1 00:00:00,640 --> 00:00:04,160 Speaker 1: Hi, I'm Molly John Fast and this is Fast Politics, 2 00:00:04,360 --> 00:00:07,120 Speaker 1: where we discussed the top political headlines with some of 3 00:00:07,160 --> 00:00:11,799 Speaker 1: today's best minds, and federal judge has halted Trump's four 4 00:00:11,880 --> 00:00:15,360 Speaker 1: hundred million dollars White House ballroom construction. 5 00:00:15,800 --> 00:00:16,400 Speaker 2: We have such a. 6 00:00:16,360 --> 00:00:20,000 Speaker 1: Great Joe for you today. The Good Liars Jason Salviag 7 00:00:20,360 --> 00:00:23,880 Speaker 1: stops by to talk about President Trump attending the Supreme 8 00:00:23,920 --> 00:00:28,040 Speaker 1: Court deliberations on First Right citizenship. Then we'll talk to 9 00:00:28,240 --> 00:00:34,240 Speaker 1: Wired's Caroline Haskins about her blockbuster reporting that the IRS 10 00:00:34,479 --> 00:00:38,160 Speaker 1: is enlisting Talenteer to help with audits. 11 00:00:38,200 --> 00:00:41,240 Speaker 3: But first the news, So Malie, yesterday we were discussing 12 00:00:41,280 --> 00:00:44,040 Speaker 3: with Charlie Sykes that what Trump says about the Iran 13 00:00:44,120 --> 00:00:46,960 Speaker 3: war is usually the opposite of what our actions are. 14 00:00:47,080 --> 00:00:50,440 Speaker 3: And here we have reporting from Axios that Trump's mixed 15 00:00:50,440 --> 00:00:52,320 Speaker 3: messages are perplexing his team. 16 00:00:52,600 --> 00:00:58,680 Speaker 1: Yeah, it's called thirty five thousand dimension chess. So many 17 00:00:59,000 --> 00:01:03,720 Speaker 1: incredibly stupid things happened yesterday. But basically this Axios reporting 18 00:01:03,840 --> 00:01:07,000 Speaker 1: is like, well, Donald Trump keeps people guessing by saying 19 00:01:07,040 --> 00:01:11,440 Speaker 1: different things at every moment, which yes he does, but 20 00:01:11,840 --> 00:01:15,680 Speaker 1: it's only because he also doesn't know what he wants 21 00:01:15,720 --> 00:01:18,800 Speaker 1: to do or what he thinks. And so we found 22 00:01:18,840 --> 00:01:22,800 Speaker 1: ourselves in this situation where Trump is offering a lot 23 00:01:22,800 --> 00:01:25,520 Speaker 1: of different answers because he doesn't have an answer, he 24 00:01:25,560 --> 00:01:27,640 Speaker 1: doesn't know what to do. He's sort of backed himself 25 00:01:27,640 --> 00:01:31,319 Speaker 1: into a corner. And the question is now can he 26 00:01:31,360 --> 00:01:33,960 Speaker 1: get himself out? And I am not convinced, you know 27 00:01:34,319 --> 00:01:37,600 Speaker 1: that this thing doesn't that he hasn't just completely lost 28 00:01:37,680 --> 00:01:39,199 Speaker 1: control of the ship at this moment. 29 00:01:39,440 --> 00:01:41,800 Speaker 3: Yeah, I think we'll really be seeing this in the 30 00:01:41,800 --> 00:01:45,920 Speaker 3: coming days. As they say, this is really the pressing moment. 31 00:01:46,200 --> 00:01:51,120 Speaker 1: Here's a quote that his sycophants are so bought into 32 00:01:51,280 --> 00:01:55,880 Speaker 1: the Trump project that we have Lindsey Graham, an unnamed 33 00:01:55,880 --> 00:01:58,360 Speaker 1: official says they had a plan for the first week 34 00:01:58,440 --> 00:02:01,000 Speaker 1: and since then they are making the plan as they 35 00:02:01,040 --> 00:02:03,120 Speaker 1: go along, which is what it looks like, right. That 36 00:02:03,240 --> 00:02:07,400 Speaker 1: makes the most sense. And that's an unnamed official. Okay. 37 00:02:07,720 --> 00:02:11,120 Speaker 1: Now others claim it's all by design. And those are 38 00:02:11,120 --> 00:02:13,320 Speaker 1: the people where you get to know their names. That's 39 00:02:13,400 --> 00:02:16,480 Speaker 1: because they want Donald Trump to know that they're saying 40 00:02:16,520 --> 00:02:19,720 Speaker 1: good things about him. So, h, Lindsey Graham, who is 41 00:02:19,760 --> 00:02:23,320 Speaker 1: Donald Trump's favorite Sicka fan, that's the plan for you, 42 00:02:23,400 --> 00:02:26,720 Speaker 1: not to have a clue. That's what Lindsay Graham said, 43 00:02:27,080 --> 00:02:31,040 Speaker 1: and Defense Secretary Pete Hegseth, also someone who keeps his 44 00:02:31,160 --> 00:02:34,560 Speaker 1: job by sucking up to Trump, said that when asked 45 00:02:34,639 --> 00:02:38,560 Speaker 1: why Trump was dangling a potential ground evasion, Heggsas said, 46 00:02:38,600 --> 00:02:43,040 Speaker 1: the point is to be unpredictable, certainly, not let anybody 47 00:02:43,120 --> 00:02:45,239 Speaker 1: know what you're willing to do or not do. 48 00:02:46,200 --> 00:02:46,799 Speaker 3: Your allies. 49 00:02:47,160 --> 00:02:49,400 Speaker 1: Yeah, and then this is the line I was looking for. 50 00:02:49,560 --> 00:02:54,120 Speaker 1: And Trump administration official claimed, it isn't three D chess, 51 00:02:54,280 --> 00:02:59,519 Speaker 1: it's twelve dimensional. He contradicts himself regularly, so no one 52 00:02:59,639 --> 00:03:03,640 Speaker 1: knows what he's thinking. It's on purpose. Guess what, guys, 53 00:03:04,120 --> 00:03:08,080 Speaker 1: he doesn't know what he's thinking, because that's what happens 54 00:03:08,160 --> 00:03:09,200 Speaker 1: when you're fucking up. 55 00:03:09,400 --> 00:03:11,359 Speaker 3: So let's put a fine point on this. I think 56 00:03:11,360 --> 00:03:13,680 Speaker 3: this is a very interesting story in a lot of ways. 57 00:03:13,800 --> 00:03:16,000 Speaker 3: We've been seeing a lot of talk this weecause a 58 00:03:16,040 --> 00:03:18,960 Speaker 3: lot of Trump people are publicly breaking with him. This 59 00:03:19,040 --> 00:03:20,760 Speaker 3: war has really set a lot of people over the 60 00:03:20,840 --> 00:03:23,800 Speaker 3: edge of particularly the podcasting class that supported him. But 61 00:03:24,000 --> 00:03:26,280 Speaker 3: one of the people most beholden to Trump that's been 62 00:03:26,400 --> 00:03:30,760 Speaker 3: very funny is Alex Jones, who's our foremost conspiracy theorist. 63 00:03:30,880 --> 00:03:32,960 Speaker 3: As his time has come, when he has been proven 64 00:03:33,040 --> 00:03:34,760 Speaker 3: right by a lot of things people said he was 65 00:03:34,760 --> 00:03:38,880 Speaker 3: crazy for He's stuck by Trump sycophantically. That ended yesterday 66 00:03:38,920 --> 00:03:41,000 Speaker 3: as he said that Trump's brain is cooked. 67 00:03:41,440 --> 00:03:44,120 Speaker 1: Yeah, so I want to pull back for a second. 68 00:03:44,440 --> 00:03:49,440 Speaker 1: It is not just that Alex Jones sucks. Alex Jones 69 00:03:49,920 --> 00:03:54,480 Speaker 1: harassed the Parkland parents to the point, right, the parents 70 00:03:54,480 --> 00:03:57,480 Speaker 1: of murdered children. He harassed them online. I mean, this 71 00:03:57,560 --> 00:04:00,560 Speaker 1: guy is hard to think of someone worse. 72 00:04:01,000 --> 00:04:03,600 Speaker 3: I think a point people also fail to make about 73 00:04:03,600 --> 00:04:06,840 Speaker 3: this is the Sandy Hook children at the Parkland ones. 74 00:04:06,960 --> 00:04:10,240 Speaker 1: Oh you're right, the Sandy Hook kindergarteners, the murdered kindergarteners. 75 00:04:10,320 --> 00:04:11,520 Speaker 1: That's how he got famous. 76 00:04:12,080 --> 00:04:14,880 Speaker 3: He did this to so many people and made up 77 00:04:14,920 --> 00:04:17,200 Speaker 3: so many stories about different people. They're just the ones 78 00:04:17,480 --> 00:04:20,800 Speaker 3: who got publicity and are ruling for themselves. But we're 79 00:04:20,839 --> 00:04:23,680 Speaker 3: literally talking about thousands of peoples whose lives he unnecessarily 80 00:04:23,760 --> 00:04:25,480 Speaker 3: ruined by just imagining things. 81 00:04:25,880 --> 00:04:29,640 Speaker 1: Right now, he no longer wants to imagine that Donald 82 00:04:29,680 --> 00:04:32,520 Speaker 1: Trump is with it. And here's the quote. When your 83 00:04:32,560 --> 00:04:35,600 Speaker 1: ankles swollow up three times the size they were before 84 00:04:35,720 --> 00:04:39,080 Speaker 1: that means heart failure, Jones said. And we've heard a 85 00:04:39,120 --> 00:04:41,680 Speaker 1: lot of people say that, I don't want to agree 86 00:04:41,760 --> 00:04:44,240 Speaker 1: with Alex Jones here, but that is actually not a 87 00:04:44,279 --> 00:04:49,320 Speaker 1: crazy conspiracy. Swollen ankles and congestive heart failure tend to 88 00:04:49,400 --> 00:04:52,160 Speaker 1: go together. That doesn't mean you die tomorrow from congestive 89 00:04:52,160 --> 00:04:55,520 Speaker 1: heart failure. He does look sick, he does babble and 90 00:04:55,680 --> 00:04:59,360 Speaker 1: sound like the brain's not doing too hot. And so 91 00:04:59,760 --> 00:05:02,760 Speaker 1: we we just cut bait on Trump and we just 92 00:05:02,880 --> 00:05:07,240 Speaker 1: mobilize against the Democrats and mobilize against the neo cons 93 00:05:07,520 --> 00:05:11,200 Speaker 1: By the way, I got some news. I got some 94 00:05:11,279 --> 00:05:15,520 Speaker 1: news for Alex Jones, and we primary them Alex Jones. 95 00:05:15,640 --> 00:05:18,080 Speaker 1: Unless you're at the Atlantic, you're not going to find 96 00:05:18,120 --> 00:05:20,560 Speaker 1: a lot of neocon Yeah. 97 00:05:20,720 --> 00:05:23,160 Speaker 3: It really is that funny thing that this is a 98 00:05:23,200 --> 00:05:26,520 Speaker 3: real man without a party type stuff, because there's not 99 00:05:26,600 --> 00:05:29,840 Speaker 3: a lot of constituency here for this stuff. Okay, so 100 00:05:30,080 --> 00:05:34,000 Speaker 3: let's talk about some more scary stupid. Trump signs sweeping 101 00:05:34,080 --> 00:05:36,560 Speaker 3: new order that aims to limit voting by mail. And 102 00:05:36,680 --> 00:05:39,480 Speaker 3: what's nice is we've seen a lot of state ags 103 00:05:39,520 --> 00:05:41,880 Speaker 3: that were really ready for this and came right out 104 00:05:41,920 --> 00:05:43,960 Speaker 3: of the gate swinging back at him. 105 00:05:44,080 --> 00:05:45,919 Speaker 1: I mean, I think we have to just assume that 106 00:05:45,960 --> 00:05:48,080 Speaker 1: Trump is going to try to mess with the midterms, 107 00:05:48,200 --> 00:05:53,120 Speaker 1: but in every which way. But the executive orders have 108 00:05:53,240 --> 00:05:55,400 Speaker 1: not so much power, so he can write a lot 109 00:05:55,400 --> 00:05:58,400 Speaker 1: of executive orders and they're not going to do shit. 110 00:05:58,800 --> 00:06:02,800 Speaker 1: What you should worry about is the Supreme Court decision 111 00:06:02,839 --> 00:06:07,320 Speaker 1: that's coming down on ballots. What you should worry about 112 00:06:07,360 --> 00:06:10,159 Speaker 1: is the Supreme Court decision that's coming down in voting rights, 113 00:06:10,400 --> 00:06:13,200 Speaker 1: the Voter Rights Act. What you shouldn't worry about is 114 00:06:13,200 --> 00:06:16,040 Speaker 1: these executive orders. I mean, except in the fact that 115 00:06:16,240 --> 00:06:19,200 Speaker 1: like people need to go to court and challenge them 116 00:06:19,240 --> 00:06:23,200 Speaker 1: so that they don't get implemented. But this stuff is 117 00:06:23,240 --> 00:06:26,960 Speaker 1: not going to do anything. And also just the irony 118 00:06:27,040 --> 00:06:29,839 Speaker 1: here for a minute, like he just voted by mail. 119 00:06:30,360 --> 00:06:33,760 Speaker 1: He literally just voted by mail. And it is also 120 00:06:33,920 --> 00:06:36,279 Speaker 1: like the voting by mail stuff is so interesting because 121 00:06:36,279 --> 00:06:40,520 Speaker 1: it's like it's not even clear. Like redistricting, his play 122 00:06:40,560 --> 00:06:44,480 Speaker 1: to redistrict those five seats in Texas, like that at 123 00:06:44,560 --> 00:06:47,479 Speaker 1: least you really thought that. I mean, it turns out 124 00:06:47,520 --> 00:06:50,000 Speaker 1: it's probably not going to help them, but it's turned 125 00:06:50,000 --> 00:06:52,320 Speaker 1: into a real demimander. But at least that made sense, Like, 126 00:06:52,680 --> 00:06:56,680 Speaker 1: it's not entirely clear that ending mail and voting is 127 00:06:56,720 --> 00:07:00,000 Speaker 1: the win for Republicans that Trump thinks it is. I mean, 128 00:07:00,040 --> 00:07:02,360 Speaker 1: and that's the other part of this. It's like it's 129 00:07:02,400 --> 00:07:05,240 Speaker 1: bad for democracy, it's bad for democratic norms, it's bad 130 00:07:05,279 --> 00:07:07,480 Speaker 1: for everyone. But it's also just may not work. I mean, 131 00:07:07,480 --> 00:07:10,600 Speaker 1: it won't work. But it's even beyond that, it's just 132 00:07:11,480 --> 00:07:13,280 Speaker 1: it's not clear that that helps his people. 133 00:07:13,520 --> 00:07:16,720 Speaker 3: Yeah, we're just over and over again seeing that these 134 00:07:16,880 --> 00:07:19,560 Speaker 3: Ross Vought type I'll do it within the system things 135 00:07:19,600 --> 00:07:22,720 Speaker 3: for Trump is not going So speaking of their attempt 136 00:07:22,840 --> 00:07:25,920 Speaker 3: to slash on PR and PBS's funding was overturned by 137 00:07:25,920 --> 00:07:26,480 Speaker 3: a judge. 138 00:07:26,680 --> 00:07:30,240 Speaker 1: Yeah, the PBS stuff was overturned by a judge and 139 00:07:30,560 --> 00:07:32,560 Speaker 1: the ballroom was stopped. 140 00:07:32,200 --> 00:07:32,880 Speaker 2: By a judge. 141 00:07:33,080 --> 00:07:36,440 Speaker 1: So those are two things, PBS and PR. This a 142 00:07:36,480 --> 00:07:39,200 Speaker 1: federal judge on Tuesday ruld that a key part of 143 00:07:39,240 --> 00:07:41,760 Speaker 1: this executive order. And by the way, this is the 144 00:07:41,840 --> 00:07:45,760 Speaker 1: thing with these executive orders, like they're just made up. Right, 145 00:07:46,000 --> 00:07:50,480 Speaker 1: it's unconstitutional blocking the administration from denying federal funds based 146 00:07:50,520 --> 00:07:53,880 Speaker 1: on an editorial viewpoint, and it really does run contrary 147 00:07:53,920 --> 00:07:57,640 Speaker 1: to the First Amendment. Right, the idea that you're going 148 00:07:57,960 --> 00:08:02,800 Speaker 1: to say, you can't because we don't like what you say. 149 00:08:03,000 --> 00:08:05,760 Speaker 1: The ruling will not reverse the Trump led campaign to 150 00:08:05,800 --> 00:08:09,880 Speaker 1: strip NPRM PBS of federal funding last summer. So it's 151 00:08:10,040 --> 00:08:13,160 Speaker 1: a win for the First Amendment, but they don't necessarily 152 00:08:13,160 --> 00:08:15,880 Speaker 1: get the money back. The court made clear that the 153 00:08:15,920 --> 00:08:19,520 Speaker 1: government cannot use funding as a lever to influence or 154 00:08:19,600 --> 00:08:22,440 Speaker 1: penalize the press, which of course is one of the 155 00:08:22,560 --> 00:08:26,680 Speaker 1: central tenants of the Mobster presidency. And by the way, 156 00:08:27,080 --> 00:08:32,440 Speaker 1: like talk about that's how Brendan Carr, the FCC chair, 157 00:08:32,720 --> 00:08:36,760 Speaker 1: has been behaving this entire time. So this was definitely 158 00:08:37,320 --> 00:08:40,400 Speaker 1: a sort of shot across the bout to the people 159 00:08:40,440 --> 00:08:45,600 Speaker 1: in this administration who have been trying to limit the 160 00:08:45,640 --> 00:08:54,120 Speaker 1: free press and stifle the First Amendment. Jason salvag is 161 00:08:54,400 --> 00:09:00,320 Speaker 1: one half of the Good Liars. Jason, welcome, Welcome, Thanks 162 00:09:00,360 --> 00:09:00,920 Speaker 1: for having me. 163 00:09:01,080 --> 00:09:01,880 Speaker 4: Always a pleasure. 164 00:09:01,880 --> 00:09:04,760 Speaker 5: We always talk about the most happy, exciting things, So 165 00:09:04,840 --> 00:09:06,120 Speaker 5: I'm excited to chat today. 166 00:09:06,360 --> 00:09:09,319 Speaker 1: Well, we're going to start by talking about something very serious, 167 00:09:09,360 --> 00:09:11,640 Speaker 1: which is Donald Trump went to the Supreme Court? 168 00:09:11,760 --> 00:09:13,720 Speaker 4: Is he actually there? Because I just have to say. 169 00:09:14,040 --> 00:09:17,160 Speaker 5: On January sixth, twenty twenty one, I was right by 170 00:09:17,160 --> 00:09:20,240 Speaker 5: the Supreme Court at the Capitol and Trump's up borders 171 00:09:20,280 --> 00:09:23,480 Speaker 5: were telling me that Donald Trump was going to walk 172 00:09:23,960 --> 00:09:26,000 Speaker 5: arm in arm with people to the Capitol. 173 00:09:26,600 --> 00:09:29,440 Speaker 4: And he did not do that. That did not happen. 174 00:09:29,880 --> 00:09:32,439 Speaker 5: So he has a history of lying, So I want 175 00:09:32,440 --> 00:09:34,000 Speaker 5: to make sure this is actually happening. 176 00:09:34,640 --> 00:09:37,959 Speaker 1: Yeah, we are told. CNN just said, we're told this 177 00:09:38,000 --> 00:09:40,839 Speaker 1: is Wolf Blitzer, so you know it's legit. We are 178 00:09:40,960 --> 00:09:44,360 Speaker 1: told President Trump has just left the Supreme Court. But 179 00:09:44,559 --> 00:09:48,280 Speaker 1: half an hour before that, Trump is sitting front row 180 00:09:48,320 --> 00:09:53,040 Speaker 1: in the Supreme Court as Justice is here arguments on 181 00:09:53,240 --> 00:09:58,360 Speaker 1: his EO on to end birthright citizenship. He is the 182 00:09:58,400 --> 00:10:04,559 Speaker 1: first sitting president to ever attend oral arguments. 183 00:10:04,720 --> 00:10:06,600 Speaker 5: Well, he's trying to find a way to make it 184 00:10:06,640 --> 00:10:10,960 Speaker 5: all about himself. And I wonder did he hackle them 185 00:10:11,040 --> 00:10:14,600 Speaker 5: at any point? Did he yell stuff out out that happen? 186 00:10:15,160 --> 00:10:16,200 Speaker 1: You lie? 187 00:10:16,840 --> 00:10:16,920 Speaker 2: No. 188 00:10:17,240 --> 00:10:22,080 Speaker 1: I could see him making that face, the mugshot face, yeah, 189 00:10:22,440 --> 00:10:27,040 Speaker 1: the right poudy face. I could see him falling asleep. 190 00:10:27,400 --> 00:10:30,720 Speaker 1: Here are some of Trump's favorite courtroom activities, because we know, 191 00:10:31,040 --> 00:10:34,160 Speaker 1: because we've seen our man in court before. Poudy face, 192 00:10:35,200 --> 00:10:39,480 Speaker 1: falling asleep, huffing, he huffs sometimes. I've heard that from 193 00:10:39,559 --> 00:10:43,640 Speaker 1: Robbie Kaplan when he does depositions, he hoffs, angry face, 194 00:10:44,080 --> 00:10:47,559 Speaker 1: his trustel kind of he tries to do Churchill a 195 00:10:47,600 --> 00:10:49,760 Speaker 1: little angry face. I want to go back to this 196 00:10:49,800 --> 00:10:52,440 Speaker 1: for a second, because Donald Trump has had a very 197 00:10:52,520 --> 00:10:56,599 Speaker 1: fraud relationship with the Supreme Court, of which he has installed. 198 00:10:56,840 --> 00:11:00,600 Speaker 1: Three justices are his right, and then two you are 199 00:11:00,640 --> 00:11:06,800 Speaker 1: practically right, So Gorsic, Barrett and uh Kavanaugh Kegstan Kavanaugh 200 00:11:06,880 --> 00:11:11,839 Speaker 1: are his. Then Alito and Thomas are basically Fox News 201 00:11:11,880 --> 00:11:14,440 Speaker 1: hosts at this point, not to put to find a 202 00:11:14,480 --> 00:11:19,640 Speaker 1: point on it. And Robert's known disliker of the Voting 203 00:11:19,720 --> 00:11:24,640 Speaker 1: Rights Act is supposedly the center, but he's you know, 204 00:11:24,880 --> 00:11:28,800 Speaker 1: so birth right citizenship. Why Donald Trump gives a fuck 205 00:11:29,120 --> 00:11:33,720 Speaker 1: about this is something to think about and sort of baffling. 206 00:11:34,120 --> 00:11:37,160 Speaker 5: Yeah, I mean, I think the reason he's there is well, 207 00:11:37,240 --> 00:11:39,440 Speaker 5: number one, he always likes to make everything about himself. 208 00:11:39,480 --> 00:11:39,839 Speaker 1: We all know. 209 00:11:40,040 --> 00:11:42,280 Speaker 4: Yeah, it's been ten to eleven years. 210 00:11:42,400 --> 00:11:45,040 Speaker 5: Gosh, this is breaking my brain whenever I think about this, 211 00:11:45,640 --> 00:11:49,319 Speaker 5: of him just trying to like interject himself, inject himself 212 00:11:49,320 --> 00:11:54,040 Speaker 5: into everything in politics and culture and everything, and him 213 00:11:54,080 --> 00:11:57,840 Speaker 5: going here, which makes no sense because number one. 214 00:11:57,840 --> 00:11:59,640 Speaker 4: He doesn't really care about the law. 215 00:12:00,400 --> 00:12:02,800 Speaker 5: He cares, he doesn't care about the finer points of 216 00:12:02,840 --> 00:12:05,360 Speaker 5: why he doesn't care about the argument. He's not gonna 217 00:12:05,360 --> 00:12:07,440 Speaker 5: be like, oh, this point that you want to that 218 00:12:07,520 --> 00:12:09,400 Speaker 5: you should have made there. It's really just about the 219 00:12:09,400 --> 00:12:12,760 Speaker 5: spectacle of of doing that and like hearing, oh I 220 00:12:12,760 --> 00:12:14,960 Speaker 5: can be one of the first presidents. I can go 221 00:12:15,000 --> 00:12:17,440 Speaker 5: and do this. This is all about me. It reminds 222 00:12:17,520 --> 00:12:20,280 Speaker 5: me of when in twenty sixteen at the RNC when 223 00:12:20,320 --> 00:12:24,000 Speaker 5: Ted Cruz was speaking and Donald Trump like showed up, 224 00:12:24,080 --> 00:12:27,040 Speaker 5: like it was like wwe raw, and like his car 225 00:12:27,080 --> 00:12:28,920 Speaker 5: pulls up and then he like shows up in the 226 00:12:28,960 --> 00:12:31,480 Speaker 5: arena and everyone cheers for him. So nobody's looking at 227 00:12:31,520 --> 00:12:34,280 Speaker 5: Ted Cruz. It's just a way to like make himself 228 00:12:34,320 --> 00:12:38,960 Speaker 5: front and center here. But like the actual ruling, I mean, 229 00:12:39,480 --> 00:12:42,720 Speaker 5: do we know what the rule? You you with your 230 00:12:42,880 --> 00:12:45,320 Speaker 5: expertise and your ear to the ground. 231 00:12:45,679 --> 00:12:49,920 Speaker 1: Well, because I'm a lawyer too, yes, No, so the 232 00:12:50,080 --> 00:12:53,040 Speaker 1: general court watcher, and you know, I think your point 233 00:12:53,080 --> 00:12:55,480 Speaker 1: is right. Donald Trump doesn't give does not care if 234 00:12:55,520 --> 00:12:58,760 Speaker 1: it's legal or illegal. So the irony of him going 235 00:12:58,800 --> 00:13:03,080 Speaker 1: to Supreme Court to try to influence their lawmaking is 236 00:13:03,160 --> 00:13:08,400 Speaker 1: pretty rich. Most people think in the in Supreme Court world, 237 00:13:08,480 --> 00:13:10,840 Speaker 1: think that this was like one of those faky cakes 238 00:13:11,080 --> 00:13:15,320 Speaker 1: cases that they took because they could rule. It was 239 00:13:15,400 --> 00:13:18,440 Speaker 1: like a feel good case where they could unanimously rule 240 00:13:18,640 --> 00:13:22,920 Speaker 1: that the Constitution gets to stay the Constitution for another day, 241 00:13:23,000 --> 00:13:26,000 Speaker 1: and then they could do all the other really craven, 242 00:13:26,160 --> 00:13:30,360 Speaker 1: really partisan things like knocking down the Voting Rights Act 243 00:13:30,480 --> 00:13:34,520 Speaker 1: and you know, killing all the whales. But which was 244 00:13:34,720 --> 00:13:37,439 Speaker 1: that's not in their review, but they set it up 245 00:13:37,480 --> 00:13:39,520 Speaker 1: so they can kill the whales. I only heard a 246 00:13:39,520 --> 00:13:41,480 Speaker 1: little bit of the oral arguments. I haven't listened to 247 00:13:41,520 --> 00:13:44,240 Speaker 1: all of it, but I did hear Roberts say something 248 00:13:44,280 --> 00:13:49,240 Speaker 1: about how old the Constitution is, which, speaking of broken brains, 249 00:13:49,280 --> 00:13:53,240 Speaker 1: like these people are pretending to be textualists, they're pretending 250 00:13:53,600 --> 00:13:56,520 Speaker 1: to be obsessed with the text of the Constitution. So 251 00:13:56,600 --> 00:13:58,480 Speaker 1: the idea that it's so old that maybe we should 252 00:13:58,520 --> 00:13:59,440 Speaker 1: throw it out now. 253 00:13:59,440 --> 00:14:00,400 Speaker 4: Which is a little bit. 254 00:14:00,440 --> 00:14:02,079 Speaker 5: You know, it's like just they made these rulies on 255 00:14:02,120 --> 00:14:04,880 Speaker 5: the Second Amendment, They've made the it's like, yeah, it's old. 256 00:14:05,080 --> 00:14:07,000 Speaker 4: Those things are old, and now we're saying. 257 00:14:06,760 --> 00:14:09,920 Speaker 5: This is the this is the part that's that's too 258 00:14:09,960 --> 00:14:10,440 Speaker 5: old here. 259 00:14:10,880 --> 00:14:11,120 Speaker 4: Yeah. 260 00:14:11,720 --> 00:14:14,040 Speaker 5: Yeah, it's like, well, I guess you know what, the 261 00:14:14,080 --> 00:14:18,719 Speaker 5: ship's going down whatever, it's the. 262 00:14:18,800 --> 00:14:24,000 Speaker 1: Larger point of lawlessness, the law and Trump's total disregard 263 00:14:24,080 --> 00:14:26,960 Speaker 1: for it, I think should be the top line here. 264 00:14:27,040 --> 00:14:29,440 Speaker 1: So even if he makes a little trip to the 265 00:14:29,480 --> 00:14:35,720 Speaker 1: Supreme Court to give dirty looks to Amy Cony Barrett 266 00:14:35,800 --> 00:14:39,880 Speaker 1: and Justice Gorsic, you know, as one does. 267 00:14:40,480 --> 00:14:41,960 Speaker 5: There was not a joke when I asked this, Did 268 00:14:42,000 --> 00:14:45,120 Speaker 5: he heckle? Did he interrupt anybody? Did that happen? 269 00:14:45,480 --> 00:14:47,840 Speaker 4: Because like I can't imagine him sitting there. 270 00:14:47,880 --> 00:14:50,000 Speaker 5: And the reason he left because it was, you know, 271 00:14:50,520 --> 00:14:52,600 Speaker 5: after thirty minutes, was he was like, oh this is boring. 272 00:14:53,000 --> 00:14:54,840 Speaker 4: Yeah, there's no cameras here, get me out of here. 273 00:14:54,880 --> 00:14:57,240 Speaker 4: I don't want to be here. That's exactly right. I 274 00:14:57,280 --> 00:14:58,960 Speaker 4: already did what said I do, so I don't want. 275 00:14:58,880 --> 00:14:59,280 Speaker 5: To be already. 276 00:14:59,520 --> 00:15:02,800 Speaker 1: Producer Jesse just sent me something. Then Marco would lose 277 00:15:02,880 --> 00:15:06,480 Speaker 1: his birthright citizenship, which may be actually why Donald Trump 278 00:15:06,560 --> 00:15:07,040 Speaker 1: is doing this. 279 00:15:07,400 --> 00:15:10,320 Speaker 5: Oh yeah, yeah, our jd vance is behind the scenes 280 00:15:10,440 --> 00:15:14,080 Speaker 5: like doing like try to pull the strigs here. 281 00:15:14,360 --> 00:15:15,840 Speaker 4: I'm next, I'm next. 282 00:15:16,080 --> 00:15:19,120 Speaker 1: Now, enough of this silliness. Let's get to a really 283 00:15:19,160 --> 00:15:22,280 Speaker 1: serious topic and one of the many reasons why you're 284 00:15:22,360 --> 00:15:27,280 Speaker 1: joining me today, you were at one of my favorite 285 00:15:27,800 --> 00:15:31,920 Speaker 1: and I don't even mean this too ironically things, which 286 00:15:31,960 --> 00:15:35,840 Speaker 1: is Seapack. So Seapac is no longer a national harbor 287 00:15:35,840 --> 00:15:40,280 Speaker 1: in scenic Maryland. It is now in Grapefield, Texas. Where 288 00:15:40,320 --> 00:15:41,640 Speaker 1: even is that it's in. 289 00:15:41,760 --> 00:15:44,120 Speaker 5: It's like right by the Dallas Fort Worth Airport, like 290 00:15:44,200 --> 00:15:45,920 Speaker 5: in between Dallas and Fort Worth. 291 00:15:46,160 --> 00:15:47,760 Speaker 4: So but it's at the Gay Ward. 292 00:15:47,840 --> 00:15:50,960 Speaker 5: It's it's the same same like looks, it's the same brand, 293 00:15:51,120 --> 00:15:53,080 Speaker 5: and it like has the big like there's like a 294 00:15:53,080 --> 00:15:56,480 Speaker 5: big glass ceiling and fountains and it has the same 295 00:15:56,640 --> 00:16:01,160 Speaker 5: feel the Gay Ward in Maryland. But it definitely did 296 00:16:01,200 --> 00:16:05,840 Speaker 5: not have any star power. Like people didn't realize Seapack 297 00:16:05,960 --> 00:16:08,440 Speaker 5: was happening. Anyone I talked to in Dallas had no 298 00:16:08,480 --> 00:16:11,600 Speaker 5: idea Seatback was there or even like some of them 299 00:16:11,600 --> 00:16:14,640 Speaker 5: were just like what seapack, But it did not. It 300 00:16:14,680 --> 00:16:18,040 Speaker 5: was not like a news story that seatback was happening 301 00:16:18,240 --> 00:16:21,040 Speaker 5: there in Dallas. And obviously the headliner wasn't there. Donald 302 00:16:21,040 --> 00:16:23,960 Speaker 5: Trump wasn't there. Ja d Vance wasn't there. Although you 303 00:16:24,000 --> 00:16:26,080 Speaker 5: can't even put them even up close to the same tier. 304 00:16:26,400 --> 00:16:28,120 Speaker 1: But Jadi Vance even wasn't there. 305 00:16:28,680 --> 00:16:31,640 Speaker 5: No, No, RFK Junior was there, and like I think, 306 00:16:31,720 --> 00:16:34,240 Speaker 5: like I said this the other day, but Ted Cruise 307 00:16:34,320 --> 00:16:36,880 Speaker 5: was like the second biggest star on Saturday, which is 308 00:16:36,880 --> 00:16:40,040 Speaker 5: like a terrible sign because it's like he is not 309 00:16:41,000 --> 00:16:43,640 Speaker 5: like he does not like put the butts in the seat, 310 00:16:43,800 --> 00:16:46,200 Speaker 5: Ted Cruise, although he likes to think of himself that way. 311 00:16:46,200 --> 00:16:49,480 Speaker 1: He the son of the Shawvron. 312 00:16:49,920 --> 00:16:52,280 Speaker 5: Yes, And actually there was a lot of Iranian people 313 00:16:52,320 --> 00:16:55,600 Speaker 5: there who were who were there, you know, supporting Donald 314 00:16:55,600 --> 00:17:00,760 Speaker 5: Trump and the quote unquote Operation not a War in 315 00:17:00,960 --> 00:17:05,040 Speaker 5: right in around right now. And that was like I 316 00:17:05,040 --> 00:17:07,240 Speaker 5: would like, I don't want to speculate on the numbers, 317 00:17:07,280 --> 00:17:10,040 Speaker 5: but it was like a large percentage of the tickets 318 00:17:10,040 --> 00:17:14,520 Speaker 5: I think were sold to them because the actual hall 319 00:17:14,680 --> 00:17:18,520 Speaker 5: where the speakers were speaking was most of the time 320 00:17:18,600 --> 00:17:20,639 Speaker 5: just not filled, like fifty percent filled. 321 00:17:21,280 --> 00:17:22,640 Speaker 1: Oh that's wild. 322 00:17:23,160 --> 00:17:25,480 Speaker 5: Yeah, So it was like it definitely didn't feel like 323 00:17:25,480 --> 00:17:27,760 Speaker 5: the seapacks of the past. 324 00:17:27,800 --> 00:17:29,120 Speaker 1: Of the times when we went. 325 00:17:29,200 --> 00:17:30,560 Speaker 4: So I love that. 326 00:17:30,640 --> 00:17:33,200 Speaker 5: You just love Seedpack You're like I love them. You're 327 00:17:33,240 --> 00:17:36,720 Speaker 5: like you were looking back at it like oh my seapack. 328 00:17:36,800 --> 00:17:37,359 Speaker 4: I love my. 329 00:17:37,800 --> 00:17:39,959 Speaker 1: Here's why I love seapack. If you're going to make 330 00:17:39,960 --> 00:17:41,280 Speaker 1: fun of me, I'm just I'm. 331 00:17:41,160 --> 00:17:44,879 Speaker 4: Not making funny. Listen, I'm just calling it like I see. 332 00:17:45,440 --> 00:17:48,119 Speaker 1: So the reason I love seapack is a couple of reasons. 333 00:17:48,160 --> 00:17:51,280 Speaker 1: One is because I think that you get to see 334 00:17:51,320 --> 00:17:55,480 Speaker 1: them the right workshop ideas. So you get to see 335 00:17:55,520 --> 00:18:01,760 Speaker 1: them start an idea, try to perfect it, see if 336 00:18:01,800 --> 00:18:04,119 Speaker 1: it works, doesn't work. Like for example, one year I 337 00:18:04,160 --> 00:18:06,800 Speaker 1: went and Donald Trump was talking about how AOC was 338 00:18:06,800 --> 00:18:09,240 Speaker 1: going to take away all your hamburgers. Remember that? 339 00:18:09,760 --> 00:18:12,720 Speaker 4: Oh yeah, yeah, that didn't last for very long though. 340 00:18:12,920 --> 00:18:15,240 Speaker 1: No, you just get to see all the sort of 341 00:18:15,359 --> 00:18:19,120 Speaker 1: way the culture war issues that they're trying to perfect. 342 00:18:19,800 --> 00:18:22,640 Speaker 1: He had a whole thing about abortion where they throw 343 00:18:22,680 --> 00:18:25,359 Speaker 1: the baby in the garbage. That did last. You know, 344 00:18:25,440 --> 00:18:28,959 Speaker 1: he just had these kind you could see these and 345 00:18:29,040 --> 00:18:32,040 Speaker 1: you'd even see it in the titles of the panels. 346 00:18:32,160 --> 00:18:34,960 Speaker 1: We are all domestic terrorists, remember that? 347 00:18:35,480 --> 00:18:39,520 Speaker 5: Yes, yeah, it. 348 00:18:39,560 --> 00:18:41,840 Speaker 4: Was a little too on the nose. Yeah it was. 349 00:18:42,160 --> 00:18:45,080 Speaker 5: This year, it seemed like one just because the attendance 350 00:18:45,200 --> 00:18:47,960 Speaker 5: was down, the ticket prices were down, like I think 351 00:18:47,960 --> 00:18:51,320 Speaker 5: it was forty seven dollars for a ticket the day before, 352 00:18:51,680 --> 00:18:54,280 Speaker 5: and usually like when Trump was there, if you just 353 00:18:54,280 --> 00:18:56,119 Speaker 5: wanted to get like and that was right for the 354 00:18:56,160 --> 00:18:59,080 Speaker 5: whole you could that's for all three or four days 355 00:18:59,359 --> 00:19:02,520 Speaker 5: was the seven dollars, and then for one day I 356 00:19:02,560 --> 00:19:03,560 Speaker 5: think when Trump. 357 00:19:03,280 --> 00:19:05,680 Speaker 4: Was speaking in twenty twenty two. 358 00:19:05,520 --> 00:19:07,480 Speaker 5: It was like two hundred and fifty or something like 359 00:19:07,520 --> 00:19:10,600 Speaker 5: that if you wanted to get like a last minute ticket. 360 00:19:10,680 --> 00:19:14,200 Speaker 5: So like that's just that there's just basic economics there. 361 00:19:14,320 --> 00:19:17,840 Speaker 5: That's like they're not selling the tickets, the prices are lower. 362 00:19:17,960 --> 00:19:20,840 Speaker 5: But it did feel like, you know, from the people 363 00:19:20,880 --> 00:19:24,040 Speaker 5: we talked to who are under the age of sixty, 364 00:19:24,560 --> 00:19:26,960 Speaker 5: that a lot of the people we talked to were 365 00:19:26,960 --> 00:19:30,040 Speaker 5: like just going to see like the death of Seapack 366 00:19:30,080 --> 00:19:33,399 Speaker 5: and just see if it really was dead. These are guys, 367 00:19:33,400 --> 00:19:36,160 Speaker 5: I'm gonna say guys, because they were men, young men 368 00:19:36,400 --> 00:19:41,080 Speaker 5: who were there who were like from the Turning Point crew. 369 00:19:41,760 --> 00:19:45,480 Speaker 5: And it became clear kind of like what the future 370 00:19:45,760 --> 00:19:49,280 Speaker 5: of the Republican Party is. And it's weird because like 371 00:19:49,320 --> 00:19:51,480 Speaker 5: you always look at Donald Trump as the and I've 372 00:19:51,520 --> 00:19:53,159 Speaker 5: I've always kind of looked at it like this, like 373 00:19:53,200 --> 00:19:55,439 Speaker 5: Donald Trump is the head of the snake. He is 374 00:19:55,560 --> 00:20:01,359 Speaker 5: like wherever he slithers, the party follows. And now it 375 00:20:01,480 --> 00:20:05,880 Speaker 5: seems like this is like a Christian nationalism, white nationalism 376 00:20:06,080 --> 00:20:09,959 Speaker 5: viewpoint that is like a little bit not that Trump 377 00:20:10,119 --> 00:20:14,119 Speaker 5: wasn't part of that, but this was something that is 378 00:20:14,160 --> 00:20:17,800 Speaker 5: like independent of Trump and is a little bit scarier 379 00:20:17,840 --> 00:20:22,960 Speaker 5: because it is so the religious aspect is so important. Yeah, 380 00:20:22,960 --> 00:20:26,480 Speaker 5: and it's kind of baked into the racist parts of 381 00:20:26,520 --> 00:20:28,600 Speaker 5: it too in a way that like, yeah, you don't 382 00:20:28,600 --> 00:20:31,520 Speaker 5: hear with Trump where Trump will be like, you know, 383 00:20:31,600 --> 00:20:34,239 Speaker 5: like they're rapists coming into the country and use all 384 00:20:34,280 --> 00:20:37,000 Speaker 5: these dog whistles, and it was never about like a 385 00:20:37,119 --> 00:20:40,400 Speaker 5: mission from God or being blessed by God or being 386 00:20:40,400 --> 00:20:43,160 Speaker 5: the people blessed by God. So it's a little terrifying 387 00:20:43,200 --> 00:20:44,879 Speaker 5: to seek kind of all that bubble up to the 388 00:20:44,920 --> 00:20:50,040 Speaker 5: surface now and knowing that like this the next generation 389 00:20:50,440 --> 00:20:53,920 Speaker 5: is not like they're the Trump generation in a way, 390 00:20:54,520 --> 00:21:00,400 Speaker 5: but it's kind of like a religious movement that I 391 00:21:00,440 --> 00:21:03,840 Speaker 5: haven't seen, you know, in my lifetime anything like that 392 00:21:03,920 --> 00:21:06,520 Speaker 5: in the United States of America. It's like a there's 393 00:21:06,560 --> 00:21:10,119 Speaker 5: like a fanaticism to it, excuse me. So it was 394 00:21:11,240 --> 00:21:12,919 Speaker 5: that part was like a little unsettling. 395 00:21:13,640 --> 00:21:16,440 Speaker 1: So let's talk about that, because that was the thing. 396 00:21:16,800 --> 00:21:18,840 Speaker 1: I mean, among other things that I really wanted to 397 00:21:18,880 --> 00:21:22,400 Speaker 1: talk to you about was this idea that the party 398 00:21:22,640 --> 00:21:26,280 Speaker 1: is now a sort of Christian nationalist party, which is 399 00:21:26,320 --> 00:21:30,920 Speaker 1: what it sounds like you're saying. I love you talk about, 400 00:21:30,960 --> 00:21:34,120 Speaker 1: Like what are the elements of it? Like I saw 401 00:21:34,160 --> 00:21:35,800 Speaker 1: an interview you did, what you talked about it and 402 00:21:35,840 --> 00:21:40,400 Speaker 1: you said there's like an expansionist manifestosity kind of element 403 00:21:40,480 --> 00:21:43,479 Speaker 1: to it. That there's can you talk about that? 404 00:21:44,400 --> 00:21:45,240 Speaker 4: Sure? Sure? 405 00:21:45,600 --> 00:21:48,399 Speaker 5: And look this is like these are from conversations with 406 00:21:48,520 --> 00:21:51,640 Speaker 5: like five people at Seedback. 407 00:21:51,840 --> 00:21:55,560 Speaker 1: This is but you see, the reason I love Seapack 408 00:21:56,320 --> 00:21:58,639 Speaker 1: is because you get stuff like this. You get to 409 00:21:58,720 --> 00:22:03,280 Speaker 1: see because you are there with the very very the 410 00:22:03,400 --> 00:22:06,920 Speaker 1: sort of most extreme. I mean not the most because 411 00:22:06,920 --> 00:22:10,960 Speaker 1: obviously they're roy Burghs, but there's it's a very extreme 412 00:22:11,040 --> 00:22:15,280 Speaker 1: group that's very interested political politically and is yeah, go. 413 00:22:15,160 --> 00:22:17,320 Speaker 5: On, but I think that those there's like crossover with 414 00:22:17,359 --> 00:22:19,879 Speaker 5: all of that. And also yeah, I mentioned that the 415 00:22:19,920 --> 00:22:22,439 Speaker 5: other night too, that like the Nick Fuentees of it 416 00:22:22,480 --> 00:22:26,520 Speaker 5: all is becoming more I don't want, yeah it is, 417 00:22:26,600 --> 00:22:28,159 Speaker 5: it is mainstream. You know, I was going to say, 418 00:22:28,200 --> 00:22:29,760 Speaker 5: for lack of a better word, but yeah, it is 419 00:22:29,840 --> 00:22:32,679 Speaker 5: kind of mainstream now and more and more people and 420 00:22:32,680 --> 00:22:34,720 Speaker 5: people you wouldn't suspect are like, yeah, I got this, 421 00:22:34,760 --> 00:22:36,840 Speaker 5: so I let this came up in my algorithm or 422 00:22:36,920 --> 00:22:40,600 Speaker 5: I'm a part of the telegram group or whatever. So 423 00:22:41,240 --> 00:22:44,160 Speaker 5: what I gathered was, you know a lot of them 424 00:22:44,200 --> 00:22:46,719 Speaker 5: believe and this is all like kind of the turning 425 00:22:46,800 --> 00:22:49,119 Speaker 5: point like this it's not even the subtext. 426 00:22:49,160 --> 00:22:50,440 Speaker 4: It's like if you just listen to some of the 427 00:22:50,440 --> 00:22:52,080 Speaker 4: stuff that Charlie Kirk was saying, this was. 428 00:22:52,040 --> 00:22:55,680 Speaker 5: Like part of it was that, you know, the United 429 00:22:55,680 --> 00:22:59,800 Speaker 5: States was blessed by God because the white Europeans who 430 00:22:59,840 --> 00:23:04,200 Speaker 5: came here and wiped out the native population, conquered the 431 00:23:04,480 --> 00:23:08,200 Speaker 5: population here. That because there was a conquering of a land, 432 00:23:08,880 --> 00:23:13,040 Speaker 5: that is a blessing from God, and there is they 433 00:23:13,080 --> 00:23:16,399 Speaker 5: are now blessed by God and this is like a 434 00:23:16,400 --> 00:23:21,320 Speaker 5: divine mission now. And because of that, there is some 435 00:23:21,359 --> 00:23:24,320 Speaker 5: sort of like a vague and like one one person 436 00:23:24,359 --> 00:23:27,000 Speaker 5: I talked to gave like a biblical reference to this, 437 00:23:27,480 --> 00:23:30,040 Speaker 5: and it was like a book. Like I'm not like 438 00:23:30,080 --> 00:23:33,080 Speaker 5: a Bible buff but like I've talked to enough people 439 00:23:33,119 --> 00:23:34,760 Speaker 5: and you know, I went to Sunday School growing up. 440 00:23:35,640 --> 00:23:37,320 Speaker 5: It was like some book in the Bible was like 441 00:23:37,359 --> 00:23:38,000 Speaker 5: what book was that? 442 00:23:38,040 --> 00:23:38,320 Speaker 2: Again? 443 00:23:40,800 --> 00:23:42,640 Speaker 4: Where is that? Is that? Like the bad I gotta 444 00:23:42,680 --> 00:23:44,280 Speaker 4: look at the index. I have to go through the 445 00:23:44,280 --> 00:23:45,320 Speaker 4: interview and see what it is. 446 00:23:45,680 --> 00:23:48,320 Speaker 5: He was like, this is the proof that America is 447 00:23:48,359 --> 00:23:50,399 Speaker 5: like this divine land and we need to keep it. 448 00:23:50,480 --> 00:23:53,600 Speaker 5: You know purre like using words like purer and things 449 00:23:53,640 --> 00:23:56,040 Speaker 5: like that, which is like another word that I would 450 00:23:56,040 --> 00:23:58,080 Speaker 5: hear whenever I would talk to people who are like 451 00:23:58,240 --> 00:24:02,440 Speaker 5: talking about the Confederate flag and how it wasn't racist. 452 00:24:02,600 --> 00:24:06,000 Speaker 5: But the thing about this was that's a little unsettling. 453 00:24:06,080 --> 00:24:08,919 Speaker 5: Is it's like you talk to at a Trump rally. 454 00:24:09,080 --> 00:24:11,119 Speaker 5: I talked to somebody with a Confederate flag and they 455 00:24:11,160 --> 00:24:14,560 Speaker 5: say something, you know, kind of terrible, and you you know, 456 00:24:15,040 --> 00:24:17,480 Speaker 5: you could tell because one they're wearing a Confederate flag 457 00:24:18,359 --> 00:24:21,120 Speaker 5: hate but they're wearing it and everyone. 458 00:24:20,760 --> 00:24:22,480 Speaker 4: Else is like that's a hateful thing, and they're like, no, 459 00:24:22,520 --> 00:24:22,760 Speaker 4: it's not. 460 00:24:23,000 --> 00:24:27,800 Speaker 5: But they're usually older and usually a little more outward 461 00:24:28,520 --> 00:24:35,800 Speaker 5: and how they feel and with this, like the people 462 00:24:35,800 --> 00:24:39,520 Speaker 5: that I talked to, one guy in particular, like it 463 00:24:39,560 --> 00:24:42,360 Speaker 5: was like a ten minutes of a conversation before I 464 00:24:42,480 --> 00:24:44,520 Speaker 5: like even made in my mind. I was like, oh, 465 00:24:44,520 --> 00:24:47,960 Speaker 5: this is like white nationalists. This is like racist, and 466 00:24:48,040 --> 00:24:50,920 Speaker 5: this is Christian nationalist. This is like using your religion 467 00:24:51,000 --> 00:24:53,600 Speaker 5: as an excuse for oppression. Because he said I want 468 00:24:53,600 --> 00:24:59,040 Speaker 5: Stephen Miller to be in charge. Yeah, he said there's 469 00:24:59,080 --> 00:25:04,359 Speaker 5: not enough deportation. We need fifty million more deportations. I 470 00:25:04,400 --> 00:25:06,720 Speaker 5: was like, is this well? I was like, am I 471 00:25:06,760 --> 00:25:10,359 Speaker 5: being trolled right now? And then like I looked up 472 00:25:10,359 --> 00:25:13,680 Speaker 5: the guy on social media and sure enough, it's been 473 00:25:13,840 --> 00:25:14,640 Speaker 5: his identity for. 474 00:25:14,600 --> 00:25:15,160 Speaker 4: A long time. 475 00:25:15,240 --> 00:25:19,320 Speaker 5: So it is much more extreme. And you can't say 476 00:25:19,320 --> 00:25:22,639 Speaker 5: this is where the whole party is going, because who knows, 477 00:25:22,720 --> 00:25:27,840 Speaker 5: but it's definitely where I think this like turning Point group, 478 00:25:28,200 --> 00:25:31,399 Speaker 5: which has become the dominant group in the conservative movement, 479 00:25:31,680 --> 00:25:36,560 Speaker 5: is going. And there's a lot more young people there 480 00:25:36,600 --> 00:25:39,879 Speaker 5: involved than in my memory have ever been involved with 481 00:25:39,920 --> 00:25:42,639 Speaker 5: a Republican party because of this religious element of it. 482 00:25:43,080 --> 00:25:45,639 Speaker 1: Yeah. You know what's interesting because it's like, what it 483 00:25:45,880 --> 00:25:50,119 Speaker 1: sounds like to me is part of the sort of 484 00:25:50,280 --> 00:25:57,560 Speaker 1: conservative movement to convince to sort of rule America. Was 485 00:25:57,680 --> 00:26:03,960 Speaker 1: this goal of getting young people to make Republicanism look cool, right, 486 00:26:04,520 --> 00:26:06,960 Speaker 1: And that was what Charlie Kirk did, right, was that 487 00:26:07,080 --> 00:26:12,000 Speaker 1: he tried to make it cool to be that type. 488 00:26:12,359 --> 00:26:14,640 Speaker 1: I think that they made it cool or they made 489 00:26:14,680 --> 00:26:19,040 Speaker 1: it appealing, right, not cool, but they somehow and in 490 00:26:19,080 --> 00:26:23,439 Speaker 1: that milane it became white nationalists. I mean, you know 491 00:26:23,640 --> 00:26:26,800 Speaker 1: they because they've basically radicalized a younger generation. 492 00:26:27,320 --> 00:26:30,359 Speaker 5: Yes, it is radicalized, just because I mean just thinking 493 00:26:30,400 --> 00:26:32,920 Speaker 5: back on like, you know, I didn't know much about 494 00:26:33,000 --> 00:26:37,520 Speaker 5: David Duke other than he was this racist guy you 495 00:26:37,560 --> 00:26:40,280 Speaker 5: know in the in the eighties and nineties, and I 496 00:26:40,320 --> 00:26:42,200 Speaker 5: didn't know he was in the KKK and all that. 497 00:26:42,320 --> 00:26:44,080 Speaker 4: And then like I like, over. 498 00:26:45,320 --> 00:26:48,960 Speaker 5: Trump's rise, I started like becoming more and more interested 499 00:26:49,000 --> 00:26:52,760 Speaker 5: in like what was he saying, Like what would he 500 00:26:52,840 --> 00:26:54,240 Speaker 5: say to the news? 501 00:26:54,520 --> 00:26:56,600 Speaker 4: Not like what was his what was in his art? 502 00:26:56,720 --> 00:26:58,800 Speaker 5: Or like you know how racist he really was and 503 00:26:58,800 --> 00:27:00,080 Speaker 5: blah blah blah. 504 00:27:00,119 --> 00:27:01,120 Speaker 4: I think is a lot. 505 00:27:01,200 --> 00:27:06,080 Speaker 5: You know, he's very close, but he was saying a 506 00:27:06,080 --> 00:27:09,360 Speaker 5: lot of similar things to what I was hearing. And 507 00:27:10,040 --> 00:27:13,920 Speaker 5: it was like people, you know, he almost was governor, right, 508 00:27:14,000 --> 00:27:15,000 Speaker 5: Like he almost. 509 00:27:14,760 --> 00:27:19,320 Speaker 4: Won in Louisiana, right, so was a governor's senate. 510 00:27:20,119 --> 00:27:24,080 Speaker 6: I just like I can't remember what, but he he, 511 00:27:25,000 --> 00:27:27,879 Speaker 6: you know, did okay and that, and we were we 512 00:27:28,000 --> 00:27:31,640 Speaker 6: kind of think like, oh, that was twenty thirty years ago. 513 00:27:31,800 --> 00:27:35,400 Speaker 5: We've moved on and we we're bigger and we're better 514 00:27:35,880 --> 00:27:38,679 Speaker 5: were then. But like, these are the same sort of 515 00:27:38,760 --> 00:27:43,399 Speaker 5: things that he was saying back then, and there was 516 00:27:43,400 --> 00:27:46,680 Speaker 5: a religious element to it, and it it's it's been 517 00:27:46,720 --> 00:27:49,080 Speaker 5: striking to be like, oh, this is just this is 518 00:27:49,119 --> 00:27:53,160 Speaker 5: a mainstream thing, Like people are saying this, and they're 519 00:27:53,200 --> 00:27:56,520 Speaker 5: saying it now because like there's so many people saying 520 00:27:56,560 --> 00:27:58,680 Speaker 5: and it's not just like one thought leader, like you're 521 00:27:58,680 --> 00:28:00,920 Speaker 5: saying it in several different ways. People we're very affable 522 00:28:01,320 --> 00:28:03,560 Speaker 5: and they're you know, they'll discuss it with you and 523 00:28:03,600 --> 00:28:06,480 Speaker 5: they'll be like, no, I'm just not racist, no, no, no, 524 00:28:06,560 --> 00:28:09,240 Speaker 5: But then if you look at what they're actually saying, 525 00:28:09,280 --> 00:28:11,119 Speaker 5: it's like, no, it is this is like this is 526 00:28:11,320 --> 00:28:16,040 Speaker 5: white nationalism and it's it's Christian nationalism. So I don't 527 00:28:16,119 --> 00:28:18,080 Speaker 5: like it. I don't like it. I want to say 528 00:28:18,080 --> 00:28:20,679 Speaker 5: that for the record. I think it's bad. It's like 529 00:28:20,760 --> 00:28:25,919 Speaker 5: with everything at take I just I should say it 530 00:28:25,960 --> 00:28:26,480 Speaker 5: on record. 531 00:28:26,520 --> 00:28:28,480 Speaker 4: I don't think it's a good thing. It's a I 532 00:28:28,520 --> 00:28:29,520 Speaker 4: don't think it's a good. 533 00:28:29,320 --> 00:28:33,320 Speaker 1: Thing now and not going anywhere. Good Jason, will you 534 00:28:33,359 --> 00:28:34,159 Speaker 1: come back please? 535 00:28:34,800 --> 00:28:35,040 Speaker 4: Yeah? 536 00:28:35,080 --> 00:28:38,240 Speaker 5: Of course, you know I will always come back and 537 00:28:38,320 --> 00:28:41,320 Speaker 5: I would do anything for you, and I hope not. 538 00:28:45,720 --> 00:28:51,880 Speaker 1: Caroline Haskins is a business reporter at Wired. Welcome, Welcome, Caroline, 539 00:28:52,080 --> 00:28:57,640 Speaker 1: Thanks for having me. So let's talk about this incredibly 540 00:28:57,760 --> 00:29:04,719 Speaker 1: scary piece. The RS wants smarter audits and they are 541 00:29:04,880 --> 00:29:09,960 Speaker 1: going to Talenteer explain to us what's going on here. 542 00:29:10,400 --> 00:29:13,960 Speaker 2: So Palenteer has actually been working with the IRS for 543 00:29:14,080 --> 00:29:17,080 Speaker 2: a number of years, but the details about most of 544 00:29:17,120 --> 00:29:20,240 Speaker 2: these contracts are pretty much at the bear basic in 545 00:29:20,320 --> 00:29:23,640 Speaker 2: terms of what's made public. So obviously whenever there's a 546 00:29:23,680 --> 00:29:27,080 Speaker 2: big Poalenteer payment, I try to send a public record 547 00:29:27,120 --> 00:29:30,280 Speaker 2: request if possible. And I got some information back on 548 00:29:30,320 --> 00:29:33,400 Speaker 2: a one point eight million dollar payment for something called 549 00:29:33,440 --> 00:29:38,000 Speaker 2: the Selection and Analytic Platform some usually abbreviated to SNAP, 550 00:29:38,080 --> 00:29:41,479 Speaker 2: which Polunteer has been building for the agency, and it 551 00:29:41,600 --> 00:29:46,000 Speaker 2: looks like that tool's specific use case is for trying 552 00:29:46,040 --> 00:29:49,120 Speaker 2: to identify the quote highest value. That was how it 553 00:29:49,160 --> 00:29:50,800 Speaker 2: was worded in one of the documents. I read. At 554 00:29:50,880 --> 00:29:54,840 Speaker 2: least cases for things like audits for collections of things 555 00:29:54,920 --> 00:30:00,160 Speaker 2: like unpaid taxes, for potential criminal investigations by looking at 556 00:30:00,280 --> 00:30:03,760 Speaker 2: unstructured data. And it doesn't really get into what types 557 00:30:03,800 --> 00:30:06,600 Speaker 2: of unstructured data it would be looking at, but it 558 00:30:06,640 --> 00:30:10,080 Speaker 2: did say that to date, the IRS has been relying 559 00:30:10,200 --> 00:30:14,840 Speaker 2: on seven hundred methods one hundred business systems, so pretty 560 00:30:14,880 --> 00:30:18,000 Speaker 2: highly splintered. So the idea there, I guess, was for 561 00:30:18,080 --> 00:30:20,600 Speaker 2: Palneer to kind of swoop in and solve these like 562 00:30:20,800 --> 00:30:22,520 Speaker 2: larger infrastructure problems. 563 00:30:22,800 --> 00:30:25,840 Speaker 1: So pre dates Dog, right, Yeah. 564 00:30:25,600 --> 00:30:29,280 Speaker 2: It definitely predates dose it's been. I mean, if you 565 00:30:29,400 --> 00:30:33,160 Speaker 2: look at some of like the federal payments, there have 566 00:30:33,240 --> 00:30:36,520 Speaker 2: actually been like additional payments kind of sparse that have 567 00:30:36,680 --> 00:30:41,040 Speaker 2: mentioned something akin to what SNAP seems to offer. And 568 00:30:41,160 --> 00:30:43,960 Speaker 2: one point eight million actually wasn't even the highest payment 569 00:30:44,080 --> 00:30:46,440 Speaker 2: that went through in twenty twenty five. There were some 570 00:30:46,480 --> 00:30:49,600 Speaker 2: other task orders that specifically mentioned SNAP. One was for 571 00:30:49,720 --> 00:30:53,040 Speaker 2: thirteen point five million. I didn't get into this in 572 00:30:53,160 --> 00:30:56,680 Speaker 2: the article in depth. Another one was for eleven point 573 00:30:56,720 --> 00:30:59,440 Speaker 2: seven million. So this is really part of like a 574 00:30:59,600 --> 00:31:03,280 Speaker 2: larger it's indicative of like a larger relationship between Talenteer 575 00:31:03,360 --> 00:31:06,160 Speaker 2: and the agency. The RS is like among the top 576 00:31:06,200 --> 00:31:08,719 Speaker 2: sub agencies, So that would be at a level of 577 00:31:08,800 --> 00:31:11,680 Speaker 2: like the army or something like ICE as opposed to 578 00:31:11,800 --> 00:31:14,800 Speaker 2: the Department of Defense or DHS. But the IRS is 579 00:31:14,840 --> 00:31:19,040 Speaker 2: like among the top like six or so agencies that 580 00:31:19,240 --> 00:31:22,200 Speaker 2: are paying Palenteer to help like provide them essentially like 581 00:31:22,280 --> 00:31:23,120 Speaker 2: tech services. 582 00:31:23,480 --> 00:31:27,840 Speaker 1: Can you explain to us sort of like where you've 583 00:31:27,880 --> 00:31:32,080 Speaker 1: written a ton about Palenteer and ICE and the ways 584 00:31:32,080 --> 00:31:35,400 Speaker 1: in which Palenteer is involved in our federal government. I 585 00:31:35,400 --> 00:31:38,240 Speaker 1: would love you to just sort of talk to us 586 00:31:38,440 --> 00:31:42,560 Speaker 1: about what parts of the government have Palenteer working in it, 587 00:31:42,800 --> 00:31:46,000 Speaker 1: and what it's doing right now, and if it's capable 588 00:31:46,040 --> 00:31:50,600 Speaker 1: of the kind of surveillance of the libs that those 589 00:31:50,600 --> 00:31:53,040 Speaker 1: of us on the LIB side are worried about. 590 00:31:53,560 --> 00:31:57,360 Speaker 2: Right So, I mean, it's pretty embedded like across parts 591 00:31:57,360 --> 00:32:00,800 Speaker 2: of the federal government. And like Palenteers, the amount of 592 00:32:00,800 --> 00:32:03,920 Speaker 2: money that it was earning in just like payments and 593 00:32:04,120 --> 00:32:06,520 Speaker 2: obligated payments, which just means they're going to be paid 594 00:32:06,520 --> 00:32:09,720 Speaker 2: at some point. It jumped hugely when Trump took office again. 595 00:32:09,800 --> 00:32:11,920 Speaker 2: It had kind of been going gradually every sense it 596 00:32:12,000 --> 00:32:14,400 Speaker 2: was founded in the early two thousands, and then I 597 00:32:14,440 --> 00:32:18,040 Speaker 2: saw for twenty twenty five that fiscal year, it got 598 00:32:18,040 --> 00:32:22,120 Speaker 2: about one billion in government contracts as opposed to like 599 00:32:22,240 --> 00:32:24,960 Speaker 2: five hundred and forty one million the year before. But yeah, 600 00:32:25,000 --> 00:32:27,880 Speaker 2: I mean it works at you know, some of these 601 00:32:27,920 --> 00:32:31,200 Speaker 2: more militant agencies. I mean also the literal military, like 602 00:32:31,240 --> 00:32:33,760 Speaker 2: it's the top sub agency it does work for is 603 00:32:33,800 --> 00:32:37,280 Speaker 2: actually the Army, and then it goes to ICE Special 604 00:32:37,320 --> 00:32:41,400 Speaker 2: Operations Command, and then it gets to more like civil matters. 605 00:32:41,440 --> 00:32:44,440 Speaker 2: But you know, obviously but something like the IRS, something 606 00:32:44,480 --> 00:32:47,320 Speaker 2: could be escalated to the level of like a criminal 607 00:32:47,360 --> 00:32:51,920 Speaker 2: investigation where like actual law enforcement is involved. But basically 608 00:32:51,920 --> 00:32:55,400 Speaker 2: what Palunteer is supposed to be doing here is solving 609 00:32:55,880 --> 00:32:59,600 Speaker 2: just this issue of a bunch of different systems that 610 00:32:59,640 --> 00:33:03,400 Speaker 2: were made at different decades, with different coding systems storing 611 00:33:03,440 --> 00:33:06,160 Speaker 2: different information. It's supposed to sit on top of that 612 00:33:06,240 --> 00:33:09,560 Speaker 2: and theoretically make it easier to work with stuff. But also, 613 00:33:09,880 --> 00:33:13,320 Speaker 2: you know, in some cases data is siloed into certain 614 00:33:13,400 --> 00:33:17,400 Speaker 2: places for privacy reasons, and we've seen under this administration 615 00:33:17,440 --> 00:33:20,480 Speaker 2: that there's been like a systematic desire to break down 616 00:33:20,560 --> 00:33:24,040 Speaker 2: some of those silos. And Talenteer is essentially they have 617 00:33:24,080 --> 00:33:27,720 Speaker 2: these things called forward deployed engineers who are essentially supposed 618 00:33:27,760 --> 00:33:30,920 Speaker 2: to respond to what the customer wants and help the 619 00:33:31,120 --> 00:33:34,200 Speaker 2: engineers that are at an agency or a company. They're 620 00:33:34,240 --> 00:33:37,040 Speaker 2: supposed to help them accomplish what they want. So it's 621 00:33:37,120 --> 00:33:40,400 Speaker 2: not that like either Palenteer has all of this data 622 00:33:40,440 --> 00:33:43,280 Speaker 2: at its own company servers. That's not exactly what it is. 623 00:33:43,400 --> 00:33:45,800 Speaker 2: It's not well, it is what it is, and it's 624 00:33:45,840 --> 00:33:49,760 Speaker 2: not that you know, talent here is directing these agencies 625 00:33:49,800 --> 00:33:53,280 Speaker 2: what to do. But whatever these agencies do want to do, 626 00:33:53,600 --> 00:33:56,880 Speaker 2: whether it's good or bad, Talenteer can at kind of 627 00:33:56,920 --> 00:33:59,880 Speaker 2: a high technical level help them facilitate that in ways 628 00:34:00,000 --> 00:34:01,680 Speaker 2: that a lot of other companies couldn't. 629 00:34:01,920 --> 00:34:07,200 Speaker 1: Is this nefarious, Is this like the way that Doge 630 00:34:07,200 --> 00:34:09,520 Speaker 1: got in there? Or do you think this is sort 631 00:34:09,520 --> 00:34:10,520 Speaker 1: of functionary. 632 00:34:11,040 --> 00:34:14,320 Speaker 2: I think there's a potential for both. It really depends 633 00:34:14,640 --> 00:34:18,920 Speaker 2: who is pushing for audits on which types of people, 634 00:34:19,080 --> 00:34:22,719 Speaker 2: on which types of potential like tax forms, things of 635 00:34:22,760 --> 00:34:25,319 Speaker 2: that nature. I mean, there's a lot of like systematic 636 00:34:25,440 --> 00:34:28,920 Speaker 2: distrust in the IRS, and I think that's only increased 637 00:34:29,000 --> 00:34:31,839 Speaker 2: under the second Trump administration. But of course there is 638 00:34:32,000 --> 00:34:35,720 Speaker 2: a functionary aspect to it, because essentially they are trying 639 00:34:35,719 --> 00:34:38,600 Speaker 2: to solve this problem of not being able to modernize 640 00:34:38,640 --> 00:34:42,160 Speaker 2: since the nineteen sixties, according to one expert I spoke with, 641 00:34:42,600 --> 00:34:45,440 Speaker 2: So there are like real problems it's trying to solve. 642 00:34:45,680 --> 00:34:48,640 Speaker 2: I think the issue of mistrust comes into play when 643 00:34:48,680 --> 00:34:52,080 Speaker 2: we're talking about, you know, the intentions of leadership, which 644 00:34:52,120 --> 00:34:54,680 Speaker 2: I can't really speak to that at the IRS, and 645 00:34:54,719 --> 00:34:57,000 Speaker 2: that wasn't really what I got into in this in 646 00:34:57,040 --> 00:35:00,200 Speaker 2: this article at least. And then the larger concerns about 647 00:35:00,360 --> 00:35:06,200 Speaker 2: Talenteers increasingly entrenched nature across a lot of different and 648 00:35:06,320 --> 00:35:10,120 Speaker 2: highly diverse federal agencies. And also one could raise fear 649 00:35:10,200 --> 00:35:13,719 Speaker 2: about vendor lock because the things that Palenteer's supposed to 650 00:35:13,760 --> 00:35:16,759 Speaker 2: be doing at these agencies is so sort of sweeping 651 00:35:17,160 --> 00:35:21,080 Speaker 2: that if you read some of these contract justifications, these 652 00:35:21,080 --> 00:35:24,480 Speaker 2: agencies consistently say it would cost a huge amount of 653 00:35:24,480 --> 00:35:26,799 Speaker 2: money to switch to a different vendor at this point. 654 00:35:26,960 --> 00:35:29,440 Speaker 2: So then you get into the situation where you have 655 00:35:29,600 --> 00:35:32,160 Speaker 2: more and more task orders, more and more money, and 656 00:35:32,280 --> 00:35:35,720 Speaker 2: more and more entrenchment getting like institution wise between these 657 00:35:36,200 --> 00:35:39,840 Speaker 2: I mean public federal agencies and you know, a private 658 00:35:39,840 --> 00:35:41,600 Speaker 2: company like Palenteer. 659 00:35:41,200 --> 00:35:43,879 Speaker 1: Right right right, Peter Thiel has had a lot of 660 00:35:44,040 --> 00:35:47,359 Speaker 1: interactions with Trump. So can you sort of explain what's 661 00:35:47,360 --> 00:35:48,680 Speaker 1: happening in that relationship. 662 00:35:48,920 --> 00:35:51,800 Speaker 2: We've seen since Trump has took office that a lot 663 00:35:51,960 --> 00:35:55,760 Speaker 2: of pretty senior like technical staff. And obviously the people 664 00:35:55,760 --> 00:35:59,640 Speaker 2: who came in with DOJE either were directly coming from 665 00:35:59,760 --> 00:36:02,840 Speaker 2: or had worked for a company that had been funded 666 00:36:02,840 --> 00:36:06,400 Speaker 2: by Peter Teel. So this obviously includes Talenteer, it includes 667 00:36:06,440 --> 00:36:09,840 Speaker 2: other one like other ones like Anderill, it includes fellows 668 00:36:09,960 --> 00:36:14,759 Speaker 2: through Peter Tele's like personally selected fellowship program. There's the 669 00:36:14,800 --> 00:36:17,319 Speaker 2: Founder's fund that funds a lot of different types of 670 00:36:17,800 --> 00:36:22,279 Speaker 2: VC ventures. So I mean compared to the previous administration 671 00:36:22,400 --> 00:36:25,400 Speaker 2: and the first Trump administration. To be sure, there's definitely 672 00:36:25,440 --> 00:36:29,560 Speaker 2: a lot more people with ties or direct work experience 673 00:36:30,000 --> 00:36:32,480 Speaker 2: going back to you know, one of these companies that 674 00:36:32,840 --> 00:36:36,759 Speaker 2: was received financing from Peter Teel, And yeah, this was 675 00:36:36,800 --> 00:36:40,120 Speaker 2: definitely more visible when Musk was kind of at the 676 00:36:40,120 --> 00:36:42,600 Speaker 2: peak of his government involvement, but there was obviously a 677 00:36:42,600 --> 00:36:45,600 Speaker 2: lot of other people coming from like SpaceX and the like. 678 00:36:45,800 --> 00:36:48,600 Speaker 2: But yeah, I think that's the senior now SI administrator. 679 00:36:48,840 --> 00:36:52,200 Speaker 1: A lot of people say that Elon is still very 680 00:36:52,360 --> 00:36:56,520 Speaker 1: much that even though he doesn't necessarily work in government 681 00:36:56,840 --> 00:37:00,680 Speaker 1: right now that his Doge people are pretty ensconced DEZINGK. 682 00:37:00,719 --> 00:37:01,280 Speaker 1: That's true. 683 00:37:01,360 --> 00:37:04,280 Speaker 2: And if so, where I mean the nature of dose 684 00:37:04,360 --> 00:37:07,279 Speaker 2: has changed. I mean there are some staffers that have 685 00:37:07,520 --> 00:37:11,440 Speaker 2: you know, obviously my coworkers McKenna and Vittorio could speak 686 00:37:11,520 --> 00:37:14,520 Speaker 2: a lot more like specifically to this, but the nature 687 00:37:14,560 --> 00:37:19,080 Speaker 2: of it has changed from a more aggressive, visible operation 688 00:37:19,280 --> 00:37:22,759 Speaker 2: to something that's a little bit more like institutionalized at 689 00:37:22,760 --> 00:37:25,520 Speaker 2: this point, with those staffers that are remaining taking on 690 00:37:25,760 --> 00:37:29,480 Speaker 2: different roles in like the Digital Service, which just kind 691 00:37:29,480 --> 00:37:31,880 Speaker 2: of took on a different name and evolved under the 692 00:37:31,880 --> 00:37:35,440 Speaker 2: second Trump administration, but I think it was originally founded 693 00:37:35,719 --> 00:37:39,400 Speaker 2: under the Obama administration, but then the sort of like 694 00:37:39,480 --> 00:37:43,560 Speaker 2: agency mandate and obviously like the constitution of its staffers 695 00:37:43,760 --> 00:37:46,040 Speaker 2: changed a lot. Yeah, since Trump took off this again. 696 00:37:46,160 --> 00:37:49,600 Speaker 1: I wonder if you could talk about you have all 697 00:37:49,640 --> 00:37:54,320 Speaker 1: of these private companies in the federal government, you have Pallenteer, 698 00:37:54,520 --> 00:37:58,279 Speaker 1: you have different sort of DOGE like groups trying to 699 00:37:58,360 --> 00:38:01,120 Speaker 1: make things more effective whatever that means. Is it working. 700 00:38:02,000 --> 00:38:05,000 Speaker 2: Yeah, I mean you can look at an agency like 701 00:38:05,080 --> 00:38:07,640 Speaker 2: the IRS, and I think I mentioned some of these 702 00:38:07,719 --> 00:38:11,080 Speaker 2: numbers and the piece, but it's lost over a quarter 703 00:38:11,120 --> 00:38:13,920 Speaker 2: of its staffers since Trump took office, and this is 704 00:38:13,920 --> 00:38:19,279 Speaker 2: an agency that has already been historically under resourced. And 705 00:38:19,680 --> 00:38:22,600 Speaker 2: as one expert told me, it's also sort of difficult 706 00:38:22,640 --> 00:38:26,239 Speaker 2: to find political will to allocate more resources to an 707 00:38:26,239 --> 00:38:31,040 Speaker 2: agency that's unpopular. But I mean, we've seen across like 708 00:38:31,200 --> 00:38:34,120 Speaker 2: pretty much every single federal agency at this point, a 709 00:38:34,120 --> 00:38:37,600 Speaker 2: lot of people taking these offers for early retirement, for 710 00:38:37,760 --> 00:38:40,239 Speaker 2: a deferred resignation. I think that was the term that 711 00:38:40,280 --> 00:38:43,400 Speaker 2: they use. And I don't know for a lot of 712 00:38:43,400 --> 00:38:46,799 Speaker 2: these agencies that already are kind of trying to find 713 00:38:46,840 --> 00:38:50,880 Speaker 2: the best ways to you know, govern and work efficiently. 714 00:38:51,360 --> 00:38:54,680 Speaker 2: It doesn't help when you just don't have the institutional 715 00:38:54,719 --> 00:38:59,080 Speaker 2: knowledge and manpower to literally get things done. It just 716 00:38:59,200 --> 00:39:01,279 Speaker 2: kind of, you know, it would be one thing if 717 00:39:01,320 --> 00:39:04,400 Speaker 2: you wanted to spend less money on I don't know 718 00:39:05,000 --> 00:39:08,600 Speaker 2: xyz specific thing, but I think when you're getting when 719 00:39:08,600 --> 00:39:12,800 Speaker 2: you're you know, systematically putting in a brain drain at 720 00:39:13,080 --> 00:39:17,960 Speaker 2: these really large and difficult to function agencies, it's you know, 721 00:39:18,680 --> 00:39:21,680 Speaker 2: I'm not sure that that's the first path ticket to 722 00:39:21,719 --> 00:39:23,680 Speaker 2: be more efficient. I think this would be, to put 723 00:39:23,680 --> 00:39:24,520 Speaker 2: it mildly. 724 00:39:24,840 --> 00:39:30,080 Speaker 1: I wonder if we could just talk for another minute 725 00:39:30,320 --> 00:39:36,480 Speaker 1: about this AI. So, like HSS is using AI tools 726 00:39:36,520 --> 00:39:40,719 Speaker 1: to target DEI and gender ideology and grants. We saw 727 00:39:40,880 --> 00:39:48,560 Speaker 1: that had some very mixed success. It seems very rudimentary, 728 00:39:49,160 --> 00:39:53,520 Speaker 1: Like is AI doing things that I can't possibly understand? 729 00:39:54,080 --> 00:39:57,040 Speaker 2: I mean in some of these cases, like you know, 730 00:39:57,239 --> 00:40:00,640 Speaker 2: grant selection. I mean we know that the these agencies 731 00:40:00,680 --> 00:40:04,920 Speaker 2: were essentially given a list of keywords to try and 732 00:40:05,239 --> 00:40:09,480 Speaker 2: weed out and re examine. And I'm not exactly sure 733 00:40:09,800 --> 00:40:14,200 Speaker 2: how much AI would improve that process more than like 734 00:40:14,520 --> 00:40:15,919 Speaker 2: a keyword search. 735 00:40:16,160 --> 00:40:19,520 Speaker 1: Right exactly. That that's what I don't understand. 736 00:40:20,040 --> 00:40:22,400 Speaker 2: Yeah, I mean we know that it was being used 737 00:40:22,520 --> 00:40:26,560 Speaker 2: at least in the cage of HHS to generate summaries 738 00:40:26,640 --> 00:40:29,520 Speaker 2: in certain cases, but then that just kind of takes 739 00:40:29,560 --> 00:40:33,040 Speaker 2: out the human work of thinking through something. And I mean, 740 00:40:33,760 --> 00:40:36,680 Speaker 2: these are studies that affect you know, real people and 741 00:40:36,760 --> 00:40:40,200 Speaker 2: real lives, and you know, obviously a lot of scientific 742 00:40:40,239 --> 00:40:43,880 Speaker 2: studies that involve gender is or you know, inequality is 743 00:40:43,920 --> 00:40:47,799 Speaker 2: about you know, real inequality and health based outcomes, and 744 00:40:48,200 --> 00:40:50,759 Speaker 2: you know, just not having adequate data on a lot 745 00:40:50,760 --> 00:40:54,920 Speaker 2: of groups. But yeah, I mean the HHS disclosures and 746 00:40:55,200 --> 00:40:57,759 Speaker 2: the disclosures about AI made a lot of these other 747 00:40:57,840 --> 00:41:02,640 Speaker 2: agencies because yeah, palent here was supposedly used to help it, 748 00:41:02,840 --> 00:41:07,680 Speaker 2: you know, weed out rants that supposedly violated this executive order. 749 00:41:07,760 --> 00:41:12,479 Speaker 2: But it doesn't detail exactly how much this improved upon 750 00:41:13,160 --> 00:41:15,760 Speaker 2: you know, just kind of going through it manually, Yeah, 751 00:41:15,840 --> 00:41:17,440 Speaker 2: or improve those outcomes at all, you know. 752 00:41:17,840 --> 00:41:21,440 Speaker 1: Yeah, thank you, thank you, thank you, Ken, thank you 753 00:41:21,480 --> 00:41:27,920 Speaker 1: so much. A momentlefecly Jesse Canon. 754 00:41:28,080 --> 00:41:31,319 Speaker 3: It's my when we think of the Republican Party, which 755 00:41:31,440 --> 00:41:34,359 Speaker 3: loves to think of itself as law and order, you know, 756 00:41:34,440 --> 00:41:36,960 Speaker 3: we're going to put the bad guys in jail, make 757 00:41:37,000 --> 00:41:41,200 Speaker 3: sure they get cuffs. This administration has done everything it 758 00:41:41,360 --> 00:41:44,560 Speaker 3: possibly can to burn down that reputation, and this new 759 00:41:44,600 --> 00:41:48,800 Speaker 3: report from Pro Publica really really you'd say, puts a 760 00:41:48,840 --> 00:41:51,080 Speaker 3: bow on it, puts a cherry on top. I feel 761 00:41:51,080 --> 00:41:53,960 Speaker 3: like this is a cherry factory of twenty three thousand cherries. 762 00:41:54,280 --> 00:41:57,640 Speaker 1: Yes, so Trump's DJ, which is basically Trump has been 763 00:41:57,719 --> 00:42:01,160 Speaker 1: using to like settle scores and go after his enemies 764 00:42:01,200 --> 00:42:04,040 Speaker 1: and not do any of the stuff that it's supposed 765 00:42:04,080 --> 00:42:07,440 Speaker 1: to be doing that DOJ. We're sort of getting the 766 00:42:07,520 --> 00:42:11,520 Speaker 1: receipts on that stuff, and that is what we're watching here. 767 00:42:11,640 --> 00:42:16,560 Speaker 1: So the administration quietly abandoned more than twenty three thousand 768 00:42:16,800 --> 00:42:20,520 Speaker 1: criminal cases within the first six months of his presidency, 769 00:42:21,000 --> 00:42:27,040 Speaker 1: eleven thousand in the first month. This is insane, okay. 770 00:42:27,320 --> 00:42:33,520 Speaker 1: These are like rapes and murders and crimes criminal cases. 771 00:42:33,600 --> 00:42:38,440 Speaker 1: These are crimes that they just decided not to focus 772 00:42:38,520 --> 00:42:48,120 Speaker 1: on because they wanted to go after Jerome Powell and 773 00:42:48,560 --> 00:42:52,160 Speaker 1: Alvin Bragg. I mean, this is insane. So they pulled 774 00:42:52,239 --> 00:42:58,280 Speaker 1: back from thousands of cases drug trafficking, terrorism, fraud, money laundering, 775 00:42:58,360 --> 00:43:03,640 Speaker 1: and white collar crime to focus on immigration like people 776 00:43:03,719 --> 00:43:07,800 Speaker 1: who overstay their visas, students who overstay their visas instead 777 00:43:07,800 --> 00:43:11,680 Speaker 1: of drug trafficking and terrorism, fraud, money laundering. I mean 778 00:43:11,719 --> 00:43:15,640 Speaker 1: things like think about a world where we're not prosecuting 779 00:43:15,840 --> 00:43:20,640 Speaker 1: terrorism cases, Like do you think that America is safer 780 00:43:21,000 --> 00:43:24,960 Speaker 1: when we're picking up the guys who work in the 781 00:43:25,040 --> 00:43:28,040 Speaker 1: home depot who you know, the day laborers and the 782 00:43:28,040 --> 00:43:33,040 Speaker 1: home depot parking lot, versus prosecuting the people who are 783 00:43:33,120 --> 00:43:36,840 Speaker 1: doing fraud and funding terrorism. Personally, I would rather have 784 00:43:36,880 --> 00:43:42,360 Speaker 1: the people funding terrorism be prosecuted versus the day laborers 785 00:43:42,560 --> 00:43:45,960 Speaker 1: who are trying to feed their families one hundred percent. 786 00:43:47,120 --> 00:43:51,680 Speaker 1: That's it for this episode of Fast Politics. Tune in 787 00:43:51,800 --> 00:43:57,240 Speaker 1: every Monday, Wednesday, Thursday, and Saturday to hear the best 788 00:43:57,320 --> 00:44:01,640 Speaker 1: minds and politics make sense of all this chaos. If 789 00:44:01,640 --> 00:44:04,720 Speaker 1: you enjoy this podcast, please send it to a friend 790 00:44:05,160 --> 00:44:08,360 Speaker 1: and keep the conversation going. Thanks for listening.