1 00:00:00,320 --> 00:00:03,840 Speaker 1: Welcome. It is Verdict with Ted Cruz week in Review. 2 00:00:04,000 --> 00:00:05,520 Speaker 1: Here are some of the stories that you may have 3 00:00:05,559 --> 00:00:08,400 Speaker 1: missed that we talked about this week. First up, a 4 00:00:08,600 --> 00:00:13,160 Speaker 1: Chinese tycoon that is having major influence in America now 5 00:00:13,200 --> 00:00:16,800 Speaker 1: being investigated. So what does this mean? We explain it. 6 00:00:17,360 --> 00:00:20,759 Speaker 1: Up Next, a big meeting at the White House in 7 00:00:20,800 --> 00:00:24,439 Speaker 1: the Oval Office talking about the future of AI. Senator 8 00:00:24,480 --> 00:00:27,159 Speaker 1: Cruz was with the President talking about that and he 9 00:00:27,200 --> 00:00:31,360 Speaker 1: gives us the details. And finally, major legislation to help 10 00:00:31,400 --> 00:00:36,080 Speaker 1: with children in America with reading. Yes, actual standards before 11 00:00:36,120 --> 00:00:39,559 Speaker 1: the federal government sends your tax dollars. So is it 12 00:00:39,640 --> 00:00:43,000 Speaker 1: biparts enough to actually pass? We break that down as well. 13 00:00:43,400 --> 00:00:46,879 Speaker 1: It's the weekend review and it starts right now. Senator 14 00:00:47,000 --> 00:00:49,160 Speaker 1: I want to start off this last segment by saying, 15 00:00:49,280 --> 00:00:52,520 Speaker 1: I don't ever want our government to be weaponized against 16 00:00:52,600 --> 00:00:55,320 Speaker 1: our political adversaries. Not that they't to use the word enemy. 17 00:00:55,320 --> 00:00:58,880 Speaker 1: Democrats use the word enemy to describe Republicans, I say adversaries, 18 00:00:59,560 --> 00:01:02,600 Speaker 1: but I do want to hold those accountable that are 19 00:01:02,720 --> 00:01:06,520 Speaker 1: actually doing corrupt things. And we now know a lot 20 00:01:06,600 --> 00:01:10,920 Speaker 1: more about the investigation and the Chinese Communist Party tycoon 21 00:01:11,080 --> 00:01:14,080 Speaker 1: Nevil Roy Singham, and it should get a lot more 22 00:01:14,080 --> 00:01:16,560 Speaker 1: attention than it is right now. Certainly the media they 23 00:01:16,600 --> 00:01:17,640 Speaker 1: are looking the other way. 24 00:01:18,120 --> 00:01:20,480 Speaker 2: Well, that's exactly right. And you know, we ended the 25 00:01:20,560 --> 00:01:24,200 Speaker 2: last segment by talking about the need for accountability of 26 00:01:24,240 --> 00:01:28,360 Speaker 2: the corruption within the Biden administration, that those who broke 27 00:01:28,440 --> 00:01:31,280 Speaker 2: the law need to be held to account. And on 28 00:01:31,319 --> 00:01:35,640 Speaker 2: this podcast we have talked at great length about the 29 00:01:35,720 --> 00:01:39,319 Speaker 2: need to follow the money that these anti American efforts. Look, 30 00:01:39,360 --> 00:01:41,640 Speaker 2: if you look at all of the stories in today's pod, 31 00:01:41,640 --> 00:01:46,760 Speaker 2: they're interwoven the DSSA. There is clearly a funding stream 32 00:01:46,959 --> 00:01:51,760 Speaker 2: funding the antisemitic protests on college campuses, funding the communists 33 00:01:51,760 --> 00:01:55,760 Speaker 2: tearing this country apart, funding the DSSA, funding the Black 34 00:01:55,800 --> 00:01:58,440 Speaker 2: Lives Matter and ANTIFA riots across the country, funding the 35 00:01:58,480 --> 00:02:02,360 Speaker 2: open border riots in LA and elsewhere. The money stream, 36 00:02:02,640 --> 00:02:05,040 Speaker 2: and what I've urged the Department of Justice, what I've 37 00:02:05,120 --> 00:02:08,360 Speaker 2: urged the FBI from the beginning of this second Trump administration, 38 00:02:08,720 --> 00:02:11,959 Speaker 2: follow the money the people who are paying for this. 39 00:02:11,960 --> 00:02:14,440 Speaker 2: This is not organic when people carry out these acts 40 00:02:14,440 --> 00:02:17,000 Speaker 2: of violence, it's not organic. When you look at the 41 00:02:17,040 --> 00:02:21,720 Speaker 2: anti Semitic protests, the tents all match. Follow the money 42 00:02:21,760 --> 00:02:25,520 Speaker 2: and then we in a previous podcast couple of weeks ago, 43 00:02:25,600 --> 00:02:29,320 Speaker 2: talked about the bombshell story that we've all seen the 44 00:02:29,440 --> 00:02:33,399 Speaker 2: rising sentiment against AI that on the left and the right, 45 00:02:33,520 --> 00:02:35,960 Speaker 2: suddenly people are saying, gosh, I don't like AI. Shut 46 00:02:35,960 --> 00:02:39,000 Speaker 2: down data centers. Kathy Hokeeld just this past couple of 47 00:02:39,040 --> 00:02:41,920 Speaker 2: weeks said no data centers in New York, and the 48 00:02:41,960 --> 00:02:45,400 Speaker 2: bombshell story that much of that is being paid for 49 00:02:46,520 --> 00:02:51,040 Speaker 2: by a communist named Neville Roy Singham who has deep 50 00:02:51,160 --> 00:02:54,400 Speaker 2: ties to the Chinese Communist Party. And listen, we're in 51 00:02:54,520 --> 00:02:58,680 Speaker 2: a race America and China to see who will develop 52 00:02:58,720 --> 00:03:01,840 Speaker 2: AI first. If China wins, it will put China in 53 00:03:01,840 --> 00:03:06,760 Speaker 2: a position to dominate the world economically. But also whichever 54 00:03:06,800 --> 00:03:11,360 Speaker 2: country wins, the values of that country will dominate AI. 55 00:03:11,480 --> 00:03:16,360 Speaker 2: So if China wins, AI will be dominated by Communist 56 00:03:16,400 --> 00:03:22,400 Speaker 2: Party control and surveillance and propaganda and espionage. And I 57 00:03:22,440 --> 00:03:26,560 Speaker 2: think all of us want AI to instead reflect American values, 58 00:03:26,560 --> 00:03:31,959 Speaker 2: to reflect free speech and individual liberty and free enterprise. Well, 59 00:03:32,040 --> 00:03:35,680 Speaker 2: a bit of good news, which is the Trump Department 60 00:03:35,680 --> 00:03:38,480 Speaker 2: of Justice is doing exactly that. It's following the money 61 00:03:38,520 --> 00:03:40,960 Speaker 2: and it's holding people to account. Let me read from 62 00:03:40,960 --> 00:03:44,280 Speaker 2: a story in CBS News. Husband of Code Pink founder 63 00:03:44,320 --> 00:03:49,800 Speaker 2: being investigated under federal forhid agent and tax laws. Devilroy Singham, 64 00:03:49,800 --> 00:03:52,560 Speaker 2: the wealthy husband of the founder of the progressive nonprofit 65 00:03:52,600 --> 00:03:56,240 Speaker 2: Code Pink and the benefactor of far left political causes, 66 00:03:56,840 --> 00:03:59,680 Speaker 2: is under criminal investigation by a grand jury in the 67 00:03:59,720 --> 00:04:02,800 Speaker 2: Southern District of New York. According to multiple sources with 68 00:04:02,840 --> 00:04:05,960 Speaker 2: knowledge of the matter, the investigation began by looking into 69 00:04:06,000 --> 00:04:09,800 Speaker 2: possible violations of the Foreign Agents Registration Act and has 70 00:04:09,840 --> 00:04:13,520 Speaker 2: since expanded into a criminal tax probe over whether the 71 00:04:13,600 --> 00:04:18,680 Speaker 2: money was unlawfully funneled through nonprofits he controls, and whether 72 00:04:18,760 --> 00:04:21,960 Speaker 2: he lied on the tax forms for those nonprofits known 73 00:04:21,960 --> 00:04:27,880 Speaker 2: as nine nineties. Singham is a major financial backer of 74 00:04:27,920 --> 00:04:30,880 Speaker 2: a New York City based nonprofit called The People's Forum, 75 00:04:31,560 --> 00:04:35,200 Speaker 2: a left leaning nonprofit that advocates for causes impacting the 76 00:04:35,240 --> 00:04:39,040 Speaker 2: working class and other marginalized groups. He's also the founder 77 00:04:39,080 --> 00:04:42,000 Speaker 2: of thought Works, an IT consulting company, and is married 78 00:04:42,000 --> 00:04:45,400 Speaker 2: to Jody Evans, co founder of the anti war group 79 00:04:45,520 --> 00:04:50,719 Speaker 2: Code Pink. Singham sold thought Works to a private equity 80 00:04:50,760 --> 00:04:54,960 Speaker 2: firm in twenty seventeen for seven hundred and eighty five 81 00:04:55,080 --> 00:04:59,359 Speaker 2: million dollars. At around the same time, Singham moved his 82 00:04:59,480 --> 00:05:03,480 Speaker 2: business off operations to Shanghai, China, and began funding a 83 00:05:03,640 --> 00:05:08,359 Speaker 2: vast global network of nonprofits and think tanks to the 84 00:05:08,480 --> 00:05:13,760 Speaker 2: tune of hundreds of millions of dollars, according to reports 85 00:05:13,800 --> 00:05:16,880 Speaker 2: of The Free Press in The New York Times, Singham 86 00:05:16,920 --> 00:05:20,520 Speaker 2: moved the funds through shell companies and other opaque entities, 87 00:05:20,600 --> 00:05:27,400 Speaker 2: advancing his brand of leftist politics while pushing pro Beijing messaging. 88 00:05:28,320 --> 00:05:30,719 Speaker 2: He injected much of his own money into Code Pink, 89 00:05:31,400 --> 00:05:34,680 Speaker 2: funding up to a quarter of its operation, according to reports. 90 00:05:35,400 --> 00:05:39,760 Speaker 2: Soon Code Pink softened its stance on China, which had 91 00:05:39,800 --> 00:05:44,760 Speaker 2: previously been highly critical of Beijing's human rights policies. Among 92 00:05:44,839 --> 00:05:48,400 Speaker 2: other things, the group defended China against widespread reports its 93 00:05:48,440 --> 00:05:52,640 Speaker 2: government was committing genocide against a Muslim minority group in 94 00:05:52,640 --> 00:05:57,000 Speaker 2: the country's far northwest. So I and numerous other senators 95 00:05:57,040 --> 00:05:59,640 Speaker 2: of the Judiciary Committee have urged the Department of Justice 96 00:05:59,640 --> 00:06:03,320 Speaker 2: to look at into this. Chuck Grassley wrote a letter 97 00:06:03,960 --> 00:06:07,000 Speaker 2: urging DOJ to do that. Here's what Grass's letter said. Quote. 98 00:06:07,040 --> 00:06:09,560 Speaker 2: Evidence suggests that the People's Forum and Code Pink have 99 00:06:09,680 --> 00:06:13,839 Speaker 2: been funded and influenced by mister Nevill Roy Singham and 100 00:06:13,920 --> 00:06:17,479 Speaker 2: the Communist Chinese government, both of which are foreign principles. 101 00:06:17,800 --> 00:06:20,359 Speaker 2: The evidence also suggests that the People's Forum and Code 102 00:06:20,360 --> 00:06:24,760 Speaker 2: Pink have engaged in covered political activities that directly advance 103 00:06:24,880 --> 00:06:29,719 Speaker 2: the Communist Chinese government's political and policy interest and by 104 00:06:29,760 --> 00:06:35,159 Speaker 2: the way Nevilroy Singham's response to that is quote, I 105 00:06:35,240 --> 00:06:38,159 Speaker 2: categorically deny and repudiate any suggestion that I am a 106 00:06:38,200 --> 00:06:41,240 Speaker 2: member of work for, take orders from, or follow instructions 107 00:06:41,240 --> 00:06:45,000 Speaker 2: of any political party or government or their representatives. I 108 00:06:45,040 --> 00:06:48,280 Speaker 2: am solely guided by my beliefs, which are long held 109 00:06:48,560 --> 00:06:51,440 Speaker 2: personal views. So well, there's going to be an investigation 110 00:06:51,520 --> 00:06:54,000 Speaker 2: into it. I don't know if this guy is just 111 00:06:54,040 --> 00:06:56,720 Speaker 2: a communist who hates American and wants to destroy our nation, 112 00:06:57,320 --> 00:06:59,320 Speaker 2: or if he's a communist who hates American wants to 113 00:06:59,360 --> 00:07:02,320 Speaker 2: destroy our nation, who is working directly for and may 114 00:07:02,360 --> 00:07:05,000 Speaker 2: even be funded by the Chinese Communist government. That's one 115 00:07:05,040 --> 00:07:07,240 Speaker 2: of the things that I would imagine the investigation will 116 00:07:07,279 --> 00:07:11,200 Speaker 2: examine either way. I am very glad the Department of 117 00:07:11,360 --> 00:07:15,320 Speaker 2: Justice is examining the hundreds of millions of dollars he 118 00:07:15,480 --> 00:07:19,320 Speaker 2: is using to fund the people that are tearing our 119 00:07:19,360 --> 00:07:20,480 Speaker 2: country apart. 120 00:07:21,240 --> 00:07:23,680 Speaker 1: Yeah, and that's the key thing there. And if you're 121 00:07:23,680 --> 00:07:27,040 Speaker 1: doing something that is illegal and it's coming in with 122 00:07:27,120 --> 00:07:30,360 Speaker 1: the Chinese Communist Party, why would anyone not want that 123 00:07:30,440 --> 00:07:33,360 Speaker 1: to be investigated if that's what the evidence is showing. 124 00:07:33,800 --> 00:07:35,760 Speaker 1: That's the core part here that I think matters for 125 00:07:35,800 --> 00:07:36,560 Speaker 1: all Americans. 126 00:07:36,880 --> 00:07:39,200 Speaker 2: You know, it's one of the things that is dangerous 127 00:07:39,440 --> 00:07:42,000 Speaker 2: in this world where we're on social media, where you 128 00:07:42,040 --> 00:07:44,640 Speaker 2: see things or on x or Facebook or wherever you are, 129 00:07:45,080 --> 00:07:47,559 Speaker 2: and suddenly a lot of people seem concerned about something 130 00:07:47,560 --> 00:07:50,600 Speaker 2: and that can seem organic, and we are seeing more 131 00:07:50,640 --> 00:07:55,240 Speaker 2: and more paid foreign influence operations. And China puts a 132 00:07:55,280 --> 00:07:59,240 Speaker 2: lot of money into undermining America. Cutter puts a lot 133 00:07:59,280 --> 00:08:02,000 Speaker 2: of money into mining America. Iran puts a lot of 134 00:08:02,040 --> 00:08:04,880 Speaker 2: money into undermining America. You know, there was a report 135 00:08:04,880 --> 00:08:08,360 Speaker 2: from the Bitcoin Policy Institute that says for the past 136 00:08:08,440 --> 00:08:12,200 Speaker 2: five years, nonprofits funded by Nevil Roy Singham have been 137 00:08:12,240 --> 00:08:17,640 Speaker 2: putting out papers opposing export controls on advanced semiconductors to China, 138 00:08:18,520 --> 00:08:23,840 Speaker 2: putting out newsletters quoting Chinese communist officials blasting America's approach 139 00:08:24,400 --> 00:08:29,400 Speaker 2: to technology, and articles characterizing US data centers as fronts 140 00:08:29,440 --> 00:08:34,160 Speaker 2: in the quote new Cold War on China. And this 141 00:08:34,320 --> 00:08:40,960 Speaker 2: is a deliberate foreign influence effort that is targeting the 142 00:08:41,000 --> 00:08:44,560 Speaker 2: American economy, it's targeting AI, it's trying to get America 143 00:08:44,600 --> 00:08:48,560 Speaker 2: to stop leading an AI, and it's trying ultimately to 144 00:08:48,640 --> 00:08:53,400 Speaker 2: defeat capitalism and destroy our country. These it has the 145 00:08:53,520 --> 00:08:57,880 Speaker 2: exact same objectives as the DSA radicals that are taking 146 00:08:57,920 --> 00:08:58,959 Speaker 2: over the Democrat Party. 147 00:08:59,360 --> 00:09:02,120 Speaker 1: Now want to hear the rest of this conversation, you 148 00:09:02,160 --> 00:09:04,640 Speaker 1: can go back and listen to the full podcast from 149 00:09:04,679 --> 00:09:09,640 Speaker 1: earlier this week. Now onto story number two. That's incredible 150 00:09:09,720 --> 00:09:12,360 Speaker 1: you went. So you went from that back to d 151 00:09:12,520 --> 00:09:15,600 Speaker 1: C straight to the Oval Monday morning, yeap for a 152 00:09:15,760 --> 00:09:18,760 Speaker 1: very interesting meeting on AI at the White House. Talk 153 00:09:18,800 --> 00:09:19,719 Speaker 1: about that a little bit. 154 00:09:20,360 --> 00:09:23,520 Speaker 2: Yeah, So I took Amtrak and came from Manhattan down 155 00:09:23,520 --> 00:09:26,040 Speaker 2: to DC on Monday, and then I had a meeting 156 00:09:26,120 --> 00:09:27,080 Speaker 2: at the Oval Monday. 157 00:09:27,040 --> 00:09:28,840 Speaker 1: And by the way, that is what we call welcome 158 00:09:28,880 --> 00:09:30,520 Speaker 1: back to your real life when you go from the 159 00:09:30,520 --> 00:09:33,600 Speaker 1: World Cup Drew Barrymore to Amtrak to d C. I 160 00:09:33,640 --> 00:09:37,240 Speaker 1: just that's an interesting step down really quick, and that's 161 00:09:37,240 --> 00:09:40,000 Speaker 1: probably got on purpose doing that. But keep going oh yeah. 162 00:09:39,960 --> 00:09:42,600 Speaker 2: Yeah, look, look it was. And so the meeting in 163 00:09:42,640 --> 00:09:45,840 Speaker 2: the Oval, I was with the President, I was with 164 00:09:46,880 --> 00:09:49,960 Speaker 2: Marsha Blackburn, Senator from Tennessee, and I was with Scott 165 00:09:49,960 --> 00:09:52,120 Speaker 2: bess at the Treasury Secretary, and Kevin Hasset at the 166 00:09:52,120 --> 00:09:54,840 Speaker 2: head of the National Economic Council, and several other members 167 00:09:54,840 --> 00:09:57,800 Speaker 2: of the White House staff, and we were talking about AI, 168 00:09:58,120 --> 00:10:02,920 Speaker 2: artificial intelligence, and it was a discussion about what to 169 00:10:02,960 --> 00:10:06,040 Speaker 2: do about it. And listen, Marcia has a package of 170 00:10:06,080 --> 00:10:10,000 Speaker 2: bills that she's pitching, and it's a package of bills. 171 00:10:10,040 --> 00:10:16,160 Speaker 2: It's kids safety bills, it's requiring app stores to verify ages. 172 00:10:16,960 --> 00:10:20,520 Speaker 2: It's a bill called no Fakes, which which deals with 173 00:10:20,640 --> 00:10:25,320 Speaker 2: preventing people from from pirting and competing copying people's voices 174 00:10:25,400 --> 00:10:30,200 Speaker 2: and images. And so she was pitching to the President, 175 00:10:31,240 --> 00:10:34,920 Speaker 2: you should support my package of bills. And I'm chairman 176 00:10:35,000 --> 00:10:38,079 Speaker 2: of the Senate Committee on Commerce, Science, Transportation, which has 177 00:10:38,160 --> 00:10:42,120 Speaker 2: jurisdiction over a ton of stuff, including AI. And so 178 00:10:42,240 --> 00:10:43,680 Speaker 2: we're going to have a mark up in the next 179 00:10:43,679 --> 00:10:46,640 Speaker 2: couple of weeks on a bunch of AI bills, and 180 00:10:47,040 --> 00:10:48,760 Speaker 2: Marsha wants her a bill to be one of them, 181 00:10:48,800 --> 00:10:51,199 Speaker 2: and so she laid it out, and I got to 182 00:10:51,240 --> 00:10:53,640 Speaker 2: say a lot of discussions, she's pushing the president back 183 00:10:53,679 --> 00:10:56,360 Speaker 2: my bill, back my bill, back my bill, and I 184 00:10:56,440 --> 00:10:58,440 Speaker 2: stayed quiet for much of the meeting. The meeting was 185 00:10:58,480 --> 00:11:00,959 Speaker 2: like hour hour and a half long, and then I 186 00:11:01,000 --> 00:11:04,960 Speaker 2: said at the end, I said, listen, if Marcia introduces 187 00:11:05,000 --> 00:11:07,120 Speaker 2: the bill, I'll mark it up. I'll put it up 188 00:11:07,120 --> 00:11:10,920 Speaker 2: on the committee for a vote. And I said, I 189 00:11:10,960 --> 00:11:13,040 Speaker 2: expect all support it. All. To be honest, I'd never 190 00:11:13,080 --> 00:11:14,679 Speaker 2: read the bill until she handed it to me, so 191 00:11:14,720 --> 00:11:17,120 Speaker 2: I like, she handed me a hundred page bill and 192 00:11:17,360 --> 00:11:18,880 Speaker 2: I didn't know what was in it. But I said, 193 00:11:18,880 --> 00:11:21,480 Speaker 2: look from what she's described in it, I anticipate I'll 194 00:11:21,480 --> 00:11:25,040 Speaker 2: support it. But I also said it was kind of 195 00:11:25,080 --> 00:11:27,480 Speaker 2: near the end of the meeting, but I said, because 196 00:11:28,000 --> 00:11:32,560 Speaker 2: they had handed the president a truth social post supporting 197 00:11:32,559 --> 00:11:36,360 Speaker 2: the bill, and I said, look, someone needs to tell 198 00:11:36,440 --> 00:11:42,080 Speaker 2: you this bill has very little, if any chance of passing. 199 00:11:43,480 --> 00:11:46,720 Speaker 2: And like Trump was surprised, and I just said, look, 200 00:11:47,080 --> 00:11:49,120 Speaker 2: there are different elements of it. Right now. There are 201 00:11:49,120 --> 00:11:53,920 Speaker 2: no Democrats backing this bill. It's not clear that every 202 00:11:53,960 --> 00:11:56,120 Speaker 2: Republican on the committee will back the bill. Maybe they will, 203 00:11:56,160 --> 00:11:58,640 Speaker 2: they might and I said, let are you clear, I'll 204 00:11:58,640 --> 00:12:01,120 Speaker 2: mark it up and I expect to vote. So I'm 205 00:12:01,120 --> 00:12:03,400 Speaker 2: not the opposition here, but I just want you to 206 00:12:03,480 --> 00:12:08,880 Speaker 2: know that at this point there's opposition from Democrats in 207 00:12:08,920 --> 00:12:12,400 Speaker 2: the Senate, there's opposition potentially from some Republicans in the Senate, 208 00:12:12,720 --> 00:12:16,199 Speaker 2: and there's strong opposition on aspects of the bill from 209 00:12:16,360 --> 00:12:19,040 Speaker 2: Republican leadership in the House. And so I just said, 210 00:12:19,440 --> 00:12:21,400 Speaker 2: I don't want you to be surprised you lean in 211 00:12:21,480 --> 00:12:24,200 Speaker 2: and say let's go pass this bill and then it 212 00:12:24,240 --> 00:12:26,400 Speaker 2: doesn't pass. And so Trump said, all right, well, then 213 00:12:26,400 --> 00:12:27,679 Speaker 2: I'm not going to support it. I don't want to 214 00:12:27,679 --> 00:12:31,000 Speaker 2: support something that doesn't have a path to passage. And 215 00:12:31,400 --> 00:12:33,439 Speaker 2: so We're going to mark up a series of bills. 216 00:12:33,720 --> 00:12:35,440 Speaker 2: I've told Marsha if she wants me to mark up 217 00:12:35,440 --> 00:12:37,960 Speaker 2: her bill, we will. I don't know she will ask 218 00:12:38,000 --> 00:12:38,440 Speaker 2: for it or not. 219 00:12:39,120 --> 00:12:42,280 Speaker 1: Can you ask a politics question on this? Yeah? How 220 00:12:42,360 --> 00:12:46,480 Speaker 1: much of her bill is her pushing because she's running 221 00:12:46,480 --> 00:12:49,199 Speaker 1: for governor and really trying to get Tennessee's hands on 222 00:12:49,240 --> 00:12:52,640 Speaker 1: a lot of AI and AI infrastructure and AI and 223 00:12:52,720 --> 00:12:55,080 Speaker 1: the state. Not blame her for that, but like, is 224 00:12:55,120 --> 00:12:58,079 Speaker 1: that part of this hardcore push where you're in the Senate, 225 00:12:58,080 --> 00:13:00,400 Speaker 1: You're going I understand both sides of this. My reading 226 00:13:00,440 --> 00:13:01,000 Speaker 1: the room wrong. 227 00:13:01,679 --> 00:13:04,040 Speaker 2: So listen, they're different components of it. So let's take 228 00:13:04,040 --> 00:13:07,559 Speaker 2: the different elements of the bill. The first bill is COSA, 229 00:13:07,559 --> 00:13:09,920 Speaker 2: and COSA is a kid's safety bill. It's a good bill. 230 00:13:10,600 --> 00:13:13,640 Speaker 2: I've supported it. I've voted for it in the last Congress. 231 00:13:13,640 --> 00:13:16,640 Speaker 2: It passed the Senate ninety three to three. So I'm 232 00:13:16,679 --> 00:13:18,920 Speaker 2: all for COSA. I'm a yes, I want it to pass. 233 00:13:19,960 --> 00:13:22,439 Speaker 2: Here's the problem. After it passed the Senate ninety three 234 00:13:22,440 --> 00:13:27,160 Speaker 2: to three, it went to the House and the House 235 00:13:27,200 --> 00:13:30,640 Speaker 2: refused to take it up. Why because because the Speaker 236 00:13:30,679 --> 00:13:34,439 Speaker 2: of the House and Steve Scalise, the majority leader, opposed 237 00:13:34,440 --> 00:13:37,800 Speaker 2: the bill. And the bill puts what's called a duty 238 00:13:37,840 --> 00:13:41,920 Speaker 2: of care on the tech companies that if there's content 239 00:13:42,000 --> 00:13:45,959 Speaker 2: that harms kids, they can be sued. And the House 240 00:13:46,040 --> 00:13:49,160 Speaker 2: leadership doesn't support that. And so look, frankly, what I 241 00:13:49,200 --> 00:13:51,480 Speaker 2: told Marsha a year and a half ago is I said, listen, Mop, 242 00:13:51,559 --> 00:13:53,520 Speaker 2: I'll back COSA again. We can pass it again. I'm 243 00:13:53,559 --> 00:13:57,920 Speaker 2: fine with that, but it will never become law until 244 00:13:57,960 --> 00:14:00,679 Speaker 2: you sit down with Johnson and Scale and work out 245 00:14:00,679 --> 00:14:03,680 Speaker 2: an agreement, because if they refuse to take up the bill, 246 00:14:03,720 --> 00:14:05,400 Speaker 2: you want to pass it again, we can do it. 247 00:14:05,440 --> 00:14:08,040 Speaker 1: You'll get if they're not going to take it up. 248 00:14:09,120 --> 00:14:11,600 Speaker 2: If the House won't take it up, it's not going 249 00:14:11,679 --> 00:14:13,760 Speaker 2: to become in the US Code. And so I said, 250 00:14:14,880 --> 00:14:17,439 Speaker 2: what you need to do is sit down and negotiate 251 00:14:17,480 --> 00:14:19,760 Speaker 2: a compromise and it won't be everything you want, but 252 00:14:19,800 --> 00:14:21,800 Speaker 2: you need to find something the House is willing to 253 00:14:21,840 --> 00:14:26,200 Speaker 2: pass that hasn't happened. So that's a real impediment. I'm 254 00:14:26,200 --> 00:14:28,320 Speaker 2: going to vote for COSA. I want COSA to pass, 255 00:14:29,120 --> 00:14:32,400 Speaker 2: but right now the House is not going to take 256 00:14:32,440 --> 00:14:35,840 Speaker 2: it up. There's a second component, which is called the 257 00:14:35,840 --> 00:14:41,200 Speaker 2: App Store Accountability App, which is putting liability on an 258 00:14:41,240 --> 00:14:45,560 Speaker 2: app store for age verification. Now there are a couple 259 00:14:45,560 --> 00:14:49,359 Speaker 2: of problems with that Number One, there are tech companies 260 00:14:49,400 --> 00:14:53,720 Speaker 2: like Meta, like Facebook that support it, but Apple and 261 00:14:53,760 --> 00:14:56,520 Speaker 2: Google hate it because they're the app stores and they're like, wait, 262 00:14:56,560 --> 00:14:59,840 Speaker 2: you're making me liable. So Apple and Google don't like it, 263 00:15:00,040 --> 00:15:02,760 Speaker 2: so they're both the tech companies are divided their lobbying 264 00:15:02,760 --> 00:15:08,600 Speaker 2: on both sides. And there's a competing bill that is 265 00:15:08,640 --> 00:15:12,200 Speaker 2: called the Parents over Platforms bill, which is frankly the 266 00:15:12,240 --> 00:15:15,760 Speaker 2: Apple and Google bill, And there are several Republicans on 267 00:15:15,800 --> 00:15:19,080 Speaker 2: the committee that support that bill, and so I said, look, 268 00:15:19,080 --> 00:15:22,080 Speaker 2: this is just a pissing match between giant tech companies. 269 00:15:23,200 --> 00:15:26,560 Speaker 2: I'd like to see age verification. I support age verification, 270 00:15:26,600 --> 00:15:30,600 Speaker 2: I'm pushing for it. But every Democrat opposes age verification. 271 00:15:30,720 --> 00:15:32,800 Speaker 2: So I said, listen, it's a simple math. If you 272 00:15:32,840 --> 00:15:36,760 Speaker 2: lose all the Democrats and if you're losing some Republicans, 273 00:15:37,760 --> 00:15:40,120 Speaker 2: I don't see how this passes. Like it's just a math. 274 00:15:40,320 --> 00:15:43,480 Speaker 2: Like I'm not opposed to it. I will vote yes, 275 00:15:44,640 --> 00:15:46,480 Speaker 2: but how do you get to the votes to pass it. 276 00:15:48,720 --> 00:15:52,280 Speaker 2: There is additionally her bill No Fakes now no Fakes. 277 00:15:52,320 --> 00:15:55,040 Speaker 2: I'm on the Judiciary Committee. Judiciary Committee has already pased 278 00:15:55,040 --> 00:15:57,680 Speaker 2: no Fakes. It was a voice vote. I was fine 279 00:15:57,720 --> 00:16:00,000 Speaker 2: with it. No Fakes has a lot of good element 280 00:16:00,200 --> 00:16:03,440 Speaker 2: to it. So no fakes is protecting. Say you have 281 00:16:03,520 --> 00:16:06,640 Speaker 2: a musician and someone uses AI to create a fake 282 00:16:06,760 --> 00:16:09,280 Speaker 2: song for a musician, it makes you liable for that 283 00:16:10,440 --> 00:16:14,240 Speaker 2: in politics. By the way, this is coming. It hasn't 284 00:16:14,320 --> 00:16:16,680 Speaker 2: really happened yet, but it's coming soon. You're going to 285 00:16:16,720 --> 00:16:19,200 Speaker 2: see someone create AI and take a video of a 286 00:16:19,200 --> 00:16:24,960 Speaker 2: politician a fake video and be like we should eat 287 00:16:25,120 --> 00:16:29,080 Speaker 2: live kittens, and it's going to be you're not going 288 00:16:29,160 --> 00:16:30,920 Speaker 2: to be able to tell that it's fake, like it's 289 00:16:30,960 --> 00:16:32,720 Speaker 2: going to appear to be. The real problem. 290 00:16:32,800 --> 00:16:36,440 Speaker 1: Can have to respond to a ridiculous, absurd video, right. 291 00:16:36,920 --> 00:16:39,120 Speaker 2: And by the way, Amy Klovichar last year had a 292 00:16:39,200 --> 00:16:41,560 Speaker 2: video of a hearing where she said a bunch of 293 00:16:41,600 --> 00:16:45,800 Speaker 2: things that were derogatory that she would never have said, 294 00:16:45,840 --> 00:16:48,840 Speaker 2: but it looked entirely real and she had to respond 295 00:16:48,880 --> 00:16:53,080 Speaker 2: to that. That's going to explode a lot. So finding 296 00:16:53,120 --> 00:16:56,080 Speaker 2: some protections to say, look, someone can't use your name, 297 00:16:56,120 --> 00:17:00,120 Speaker 2: image and likeness and create a counterfeit that no but 298 00:17:00,200 --> 00:17:05,160 Speaker 2: he knows is fake. I'm quite supportive of that. When 299 00:17:05,160 --> 00:17:09,480 Speaker 2: the judiciary passed this bill, there were several Republicans Mike Lee, 300 00:17:10,040 --> 00:17:14,639 Speaker 2: Eric Schmidt, and myself who raised free speech concerns because 301 00:17:14,680 --> 00:17:16,879 Speaker 2: the way the language is written it's quite broad. So 302 00:17:16,960 --> 00:17:21,760 Speaker 2: for example, Trump send out the meme of a Keem 303 00:17:21,840 --> 00:17:26,199 Speaker 2: Jeffries and Chuck Schumer wearing sombrero singing yes, now that 304 00:17:26,359 --> 00:17:31,600 Speaker 2: was parody, it wasn't real, and I've retweeted it and 305 00:17:31,680 --> 00:17:36,280 Speaker 2: then amplified it, but there is an argument that under 306 00:17:36,320 --> 00:17:40,440 Speaker 2: the language to know fakes, that could be banned. Now 307 00:17:40,520 --> 00:17:45,919 Speaker 2: there is some language saying bonafide satire is okay, but 308 00:17:46,040 --> 00:17:47,960 Speaker 2: there's a lot of gray area. You think of Spencer 309 00:17:48,000 --> 00:17:53,879 Speaker 2: Pratt and the hysterical ads he put out with Gavin 310 00:17:53,960 --> 00:17:57,520 Speaker 2: Newsom and Karen Bass just like doing horrible things to 311 00:17:57,560 --> 00:18:02,040 Speaker 2: people of California. I have a concern that under the 312 00:18:02,119 --> 00:18:06,760 Speaker 2: language and no fakes, the tech platforms would take down 313 00:18:06,880 --> 00:18:11,159 Speaker 2: those ads because they'd say, you're using Gavin Newsom's image 314 00:18:11,960 --> 00:18:13,960 Speaker 2: in a way that he has not approved. And so 315 00:18:15,240 --> 00:18:18,320 Speaker 2: my point was, look, I'd love to see this get done, 316 00:18:18,480 --> 00:18:21,960 Speaker 2: but I also want to protect free speech. So my 317 00:18:22,200 --> 00:18:24,320 Speaker 2: point to the President was, Hey, if you want to 318 00:18:24,400 --> 00:18:26,640 Speaker 2: endorse this, great, I've got no problem with it, but 319 00:18:26,800 --> 00:18:31,159 Speaker 2: you need to know that I don't see a path 320 00:18:31,240 --> 00:18:33,920 Speaker 2: that this actually gets to pass in the Senate take 321 00:18:34,000 --> 00:18:37,280 Speaker 2: sixty votes, given that I don't know of a single 322 00:18:37,320 --> 00:18:42,040 Speaker 2: Democrat supporting this bill, and there may be Republicans opposing 323 00:18:42,080 --> 00:18:47,120 Speaker 2: this bill. The math doesn't work, and so the President 324 00:18:47,160 --> 00:18:51,880 Speaker 2: decided not to support it. Listen, I still expect that 325 00:18:51,960 --> 00:18:53,840 Speaker 2: we will take up in the next couple of weeks 326 00:18:54,080 --> 00:18:56,199 Speaker 2: a series of AI bills. And by the way, we 327 00:18:56,240 --> 00:18:58,560 Speaker 2: will do a podcast when we do that markup where 328 00:18:58,560 --> 00:19:01,600 Speaker 2: we talk about the AI bills pass. But what I'm 329 00:19:01,640 --> 00:19:03,879 Speaker 2: trying to do right now is find all right, let 330 00:19:03,960 --> 00:19:09,639 Speaker 2: me use a Kamala Harris phrase the ven diagram, that 331 00:19:09,800 --> 00:19:13,680 Speaker 2: is the intersection of what bills could make a positive 332 00:19:13,760 --> 00:19:17,640 Speaker 2: impact protecting people from some of the harms of AI yep, 333 00:19:17,720 --> 00:19:20,440 Speaker 2: but at the same time that have a real pass 334 00:19:20,720 --> 00:19:24,479 Speaker 2: to passage. And so we'll move several bills on that. 335 00:19:24,560 --> 00:19:28,560 Speaker 2: But I'm trying to find exactly the right intersection right there. 336 00:19:28,600 --> 00:19:31,680 Speaker 2: And so we had that conversation and the President agreed 337 00:19:31,680 --> 00:19:32,960 Speaker 2: with me as before. 338 00:19:33,119 --> 00:19:35,040 Speaker 1: If you want to hear the rest of this conversation 339 00:19:35,320 --> 00:19:37,639 Speaker 1: on this topic, you can go back and dow the 340 00:19:37,800 --> 00:19:40,359 Speaker 1: podcast from earlier this week to hear the entire thing. 341 00:19:41,640 --> 00:19:43,960 Speaker 1: I want to get back to the big story number 342 00:19:44,000 --> 00:19:46,280 Speaker 1: three of the week you may have missed, Senata, I 343 00:19:46,359 --> 00:19:48,639 Speaker 1: want to move to this education bill that is so 344 00:19:48,960 --> 00:19:53,440 Speaker 1: important that you have been working on. Explain what this 345 00:19:53,560 --> 00:19:57,840 Speaker 1: bill is, why it's important right now, and why American 346 00:19:57,880 --> 00:19:59,119 Speaker 1: should be paying attention to it. 347 00:19:59,560 --> 00:20:02,400 Speaker 2: Yeah. Look, you talked a minute ago about how one 348 00:20:02,400 --> 00:20:06,800 Speaker 2: of the reasons why we're having young people, particularly young 349 00:20:06,800 --> 00:20:09,520 Speaker 2: people who stay in the education system for a long time, 350 00:20:09,640 --> 00:20:14,080 Speaker 2: gets so radicalized, so left wing, so America, hating so capitalism, 351 00:20:14,160 --> 00:20:19,679 Speaker 2: hating so communism, embracing is because our education system is broken. 352 00:20:19,760 --> 00:20:23,000 Speaker 2: And that's certainly true at the university level, particularly the 353 00:20:23,000 --> 00:20:26,560 Speaker 2: so called elite universities, but it is also true in 354 00:20:26,640 --> 00:20:30,480 Speaker 2: K through twelve. And one consequence of K through twelve 355 00:20:30,520 --> 00:20:34,080 Speaker 2: getting radicalized is that it drives the politics crazy left. 356 00:20:34,800 --> 00:20:38,080 Speaker 2: But another consequence is they failed in their basic job 357 00:20:38,119 --> 00:20:41,040 Speaker 2: of teaching. And you know, you used to go and 358 00:20:41,119 --> 00:20:44,240 Speaker 2: learn the three r's, reading, writing, and arithmetic, And I 359 00:20:44,240 --> 00:20:46,199 Speaker 2: mean that used to be like the core of what 360 00:20:46,240 --> 00:20:48,960 Speaker 2: you were learning. Yeah, if you look. 361 00:20:48,800 --> 00:20:51,200 Speaker 1: At a novel idea. By the way, what a novel idea? 362 00:20:51,240 --> 00:20:54,199 Speaker 1: You go to school to learn to read, writing to arithmetic, Like, 363 00:20:54,280 --> 00:20:56,720 Speaker 1: isn't that amazing that someone came up with that curriculum 364 00:20:56,720 --> 00:20:59,240 Speaker 1: one day and then we just decided to abandon it right. 365 00:21:00,080 --> 00:21:04,000 Speaker 2: Well, and there is a literacy crisis. The numbers of 366 00:21:04,200 --> 00:21:07,760 Speaker 2: students coming out of school who can't read, who don't 367 00:21:07,800 --> 00:21:09,560 Speaker 2: have the ability to read, is staggering. I'm gonna give 368 00:21:09,560 --> 00:21:13,560 Speaker 2: you some of the stats. So in twenty twenty four, 369 00:21:13,680 --> 00:21:17,920 Speaker 2: the National Assessment of Educational Progress what's called the NAPE, 370 00:21:17,760 --> 00:21:22,680 Speaker 2: the reading assessment, showed that thirty three percent of eighth 371 00:21:22,680 --> 00:21:27,920 Speaker 2: graders are reading at a level that is quote below basic. 372 00:21:28,560 --> 00:21:31,240 Speaker 2: Thirty three percent. A third of eighth graders can't read 373 00:21:31,800 --> 00:21:36,160 Speaker 2: at even the barest minimum of levels. For twelfth graders, 374 00:21:36,880 --> 00:21:41,040 Speaker 2: the average reading scores were three points lower than in 375 00:21:41,080 --> 00:21:45,320 Speaker 2: twenty nineteen and ten point points lower than in nineteen 376 00:21:45,440 --> 00:21:51,680 Speaker 2: ninety two. So it is a staggering crisis. And one 377 00:21:51,680 --> 00:21:54,920 Speaker 2: of the big reasons for that it is that you've 378 00:21:54,960 --> 00:21:59,879 Speaker 2: had left wing radicals takeover teachers, colleges, education programs that 379 00:22:00,040 --> 00:22:04,880 Speaker 2: teachers unions, and they've moved away from what actually works. 380 00:22:06,119 --> 00:22:10,639 Speaker 2: They've adopted an approach to reading that is called three quing. 381 00:22:11,520 --> 00:22:17,199 Speaker 2: So three quing it is something that uses context and 382 00:22:17,320 --> 00:22:21,520 Speaker 2: pictures and sentence structures rather than phonics. Look, when I 383 00:22:21,600 --> 00:22:25,280 Speaker 2: learned to read, we learned phonics. We would diagram sentences. 384 00:22:25,320 --> 00:22:28,760 Speaker 2: Phonics works, and you know what we now know three 385 00:22:28,880 --> 00:22:35,080 Speaker 2: quing does not. It's a disaster and it's produced terrible results. 386 00:22:35,080 --> 00:22:38,080 Speaker 2: So a number of states Florida, Indiana, North Carolina, Ohio, 387 00:22:38,200 --> 00:22:42,120 Speaker 2: South Carolina, Texas, West Virginia, and Wisconsin have all banned 388 00:22:42,600 --> 00:22:46,680 Speaker 2: teaching three qing because the data are terrible. It fails 389 00:22:46,760 --> 00:22:51,359 Speaker 2: to teach kids to read. What is amazing, though, is 390 00:22:51,400 --> 00:22:55,840 Speaker 2: a number of schools instead have focused on what's called 391 00:22:55,840 --> 00:22:59,360 Speaker 2: the science of reading, which is going back to phonics, 392 00:22:59,400 --> 00:23:02,800 Speaker 2: going back to the basics of teaching reading. And the 393 00:23:02,840 --> 00:23:06,520 Speaker 2: results have been staggering. And there's something called all right, 394 00:23:06,680 --> 00:23:09,200 Speaker 2: you're an all miss grad You're gonna like this. There's 395 00:23:09,240 --> 00:23:12,160 Speaker 2: something called the Mississippi Miracle. 396 00:23:13,160 --> 00:23:16,680 Speaker 1: So love this already, keep singing this song. I'm ready. 397 00:23:17,720 --> 00:23:23,080 Speaker 2: In twenty thirteen, Mississippi's reading numbers were not good. Mississippi 398 00:23:23,200 --> 00:23:27,080 Speaker 2: was forty ninth in the nation on the national assessments 399 00:23:27,080 --> 00:23:31,520 Speaker 2: and reading. They began then going in on the science 400 00:23:31,600 --> 00:23:35,720 Speaker 2: of reading and vigorously teaching phonics, and Mississippi has risen 401 00:23:35,760 --> 00:23:40,000 Speaker 2: from forty nine in the country to a top ten 402 00:23:40,320 --> 00:23:44,360 Speaker 2: state in the country in fourth grade reading achievement. By 403 00:23:44,400 --> 00:23:47,600 Speaker 2: the way, it wasn't money that did it, it was 404 00:23:47,760 --> 00:23:52,159 Speaker 2: actually teaching what works. Alabama, by the way, did the 405 00:23:52,200 --> 00:23:57,520 Speaker 2: same thing. They moved from forty ninth to thirty fourth. Louisiana, 406 00:23:57,680 --> 00:24:02,040 Speaker 2: Louisiana moved from forty ninth to thirty seconds. And here's 407 00:24:02,080 --> 00:24:04,000 Speaker 2: what the New York Times said, you're gonna like this. 408 00:24:05,160 --> 00:24:07,760 Speaker 2: The New York Times said, in twenty nineteen, blue states 409 00:24:07,760 --> 00:24:10,480 Speaker 2: had better average test scores than red states after adjusting 410 00:24:10,480 --> 00:24:15,239 Speaker 2: for democraphics. Now red states are mostly ahead. That's the 411 00:24:15,280 --> 00:24:18,919 Speaker 2: New York Times. And so what happened on this legislation 412 00:24:19,800 --> 00:24:23,000 Speaker 2: is I introduce legislation this week that takes the existing 413 00:24:23,080 --> 00:24:25,840 Speaker 2: federal grants that go to education. There's a pretty big 414 00:24:26,160 --> 00:24:29,760 Speaker 2: funding stream from the federal government to states for education 415 00:24:29,920 --> 00:24:34,240 Speaker 2: and the reading funds. The legislation I introduced said, if 416 00:24:34,280 --> 00:24:37,800 Speaker 2: you want to get those reading funds, you have to 417 00:24:38,000 --> 00:24:42,600 Speaker 2: use the reading methods that are demonstrated empirically to work. 418 00:24:43,400 --> 00:24:46,679 Speaker 2: You have to have what actually works and what the 419 00:24:46,760 --> 00:24:50,760 Speaker 2: data shows work. You can't teach this garbage that results 420 00:24:50,800 --> 00:24:53,879 Speaker 2: in kids not learning. You've got to use the empirically 421 00:24:54,440 --> 00:24:58,280 Speaker 2: successful methods. And what's interesting, by the way, who's against 422 00:24:58,320 --> 00:24:58,800 Speaker 2: this bill? 423 00:24:58,840 --> 00:25:01,520 Speaker 1: Because if you have the data you just mentioned there 424 00:25:01,800 --> 00:25:04,760 Speaker 1: showing where this is working, you would think this would 425 00:25:04,800 --> 00:25:06,320 Speaker 1: be by partisan. 426 00:25:06,520 --> 00:25:09,520 Speaker 2: So it actually is. So I introduced this bill with 427 00:25:09,560 --> 00:25:12,440 Speaker 2: Brian Shotts. Brian Shotts is a Democrat. He's from Hawaii. 428 00:25:13,200 --> 00:25:17,919 Speaker 2: Interestingly enough, Brian is widely considered the next Democrat leader 429 00:25:18,440 --> 00:25:21,639 Speaker 2: in the Senate. He's widely considered the most likely successor 430 00:25:21,640 --> 00:25:25,399 Speaker 2: to Chuck Schumer. And Brian I know, well, he's a 431 00:25:25,440 --> 00:25:28,000 Speaker 2: friend of mine. He's on the Commerce Committee with me. 432 00:25:28,040 --> 00:25:29,760 Speaker 2: I'm the chairman of the Commerce Committee. He and I 433 00:25:29,760 --> 00:25:32,800 Speaker 2: have done a number of bills together. And look, would 434 00:25:32,800 --> 00:25:35,400 Speaker 2: you talk with Brian. He's a Democrat, so he can 435 00:25:35,440 --> 00:25:38,360 Speaker 2: be left wing on a lot of issues, but one 436 00:25:38,440 --> 00:25:40,800 Speaker 2: on one he can be quite reasonable. As you know, 437 00:25:40,920 --> 00:25:43,280 Speaker 2: I play hoops every week. Brian's come out several times 438 00:25:43,280 --> 00:25:46,240 Speaker 2: and played hoops with me. I mean, he's and I'm 439 00:25:46,280 --> 00:25:49,240 Speaker 2: going to say something that's going to surprise you. This 440 00:25:49,280 --> 00:25:50,240 Speaker 2: bill was his idea. 441 00:25:51,119 --> 00:25:51,479 Speaker 1: Really. 442 00:25:52,280 --> 00:25:54,840 Speaker 2: He came to me. He came to me on the 443 00:25:54,880 --> 00:25:57,840 Speaker 2: Senate floor and he said, Ted, have you've seen the 444 00:25:57,960 --> 00:26:01,800 Speaker 2: data from Mississippi and the Mississippi Miracle and the incredible 445 00:26:01,840 --> 00:26:04,080 Speaker 2: reading scores that are coming out of Mississippi. And by 446 00:26:04,119 --> 00:26:07,560 Speaker 2: the way, this doesn't happen often. Democrats don't praise red 447 00:26:07,600 --> 00:26:11,960 Speaker 2: states that often. And I said, yeah, I have. It's fantastic. 448 00:26:12,040 --> 00:26:14,959 Speaker 2: And he said, what do you think about us joining 449 00:26:15,000 --> 00:26:17,760 Speaker 2: together to draft legislation that would require if you're going 450 00:26:17,840 --> 00:26:20,000 Speaker 2: to get the federal funds that are going for literacy, 451 00:26:20,960 --> 00:26:24,560 Speaker 2: you've got to teach using the reading methods that the 452 00:26:24,680 --> 00:26:27,920 Speaker 2: data show actually produced results. And I said, I think 453 00:26:27,960 --> 00:26:30,480 Speaker 2: that'd be fantastic. I'm a huge fan of phonics. I 454 00:26:30,480 --> 00:26:34,520 Speaker 2: don't like these woke teaching methods that are just a 455 00:26:34,600 --> 00:26:37,960 Speaker 2: failure and a disaster. And it's interesting my team. I 456 00:26:38,000 --> 00:26:39,439 Speaker 2: went to them and so I said, hey, you know, 457 00:26:39,520 --> 00:26:43,200 Speaker 2: shots pitch doing this, and my team was skeptical. They said, 458 00:26:43,200 --> 00:26:45,760 Speaker 2: we don't really believe a Democrat's going to go along 459 00:26:45,800 --> 00:26:49,600 Speaker 2: with something that is praising what's working in red states 460 00:26:49,600 --> 00:26:54,720 Speaker 2: and by the way, implicitly criticizing the woke education policies 461 00:26:54,760 --> 00:26:57,920 Speaker 2: in many Blue states. To Brian's credit, Look, I mean 462 00:26:57,960 --> 00:27:02,239 Speaker 2: he we introduced it to getather. You asked who opposes it. 463 00:27:02,440 --> 00:27:05,040 Speaker 2: I will confess it's early enough now that I don't 464 00:27:05,040 --> 00:27:07,679 Speaker 2: want to give you an answer to that. My assumption, 465 00:27:07,880 --> 00:27:10,480 Speaker 2: My assumption is the teachers' unions will oppose it. My 466 00:27:10,560 --> 00:27:13,239 Speaker 2: assumption is some of the Blue states will oppose it, 467 00:27:13,920 --> 00:27:17,840 Speaker 2: and the sort of woke educrats, the people who are 468 00:27:17,880 --> 00:27:21,240 Speaker 2: teaching at the education schools who are teaching teachers who 469 00:27:21,240 --> 00:27:24,719 Speaker 2: are teaching this nonsense that doesn't work. I assume all 470 00:27:24,800 --> 00:27:28,439 Speaker 2: those guys will oppose it. But I'll say this, we 471 00:27:28,680 --> 00:27:30,399 Speaker 2: just introduced it. I'm going to try to see if 472 00:27:30,400 --> 00:27:33,679 Speaker 2: we could move it forward and maybe we get support 473 00:27:33,720 --> 00:27:34,680 Speaker 2: for it. I hope we do. 474 00:27:34,840 --> 00:27:36,360 Speaker 1: By the way, what do you need when you say 475 00:27:36,400 --> 00:27:39,680 Speaker 1: moving forward to people understand? And this is one of 476 00:27:39,680 --> 00:27:41,639 Speaker 1: the reasons why I love doing the show. When you 477 00:27:41,680 --> 00:27:44,359 Speaker 1: say you're hoping you get the support, what is moving 478 00:27:44,359 --> 00:27:46,440 Speaker 1: it forward actually look like in the legislature. 479 00:27:47,160 --> 00:27:50,439 Speaker 2: So look, you drop the bill initially. The next step 480 00:27:50,480 --> 00:27:53,240 Speaker 2: that we'll work on doing is trying to get other supporters, 481 00:27:53,320 --> 00:27:55,840 Speaker 2: trying to get other co sponsors. So I'll reach out 482 00:27:55,840 --> 00:27:58,479 Speaker 2: to other Republicans and other Democrats. Brian will reach out 483 00:27:58,520 --> 00:28:01,879 Speaker 2: to other Democrats and also Republicans. I'd like to get 484 00:28:02,680 --> 00:28:05,879 Speaker 2: a pretty good group of bipartisan co sponsors, and there 485 00:28:05,880 --> 00:28:07,800 Speaker 2: are number of Democrats that I've worked with on different 486 00:28:07,800 --> 00:28:09,960 Speaker 2: bills who and particularly given that it's Brian and me, 487 00:28:10,040 --> 00:28:12,879 Speaker 2: we I think we can get other senators to co 488 00:28:12,920 --> 00:28:14,960 Speaker 2: sponsor it. So let's say we get a half dozen 489 00:28:15,080 --> 00:28:17,800 Speaker 2: rs and a half dozen d's that starts to be 490 00:28:17,880 --> 00:28:19,800 Speaker 2: a bill that's got some real heft to it, because 491 00:28:19,840 --> 00:28:23,439 Speaker 2: you look, particularly if you've got some ideological diversity. The 492 00:28:23,560 --> 00:28:28,479 Speaker 2: bill would go, uh, go to to committee at first. 493 00:28:30,280 --> 00:28:33,040 Speaker 2: I assume this would go to what's called the Help Committee, 494 00:28:33,040 --> 00:28:36,119 Speaker 2: which is the Health, Education, Labor and Pensions Committee. So 495 00:28:36,200 --> 00:28:38,960 Speaker 2: the first step is to get the committee to mark 496 00:28:39,000 --> 00:28:43,200 Speaker 2: it up, will work to get more by more sponsors, 497 00:28:43,240 --> 00:28:45,800 Speaker 2: to get a bigger coalition behind it, and then I'll 498 00:28:45,800 --> 00:28:48,080 Speaker 2: go to the chairman of that committee, that's Bill Cassidy, 499 00:28:48,760 --> 00:28:50,600 Speaker 2: and ask him to mark it up, which is for 500 00:28:50,640 --> 00:28:52,320 Speaker 2: the committee to take it up and pass it. And 501 00:28:52,360 --> 00:28:54,680 Speaker 2: we've got if we've got a good enough coalition behind it, 502 00:28:54,680 --> 00:28:57,680 Speaker 2: we've got a real chance at that. Once it gets 503 00:28:57,680 --> 00:28:59,360 Speaker 2: out of committee. There are a couple of paths you 504 00:28:59,360 --> 00:29:02,720 Speaker 2: can take to pass. One path is to try to 505 00:29:02,760 --> 00:29:06,760 Speaker 2: pass it by unanimous consent. Now I've passed a lot 506 00:29:06,800 --> 00:29:09,200 Speaker 2: by unanimous consent. If you do the work and build 507 00:29:09,200 --> 00:29:12,000 Speaker 2: the coalition, you can get things done that way. But 508 00:29:12,200 --> 00:29:16,080 Speaker 2: a single senator can object, So I don't know right 509 00:29:16,120 --> 00:29:18,440 Speaker 2: now if this is possible. You may have an Elizabeth 510 00:29:18,480 --> 00:29:21,600 Speaker 2: Warren or someone on the far left who objects to this. Uh. 511 00:29:22,120 --> 00:29:25,800 Speaker 2: The other way to pass it is to attach it 512 00:29:26,200 --> 00:29:29,240 Speaker 2: to another vehicle that is moving another bill that is 513 00:29:29,280 --> 00:29:32,160 Speaker 2: being passed, to put it on that And and so 514 00:29:33,040 --> 00:29:34,720 Speaker 2: we've got some time to get there. We've got to 515 00:29:34,720 --> 00:29:36,680 Speaker 2: build the coalition, we've got to get it out of committee, 516 00:29:36,720 --> 00:29:39,120 Speaker 2: we've got to get it teed up where it's at 517 00:29:39,160 --> 00:29:40,959 Speaker 2: a position to then try to pass it. And then 518 00:29:40,960 --> 00:29:42,440 Speaker 2: when you get out of the Senate, then you try 519 00:29:42,440 --> 00:29:45,200 Speaker 2: to pass it in the House. And I'm confident the 520 00:29:45,280 --> 00:29:48,240 Speaker 2: President would sign it. So we are early in that process, 521 00:29:49,240 --> 00:29:52,120 Speaker 2: but I'm encouraged to see that that that we're able 522 00:29:52,160 --> 00:29:55,080 Speaker 2: to get a Democrat and Republican working together saying, look, 523 00:29:55,320 --> 00:29:57,720 Speaker 2: we really got to teach our kids to read that. 524 00:29:58,320 --> 00:30:00,200 Speaker 1: It should it should be one hundred to one in 525 00:30:00,200 --> 00:30:02,320 Speaker 1: my opinion, teaching kids to read that shit. It might 526 00:30:02,360 --> 00:30:05,800 Speaker 1: be a problem and it might be as always, thank 527 00:30:05,840 --> 00:30:08,760 Speaker 1: you for listening to Verdict with Center Ted Cruz Ben 528 00:30:08,800 --> 00:30:11,320 Speaker 1: Ferguson with you don't forget to deal with my podcast, 529 00:30:11,360 --> 00:30:13,160 Speaker 1: and you can listen to my podcast every other day 530 00:30:13,160 --> 00:30:15,080 Speaker 1: you're not listening to Verdict or each day when you 531 00:30:15,080 --> 00:30:17,640 Speaker 1: listen to Verdict. Afterwards, I'd love to have you as 532 00:30:17,640 --> 00:30:20,440 Speaker 1: a listener to again the Ben Ferguson Podcasts, and we 533 00:30:20,480 --> 00:30:22,760 Speaker 1: will see you back here on Monday morning.