1 00:00:00,440 --> 00:00:03,000 Speaker 1: Welcome to the Tutor Dixon Podcast. So, every now and 2 00:00:03,000 --> 00:00:06,560 Speaker 1: again a Democrat decides they are going to step into 3 00:00:06,640 --> 00:00:10,240 Speaker 1: that independent world. And we've seen that with Tulsea Gabbard 4 00:00:10,240 --> 00:00:12,440 Speaker 1: who is now in the administration. 5 00:00:12,840 --> 00:00:13,600 Speaker 2: We've seen that with. 6 00:00:13,880 --> 00:00:17,400 Speaker 1: A couple of other high profile Democrats. But some people 7 00:00:17,440 --> 00:00:19,680 Speaker 1: behind the scenes are doing that too, and so I'm 8 00:00:19,720 --> 00:00:22,480 Speaker 1: glad to say that today we have Alison Wynn with us. 9 00:00:22,520 --> 00:00:26,320 Speaker 1: She is a child refugee from Vietnam and she turned 10 00:00:26,320 --> 00:00:30,680 Speaker 1: into a Silicon Valley entrepreneur, a venture capitalist, and then 11 00:00:30,720 --> 00:00:35,080 Speaker 1: became a fundraiser for former President Barack Obama. But now 12 00:00:35,120 --> 00:00:38,519 Speaker 1: she's joined the world of the independence. Allison, thank you 13 00:00:38,560 --> 00:00:39,360 Speaker 1: for joining us. 14 00:00:39,680 --> 00:00:41,159 Speaker 3: Thanks for having me here, Tutor. 15 00:00:41,800 --> 00:00:43,800 Speaker 1: So tell us what I mean. I've read this article 16 00:00:43,840 --> 00:00:48,400 Speaker 1: that you have all this like democrat like these historical 17 00:00:48,440 --> 00:00:52,720 Speaker 1: things JFK's chair, President Obama painting all of the stuff, 18 00:00:52,760 --> 00:00:55,000 Speaker 1: and you're like, you know what, I feel like, it 19 00:00:55,080 --> 00:00:57,480 Speaker 1: wasn't it didn't go the direction I expected. 20 00:00:57,560 --> 00:00:59,520 Speaker 2: So kind of break that down for us. 21 00:01:00,240 --> 00:01:03,680 Speaker 3: Yes, I was a very idealistic kid. I grew up 22 00:01:03,680 --> 00:01:06,720 Speaker 3: from a war torn country, lived the American dream, became 23 00:01:06,840 --> 00:01:10,959 Speaker 3: part of the whole kind of Google, rise to dominance, 24 00:01:11,040 --> 00:01:14,840 Speaker 3: really believe in the idea of do know evil, and 25 00:01:14,880 --> 00:01:18,920 Speaker 3: then got really disillusion with Google seeing how the sausage 26 00:01:19,040 --> 00:01:23,000 Speaker 3: was made. Also, you know, went on the Obama bandwagon 27 00:01:23,280 --> 00:01:28,200 Speaker 3: as well, hope and inspiring young people, people of color. 28 00:01:28,720 --> 00:01:31,160 Speaker 3: He talked the talk, it was very much like Martin 29 00:01:31,240 --> 00:01:34,639 Speaker 3: Luther King, but when it came to walking the walk, 30 00:01:35,240 --> 00:01:39,559 Speaker 3: his politics were racially divisive. And I'm a very big 31 00:01:39,640 --> 00:01:44,360 Speaker 3: anti war proponent, much like President Trump. Of course, through 32 00:01:44,400 --> 00:01:48,200 Speaker 3: strength and we had more wars, we had more international 33 00:01:48,200 --> 00:01:52,560 Speaker 3: conflicts trying to topple all these regimes. This is exactly 34 00:01:52,600 --> 00:01:57,200 Speaker 3: what I'm against. What happened, what happened to peace, hope, prosperity. 35 00:01:57,720 --> 00:02:02,320 Speaker 3: So he was just another Bush Cheney puppet. And I 36 00:02:02,360 --> 00:02:06,480 Speaker 3: don't really blame him or Bill Clinton. They talk beautifully, 37 00:02:06,520 --> 00:02:10,600 Speaker 3: they're very charming, charismatic, but they are not hands on. 38 00:02:11,040 --> 00:02:14,640 Speaker 3: They don't have the skill set. And as an entrepreneur 39 00:02:14,680 --> 00:02:18,840 Speaker 3: in Silicon Valley engineering and science background, to be a CEO, 40 00:02:19,000 --> 00:02:22,320 Speaker 3: to be a successful investor, you have to think big, 41 00:02:22,320 --> 00:02:24,200 Speaker 3: you have to dream big, but you also have to 42 00:02:24,240 --> 00:02:29,200 Speaker 3: be very specific. Obama and Clinton's they were just professional 43 00:02:29,280 --> 00:02:32,640 Speaker 3: politicians and dreamers. They didn't know how to actually get 44 00:02:32,680 --> 00:02:36,560 Speaker 3: things done. I do believe the deep state just hijacked them, 45 00:02:36,960 --> 00:02:39,640 Speaker 3: and then they became part of the deep state themselves, 46 00:02:39,680 --> 00:02:44,800 Speaker 3: because that's the universe that they inhabit. They themselves were 47 00:02:44,840 --> 00:02:49,960 Speaker 3: criticizing the swamp, but because they didn't know another real world, 48 00:02:50,080 --> 00:02:52,320 Speaker 3: they became a swamp monster themselves. 49 00:02:52,840 --> 00:02:55,240 Speaker 1: You know, it's interesting that you say that, because I 50 00:02:55,240 --> 00:02:57,519 Speaker 1: think I've told this story on here before. But when 51 00:02:57,600 --> 00:03:00,840 Speaker 1: I was deciding whether or not I would run for office, 52 00:03:01,560 --> 00:03:03,400 Speaker 1: I was going around, I was talking to some of 53 00:03:03,440 --> 00:03:07,120 Speaker 1: the local elected officials and state elected officials, and I 54 00:03:07,160 --> 00:03:11,600 Speaker 1: walked into one of the leadership people's offices and we 55 00:03:11,639 --> 00:03:13,720 Speaker 1: sat down. We talked for a long time, and we 56 00:03:13,760 --> 00:03:16,880 Speaker 1: had both been in manufacturing, and so I was new 57 00:03:16,919 --> 00:03:20,000 Speaker 1: to this and I had it just sounds like you. 58 00:03:20,000 --> 00:03:22,520 Speaker 1: You know, I had this view of it was good 59 00:03:22,520 --> 00:03:25,040 Speaker 1: people that wanted to serve that walked in and they 60 00:03:25,080 --> 00:03:27,280 Speaker 1: decided that they would run for office. And running for 61 00:03:27,360 --> 00:03:30,960 Speaker 1: office was this a service? A service you wanted to 62 00:03:30,960 --> 00:03:33,639 Speaker 1: provide a service to other people. And as I walked 63 00:03:33,680 --> 00:03:35,880 Speaker 1: out of his office, he looked up at me and 64 00:03:35,960 --> 00:03:40,160 Speaker 1: he said, don't let it seduce you. And I remember thinking, oh, 65 00:03:40,200 --> 00:03:43,080 Speaker 1: that's a really gross thing to say. I and I 66 00:03:43,160 --> 00:03:45,480 Speaker 1: had no idea what he meant because I had not 67 00:03:45,840 --> 00:03:49,160 Speaker 1: been in this world. But exactly what you've just said, 68 00:03:49,200 --> 00:03:51,600 Speaker 1: it's like this, this swamp comes to you and not oh, 69 00:03:51,720 --> 00:03:53,640 Speaker 1: you could do this and you could help us out here. 70 00:03:53,840 --> 00:03:57,360 Speaker 1: And that's even the dark money and the super packs 71 00:03:57,400 --> 00:04:00,240 Speaker 1: and all of these things that the amount of money 72 00:04:00,360 --> 00:04:04,000 Speaker 1: in the political industry is so hard to not be 73 00:04:04,160 --> 00:04:07,720 Speaker 1: jocking for that. You are, oh, just compromise here, just 74 00:04:07,760 --> 00:04:10,480 Speaker 1: compromise there, and then suddenly you're lost. And I think 75 00:04:10,520 --> 00:04:13,840 Speaker 1: that's what he meant by that statement exactly. 76 00:04:13,920 --> 00:04:18,960 Speaker 3: That's part of the swamp, the metaphorical and actually literal swamp, 77 00:04:19,040 --> 00:04:22,520 Speaker 3: especially during the summer during DC. It's very human. I 78 00:04:22,600 --> 00:04:25,280 Speaker 3: just came from there, and a lot of it is 79 00:04:25,360 --> 00:04:30,279 Speaker 3: paid to play, and I refuse personally to be compromised. 80 00:04:30,320 --> 00:04:33,960 Speaker 3: And it seems like you are as well, because we 81 00:04:34,279 --> 00:04:38,280 Speaker 3: are builders, you and manufacturing me and tech so and 82 00:04:38,520 --> 00:04:42,240 Speaker 3: President Trump as well, because let's remember he's a builder 83 00:04:42,560 --> 00:04:45,080 Speaker 3: from Queens, New York. He knows how to talk to 84 00:04:45,760 --> 00:04:49,800 Speaker 3: the plumbers, the electricians, the craft people, and so he's 85 00:04:49,839 --> 00:04:52,560 Speaker 3: the first one, I mean, I've met him personally, and 86 00:04:52,640 --> 00:04:55,919 Speaker 3: he's the first one in and he talks to everybody 87 00:04:56,000 --> 00:04:59,600 Speaker 3: on the ground floor. I think that came from his dad, Fred, right, 88 00:04:59,640 --> 00:05:04,080 Speaker 3: And so that's how you minimize the swamp. You actually 89 00:05:04,200 --> 00:05:08,320 Speaker 3: outwork them and you just become so productive. That's really 90 00:05:08,360 --> 00:05:14,120 Speaker 3: the spirit of American innovation and entrepreneurship. That's why we 91 00:05:14,200 --> 00:05:18,880 Speaker 3: have all these innovation, whether it's the railroad, the car, 92 00:05:19,360 --> 00:05:25,359 Speaker 3: the the telephone, the Internet, AI, a lot of the 93 00:05:25,360 --> 00:05:29,920 Speaker 3: great American blockchain that we're trying to push offshore. Now 94 00:05:29,920 --> 00:05:33,040 Speaker 3: we're on shoring many of these companies. So I'm really 95 00:05:33,040 --> 00:05:37,120 Speaker 3: excited that we have a president and hopefully getting more 96 00:05:37,160 --> 00:05:40,839 Speaker 3: people and hopefully we can seduce you back to running 97 00:05:40,880 --> 00:05:45,839 Speaker 3: for office, tutor, because we need more doers and builders 98 00:05:45,880 --> 00:05:50,479 Speaker 3: in this country who can communicate and think big, but 99 00:05:50,640 --> 00:05:54,400 Speaker 3: who can actually do things and be very specific with 100 00:05:54,640 --> 00:05:58,040 Speaker 3: the way they communicate. And so we look at President 101 00:05:58,120 --> 00:06:02,560 Speaker 3: Trump's policies, promise has made and promises kept right with 102 00:06:02,640 --> 00:06:05,600 Speaker 3: the Big Beautiful Bill, he talked about taking care of 103 00:06:05,680 --> 00:06:09,880 Speaker 3: his base, the working class specifically, what does that mean, Well, 104 00:06:09,960 --> 00:06:14,880 Speaker 3: then that translates to no taxes on tips, on overtime. 105 00:06:15,240 --> 00:06:18,520 Speaker 3: That's what the working class is all about also uniting 106 00:06:18,560 --> 00:06:21,920 Speaker 3: the investor class, right, extending a lot of those twenty 107 00:06:22,000 --> 00:06:27,800 Speaker 3: sixteen Jobs Act for the light industrial investments. The vehicles 108 00:06:28,600 --> 00:06:33,040 Speaker 3: that many of these small medium sized businesses have, you know, 109 00:06:34,040 --> 00:06:37,520 Speaker 3: part of the opportunity zones if you have like a 110 00:06:37,600 --> 00:06:41,880 Speaker 3: light industrial truck aircraft for hauling stuff around. These are 111 00:06:41,920 --> 00:06:46,320 Speaker 3: like the specifics of running a business to really jumpstart 112 00:06:46,440 --> 00:06:51,000 Speaker 3: our economy manufacturing here in the US. And also all 113 00:06:51,040 --> 00:06:54,080 Speaker 3: these wonderful trade deals. Now we have seven fifty billion 114 00:06:54,120 --> 00:06:57,640 Speaker 3: dollars from the EU coming into the US, five point 115 00:06:57,600 --> 00:07:02,200 Speaker 3: fifty billion from pan alone. I brought in a small 116 00:07:02,200 --> 00:07:06,120 Speaker 3: amount sixty four billion from the country of Vietnam, and 117 00:07:06,160 --> 00:07:09,119 Speaker 3: I'm helping with like some small, you know investments a small, 118 00:07:09,160 --> 00:07:12,440 Speaker 3: medium sized country that was war torn. But you know, 119 00:07:12,560 --> 00:07:17,160 Speaker 3: Vietnam is doing what it can to really be a 120 00:07:17,200 --> 00:07:20,520 Speaker 3: great ally of the United States. And you know President 121 00:07:20,520 --> 00:07:25,400 Speaker 3: Trump knows how to do these deals and align everyone's interest. 122 00:07:25,520 --> 00:07:28,560 Speaker 3: So it's a win win. It's easy to say this, 123 00:07:28,840 --> 00:07:32,360 Speaker 3: but the devil is in the details, right to like, 124 00:07:32,720 --> 00:07:36,080 Speaker 3: wake up really early, be a deal junkie, look at 125 00:07:36,080 --> 00:07:38,720 Speaker 3: all the details. I mean, you know, with manufacturing, it's 126 00:07:38,720 --> 00:07:41,920 Speaker 3: all about the supply chain. It's all about your workforce, 127 00:07:42,280 --> 00:07:46,000 Speaker 3: so you have to want to be curious about that 128 00:07:46,520 --> 00:07:49,240 Speaker 3: and get all the ducks in a row. And you know, 129 00:07:49,320 --> 00:07:51,200 Speaker 3: it's not that hard at the end of the day. 130 00:07:51,200 --> 00:07:54,960 Speaker 3: But we just have a president and hopefully a party 131 00:07:55,320 --> 00:07:58,320 Speaker 3: in charge that is, you know, willing to get down 132 00:07:58,360 --> 00:07:59,080 Speaker 3: to business. 133 00:08:00,080 --> 00:08:02,120 Speaker 1: And I think it's it is an interesting party. You 134 00:08:02,240 --> 00:08:05,360 Speaker 1: talked about the Bushes, you talked about the Clintons and 135 00:08:05,440 --> 00:08:08,800 Speaker 1: the Obama's and that being kind of like a different 136 00:08:08,880 --> 00:08:13,400 Speaker 1: type of governing and Trump is I do believe different 137 00:08:13,440 --> 00:08:16,600 Speaker 1: because obviously we see r K in there, and like 138 00:08:16,640 --> 00:08:19,320 Speaker 1: I said, we see Tulca Gabbart, but we also see 139 00:08:19,440 --> 00:08:23,920 Speaker 1: Pete Hegseth and Pambondi, And it's an interesting group of 140 00:08:23,960 --> 00:08:29,240 Speaker 1: people who don't necessarily they're not necessarily lifelong Republicans, they 141 00:08:29,360 --> 00:08:33,120 Speaker 1: are lifelong Americans. And it's a really different message than 142 00:08:33,160 --> 00:08:35,920 Speaker 1: we've seen in the past. And I think there are 143 00:08:35,920 --> 00:08:37,760 Speaker 1: a lot of people out there saying, well, how do 144 00:08:37,840 --> 00:08:41,120 Speaker 1: we continue this? Because Trump has four years? There is 145 00:08:41,200 --> 00:08:44,800 Speaker 1: no other Donald Trump. No matter what who you create 146 00:08:45,000 --> 00:08:47,800 Speaker 1: or groom below him, there's no one that's going to 147 00:08:47,800 --> 00:08:50,280 Speaker 1: be Donald Trump again. So how do you keep this 148 00:08:50,440 --> 00:08:52,840 Speaker 1: swamp at bay. And I think one of the things 149 00:08:52,880 --> 00:08:57,079 Speaker 1: that you were covering was you're talking about AI and 150 00:08:57,120 --> 00:08:59,319 Speaker 1: you're talking about investment, you're talking about money coming in 151 00:08:59,360 --> 00:09:02,200 Speaker 1: from overseas. But I've also heard you talk about a 152 00:09:02,320 --> 00:09:05,240 Speaker 1: secure border. And as you talked about the workforce, it 153 00:09:05,280 --> 00:09:08,240 Speaker 1: made me think about the importance of making sure that 154 00:09:08,280 --> 00:09:11,320 Speaker 1: people are treated right in this country, because we've heard 155 00:09:11,360 --> 00:09:14,240 Speaker 1: all of these folks on the left complaining, Oh, if 156 00:09:14,240 --> 00:09:16,600 Speaker 1: you shut the border, we won't have people to clean 157 00:09:16,640 --> 00:09:19,160 Speaker 1: our toilets and pick our vegetables and get our fruit 158 00:09:19,200 --> 00:09:20,280 Speaker 1: to the grocery store. 159 00:09:21,120 --> 00:09:23,680 Speaker 2: And I kind of I have to push back. 160 00:09:23,480 --> 00:09:26,360 Speaker 1: On that a little bit, because if those people are needed, 161 00:09:27,200 --> 00:09:30,400 Speaker 1: a closed border allows us to make sure that the 162 00:09:30,480 --> 00:09:32,920 Speaker 1: right people are coming through and that they're also being 163 00:09:33,240 --> 00:09:36,360 Speaker 1: paid well, that they are being taken care of. If 164 00:09:36,400 --> 00:09:39,559 Speaker 1: you're being paid under the table, you're essentially slave labor. 165 00:09:40,840 --> 00:09:45,120 Speaker 3: That's right, we're actually taking better care of the immigrants. 166 00:09:45,160 --> 00:09:48,080 Speaker 3: We need to close the border. We can't this whole 167 00:09:48,200 --> 00:09:52,360 Speaker 3: open border, open sanctuary. I live in San Francisco, so 168 00:09:52,440 --> 00:09:57,200 Speaker 3: this social science experiment has failed. Okay, I've been on TV. 169 00:09:57,520 --> 00:10:00,360 Speaker 3: Was one of the first people on TV to call 170 00:10:00,480 --> 00:10:05,240 Speaker 3: out the governance of California of San Francisco raising three 171 00:10:05,280 --> 00:10:10,400 Speaker 3: teenagers here. During the whole FEDEROL crisis, there actually were 172 00:10:10,440 --> 00:10:13,679 Speaker 3: more drug users and drug dealers in San Francisco. It's 173 00:10:13,720 --> 00:10:16,160 Speaker 3: really hard to believe than there were high school students. 174 00:10:16,200 --> 00:10:19,080 Speaker 3: And there's something wrong with our society. Wow, and we 175 00:10:19,240 --> 00:10:22,880 Speaker 3: have to call that out. We've got to stop this insanity. 176 00:10:23,679 --> 00:10:27,240 Speaker 3: America first, family first, okay, and then now we have 177 00:10:27,320 --> 00:10:31,600 Speaker 3: to get into the specifics of immigration. I'm not an 178 00:10:31,679 --> 00:10:36,360 Speaker 3: immigration lawyer or specialist, right, but there are certain visas. 179 00:10:36,400 --> 00:10:39,600 Speaker 3: There's the EB five visa, there is the H one 180 00:10:39,720 --> 00:10:42,640 Speaker 3: B visa. We have a visa for students. Yes, that 181 00:10:42,760 --> 00:10:46,120 Speaker 3: needs to be reform, so that way we put American 182 00:10:46,160 --> 00:10:50,240 Speaker 3: students first. We also have visas for farm workers. Right. 183 00:10:50,559 --> 00:10:53,600 Speaker 3: And so when we have these arguments and talking head 184 00:10:54,040 --> 00:10:58,719 Speaker 3: on cable news such as MSNBC and CNN, they are 185 00:10:58,880 --> 00:11:03,080 Speaker 3: very reductive and oh you know, they're anti immigrants. It's like, okay, 186 00:11:03,440 --> 00:11:07,560 Speaker 3: big picture, you know, America is built on immigrants, but 187 00:11:07,840 --> 00:11:12,280 Speaker 3: hard working immigrants who went through the right process and 188 00:11:12,559 --> 00:11:16,679 Speaker 3: is making a contribution. I am an example of that 189 00:11:16,800 --> 00:11:20,520 Speaker 3: who came through this country legally. We stood in line. 190 00:11:21,040 --> 00:11:24,280 Speaker 3: We came to this country. My parents are hard working. 191 00:11:24,720 --> 00:11:28,600 Speaker 3: They sent all five kids to university. I went to 192 00:11:28,640 --> 00:11:33,040 Speaker 3: Stanford University. I made a contribution in tech. And so 193 00:11:33,200 --> 00:11:36,080 Speaker 3: now we have to look at the case of farm workers. 194 00:11:36,120 --> 00:11:39,520 Speaker 3: If we need more farm workers, there is a farm 195 00:11:39,559 --> 00:11:44,920 Speaker 3: working visa. We see how Spain and France have farm 196 00:11:44,960 --> 00:11:48,640 Speaker 3: worker visas. We have farm workers visa too. We can't 197 00:11:48,720 --> 00:11:55,120 Speaker 3: conflate open border sanctuary cities with the specific case of 198 00:11:55,240 --> 00:11:59,280 Speaker 3: farm visa workers. We have a special carve out for that. 199 00:11:59,679 --> 00:12:03,600 Speaker 3: If we need workers for a special industry, let's have 200 00:12:04,160 --> 00:12:06,440 Speaker 3: a carve out for that and do it in a 201 00:12:06,640 --> 00:12:10,600 Speaker 3: very orderly fashion. As you know, when you're running a 202 00:12:10,679 --> 00:12:14,160 Speaker 3: business in manufacturing or supply chain, you can't have these 203 00:12:14,200 --> 00:12:17,760 Speaker 3: broad strokes and you can't say, like you know, everything 204 00:12:17,840 --> 00:12:20,640 Speaker 3: is this or everything is that. Your business will fail, 205 00:12:20,760 --> 00:12:25,400 Speaker 3: your country will fail. We love all immigrants. Well, there 206 00:12:25,440 --> 00:12:29,560 Speaker 3: are legal immigrants and there are illegal immigrants. In that 207 00:12:29,679 --> 00:12:33,400 Speaker 3: illegal immigrants, there are violent criminals, and there is a 208 00:12:33,440 --> 00:12:36,960 Speaker 3: lot of them. And you know, manufacturing in the US 209 00:12:37,600 --> 00:12:41,720 Speaker 3: is very different from manufacturing in the US during the 210 00:12:41,760 --> 00:12:44,840 Speaker 3: seventies and eighties, when a lot of these illegal immigrants 211 00:12:45,080 --> 00:12:48,880 Speaker 3: came in during the seventies and eighties, it was a 212 00:12:48,920 --> 00:12:51,959 Speaker 3: lot simpler. Now it's you know, a lot of it 213 00:12:52,000 --> 00:12:54,679 Speaker 3: is like computer science, so you have to be very technical, 214 00:12:54,920 --> 00:12:57,240 Speaker 3: you have to know English. And so we when we 215 00:12:57,320 --> 00:13:01,280 Speaker 3: have this influx of illegal immigrants and they can't actually 216 00:13:01,360 --> 00:13:03,800 Speaker 3: work in a factory because a lot of our factory 217 00:13:03,840 --> 00:13:07,079 Speaker 3: jobs are gone, right, there's really nothing that they can do. 218 00:13:07,200 --> 00:13:09,959 Speaker 3: The easiest thing for them to do is to stand 219 00:13:10,320 --> 00:13:13,320 Speaker 3: in the streets of San Francisco. And there's a lot 220 00:13:13,360 --> 00:13:18,240 Speaker 3: of them selling fentanyl from the Mexican cartels to our children. 221 00:13:18,480 --> 00:13:21,960 Speaker 3: And so that's why we have more drug dealers and 222 00:13:22,360 --> 00:13:26,160 Speaker 3: users in San Francisco then there are high school students. 223 00:13:26,360 --> 00:13:30,640 Speaker 3: So that is a very specific case in point. I 224 00:13:30,679 --> 00:13:33,560 Speaker 3: only know about that because I am a mom of 225 00:13:33,640 --> 00:13:37,920 Speaker 3: three teenagers. But we need to have people who understand 226 00:13:38,480 --> 00:13:42,800 Speaker 3: the specific and who can have these types of policy 227 00:13:42,960 --> 00:13:47,520 Speaker 3: discussions instead of using fear and hate and saying, oh, 228 00:13:48,120 --> 00:13:51,679 Speaker 3: they just like hate brown and black people and all 229 00:13:51,720 --> 00:13:55,520 Speaker 3: these immigrants. It's like, no, we love immigrants this country. 230 00:13:55,520 --> 00:13:58,640 Speaker 3: We're all immigrants here, even the Native Americans. They came 231 00:13:58,679 --> 00:14:03,160 Speaker 3: here through the land bridged and so we love immigrants. 232 00:14:03,160 --> 00:14:05,880 Speaker 3: But we love legal, hard working immigrants. 233 00:14:06,280 --> 00:14:09,000 Speaker 1: Let's take a quick commercial break. We'll continue next on 234 00:14:09,040 --> 00:14:15,480 Speaker 1: the Tutor Dixon Podcast. The depressing part about the fact 235 00:14:15,520 --> 00:14:18,400 Speaker 1: that we can't have people work in a bipartisan manner anymore, 236 00:14:18,480 --> 00:14:21,800 Speaker 1: because we have talked for decades about the need for 237 00:14:21,880 --> 00:14:25,320 Speaker 1: immigration reform, and what you're talking about is something that 238 00:14:25,360 --> 00:14:28,400 Speaker 1: could be very easily looked at by folks in the 239 00:14:28,440 --> 00:14:30,680 Speaker 1: Senate if you had senators on either side of the aisle, 240 00:14:30,720 --> 00:14:33,920 Speaker 1: folks in the House come together and say, let's look 241 00:14:33,920 --> 00:14:36,480 Speaker 1: at what it would be to make sure that we 242 00:14:36,600 --> 00:14:39,040 Speaker 1: have the right amount of farm workers. Because having an 243 00:14:39,080 --> 00:14:42,920 Speaker 1: open border does not mean that you have, oh, all 244 00:14:43,000 --> 00:14:45,560 Speaker 1: of our farms are perfectly staffed with the right amount 245 00:14:45,600 --> 00:14:48,600 Speaker 1: of people. You can do that and still know who's 246 00:14:48,640 --> 00:14:49,840 Speaker 1: in the country. 247 00:14:49,880 --> 00:14:51,920 Speaker 2: These two things are not mutually exclusive. 248 00:14:51,960 --> 00:14:54,440 Speaker 1: You don't have to have an open border to have 249 00:14:54,560 --> 00:14:55,960 Speaker 1: people working that. 250 00:14:56,280 --> 00:14:59,000 Speaker 2: It just has to Life has changed, things are different. 251 00:14:59,080 --> 00:15:01,040 Speaker 1: Let's make sure the right pa people coming in and 252 00:15:01,160 --> 00:15:06,160 Speaker 1: we have a policy and a system that works for 253 00:15:06,280 --> 00:15:07,040 Speaker 1: people today. 254 00:15:07,280 --> 00:15:08,520 Speaker 2: You've also talked about. 255 00:15:08,320 --> 00:15:10,320 Speaker 1: Law and order a lot, and that is something that 256 00:15:10,400 --> 00:15:15,320 Speaker 1: has kind of been also something I mean, we certainly 257 00:15:15,320 --> 00:15:18,040 Speaker 1: see the anti ice people, the anti ICE people are. 258 00:15:18,400 --> 00:15:22,480 Speaker 1: That's a disaster, and that's a you see a lot 259 00:15:22,480 --> 00:15:26,440 Speaker 1: of conflict in California there, but you have also experienced, 260 00:15:26,520 --> 00:15:29,080 Speaker 1: especially in California, this idea that well, you're going to 261 00:15:29,120 --> 00:15:31,680 Speaker 1: be able to steal up to one thousand dollars, we 262 00:15:31,720 --> 00:15:33,640 Speaker 1: don't actually have to have police involved. 263 00:15:34,280 --> 00:15:35,400 Speaker 2: This has been a disaster. 264 00:15:35,840 --> 00:15:39,120 Speaker 3: What happened. Grocery stores have closed down. There's hardly any 265 00:15:39,120 --> 00:15:42,400 Speaker 3: grocery stores left in San Francisco. In some of the 266 00:15:42,440 --> 00:15:46,760 Speaker 3: neighborhoods right like Hayes Valley, the last Safeway, the last 267 00:15:46,760 --> 00:15:51,920 Speaker 3: grocery store closed. And so there are unintended consequences to 268 00:15:52,200 --> 00:15:59,240 Speaker 3: these ultraliberal socialist ideas, and it is a social science 269 00:15:59,320 --> 00:16:02,400 Speaker 3: experiment that has failed. We need to go back to 270 00:16:02,800 --> 00:16:06,000 Speaker 3: common sense. And it's really not that hard, but we 271 00:16:06,120 --> 00:16:09,600 Speaker 3: need I guess, like, when I hear you talk, see 272 00:16:09,640 --> 00:16:14,160 Speaker 3: you're going deep. So you have the stamina, whether it's 273 00:16:14,480 --> 00:16:18,480 Speaker 3: law and order or immigration. So let's really think about this, 274 00:16:18,640 --> 00:16:23,760 Speaker 3: and let's go through the logical consequences of hating on 275 00:16:23,920 --> 00:16:29,520 Speaker 3: ICE and like being anti ICE, and let's have these 276 00:16:29,560 --> 00:16:34,040 Speaker 3: policies where you know, we feel so empathetic to the 277 00:16:34,160 --> 00:16:38,520 Speaker 3: criminals and to the illegal immigrants that we come up 278 00:16:38,560 --> 00:16:41,680 Speaker 3: with these policies that allow them to steal up to 279 00:16:41,960 --> 00:16:46,880 Speaker 3: one thousand dollars per transaction. Right, And so what happens 280 00:16:47,160 --> 00:16:52,000 Speaker 3: now we get into the specific details which the liberal 281 00:16:52,080 --> 00:16:56,160 Speaker 3: lawmakers didn't think about because they didn't have that intellectual 282 00:16:56,200 --> 00:16:59,560 Speaker 3: stamina to like go through we have to actually sit down, 283 00:17:00,040 --> 00:17:01,720 Speaker 3: you know. It's like, oh, we come up with something 284 00:17:01,840 --> 00:17:04,320 Speaker 3: like just really quick, and it helps us get the vote, 285 00:17:04,400 --> 00:17:07,119 Speaker 3: and it's like, oh, it makes us feel good. Oh 286 00:17:07,240 --> 00:17:09,879 Speaker 3: you know, it's like les miserrole. And it's like, you know, 287 00:17:09,960 --> 00:17:13,439 Speaker 3: if you're starving, of course you should have you know, 288 00:17:13,520 --> 00:17:16,440 Speaker 3: a bad get right, and like don't like go after 289 00:17:16,560 --> 00:17:18,840 Speaker 3: us and like throw us twenty years in jail. So, 290 00:17:19,000 --> 00:17:22,000 Speaker 3: I mean, these are some of the socialist ideas, the 291 00:17:22,000 --> 00:17:25,600 Speaker 3: Marxist ideas that help to come up with like the 292 00:17:25,680 --> 00:17:30,960 Speaker 3: liberal idealism. It is very seductive and that's how they 293 00:17:31,080 --> 00:17:34,119 Speaker 3: talk to pull you into the swamp and you become 294 00:17:34,119 --> 00:17:38,560 Speaker 3: a swamp monster. But when we actually stand still and 295 00:17:38,760 --> 00:17:42,520 Speaker 3: think deeply and have that stamina to look at the 296 00:17:42,600 --> 00:17:45,199 Speaker 3: truth in the eye, the truth is very dangerous and 297 00:17:45,240 --> 00:17:49,679 Speaker 3: it will set you free. And the truth being that Okay, 298 00:17:49,840 --> 00:17:53,080 Speaker 3: what are the consequences of allowing someone to steal up 299 00:17:53,160 --> 00:17:56,679 Speaker 3: to one thousand dollars? And technically it's a thousand dollars 300 00:17:56,760 --> 00:17:58,960 Speaker 3: at a time. So I can steal this for a 301 00:17:59,000 --> 00:18:01,159 Speaker 3: thousand and then I and I give it to this 302 00:18:01,200 --> 00:18:04,080 Speaker 3: guy who then puts it on eBay right as part 303 00:18:04,200 --> 00:18:07,480 Speaker 3: of a criminal syndicate. Then I come back in and 304 00:18:07,520 --> 00:18:09,560 Speaker 3: then I'm doing that all day long. So it's not 305 00:18:09,640 --> 00:18:13,639 Speaker 3: even a thousand dollars. It's like, so we are now 306 00:18:13,880 --> 00:18:19,600 Speaker 3: we're awarding professional criminals. We're turning people and even students, 307 00:18:19,720 --> 00:18:22,240 Speaker 3: like young people as young as like ten or fourteen? 308 00:18:22,520 --> 00:18:25,240 Speaker 3: Why work? Why go to school? This is a first 309 00:18:25,359 --> 00:18:30,760 Speaker 3: principle of now economics, you know, the very basis of 310 00:18:31,320 --> 00:18:35,439 Speaker 3: human actions and intellect. So we need to think about 311 00:18:35,560 --> 00:18:39,280 Speaker 3: first principles. There is the carrot and the stick, and 312 00:18:39,320 --> 00:18:42,720 Speaker 3: so there's a reward system. This is how human beings are. 313 00:18:42,960 --> 00:18:47,040 Speaker 3: So we're rewarding the young people, the people in California 314 00:18:47,160 --> 00:18:50,800 Speaker 3: to steal and not work. And this is the society 315 00:18:51,040 --> 00:18:54,400 Speaker 3: that we are encouraging. Is this what we want to do? 316 00:18:55,040 --> 00:18:58,280 Speaker 3: According to Gavin Newsom and some of the very liberal 317 00:18:58,680 --> 00:19:02,480 Speaker 3: mayors and politicians in California. Yes, and they need to 318 00:19:02,520 --> 00:19:05,320 Speaker 3: be called out. This doesn't make any cut. 319 00:19:05,880 --> 00:19:09,159 Speaker 1: That's also I remember AOC coming out and saying, you 320 00:19:09,200 --> 00:19:12,080 Speaker 1: have to understand, these people need to steal these high 321 00:19:12,160 --> 00:19:14,639 Speaker 1: end this high end merchandise. And I think this was 322 00:19:14,680 --> 00:19:18,800 Speaker 1: when Chicago, when the Magnificent Mile was just rated by 323 00:19:18,840 --> 00:19:21,320 Speaker 1: people who were stealing out of these high end stores. 324 00:19:21,760 --> 00:19:24,640 Speaker 1: And she said, they don't have enough bread for their 325 00:19:24,680 --> 00:19:26,840 Speaker 1: food at night, for their table at night. They have 326 00:19:26,920 --> 00:19:28,719 Speaker 1: to be able to steal so they can sell it 327 00:19:28,760 --> 00:19:31,760 Speaker 1: so that they can buy bread. Meanwhile, I mean you 328 00:19:31,840 --> 00:19:35,239 Speaker 1: tie the way you're talking getting into the depth of this. 329 00:19:35,520 --> 00:19:38,199 Speaker 1: You know, people go, oh, who cares. Walgreens is a 330 00:19:38,240 --> 00:19:41,800 Speaker 1: big corporation and they'll continue. Well, first of all, Walgreens, 331 00:19:41,920 --> 00:19:44,600 Speaker 1: even as a big corporation, can only take so much. 332 00:19:44,680 --> 00:19:47,320 Speaker 1: So their stores have been closing across the country. 333 00:19:47,520 --> 00:19:50,879 Speaker 3: But what about the mom and stores and they eloy 334 00:19:51,119 --> 00:19:55,120 Speaker 3: people pharmists, Yes, right, and so if you need drugs, 335 00:19:55,160 --> 00:19:58,360 Speaker 3: if you are on diabetic drug now you're driving ten 336 00:19:58,480 --> 00:20:01,719 Speaker 3: twenty miles away for your necessities. 337 00:20:01,760 --> 00:20:02,879 Speaker 2: So we have to go. 338 00:20:02,880 --> 00:20:05,760 Speaker 3: Really deep on that and not just like at that 339 00:20:05,960 --> 00:20:10,399 Speaker 3: superficial aocoh these you know, Ley Misrael. These people. 340 00:20:10,480 --> 00:20:11,680 Speaker 2: You know, it sounds so good. 341 00:20:11,720 --> 00:20:14,679 Speaker 1: I mean, you're right when you hear it, that sounds like, 342 00:20:14,760 --> 00:20:17,399 Speaker 1: oh my gosh, you know that. That Why aren't we 343 00:20:17,480 --> 00:20:19,040 Speaker 1: taking care of these people? 344 00:20:19,920 --> 00:20:24,040 Speaker 3: We're Americans, we're good Christian. Let's take care of the 345 00:20:24,160 --> 00:20:27,600 Speaker 3: less fortunate. But are they really less fortunate? Many of 346 00:20:27,600 --> 00:20:31,600 Speaker 3: them are making so much money. They're building mansions back 347 00:20:31,800 --> 00:20:37,080 Speaker 3: in Honduras and Guatemala, and uh, you know we're feeding 348 00:20:37,240 --> 00:20:40,760 Speaker 3: criminal enterprise. This isn't just small you know, mom. 349 00:20:40,560 --> 00:20:42,040 Speaker 2: And yeah, that's the problem. 350 00:20:42,080 --> 00:20:44,679 Speaker 1: You don't have any criminal enterprises. 351 00:20:45,520 --> 00:20:49,560 Speaker 3: Enterprise and they take so much stuff And there's a 352 00:20:49,680 --> 00:20:52,879 Speaker 3: van sitting in the parking lot and as soon as 353 00:20:52,880 --> 00:20:57,119 Speaker 3: they get it, they list it on eBay, on Amazon 354 00:20:57,520 --> 00:21:01,320 Speaker 3: or on Google. And big tech is complicit in this. 355 00:21:01,400 --> 00:21:05,080 Speaker 3: There's a whole eCos I think about that. Yeah, there's 356 00:21:05,119 --> 00:21:07,920 Speaker 3: a whole Like we really have to go very deep 357 00:21:08,440 --> 00:21:12,919 Speaker 3: into this and is it really helping the dignity of 358 00:21:13,040 --> 00:21:13,600 Speaker 3: the poor? 359 00:21:15,359 --> 00:21:18,960 Speaker 1: So how do you I mean, this is your background, 360 00:21:19,000 --> 00:21:20,440 Speaker 1: Big tech is your background. 361 00:21:20,640 --> 00:21:22,320 Speaker 2: How do you weed this out? 362 00:21:22,359 --> 00:21:24,920 Speaker 1: If you have people who are i mean even Facebook, 363 00:21:25,000 --> 00:21:27,359 Speaker 1: Marketplace and all these that could be a place where 364 00:21:27,400 --> 00:21:29,800 Speaker 1: people are just stealing and selling other people's stuff, which 365 00:21:29,840 --> 00:21:31,560 Speaker 1: I hadn't really thought about, but now that you bring 366 00:21:31,640 --> 00:21:32,920 Speaker 1: it up, I'm sure that is happening. 367 00:21:33,600 --> 00:21:37,560 Speaker 3: It is. That's how they're making money because they're moving 368 00:21:37,920 --> 00:21:40,119 Speaker 3: so much stuff, and it's not just like one thousand 369 00:21:40,200 --> 00:21:43,400 Speaker 3: dollars to feed their family. They're just going in and out, 370 00:21:43,440 --> 00:21:46,360 Speaker 3: in and out. And kids I know who are as 371 00:21:46,400 --> 00:21:49,360 Speaker 3: young as fourteen. Why do we need to work, Why 372 00:21:49,359 --> 00:21:52,159 Speaker 3: do we need to go to school? Whatever we need, 373 00:21:52,520 --> 00:21:54,800 Speaker 3: we can just go and then we can like steal 374 00:21:55,320 --> 00:21:58,720 Speaker 3: and then we could give it to this person, sell 375 00:21:58,720 --> 00:22:01,560 Speaker 3: it on eBay, give us the money. So that becomes 376 00:22:01,680 --> 00:22:06,960 Speaker 3: their reward system. So you know, it's a first principle 377 00:22:07,000 --> 00:22:11,359 Speaker 3: in terms of human behavior. You reward good behavior, you 378 00:22:11,400 --> 00:22:14,720 Speaker 3: punish bad behavior. And so now we've flipped it right, 379 00:22:15,080 --> 00:22:19,560 Speaker 3: So now we're rewarding bad behavior and punishing good behavior. 380 00:22:20,040 --> 00:22:24,280 Speaker 3: So if you're good Christian family values, you are being punished. 381 00:22:24,720 --> 00:22:28,440 Speaker 3: In the state of California. Your life is miserable. Taxes 382 00:22:28,440 --> 00:22:34,000 Speaker 3: are really high. It's very difficult to raise high school students. 383 00:22:34,359 --> 00:22:37,960 Speaker 3: Kids here at the public school. We're using our money 384 00:22:38,000 --> 00:22:42,280 Speaker 3: to support the drug dealers, the drug users, the homeless. 385 00:22:42,359 --> 00:22:45,240 Speaker 3: Fifty billion dollars for the homeless, and yet they've built 386 00:22:45,280 --> 00:22:48,840 Speaker 3: like a few houses. Where's all this money going? Yeah, 387 00:22:49,440 --> 00:22:53,119 Speaker 3: you know you really we need to have some investigative 388 00:22:53,680 --> 00:22:58,119 Speaker 3: reporters and forensic accountant to follow the money. I'm not 389 00:22:58,160 --> 00:23:02,320 Speaker 3: an expert in forensic accounting. I'm just a very practical 390 00:23:02,760 --> 00:23:06,360 Speaker 3: PTA mom, right, But it's just like, look, this doesn't 391 00:23:06,520 --> 00:23:10,159 Speaker 3: make sense. Like my budget at the high school is 392 00:23:10,400 --> 00:23:13,440 Speaker 3: xyz and I'm able to take care of the students, 393 00:23:13,480 --> 00:23:16,080 Speaker 3: the bus driver, and you have fifty billion and you 394 00:23:16,119 --> 00:23:19,600 Speaker 3: can't even build three houses and we have more homeless 395 00:23:19,640 --> 00:23:22,879 Speaker 3: than ever before. Where there's somebody really going I don't know. 396 00:23:23,040 --> 00:23:26,720 Speaker 1: Yes, that was ten years ago. It was in La 397 00:23:27,000 --> 00:23:30,760 Speaker 1: and La and San Francisco. They each had between three 398 00:23:30,760 --> 00:23:33,520 Speaker 1: and four hundred million that they put into homelessness. 399 00:23:33,720 --> 00:23:34,359 Speaker 2: Think about this. 400 00:23:34,600 --> 00:23:37,080 Speaker 1: That has just increased over time. So this is just 401 00:23:37,200 --> 00:23:40,679 Speaker 1: government jobs, government creating spaces for people to go. 402 00:23:41,000 --> 00:23:42,720 Speaker 2: But homelessness has gone up. 403 00:23:43,000 --> 00:23:47,720 Speaker 1: So how is this multiple hundreds of millions of dollars 404 00:23:47,760 --> 00:23:49,080 Speaker 1: being spent if. 405 00:23:48,880 --> 00:23:52,080 Speaker 2: I think the homeless number continues to rise. But that's it. 406 00:23:52,240 --> 00:23:56,119 Speaker 1: So the government across the country, government is the biggest employer. 407 00:23:56,400 --> 00:24:00,919 Speaker 1: They take care of healthcare, they take care of infrastructure, 408 00:24:01,200 --> 00:24:04,320 Speaker 1: and now they're involved in energy and you talk about AI. 409 00:24:04,520 --> 00:24:06,240 Speaker 2: This is something in the state of Michigan. 410 00:24:06,400 --> 00:24:08,360 Speaker 1: The State of Michigan has said, well, maybe we can 411 00:24:08,400 --> 00:24:12,960 Speaker 1: be a haven for tech. There's opportunities for us to 412 00:24:13,000 --> 00:24:15,560 Speaker 1: have data centers and to I mean, we have all. 413 00:24:15,480 --> 00:24:18,760 Speaker 3: Of this land, so we have great idea like native 414 00:24:18,960 --> 00:24:24,560 Speaker 3: AI supply chain, native AI based manufacturing. You guys should 415 00:24:24,600 --> 00:24:27,640 Speaker 3: really look at that, right and with all the investments 416 00:24:27,680 --> 00:24:33,600 Speaker 3: coming in, do smart AI manufacturing. I could. That's now 417 00:24:33,640 --> 00:24:35,000 Speaker 3: that's my lane. 418 00:24:35,800 --> 00:24:39,800 Speaker 1: But that's a huge opportunity. That is a huge opportunity 419 00:24:39,840 --> 00:24:42,119 Speaker 1: for the state of Michigan. The problem the state of 420 00:24:42,160 --> 00:24:44,800 Speaker 1: Michigan has is that in the Midwest, we have the 421 00:24:44,920 --> 00:24:48,239 Speaker 1: highest energy cost in the Midwest. So people look at 422 00:24:48,240 --> 00:24:50,600 Speaker 1: that and they go, oh, that doesn't those two things 423 00:24:50,640 --> 00:24:51,600 Speaker 1: don't marry together. 424 00:24:51,720 --> 00:24:54,720 Speaker 3: Well, why do you have that when like you're so 425 00:24:54,960 --> 00:24:57,960 Speaker 3: close to so I know, up in the. 426 00:24:58,000 --> 00:25:00,560 Speaker 2: Climate change, we got rid of all of our great energy. 427 00:25:01,080 --> 00:25:03,800 Speaker 3: Well what about like LNG. There's like you know, since 428 00:25:03,840 --> 00:25:07,920 Speaker 3: we kind of invented horizontal shale drilling, there's a lot 429 00:25:07,960 --> 00:25:11,120 Speaker 3: of LNG. So you can look at like the Dakotas, and. 430 00:25:11,480 --> 00:25:16,520 Speaker 2: You know, there are opportunities we canracking. 431 00:25:16,720 --> 00:25:20,600 Speaker 3: There's a bad reputation with fracking, right, so you know, 432 00:25:20,720 --> 00:25:24,520 Speaker 3: but we have those opportunities here smart fracking. You're getting 433 00:25:24,800 --> 00:25:29,280 Speaker 3: very inexpensive energy and energy is very clean. How about 434 00:25:29,760 --> 00:25:32,719 Speaker 3: now I'm just riffing, right because like in the normer 435 00:25:32,680 --> 00:25:32,920 Speaker 3: of the. 436 00:25:32,840 --> 00:25:35,760 Speaker 1: Things that that's where we we need a government that 437 00:25:35,800 --> 00:25:38,720 Speaker 1: can come together with people like you who come into 438 00:25:38,800 --> 00:25:41,439 Speaker 1: the state and say, okay, where are our opportunities to 439 00:25:41,520 --> 00:25:44,760 Speaker 1: reduce costs to increase energy, because that, to me is 440 00:25:44,800 --> 00:25:47,639 Speaker 1: the key to getting more businesses into this state. The 441 00:25:47,720 --> 00:25:51,520 Speaker 1: state has a beautiful workforce. We have machine shops galore, 442 00:25:51,680 --> 00:25:54,520 Speaker 1: We have all of the the setup necessary to have 443 00:25:54,680 --> 00:25:59,879 Speaker 1: incredibly effective manufacturing. But we just have this outrageous energy 444 00:26:00,080 --> 00:26:03,200 Speaker 1: costs and over regulation. But if you are I think it. 445 00:26:03,080 --> 00:26:07,119 Speaker 3: Is over regulation because this is in Michigan, the Dakotas, 446 00:26:07,160 --> 00:26:09,840 Speaker 3: the North. You're sitting on a lot of oil and 447 00:26:09,880 --> 00:26:14,760 Speaker 3: gas that you know, since horizontal drilling, you can drill 448 00:26:14,880 --> 00:26:18,399 Speaker 3: for oil and gas at a much cheaper price and 449 00:26:18,560 --> 00:26:23,840 Speaker 3: be very competitive with the Qatar, Russia. Some I know 450 00:26:23,960 --> 00:26:26,400 Speaker 3: a little bit about this to be dangerous because I'm 451 00:26:26,400 --> 00:26:29,840 Speaker 3: from the state of Texas, West Texas, and I remember 452 00:26:30,000 --> 00:26:33,240 Speaker 3: like the tech, you know, the whole landscape change around 453 00:26:33,280 --> 00:26:36,919 Speaker 3: like twenty ten, twenty twelve with horizontal drilling. It got 454 00:26:36,960 --> 00:26:39,879 Speaker 3: a bad name and a lot of environmental regulation. I 455 00:26:39,920 --> 00:26:43,800 Speaker 3: guess the street name is fracking, right, and they're like, oh, 456 00:26:43,880 --> 00:26:47,159 Speaker 3: it's going to poison the water with like Michigan. You 457 00:26:47,240 --> 00:26:49,679 Speaker 3: got flip Michigan and you know, so we have to 458 00:26:49,680 --> 00:26:52,720 Speaker 3: be very careful about that. But I think there are 459 00:26:52,960 --> 00:26:57,080 Speaker 3: very smart ways to do fracking and the filtering to 460 00:26:57,160 --> 00:27:00,280 Speaker 3: make sure that it doesn't affect the drinking water. And 461 00:27:00,359 --> 00:27:03,000 Speaker 3: so you have to be really smart with your regulation. 462 00:27:03,440 --> 00:27:05,840 Speaker 3: So and you're sitting on so much. You have like 463 00:27:05,920 --> 00:27:08,560 Speaker 3: the you know, the workforce, and you have to like 464 00:27:08,680 --> 00:27:12,040 Speaker 3: really gear up for that because many of them are aging. 465 00:27:12,280 --> 00:27:16,680 Speaker 3: They are our national treasures and they need to train 466 00:27:16,800 --> 00:27:19,560 Speaker 3: the next generation. Now we have to get into the details, 467 00:27:19,680 --> 00:27:22,760 Speaker 3: like we're getting these huge contracts from the EU and Japan, 468 00:27:23,200 --> 00:27:26,960 Speaker 3: but like, do we have the manufacturing know how? I 469 00:27:27,000 --> 00:27:29,960 Speaker 3: would assume that many of these people in Michigan, they're 470 00:27:30,000 --> 00:27:32,400 Speaker 3: probably in their fifties or sixties. 471 00:27:32,040 --> 00:27:36,000 Speaker 1: Right exactly. Our workforce is aging out. There's been this 472 00:27:36,040 --> 00:27:39,160 Speaker 1: demonization of manufacturing. Like you said at the beginning, when 473 00:27:39,240 --> 00:27:43,399 Speaker 1: you're saying, well, now that we don't have these tax on, 474 00:27:43,520 --> 00:27:48,280 Speaker 1: this tax on overtime, this makes our working class much stronger, 475 00:27:48,359 --> 00:27:50,200 Speaker 1: much more financially powerful. 476 00:27:50,520 --> 00:27:52,280 Speaker 2: They become they become. 477 00:27:52,160 --> 00:27:54,440 Speaker 1: Kind of like the gems that are able to invest 478 00:27:54,600 --> 00:27:57,720 Speaker 1: into the economy rather than people who have been struggling. 479 00:27:57,800 --> 00:28:00,920 Speaker 1: Now they have a much higher soulid then the person 480 00:28:00,920 --> 00:28:03,119 Speaker 1: who's coming out of college with a massive amount of 481 00:28:03,119 --> 00:28:05,640 Speaker 1: college debt. So you have people that can go directly 482 00:28:05,680 --> 00:28:08,760 Speaker 1: into the workforce and make a good salary, and now 483 00:28:08,960 --> 00:28:11,639 Speaker 1: with overtime, they can be making much more than the 484 00:28:11,680 --> 00:28:15,520 Speaker 1: average person. But those people are aging out. So we 485 00:28:15,640 --> 00:28:18,560 Speaker 1: have to reset the mindset of everybody has to go 486 00:28:18,600 --> 00:28:20,680 Speaker 1: to college, and everybody has to have an office job, 487 00:28:20,760 --> 00:28:24,040 Speaker 1: because some people are much better in an environment where 488 00:28:24,040 --> 00:28:26,399 Speaker 1: you're not sitting at desk all day, where you're making 489 00:28:26,440 --> 00:28:29,320 Speaker 1: something that is Some people's minds just work that way 490 00:28:29,480 --> 00:28:31,520 Speaker 1: and you can make a lot of money doing it. 491 00:28:31,520 --> 00:28:32,960 Speaker 2: It's not the dirty job. 492 00:28:32,840 --> 00:28:37,320 Speaker 3: More and sometimes more money, but it is. We have 493 00:28:37,359 --> 00:28:39,320 Speaker 3: to think about this holistic. We have to look at 494 00:28:39,320 --> 00:28:43,560 Speaker 3: the energy situation and also the environmental regulation Oh, we 495 00:28:43,600 --> 00:28:46,600 Speaker 3: need to save the environment. Oh that's bad for drinking water. 496 00:28:47,000 --> 00:28:50,360 Speaker 3: So yes, that happened in maybe late twenty ten, twenty 497 00:28:50,440 --> 00:28:54,720 Speaker 3: twelve when the technology just came out. And oftentimes that's 498 00:28:54,840 --> 00:28:59,160 Speaker 3: with technology cycles. When nuclear energy nuclear power came out, 499 00:28:59,160 --> 00:29:03,040 Speaker 3: it was very unstabed, remember like all the situations during 500 00:29:03,160 --> 00:29:06,240 Speaker 3: like the seventies, eighties or novel But now like nuclear 501 00:29:06,320 --> 00:29:09,800 Speaker 3: is coming back because we've learned ways to contain it 502 00:29:10,160 --> 00:29:14,200 Speaker 3: to really make it more efficient, more safe. I believe 503 00:29:14,240 --> 00:29:18,800 Speaker 3: it's the same. And I'm not an expert with horizontal drilling, 504 00:29:18,880 --> 00:29:23,640 Speaker 3: shill horizontal drilling or fracking, right, And so sometimes we 505 00:29:23,760 --> 00:29:27,240 Speaker 3: have the socialist liberal and they just get hung up 506 00:29:27,320 --> 00:29:30,400 Speaker 3: on an idea, got to save the planet. Oh that's 507 00:29:30,440 --> 00:29:32,920 Speaker 3: bad for the drinking it's bad for the environment. Well 508 00:29:33,080 --> 00:29:34,120 Speaker 3: what about the people? 509 00:29:34,920 --> 00:29:37,880 Speaker 1: Okay, So also, we're all on the same globe, so 510 00:29:37,960 --> 00:29:40,400 Speaker 1: you'd rather have it done in China. They're just they're 511 00:29:40,440 --> 00:29:43,040 Speaker 1: just ignoring the fact that it's actually still being done. 512 00:29:43,240 --> 00:29:45,840 Speaker 1: You're not manufacturing here. The money is all going to China. 513 00:29:46,160 --> 00:29:48,600 Speaker 1: They are one of the biggest I think they are 514 00:29:48,600 --> 00:29:50,360 Speaker 1: the biggest polluter in the world. 515 00:29:50,440 --> 00:29:51,720 Speaker 2: We're all living on the same world. 516 00:29:51,760 --> 00:29:54,920 Speaker 1: Wouldn't you rather the manufacturing be done here where we're 517 00:29:54,960 --> 00:29:58,400 Speaker 1: constantly making it cleaner, we're constantly watching now we're affecting 518 00:29:58,400 --> 00:29:59,040 Speaker 1: the environment. 519 00:30:00,080 --> 00:30:03,240 Speaker 3: Yeah, I love your thought process. We need more people 520 00:30:03,480 --> 00:30:07,320 Speaker 3: like that in office. You know, these types of discussions 521 00:30:07,360 --> 00:30:10,960 Speaker 3: where you have to have the intellectual stamina and not 522 00:30:11,240 --> 00:30:14,520 Speaker 3: just start calling names or saying, oh, you're a polluter. 523 00:30:14,960 --> 00:30:17,120 Speaker 3: You're just you know, you don't care, you don't care 524 00:30:17,160 --> 00:30:19,680 Speaker 3: about the environment it is. You know, in fact, we 525 00:30:19,800 --> 00:30:23,640 Speaker 3: are all humans, we're all living here. And yes, we 526 00:30:23,720 --> 00:30:26,960 Speaker 3: made mistakes maybe with like fracking early on there were 527 00:30:27,000 --> 00:30:30,800 Speaker 3: like a few instances and the companies now learn from that. 528 00:30:30,880 --> 00:30:33,440 Speaker 3: But hey, it's the same thing with social media, right, 529 00:30:33,840 --> 00:30:38,120 Speaker 3: and so just because many of those companies were on 530 00:30:38,280 --> 00:30:41,800 Speaker 3: the right, they were demonized. Have we really demonized social 531 00:30:41,840 --> 00:30:44,040 Speaker 3: media that much? I mean, look at when social media 532 00:30:44,400 --> 00:30:48,560 Speaker 3: came out and like all the stuff with anxiety, the 533 00:30:48,840 --> 00:30:53,200 Speaker 3: anxious generation. Right, this is part of the technology cycle 534 00:30:53,280 --> 00:30:56,120 Speaker 3: where when we come out with like new things, there 535 00:30:56,160 --> 00:31:01,240 Speaker 3: are unexpected consequences. But we allow Facebook to get better 536 00:31:01,400 --> 00:31:04,160 Speaker 3: and to make apologies. I don't know if they're doing 537 00:31:04,240 --> 00:31:07,160 Speaker 3: the best job on that. There needs to be maybe 538 00:31:07,440 --> 00:31:09,920 Speaker 3: you know, a little bit more filtering of some of 539 00:31:09,960 --> 00:31:14,480 Speaker 3: the social media stuff, especially with you know, young children, 540 00:31:15,400 --> 00:31:19,040 Speaker 3: so not to cause anxiety and depression. But why can't 541 00:31:19,040 --> 00:31:22,360 Speaker 3: we extend that to the oil and gas and coal energy. 542 00:31:22,400 --> 00:31:25,080 Speaker 3: Why is that like, oh, they made some mistakes and 543 00:31:25,160 --> 00:31:29,560 Speaker 3: so why are they paying the price for their ancestors 544 00:31:29,600 --> 00:31:32,239 Speaker 3: like back in twenty ten and twenty twelve. I mean, 545 00:31:32,280 --> 00:31:34,440 Speaker 3: I'm not from that industry, but it's so weird. 546 00:31:35,000 --> 00:31:37,720 Speaker 1: Yeah, you make such a great point, because we we 547 00:31:38,360 --> 00:31:40,400 Speaker 1: I think unless you've lived it, and I think this 548 00:31:40,520 --> 00:31:42,360 Speaker 1: is part of the problem, because you have a bunch 549 00:31:42,400 --> 00:31:45,280 Speaker 1: of the young activists are very young, straight out of 550 00:31:45,280 --> 00:31:47,880 Speaker 1: college and we're still in college. So they have not 551 00:31:48,400 --> 00:31:51,400 Speaker 1: worked in industry by any means, and some of them 552 00:31:51,640 --> 00:31:53,840 Speaker 1: will never work in industry. But unless you've been in 553 00:31:53,880 --> 00:31:57,680 Speaker 1: a factory and you've seen, Okay, we're constantly changing how 554 00:31:57,720 --> 00:31:59,800 Speaker 1: we do things. We have desk collectors, we have this 555 00:32:00,080 --> 00:32:04,280 Speaker 1: of these environmental masks. We're protecting people and we're protecting 556 00:32:04,320 --> 00:32:08,360 Speaker 1: the environment in ways that you can't see any place ELTs. 557 00:32:08,440 --> 00:32:12,040 Speaker 1: But the thing is that the manufacturing process doesn't stop 558 00:32:12,120 --> 00:32:14,680 Speaker 1: because you don't do it in Michigan doesn't mean that 559 00:32:14,720 --> 00:32:18,160 Speaker 1: it's not being manufactured. It's being manufactured overseas in a 560 00:32:18,240 --> 00:32:21,160 Speaker 1: much worse environment. When don't you prefer to see it 561 00:32:21,240 --> 00:32:23,560 Speaker 1: here where we know how to do it safely. And 562 00:32:23,560 --> 00:32:26,800 Speaker 1: that's something that is a re education, that is it is. 563 00:32:26,800 --> 00:32:27,320 Speaker 2: Hard to do. 564 00:32:27,400 --> 00:32:29,480 Speaker 1: But I think that the American people are seeing that 565 00:32:30,000 --> 00:32:32,520 Speaker 1: because of Donald Trump speaking in a different way. But 566 00:32:32,720 --> 00:32:35,400 Speaker 1: to go to your point at the beginning, unless you 567 00:32:35,440 --> 00:32:40,280 Speaker 1: can continue to have politicians who are not lifelong politicians 568 00:32:40,320 --> 00:32:42,360 Speaker 1: who have not been affected by the swamp and Donald 569 00:32:42,360 --> 00:32:44,680 Speaker 1: Trump is unique in the fact that he doesn't have 570 00:32:44,720 --> 00:32:47,320 Speaker 1: to fund raise. He can go out there and he 571 00:32:47,320 --> 00:32:49,920 Speaker 1: can use his own money, but he also has these 572 00:32:49,960 --> 00:32:54,360 Speaker 1: small dollar donations because people just believe in him. That's 573 00:32:54,400 --> 00:32:57,000 Speaker 1: a very unique situation. So we need to keep doing that. 574 00:32:57,280 --> 00:32:59,600 Speaker 3: To fix the problem. Yea, I think it really started 575 00:32:59,640 --> 00:33:03,400 Speaker 3: with Bill Clinton, who I did vote for, but I 576 00:33:03,400 --> 00:33:06,800 Speaker 3: didn't understand because I was a teenager that's when I 577 00:33:06,880 --> 00:33:09,080 Speaker 3: was first able to vote. And I do think it 578 00:33:09,120 --> 00:33:12,360 Speaker 3: was these deals with the you know that was made 579 00:33:12,440 --> 00:33:16,480 Speaker 3: at the World Economic Forum, and back then, the you know, 580 00:33:16,520 --> 00:33:21,040 Speaker 3: these traditional industries didn't have a good lobbyist, you see, 581 00:33:21,080 --> 00:33:23,840 Speaker 3: like Mark Zuckerberg. I'm actually at mar A Lago quite 582 00:33:23,920 --> 00:33:26,840 Speaker 3: often and now in d C. I mean I saw 583 00:33:27,280 --> 00:33:31,160 Speaker 3: when I was doing the the my Indo Pacific Conference, 584 00:33:31,160 --> 00:33:34,920 Speaker 3: I actually saw him there, you know, walking around waiting 585 00:33:34,960 --> 00:33:38,240 Speaker 3: for Donald Trump. So they're very active, and so, you know, 586 00:33:38,400 --> 00:33:41,040 Speaker 3: I think a lot of the issues that and I'm 587 00:33:41,080 --> 00:33:44,760 Speaker 3: hypothesizing because I don't come from this world. I think Michigan, 588 00:33:44,960 --> 00:33:48,120 Speaker 3: a lot of the rust belt state was sold out 589 00:33:48,240 --> 00:33:53,200 Speaker 3: by Bill Clinton and then reinforced by Obama and Biden 590 00:33:53,560 --> 00:33:59,920 Speaker 3: and offshore to China, to other countries just as a deal, 591 00:34:00,520 --> 00:34:05,959 Speaker 3: you know, and they were supported heavily financially. You know, 592 00:34:06,040 --> 00:34:09,440 Speaker 3: they had their own deal and also Bush too, you know. 593 00:34:10,600 --> 00:34:12,879 Speaker 3: And like I say, when you go back selling out 594 00:34:12,960 --> 00:34:18,400 Speaker 3: of the Americans working class, you know, uh Main Street 595 00:34:18,440 --> 00:34:24,400 Speaker 3: America for uh the Chinese investment into Wall Street companies. 596 00:34:24,680 --> 00:34:27,400 Speaker 1: Let's take a quick commercial break. We'll continue next on 597 00:34:27,440 --> 00:34:33,720 Speaker 1: the Tutor Dixon podcast. A lot of this was the 598 00:34:33,840 --> 00:34:36,279 Speaker 1: lack of deep thinking about, Okay, if you do this, 599 00:34:36,600 --> 00:34:39,360 Speaker 1: what are the consequences of this, what are the ultimate 600 00:34:39,360 --> 00:34:41,640 Speaker 1: effects of that? And that is that you shut down 601 00:34:41,960 --> 00:34:44,040 Speaker 1: an entire section of the country. 602 00:34:44,239 --> 00:34:48,200 Speaker 2: That is the menu. And then we were the manufacturing giants. 603 00:34:47,640 --> 00:34:50,120 Speaker 3: But well, why aren't you doing that with Facebook? You 604 00:34:50,120 --> 00:34:54,239 Speaker 3: know they were caught red handed. You were caught red handed, okay, 605 00:34:54,560 --> 00:34:58,080 Speaker 3: with what you were doing with the teenage girls. And 606 00:34:58,280 --> 00:35:01,040 Speaker 3: that girl who worked at face books, she called you 607 00:35:01,080 --> 00:35:04,440 Speaker 3: out on sixteen minutes. Okay, then you were caught red handed. 608 00:35:04,840 --> 00:35:08,520 Speaker 2: Because we don't have money. Mental health issues make them money. 609 00:35:08,719 --> 00:35:11,840 Speaker 3: Yeah, we don't see. You know the US government offshoring 610 00:35:12,040 --> 00:35:13,440 Speaker 3: Facebook or Google? 611 00:35:13,640 --> 00:35:14,359 Speaker 1: Right right? 612 00:35:14,360 --> 00:35:18,640 Speaker 3: And so why are we offshoring American manufacturing because of 613 00:35:18,719 --> 00:35:21,319 Speaker 3: this and that? But now like we have better technology, 614 00:35:21,400 --> 00:35:22,880 Speaker 3: we have like the rubbers. 615 00:35:23,520 --> 00:35:26,399 Speaker 1: That's the seduction of it all, because if you have 616 00:35:26,680 --> 00:35:28,760 Speaker 1: if you have health care issues, if you have mental 617 00:35:28,800 --> 00:35:30,799 Speaker 1: health issues, you have health care issues, and then you 618 00:35:30,840 --> 00:35:33,520 Speaker 1: can sell. We need to have free health care for all, 619 00:35:33,560 --> 00:35:36,279 Speaker 1: health care for all that. Look at what's happening. These 620 00:35:36,360 --> 00:35:38,560 Speaker 1: kids are more depressed than they've ever been. We need 621 00:35:38,600 --> 00:35:41,279 Speaker 1: health care for all. That's our solution. It's not that 622 00:35:41,320 --> 00:35:43,640 Speaker 1: we're going to look at what's the causing the problem. 623 00:35:43,960 --> 00:35:45,200 Speaker 1: It's that we have to come up. 624 00:35:45,239 --> 00:35:46,600 Speaker 2: We have to add some I mean, it's just like 625 00:35:46,920 --> 00:35:47,520 Speaker 2: anything else. 626 00:35:47,560 --> 00:35:50,239 Speaker 1: It's like, oh, well this medication is causing you this, 627 00:35:50,320 --> 00:35:52,719 Speaker 1: let's add this medication on to fix it. That's how 628 00:35:52,760 --> 00:35:55,600 Speaker 1: the government is like, we've created this problem, let's add 629 00:35:55,640 --> 00:35:59,200 Speaker 1: another problem. Let's add another problem I've and nobody's stepping 630 00:35:59,200 --> 00:36:01,239 Speaker 1: back and saying, I mean, it's the same with the 631 00:36:01,280 --> 00:36:01,800 Speaker 1: old exporter. 632 00:36:02,400 --> 00:36:06,480 Speaker 3: What's the real problem. They get back to common sense 633 00:36:07,120 --> 00:36:11,640 Speaker 3: first principle, whether it's uh, like, how do we raise 634 00:36:12,040 --> 00:36:16,319 Speaker 3: our families in a safe way where they'll learn and 635 00:36:16,440 --> 00:36:20,840 Speaker 3: be a good Americans and with the principles of American 636 00:36:20,920 --> 00:36:25,759 Speaker 3: creativity and entrepreneurship and not raise a generation that's anxious 637 00:36:25,800 --> 00:36:29,799 Speaker 3: and we're rewarding them to steal, lie and do drugs. 638 00:36:30,320 --> 00:36:32,920 Speaker 3: You know, what are American values? We need to be 639 00:36:33,080 --> 00:36:35,640 Speaker 3: in alignment with that. And you know that's why I 640 00:36:35,680 --> 00:36:40,239 Speaker 3: became a Trump Republican because uh, and I you know, 641 00:36:40,280 --> 00:36:42,279 Speaker 3: and I haven't changed. People are like, oh, did you change? 642 00:36:42,280 --> 00:36:47,520 Speaker 3: Alison's like, no, I'm I'm exactly the same person I was. 643 00:36:47,719 --> 00:36:52,440 Speaker 3: But he's just now, uh, you know, he talks the 644 00:36:52,480 --> 00:36:55,200 Speaker 3: talk of Obama, he talks the talk of Clinton. 645 00:36:55,480 --> 00:36:59,640 Speaker 1: That's interesting. Actual he has that swagger where people are 646 00:37:00,200 --> 00:37:03,160 Speaker 1: kind of following what he's doing, but it's not it's 647 00:37:03,160 --> 00:37:05,919 Speaker 1: not just a swag or we're seeing results, and that's 648 00:37:06,520 --> 00:37:09,000 Speaker 1: that's where I say, gosh, we have four years to 649 00:37:09,080 --> 00:37:11,600 Speaker 1: show results and to really get people on board, and 650 00:37:12,120 --> 00:37:13,480 Speaker 1: people like you are helping us. 651 00:37:13,480 --> 00:37:14,600 Speaker 2: So thank you so much. 652 00:37:14,680 --> 00:37:17,400 Speaker 1: Thank you for coming on today, Alison. When where can 653 00:37:17,440 --> 00:37:19,560 Speaker 1: people follow you and find out what you're doing next? 654 00:37:20,360 --> 00:37:24,759 Speaker 3: Yeah? So I'm on Twitter, Instagram at aliwinn a, l 655 00:37:24,800 --> 00:37:28,280 Speaker 3: o I, h u I and h awesome. 656 00:37:28,440 --> 00:37:31,360 Speaker 1: It's been a pleasure talking to you to you today. 657 00:37:31,360 --> 00:37:32,560 Speaker 1: Thank you so much for coming. 658 00:37:32,400 --> 00:37:34,480 Speaker 3: On, Thanks for having me tutor. 659 00:37:34,840 --> 00:37:37,759 Speaker 1: Absolutely, and thank you all for joining us on the podcast. 660 00:37:37,760 --> 00:37:39,919 Speaker 1: To make sure you go to Tutor Dixon podcast dot 661 00:37:39,960 --> 00:37:43,239 Speaker 1: com or the iHeartRadio app, Apple Podcasts or wherever you 662 00:37:43,280 --> 00:37:45,600 Speaker 1: get your podcasts, or you can watch the video on 663 00:37:45,719 --> 00:37:48,640 Speaker 1: Rumble or YouTube at Tutor Dixon and join us next time. 664 00:37:48,840 --> 00:37:49,600 Speaker 2: Have a blessed day.