1 00:00:01,840 --> 00:00:04,560 Speaker 1: Hi, It's Peter Schweizer and Eric Edgers. We are filling 2 00:00:04,600 --> 00:00:07,160 Speaker 1: in for Sean. You can join the conversation at one 3 00:00:07,200 --> 00:00:10,000 Speaker 1: eight hundred and nine four one seven three two six. 4 00:00:10,360 --> 00:00:14,160 Speaker 1: You can find our podcast at the drilldown dot com. 5 00:00:14,200 --> 00:00:16,840 Speaker 1: A topic that I know is important to you, Eric 6 00:00:16,840 --> 00:00:18,960 Speaker 1: and important to me is big Tech. We talked a 7 00:00:19,000 --> 00:00:21,360 Speaker 1: little bit about Twitter, the role they played, but it's 8 00:00:21,400 --> 00:00:24,440 Speaker 1: about more than just Twitter. It's absolutely about more than 9 00:00:24,480 --> 00:00:26,920 Speaker 1: just Twitter. It's about American elections, and I think it's 10 00:00:26,960 --> 00:00:29,800 Speaker 1: about one of the fundamental tenets of what we talk 11 00:00:29,840 --> 00:00:33,680 Speaker 1: about and investigate and expose at the Government Accountability Institute, 12 00:00:33,720 --> 00:00:36,519 Speaker 1: and that's the fact that, contrary to what many people believe, 13 00:00:37,040 --> 00:00:41,120 Speaker 1: big business and big government are not enemies. They're actually friends, absolutely. 14 00:00:41,120 --> 00:00:43,600 Speaker 1: And who is the biggest business in the Biden administration? 15 00:00:44,000 --> 00:00:47,320 Speaker 1: But big Tech? Now you starred in and we both 16 00:00:47,360 --> 00:00:49,960 Speaker 1: co produced a documentary that you can see on Amazon 17 00:00:50,040 --> 00:00:52,040 Speaker 1: called The Creepy Line. And one of the things that 18 00:00:52,440 --> 00:00:56,200 Speaker 1: this documentary came out in twenty eighteen exposed was the 19 00:00:56,240 --> 00:01:00,360 Speaker 1: idea that the role that Google could play in altering 20 00:01:00,440 --> 00:01:03,480 Speaker 1: what people could see and filter what people couldn't see, 21 00:01:03,560 --> 00:01:07,120 Speaker 1: and the way that might shape outcomes in elections, and 22 00:01:07,360 --> 00:01:10,000 Speaker 1: doctor Robert Epstein who was sort of a central scientist, 23 00:01:10,000 --> 00:01:13,360 Speaker 1: and that exposed that votes could be shifted up to 24 00:01:13,360 --> 00:01:15,920 Speaker 1: twenty percent. So we thought that was a big deal 25 00:01:15,959 --> 00:01:18,280 Speaker 1: in twenty eighteen. We never would have expected what we're 26 00:01:18,319 --> 00:01:20,840 Speaker 1: now learning more and more every day that Twitter and 27 00:01:20,880 --> 00:01:23,680 Speaker 1: other big tech companies did for the twenty twenty election. 28 00:01:23,959 --> 00:01:27,160 Speaker 1: That's exactly right. Well, you know, we were outsiders looking 29 00:01:27,280 --> 00:01:30,920 Speaker 1: inside at big tech. But we're fortunate because we have 30 00:01:31,120 --> 00:01:34,360 Speaker 1: someone on the line who is actually an insider, Kara Frederick. 31 00:01:34,480 --> 00:01:37,480 Speaker 1: She's the director of Tech Policy at the Heritage Foundation. 32 00:01:37,560 --> 00:01:42,640 Speaker 1: But before that, Kara was a Facebook intelligence analyst. Kara, 33 00:01:42,760 --> 00:01:45,000 Speaker 1: thanks so much for joining us on the Sean Hannity Show. 34 00:01:45,720 --> 00:01:48,720 Speaker 1: Of course. Well, so I've got to ask you. I've 35 00:01:48,720 --> 00:01:51,560 Speaker 1: been dying to ask you. What does a Facebook intelligence 36 00:01:51,600 --> 00:01:55,880 Speaker 1: analysts do a number of things. So I worked in 37 00:01:55,920 --> 00:01:59,880 Speaker 1: global security and it's called Global Security Intelligence and Investigation. 38 00:02:00,200 --> 00:02:02,520 Speaker 1: And what I did was I helped start and run 39 00:02:02,560 --> 00:02:06,600 Speaker 1: the counter terrorism Analysis program, So we were effectively looking 40 00:02:06,640 --> 00:02:10,160 Speaker 1: at foreign Islamic terrorism on the platform. So if there 41 00:02:10,200 --> 00:02:13,800 Speaker 1: were any sort of propaganda, we called it sort of 42 00:02:13,880 --> 00:02:17,959 Speaker 1: cheerleading for terrorists. Our job was to identify these individuals 43 00:02:18,160 --> 00:02:20,560 Speaker 1: and pitch them over to the content moderation team, the 44 00:02:20,639 --> 00:02:23,960 Speaker 1: community operations team, and sort of act as that central 45 00:02:24,080 --> 00:02:27,119 Speaker 1: focal point for the policy team as well to get 46 00:02:27,160 --> 00:02:30,280 Speaker 1: all of the information about the terrorists, their networks, and 47 00:02:30,880 --> 00:02:33,960 Speaker 1: effectively get them off the platform. We called it making 48 00:02:34,080 --> 00:02:38,400 Speaker 1: the platform hostel to these specific actors so noble purpose. 49 00:02:38,800 --> 00:02:40,800 Speaker 1: I did the same sort of thing in the intelligence 50 00:02:40,840 --> 00:02:43,600 Speaker 1: community for the US government, went over the Facebook to 51 00:02:43,600 --> 00:02:47,360 Speaker 1: sort of recreate all of that those mechanisms, those muscle memories. 52 00:02:47,400 --> 00:02:49,840 Speaker 1: And it appears that we did our job too well 53 00:02:49,880 --> 00:02:53,200 Speaker 1: and now they're using it for a little more sinister purposes. Well, 54 00:02:53,240 --> 00:02:55,440 Speaker 1: that's the interesting question I wanted to ask you. I 55 00:02:55,480 --> 00:02:58,639 Speaker 1: think most people would say what you just describe, what 56 00:02:58,680 --> 00:03:01,440 Speaker 1: you did with Facebook is essential. We've got to make 57 00:03:01,440 --> 00:03:05,080 Speaker 1: sure social media is not fostering terrorism or criminal activity. 58 00:03:05,480 --> 00:03:08,040 Speaker 1: But how do you draw the line? What would you 59 00:03:08,120 --> 00:03:10,840 Speaker 1: say is the problem? Because clearly, in the case of Twitter, 60 00:03:11,560 --> 00:03:13,400 Speaker 1: and I'm sure in the case of Facebook, they're no 61 00:03:13,400 --> 00:03:17,519 Speaker 1: longer censoring just people because of their violent, criminal intent. 62 00:03:17,880 --> 00:03:20,160 Speaker 1: They're doing it for political reasons. So how do you 63 00:03:20,240 --> 00:03:22,040 Speaker 1: draw the line and how do you hold these big 64 00:03:22,080 --> 00:03:24,239 Speaker 1: tech firms an account for what they're doing here to 65 00:03:24,320 --> 00:03:28,000 Speaker 1: a First Amendment standard. So it is very important I think, 66 00:03:28,040 --> 00:03:31,239 Speaker 1: at least for the government to communicate with these companies 67 00:03:31,400 --> 00:03:35,280 Speaker 1: if it's confined to things like child sexual abuse material 68 00:03:35,440 --> 00:03:38,440 Speaker 1: see SAM. When you know you have predators on these 69 00:03:38,440 --> 00:03:41,240 Speaker 1: platforms trying to exploit children, okay, you can talk to 70 00:03:41,280 --> 00:03:44,480 Speaker 1: the FBI about it. You can get removed these predators 71 00:03:44,760 --> 00:03:48,320 Speaker 1: frankly from the digital space and roll them up if 72 00:03:48,320 --> 00:03:51,920 Speaker 1: you have to arrest them. However, when you start using 73 00:03:52,240 --> 00:03:55,119 Speaker 1: all of the like I said, those avenues that you've 74 00:03:55,120 --> 00:03:58,920 Speaker 1: created to police the speech of Americans that does not 75 00:03:59,080 --> 00:04:01,640 Speaker 1: adhere to a First then the standard whatsoever, it doesn't 76 00:04:01,640 --> 00:04:04,680 Speaker 1: even get close to one, then I think you run 77 00:04:04,680 --> 00:04:07,160 Speaker 1: into problems. So you have to keep it to things 78 00:04:07,200 --> 00:04:09,560 Speaker 1: like foreign Islamic terrorism. You have to keep it to 79 00:04:09,880 --> 00:04:12,840 Speaker 1: see SAM, child sexual abuse material. But once you start 80 00:04:12,880 --> 00:04:17,040 Speaker 1: to get into the game of policing legitimate political perspectives 81 00:04:17,040 --> 00:04:20,200 Speaker 1: and viewpoints, then you've lost the plot. So if you 82 00:04:20,240 --> 00:04:23,400 Speaker 1: could draw a bright line between that foreign terrorism and 83 00:04:23,680 --> 00:04:26,880 Speaker 1: you know what they're doing when it comes to American speech, 84 00:04:27,120 --> 00:04:29,799 Speaker 1: all the better, I will say. Peter, though, at this point, 85 00:04:30,120 --> 00:04:33,000 Speaker 1: I don't trust these companies to do that, given the 86 00:04:33,400 --> 00:04:36,960 Speaker 1: fact that the specter of the Trump Russia collusion hoax 87 00:04:37,160 --> 00:04:40,280 Speaker 1: was the justification and that sort of hanging over the 88 00:04:40,279 --> 00:04:44,159 Speaker 1: heads of all of these executives of these companies. They 89 00:04:44,320 --> 00:04:47,120 Speaker 1: use that, you know, foreign malign influence to start policing 90 00:04:47,160 --> 00:04:50,960 Speaker 1: the speech of Americans, to expunge users for jokes on 91 00:04:51,000 --> 00:04:54,080 Speaker 1: the platform. It's very, very disy territory, and in the 92 00:04:54,080 --> 00:04:56,320 Speaker 1: absence of that bright line, I'd say they have to 93 00:04:56,320 --> 00:04:59,559 Speaker 1: get out of the business altogether. Is that the tipping point, 94 00:05:00,080 --> 00:05:02,520 Speaker 1: because I think nobody has a problem with the idea of, hey, 95 00:05:02,520 --> 00:05:04,760 Speaker 1: we're gonna use social media, we're going to coordinate with 96 00:05:05,040 --> 00:05:07,720 Speaker 1: National security and Department Homeland Security to like make sure 97 00:05:08,040 --> 00:05:11,440 Speaker 1: that America is protected from threats foreign and domestic. But 98 00:05:11,480 --> 00:05:14,599 Speaker 1: that's very different than hey, here's the story that's possibly 99 00:05:14,640 --> 00:05:18,760 Speaker 1: misinformation about COVID or here's a story about Hunter Biden's laptop. 100 00:05:18,960 --> 00:05:22,440 Speaker 1: When did you see the line start to shift? Yeah, 101 00:05:22,480 --> 00:05:27,520 Speaker 1: I think that's when they blended the national security justifications 102 00:05:27,640 --> 00:05:31,080 Speaker 1: into this whole idea that you know, police COVID speech, 103 00:05:31,080 --> 00:05:33,440 Speaker 1: et cetera. So, like I said, when it came to 104 00:05:34,120 --> 00:05:36,920 Speaker 1: when it came to Trump's election in twenty sixteen, there 105 00:05:37,000 --> 00:05:39,440 Speaker 1: is a lot of self flagellation, you know, within Facebook, 106 00:05:39,520 --> 00:05:42,599 Speaker 1: within other social media companies, because the media painted this 107 00:05:42,760 --> 00:05:46,480 Speaker 1: narrative of these companies handed the election to Trump. And 108 00:05:46,520 --> 00:05:49,560 Speaker 1: then when you layer on that Russia collision, Okay, all 109 00:05:49,600 --> 00:05:52,200 Speaker 1: of a sudden you have that ding dinging foreign malign 110 00:05:52,400 --> 00:05:56,040 Speaker 1: influenced tag, and so I think they use that to 111 00:05:56,080 --> 00:05:59,400 Speaker 1: sort of make inroads into the policing American speech, the 112 00:05:59,480 --> 00:06:04,400 Speaker 1: domestic game unfortunately. So yeah, in terms of you know, 113 00:06:05,200 --> 00:06:07,679 Speaker 1: letting it bleed over, I think you have to stop 114 00:06:07,720 --> 00:06:12,400 Speaker 1: them at that point. You have to say, foreign influence campaigns, okay, 115 00:06:12,480 --> 00:06:15,320 Speaker 1: but when it comes to domestic Americans, even if they're 116 00:06:15,360 --> 00:06:18,039 Speaker 1: unwillingly spreading this kind of thing, you have to let 117 00:06:18,080 --> 00:06:20,800 Speaker 1: Americans talk. We have free speech here for a reason. 118 00:06:21,560 --> 00:06:24,280 Speaker 1: It's almost like you guys built a weapon to try 119 00:06:24,279 --> 00:06:28,039 Speaker 1: to protect the country from Islamic terrorism and other types 120 00:06:28,080 --> 00:06:31,640 Speaker 1: of threats, like you said, child sexual imagery, and then 121 00:06:31,680 --> 00:06:36,040 Speaker 1: when people's cultural and political sensitivities were so dramatically offended 122 00:06:36,080 --> 00:06:39,159 Speaker 1: because they're so monolithic within big tech, they're like, well, 123 00:06:39,160 --> 00:06:41,720 Speaker 1: we do have this weapon, and so we could use 124 00:06:41,760 --> 00:06:46,080 Speaker 1: it for this exactly. And that's the story of tech really, 125 00:06:46,560 --> 00:06:50,000 Speaker 1: you know, from Time memorium, right, So you have just 126 00:06:50,160 --> 00:06:52,240 Speaker 1: saying that we sometimes say, if you build it, they 127 00:06:52,279 --> 00:06:55,080 Speaker 1: will come, right, a playoff of the Robbert reference to 128 00:06:55,200 --> 00:06:58,360 Speaker 1: the teams. And if you build these tools, they're gonna 129 00:06:58,360 --> 00:07:01,600 Speaker 1: get used for nefarious purposes. You might have all of 130 00:07:01,640 --> 00:07:04,359 Speaker 1: the best intentions in the world, but it's sort of 131 00:07:04,400 --> 00:07:07,520 Speaker 1: like the chat GPT that everybody's talking about. This AI, 132 00:07:07,680 --> 00:07:10,960 Speaker 1: this machine learning tool that can effectively use a computer 133 00:07:11,040 --> 00:07:13,679 Speaker 1: to spit out language that sounds as if the human 134 00:07:13,760 --> 00:07:16,440 Speaker 1: has created it. You know, your people are gonna use 135 00:07:16,440 --> 00:07:18,840 Speaker 1: it for ill even if you have the best of intentions. 136 00:07:19,120 --> 00:07:21,480 Speaker 1: This is what happened in these tech companies. You know, 137 00:07:21,560 --> 00:07:24,800 Speaker 1: you try to get child predators off the platform, you 138 00:07:24,880 --> 00:07:27,720 Speaker 1: try to prevent terrorists from recruiting on these platforms, and 139 00:07:27,800 --> 00:07:30,160 Speaker 1: it's gonna bleed over, as you said, because of the 140 00:07:30,200 --> 00:07:33,080 Speaker 1: ideological proclivities of a lot of people in charge. And 141 00:07:33,120 --> 00:07:36,480 Speaker 1: the SBI didn't help. They ran an influence campaign themselves. 142 00:07:37,520 --> 00:07:39,720 Speaker 1: So we're talking to Kara Frederick. She's the director of 143 00:07:39,760 --> 00:07:44,080 Speaker 1: Tech Policy the Heritage Foundation and a former Facebook intelligence analyst. 144 00:07:44,560 --> 00:07:46,120 Speaker 1: You know, Kara, I want to get your take on 145 00:07:46,200 --> 00:07:50,120 Speaker 1: the Twitter dump that we're seeing. I went into this thinking, well, 146 00:07:50,160 --> 00:07:55,040 Speaker 1: this is just Twitter massively censoring. Twitter employees were making 147 00:07:55,080 --> 00:07:59,400 Speaker 1: these these aggressive, random decisions based on their political proclivities. 148 00:07:59,680 --> 00:08:02,320 Speaker 1: Now and I see what's been released. There was a 149 00:08:02,360 --> 00:08:04,920 Speaker 1: big role here played by the FBI, and to a 150 00:08:04,960 --> 00:08:08,280 Speaker 1: certain extent, I would argue the FBI was more responsible 151 00:08:08,720 --> 00:08:12,000 Speaker 1: for the censorship in terms of driving it than actual 152 00:08:12,080 --> 00:08:15,480 Speaker 1: Twitter employees themselves. Is that your experience at Facebook? Is 153 00:08:15,520 --> 00:08:18,960 Speaker 1: that the way that you read this Twitter data dump? Yeah? 154 00:08:18,960 --> 00:08:21,920 Speaker 1: So lucky me. I was there when Trump got elected, 155 00:08:21,920 --> 00:08:24,440 Speaker 1: but I got out in twenty seventeen, so I really 156 00:08:24,560 --> 00:08:29,400 Speaker 1: missed the whole big disinformation misinformation push, and you know, 157 00:08:29,480 --> 00:08:32,080 Speaker 1: thankfully right that I didn't have to sort of deal 158 00:08:32,160 --> 00:08:35,679 Speaker 1: with that. So I when we communicated with the government, 159 00:08:35,720 --> 00:08:39,280 Speaker 1: we did so through specific mechanisms and again for I 160 00:08:39,320 --> 00:08:43,679 Speaker 1: think ultimately noble purposes. We were looking specifically at foreign influence, 161 00:08:43,880 --> 00:08:46,280 Speaker 1: and we were looking specifically or my team wasn't, but 162 00:08:46,320 --> 00:08:48,800 Speaker 1: we dealt with people who were looking at child sexual 163 00:08:48,840 --> 00:08:52,280 Speaker 1: abuse material. So that was my experience at Facebook. It 164 00:08:52,320 --> 00:08:56,760 Speaker 1: looked like, as we've talked about before, they've taken those tools, 165 00:08:57,200 --> 00:08:59,920 Speaker 1: maybe not the exact internal tools because they build new 166 00:09:00,040 --> 00:09:04,199 Speaker 1: ones every week, it seems they've taken specific ideas and 167 00:09:04,760 --> 00:09:08,840 Speaker 1: you transferred them to this whole idea of policing the 168 00:09:08,880 --> 00:09:11,960 Speaker 1: speech of Americans in terms of what you know the 169 00:09:12,040 --> 00:09:14,760 Speaker 1: FBI is doing. I was gob snacked. I mean, we 170 00:09:14,840 --> 00:09:17,200 Speaker 1: at the Heritage Foundation we wrote a paper in February 171 00:09:17,200 --> 00:09:19,280 Speaker 1: of twenty twenty two and we said, be on the 172 00:09:19,320 --> 00:09:22,600 Speaker 1: lookout for the increasing symbiosis between the government and big tech, 173 00:09:22,840 --> 00:09:25,040 Speaker 1: and big tech will often work hand in glove with 174 00:09:25,080 --> 00:09:27,360 Speaker 1: the government to do what's bidding. And we knew that 175 00:09:27,440 --> 00:09:29,960 Speaker 1: because of what Jensaki had said from the White House 176 00:09:29,960 --> 00:09:32,480 Speaker 1: podium in July of twenty twenty one. You know, we're 177 00:09:32,520 --> 00:09:35,440 Speaker 1: working with Facebook to single out accounts then post for censorship, 178 00:09:35,600 --> 00:09:38,080 Speaker 1: and we knew these users had been jettison from the 179 00:09:38,080 --> 00:09:40,840 Speaker 1: platform after she pointed them out, So we knew that 180 00:09:40,920 --> 00:09:43,640 Speaker 1: this was happening. There were other data points along that line, 181 00:09:43,840 --> 00:09:46,640 Speaker 1: but we didn't know the extent to which it was happening. 182 00:09:46,679 --> 00:09:50,440 Speaker 1: So that did surprise me, especially having worked, i would say, 183 00:09:50,679 --> 00:09:54,319 Speaker 1: cleanly with some of these government agencies for good purposes, 184 00:09:54,480 --> 00:10:00,680 Speaker 1: to see it perverted in this manner. I'm very area upset, 185 00:10:00,720 --> 00:10:03,280 Speaker 1: and I think it's something that every American should be 186 00:10:03,679 --> 00:10:06,839 Speaker 1: as upset as I am about. I think that's it, right, 187 00:10:06,880 --> 00:10:09,520 Speaker 1: I mean so. Peter Schweitzer wrote the book called Clinton Cash, 188 00:10:09,559 --> 00:10:12,240 Speaker 1: which came out in twenty fifteen, and it exposed the 189 00:10:12,360 --> 00:10:15,600 Speaker 1: interlap of relationships between people that donated the Clinton Foundation 190 00:10:15,600 --> 00:10:18,640 Speaker 1: and the people got favors from the State Department when 191 00:10:18,679 --> 00:10:21,160 Speaker 1: Hillary Clinton was Secretary of State. And that was reported 192 00:10:21,160 --> 00:10:24,440 Speaker 1: on by The New York Times, ABC News, Bloomberg, Washington Post, 193 00:10:24,720 --> 00:10:27,400 Speaker 1: every mainstream media outlet. And I think what happened is 194 00:10:27,440 --> 00:10:30,560 Speaker 1: after Donald Trump got elected, those mainstream media outlets said, 195 00:10:30,720 --> 00:10:33,000 Speaker 1: m maybe we were part of the problem. And guests, 196 00:10:33,000 --> 00:10:35,199 Speaker 1: who doesn't report on stuff that we do anymore? Those guys, 197 00:10:35,559 --> 00:10:37,720 Speaker 1: So do you think that that's basically like Facebook and 198 00:10:37,800 --> 00:10:40,520 Speaker 1: big Tech said, maybe we were manipulated, maybe we were 199 00:10:40,600 --> 00:10:42,440 Speaker 1: used by the Trump campaign. We're gonna make sure that 200 00:10:42,520 --> 00:10:46,760 Speaker 1: never happens again. Oh and you even had you all Wroth, 201 00:10:47,200 --> 00:10:49,720 Speaker 1: the former head of Trust and Safety from Twitter, he 202 00:10:49,840 --> 00:10:54,040 Speaker 1: basically invoked quote Lessons of twenty sixteen when he was 203 00:10:54,080 --> 00:10:57,680 Speaker 1: providing justification internally for the censorship of the Hunter Biden 204 00:10:57,760 --> 00:11:01,360 Speaker 1: laptop story. So this was something in everyone's mind, and, 205 00:11:01,720 --> 00:11:03,520 Speaker 1: like I said, the specter of it for a hover 206 00:11:03,760 --> 00:11:06,720 Speaker 1: throughout the place. I was there on election night. I 207 00:11:06,720 --> 00:11:09,520 Speaker 1: was actually sitting at my desk when Trump got elected 208 00:11:09,520 --> 00:11:11,600 Speaker 1: in the dead of the night. It was a long day, 209 00:11:11,840 --> 00:11:15,040 Speaker 1: and you know, coming into Facebook the day after was 210 00:11:15,240 --> 00:11:17,720 Speaker 1: it was like a funeral. You know, the place was 211 00:11:17,800 --> 00:11:20,720 Speaker 1: just people were so upset. And then when you had 212 00:11:20,800 --> 00:11:25,600 Speaker 1: the whole narrative about Cambridge Analytica come out basically saying that, 213 00:11:25,679 --> 00:11:28,880 Speaker 1: you know, people were propagandized on Facebook, on these platforms 214 00:11:28,880 --> 00:11:33,080 Speaker 1: into voting for Trump, then they I think there was 215 00:11:33,120 --> 00:11:36,840 Speaker 1: this cognition of never again, we will never be you know, 216 00:11:37,000 --> 00:11:40,839 Speaker 1: CAP's pause of conservatives or Republicans, especially given the way 217 00:11:40,840 --> 00:11:44,480 Speaker 1: they think, where they're headquartered, etc. So so absolutely it 218 00:11:44,320 --> 00:11:46,560 Speaker 1: was it was a massive factor, and y'all Roth even 219 00:11:46,559 --> 00:11:49,400 Speaker 1: admitted it. We're talking to Kara Frederick, she's the director 220 00:11:49,440 --> 00:11:52,480 Speaker 1: of Tech policy at the Heritage Foundation, the former Facebook 221 00:11:52,480 --> 00:11:54,679 Speaker 1: intelligence analyst. A couple more things we want to get 222 00:11:54,679 --> 00:11:56,600 Speaker 1: to with her, and we come back. I'm Erica Aggers, 223 00:11:56,679 --> 00:11:59,640 Speaker 1: He's Peter Schweitzer. We are filling in for Sean Hannity 224 00:12:00,000 --> 00:12:01,280 Speaker 1: and give us a call at one eight hundred and 225 00:12:01,360 --> 00:12:03,400 Speaker 1: nine four one seven three two six. That's one eight 226 00:12:03,480 --> 00:12:05,600 Speaker 1: hundred and nine four one Sean. If you like what 227 00:12:05,679 --> 00:12:07,640 Speaker 1: you hear, you can find our podcast at the drilldown 228 00:12:07,640 --> 00:12:19,480 Speaker 1: dot com. Breaking every single day. This is the Sean 229 00:12:19,760 --> 00:12:22,760 Speaker 1: Hannity Show. 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That's the Sean Hannity 249 00:13:19,320 --> 00:13:23,720 Speaker 1: Square at my pillow dot com. Peter Schweitzer and Eric Eckers, 250 00:13:23,720 --> 00:13:26,720 Speaker 1: we're filling in for Sean on the Sean Hannity Radio Show. 251 00:13:26,840 --> 00:13:29,360 Speaker 1: We have as our guest Kara Frederick, director of Tech 252 00:13:29,400 --> 00:13:34,720 Speaker 1: policy at the Heritage Foundation and a former Facebook intelligence analyst. So, Kara, 253 00:13:34,760 --> 00:13:36,520 Speaker 1: you've done a great job in laying out what the 254 00:13:36,559 --> 00:13:40,280 Speaker 1: problems are, how we've reached the point to where we 255 00:13:40,360 --> 00:13:44,640 Speaker 1: are today in terms of this collusion between the federal 256 00:13:44,920 --> 00:13:48,280 Speaker 1: law enforcement system and big tech companies. How do we 257 00:13:48,320 --> 00:13:51,199 Speaker 1: fix the problem? Is this is a problem for government reform? 258 00:13:51,320 --> 00:13:53,840 Speaker 1: Is this a problem changing big tech? How do we 259 00:13:53,880 --> 00:13:57,000 Speaker 1: fix this? Yeah? So, I definitely think that there's a 260 00:13:57,080 --> 00:14:00,280 Speaker 1: number of political solutions that we can explore here. And 261 00:14:00,640 --> 00:14:02,320 Speaker 1: you know, first some forums, I want to say that 262 00:14:02,640 --> 00:14:05,200 Speaker 1: Elon Musk buying Twitter to the tune of forty four 263 00:14:05,200 --> 00:14:10,880 Speaker 1: billion dollars. That's not a repeatable strategy, right, and it's 264 00:14:10,920 --> 00:14:13,679 Speaker 1: a singular moment in time. So if we think, oh, yes, 265 00:14:13,960 --> 00:14:17,800 Speaker 1: the free market adjudicated properly, we're good to go. Sorry, guys, 266 00:14:17,840 --> 00:14:20,280 Speaker 1: that's not the case. There's I would love for it 267 00:14:20,360 --> 00:14:22,040 Speaker 1: to be the case, but you know, he is one 268 00:14:22,120 --> 00:14:24,520 Speaker 1: in a million, or one in a billion, even more so, 269 00:14:24,520 --> 00:14:27,680 Speaker 1: so I think that relying on you know, our next 270 00:14:27,680 --> 00:14:30,240 Speaker 1: White Knight billionaire to come riding to save us, it's 271 00:14:30,280 --> 00:14:32,520 Speaker 1: probably not going to happen. So what we need to do, 272 00:14:32,600 --> 00:14:35,400 Speaker 1: and we again improved, I think at the Heritage Foundation 273 00:14:35,440 --> 00:14:38,600 Speaker 1: prophetic in this regard. In February of this year, we 274 00:14:38,720 --> 00:14:41,640 Speaker 1: basically said, you have to prohibit the government use of 275 00:14:41,680 --> 00:14:44,680 Speaker 1: tech companies to chill speech. So if there's any sort 276 00:14:44,680 --> 00:14:48,720 Speaker 1: of suppression of political cannadis things like that, then this 277 00:14:48,800 --> 00:14:51,360 Speaker 1: has to be reported. There has to be that radical 278 00:14:51,360 --> 00:14:55,560 Speaker 1: transparency coming from the tea frankly, of the government in 279 00:14:55,600 --> 00:14:57,840 Speaker 1: a very pointed way, in a very judicious way. You know, 280 00:14:57,920 --> 00:15:00,840 Speaker 1: I'm not saying make the governments, you know, big and powerful. 281 00:15:00,880 --> 00:15:03,120 Speaker 1: They're part of the reason why we're in this particle anyway. 282 00:15:03,280 --> 00:15:05,600 Speaker 1: But at the same time, you have to understand that 283 00:15:05,880 --> 00:15:09,400 Speaker 1: this cannot happen, and you have to frankly punish the 284 00:15:10,520 --> 00:15:14,600 Speaker 1: this happening from the government leaning on these big tech companies. 285 00:15:14,640 --> 00:15:18,120 Speaker 1: This is something that Jim Jordan has talked about introducing 286 00:15:18,480 --> 00:15:21,240 Speaker 1: draft legislation to this end. So I think it's a 287 00:15:21,320 --> 00:15:23,920 Speaker 1: good thing if we frankly just ban the government use 288 00:15:23,960 --> 00:15:26,800 Speaker 1: of tech companies to chill the speech of Americans, and 289 00:15:26,840 --> 00:15:31,720 Speaker 1: then you require transparency, require transparency and content moderation practices 290 00:15:31,800 --> 00:15:35,720 Speaker 1: in algorithmic impact in data use. Have that National Data 291 00:15:35,760 --> 00:15:39,040 Speaker 1: Privacy and Protection Framework to let people get a taste 292 00:15:39,040 --> 00:15:42,560 Speaker 1: of controlling their own data. So we're not just beholden 293 00:15:42,640 --> 00:15:45,160 Speaker 1: to these tech companies and whoever they want to share 294 00:15:45,200 --> 00:15:48,480 Speaker 1: it with, etc. So that's a broader problem, but you 295 00:15:48,560 --> 00:15:50,960 Speaker 1: have to start by prohibiting government use of these tech 296 00:15:50,960 --> 00:15:54,560 Speaker 1: companies to kill the speech of Americans period. Care Frederick 297 00:15:54,560 --> 00:15:56,440 Speaker 1: with the Heritage Foundation, thank you very much. It's such 298 00:15:56,480 --> 00:15:59,200 Speaker 1: an important topic. We've talked for a long time about 299 00:15:59,200 --> 00:16:01,720 Speaker 1: how I think we're still very new in terms of 300 00:16:01,800 --> 00:16:05,680 Speaker 1: realizing how empowered we should be with our own data. 301 00:16:05,800 --> 00:16:07,640 Speaker 1: We've talked before about the fact that it took us 302 00:16:07,880 --> 00:16:10,120 Speaker 1: one hundred plus years to figure out that, hey, maybe 303 00:16:10,120 --> 00:16:14,280 Speaker 1: we shouldn't pour chemicals in rivers. Right, cars existed for 304 00:16:14,360 --> 00:16:17,520 Speaker 1: a while before we realize that maybe we need seat belts. 305 00:16:18,040 --> 00:16:21,200 Speaker 1: And I think we're still very new and very early 306 00:16:21,280 --> 00:16:24,040 Speaker 1: in the how much is our data worth? And who's 307 00:16:24,040 --> 00:16:28,040 Speaker 1: it worth it too? And I think companies like Facebook, Twitter, Google, 308 00:16:28,160 --> 00:16:30,320 Speaker 1: they know the answer. But I think if if there's 309 00:16:30,320 --> 00:16:33,480 Speaker 1: a government solution, it's to be to empower Americans to 310 00:16:33,480 --> 00:16:37,040 Speaker 1: take more ownership over their data. I think you're exactly right. 311 00:16:37,200 --> 00:16:39,440 Speaker 1: We need to take charge of it ourselves. Kara, thank 312 00:16:39,480 --> 00:16:41,400 Speaker 1: you so much for joining us. We appreciate all the 313 00:16:41,480 --> 00:16:44,000 Speaker 1: great work you're doing up there at the Heritage Foundation. 314 00:16:44,760 --> 00:16:46,960 Speaker 1: Thanks for having me have a great night. Thank you, Kara. 315 00:16:47,040 --> 00:16:49,640 Speaker 1: That's Peter Schweitzer. I'm Eric Eggers. We are filling in 316 00:16:49,680 --> 00:16:51,480 Speaker 1: for the Shawn Handy Show. If you'd like to join 317 00:16:51,520 --> 00:16:53,480 Speaker 1: the conversation, give us a call at one eight hundred 318 00:16:53,480 --> 00:17:05,000 Speaker 1: and nine four one seven three two six. That's one. Sean. Hey, 319 00:17:05,040 --> 00:17:07,280 Speaker 1: Sean Hannity here from my friends at Loan Star Transfer. 320 00:17:07,400 --> 00:17:09,240 Speaker 1: Now you've heard me for a while. Tell you the 321 00:17:09,280 --> 00:17:11,159 Speaker 1: time shares are kind of becoming a thing of the 322 00:17:11,200 --> 00:17:14,240 Speaker 1: past now. Unfortunately, many of you are still stuck in one. 323 00:17:14,320 --> 00:17:16,720 Speaker 1: If you are, you don't have to be. That's where 324 00:17:16,720 --> 00:17:19,640 Speaker 1: our friends at lone Star Transfer can help. 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Hey, it's 342 00:18:18,359 --> 00:18:21,280 Speaker 1: Peter Schweitzer and Eric Eggers, we're failing in for Sean. 343 00:18:21,440 --> 00:18:25,119 Speaker 1: We hope you are preparing for a very merry Christmas 344 00:18:25,200 --> 00:18:28,560 Speaker 1: and a happy Hanukkah at this holiday season. We have 345 00:18:28,600 --> 00:18:32,720 Speaker 1: some breaking news. The Supreme Court is putting a hold 346 00:18:32,960 --> 00:18:37,399 Speaker 1: on the Title forty two suspension. Remember Joe Biden wanted 347 00:18:37,400 --> 00:18:39,560 Speaker 1: to get rid of Title forty two that allows us 348 00:18:39,560 --> 00:18:42,840 Speaker 1: to return people who get across the border illegally because 349 00:18:42,880 --> 00:18:46,000 Speaker 1: of the medical situation with a pandemic. He was going 350 00:18:46,040 --> 00:18:48,240 Speaker 1: to get rid of Title forty two. The Supreme Court 351 00:18:48,359 --> 00:18:51,000 Speaker 1: is right now saying that they were going to put 352 00:18:51,040 --> 00:18:53,000 Speaker 1: that on hold. So it means they're going to have 353 00:18:53,040 --> 00:18:55,400 Speaker 1: a decision. But this is a huge win for those 354 00:18:55,440 --> 00:18:58,680 Speaker 1: states that we're suing the Biden administration over this policy. 355 00:18:58,720 --> 00:19:01,159 Speaker 1: It just shows you the power of on Handity's radio program. 356 00:19:01,200 --> 00:19:03,159 Speaker 1: We led the program in the three o'clock hour or 357 00:19:03,160 --> 00:19:05,720 Speaker 1: the discussion about Tddle forty two being repealed and what 358 00:19:05,720 --> 00:19:08,000 Speaker 1: it would mean for the immigration and within two hours, 359 00:19:08,040 --> 00:19:10,800 Speaker 1: Supreme Court Chief Justice John Roberts says, Okay, Eric Competer, 360 00:19:10,840 --> 00:19:13,320 Speaker 1: you're right. Yeah, this is called a causal relationship. Right. 361 00:19:14,600 --> 00:19:16,680 Speaker 1: I was never good at statistics, but no but I 362 00:19:16,720 --> 00:19:18,800 Speaker 1: think it's a big deal, and I think it underscores 363 00:19:18,920 --> 00:19:23,080 Speaker 1: several different like very challenging and dynamic elements to the 364 00:19:23,119 --> 00:19:26,000 Speaker 1: border because it's on the one hand, there's a reason 365 00:19:26,040 --> 00:19:28,320 Speaker 1: why the border stays open. Yeah, it's because you do 366 00:19:28,440 --> 00:19:30,360 Speaker 1: have Chamber of commerce type interests. I mean, there are 367 00:19:30,400 --> 00:19:33,960 Speaker 1: big businesses in the United States, and we always say 368 00:19:34,080 --> 00:19:37,160 Speaker 1: big business and big government are business partners. So if 369 00:19:37,200 --> 00:19:40,120 Speaker 1: big business wanted the border to be closed, it would 370 00:19:40,160 --> 00:19:45,040 Speaker 1: be more closed. And of course because they want those workers, 371 00:19:45,080 --> 00:19:47,000 Speaker 1: they want cheap labor, and they want people, and they're 372 00:19:47,000 --> 00:19:49,760 Speaker 1: buying some of the different goods. Right. So now, of course, 373 00:19:49,800 --> 00:19:53,080 Speaker 1: if you listen to Gus Mayorchis two weeks ago, we 374 00:19:53,080 --> 00:19:56,399 Speaker 1: were told that actually the border was closed. Is the 375 00:19:56,480 --> 00:20:00,360 Speaker 1: border safe now? I was watching a news channel and 376 00:20:00,440 --> 00:20:02,840 Speaker 1: they were talking about an invasion. What's happening and I 377 00:20:02,880 --> 00:20:10,720 Speaker 1: got a little concerned. Look, the border, the border is secure. 378 00:20:11,640 --> 00:20:15,960 Speaker 1: The border. We are working to make the border more secure. 379 00:20:16,359 --> 00:20:20,880 Speaker 1: That has been a historic challenge. I have said to 380 00:20:20,880 --> 00:20:27,359 Speaker 1: a number of legislators who expressed to me that we 381 00:20:27,440 --> 00:20:33,280 Speaker 1: need to address the challenge at the border before they 382 00:20:33,359 --> 00:20:38,640 Speaker 1: pass legislation. And I take issue with the math of 383 00:20:38,720 --> 00:20:45,840 Speaker 1: holding the solution hostage until the problem is resolved. There 384 00:20:46,000 --> 00:20:51,680 Speaker 1: is work to be done. When you safe and secure 385 00:20:51,680 --> 00:20:57,000 Speaker 1: are two different words. There are smugglers that operate on 386 00:20:57,040 --> 00:21:02,480 Speaker 1: the Mexican side of the border, and placing one's life 387 00:21:02,800 --> 00:21:06,520 Speaker 1: in their hands is not safe. Yeah, this is a 388 00:21:06,560 --> 00:21:10,240 Speaker 1: remarkable statement by our secretary for Homeland Security that the 389 00:21:10,320 --> 00:21:13,760 Speaker 1: border is secure. He had a predecessor during the Obama 390 00:21:13,760 --> 00:21:18,120 Speaker 1: administration named Jay Johnson. He was asked what he would 391 00:21:18,200 --> 00:21:20,760 Speaker 1: regard as a crisis at the border. He said, if 392 00:21:20,800 --> 00:21:23,080 Speaker 1: we have more than a thousand people a day sneaking 393 00:21:23,119 --> 00:21:26,840 Speaker 1: across the border, that's a crisis. That was Obama's head 394 00:21:26,880 --> 00:21:30,320 Speaker 1: of Homeland Security. We now literally today have seven to 395 00:21:30,359 --> 00:21:33,440 Speaker 1: eight times that amount every day, and my Orcas says, 396 00:21:33,800 --> 00:21:35,840 Speaker 1: no problem, the border is secure. I do like what 397 00:21:35,880 --> 00:21:38,880 Speaker 1: Majorca said. There's a difference between being safe and secure. 398 00:21:39,480 --> 00:21:42,119 Speaker 1: When my children are buckled up in the car, they 399 00:21:42,160 --> 00:21:45,119 Speaker 1: are secure. But when I'm driving, they're not necessarily safe. 400 00:21:45,840 --> 00:21:49,560 Speaker 1: You know, they scream, it's distracted drive and it's all 401 00:21:49,600 --> 00:21:52,000 Speaker 1: not great. But no, um, I think that's but. But 402 00:21:52,080 --> 00:21:54,720 Speaker 1: that's an example of this double speak that we consistently 403 00:21:54,800 --> 00:21:58,040 Speaker 1: here on the boarder listen to this montage of the 404 00:21:58,160 --> 00:22:00,520 Speaker 1: level of flip flops we hear from members of Congress 405 00:22:00,560 --> 00:22:03,680 Speaker 1: on what exactly the reality is at our border. People 406 00:22:03,680 --> 00:22:07,600 Speaker 1: who enter the United States without our permission, our illegal aliens, 407 00:22:07,600 --> 00:22:10,240 Speaker 1: and illegal aliens should not be treated the same as 408 00:22:10,280 --> 00:22:13,600 Speaker 1: people who entered the US legally. President's decision to end 409 00:22:13,680 --> 00:22:17,840 Speaker 1: DACA was heartless and it was brainless. Hundreds hundreds of 410 00:22:17,920 --> 00:22:21,000 Speaker 1: thousands of families will be ripped apart. And the argument 411 00:22:21,080 --> 00:22:25,119 Speaker 1: them as the president is Americans don't want to do 412 00:22:25,200 --> 00:22:29,000 Speaker 1: the work. Wait, just can't find American workers to do 413 00:22:29,080 --> 00:22:32,239 Speaker 1: the work. But the president that is a cruck in 414 00:22:32,320 --> 00:22:37,240 Speaker 1: many instances, it's just not true. In my view, Fromp's 415 00:22:37,240 --> 00:22:42,440 Speaker 1: decision to end the DOCCER program was some eight hundred 416 00:22:42,800 --> 00:22:48,480 Speaker 1: thousand young people. Is the cruelest and most ugly presidential 417 00:22:48,600 --> 00:22:51,800 Speaker 1: act in the modern history of this country. We've got 418 00:22:51,800 --> 00:22:54,240 Speaker 1: to do several things, and I am, you know, adamantly 419 00:22:54,359 --> 00:22:58,800 Speaker 1: against illegal immigrants. People have to stop employing illegal immigrants. 420 00:22:58,800 --> 00:23:04,400 Speaker 1: My proposal well, keep families together and it will include 421 00:23:04,520 --> 00:23:09,280 Speaker 1: a path to citizenship. We simply cannot allow people to 422 00:23:09,320 --> 00:23:16,040 Speaker 1: pour into the United States undetected, undocumented, unchecked, and circumventing 423 00:23:16,320 --> 00:23:19,720 Speaker 1: the line of people who are waiting patiently, diligently, and 424 00:23:19,880 --> 00:23:25,119 Speaker 1: lawfully to become immigrants. Real reform means establishing a responsible 425 00:23:25,200 --> 00:23:30,359 Speaker 1: pathway to earn citizenship. To show you how this flip 426 00:23:30,400 --> 00:23:34,359 Speaker 1: flop exists right now in the Biden administration, the reason 427 00:23:34,359 --> 00:23:36,200 Speaker 1: they want to get rid of Title forty two is said, 428 00:23:36,200 --> 00:23:39,000 Speaker 1: the pandemic is over right, we don't need this anymore. 429 00:23:39,680 --> 00:23:42,360 Speaker 1: What did they do just a few weeks ago they 430 00:23:42,400 --> 00:23:46,879 Speaker 1: extended the moratorium on student loan payments that people have 431 00:23:46,960 --> 00:23:50,400 Speaker 1: to make. What authorization did they use because we still 432 00:23:50,440 --> 00:23:53,840 Speaker 1: have a pandemic, so it's totally political. They use it 433 00:23:53,880 --> 00:23:57,040 Speaker 1: and justify whatever action they want to take, and it 434 00:23:57,080 --> 00:23:59,560 Speaker 1: has nothing to do with a pandemic. And that's the problem. 435 00:23:59,560 --> 00:24:01,520 Speaker 1: When did we get to the point in this country 436 00:24:01,600 --> 00:24:06,000 Speaker 1: when basic border security Jay Johnson saying a thousand people 437 00:24:06,040 --> 00:24:08,119 Speaker 1: a day over the borders too much, we're now seven 438 00:24:08,160 --> 00:24:10,680 Speaker 1: to eight thousand. When did we get to the point 439 00:24:10,720 --> 00:24:16,040 Speaker 1: where this doesn't matter anymore to one particular political party, 440 00:24:16,080 --> 00:24:18,879 Speaker 1: the Democrats, who you have to wonder what would it 441 00:24:18,960 --> 00:24:22,800 Speaker 1: take for them actually in Washington, DC, to pay attention 442 00:24:22,800 --> 00:24:25,199 Speaker 1: to this issue and just to be clear about it. 443 00:24:25,680 --> 00:24:29,000 Speaker 1: We're not necessarily anti immigrant and anti people that come 444 00:24:29,040 --> 00:24:30,880 Speaker 1: to this country for a better way of life, right, 445 00:24:30,920 --> 00:24:33,280 Speaker 1: You and I, I I think both know people that work 446 00:24:33,280 --> 00:24:37,239 Speaker 1: on the front lines to help Afghan refugees, Ukrainian refugees, right, 447 00:24:37,240 --> 00:24:38,840 Speaker 1: And so I think I met a family was a 448 00:24:38,920 --> 00:24:42,600 Speaker 1: Zambian refugee not too long ago. So there's people here 449 00:24:42,600 --> 00:24:45,119 Speaker 1: who have very real needs. Yeah, and you know, I'm 450 00:24:45,160 --> 00:24:47,720 Speaker 1: aware of groups like Tennessee Resettlement Aid and the Georgian 451 00:24:47,760 --> 00:24:49,919 Speaker 1: Foundation that contributes to that, and so people are doing 452 00:24:49,960 --> 00:24:52,640 Speaker 1: the work to try to care for people, care for 453 00:24:52,680 --> 00:24:55,040 Speaker 1: the least of these and so that's why it matters, right, 454 00:24:55,040 --> 00:24:57,600 Speaker 1: because you've already got people in the country that need things, 455 00:24:57,600 --> 00:24:59,320 Speaker 1: and so if you just open up the border, then 456 00:24:59,359 --> 00:25:01,040 Speaker 1: those people do they go to the front of the line, 457 00:25:01,080 --> 00:25:04,080 Speaker 1: and it negatively impacts these groups that we're told by 458 00:25:04,119 --> 00:25:06,920 Speaker 1: the Biden administration and the political left matter more than 459 00:25:06,960 --> 00:25:09,199 Speaker 1: other people. That's right, that's right. I mean, we have 460 00:25:09,240 --> 00:25:12,760 Speaker 1: a process and so legal immigration is great. My parents 461 00:25:12,840 --> 00:25:16,200 Speaker 1: were immigrants from Europe. There, that's a story that's replicated elsewhere. 462 00:25:16,520 --> 00:25:18,520 Speaker 1: But this notion that we're going to have a wide 463 00:25:18,520 --> 00:25:21,199 Speaker 1: open border and all the problems that are associated with 464 00:25:21,240 --> 00:25:23,760 Speaker 1: an open border. Not just the fact that you have 465 00:25:23,880 --> 00:25:26,080 Speaker 1: this flood of people coming into the country who are 466 00:25:26,160 --> 00:25:30,080 Speaker 1: committing criminal acts in some instances are terrorists, but you 467 00:25:30,160 --> 00:25:33,119 Speaker 1: have the added problem that they're suppressing wages. We have 468 00:25:33,200 --> 00:25:36,399 Speaker 1: high inflation in this country right now seven to eight percent. 469 00:25:36,840 --> 00:25:40,199 Speaker 1: Wages should ideally be going up for working families, and 470 00:25:40,240 --> 00:25:42,679 Speaker 1: they're not. And one of the reasons is you have 471 00:25:43,320 --> 00:25:46,160 Speaker 1: this labor pool that comes in. And again this goes 472 00:25:46,200 --> 00:25:48,719 Speaker 1: back to something we were talking about with the COVID shutdowns, 473 00:25:48,760 --> 00:25:51,679 Speaker 1: about what I call the keyboard commandos, the people that 474 00:25:51,760 --> 00:25:55,320 Speaker 1: work in corporate offices and they support policy positions that 475 00:25:55,400 --> 00:25:57,560 Speaker 1: don't affect them and impact them. So they didn't care 476 00:25:57,560 --> 00:25:59,719 Speaker 1: if the schools got shut down because they could work 477 00:25:59,800 --> 00:26:02,240 Speaker 1: from home and take care of their kids. It's very 478 00:26:02,320 --> 00:26:06,840 Speaker 1: similar here. The people that get affected by illegal immigration, adversely, 479 00:26:06,880 --> 00:26:10,920 Speaker 1: are people that have blue collar jobs because unskilled workers 480 00:26:10,960 --> 00:26:14,879 Speaker 1: come in and they can drive wages down. The person 481 00:26:14,960 --> 00:26:18,160 Speaker 1: who works at a corporate office in their office, they 482 00:26:18,200 --> 00:26:20,360 Speaker 1: love the immigrants coming in because you know what, Now 483 00:26:20,400 --> 00:26:23,200 Speaker 1: I can hire the illegals to do my yard service, 484 00:26:23,440 --> 00:26:26,240 Speaker 1: and I can pay them half what I would pay 485 00:26:26,320 --> 00:26:29,760 Speaker 1: the Americans to do the same work. So they love it. 486 00:26:29,800 --> 00:26:34,000 Speaker 1: And again, the policies that they're advocating have terrible repercussions 487 00:26:34,040 --> 00:26:36,320 Speaker 1: for other people in our country, and they don't seem 488 00:26:36,320 --> 00:26:39,000 Speaker 1: to care because it's all about them. I love. Number 489 00:26:39,000 --> 00:26:42,560 Speaker 1: one New York Times bestselling author Peter Schweitzer positioned himself 490 00:26:42,880 --> 00:26:46,280 Speaker 1: as the son of immigrants and the champion of blue 491 00:26:46,280 --> 00:26:48,760 Speaker 1: collar every month, this is the man who just to 492 00:26:48,800 --> 00:26:52,000 Speaker 1: be clear parks in short term parking at the airport, 493 00:26:52,119 --> 00:26:55,040 Speaker 1: regardless of how long his trip will be. Hey, we 494 00:26:55,119 --> 00:26:57,880 Speaker 1: all have our luxuries. We all have our luxury. That's 495 00:26:57,880 --> 00:27:01,280 Speaker 1: get into thy name is Peter Schweitzer, Yeah, it's you know, 496 00:27:01,640 --> 00:27:03,679 Speaker 1: this is I think one of the biggest problems that 497 00:27:03,680 --> 00:27:05,359 Speaker 1: we have in the country today when it comes to 498 00:27:05,359 --> 00:27:07,400 Speaker 1: the border and the other issues. One of the things 499 00:27:07,400 --> 00:27:10,400 Speaker 1: I hear the Republican Congress that's coming in that they 500 00:27:10,440 --> 00:27:12,520 Speaker 1: want to do, which I think is a great idea. 501 00:27:12,680 --> 00:27:15,960 Speaker 1: They cannot get Democrats to go to the border to 502 00:27:16,040 --> 00:27:18,480 Speaker 1: actually see the problem. I mean you can see it 503 00:27:18,480 --> 00:27:20,679 Speaker 1: if you go on Twitter and elsewhere. So they're actually 504 00:27:20,720 --> 00:27:25,080 Speaker 1: saying we're going to convene congressional hearings in Texas on 505 00:27:25,119 --> 00:27:28,720 Speaker 1: the border, so that effectively will force these members of Congress, 506 00:27:28,760 --> 00:27:31,479 Speaker 1: if they want to attend congressional hearings, to go to 507 00:27:31,520 --> 00:27:34,000 Speaker 1: the border. I think it's a genius idea, and I 508 00:27:34,000 --> 00:27:36,680 Speaker 1: think we actually ought to have a twenty twenty four 509 00:27:36,760 --> 00:27:39,560 Speaker 1: presidential debate at the border. At the border. You know, 510 00:27:39,560 --> 00:27:41,119 Speaker 1: it's wild about what you just said. It's such a 511 00:27:41,119 --> 00:27:44,280 Speaker 1: great point. But we had a dang bullet train NonStop 512 00:27:44,320 --> 00:27:46,800 Speaker 1: from DC to the border when during the Trump administration 513 00:27:46,880 --> 00:27:48,800 Speaker 1: we were putting these kids in cages, right, we couldn't 514 00:27:48,840 --> 00:27:51,280 Speaker 1: stop having people come by there. We didn't have a 515 00:27:51,280 --> 00:27:53,480 Speaker 1: border crisis. We had a congressional invasion of the border 516 00:27:53,560 --> 00:27:56,479 Speaker 1: crisis when we had these kids and being separated from 517 00:27:56,520 --> 00:27:58,600 Speaker 1: their families. But you're absolutely right, now that the Biden 518 00:27:58,600 --> 00:28:01,440 Speaker 1: administration has taken over, we see less imagery from there. 519 00:28:01,520 --> 00:28:04,359 Speaker 1: We don't see AOC crying at the border anymore like 520 00:28:04,400 --> 00:28:06,200 Speaker 1: she did. I think she might even even kneel down. 521 00:28:06,880 --> 00:28:09,320 Speaker 1: We don't see them anymore, even though the crisis is 522 00:28:09,359 --> 00:28:13,560 Speaker 1: now worse. And again, the victims are the people that 523 00:28:13,600 --> 00:28:17,879 Speaker 1: are getting brought over by these criminal cartels, that are 524 00:28:17,920 --> 00:28:20,600 Speaker 1: being exploited and they're being put in a situation where 525 00:28:20,600 --> 00:28:23,240 Speaker 1: they're not legally in the country, so that's going to 526 00:28:23,359 --> 00:28:26,440 Speaker 1: limit some of their options. It makes them very, very vulnerable. 527 00:28:26,600 --> 00:28:29,160 Speaker 1: It needs to be done in an orderly way. Again, 528 00:28:29,680 --> 00:28:32,520 Speaker 1: the fact that you have people making decisions they don't 529 00:28:32,560 --> 00:28:36,720 Speaker 1: bear the consequences of those decisions is a huge part 530 00:28:36,800 --> 00:28:39,440 Speaker 1: of this problem, and I think it's actually getting worse 531 00:28:39,480 --> 00:28:42,240 Speaker 1: in this country. If you look at the demographics. People 532 00:28:42,320 --> 00:28:44,800 Speaker 1: look at members of Congress in the context of, you know, 533 00:28:44,920 --> 00:28:47,640 Speaker 1: what their races and what their creed is, and that's important, 534 00:28:47,680 --> 00:28:50,560 Speaker 1: that's fine, but look at actually what their jobs are. 535 00:28:50,640 --> 00:28:55,200 Speaker 1: We have fewer and fewer people that are businessmen that 536 00:28:55,520 --> 00:28:58,600 Speaker 1: you know, are skilled tradesmen like you know, plumbers and 537 00:28:59,200 --> 00:29:01,480 Speaker 1: people like that that are running for Congress and serving. 538 00:29:01,760 --> 00:29:05,200 Speaker 1: Most of them are either former government officials or people 539 00:29:05,200 --> 00:29:08,040 Speaker 1: that come from academ or from a corporate environment, and 540 00:29:08,120 --> 00:29:11,560 Speaker 1: yet they're making decisions that impact the lives of ordinary 541 00:29:11,560 --> 00:29:15,080 Speaker 1: Americans on issues like immigration. They have no context, and 542 00:29:15,120 --> 00:29:19,000 Speaker 1: they don't seem to be particularly interested in even figuring 543 00:29:19,040 --> 00:29:21,840 Speaker 1: out what the context of these problems are. One of 544 00:29:21,840 --> 00:29:23,720 Speaker 1: the things that we study at the government Accountability and 545 00:29:23,760 --> 00:29:26,440 Speaker 1: suit is incentives, and one of the things that I 546 00:29:26,440 --> 00:29:28,520 Speaker 1: think my favorite thing that we do is, hey, if 547 00:29:28,560 --> 00:29:31,480 Speaker 1: this seems like a problem, and it's always been a problem, 548 00:29:31,800 --> 00:29:34,080 Speaker 1: and it seems like solutions are possible, how come no 549 00:29:34,120 --> 00:29:37,520 Speaker 1: one's interested in pursuing the solutions. And the answer is 550 00:29:37,520 --> 00:29:40,480 Speaker 1: because entrenched interests continue to make money off of the 551 00:29:40,520 --> 00:29:44,000 Speaker 1: status quo. And I think honestly the political left happens 552 00:29:44,000 --> 00:29:46,800 Speaker 1: to also benefit politically as well. They do, they do. 553 00:29:46,840 --> 00:29:49,840 Speaker 1: I mean so many of these issues. Sometimes people go 554 00:29:50,080 --> 00:29:53,840 Speaker 1: and argue that these issues are somehow a conspiracy that 555 00:29:53,920 --> 00:29:56,800 Speaker 1: people that are you know, wear funny robes that have 556 00:29:56,880 --> 00:30:00,400 Speaker 1: secret handshakes, that are part of secret society. That's not it. 557 00:30:00,600 --> 00:30:04,880 Speaker 1: This is all about the industrial logic of big governments. Yeah, 558 00:30:04,880 --> 00:30:07,840 Speaker 1: they're not. It's not a conspiracy. It's their business model. 559 00:30:07,960 --> 00:30:10,080 Speaker 1: And as they do is the left likes to say 560 00:30:10,080 --> 00:30:12,200 Speaker 1: they say the quiet part out loud. Just listen to 561 00:30:12,200 --> 00:30:14,240 Speaker 1: what Tom Pereza says as far as what the Democrat 562 00:30:14,280 --> 00:30:17,680 Speaker 1: electoral strategy, we'll be moving forward, So it's it continues 563 00:30:17,680 --> 00:30:20,680 Speaker 1: to be troubling. He's Peter Schweizer, I'm Eric Eggers. We 564 00:30:20,720 --> 00:30:23,400 Speaker 1: want to leave you with our last segment, coming up 565 00:30:23,520 --> 00:30:26,240 Speaker 1: with maybe something slightly more hopeful than just the depressed 566 00:30:26,240 --> 00:30:29,080 Speaker 1: state of the economy and American immigration system. We'll see 567 00:30:29,120 --> 00:30:30,880 Speaker 1: if we're successful or not. If you want to give 568 00:30:30,920 --> 00:30:33,280 Speaker 1: us a call, it's one eight hundred and nine four one. Sean, 569 00:30:33,320 --> 00:30:35,640 Speaker 1: it's one eight hundred and nine four one seven, three 570 00:30:35,720 --> 00:30:37,720 Speaker 1: two six. Maybe like what you hear. You can find 571 00:30:37,760 --> 00:30:40,680 Speaker 1: our podcast at the drilldown dot Com. Is Peter Schweizer. 572 00:30:40,720 --> 00:30:43,040 Speaker 1: I'm with Eric Eggers. We are filling in for Sean 573 00:30:43,960 --> 00:30:46,800 Speaker 1: on this wonderful December of the nineteenth. We're gonna go 574 00:30:46,840 --> 00:30:51,720 Speaker 1: to Jim in Florida. Jim, how are you hey? Good easy, gentlemen, 575 00:30:52,200 --> 00:30:56,080 Speaker 1: It's it's a deliverature to speak with you. Thank you 576 00:30:56,600 --> 00:30:59,040 Speaker 1: real quick. Let me predicate this real quick, and that 577 00:30:59,520 --> 00:31:02,240 Speaker 1: I bet you're and my days are filled with a 578 00:31:02,320 --> 00:31:06,360 Speaker 1: Patriot channel from Breitbart all the way after Stacey washing 579 00:31:06,400 --> 00:31:09,440 Speaker 1: did in the evening. So I consider myself a pretty 580 00:31:09,440 --> 00:31:12,680 Speaker 1: political savay fart above and beyond your average and mount 581 00:31:12,840 --> 00:31:17,880 Speaker 1: cabin boy. But over the years, what I do with 582 00:31:17,880 --> 00:31:19,960 Speaker 1: all the guests and things that they've had on that 583 00:31:20,040 --> 00:31:24,080 Speaker 1: the channels about on the programs have had, you know, 584 00:31:24,160 --> 00:31:26,880 Speaker 1: it's it's the semantics. It's like this needs to be done. 585 00:31:26,920 --> 00:31:28,680 Speaker 1: This should be done. Well, this needs to be done. 586 00:31:28,680 --> 00:31:32,080 Speaker 1: It should be done. And Peter, your work is magical 587 00:31:32,400 --> 00:31:37,880 Speaker 1: and you've explored so much, but yet nothing has been done. 588 00:31:38,320 --> 00:31:42,920 Speaker 1: There's really been no change. It's like there's this apathy 589 00:31:42,960 --> 00:31:46,320 Speaker 1: across this country now. It's like a Bruce Hornsby song 590 00:31:46,440 --> 00:31:48,080 Speaker 1: and it's just that's the way it is. And what 591 00:31:48,440 --> 00:31:52,800 Speaker 1: do you do about it? Well, look, I appreciate the 592 00:31:52,880 --> 00:31:55,280 Speaker 1: sentiments and the kind words. What I would say is 593 00:31:55,280 --> 00:31:57,440 Speaker 1: that there are things that are moving, we want them 594 00:31:57,480 --> 00:32:01,440 Speaker 1: to move faster. In fact, we've got podcast a next 595 00:32:01,560 --> 00:32:04,680 Speaker 1: week that you can find on their drilldown dot com. 596 00:32:04,760 --> 00:32:09,080 Speaker 1: It is a podcast where we interview two gentlemen, local 597 00:32:09,120 --> 00:32:12,080 Speaker 1: guys retired military in the state of Illinois, and over 598 00:32:12,120 --> 00:32:15,360 Speaker 1: the last ten years they have been working to clean 599 00:32:15,480 --> 00:32:19,120 Speaker 1: up the state and more than five hundred local officials 600 00:32:19,120 --> 00:32:22,440 Speaker 1: have either gone to jail or have lost their jobs 601 00:32:22,520 --> 00:32:24,720 Speaker 1: because of the corruption they're engaging. And so I agree 602 00:32:24,720 --> 00:32:27,560 Speaker 1: with you Washington, DC. It's hard, but there are things 603 00:32:27,560 --> 00:32:29,720 Speaker 1: that we can do at a local level and move 604 00:32:29,800 --> 00:32:31,400 Speaker 1: up to the federal level. And Jim, we hear that 605 00:32:31,440 --> 00:32:33,480 Speaker 1: all the time, and that's a very real thing. You're expressing. 606 00:32:33,480 --> 00:32:37,720 Speaker 1: It's called outrage fatigue, and the media websites that deal 607 00:32:37,760 --> 00:32:40,600 Speaker 1: with conservative reporting and they see it often. I know 608 00:32:40,640 --> 00:32:42,719 Speaker 1: Peter Schweitzer likes to refer to what we do at 609 00:32:42,720 --> 00:32:45,920 Speaker 1: the Government Accountability Institute as Paul Revere, and that's not 610 00:32:45,960 --> 00:32:48,560 Speaker 1: because he has delusions of patriotic granger, but because he 611 00:32:48,600 --> 00:32:51,760 Speaker 1: thinks it's our job to tell people where the problems 612 00:32:51,800 --> 00:32:54,680 Speaker 1: are and then the mechanisms of government who are tasked 613 00:32:54,760 --> 00:32:57,960 Speaker 1: with identify them, like congressional committees. I think now that 614 00:32:57,960 --> 00:33:00,280 Speaker 1: we have Republicans in charge, you actually have some optimism 615 00:33:00,320 --> 00:33:02,000 Speaker 1: that will see some of the things that you reported 616 00:33:02,040 --> 00:33:04,480 Speaker 1: on for the last four years actually be investigated and 617 00:33:04,640 --> 00:33:07,520 Speaker 1: maybe charges will actually be filed. Yeah, the wheels of 618 00:33:07,680 --> 00:33:10,600 Speaker 1: government turn slowly, but they do turn, and you're right, 619 00:33:10,680 --> 00:33:13,600 Speaker 1: we view ourselves as Paul Revere. Paul Revere could alert 620 00:33:13,680 --> 00:33:16,040 Speaker 1: people that the British were coming, but it wasn't his 621 00:33:16,160 --> 00:33:19,280 Speaker 1: job to rally the Continental Congress or the Continental Army 622 00:33:19,840 --> 00:33:21,960 Speaker 1: to fight the British. And what we're seeing I think 623 00:33:22,080 --> 00:33:25,160 Speaker 1: going to see with this new Congress. Our actual congressional 624 00:33:25,200 --> 00:33:28,920 Speaker 1: hearings were Hunter Biden's subpoena. It's been four years since 625 00:33:28,960 --> 00:33:32,040 Speaker 1: we first broke this story with Sean Hannity in twenty eighteen. 626 00:33:32,280 --> 00:33:35,000 Speaker 1: But it's now finally coming to fruition and that's something 627 00:33:35,000 --> 00:33:37,520 Speaker 1: we should all be very excited about. We are excited. 628 00:33:37,560 --> 00:33:39,960 Speaker 1: That's Peter Schweizer Imackager has been an honor to talk 629 00:33:39,960 --> 00:33:42,040 Speaker 1: to you today. Thank you, Linda, Thank you Sean. This 630 00:33:42,120 --> 00:33:43,320 Speaker 1: is the Sean Hanny Radio Show.