45:09,880
Speaker 2: Actually, let me ask you about that, because it's interesting.

828
00:45:09,880 --> 00:45:13,040
Speaker 2: We have a governor's race and literally determine the primary

829
00:45:13,040 --> 00:45:18,000
Speaker 2: today are as we're taping this, and there's been a

830
00:45:18,040 --> 00:45:21,640
Speaker 2: lot of reporting about influencers have gotten hundreds and hundreds

831
00:45:21,640 --> 00:45:23,440
Speaker 2: of thousands of dollars. No one was aware of it.

832
00:45:23,960 --> 00:45:27,840
Speaker 2: There was no nothing transparent about it. So that's just

833
00:45:27,880 --> 00:45:31,360
Speaker 2: a space that's the wild West, isn't it? For candidates

834
00:45:31,360 --> 00:45:35,640
Speaker 2: and causes where influencers are paid and we think it's

835
00:45:35,680 --> 00:45:38,919
Speaker 2: their voice, but there's no political even in a political sense,

836
00:45:38,920 --> 00:45:42,920
Speaker 2: there's no rules necessarily for transparency.

837
00:45:43,160 --> 00:45:46,400
Speaker 1: Yes, because the mechanism, as I'm sure you know, is

838
00:45:46,440 --> 00:45:52,200
Speaker 1: the consulting houses. The consulting houses, they are advantaged by

839
00:45:52,239 --> 00:45:54,560
Speaker 1: a degree of privacy that they shouldn't have. I think

840
00:45:54,560 --> 00:45:57,440
Speaker 1: if you were a consulting house who's on these FEC reports,

841
00:45:57,560 --> 00:45:59,960
Speaker 1: you should have to disclose everything in your books as well.

842
00:46:00,040 --> 00:46:04,000
Speaker 1: Shouldn't disappear once it hits a consulting house. That's so easy.

843
00:46:04,080 --> 00:46:06,920
Speaker 1: I can start an LLC tomorrow. You pay me a

844
00:46:07,000 --> 00:46:09,560
Speaker 1: million dollars for your campaign, and I disperse it to

845
00:46:09,600 --> 00:46:14,080
Speaker 1: my secret influencers and nobody will ever know. That should

846
00:46:14,080 --> 00:46:15,280
Speaker 1: not be allowed to occur.

847
00:46:17,520 --> 00:46:19,360
Speaker 2: I think this, I could agree with you more of

848
00:46:19,400 --> 00:46:21,279
Speaker 2: this in an area that we're going to have to significantly,

849
00:46:21,360 --> 00:46:24,480
Speaker 2: I mean aggressively and quickly tighten up. So what you

850
00:46:24,680 --> 00:46:26,520
Speaker 2: mentioned the other day, and you know, I got a

851
00:46:26,520 --> 00:46:31,120
Speaker 2: lot of attention. You posted something about ten thousand late.

852
00:46:31,280 --> 00:46:32,960
Speaker 2: I mean, what, what, what? What the hell did you

853
00:46:33,000 --> 00:46:36,600
Speaker 2: post ten thousand layers? I did the implication the election

854
00:46:36,760 --> 00:46:40,080
Speaker 2: was stolen, all the conspiracy theories, and I knew it.

855
00:46:40,280 --> 00:46:42,279
Speaker 2: I had my friends. I told you, so I'm like,

856
00:46:42,320 --> 00:46:44,000
Speaker 2: oh God, what's going on here?

857
00:46:44,239 --> 00:46:46,839
Speaker 1: I think people people really need to And I want

858
00:46:46,840 --> 00:46:48,920
Speaker 1: to preface this by saying people should vote, and they

859
00:46:48,920 --> 00:46:52,200
Speaker 1: should vote loudly. There is something to say about the

860
00:46:52,239 --> 00:46:54,400
Speaker 1: right saying you know, too big to rig everyone should

861
00:46:54,400 --> 00:46:56,440
Speaker 1: turn out, and I don't want to discourage vote or

862
00:46:56,440 --> 00:46:59,960
Speaker 1: turnout when I talk about this experience. But shortly before

863
00:47:00,160 --> 00:47:03,320
Speaker 1: the election in October, Elon had texted me and said,

864
00:47:03,440 --> 00:47:06,680
Speaker 1: you know, I'm feeling more optimistic about the election, and

865
00:47:06,719 --> 00:47:09,200
Speaker 1: tomorrow I'm going to release my anomaly in the matrix.

866
00:47:09,800 --> 00:47:12,359
Speaker 1: I have lasers in space. And then he quantifies it.

867
00:47:12,440 --> 00:47:14,760
Speaker 1: He says, I have over ten thousand lasers in space,

868
00:47:14,800 --> 00:47:17,919
Speaker 1: which is nearly identical to the number of satellites he has.

869
00:47:18,520 --> 00:47:20,360
Speaker 1: And I told him, I said, I'd ask more, but

870
00:47:20,400 --> 00:47:23,680
Speaker 1: I don't want to be deposed, and he said wise.

871
00:47:23,920 --> 00:47:26,200
Speaker 1: But something else I had said, I said, you know,

872
00:47:26,239 --> 00:47:28,560
Speaker 1: if this ends up being your lasers in space end

873
00:47:28,680 --> 00:47:31,560
Speaker 1: up being the reason that Trump wins, this would be

874
00:47:31,640 --> 00:47:34,560
Speaker 1: like a sci fi drama. And you know, he replied

875
00:47:34,600 --> 00:47:38,160
Speaker 1: and agreed with that. So those are important aspects. What

876
00:47:38,200 --> 00:47:41,160
Speaker 1: that means, I'm not entirely sure. I also have other

877
00:47:41,280 --> 00:47:45,279
Speaker 1: information that you know, I came across during my time

878
00:47:45,320 --> 00:47:48,919
Speaker 1: with him and speaking to his engineers that is incredibly uncomfortable.

879
00:47:49,560 --> 00:47:52,640
Speaker 1: But this again goes back to the governing architecture. Does

880
00:47:52,680 --> 00:47:56,279
Speaker 1: anybody know is there any regulations or laws in it?

881
00:47:56,480 --> 00:47:59,120
Speaker 1: Right now saying you cannot use your data from your

882
00:47:59,160 --> 00:48:04,160
Speaker 1: satellites for elections or for a proprietary data. Is all

883
00:48:04,200 --> 00:48:08,320
Speaker 1: of this being hid under proprietary data in intellectual property

884
00:48:08,640 --> 00:48:11,960
Speaker 1: that is not okay? And right now we don't have

885
00:48:12,040 --> 00:48:17,120
Speaker 1: the infrastructure. There's not infrastructure or laws against using data

886
00:48:17,120 --> 00:48:19,799
Speaker 1: from your space company, whose ever space company it is,

887
00:48:20,320 --> 00:48:23,600
Speaker 1: for whatever purpose you want. If it's private, We've had

888
00:48:23,800 --> 00:48:28,080
Speaker 1: so much hidden under private capital and that needs to

889
00:48:28,120 --> 00:48:28,799
Speaker 1: be addressed.

890
00:48:29,120 --> 00:48:30,840
Speaker 2: Why did actually, why do you feel the need to

891
00:48:31,239 --> 00:48:32,879
Speaker 2: share that and why now?

892
00:48:33,600 --> 00:48:37,799
Speaker 1: Because I'm speaking about my entire experience as honestly and

893
00:48:37,880 --> 00:48:40,880
Speaker 1: openly as I can, including moments that made me really

894
00:48:41,080 --> 00:48:44,480
Speaker 1: raise an eyebrow and say, this is concerning As someone

895
00:48:44,520 --> 00:48:48,919
Speaker 1: who you know throughout my time in this relationship with Elon,

896
00:48:49,000 --> 00:48:51,560
Speaker 1: he had also sent me data of real time Delta

897
00:48:51,680 --> 00:48:56,440
Speaker 1: vote metrics in October from Pennsylvania and information from his

898
00:48:56,600 --> 00:48:59,480
Speaker 1: pack And as someone who was cleaning bad door knocking

899
00:48:59,520 --> 00:49:03,680
Speaker 1: data from Whatt's canvassing since I was eighteen, I looked

900
00:49:03,680 --> 00:49:06,520
Speaker 1: at that and said, there's no apparatus that I know

901
00:49:06,640 --> 00:49:11,719
Speaker 1: of that can create that data. So your what are

902
00:49:11,760 --> 00:49:14,920
Speaker 1: your inputs? What inputs are you using? And that's the

903
00:49:15,040 --> 00:49:17,919
Speaker 1: question that other people need to ask. And when people

904
00:49:18,000 --> 00:49:21,440
Speaker 1: ask them, and hopefully governing bodies who come to me

905
00:49:21,520 --> 00:49:23,920
Speaker 1: for this information, I can tell them what I know

906
00:49:24,040 --> 00:49:26,359
Speaker 1: and what I think, and the individuals who I spoke

907
00:49:26,400 --> 00:49:30,040
Speaker 1: to as well. But what inputs create that level of

908
00:49:30,120 --> 00:49:33,800
Speaker 1: certainty that nobody else had previously about when the election

909
00:49:33,920 --> 00:49:36,680
Speaker 1: results were in. Those are the questions that need to

910
00:49:36,680 --> 00:49:37,200
Speaker 1: be asked.

911
00:49:37,719 --> 00:49:41,400
Speaker 2: And when you start to I mean, you've expressed literal concern,

912
00:49:41,600 --> 00:49:45,760
Speaker 2: But for sharing this information publicly you even suggested, didn't suggest,

913
00:49:45,800 --> 00:49:48,080
Speaker 2: I think you stated, and maybe you can clarify that

914
00:49:49,080 --> 00:49:52,040
Speaker 2: there was an opportunity effort to say, hey, you don't

915
00:49:52,080 --> 00:49:54,239
Speaker 2: need to share this. Actually it will take care of you.

916
00:49:54,320 --> 00:49:56,919
Speaker 2: I'll take care of you, right, A big, big damn check.

917
00:49:57,480 --> 00:50:00,640
Speaker 1: Yeah. I was offered forty million dollars with which included

918
00:50:00,680 --> 00:50:04,120
Speaker 1: an NDA and non discouragement into eternity, which I declined.

919
00:50:05,880 --> 00:50:10,000
Speaker 1: Part of this information is why because I do believe

920
00:50:10,080 --> 00:50:12,560
Speaker 1: him and his companies and everything that's being built to

921
00:50:12,600 --> 00:50:16,120
Speaker 1: be incredibly consequential for the future of our country, the

922
00:50:16,160 --> 00:50:18,480
Speaker 1: future of the country that my children will have to

923
00:50:18,480 --> 00:50:20,680
Speaker 1: live in, the digital landscape that they'll have to live

924
00:50:20,719 --> 00:50:25,399
Speaker 1: in and I think there's a lot worse than being,

925
00:50:26,920 --> 00:50:31,239
Speaker 1: you know, middle class in America, and that's okay. I'm

926
00:50:31,239 --> 00:50:34,160
Speaker 1: comfortable with that to keep my integrity and at least

927
00:50:34,200 --> 00:50:37,279
Speaker 1: when push came to shove that I was able to

928
00:50:37,320 --> 00:50:41,200
Speaker 1: turn that down. And I also think women need to

929
00:50:41,239 --> 00:50:43,840
Speaker 1: speak up. I think a lot would not be allowed

930
00:50:43,840 --> 00:50:47,280
Speaker 1: to happen if women stopped keeping a lot of secrets

931
00:50:47,320 --> 00:50:47,719
Speaker 1: for men.

932
00:50:48,120 --> 00:50:52,239
Speaker 2: And is that because you're uniquely positioned, because you have

933
00:50:52,280 --> 00:50:57,600
Speaker 2: a voice, because you have enough resourcefulness, if not the resources.

934
00:50:58,040 --> 00:50:59,560
Speaker 2: I mean, what do you say to those other women?

935
00:50:59,640 --> 00:51:01,839
Speaker 2: I mean, what about all these folks that are sort

936
00:51:01,880 --> 00:51:04,000
Speaker 2: of trapped in this mindset?

937
00:51:04,000 --> 00:51:07,040
Speaker 1: I think particularly the women of privilege, like I have

938
00:51:07,120 --> 00:51:10,120
Speaker 1: a level of privilege having some sort of platform, and

939
00:51:10,400 --> 00:51:13,440
Speaker 1: even if there's material hardship, I do have access to

940
00:51:13,560 --> 00:51:17,200
Speaker 1: resources and educated individuals and people who are well networked

941
00:51:17,200 --> 00:51:20,200
Speaker 1: that I can utilize. And there are many women within

942
00:51:20,239 --> 00:51:23,239
Speaker 1: those Maro Lago in the magaspheres that have that same

943
00:51:23,280 --> 00:51:27,000
Speaker 1: access who can do something. And I'm very concerned about

944
00:51:27,000 --> 00:51:32,239
Speaker 1: the proliferation of this privatized legal system through NDAs. I

945
00:51:32,280 --> 00:51:35,840
Speaker 1: don't think with most NDAs that there is any meaningful

946
00:51:35,880 --> 00:51:39,160
Speaker 1: consent when people are signing them to pay their bills,

947
00:51:39,200 --> 00:51:42,279
Speaker 1: feed their family or whatever. So I do think that's

948
00:51:42,320 --> 00:51:44,560
Speaker 1: another aspect that needs to be addressed because it's how

949
00:51:44,680 --> 00:51:48,000
Speaker 1: so much evil has been allowed to occur. And if

950
00:51:48,040 --> 00:51:51,440
Speaker 1: we're supposed to be building a system to aggregate humanity

951
00:51:51,520 --> 00:51:54,800
Speaker 1: and the honest version of it, but the honesty about

952
00:51:54,840 --> 00:51:57,880
Speaker 1: the most powerful people cannot be said because of NDAs

953
00:51:57,920 --> 00:52:03,279
Speaker 1: and this proliferation of this industry of silence, then we

954
00:52:03,360 --> 00:52:04,080
Speaker 1: have a problem.

955
00:52:04,840 --> 00:52:07,440
Speaker 2: Yeah, well said, by the way, I couldn't agree with

956
00:52:07,480 --> 00:52:10,120
Speaker 2: you more So, look, Ashley, as we you know, as

957
00:52:10,160 --> 00:52:12,200
Speaker 2: you move forward, as we move forward, as we move

958
00:52:12,239 --> 00:52:16,239
Speaker 2: into midterm elections, not making everything electoral, as we move

959
00:52:16,719 --> 00:52:20,440
Speaker 2: continue to move forward with this letter. Rip attitude of

960
00:52:20,040 --> 00:52:22,879
Speaker 2: the of the Trump administration as it relates to AI

961
00:52:23,000 --> 00:52:27,440
Speaker 2: regulation or lack thereof, sort of the David sassification of

962
00:52:28,160 --> 00:52:32,120
Speaker 2: regulatory policy, and you know, highlighted by the fact that

963
00:52:32,160 --> 00:52:34,919
Speaker 2: Elon and a few others Zuckerberg made calls to Trump

964
00:52:35,000 --> 00:52:38,640
Speaker 2: to stop them from even a modest executive order to

965
00:52:38,920 --> 00:52:41,439
Speaker 2: begin to do something. By the way, all they're trying

966
00:52:41,480 --> 00:52:44,400
Speaker 2: to do is preempt California and our leadership on this.

967
00:52:44,520 --> 00:52:50,239
Speaker 2: They've tried to neutralize California. We saw Governor Hokeel and

968
00:52:50,280 --> 00:52:53,600
Speaker 2: now Pritzker back into aspects of what California did to

969
00:52:53,680 --> 00:52:56,479
Speaker 2: lead on some of the safety issues on AI's still

970
00:52:56,480 --> 00:52:58,359
Speaker 2: not enough. I get it, and we have more work

971
00:52:58,400 --> 00:53:03,200
Speaker 2: to do, but the contrast with Trump is pretty illuminating.

972
00:53:03,680 --> 00:53:06,399
Speaker 2: How worried are you about fair and free elections? How

973
00:53:06,440 --> 00:53:10,759
Speaker 2: worried about you you know your son's father is going

974
00:53:10,840 --> 00:53:13,000
Speaker 2: to be likely the first trillionaire in a matter of week,

975
00:53:13,520 --> 00:53:17,840
Speaker 2: a couple of weeks. How concerned are you about capture

976
00:53:18,239 --> 00:53:21,880
Speaker 2: and these algorithms and just a handful of people deciding

977
00:53:21,960 --> 00:53:23,600
Speaker 2: our fate and future in terms of what we read,

978
00:53:23,680 --> 00:53:25,560
Speaker 2: see here and believe.

979
00:53:26,120 --> 00:53:29,840
Speaker 1: I think people should be incredibly concerned about the elections

980
00:53:30,000 --> 00:53:32,560
Speaker 1: just because of the new landscape we're creating. I often

981
00:53:32,800 --> 00:53:36,600
Speaker 1: describe the Internet as we built this new planet. We're

982
00:53:36,600 --> 00:53:38,680
Speaker 1: demanding that people inhabit it and live on it, and

983
00:53:38,719 --> 00:53:41,680
Speaker 1: we have no idea if there's enough oxygen for people here,

984
00:53:42,160 --> 00:53:44,359
Speaker 1: and so we really need to be critical of this

985
00:53:44,520 --> 00:53:47,799
Speaker 1: digital landscape and terrain that we've built and how that

986
00:53:47,840 --> 00:53:53,480
Speaker 1: impacts our elections, from data to manipulation to perception. This

987
00:53:53,640 --> 00:53:56,440
Speaker 1: is very important do I think that maybe there's lasers

988
00:53:56,440 --> 00:53:59,400
Speaker 1: beaming down from space to change the vote on the

989
00:53:59,400 --> 00:54:02,839
Speaker 1: dominion miss machines? Probably not. But do I believe that

990
00:54:03,280 --> 00:54:07,359
Speaker 1: very powerful technology from very powerful individuals is being exploited

991
00:54:07,680 --> 00:54:10,720
Speaker 1: to create outcomes that they want. Yes, That's happened throughout

992
00:54:10,800 --> 00:54:12,880
Speaker 1: all of human history, and to say that that's not

993
00:54:12,960 --> 00:54:17,600
Speaker 1: happening would be incredibly ignorant to these levers of capitalism.

994
00:54:18,080 --> 00:54:19,919
Speaker 1: And one thing I want people to know is that

995
00:54:20,600 --> 00:54:24,440
Speaker 1: the Silicon Valley bros. Would be very proficient in plantation accounting.

996
00:54:24,920 --> 00:54:29,640
Speaker 1: And these are systems that we've seen before, just at

997
00:54:29,680 --> 00:54:31,280
Speaker 1: a much larger scale.

998
00:54:32,600 --> 00:54:38,279
Speaker 2: So do you and forgive me, I'm just sort of

999
00:54:38,360 --> 00:54:45,359
Speaker 2: belaboring this and diving deeper. How embedded from your perspective

1000
00:54:46,040 --> 00:54:51,239
Speaker 2: are the operations on the inside MAGA and those operations

1001
00:54:51,239 --> 00:54:56,080
Speaker 2: with some of these elite tech titans in the context

1002
00:54:56,120 --> 00:55:01,920
Speaker 2: of being even more deliberative in terms of of hardwiring.

1003
00:55:01,719 --> 00:55:05,520
Speaker 1: They are intimately intertwined. This is why big tech was

1004
00:55:05,560 --> 00:55:08,680
Speaker 1: at the forefront of all of these issues within MAGA,

1005
00:55:08,760 --> 00:55:11,800
Speaker 1: especially in twenty twenty, and then Mark Zuckerberg changes course

1006
00:55:12,160 --> 00:55:14,160
Speaker 1: and just look at who was front and center at

1007
00:55:14,160 --> 00:55:17,200
Speaker 1: the inauguration you had showing up.

1008
00:55:17,840 --> 00:55:20,240
Speaker 2: I mean, there's benefit just showing up, But that doesn't

1009
00:55:20,239 --> 00:55:22,759
Speaker 2: mean you're I mean, is it your perspective that by

1010
00:55:22,800 --> 00:55:26,200
Speaker 2: showing up, you're I mean that they're taking there. They're

1011
00:55:26,239 --> 00:55:29,360
Speaker 2: not just dipping their toe of support, They're they're swimming.

1012
00:55:29,800 --> 00:55:32,480
Speaker 1: Yes, they changed the algorithms. Some of these people who

1013
00:55:32,480 --> 00:55:36,600
Speaker 1: were previously banned or not allowed to monetize on these platforms,

1014
00:55:36,680 --> 00:55:39,920
Speaker 1: the floodgates have been opened and they are allowed to

1015
00:55:40,000 --> 00:55:43,080
Speaker 1: do this. And you know, there is an important distinction

1016
00:55:43,200 --> 00:55:45,520
Speaker 1: to make because I was very much on the free

1017
00:55:45,520 --> 00:55:49,839
Speaker 1: speech absolutism. And that's different when you're the audience, you're

1018
00:55:49,880 --> 00:55:52,480
Speaker 1: speaking to his local or you're making local change or

1019
00:55:52,560 --> 00:55:54,600
Speaker 1: national change. But now you're demanding to be on this

1020
00:55:54,719 --> 00:55:58,160
Speaker 1: global platform and your words have global consequences, and to

1021
00:55:58,560 --> 00:56:02,120
Speaker 1: pretend like the rules of the Inn and these influence

1022
00:56:02,160 --> 00:56:05,600
Speaker 1: operations and speech can be comparable to that within your

1023
00:56:05,640 --> 00:56:07,839
Speaker 1: local town square is asinine.

1024
00:56:09,800 --> 00:56:14,120
Speaker 2: You're going to law school, Ashley, Yes, and so what's

1025
00:56:14,160 --> 00:56:16,719
Speaker 2: the what's the I mean is there there's got to

1026
00:56:16,719 --> 00:56:18,840
Speaker 2: be a book? Come on, you're telling me you're not

1027
00:56:18,880 --> 00:56:19,560
Speaker 2: working on a book.

1028
00:56:19,600 --> 00:56:22,040
Speaker 1: It's impossible, You're i do write a lot. I write

1029
00:56:22,160 --> 00:56:24,160
Speaker 1: enough that if I wanted to make a book, I

1030
00:56:24,160 --> 00:56:25,480
Speaker 1: could publish it tomorrow.

1031
00:56:26,560 --> 00:56:28,560
Speaker 2: So you're writing a book.

1032
00:56:28,600 --> 00:56:30,440
Speaker 1: I do write. I write, and I do a lot

1033
00:56:30,440 --> 00:56:34,680
Speaker 1: of like aid memoir. But it's not the right time

1034
00:56:34,719 --> 00:56:37,359
Speaker 1: for me to sell anything to anybody right now. It's

1035
00:56:37,440 --> 00:56:40,480
Speaker 1: just not I have a lot of work that I

1036
00:56:40,520 --> 00:56:42,520
Speaker 1: need to do in financial amends that I need to

1037
00:56:42,560 --> 00:56:46,359
Speaker 1: make to the communities that I contributed harm to, and

1038
00:56:46,400 --> 00:56:48,520
Speaker 1: there's there's gonna be a lot of backlash for a while.

1039
00:56:48,600 --> 00:56:51,440
Speaker 1: I think there's also this this effect where I'm the

1040
00:56:51,440 --> 00:56:54,799
Speaker 1: most accessible MAGA figure to many people now, so they

1041
00:56:54,920 --> 00:56:57,040
Speaker 1: like to take it out on me. And that's okay,

1042
00:56:57,160 --> 00:57:00,840
Speaker 1: and I understand, but there is when you leave, you

1043
00:57:00,920 --> 00:57:04,319
Speaker 1: realize the vast amounts of harm that you contributed to

1044
00:57:04,719 --> 00:57:07,200
Speaker 1: and the very real harm that I was ignorant to

1045
00:57:07,280 --> 00:57:10,120
Speaker 1: because of my own privilege, Like I just didn't have

1046
00:57:10,239 --> 00:57:15,279
Speaker 1: these experiences. And there's so much happening. They talk about

1047
00:57:15,280 --> 00:57:18,040
Speaker 1: the transfer of wealth, it's not really a transfer wealth.

1048
00:57:18,040 --> 00:57:20,640
Speaker 1: It's a transfer of losses. Even if we take the

1049
00:57:20,640 --> 00:57:23,400
Speaker 1: space X I p O right, there's a lot of

1050
00:57:23,440 --> 00:57:25,200
Speaker 1: people who are going to lose in their four A

1051
00:57:25,240 --> 00:57:27,800
Speaker 1: one case, and this is their pensions. In their four

1052
00:57:27,840 --> 00:57:30,560
Speaker 1: to one case, the losses are being transferred to them

1053
00:57:30,600 --> 00:57:33,040
Speaker 1: because the big banks don't want to take the losses.

1054
00:57:33,480 --> 00:57:36,960
Speaker 1: It's this transfer of losses onto the lesser people that

1055
00:57:37,040 --> 00:57:40,960
Speaker 1: I think we really need to consider and start demanding

1056
00:57:41,040 --> 00:57:44,400
Speaker 1: that people in positions of privilege take more losses on themselves.

1057
00:57:44,520 --> 00:57:47,720
Speaker 2: Yeah, I mean making me think of Trump and Millennia's

1058
00:57:47,800 --> 00:57:51,280
Speaker 2: are Donald and Millennia's meme coins and they come to

1059
00:57:51,320 --> 00:57:54,840
Speaker 2: trate all the losses or absorbed by the base of

1060
00:57:54,920 --> 00:57:59,520
Speaker 2: the party, And yes, we're betefitan them. What, by the way,

1061
00:57:59,680 --> 00:58:01,960
Speaker 2: I did ask you the obvious question, what was the

1062
00:58:02,000 --> 00:58:03,640
Speaker 2: trigger that made you say I got to get the

1063
00:58:03,680 --> 00:58:04,280
Speaker 2: hell out of here?

1064
00:58:05,440 --> 00:58:07,760
Speaker 1: There were many things. I always say it was cumulative,

1065
00:58:07,840 --> 00:58:10,040
Speaker 1: like I saw so much harm, but I didn't I

1066
00:58:10,080 --> 00:58:12,040
Speaker 1: didn't have the coconuts to leave. I didn't have the

1067
00:58:12,080 --> 00:58:15,320
Speaker 1: courage to leave. But then once you're given an offer,

1068
00:58:15,600 --> 00:58:18,800
Speaker 1: like a forty million dollar NDA, and you're looking at

1069
00:58:18,800 --> 00:58:21,080
Speaker 1: your two kids, who you want nothing but the best for,

1070
00:58:21,280 --> 00:58:24,240
Speaker 1: and you have to say, like what, am I gonna

1071
00:58:24,280 --> 00:58:26,400
Speaker 1: have integrity right now? Or am I gonna have a

1072
00:58:26,440 --> 00:58:30,880
Speaker 1: burken And so I had to make that decision. I'm like,

1073
00:58:31,080 --> 00:58:32,800
Speaker 1: am I going to buy a house for my kids?

1074
00:58:33,200 --> 00:58:35,040
Speaker 1: Or am I going to struggle and do the right thing?

1075
00:58:35,760 --> 00:58:38,200
Speaker 1: And I decided to struggle and do the right thing.

1076
00:58:38,840 --> 00:58:40,920
Speaker 1: So that was the moment that I'm like, Okay, well,

1077
00:58:40,920 --> 00:58:43,960
Speaker 1: once I say no to this, because once you say

1078
00:58:43,960 --> 00:58:45,600
Speaker 1: no to a man like Elon, it's as if you

1079
00:58:45,680 --> 00:58:48,800
Speaker 1: never said yes. You know, so I knew what the

1080
00:58:48,840 --> 00:58:52,360
Speaker 1: effects of telling him no, we're going to be.

1081
00:58:53,760 --> 00:58:57,160
Speaker 2: Are you been surprised by people in the movement that

1082
00:58:57,200 --> 00:59:01,440
Speaker 2: have remained loyal to you, that are quiet, have your back,

1083
00:59:01,600 --> 00:59:02,600
Speaker 2: that are cheering.

1084
00:59:02,280 --> 00:59:06,240
Speaker 1: You on no, And there's a lot I've been surprised

1085
00:59:06,240 --> 00:59:08,520
Speaker 1: by more of the people who have resonated with what

1086
00:59:08,560 --> 00:59:11,400
Speaker 1: I'm saying and and said they really want to speak out.

1087
00:59:11,440 --> 00:59:13,400
Speaker 1: But I'll tell you a lot of these people can't

1088
00:59:13,400 --> 00:59:17,560
Speaker 1: because of NDAs, because of their employment agreements with Fox,

1089
00:59:17,720 --> 00:59:21,800
Speaker 1: because of their agreements with various companies, And that needs

1090
00:59:21,840 --> 00:59:24,120
Speaker 1: to be addressed. If we want more people to speak out,

1091
00:59:24,160 --> 00:59:27,880
Speaker 1: there has to be this has to be addressed, this

1092
00:59:28,000 --> 00:59:31,600
Speaker 1: proliferation of NDAs, and we have to protect them.

1093
00:59:31,960 --> 00:59:34,600
Speaker 2: Who's been the most vicious to you, Who's who are

1094
00:59:34,640 --> 00:59:37,480
Speaker 2: you really disappointed that you're, like, I mean, they are

1095
00:59:37,520 --> 00:59:39,920
Speaker 2: really taking it out on you for a quote unquote

1096
00:59:40,000 --> 00:59:42,680
Speaker 2: selling out or something or you know, turning your back

1097
00:59:42,960 --> 00:59:43,600
Speaker 2: to the movement.

1098
00:59:44,600 --> 00:59:46,400
Speaker 1: I think I'm most disappointed in Elon.

1099
00:59:48,360 --> 00:59:59,800
Speaker 2: Yeah, well, on that note, it's a good stuff that

1100
01:00:00,080 --> 01:00:01,920
Speaker 2: spots to many questions.

1101
01:00:02,720 --> 01:00:05,120
Speaker 1: But but no, actually, you know, I will say, I'm

1102
01:00:05,160 --> 01:00:07,440
Speaker 1: most disappointed in myself.

1103
01:00:08,480 --> 01:00:11,160
Speaker 2: I must disappointed to regret who you were.

1104
01:00:12,040 --> 01:00:14,760
Speaker 1: I most disappointed that I didn't have courage sooner, and

1105
01:00:14,760 --> 01:00:17,640
Speaker 1: I would encourage anyone who's still in that to to

1106
01:00:17,760 --> 01:00:23,160
Speaker 1: not let a decade of regret pile up.

1107
01:00:26,000 --> 01:00:29,040
Speaker 2: I mean, it's a it's a mature thing to say,

1108
01:00:29,120 --> 01:00:32,880
Speaker 2: and and uh and it's and it look it's you know,

1109
01:00:32,880 --> 01:00:35,760
Speaker 2: I I wish you the best, and I hope you

1110
01:00:35,800 --> 01:00:38,919
Speaker 2: don't feel exploited by folks like myself on the other

1111
01:00:38,960 --> 01:00:42,600
Speaker 2: side of this that will obviously be chasing you to

1112
01:00:43,120 --> 01:00:46,040
Speaker 2: exploit the other side.

1113
01:00:46,280 --> 01:00:49,040
Speaker 1: You really believe having an open conversation, because I could

1114
01:00:49,040 --> 01:00:51,920
Speaker 1: have come on here and just been you know, thank you, governor.

1115
01:00:51,960 --> 01:00:54,120
Speaker 1: But there were things that I want to ask you

1116
01:00:54,160 --> 01:00:57,200
Speaker 1: about that just with my personal experience with tech and

1117
01:00:57,280 --> 01:01:01,640
Speaker 1: AI that I've come to the understand that okay, if

1118
01:01:01,680 --> 01:01:04,120
Speaker 1: you're going to do it, make sure that you're honest

1119
01:01:04,240 --> 01:01:07,480
Speaker 1: and you don't hold anything back. So I appreciate you

1120
01:01:07,520 --> 01:01:11,360
Speaker 1: for being open with those conversations and concerns as well.

1121
01:01:11,640 --> 01:01:14,320
Speaker 2: I appreciate it. I appreciate highlighting I mean, just a

1122
01:01:14,360 --> 01:01:17,760
Speaker 2: new age of transparency and accountability, but also what's so

1123
01:01:17,840 --> 01:01:20,400
Speaker 2: opaque and we're not even looking at in terms of

1124
01:01:20,480 --> 01:01:23,480
Speaker 2: the rules and regulations and truth and trust and so

1125
01:01:24,080 --> 01:01:26,640
Speaker 2: this has been a fun conversation, Ashley. I really appreciate

1126
01:01:26,640 --> 01:01:29,640
Speaker 2: you taking the time, and good luck with everything, and

1127
01:01:30,360 --> 01:01:31,520
Speaker 2: thanks again for joining us.

1128
01:01:31,840 --> 01:01:34,840
Speaker 1: Thank you, thank you.