1 00:00:00,080 --> 00:00:10,200 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Welcome to the Bloomberg 2 00:00:10,280 --> 00:00:15,960 Speaker 1: This Weekend podcast with David Gura, Christina Raffini, and Lisa Matteo. 3 00:00:17,720 --> 00:00:20,600 Speaker 2: Thanks for joining us for today's selection of conversations from 4 00:00:20,640 --> 00:00:21,000 Speaker 2: the show. 5 00:00:21,200 --> 00:00:23,479 Speaker 3: You can listen to our favorite discussions right here on 6 00:00:23,520 --> 00:00:25,800 Speaker 3: the podcast, and also make sure to join us live 7 00:00:25,960 --> 00:00:28,960 Speaker 3: every Saturday and Sunday morning starting at seven am Easter. 8 00:00:29,200 --> 00:00:32,800 Speaker 4: We're on Bloomberg Television, Radio and the Bloomberg Business App, 9 00:00:33,080 --> 00:00:37,640 Speaker 4: bringing you unique takes and in depth interviews on news, politics, 10 00:00:37,680 --> 00:00:41,000 Speaker 4: lifestyle and culture. 11 00:00:41,680 --> 00:00:43,640 Speaker 3: Now for our exclusive sit down interview with the heads 12 00:00:43,640 --> 00:00:47,840 Speaker 3: of the National Governors Association. Two Republicans, two Democrats, two 13 00:00:47,880 --> 00:00:50,040 Speaker 3: ten gallon hats between the four of them, joining Bloomberg 14 00:00:50,080 --> 00:00:52,920 Speaker 3: this weekend on Saturday to announce a bipartisan task force 15 00:00:53,120 --> 00:00:54,840 Speaker 3: designed to tackle immigration reform. 16 00:00:54,880 --> 00:00:56,080 Speaker 2: I will say they did share the hats at our 17 00:00:56,120 --> 00:00:59,520 Speaker 2: previous clip. Governor Spencer Cox of you Tap, Wesmore of Maryland, 18 00:00:59,680 --> 00:01:02,720 Speaker 2: Kevin did of Oklahoma, and Matt Meyer of Delaware. 19 00:01:02,440 --> 00:01:03,000 Speaker 5: Take a listen. 20 00:01:03,880 --> 00:01:07,680 Speaker 6: We get elected. We always say that the governors really 21 00:01:08,000 --> 00:01:13,560 Speaker 6: can't be that partisan, because potholes aren't partisan. We actually 22 00:01:13,560 --> 00:01:16,280 Speaker 6: get judged by what we accomplish. We get held accountable 23 00:01:16,319 --> 00:01:20,559 Speaker 6: for that. So unlike Congress, we have to do those things. 24 00:01:20,600 --> 00:01:23,720 Speaker 6: And there's this cool thing we're celebrating America to fifty. 25 00:01:23,720 --> 00:01:25,119 Speaker 7: But the way our country. 26 00:01:24,840 --> 00:01:27,959 Speaker 6: Was set up, most of the power was left to 27 00:01:28,000 --> 00:01:30,600 Speaker 6: the states, not to the federal government. That's certainly changed 28 00:01:30,600 --> 00:01:32,920 Speaker 6: over the years. Unfortunately, we think that that's one of 29 00:01:32,959 --> 00:01:37,200 Speaker 6: the problems. But here's I think why this really matters 30 00:01:37,200 --> 00:01:39,720 Speaker 6: and should matter to all Americans is that we are 31 00:01:39,720 --> 00:01:43,520 Speaker 6: the laboratories of democracy. So if a blue state comes 32 00:01:43,600 --> 00:01:45,760 Speaker 6: up with a new policy that solves a problem in 33 00:01:45,800 --> 00:01:47,680 Speaker 6: their state, I'm going to steal that. 34 00:01:48,480 --> 00:01:50,400 Speaker 7: I want the best for my people. It goes the 35 00:01:50,440 --> 00:01:51,000 Speaker 7: other way around. 36 00:01:51,040 --> 00:01:54,880 Speaker 6: We were just talking about Mississippi today and they're reading scores, 37 00:01:54,920 --> 00:01:56,040 Speaker 6: the third grade reading scores. 38 00:01:56,080 --> 00:01:57,080 Speaker 7: They went from forty. 39 00:01:56,880 --> 00:01:59,560 Speaker 6: Nine to top ten, and all of us looked around 40 00:01:59,600 --> 00:02:03,360 Speaker 6: and said, hey, yeah, what is Mississippi doing. We should 41 00:02:03,360 --> 00:02:05,360 Speaker 6: copy that. And so almost all of us, I think, 42 00:02:05,400 --> 00:02:08,520 Speaker 6: have adopted some portion of Mississippi's policies around the science 43 00:02:08,560 --> 00:02:12,880 Speaker 6: of reading. That's why governors and mayors are I think 44 00:02:12,919 --> 00:02:13,600 Speaker 6: more popular. 45 00:02:14,320 --> 00:02:16,840 Speaker 7: There's a little more trust. Although we're all struggling with 46 00:02:16,840 --> 00:02:17,480 Speaker 7: that right now. 47 00:02:17,960 --> 00:02:20,280 Speaker 6: But we're lucky to have these events where we can 48 00:02:20,320 --> 00:02:21,560 Speaker 6: get together and learn from each other. 49 00:02:22,000 --> 00:02:23,640 Speaker 8: I can tell you I took it a step further 50 00:02:23,960 --> 00:02:26,640 Speaker 8: where we saw what was happening in Mississippi. We didn't 51 00:02:26,680 --> 00:02:30,320 Speaker 8: just copy the model. We actually told our superintendent who's 52 00:02:30,320 --> 00:02:32,359 Speaker 8: now the superintendent of the state of Maryland. So it's 53 00:02:32,360 --> 00:02:33,640 Speaker 8: now becoming the Maryland model. 54 00:02:34,440 --> 00:02:36,120 Speaker 5: I don't know if I want to encourage that. 55 00:02:39,560 --> 00:02:42,480 Speaker 2: No poaching people, guys, everybody playing nice in the sandbox 56 00:02:43,520 --> 00:02:46,679 Speaker 2: governors did when you talk to constituents, what is the 57 00:02:46,800 --> 00:02:49,320 Speaker 2: number one issue, number one or two issues that they 58 00:02:49,320 --> 00:02:51,760 Speaker 2: talked to you about? And have you found when you 59 00:02:51,760 --> 00:02:53,520 Speaker 2: go to the NNGA, when you talk to your colleagues 60 00:02:53,560 --> 00:02:56,080 Speaker 2: that those are common pretty much about across all the 61 00:02:56,120 --> 00:02:56,920 Speaker 2: states right now? 62 00:02:59,320 --> 00:03:02,160 Speaker 9: Yeah, I mean I tell people all the time and 63 00:03:02,320 --> 00:03:04,440 Speaker 9: every year of my I've been governor now for eight 64 00:03:04,520 --> 00:03:05,919 Speaker 9: years and it hasn't changed. 65 00:03:05,960 --> 00:03:08,560 Speaker 7: I mean, I believe that whether you live in rural. 66 00:03:08,400 --> 00:03:11,919 Speaker 9: Oklahoma or urban Oklahoma, you want the same thing, whether 67 00:03:11,919 --> 00:03:15,160 Speaker 9: you're Republican or Democrat, you really want the best education 68 00:03:15,240 --> 00:03:17,160 Speaker 9: for your kids, the best opportunity. 69 00:03:17,280 --> 00:03:18,320 Speaker 7: I want to make sure I put my. 70 00:03:18,400 --> 00:03:20,800 Speaker 9: Kids in the best situation possible so. 71 00:03:20,720 --> 00:03:22,240 Speaker 7: They can chase their American dream. 72 00:03:22,480 --> 00:03:25,080 Speaker 9: I want the best access to healthcare. I want the 73 00:03:25,120 --> 00:03:28,959 Speaker 9: best roads and bridges and infrastructure and utility cost. And 74 00:03:29,000 --> 00:03:31,239 Speaker 9: then I want the best economy. I want wages to growth. 75 00:03:31,240 --> 00:03:34,280 Speaker 9: I want opportunities for upward mobility. And so those four 76 00:03:34,360 --> 00:03:38,160 Speaker 9: things are non political, and I always tell Oklahomas, Hey, 77 00:03:38,680 --> 00:03:42,640 Speaker 9: let DC play politics. We're all Oklahomas. Let's make Oklahoma 78 00:03:42,720 --> 00:03:44,480 Speaker 9: top ten. And so I focus on those things. And 79 00:03:44,480 --> 00:03:46,280 Speaker 9: I don't think it's any different when I meet with 80 00:03:46,760 --> 00:03:49,880 Speaker 9: my colleagues around the country. They're dealing with the exact 81 00:03:49,920 --> 00:03:53,360 Speaker 9: same things in their state. So it's those four things 82 00:03:53,400 --> 00:03:54,160 Speaker 9: I always focus on. 83 00:03:54,280 --> 00:03:58,280 Speaker 10: People are starving for government that delivers, for people that delivers. 84 00:03:58,560 --> 00:04:02,360 Speaker 10: There's so much nonsense out there, not just in politics 85 00:04:02,360 --> 00:04:04,920 Speaker 10: and government, but everywhere, and I think people are just 86 00:04:05,000 --> 00:04:07,800 Speaker 10: looking for people they elect to roll up their sleeves 87 00:04:07,880 --> 00:04:10,680 Speaker 10: and get actual, real work done to help educate their kids, 88 00:04:11,280 --> 00:04:14,600 Speaker 10: deal with childcare, the costs that I have three kids, 89 00:04:14,760 --> 00:04:17,560 Speaker 10: one more on the way, and the costs are skyrocketing. 90 00:04:17,600 --> 00:04:20,040 Speaker 10: Making sure when you go and get gas it's affordable, 91 00:04:20,240 --> 00:04:23,039 Speaker 10: and so that's really what we're spending time on all day. 92 00:04:23,080 --> 00:04:25,160 Speaker 10: You look at the national news and things people are 93 00:04:25,160 --> 00:04:28,920 Speaker 10: fighting about. Most of what we do our kitchen table issues, 94 00:04:29,120 --> 00:04:30,760 Speaker 10: just trying to make life a little bit easier for 95 00:04:30,800 --> 00:04:32,560 Speaker 10: the people that live in our respective states. 96 00:04:32,839 --> 00:04:35,680 Speaker 6: I would just add the price of housing is a 97 00:04:35,680 --> 00:04:36,360 Speaker 6: big piece of that. 98 00:04:36,360 --> 00:04:38,400 Speaker 7: That's when we hear you do energy too. 99 00:04:38,480 --> 00:04:41,359 Speaker 6: Yeah, all of the consumer costs, that's huge for all 100 00:04:41,400 --> 00:04:42,000 Speaker 6: of us. 101 00:04:41,839 --> 00:04:42,480 Speaker 5: That's funny. 102 00:04:42,480 --> 00:04:44,080 Speaker 2: I was actually just going to say, so obviously, I'm 103 00:04:44,120 --> 00:04:46,120 Speaker 2: here in New York. I moved here recently, and I 104 00:04:46,120 --> 00:04:48,000 Speaker 2: talked about on the show a lot. Everything here is 105 00:04:48,040 --> 00:04:50,520 Speaker 2: insane expensive. But I grew up in Colorado. And I 106 00:04:50,600 --> 00:04:52,479 Speaker 2: was talking to a friend who was a very different 107 00:04:52,480 --> 00:04:54,440 Speaker 2: life than me earlier this week, and she was saying 108 00:04:54,440 --> 00:04:56,400 Speaker 2: the same things I was dealing with. She was like, 109 00:04:56,720 --> 00:04:58,800 Speaker 2: we've gotten to a place in our lives we always 110 00:04:58,839 --> 00:05:00,560 Speaker 2: wanted to be. My husband and I are making the 111 00:05:00,600 --> 00:05:02,560 Speaker 2: money we always wanted to and we feel like we 112 00:05:02,640 --> 00:05:06,279 Speaker 2: can't afford even the basic things. So governor more, I 113 00:05:06,279 --> 00:05:08,320 Speaker 2: want to start with you, but what is your plan 114 00:05:08,440 --> 00:05:11,000 Speaker 2: to tackle affordability? How are you going to tackle this? 115 00:05:11,080 --> 00:05:12,479 Speaker 2: And then I brought it out to the group. What 116 00:05:12,520 --> 00:05:14,279 Speaker 2: are you guys doing to bring these prices down. 117 00:05:16,279 --> 00:05:18,560 Speaker 8: Well, I think one thing that all the governors recognize 118 00:05:18,680 --> 00:05:21,080 Speaker 8: is that, you know, we wish we could control the 119 00:05:21,120 --> 00:05:24,760 Speaker 8: price of gas, you know that, but that's not something 120 00:05:24,760 --> 00:05:26,239 Speaker 8: that governors control. 121 00:05:26,320 --> 00:05:26,520 Speaker 2: You know. 122 00:05:26,560 --> 00:05:29,400 Speaker 8: We know we are seeing how nationwide the price of 123 00:05:29,800 --> 00:05:33,040 Speaker 8: gas has just skyrocket over the over the past twelve weeks. 124 00:05:33,640 --> 00:05:36,040 Speaker 8: We see how, you know, we wish we could control. 125 00:05:35,839 --> 00:05:37,320 Speaker 7: The price of groceries. 126 00:05:37,680 --> 00:05:40,320 Speaker 8: Unfortunately, we're now seeing how inflation is the highest that 127 00:05:40,360 --> 00:05:42,640 Speaker 8: it's been in three years, and so you're watching the 128 00:05:42,680 --> 00:05:44,880 Speaker 8: price of groceries continue to go up. And so there 129 00:05:44,880 --> 00:05:47,960 Speaker 8: are certain factors that that as governors, we don't control 130 00:05:48,000 --> 00:05:50,400 Speaker 8: the fact that things continue to rise, but we can 131 00:05:50,440 --> 00:05:51,880 Speaker 8: control the things we can control. 132 00:05:52,120 --> 00:05:53,360 Speaker 7: So, for example, when. 133 00:05:53,200 --> 00:05:56,200 Speaker 8: We're talking about best practices that we've seen and that 134 00:05:56,240 --> 00:05:59,000 Speaker 8: as other states we've also brought on board. You know, 135 00:05:59,120 --> 00:06:01,920 Speaker 8: we actually in Maryland we pass legislation that deals with 136 00:06:01,960 --> 00:06:05,000 Speaker 8: the issue of price manipulation at supermarkets, where you know, 137 00:06:05,080 --> 00:06:08,520 Speaker 8: supermarkets and big supermarket chains cannot use your data against 138 00:06:08,520 --> 00:06:11,200 Speaker 8: you when you walk into a supermarket and increase the 139 00:06:11,240 --> 00:06:14,000 Speaker 8: prices because they know that you will pay for the 140 00:06:14,080 --> 00:06:16,720 Speaker 8: increased prices. So we are the first state to actually 141 00:06:16,760 --> 00:06:19,440 Speaker 8: ban price manipulation that when it came to things like 142 00:06:19,520 --> 00:06:22,560 Speaker 8: rising energy prices that we're all wrestling with, you know, 143 00:06:22,640 --> 00:06:24,840 Speaker 8: in our state, and I know other states have done 144 00:06:24,839 --> 00:06:27,720 Speaker 8: the same. We've now put one hundreds of dollars back 145 00:06:27,760 --> 00:06:30,640 Speaker 8: in the pockets of our people in Maryland. You know, 146 00:06:30,640 --> 00:06:33,159 Speaker 8: it's three hundred million dollars that we've now put back 147 00:06:33,360 --> 00:06:35,480 Speaker 8: to the people of Maryland to deal with these rising 148 00:06:35,640 --> 00:06:39,360 Speaker 8: energy prices. And so we're making sure we can control 149 00:06:39,680 --> 00:06:42,880 Speaker 8: the things we can control, making historic investments in childcare, 150 00:06:43,160 --> 00:06:45,400 Speaker 8: as Matt was talking about, because that is one of 151 00:06:45,440 --> 00:06:47,840 Speaker 8: the largest costs that families are dealing with, whether they're 152 00:06:47,839 --> 00:06:50,159 Speaker 8: now having to choose between are my kids going to 153 00:06:50,200 --> 00:06:50,599 Speaker 8: be okay? 154 00:06:50,800 --> 00:06:52,880 Speaker 7: Or can I go back into the workforce. 155 00:06:53,120 --> 00:06:55,960 Speaker 8: And so we're making sure as governors that while we 156 00:06:56,040 --> 00:06:58,640 Speaker 8: cannot control a lot of the dynamics that are existing 157 00:06:59,000 --> 00:07:01,640 Speaker 8: within our states, the things that we can control to 158 00:07:01,680 --> 00:07:03,960 Speaker 8: make life a little bit easier for the people of 159 00:07:03,960 --> 00:07:05,720 Speaker 8: our states, we can and we will. 160 00:07:07,240 --> 00:07:09,240 Speaker 2: Does anybody else want to get to anything any other 161 00:07:09,279 --> 00:07:11,960 Speaker 2: specific policies that y'all want to highlight that you are 162 00:07:11,960 --> 00:07:13,880 Speaker 2: trying to do, either on housing or I know, energy 163 00:07:13,920 --> 00:07:16,200 Speaker 2: is a big concern, especially with data centers going in 164 00:07:16,400 --> 00:07:19,640 Speaker 2: a bunch of places, food costs, childcare, of any of 165 00:07:19,680 --> 00:07:21,920 Speaker 2: the policies that come to mind that you're trying to 166 00:07:22,320 --> 00:07:23,200 Speaker 2: enact in your states. 167 00:07:24,840 --> 00:07:27,440 Speaker 7: Well, you know, I think we all want to do 168 00:07:28,280 --> 00:07:29,920 Speaker 7: all right, keep. 169 00:07:29,800 --> 00:07:31,800 Speaker 5: Going down the road. But you're grown up, so you 170 00:07:31,840 --> 00:07:33,080 Speaker 5: can figure out. All right, thanks guys. 171 00:07:33,080 --> 00:07:37,400 Speaker 9: Good Well, I would just say on housing, we're all 172 00:07:37,440 --> 00:07:40,480 Speaker 9: dealing with affordability. We want you know, home ownership is 173 00:07:40,520 --> 00:07:43,240 Speaker 9: so important. My whole career has been in the mortgage 174 00:07:43,240 --> 00:07:47,360 Speaker 9: business and banking and promoting home ownership and strengthening families 175 00:07:47,360 --> 00:07:50,080 Speaker 9: and how important that is to own homes. And so 176 00:07:50,360 --> 00:07:52,520 Speaker 9: when you see that cost rising and you see people 177 00:07:52,560 --> 00:07:55,840 Speaker 9: delaying housing, perching the first house so they're in their thirties, 178 00:07:55,880 --> 00:07:59,280 Speaker 9: Now what is that? Well, if you believe in economics, 179 00:07:59,280 --> 00:08:01,920 Speaker 9: I believe it's a it's a supply problem, right, So 180 00:08:01,960 --> 00:08:04,120 Speaker 9: how do we get more houses built? Some of that 181 00:08:04,240 --> 00:08:07,720 Speaker 9: is zoning problems. We're not allowing more developers. To me, 182 00:08:07,880 --> 00:08:10,880 Speaker 9: it's always over regulation, right, So we passed a built 183 00:08:10,880 --> 00:08:15,520 Speaker 9: to encourage zero interest loans to developers to develop more houses. 184 00:08:15,560 --> 00:08:19,000 Speaker 9: And then for that they had to produce affordable houses 185 00:08:19,000 --> 00:08:22,760 Speaker 9: for the working families. The Build Act that we did 186 00:08:23,000 --> 00:08:29,840 Speaker 9: allows developers now to burden the cost of utilities, infrastructure 187 00:08:29,880 --> 00:08:32,520 Speaker 9: as far as water sewage instead of back on to 188 00:08:33,040 --> 00:08:35,880 Speaker 9: the municipality. So we're doing everything we can to encourage 189 00:08:35,920 --> 00:08:39,720 Speaker 9: more supply coming in. It's already we're already very affordable 190 00:08:39,720 --> 00:08:42,600 Speaker 9: in Oklahoma, and we're getting tremendous economic development. 191 00:08:42,600 --> 00:08:43,600 Speaker 7: But we want we want more. 192 00:08:43,679 --> 00:08:47,360 Speaker 9: We want to unleash the UH, the innovation of companies 193 00:08:47,400 --> 00:08:49,319 Speaker 9: to go meet the demands of Americans. And I think 194 00:08:49,360 --> 00:08:51,920 Speaker 9: that's the best policy, just a free market approach. 195 00:08:52,600 --> 00:08:53,200 Speaker 5: Governor Meyer. 196 00:08:54,040 --> 00:08:55,800 Speaker 2: One of the big things that we were just talking 197 00:08:55,840 --> 00:08:58,440 Speaker 2: about with the big costs is energy, and energy costs 198 00:08:58,480 --> 00:09:00,880 Speaker 2: are really going up, and we're seeing that coincide, of course, 199 00:09:00,920 --> 00:09:03,679 Speaker 2: with these big data centers that are going in all 200 00:09:03,720 --> 00:09:04,680 Speaker 2: across the country. 201 00:09:04,960 --> 00:09:06,960 Speaker 5: I'm wondering if you are hearing from your. 202 00:09:06,880 --> 00:09:09,480 Speaker 2: Constituents that they are concerned about AI, they are concerned 203 00:09:09,520 --> 00:09:11,800 Speaker 2: about the energy draw of these data centers, and what 204 00:09:11,840 --> 00:09:13,160 Speaker 2: you're doing about that in your state. 205 00:09:15,280 --> 00:09:16,199 Speaker 7: I am hearing a lot. 206 00:09:16,240 --> 00:09:17,600 Speaker 10: I think all of us are hearing a lot about 207 00:09:17,640 --> 00:09:21,520 Speaker 10: data centers and the concerns about AI. They run the 208 00:09:21,559 --> 00:09:27,360 Speaker 10: gamut from security concerns, privacy concerns, environmental concerns, and wealth 209 00:09:27,520 --> 00:09:30,160 Speaker 10: inequality concerns, and. 210 00:09:30,080 --> 00:09:32,319 Speaker 7: I think each of us have a different approach. 211 00:09:33,160 --> 00:09:36,200 Speaker 10: We're looking to attract employers in Delaware, where in my 212 00:09:36,240 --> 00:09:39,120 Speaker 10: first eighteen months in office, we've been very successful doing that. 213 00:09:39,320 --> 00:09:42,280 Speaker 10: But I've also been very clear that if you're going 214 00:09:42,320 --> 00:09:45,400 Speaker 10: to negatively impact our environment, if you're going to increase 215 00:09:45,559 --> 00:09:49,400 Speaker 10: rate payers energy bills by a single penny, then we're 216 00:09:49,400 --> 00:09:51,080 Speaker 10: not going to have you here. So we're putting in 217 00:09:51,120 --> 00:09:54,000 Speaker 10: place rules, we're about to finalize them, about to sign 218 00:09:54,080 --> 00:09:57,520 Speaker 10: some legislation that does just that, that says, hey, if 219 00:09:57,520 --> 00:10:00,200 Speaker 10: you want a data center or anything like that in 220 00:10:00,240 --> 00:10:02,120 Speaker 10: our community, you have to come with. 221 00:10:02,200 --> 00:10:04,160 Speaker 7: Benefit for the community. 222 00:10:04,240 --> 00:10:05,760 Speaker 10: I think a number of us that are doing behind 223 00:10:05,760 --> 00:10:08,280 Speaker 10: the meter policies where kind of bring your own energy. 224 00:10:08,280 --> 00:10:10,839 Speaker 10: If you bring your own energy and you're not drawing 225 00:10:10,840 --> 00:10:14,040 Speaker 10: from the grid, it's much easier to get a pathway. 226 00:10:14,160 --> 00:10:16,920 Speaker 10: I think we also understand that data centers and AI 227 00:10:17,520 --> 00:10:21,520 Speaker 10: at some level is a national economic and security imperative. 228 00:10:21,720 --> 00:10:23,720 Speaker 7: We cannot let China win on this one. 229 00:10:23,800 --> 00:10:26,760 Speaker 10: We have to make sure that our respective states aren't 230 00:10:26,800 --> 00:10:29,679 Speaker 10: blocking each other and blocking things so that we as 231 00:10:29,679 --> 00:10:31,160 Speaker 10: a country cannot move forward. 232 00:10:31,480 --> 00:10:33,840 Speaker 2: All right, gentlemen, we're running a little short on time. 233 00:10:34,200 --> 00:10:36,520 Speaker 2: I really appreciate you taking time. Before I let you go, 234 00:10:36,960 --> 00:10:39,199 Speaker 2: I do want to play a game. So if everybody 235 00:10:39,240 --> 00:10:41,120 Speaker 2: could please raise your hand like this. Wait, I have 236 00:10:41,160 --> 00:10:42,040 Speaker 2: to find my camera here. 237 00:10:42,200 --> 00:10:43,920 Speaker 5: Put your hand up. We're going to do. Put a 238 00:10:43,920 --> 00:10:44,520 Speaker 5: finger down. 239 00:10:44,600 --> 00:10:46,520 Speaker 2: If I'm sure you have children or have been on 240 00:10:46,559 --> 00:10:48,600 Speaker 2: the internet and you understand how this works, all right, 241 00:10:48,640 --> 00:10:51,360 Speaker 2: you ready, Please put a finger down. If you are 242 00:10:51,400 --> 00:10:53,719 Speaker 2: concerned about affordability in your state. 243 00:10:54,559 --> 00:10:55,960 Speaker 7: Put a figure down. If you're concerned. 244 00:10:56,000 --> 00:10:58,520 Speaker 2: Yeah, if you're concerned about affordability in a state, put 245 00:10:58,559 --> 00:10:59,320 Speaker 2: one of your fingers down. 246 00:10:59,320 --> 00:11:00,360 Speaker 5: Please put a finger down. 247 00:11:00,400 --> 00:11:02,680 Speaker 2: If you have released a book in the past year, 248 00:11:02,880 --> 00:11:05,120 Speaker 2: or planning to release a book in the coming year. 249 00:11:11,280 --> 00:11:13,520 Speaker 5: All right, that's two out of the floor. Put a 250 00:11:13,520 --> 00:11:14,000 Speaker 5: finger down. 251 00:11:14,000 --> 00:11:16,120 Speaker 2: If you're going to Iowa this year or in the 252 00:11:16,160 --> 00:11:17,120 Speaker 2: next cycle. 253 00:11:18,320 --> 00:11:20,280 Speaker 7: Iowa, old meyer. 254 00:11:22,160 --> 00:11:25,480 Speaker 2: Yeah, the gentleman from Delaware has put a finger down. 255 00:11:26,200 --> 00:11:28,240 Speaker 2: And finally, please put a finger down. 256 00:11:28,640 --> 00:11:30,040 Speaker 7: We're just going to New Hampshire. 257 00:11:30,559 --> 00:11:37,079 Speaker 2: New Hampshire also counts. Okay, dream my final question of 258 00:11:37,120 --> 00:11:39,800 Speaker 2: the day, Please put a finger down. Gentlemen, if you 259 00:11:39,840 --> 00:11:44,200 Speaker 2: are running for president in twenty twenty eight. 260 00:11:44,040 --> 00:11:46,880 Speaker 5: I'm looking. I'm looking all right. 261 00:11:46,960 --> 00:11:51,240 Speaker 2: No one committed, no one committed. Thank you for being 262 00:11:51,240 --> 00:12:00,640 Speaker 2: good sports. I appreciate it. Thank you again with the task. 263 00:12:00,679 --> 00:12:03,560 Speaker 8: I have to say, though, I'm the only one of 264 00:12:03,600 --> 00:12:07,400 Speaker 8: this group who actually has a reelection in less than 265 00:12:07,440 --> 00:12:10,240 Speaker 8: one hundred days, So I'm sweating a whole lot more 266 00:12:10,280 --> 00:12:11,960 Speaker 8: than than my friends are here. 267 00:12:12,040 --> 00:12:12,400 Speaker 5: That's all right. 268 00:12:12,400 --> 00:12:15,079 Speaker 2: If it's a little hot, friends can let you borrow 269 00:12:15,120 --> 00:12:15,559 Speaker 2: a hat. 270 00:12:16,040 --> 00:12:17,440 Speaker 5: Gentlemen, Thank you so much. 271 00:12:17,800 --> 00:12:19,800 Speaker 2: I have a great time with the stockyards. We really 272 00:12:19,800 --> 00:12:21,200 Speaker 2: appreciate you joining us today. 273 00:12:23,559 --> 00:12:26,560 Speaker 3: Stay with us for more on Bloomberg this weekend right 274 00:12:26,559 --> 00:12:41,840 Speaker 3: after this. As artificial intelligence becomes ingrained in everyday life, 275 00:12:42,120 --> 00:12:46,720 Speaker 3: disagreements over the technology are increasingly becoming disagreements over values and. 276 00:12:46,760 --> 00:12:50,199 Speaker 2: The latest Bloomberg Forecast newsletter, Bloomberg News contributor Josie Cox 277 00:12:50,240 --> 00:12:55,160 Speaker 2: explores how AI adoption is dividing friends, families, and coworkers, writing, 278 00:12:55,200 --> 00:12:59,079 Speaker 2: researchers have only just begun to study AI social consequences, 279 00:12:59,080 --> 00:13:01,839 Speaker 2: and there's little impair work examining whether attitudes or the 280 00:13:01,880 --> 00:13:04,839 Speaker 2: technology are becoming part of people's identities. 281 00:13:05,320 --> 00:13:06,920 Speaker 5: I have opinions about that, but I will leave them 282 00:13:06,960 --> 00:13:07,520 Speaker 5: to the expert. 283 00:13:07,960 --> 00:13:10,640 Speaker 2: But interviews with the ai skeptics suggest that for some people, 284 00:13:10,679 --> 00:13:12,880 Speaker 2: AIUS has become a proxy for values. 285 00:13:13,040 --> 00:13:14,000 Speaker 11: Josie Cox joins us. 286 00:13:14,000 --> 00:13:15,400 Speaker 3: Now she sells with the author, I should save the 287 00:13:15,400 --> 00:13:18,360 Speaker 3: book Women, Money Power, The Rise and Fall of Economic Equality. 288 00:13:18,400 --> 00:13:22,880 Speaker 3: Great to have you with us. Let's start with this disagreement. 289 00:13:22,960 --> 00:13:25,000 Speaker 3: We can maybe not to how popular this has become 290 00:13:25,000 --> 00:13:26,400 Speaker 3: and how we're all kind of fumbling through. And I 291 00:13:26,400 --> 00:13:29,000 Speaker 3: think we can acknowledge that what did you find as 292 00:13:29,040 --> 00:13:31,240 Speaker 3: you dug into this in terms of what the personal 293 00:13:31,320 --> 00:13:33,960 Speaker 3: or interpersonal ramifications of this are thus far. 294 00:13:34,320 --> 00:13:36,640 Speaker 12: Yeah, it's so interesting. I mean everyone is familiar, of course, 295 00:13:36,640 --> 00:13:39,400 Speaker 12: with the headlines of just the meteoric rise of ai 296 00:13:39,640 --> 00:13:42,280 Speaker 12: It's doing everything for us. It's in our work lives, 297 00:13:42,280 --> 00:13:46,440 Speaker 12: our personal lives, in our bedrooms, it's everywhere. But what 298 00:13:46,520 --> 00:13:49,280 Speaker 12: I have generally found really interesting is the ways in 299 00:13:49,320 --> 00:13:53,360 Speaker 12: which it's exacerbating divides. Initially I was reporting on the 300 00:13:53,920 --> 00:13:57,840 Speaker 12: gender gap that it was potentially exacerbating men more apt 301 00:13:57,920 --> 00:13:59,720 Speaker 12: to use it. They are more apt to use it. 302 00:14:00,120 --> 00:14:02,520 Speaker 12: Bloomberg a couple of years ago really kind of the 303 00:14:02,640 --> 00:14:05,959 Speaker 12: in the sort of beginnings of AI dominance, showing that 304 00:14:06,000 --> 00:14:09,040 Speaker 12: there was actually quite a stark divide between used rates 305 00:14:09,040 --> 00:14:11,520 Speaker 12: among women and use rates among men. The gap has 306 00:14:11,520 --> 00:14:13,960 Speaker 12: closed a little bit, but that really sort of planted 307 00:14:13,960 --> 00:14:19,000 Speaker 12: the seed of interest, and since then I've been interested in, 308 00:14:19,360 --> 00:14:22,600 Speaker 12: you know, ways in which AI is not only uniting 309 00:14:22,680 --> 00:14:26,800 Speaker 12: us but also dividing us. And so this story really 310 00:14:26,840 --> 00:14:29,440 Speaker 12: came from sort of anecdotal evidence and conversations that I 311 00:14:29,480 --> 00:14:32,280 Speaker 12: was happening with people in my life who were sort 312 00:14:32,280 --> 00:14:35,040 Speaker 12: of vehemently anti AI, and I just thought it was 313 00:14:35,040 --> 00:14:38,040 Speaker 12: really interesting because a lot of people have different reasons 314 00:14:38,080 --> 00:14:40,200 Speaker 12: for being anti AI, for being sort of AI refused 315 00:14:40,200 --> 00:14:42,120 Speaker 12: and ex as I like to call them, you know, 316 00:14:42,160 --> 00:14:44,960 Speaker 12: be that the environment or ethical concerns, or in the 317 00:14:44,960 --> 00:14:47,440 Speaker 12: creative industries, a lot of people are concerned about copyright 318 00:14:47,480 --> 00:14:51,520 Speaker 12: things like that, but ultimately they all sort of tend 319 00:14:51,520 --> 00:14:54,640 Speaker 12: to kind of congregate around this idea of it being 320 00:14:54,680 --> 00:14:57,400 Speaker 12: a bit of an identity, right, and it's sort of 321 00:14:57,440 --> 00:14:59,960 Speaker 12: a you know, as I was reporting the story, I 322 00:15:00,000 --> 00:15:02,600 Speaker 12: realize that it was almost tribal. It was like us 323 00:15:02,680 --> 00:15:06,480 Speaker 12: versus them. Interesting, and I just think it's fascinating to 324 00:15:06,640 --> 00:15:10,080 Speaker 12: kind of consider as AI continues to dominate, continues to 325 00:15:10,200 --> 00:15:15,000 Speaker 12: infiltrate our lives, what that will ultimately mean for workplaces, families, relationships, 326 00:15:15,000 --> 00:15:15,360 Speaker 12: et cetera. 327 00:15:15,800 --> 00:15:18,400 Speaker 2: I am one of those people who gets very surprised 328 00:15:18,400 --> 00:15:20,600 Speaker 2: by the people in my life who have started relying 329 00:15:20,600 --> 00:15:23,360 Speaker 2: on AI so quickly, especially people my age and like, 330 00:15:23,440 --> 00:15:25,600 Speaker 2: as we've managed to make it our whole lives without 331 00:15:25,640 --> 00:15:27,600 Speaker 2: having your computer tell you how to get on the 332 00:15:27,600 --> 00:15:31,240 Speaker 2: subway or what to order it dinner. And the people 333 00:15:31,280 --> 00:15:35,160 Speaker 2: who adopt it, even people in creative industries, people who 334 00:15:35,200 --> 00:15:38,960 Speaker 2: it's threatening their livelihood, are adopting it in a way 335 00:15:39,000 --> 00:15:40,800 Speaker 2: that I think counteracts. 336 00:15:40,240 --> 00:15:41,400 Speaker 5: All the rest of their values. 337 00:15:41,440 --> 00:15:43,760 Speaker 2: But I personally get really upset. I was at dinner 338 00:15:43,760 --> 00:15:45,680 Speaker 2: the other day and we needed to google something, and 339 00:15:45,720 --> 00:15:47,640 Speaker 2: my friend picked up his phone and said, hey, chat, 340 00:15:48,280 --> 00:15:49,120 Speaker 2: just google it. 341 00:15:49,160 --> 00:15:51,160 Speaker 5: But like, what do I care? You know what I mean? 342 00:15:51,320 --> 00:15:52,640 Speaker 5: Why is it so emotionally interesting? 343 00:15:52,880 --> 00:15:54,680 Speaker 12: I think the reason one of the reasons that's so 344 00:15:54,960 --> 00:15:58,480 Speaker 12: emotional is because a lot of the uses of AI 345 00:15:58,840 --> 00:16:01,520 Speaker 12: that we're resorting to to do with communication, right, and 346 00:16:01,560 --> 00:16:05,160 Speaker 12: communication is something that is so personal. One of the academics, 347 00:16:05,160 --> 00:16:07,320 Speaker 12: so I spoke to who's a sociologist and who kind 348 00:16:07,320 --> 00:16:09,920 Speaker 12: of studies political divides, which is sort of a good 349 00:16:09,960 --> 00:16:13,040 Speaker 12: corollary for this. Said that, there's a lot of AI 350 00:16:13,160 --> 00:16:18,200 Speaker 12: skepticism around communications that should be personal, like wedding vowels, right, 351 00:16:18,600 --> 00:16:20,600 Speaker 12: like birthday greetings. 352 00:16:20,160 --> 00:16:22,400 Speaker 2: Or dating as people are like having their dating asks 353 00:16:22,480 --> 00:16:23,360 Speaker 2: just talk to each other. 354 00:16:23,760 --> 00:16:25,960 Speaker 5: The messages are completely AI generated. 355 00:16:25,600 --> 00:16:29,680 Speaker 12: Right, and communication is one of the most personal things 356 00:16:29,800 --> 00:16:31,960 Speaker 12: that we rely on and one of the most sort 357 00:16:31,960 --> 00:16:34,480 Speaker 12: of personal building blocks of our lives. So if we're 358 00:16:34,560 --> 00:16:36,640 Speaker 12: relying on a machine to do that, you know, what 359 00:16:36,960 --> 00:16:38,920 Speaker 12: does that tell us about the state of humanity? 360 00:16:39,000 --> 00:16:41,600 Speaker 3: Quite frankly, we stuck with this agentic setup that's happening. 361 00:16:41,960 --> 00:16:43,160 Speaker 5: Yeah, it's terrifying. 362 00:16:43,240 --> 00:16:47,120 Speaker 2: They've like programs, you know, prompt responses because you know, 363 00:16:48,040 --> 00:16:49,560 Speaker 2: but it is a quite exhausting process. 364 00:16:50,120 --> 00:16:52,600 Speaker 3: A lot on the subject of dating. You cite in 365 00:16:52,640 --> 00:16:55,880 Speaker 3: your piece here a survey by the dating app Hillys 366 00:16:55,920 --> 00:16:59,160 Speaker 3: that right, I think, so sixty four gen z fifty 367 00:16:59,200 --> 00:17:01,200 Speaker 3: six percent of millennial dators say they would not date 368 00:17:01,240 --> 00:17:05,119 Speaker 3: someone who relies on AI for everyday decisions. Here, we 369 00:17:05,160 --> 00:17:07,120 Speaker 3: do have some empirical evidence, at least there's a survey 370 00:17:07,160 --> 00:17:09,040 Speaker 3: that's taken place here. We have some data here, but 371 00:17:10,040 --> 00:17:11,760 Speaker 3: what does that tell you just about the way that 372 00:17:11,880 --> 00:17:13,760 Speaker 3: like lines are being drawn even preemptively? 373 00:17:13,840 --> 00:17:15,800 Speaker 12: I think, yeah, well, I think you know, to your point, 374 00:17:15,880 --> 00:17:18,000 Speaker 12: empirical data is scant. 375 00:17:17,760 --> 00:17:20,000 Speaker 3: Right now, even about you know, economic impact. 376 00:17:19,680 --> 00:17:22,439 Speaker 12: Or all that were kind of so I am completely 377 00:17:22,440 --> 00:17:24,320 Speaker 12: I had a cast around for this, right, but I 378 00:17:24,320 --> 00:17:26,640 Speaker 12: thought this was a really interesting data point. The other 379 00:17:26,640 --> 00:17:28,359 Speaker 12: thing I should say about it is that this is 380 00:17:28,560 --> 00:17:31,040 Speaker 12: cause people who are saying sure that they feel this 381 00:17:31,080 --> 00:17:33,639 Speaker 12: way about AI, right, whether they're actually acting on it 382 00:17:33,680 --> 00:17:35,399 Speaker 12: is another thing. This is the same as you know, 383 00:17:35,440 --> 00:17:39,639 Speaker 12: the perennial issue with political polling, right. But I think 384 00:17:39,760 --> 00:17:41,840 Speaker 12: what it does tell us is that there is a 385 00:17:41,840 --> 00:17:45,400 Speaker 12: bit of a backlash, right Obviously, you know, as we're 386 00:17:45,400 --> 00:17:47,320 Speaker 12: saying at the beginning of this conversation, the rise has 387 00:17:47,320 --> 00:17:50,679 Speaker 12: been absolutely meteoric, and I think that there is a 388 00:17:50,680 --> 00:17:54,439 Speaker 12: sort of hankering for personal connection amid this AI era 389 00:17:54,520 --> 00:17:57,320 Speaker 12: that we're all finding ourselves in. So I'm hopeful that 390 00:17:57,359 --> 00:17:59,920 Speaker 12: we'll get more empirical data on this. Stanford is to 391 00:18:00,119 --> 00:18:02,440 Speaker 12: some good research on this. We also had some I 392 00:18:02,480 --> 00:18:06,520 Speaker 12: came across some data for the piece showing that skepticism 393 00:18:06,600 --> 00:18:09,119 Speaker 12: or lack of trust in AI is rising at a 394 00:18:09,160 --> 00:18:15,000 Speaker 12: pretty rapid clip globally, with some regional differences, But over 395 00:18:15,040 --> 00:18:18,960 Speaker 12: the last sort of three four years, distrust in AI 396 00:18:19,040 --> 00:18:22,000 Speaker 12: has actually risen by about ten percentage points, which is 397 00:18:22,040 --> 00:18:26,600 Speaker 12: a remarkable rate of increase for anything really. So you know, 398 00:18:26,680 --> 00:18:29,520 Speaker 12: let's see what the next generation does and what the 399 00:18:29,600 --> 00:18:30,320 Speaker 12: dynamics look like. 400 00:18:30,320 --> 00:18:31,439 Speaker 5: There, well quickly before we let you go. 401 00:18:31,560 --> 00:18:33,680 Speaker 2: I mean, I want to ask about that next generation 402 00:18:33,720 --> 00:18:35,480 Speaker 2: because I was surprised. I don't know if there's again 403 00:18:35,560 --> 00:18:38,600 Speaker 2: researchers scant, but is there an age difference with adopters 404 00:18:38,640 --> 00:18:41,359 Speaker 2: as well? Because I noticed in my life younger people 405 00:18:41,520 --> 00:18:44,200 Speaker 2: have almost stronger ANTIAI feelings than some of the older 406 00:18:44,200 --> 00:18:45,280 Speaker 2: people in my life, who. 407 00:18:45,080 --> 00:18:46,720 Speaker 5: Were like, this is cool, I can do this thing. 408 00:18:46,800 --> 00:18:49,199 Speaker 2: And then I noticed this week LinkedIn now has an 409 00:18:49,240 --> 00:18:51,240 Speaker 2: option where you can hit the little button and say 410 00:18:51,280 --> 00:18:53,239 Speaker 2: this looks like AI slot. Because I think they were 411 00:18:53,240 --> 00:18:55,159 Speaker 2: getting bombarded with things that people didn't like and it 412 00:18:55,160 --> 00:18:56,199 Speaker 2: was ruining the user experience. 413 00:18:56,280 --> 00:18:58,719 Speaker 12: Yeah, I mean, I think, as ever with new technologies, 414 00:18:58,760 --> 00:19:02,400 Speaker 12: it comes down to literacy, right, and the younger generations 415 00:19:02,600 --> 00:19:05,600 Speaker 12: are individuals who grew up with the Internet, right, They 416 00:19:05,600 --> 00:19:08,680 Speaker 12: don't know a time before the Internet, so maybe that 417 00:19:08,840 --> 00:19:13,120 Speaker 12: sort of skepticism is a little bit more intuitive for them. 418 00:19:13,240 --> 00:19:14,359 Speaker 12: But again, let's see. 419 00:19:14,920 --> 00:19:16,800 Speaker 3: I would ask you lastly just about the difficulty of 420 00:19:16,840 --> 00:19:18,919 Speaker 3: being a skeptic or a fusee as you put it, 421 00:19:19,080 --> 00:19:20,600 Speaker 3: use site in the piece. There are companies now that 422 00:19:20,640 --> 00:19:23,399 Speaker 3: are incentivizing employees to use AI, and so even if 423 00:19:23,440 --> 00:19:25,600 Speaker 3: you don't want to do it or don't think that 424 00:19:25,600 --> 00:19:28,160 Speaker 3: it's going to help or be a positive thing, there 425 00:19:28,240 --> 00:19:30,439 Speaker 3: is pressure now being placed on people to use it 426 00:19:30,440 --> 00:19:30,959 Speaker 3: in the workplace. 427 00:19:31,040 --> 00:19:33,520 Speaker 12: Yeah. Absolutely, there are large companies that are not only 428 00:19:33,560 --> 00:19:38,359 Speaker 12: incentivizing employees to use AI, but actively almost forcing them, right, 429 00:19:38,440 --> 00:19:41,600 Speaker 12: mandating it. And I think those are the skeptics who 430 00:19:42,200 --> 00:19:45,359 Speaker 12: were least willing to speak to me, sure, right, because 431 00:19:45,400 --> 00:19:46,840 Speaker 12: they think their job might be on the line. 432 00:19:47,200 --> 00:19:47,440 Speaker 11: Right. 433 00:19:48,359 --> 00:19:50,600 Speaker 12: But I think that is where we see kind of 434 00:19:50,800 --> 00:19:53,119 Speaker 12: that's really concerning, right, if you're being forced to do 435 00:19:53,160 --> 00:19:55,520 Speaker 12: something in your work that becomes a productivity issue, that 436 00:19:55,560 --> 00:19:59,200 Speaker 12: becomes an engagement issue. Ultimately that could become a workforce issue. 437 00:20:00,040 --> 00:20:00,639 Speaker 5: Stating subject. 438 00:20:00,680 --> 00:20:02,040 Speaker 2: I think it's one that we're all thinking about all 439 00:20:02,080 --> 00:20:03,760 Speaker 2: the time, especially when I don't have kids. 440 00:20:03,520 --> 00:20:05,920 Speaker 5: But I will trying to parents in the water. 441 00:20:05,760 --> 00:20:08,600 Speaker 2: Has to be especially especially difficult that my dog doesn't 442 00:20:08,600 --> 00:20:09,760 Speaker 2: know how to AI, so we're safe there. 443 00:20:09,800 --> 00:20:11,600 Speaker 11: But yes, Cox, thank you so come back because you 444 00:20:11,640 --> 00:20:14,040 Speaker 11: get more empiricals. Please let us know well I can 445 00:20:14,080 --> 00:20:15,040 Speaker 11: see the story as well. 446 00:20:14,920 --> 00:20:16,320 Speaker 2: As to see you. 447 00:20:18,920 --> 00:20:21,120 Speaker 5: Stay with us for more on Bloomberg this weekend. 448 00:20:21,320 --> 00:20:35,119 Speaker 2: Right after this, I want to start by saying the 449 00:20:35,160 --> 00:20:38,879 Speaker 2: story is allegedly a data based analysis, and I am 450 00:20:38,920 --> 00:20:40,399 Speaker 2: now surrounded by legs. 451 00:20:40,480 --> 00:20:41,800 Speaker 5: We've got David. 452 00:20:41,640 --> 00:20:45,280 Speaker 2: Cara and our friend Chris Browser is here. Boys, you're 453 00:20:45,320 --> 00:20:47,080 Speaker 2: showing a lot of leg Is this office. 454 00:20:46,800 --> 00:20:49,439 Speaker 3: Approach showing a lot of leg This piece we're going 455 00:20:49,480 --> 00:20:51,199 Speaker 3: to talk about by Chris has cost more than a 456 00:20:51,200 --> 00:20:53,560 Speaker 3: minor tempest and office towers across New York City and 457 00:20:53,600 --> 00:20:57,120 Speaker 3: indeed in commercial capitals around the world. He not proposing 458 00:20:57,119 --> 00:20:59,200 Speaker 3: the shorts be allowed in the workplace, but investigating whether 459 00:20:59,240 --> 00:21:02,080 Speaker 3: or not there's appetite for it. And Chris, to Christina's point, 460 00:21:02,640 --> 00:21:04,600 Speaker 3: you did this in a very data driven way. You 461 00:21:04,600 --> 00:21:07,480 Speaker 3: conducted a survey. Is now the time, in the dog 462 00:21:07,560 --> 00:21:09,240 Speaker 3: days of summer you feel about it? 463 00:21:09,280 --> 00:21:09,919 Speaker 5: Their facts here? 464 00:21:10,200 --> 00:21:13,160 Speaker 13: No, we had we had the bloom Bloomberg Terminal People 465 00:21:13,280 --> 00:21:17,280 Speaker 13: survey using one of their market pul surveys analysts and 466 00:21:17,480 --> 00:21:20,400 Speaker 13: Terminal subscribers, and forty five percent of. 467 00:21:20,320 --> 00:21:24,080 Speaker 3: People forty five percent, not a majority, said that it 468 00:21:24,119 --> 00:21:25,840 Speaker 3: was suitable to wear shorts to work. 469 00:21:26,280 --> 00:21:28,920 Speaker 13: Now, some of these people responded and said, yeah, oh yeah, 470 00:21:28,960 --> 00:21:30,399 Speaker 13: it's of course it's okay. If you work at a 471 00:21:30,400 --> 00:21:34,720 Speaker 13: surf shop. You know, people really do not support wearing 472 00:21:34,800 --> 00:21:36,800 Speaker 13: shorts work. However, I believe it's time. 473 00:21:37,280 --> 00:21:39,480 Speaker 3: You believe it's time you're going to take that position. 474 00:21:40,800 --> 00:21:44,160 Speaker 3: I work near you physically in the office. You often 475 00:21:44,200 --> 00:21:46,520 Speaker 3: do wear shorts in the summer. You've been taking the 476 00:21:46,600 --> 00:21:48,800 Speaker 3: stand for a while. I have Before you put pen 477 00:21:48,880 --> 00:21:50,919 Speaker 3: to paper, I want you to go back to when 478 00:21:50,960 --> 00:21:53,560 Speaker 3: you first did it. Were you apprehensive about it? What 479 00:21:53,600 --> 00:21:54,919 Speaker 3: did you think the reaction was going to be? 480 00:21:55,160 --> 00:21:56,520 Speaker 13: Yeah, Well, like a lot of people I talked to 481 00:21:56,520 --> 00:21:58,760 Speaker 13: you for this piece, I had, at one point or 482 00:21:58,760 --> 00:22:01,040 Speaker 13: another my career been scolded for not being dressed up 483 00:22:01,119 --> 00:22:02,360 Speaker 13: enough for work. And that's a real thing. 484 00:22:02,440 --> 00:22:04,320 Speaker 3: I mean, this is a guy who wears Monograham shirts 485 00:22:04,440 --> 00:22:06,080 Speaker 3: to work. Would be clear about that. 486 00:22:06,960 --> 00:22:09,639 Speaker 5: Very fancy, very she glen and pants on. Last time 487 00:22:09,640 --> 00:22:10,000 Speaker 5: he was here. 488 00:22:10,040 --> 00:22:12,080 Speaker 13: But there are times, you know when you're not dressed 489 00:22:12,080 --> 00:22:14,160 Speaker 13: appropolyated for a situation, if you're in meeting with people 490 00:22:14,200 --> 00:22:16,440 Speaker 13: or whatever. But if you're not, if you're just going 491 00:22:16,480 --> 00:22:17,720 Speaker 13: to work, you know you're just gonna be a desk 492 00:22:17,840 --> 00:22:20,439 Speaker 13: jockey for the day. My personal rule is that if 493 00:22:20,480 --> 00:22:23,680 Speaker 13: it's over ninety degrees farenhet be allowed to wear fahrenheit 494 00:22:23,920 --> 00:22:27,160 Speaker 13: about thirty two, you should be. 495 00:22:27,119 --> 00:22:29,280 Speaker 5: Allowed to our listeners and shorts. 496 00:22:29,760 --> 00:22:33,560 Speaker 13: Now, one of the first times I did in this office, 497 00:22:33,640 --> 00:22:36,600 Speaker 13: I was walking through the newsroom and the deputy editor 498 00:22:36,600 --> 00:22:38,399 Speaker 13: in chief of Bloomberg News yellow. 499 00:22:38,200 --> 00:22:40,639 Speaker 11: Hello, Reda Grigory. We said good morning to you, Yes. 500 00:22:40,480 --> 00:22:40,960 Speaker 13: Good morning. 501 00:22:41,800 --> 00:22:45,760 Speaker 7: He said, what are you going to the beach? And 502 00:22:45,800 --> 00:22:47,680 Speaker 7: this is a scary Swiss. 503 00:22:47,280 --> 00:22:50,640 Speaker 5: Many lovely but very attached plush Yes. 504 00:22:50,720 --> 00:22:55,160 Speaker 13: So I thought, okay, this is maybe not super accepted, 505 00:22:55,200 --> 00:22:58,320 Speaker 13: but I powered through, and now I think it's a 506 00:22:58,400 --> 00:23:01,080 Speaker 13: It's a topic of conversation all over New York City. 507 00:23:01,200 --> 00:23:03,200 Speaker 2: I will say, since I knew we were doing this piece, 508 00:23:04,600 --> 00:23:05,200 Speaker 2: forget my shorts. 509 00:23:05,240 --> 00:23:06,639 Speaker 5: I'm sorry, I just came out for vacation. I did 510 00:23:06,680 --> 00:23:07,400 Speaker 5: forget my shorts. 511 00:23:07,440 --> 00:23:10,040 Speaker 2: Ironically, but as I was looking around today on a 512 00:23:10,040 --> 00:23:12,920 Speaker 2: Friday in the summer, there were quite a few pair. 513 00:23:12,760 --> 00:23:13,439 Speaker 5: Of work shorts. 514 00:23:13,480 --> 00:23:16,199 Speaker 2: Now I've never done summer shorts, but I do have 515 00:23:16,280 --> 00:23:17,960 Speaker 2: like the really long bermudas that kind of go with 516 00:23:18,000 --> 00:23:18,679 Speaker 2: the matching. 517 00:23:18,520 --> 00:23:21,560 Speaker 11: Jocket with all those cool clam diggers. 518 00:23:21,600 --> 00:23:23,920 Speaker 2: And I've done winter shorts because you can wear them 519 00:23:24,040 --> 00:23:27,760 Speaker 2: with tights. Because for me, the controversy here, especially on 520 00:23:27,800 --> 00:23:31,840 Speaker 2: the women's end, is what length of short is workplace appropriate? 521 00:23:31,880 --> 00:23:34,360 Speaker 2: Because we have variant hemlines on YouTube. 522 00:23:34,480 --> 00:23:37,080 Speaker 11: We wanted to show a little leg. Yes, yeah, well. 523 00:23:37,000 --> 00:23:38,840 Speaker 2: But I mean, is there a fine is there a 524 00:23:38,840 --> 00:23:41,440 Speaker 2: thigh threshold for work appropriate? Is did you ask people 525 00:23:41,440 --> 00:23:43,320 Speaker 2: about the length and kind of short people? 526 00:23:43,720 --> 00:23:46,320 Speaker 13: You know, the thing is you think the longer like 527 00:23:46,359 --> 00:23:48,040 Speaker 13: the more appropriate. But if you get shorts that are 528 00:23:48,119 --> 00:23:50,520 Speaker 13: kind of below the knee, that's also a different look 529 00:23:50,640 --> 00:23:53,320 Speaker 13: that can be like feel less tidy. So my feeling 530 00:23:53,400 --> 00:23:56,479 Speaker 13: is like a seven to nine inch in seem anything 531 00:23:56,520 --> 00:23:58,480 Speaker 13: shorter than that. Usually my husband tells me what is 532 00:23:58,480 --> 00:24:00,919 Speaker 13: appropriate for work. And one day he wasn't home, he 533 00:24:00,960 --> 00:24:02,560 Speaker 13: was traveling, and I went to work and I immediately 534 00:24:02,560 --> 00:24:03,959 Speaker 13: walked in the office and I was like, these are 535 00:24:04,000 --> 00:24:04,840 Speaker 13: too short. 536 00:24:05,040 --> 00:24:05,800 Speaker 7: I'd made a mistake. 537 00:24:07,040 --> 00:24:08,480 Speaker 11: You dig into the history here. 538 00:24:09,040 --> 00:24:13,600 Speaker 3: Look, during revolutionary war times, the men in power were 539 00:24:13,600 --> 00:24:16,160 Speaker 3: wearing I guess not shorts, but breeches. 540 00:24:16,320 --> 00:24:16,760 Speaker 7: Is the thing. 541 00:24:16,920 --> 00:24:19,480 Speaker 13: We think that like, we've been wearing suits and stuff 542 00:24:19,560 --> 00:24:22,280 Speaker 13: to work forever, and that's simply not true. 543 00:24:22,520 --> 00:24:24,200 Speaker 7: It used to be that. 544 00:24:24,359 --> 00:24:26,800 Speaker 13: Wearing clothes that recognize that you live in the world 545 00:24:26,800 --> 00:24:28,800 Speaker 13: and you have to use your body for work was 546 00:24:29,000 --> 00:24:32,320 Speaker 13: very like, was very not fancy. Like if you were 547 00:24:32,320 --> 00:24:35,280 Speaker 13: an aristocrat, you needed to wear clothes like corsets and 548 00:24:35,320 --> 00:24:37,320 Speaker 13: tight things and things that showed that you didn't have 549 00:24:37,359 --> 00:24:39,160 Speaker 13: a body or you could never possibly use. 550 00:24:39,119 --> 00:24:40,600 Speaker 5: Your body for you You didn't have to do labor, 551 00:24:40,640 --> 00:24:41,320 Speaker 5: you didn't. 552 00:24:41,040 --> 00:24:42,520 Speaker 13: Have to do it, like prove that you didn't have 553 00:24:42,560 --> 00:24:46,800 Speaker 13: to do labor. But even then, men showed their legs, 554 00:24:47,200 --> 00:24:50,440 Speaker 13: people wore breeches and wore tights. At the signing of 555 00:24:50,680 --> 00:24:54,639 Speaker 13: the Declaration of Independence, John Adams was wearing stockings and 556 00:24:54,680 --> 00:24:57,600 Speaker 13: showed his calves. So like you can do it. 557 00:24:57,600 --> 00:25:01,800 Speaker 3: Celebrate that two fiftieth Christina, right now, can I ask 558 00:25:01,840 --> 00:25:03,480 Speaker 3: you last week a minute loud, I go home. 559 00:25:03,560 --> 00:25:04,240 Speaker 11: I can't go home. 560 00:25:05,320 --> 00:25:07,880 Speaker 3: You know you're you're paving this path or designers doing 561 00:25:07,880 --> 00:25:09,240 Speaker 3: it as well? Are we seeing this like on the 562 00:25:09,320 --> 00:25:11,359 Speaker 3: runways that now one comes to men's. 563 00:25:11,080 --> 00:25:15,240 Speaker 2: Fashion and women as well, there are suit short outfits 564 00:25:15,520 --> 00:25:16,280 Speaker 2: more frequently that. 565 00:25:16,240 --> 00:25:17,600 Speaker 5: You can buy two two. 566 00:25:17,640 --> 00:25:19,119 Speaker 13: There were two main pegs for this story, one of 567 00:25:19,160 --> 00:25:21,760 Speaker 13: which was in Tokyo, there's actually like a government and 568 00:25:21,840 --> 00:25:24,159 Speaker 13: mandate the municipal workers are allowed to wear shorts and 569 00:25:24,160 --> 00:25:27,600 Speaker 13: that has caused and has caused a lot of consternation. 570 00:25:28,000 --> 00:25:30,400 Speaker 13: And then also on the on the runs the runways 571 00:25:30,400 --> 00:25:32,760 Speaker 13: at the Men's Wort show in Milan and in Paris, 572 00:25:32,800 --> 00:25:35,080 Speaker 13: there were a lot of shorts paired with blazers, suits 573 00:25:35,080 --> 00:25:38,360 Speaker 13: and jackets. So like, uh, you know, Tom Ford lou Vitan. 574 00:25:38,960 --> 00:25:41,080 Speaker 5: Has been doing this forever too, like the short suits. 575 00:25:41,080 --> 00:25:42,919 Speaker 13: I meant Tom Brown, Yeah, Tom Brown has always been 576 00:25:42,960 --> 00:25:45,640 Speaker 13: doing it, doing it. Saint Laurent sent down a look 577 00:25:45,640 --> 00:25:47,480 Speaker 13: on the runway which was basically like a guy in 578 00:25:47,520 --> 00:25:50,359 Speaker 13: a blazer with no bottoms and that is like a 579 00:25:50,440 --> 00:25:52,280 Speaker 13: nightmare that a lot of us have actually had and 580 00:25:52,320 --> 00:25:53,200 Speaker 13: what it feels like. 581 00:25:53,240 --> 00:25:54,680 Speaker 11: To show up summer of twenty seven. 582 00:25:54,720 --> 00:25:58,199 Speaker 3: Maybe maybe not here, Chris, Thank you very much, co 583 00:25:58,280 --> 00:25:59,200 Speaker 3: rats on the controversy. 584 00:25:59,280 --> 00:26:00,960 Speaker 5: Thank you well for breaking down borders. 585 00:26:01,000 --> 00:26:04,800 Speaker 2: And raising hemlines starting you appreciate it. 586 00:26:04,880 --> 00:26:08,560 Speaker 4: Stay with us for more on Bloomberg this weekend right 587 00:26:08,600 --> 00:26:21,840 Speaker 4: after this, Welcome. 588 00:26:21,560 --> 00:26:24,960 Speaker 3: Back to Bloomberg this weekend, Bloomberg B this T Weekend 589 00:26:25,119 --> 00:26:26,200 Speaker 3: w B T W. 590 00:26:26,680 --> 00:26:27,640 Speaker 11: As we say, David. 591 00:26:27,440 --> 00:26:32,440 Speaker 3: Grew, Christina Lisa Matteos, you've ascertained out this week. Nathan 592 00:26:32,480 --> 00:26:34,439 Speaker 3: Hager with us with some stories you might have missed. 593 00:26:35,760 --> 00:26:38,679 Speaker 3: You've been mining the terminal, mining Bloomberg dot com, mining. 594 00:26:38,480 --> 00:26:39,439 Speaker 11: Outside sites as well. 595 00:26:39,480 --> 00:26:41,200 Speaker 14: I should say it's not for us to look. 596 00:26:41,119 --> 00:26:45,520 Speaker 5: Broadly at the news, not using AI. Using your brain. 597 00:26:45,680 --> 00:26:47,280 Speaker 14: Can't do that critical thinking. 598 00:26:47,560 --> 00:26:49,840 Speaker 15: We even do that this early in the morning, and 599 00:26:49,920 --> 00:26:51,360 Speaker 15: morning it's hard, is a struggling. 600 00:26:51,480 --> 00:26:52,240 Speaker 11: There is coffee. 601 00:26:52,280 --> 00:26:55,760 Speaker 15: There is coffee speaking of right, this is about coffee. 602 00:26:55,800 --> 00:26:59,040 Speaker 15: This is about drinking culture. Because I don't think there's 603 00:26:59,119 --> 00:27:02,880 Speaker 15: it's any secret that the beverage industry has been dealing 604 00:27:03,040 --> 00:27:06,600 Speaker 15: with the changes twenty somethings kind of pulling back because 605 00:27:06,640 --> 00:27:08,439 Speaker 15: of health concerns or the economy. 606 00:27:08,520 --> 00:27:10,440 Speaker 2: Yeah, we just have a story of Jim Beam and 607 00:27:10,080 --> 00:27:12,080 Speaker 2: they're owned by this big Japanese conglomerate and. 608 00:27:12,080 --> 00:27:15,159 Speaker 3: They because that they're actually getting into not a non 609 00:27:15,200 --> 00:27:16,840 Speaker 3: alcoholic whiskey, but like no. 610 00:27:16,960 --> 00:27:17,480 Speaker 5: But Jim Beam. 611 00:27:17,520 --> 00:27:20,600 Speaker 2: They're doing non alcoholic cocktails to try to, you know, 612 00:27:20,680 --> 00:27:23,639 Speaker 2: get these young people who are not drinking alcohol to 613 00:27:23,680 --> 00:27:24,600 Speaker 2: purchase some of their produities. 614 00:27:24,600 --> 00:27:26,960 Speaker 15: Well, this isn't just a Western phenomenon or here in 615 00:27:27,000 --> 00:27:29,880 Speaker 15: the States. It's even spreading to China. Although the reasons 616 00:27:29,920 --> 00:27:32,240 Speaker 15: here are a little bit different. This is really about 617 00:27:32,240 --> 00:27:35,159 Speaker 15: a generational divide. This was from the Wall Street Journal 618 00:27:35,160 --> 00:27:39,240 Speaker 15: this week. A sober curious generation is challenging the business 619 00:27:39,280 --> 00:27:41,919 Speaker 15: culture of heavy drinking. Because you can see it right 620 00:27:41,960 --> 00:27:44,919 Speaker 15: here for our listeners on radio, they do toasts. This 621 00:27:44,960 --> 00:27:48,400 Speaker 15: has been a part of the culture for dagoes. Now 622 00:27:49,480 --> 00:27:52,600 Speaker 15: some business leaders say that you know, just you can 623 00:27:52,680 --> 00:27:55,600 Speaker 15: tell whether a deal is going to go down based 624 00:27:55,640 --> 00:27:59,479 Speaker 15: on how many toasts are in the deal. So an 625 00:27:59,520 --> 00:28:02,679 Speaker 15: initial business steel is even about business. It's about just 626 00:28:02,840 --> 00:28:05,520 Speaker 15: doing the toast. And this is around a national drink 627 00:28:05,560 --> 00:28:08,119 Speaker 15: called by Jew It's actually one hundred and seventy billion 628 00:28:08,160 --> 00:28:11,560 Speaker 15: dollar business. This is a clear spirit that's distilled from sorghum, 629 00:28:11,600 --> 00:28:16,040 Speaker 15: and it's kind of the traditional alcoholic beverage that Chinese 630 00:28:16,040 --> 00:28:19,600 Speaker 15: business people and at social gatherings do to do these toasts. 631 00:28:19,680 --> 00:28:22,359 Speaker 15: But only about a fifth of adults in China ages 632 00:28:22,400 --> 00:28:24,680 Speaker 15: twenty five to thirty five name it as their preferred 633 00:28:24,720 --> 00:28:28,159 Speaker 15: alcoholic drink. They say at least one worker says, it 634 00:28:28,160 --> 00:28:33,200 Speaker 15: burns your thoughts instinct It is very I have, but 635 00:28:33,240 --> 00:28:33,840 Speaker 15: I've never had this. 636 00:28:34,000 --> 00:28:35,200 Speaker 11: It's extremely strong. 637 00:28:35,280 --> 00:28:37,560 Speaker 15: Would you say that the aftertaste is worse than a 638 00:28:37,600 --> 00:28:41,280 Speaker 15: mix of funky cheese and ferment well juice, you know. 639 00:28:41,520 --> 00:28:43,080 Speaker 3: I don't even know if I had time to process 640 00:28:43,160 --> 00:28:45,600 Speaker 3: the taste because it was so powerful and strong. Oh, 641 00:28:45,800 --> 00:28:49,320 Speaker 3: it reminds me of that. But mylord, isn't that the 642 00:28:49,600 --> 00:28:51,760 Speaker 3: Chicago drink. It's like a very strong I don't know 643 00:28:51,800 --> 00:28:53,560 Speaker 3: what that is either. Well, I will bring some in 644 00:28:53,600 --> 00:28:54,880 Speaker 3: for you to have, But I mean I. 645 00:28:54,800 --> 00:28:56,960 Speaker 5: Had moonshine ones. Well it almost killed me. 646 00:28:58,000 --> 00:29:00,360 Speaker 15: So the bottom line about how this is worked in 647 00:29:00,440 --> 00:29:05,760 Speaker 15: China is that it's not just about giving up alcohol necessarily. 648 00:29:05,880 --> 00:29:10,360 Speaker 15: It's about changing the way that young people decide to 649 00:29:10,480 --> 00:29:13,160 Speaker 15: drink and sort of rejecting or you know, going a 650 00:29:13,160 --> 00:29:15,440 Speaker 15: little bit against how the older generation have done it 651 00:29:16,080 --> 00:29:19,400 Speaker 15: with their alcohol experience or what else you got, Well, 652 00:29:19,480 --> 00:29:23,160 Speaker 15: you mentioned the must have summer status symbols. 653 00:29:23,200 --> 00:29:25,240 Speaker 14: Weased well, something to drink. 654 00:29:25,480 --> 00:29:27,440 Speaker 2: It's not a tan because we've all learned that's not 655 00:29:27,520 --> 00:29:28,160 Speaker 2: happening for me. 656 00:29:28,520 --> 00:29:31,720 Speaker 14: Well, it's something in a bottle. It's not sunscreen. It's 657 00:29:31,760 --> 00:29:35,240 Speaker 14: a three ninety nine dollars bottle of water. 658 00:29:35,600 --> 00:29:38,240 Speaker 15: As you can forget your bai juw flavored lattes or 659 00:29:38,280 --> 00:29:39,040 Speaker 15: your bubble tea. 660 00:29:39,200 --> 00:29:42,520 Speaker 14: This is lunar water. It's showing up. 661 00:29:42,400 --> 00:29:46,320 Speaker 15: At bougie grocery stores, private events here in New York City. 662 00:29:46,720 --> 00:29:50,640 Speaker 5: Must have seen it and the show how dare you? Also? Yes, 663 00:29:50,680 --> 00:29:51,800 Speaker 5: I have, I'll have you know. 664 00:29:52,280 --> 00:29:55,520 Speaker 15: And the way they sell this is it's sourced from 665 00:29:55,520 --> 00:29:59,720 Speaker 15: a southern California spring. Yes, there stainless steel filtration, adding 666 00:29:59,800 --> 00:30:04,880 Speaker 15: net minerals like Celtic sea salt, magnesium, potassium, and calcium, 667 00:30:04,920 --> 00:30:08,320 Speaker 15: all this for the low low price of three dollars 668 00:30:08,640 --> 00:30:12,880 Speaker 15: and ninety nine cents. Now, this was founded co founded 669 00:30:12,960 --> 00:30:15,640 Speaker 15: last year actually by a woman named Clara cig She's 670 00:30:15,680 --> 00:30:19,000 Speaker 15: a former venture capitalist too. When she was, you know, 671 00:30:19,440 --> 00:30:22,680 Speaker 15: deciding to get pregnant, getting ready to decided to educate 672 00:30:22,680 --> 00:30:26,640 Speaker 15: herself about micro plastics and found that. 673 00:30:26,680 --> 00:30:28,800 Speaker 14: She says that the stainless steel. 674 00:30:28,520 --> 00:30:33,560 Speaker 15: Filtration process gets out more of the microplastics. But when 675 00:30:33,600 --> 00:30:38,320 Speaker 15: you talk to experts, they say water's water. And even 676 00:30:38,360 --> 00:30:42,360 Speaker 15: if there is a you know, evy on or liquid bovy, 677 00:30:43,120 --> 00:30:45,560 Speaker 15: there is no evidence that any of these elite brands 678 00:30:45,800 --> 00:30:47,960 Speaker 15: are going to give you any other water. 679 00:30:48,040 --> 00:30:49,440 Speaker 5: And glass does taste. 680 00:30:50,800 --> 00:31:00,960 Speaker 16: It's it's called Luninkay what else editorial drink? Why would 681 00:31:00,960 --> 00:31:01,760 Speaker 16: I editorialize? 682 00:31:01,800 --> 00:31:02,000 Speaker 9: Never? 683 00:31:02,200 --> 00:31:02,720 Speaker 14: Okay never. 684 00:31:02,880 --> 00:31:06,640 Speaker 15: So we're going to go from luxury water to luxury 685 00:31:06,680 --> 00:31:11,120 Speaker 15: hotels here because this is a new trend across Europe. 686 00:31:11,160 --> 00:31:14,200 Speaker 15: Actually it's not just about the thread count or the 687 00:31:14,200 --> 00:31:18,320 Speaker 15: buzzy restaurant. History is the new amenity. This story is 688 00:31:18,600 --> 00:31:22,160 Speaker 15: actually from Bloomberg Today. This week, you can go to 689 00:31:22,200 --> 00:31:25,920 Speaker 15: the Raffles London at the ow Woe and sim Martinis 690 00:31:25,920 --> 00:31:29,600 Speaker 15: in a basement that was once used by British intelligence 691 00:31:29,640 --> 00:31:29,840 Speaker 15: like that. 692 00:31:29,880 --> 00:31:33,600 Speaker 2: Of course you're speaking my language history nerd and bougie hotel. 693 00:31:34,200 --> 00:31:39,720 Speaker 14: Quiz O w WO stands for Office of Wartime along 694 00:31:39,760 --> 00:31:40,440 Speaker 14: the lines. 695 00:31:40,160 --> 00:31:45,920 Speaker 15: The Old War Office the Nomad London. You can tour 696 00:31:46,000 --> 00:31:51,240 Speaker 15: old prison cells where Oscar Wilde once waited for sentencing. 697 00:31:52,000 --> 00:31:59,800 Speaker 15: So guests are paying upwards of thirteen thousand thirteen. So 698 00:31:59,840 --> 00:32:02,080 Speaker 15: you can stay at places that were once limited to 699 00:32:02,240 --> 00:32:04,200 Speaker 15: the most powerful, and like I said, this is a 700 00:32:04,240 --> 00:32:06,840 Speaker 15: trend to cross Europe. Their old ministries in Paris and 701 00:32:06,920 --> 00:32:09,960 Speaker 15: Lisbon that are turning into hotels, the former Italian Central 702 00:32:10,000 --> 00:32:13,560 Speaker 15: Bank headquarters in Rome, because they got to offload some 703 00:32:13,640 --> 00:32:16,520 Speaker 15: of these old buildings as the governments are modernizing, and 704 00:32:16,560 --> 00:32:18,760 Speaker 15: these hotel chains are saying, you know what, we'll go 705 00:32:18,760 --> 00:32:21,440 Speaker 15: ahead and snap them up and give our guests an 706 00:32:21,640 --> 00:32:24,240 Speaker 15: experience that they'll never forget compared to like the museums 707 00:32:24,320 --> 00:32:25,840 Speaker 15: or the spa or whatever. 708 00:32:25,920 --> 00:32:28,240 Speaker 2: You know, I understand there's an access issue here and 709 00:32:28,280 --> 00:32:30,120 Speaker 2: it's not equitable, but I also do think it is 710 00:32:30,240 --> 00:32:32,960 Speaker 2: nice to preserve these buildings that other might otherwise not 711 00:32:33,000 --> 00:32:35,400 Speaker 2: have a purpose. At least someone is paying to save them. 712 00:32:35,440 --> 00:32:37,400 Speaker 2: And you know you got to buy a fourteen dollar 713 00:32:37,440 --> 00:32:38,840 Speaker 2: martini to help an. 714 00:32:38,760 --> 00:32:42,840 Speaker 15: Old post office V Well, there's a olderf historian now. 715 00:32:43,240 --> 00:32:44,920 Speaker 5: It is now and has a very nice bar. I've 716 00:32:44,920 --> 00:32:47,240 Speaker 5: been there multiple times, Nathan. 717 00:32:46,960 --> 00:32:48,080 Speaker 11: Thank you very much, appreciate that. 718 00:32:48,200 --> 00:32:49,560 Speaker 14: Give btw. 719 00:32:51,400 --> 00:32:54,360 Speaker 2: Thanks for joining us on today's Bloomberg This Weekend podcast. 720 00:32:54,480 --> 00:32:56,720 Speaker 2: Don't forget to tune in live for the show every 721 00:32:56,760 --> 00:32:59,400 Speaker 2: Saturday and Sunday morning, starting at seven am Eastern 722 00:32:59,440 --> 00:33:02,480 Speaker 3: We're on bloom Television, radio, and the Bloomberg Business App, 723 00:33:02,600 --> 00:33:06,120 Speaker 3: bringing you unique takes and in depth interviews on news, politics, 724 00:33:06,200 --> 00:33:07,400 Speaker 3: lifestyle and culture.