1 00:00:02,560 --> 00:00:11,080 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:08,960 --> 00:00:11,200 Speaker 2: Max Chaffkin, Stacy Van Smith. 3 00:00:11,320 --> 00:00:13,080 Speaker 3: Hello, Hello, it. 4 00:00:13,160 --> 00:00:17,800 Speaker 4: Is another week, another giant set of confusing data from 5 00:00:17,840 --> 00:00:18,680 Speaker 4: the US economy. 6 00:00:22,800 --> 00:00:26,360 Speaker 5: Every big company has reported earnings or is about to 7 00:00:26,400 --> 00:00:29,120 Speaker 5: report earnings. That's sending the markets all over the place. 8 00:00:29,320 --> 00:00:31,880 Speaker 5: You got the Federal Reserve, you got GDP numbers, you 9 00:00:31,960 --> 00:00:33,920 Speaker 5: got inflation super confidence. 10 00:00:34,080 --> 00:00:35,239 Speaker 3: The economy is. 11 00:00:35,320 --> 00:00:39,720 Speaker 5: Kind of teetering, maybe, and we're going to talk about that. 12 00:00:40,080 --> 00:00:40,880 Speaker 2: Yes, we are. 13 00:00:40,960 --> 00:00:43,280 Speaker 4: In addition to that, we are talking about tariffs. 14 00:00:43,320 --> 00:00:44,440 Speaker 2: We are talking to a company. 15 00:00:44,280 --> 00:00:47,080 Speaker 4: That is suing the Trump administration over this latest rounds 16 00:00:47,080 --> 00:00:47,680 Speaker 4: of tariffs. 17 00:00:48,040 --> 00:00:51,480 Speaker 2: And of course prediction markets, yes, your right to vote. 18 00:00:51,640 --> 00:00:54,920 Speaker 5: We are going to talk about the brave prediction market 19 00:00:54,960 --> 00:00:59,520 Speaker 5: traders who are having their franchise threatened by some Wisconsin. 20 00:00:59,000 --> 00:01:01,080 Speaker 3: Bureaucrats of life. 21 00:01:01,320 --> 00:01:02,240 Speaker 6: Or maybe you. 22 00:01:02,160 --> 00:01:03,240 Speaker 3: Shouldn't bet on elections. 23 00:01:03,320 --> 00:01:05,560 Speaker 5: I don't know, but we will get into it on 24 00:01:05,640 --> 00:01:07,160 Speaker 5: our this week in Prediction Market segment. 25 00:01:07,520 --> 00:01:10,080 Speaker 4: This is Everybody's business from Bloomberg BusinessWeek. 26 00:01:10,080 --> 00:01:13,240 Speaker 5: I'm Stacey Vanocksmith, I'm Max Schafkin. We got the economy, 27 00:01:13,680 --> 00:01:16,039 Speaker 5: We've got tariffs, prediction markets, it's. 28 00:01:15,920 --> 00:01:17,199 Speaker 2: All there, it's all there. 29 00:01:17,400 --> 00:01:26,120 Speaker 3: Stick around, Stacy. 30 00:01:26,440 --> 00:01:30,640 Speaker 5: We've had just a ton of economic news, some of 31 00:01:30,680 --> 00:01:33,000 Speaker 5: it related to the FED, some of it related to 32 00:01:33,040 --> 00:01:33,800 Speaker 5: stock market. 33 00:01:34,040 --> 00:01:35,520 Speaker 3: We've got a great person to talk about this. 34 00:01:35,600 --> 00:01:38,679 Speaker 5: It's Eric Wiener, Bloomberg Senior Editor, author of The Shadow 35 00:01:38,720 --> 00:01:39,760 Speaker 5: Market and What Goes Up? 36 00:01:39,760 --> 00:01:42,160 Speaker 3: Hey? Eric, Hi, how you doing? Okay? So here's where 37 00:01:42,160 --> 00:01:42,880 Speaker 3: I want to start. 38 00:01:43,160 --> 00:01:45,240 Speaker 5: I feel like this has been going on so long 39 00:01:45,560 --> 00:01:47,720 Speaker 5: that I forgot when it started. But there was a 40 00:01:47,760 --> 00:01:50,520 Speaker 5: point where we started saying, like all of the stock 41 00:01:50,560 --> 00:01:53,120 Speaker 5: market gains are related to the Magnificent Seven. There were 42 00:01:53,120 --> 00:02:00,960 Speaker 5: these seven stocks, Microsoft, Apple, Amazon Video, Tesla forgot, I forgot, 43 00:02:01,040 --> 00:02:05,200 Speaker 5: Alphabet Google, Yeah, okay, all those stocks. They are basically 44 00:02:05,560 --> 00:02:09,280 Speaker 5: these sort of AI powerhouses in one way or another. 45 00:02:09,520 --> 00:02:13,400 Speaker 5: Everyone's excited about AI, and you know, everyone's excited about 46 00:02:13,440 --> 00:02:15,600 Speaker 5: Trump and the way he's managing AI and all. And 47 00:02:16,120 --> 00:02:19,079 Speaker 5: for like about a year, maybe even longer, Eric, I 48 00:02:19,080 --> 00:02:21,160 Speaker 5: don't know, these stocks just kind of ripped. 49 00:02:21,280 --> 00:02:24,360 Speaker 3: They were driving so much wealth creation, and. 50 00:02:24,280 --> 00:02:29,079 Speaker 5: We're kind of seeing that breakdown right now, right Eric. 51 00:02:29,320 --> 00:02:34,880 Speaker 6: It is breaking down in a very strange way. The 52 00:02:34,919 --> 00:02:37,640 Speaker 6: mag seven, for lack of a better term, is no 53 00:02:37,680 --> 00:02:42,840 Speaker 6: longer really a coherent group AI has messed the whole 54 00:02:42,840 --> 00:02:46,680 Speaker 6: thing up. And what you're seeing now is within the 55 00:02:46,680 --> 00:02:51,360 Speaker 6: Magnificent seven, four of them are huge spenders on AI. 56 00:02:51,480 --> 00:02:56,840 Speaker 6: That's Alphabet, Amazon, Microsoft, and Meta. Then you have Tesla, 57 00:02:56,960 --> 00:02:59,520 Speaker 6: which isn't a tech company and is trying to get 58 00:02:59,520 --> 00:03:01,840 Speaker 6: into AI, but isn't spending very much on it. You 59 00:03:01,880 --> 00:03:03,920 Speaker 6: have Nvidia, which is the chip maker for these guys, 60 00:03:03,960 --> 00:03:06,320 Speaker 6: and then you have Apple, which isn't spending at all. 61 00:03:06,560 --> 00:03:12,720 Speaker 6: So this year Apple is dominating the Magnificent seven because 62 00:03:12,760 --> 00:03:17,079 Speaker 6: they don't have the AI risk that the others do. Today, 63 00:03:17,360 --> 00:03:21,120 Speaker 6: Microsoft is ripping higher because they had this great cloud revenue, 64 00:03:21,240 --> 00:03:24,000 Speaker 6: which means that they're getting a lot of traction in 65 00:03:24,040 --> 00:03:28,600 Speaker 6: their AI sales. And Meta is getting killed because well, 66 00:03:28,600 --> 00:03:29,720 Speaker 6: really nobody believes in Mark. 67 00:03:29,639 --> 00:03:32,040 Speaker 3: Zuckerberg because they're AI stinks. 68 00:03:32,120 --> 00:03:35,280 Speaker 5: They've spent a fortune on these potentially game changing but 69 00:03:35,520 --> 00:03:39,720 Speaker 5: still unproven sort of augmented reality technologies. They don't have 70 00:03:39,840 --> 00:03:41,640 Speaker 5: like a clear AI revenue stream. 71 00:03:41,680 --> 00:03:45,600 Speaker 6: There's a bigger problem, and it's the metaverse. Nobody buys 72 00:03:45,720 --> 00:03:48,520 Speaker 6: what Zuckerberg is selling. And then so like you look 73 00:03:48,520 --> 00:03:53,119 Speaker 6: at Google and or well Alphabet and they're all over 74 00:03:53,160 --> 00:03:55,240 Speaker 6: the police. At this time last year, they were considered 75 00:03:55,320 --> 00:03:58,520 Speaker 6: kind of an AI afterthought, and then all of a sudden, 76 00:03:58,640 --> 00:04:02,040 Speaker 6: Gemini takes off, and then people realize, oh my god, 77 00:04:02,040 --> 00:04:03,680 Speaker 6: they're the search engine for all of this. 78 00:04:04,200 --> 00:04:05,320 Speaker 3: So they're diversified. 79 00:04:05,480 --> 00:04:07,920 Speaker 6: And all of these companies which we all had lumped 80 00:04:07,920 --> 00:04:11,280 Speaker 6: together into one kind of group, have fallen apart the 81 00:04:11,280 --> 00:04:14,160 Speaker 6: same way that like they always do bricks or whatever else, 82 00:04:14,160 --> 00:04:16,880 Speaker 6: pick your you know your name, and this happens. 83 00:04:17,120 --> 00:04:18,240 Speaker 2: Well, to back up. 84 00:04:18,200 --> 00:04:20,880 Speaker 4: A little bit here, we've been getting earnings from a 85 00:04:20,880 --> 00:04:23,000 Speaker 4: lot of these companies that had been really not only 86 00:04:23,120 --> 00:04:25,320 Speaker 4: driving the stock market, but really driving a lot of 87 00:04:25,360 --> 00:04:27,680 Speaker 4: the economic growth. Like Max was saying, I mean just 88 00:04:27,720 --> 00:04:30,400 Speaker 4: really seeping into all these parts of the economy. Now 89 00:04:30,440 --> 00:04:33,960 Speaker 4: that there's a more mixed picture maybe within these companies, 90 00:04:34,240 --> 00:04:36,400 Speaker 4: what does that mean for the economy? 91 00:04:36,440 --> 00:04:37,680 Speaker 2: What does that mean for us? 92 00:04:38,040 --> 00:04:43,000 Speaker 6: So the economy is actually doing pretty well when you 93 00:04:43,040 --> 00:04:46,400 Speaker 6: look at the overall the top line numbers. Yeah, when 94 00:04:46,400 --> 00:04:50,320 Speaker 6: you look underneath, it's not so great. The whole idea 95 00:04:50,400 --> 00:04:54,640 Speaker 6: is predicated on a linear growth pattern, and if you 96 00:04:54,680 --> 00:04:57,240 Speaker 6: look at the history of technology, that just isn't what happens. 97 00:04:57,560 --> 00:05:01,120 Speaker 6: So right now you are looking at trying to price 98 00:05:01,240 --> 00:05:05,279 Speaker 6: AI as if it's going to happen tomorrow, and that's 99 00:05:05,400 --> 00:05:10,560 Speaker 6: just not the way technology evolves. So the concern about 100 00:05:10,640 --> 00:05:14,840 Speaker 6: the economy is interest rates. Are these companies going to 101 00:05:14,880 --> 00:05:17,320 Speaker 6: be able to continue to raise money at the levels 102 00:05:17,360 --> 00:05:20,599 Speaker 6: that they were raising them at before stock prices because 103 00:05:20,680 --> 00:05:24,240 Speaker 6: if they can't sell their stock, they can't offer you know, 104 00:05:24,240 --> 00:05:26,760 Speaker 6: it can't do more issuance. That means they're not going 105 00:05:26,800 --> 00:05:28,800 Speaker 6: to be able to get the capital. And if they 106 00:05:28,839 --> 00:05:32,680 Speaker 6: can't do that, then all those those chip makers they 107 00:05:32,680 --> 00:05:35,560 Speaker 6: don't get their money, and then all of this that 108 00:05:35,839 --> 00:05:39,159 Speaker 6: money that filters down into the economy that creates growth. 109 00:05:39,160 --> 00:05:42,160 Speaker 6: I mean right now we're seeing booming growth in construction 110 00:05:42,480 --> 00:05:44,600 Speaker 6: because who's going to build the data centers? You know, 111 00:05:44,960 --> 00:05:48,040 Speaker 6: all of these things flick off in different ways. When 112 00:05:48,160 --> 00:05:51,640 Speaker 6: markets tighten up, it's always because of a liquidity crisis. 113 00:05:51,640 --> 00:05:53,440 Speaker 6: People can't get money. And so this is what I'm 114 00:05:53,440 --> 00:05:57,320 Speaker 6: describing right now, is the fear is that if interest 115 00:05:57,400 --> 00:05:59,880 Speaker 6: rates get to a point where they can't raise cash, 116 00:06:00,279 --> 00:06:02,480 Speaker 6: and stock prices get to a point where they're not 117 00:06:02,560 --> 00:06:05,760 Speaker 6: issuing stock, then where are they going to get the money. 118 00:06:06,000 --> 00:06:08,760 Speaker 6: So now they have to raise money, and if that 119 00:06:08,880 --> 00:06:13,599 Speaker 6: money isn't there. Suddenly liquidity dries up and the market 120 00:06:13,680 --> 00:06:17,160 Speaker 6: goes crazy over that because it means that money isn't 121 00:06:17,200 --> 00:06:21,279 Speaker 6: flowing and all of commerce just slows down when that happens. 122 00:06:21,640 --> 00:06:24,640 Speaker 5: Enter Kevin warsh right and Ken wars and that is 123 00:06:24,680 --> 00:06:27,200 Speaker 5: one of the reasons why this FED meeting, which which 124 00:06:27,680 --> 00:06:31,360 Speaker 5: happened yesterday as we're recording this on Thursday, was so interesting. 125 00:06:31,600 --> 00:06:34,359 Speaker 5: So just Sacey, you follow this more closely than I do. 126 00:06:34,480 --> 00:06:37,359 Speaker 5: You are a more of a FED watcher than me. 127 00:06:37,880 --> 00:06:39,920 Speaker 5: Give us the kind of top line on what happened, 128 00:06:39,960 --> 00:06:41,920 Speaker 5: and you know what you found interesting. 129 00:06:42,040 --> 00:06:45,200 Speaker 4: So people were not sure quite what to expect. Everybody 130 00:06:45,279 --> 00:06:47,800 Speaker 4: kind of thought the Federalserve Board would hold interest rates 131 00:06:47,839 --> 00:06:52,640 Speaker 4: where they were because inflation is higher than we want, 132 00:06:53,000 --> 00:06:57,000 Speaker 4: but also the job market is a little sluggish. 133 00:06:57,200 --> 00:07:02,440 Speaker 3: And also Donald Trump set Kevin Worshed down, I want 134 00:07:02,440 --> 00:07:03,640 Speaker 3: you to raise interest rates. 135 00:07:04,120 --> 00:07:05,719 Speaker 2: Actually it was like you, we want you to cut 136 00:07:05,760 --> 00:07:06,240 Speaker 2: interest rates. 137 00:07:06,240 --> 00:07:08,080 Speaker 4: And then Kevin Wassh got into the job and was like, 138 00:07:08,120 --> 00:07:10,960 Speaker 4: I really care about inflation. I feel a little bit 139 00:07:11,040 --> 00:07:14,840 Speaker 4: for Trump in that way. So yeah, so Worsh basically 140 00:07:15,280 --> 00:07:18,080 Speaker 4: came out and they held interest rates steady. But I 141 00:07:18,120 --> 00:07:21,679 Speaker 4: think what rattled It's part of what rattled the markets 142 00:07:21,720 --> 00:07:24,200 Speaker 4: this week, along with some of the mixed earnings, is 143 00:07:24,240 --> 00:07:27,640 Speaker 4: that there were they show you how people vote. There 144 00:07:27,640 --> 00:07:30,920 Speaker 4: are twelve voting members of the Federal Reserve Board, and 145 00:07:31,800 --> 00:07:35,720 Speaker 4: three people voted to raise interest rates. So this is 146 00:07:35,760 --> 00:07:38,920 Speaker 4: sort of maybe hinting that interest rates are going to 147 00:07:38,960 --> 00:07:39,440 Speaker 4: go up. 148 00:07:39,320 --> 00:07:42,040 Speaker 5: And just for not that's a lot for this board. 149 00:07:42,320 --> 00:07:45,040 Speaker 5: Three people who stand up, raise their hand and disagree 150 00:07:45,080 --> 00:07:45,600 Speaker 5: with the fetcher. 151 00:07:45,680 --> 00:07:46,360 Speaker 3: That's unusual. 152 00:07:46,680 --> 00:07:49,360 Speaker 4: That is yeah, they like used to like unanimity. So 153 00:07:49,760 --> 00:07:52,239 Speaker 4: I'm so curious, like, how did the market see this moment? 154 00:07:52,760 --> 00:07:58,600 Speaker 6: Well, they're angry, traders are are upset, and the reason is, well, 155 00:07:58,640 --> 00:08:02,800 Speaker 6: they're calling it a hawkish hold. That is the terminology 156 00:08:02,840 --> 00:08:06,480 Speaker 6: that they're using, which means that they are leaning toward 157 00:08:06,800 --> 00:08:12,040 Speaker 6: hiking rates and they're pointing toward raising rates. But they 158 00:08:12,120 --> 00:08:17,200 Speaker 6: held and to your point, Max, the idea that three 159 00:08:17,280 --> 00:08:22,080 Speaker 6: people disagreed. So on the prior FED you had one 160 00:08:22,640 --> 00:08:26,840 Speaker 6: member who was decidedly against Powell, so he was there 161 00:08:26,920 --> 00:08:30,520 Speaker 6: to descent, but there was one meeting where he dissented, 162 00:08:30,640 --> 00:08:33,880 Speaker 6: and then two people dissented the other way, and we 163 00:08:34,080 --> 00:08:37,280 Speaker 6: had headlines all over the place feding crisis or feding chaos. 164 00:08:37,600 --> 00:08:42,360 Speaker 6: That we're not getting feding chaos very muted opposite. Yes, 165 00:08:42,720 --> 00:08:44,880 Speaker 6: we're now having a good family. 166 00:08:44,720 --> 00:08:46,680 Speaker 2: Three respectful dissenting votes. Chaos. 167 00:08:47,400 --> 00:08:51,360 Speaker 6: Well, so before the next meeting, we're going to have 168 00:08:51,600 --> 00:08:55,440 Speaker 6: a couple of readings on inflation. We're going to have 169 00:08:55,559 --> 00:08:59,280 Speaker 6: the Fed's meeting in Jackson Hole where they'll be speaking, 170 00:08:59,800 --> 00:09:03,720 Speaker 6: and we should have, you know, a somewhat of a 171 00:09:03,720 --> 00:09:08,600 Speaker 6: better idea. But the concern among traders is that they're 172 00:09:08,640 --> 00:09:11,720 Speaker 6: not getting any guidance on where things are going. So 173 00:09:12,640 --> 00:09:15,880 Speaker 6: how do you come out of this meeting When they 174 00:09:15,920 --> 00:09:20,760 Speaker 6: are looking at trying to price any asset, whether it's stocks, bonds, 175 00:09:20,840 --> 00:09:24,760 Speaker 6: or whatever, they are looking at what is going to 176 00:09:24,760 --> 00:09:27,800 Speaker 6: happen in the future, where is where are things going 177 00:09:27,840 --> 00:09:32,280 Speaker 6: down the line, and you don't know, Like so in 178 00:09:32,600 --> 00:09:35,200 Speaker 6: when they were giving guidance, they you would have a 179 00:09:35,240 --> 00:09:37,560 Speaker 6: sense that like, okay, we're looking probably at two or 180 00:09:37,559 --> 00:09:41,200 Speaker 6: three hikes, or when inflation really got out of hand 181 00:09:41,440 --> 00:09:45,480 Speaker 6: in UH twenty twenty one, twenty twenty two, it was 182 00:09:45,480 --> 00:09:47,560 Speaker 6: like we're going to be going seventy five basis points 183 00:09:47,640 --> 00:09:49,040 Speaker 6: or you know, three twenty five. 184 00:09:49,000 --> 00:09:50,360 Speaker 4: They were like this is what we're doing this time, 185 00:09:50,400 --> 00:09:52,520 Speaker 4: this is what we're probably doing next time, and worsh 186 00:09:52,600 --> 00:09:53,240 Speaker 4: is like none of that. 187 00:09:53,559 --> 00:09:57,520 Speaker 6: Right, and the market like that. Speaking in normal English, 188 00:09:57,720 --> 00:09:59,920 Speaker 6: we need to communicate with the market frequently. 189 00:10:00,240 --> 00:10:02,360 Speaker 3: We need to kind of let people know so. 190 00:10:02,320 --> 00:10:06,080 Speaker 6: We don't have wild swings, so we don't get volatility, 191 00:10:06,120 --> 00:10:09,680 Speaker 6: which is where traders make money. However, when things break 192 00:10:09,920 --> 00:10:12,240 Speaker 6: the other way from what they were betting on, they 193 00:10:12,320 --> 00:10:13,080 Speaker 6: get really angry. 194 00:10:13,400 --> 00:10:17,160 Speaker 5: All right, So we're talking about the threat that you know, 195 00:10:17,240 --> 00:10:20,240 Speaker 5: interest rates go up and there's a cash shortage, and 196 00:10:20,679 --> 00:10:22,800 Speaker 5: all of a sudden, all these AI bets they're not 197 00:10:22,880 --> 00:10:26,319 Speaker 5: generating revenue and their companies have not enough money to 198 00:10:26,679 --> 00:10:29,400 Speaker 5: keep it going, and we have some kind of crisis, 199 00:10:29,440 --> 00:10:31,680 Speaker 5: either a stock market crash even an economic crist But 200 00:10:31,720 --> 00:10:35,440 Speaker 5: there's one thing that I think we may not be considering, Eric, 201 00:10:35,480 --> 00:10:39,000 Speaker 5: which is that if the AI happens, we will have 202 00:10:39,040 --> 00:10:41,600 Speaker 5: all the money we possibly need. And I bring this 203 00:10:41,679 --> 00:10:45,040 Speaker 5: up because Elon Musk, in an interview with the economist 204 00:10:45,160 --> 00:10:47,720 Speaker 5: I believe it was last week, said that by twenty 205 00:10:47,800 --> 00:10:50,679 Speaker 5: thirty six, that's like ten years from now, we will 206 00:10:50,720 --> 00:10:51,920 Speaker 5: have no need for money. 207 00:10:51,960 --> 00:10:54,280 Speaker 3: And you know what, Elon Musk. He's obviously a bit 208 00:10:54,320 --> 00:10:57,480 Speaker 3: of a Carnival barker. He's selling he's selling AI. 209 00:10:57,720 --> 00:11:01,920 Speaker 5: He has an incentive, perhaps to exaggerate the timeline here. 210 00:11:02,120 --> 00:11:04,000 Speaker 5: But you know who doesn't or who should not have 211 00:11:04,040 --> 00:11:07,320 Speaker 5: an incentive to do that. It's Scott Besson, the Treasury Secretary. 212 00:11:07,600 --> 00:11:09,520 Speaker 5: And I bring this up because in an interview with 213 00:11:09,559 --> 00:11:12,000 Speaker 5: Sean Hannity, let's just give a listen to Scott Besson's 214 00:11:12,040 --> 00:11:15,160 Speaker 5: take on the end of money purple question. 215 00:11:16,440 --> 00:11:19,240 Speaker 7: Elon Musk gave an interview to I believe to the economists, 216 00:11:19,520 --> 00:11:22,240 Speaker 7: and he said that in five to six years, it 217 00:11:22,280 --> 00:11:24,720 Speaker 7: will have five times besides the economy we have now. 218 00:11:24,760 --> 00:11:28,240 Speaker 7: And he talked about abundance. He talked about every American 219 00:11:28,280 --> 00:11:30,760 Speaker 7: having every need and there won't be even a need 220 00:11:30,800 --> 00:11:34,080 Speaker 7: to save, you know, for your retirement like we have 221 00:11:34,360 --> 00:11:37,360 Speaker 7: historically because of this quote abundance that he believes AI 222 00:11:37,440 --> 00:11:37,959 Speaker 7: will create. 223 00:11:38,000 --> 00:11:40,000 Speaker 8: Do you believe that I think I would change the 224 00:11:40,040 --> 00:11:44,960 Speaker 8: timeline that I've seen Elon speak for a long time, 225 00:11:45,080 --> 00:11:48,760 Speaker 8: and his record speaks for itself, both in terms as 226 00:11:48,800 --> 00:11:52,439 Speaker 8: an inventor, as a venture capitalist, as a great American. 227 00:11:52,760 --> 00:11:55,440 Speaker 8: But he's normally early. He's just so far ahead of 228 00:11:55,440 --> 00:11:57,840 Speaker 8: the curve. He sees things that no one else sees. 229 00:11:58,120 --> 00:12:01,600 Speaker 8: But I do think we are building this incredible economy 230 00:12:01,640 --> 00:12:04,960 Speaker 8: that we can't even imagine have sewn. Twenty five percent 231 00:12:05,000 --> 00:12:07,400 Speaker 8: of the jobs that exist today did not exist in 232 00:12:07,440 --> 00:12:08,040 Speaker 8: two thousand. 233 00:12:08,960 --> 00:12:10,000 Speaker 7: That's an amazing thing. 234 00:12:11,120 --> 00:12:14,360 Speaker 5: I love always like Elon's track record, great innovator, not 235 00:12:14,480 --> 00:12:15,719 Speaker 5: so good on timelines. 236 00:12:16,040 --> 00:12:20,080 Speaker 6: Well, so, look he's going to Mars. He's competing with NASA. 237 00:12:20,480 --> 00:12:24,400 Speaker 3: But do you think there is an inconsistency here? 238 00:12:24,920 --> 00:12:27,400 Speaker 5: You have all these guys who are saying we are 239 00:12:27,800 --> 00:12:33,439 Speaker 5: mirror years away from complete abundance. Meanwhile they're doing layoffs. 240 00:12:33,559 --> 00:12:36,480 Speaker 5: One of the things that I felt watching this whole 241 00:12:36,480 --> 00:12:38,960 Speaker 5: AI boom play out is that the people who are 242 00:12:39,000 --> 00:12:43,200 Speaker 5: participating in it don't really believe the things that they're saying, 243 00:12:43,200 --> 00:12:44,640 Speaker 5: because if they did believe the things they were saying, 244 00:12:44,640 --> 00:12:45,640 Speaker 5: they'd be doing different things. 245 00:12:45,920 --> 00:12:48,840 Speaker 6: I feel like that actually is the big difference between 246 00:12:49,080 --> 00:12:52,920 Speaker 6: this bubble and the Internet bubble, where people actually did 247 00:12:53,000 --> 00:12:55,600 Speaker 6: believe all of that stuff. They did believe that pets 248 00:12:55,600 --> 00:12:58,920 Speaker 6: dot Com was a technology company rather than a pet 249 00:12:58,920 --> 00:13:01,760 Speaker 6: store that was on. You didn't really understand where things were. 250 00:13:02,440 --> 00:13:07,840 Speaker 6: The point on all of this is technology advances the economy. 251 00:13:08,400 --> 00:13:12,959 Speaker 6: It dislocates workers, Automobiles put buggy whips out of business, 252 00:13:13,040 --> 00:13:15,440 Speaker 6: you know, like that that all of that's real. But 253 00:13:15,559 --> 00:13:19,040 Speaker 6: the idea that we are going to reinvent the economy, 254 00:13:19,120 --> 00:13:26,560 Speaker 6: the entire economy because of one area of technology, seems 255 00:13:26,760 --> 00:13:31,360 Speaker 6: quite hyperbolic. And to the bond markets perspective, they're expecting 256 00:13:31,360 --> 00:13:35,400 Speaker 6: the long bond five percent in thirty years, so they're 257 00:13:35,440 --> 00:13:37,960 Speaker 6: still expecting there to be money. 258 00:13:38,040 --> 00:13:40,880 Speaker 3: They're expecting to be paid in thirty years. 259 00:13:41,200 --> 00:13:43,800 Speaker 6: That so like, well, you know, we're done, but I mean. 260 00:13:43,800 --> 00:13:45,920 Speaker 2: This is in case money is still around. 261 00:13:47,640 --> 00:13:52,480 Speaker 3: Five percent. Sir, Eric, thanks for being here. Come back soon. 262 00:13:52,840 --> 00:13:53,120 Speaker 8: Thank you. 263 00:13:53,280 --> 00:14:06,760 Speaker 9: Eric Somacs Stacy tariffs, Wait, which tariffs? 264 00:14:06,960 --> 00:14:07,680 Speaker 3: Which tariffs? 265 00:14:07,920 --> 00:14:08,400 Speaker 2: Is right? 266 00:14:08,640 --> 00:14:11,840 Speaker 4: Because we have been through many iterations of tariffs since 267 00:14:11,880 --> 00:14:14,880 Speaker 4: Liberation Day. We are on I think tariffs three point zero. 268 00:14:14,880 --> 00:14:18,320 Speaker 4: Now the tariffs that were in place, the emergency tariffs 269 00:14:18,400 --> 00:14:20,400 Speaker 4: expired I think there was one hundred and eighty days 270 00:14:20,440 --> 00:14:24,000 Speaker 4: and now there is a new set of tariffs in place. 271 00:14:24,120 --> 00:14:24,320 Speaker 3: Yeah. 272 00:14:24,360 --> 00:14:28,160 Speaker 5: Well, what keeps happening is courts keep saying no, these 273 00:14:28,240 --> 00:14:31,920 Speaker 5: terror dice are not allowed. You need an Act of Congress, 274 00:14:32,240 --> 00:14:35,360 Speaker 5: and the Trump administration, making good on its promise, keeps 275 00:14:35,360 --> 00:14:38,720 Speaker 5: coming up with new tariffs to replace the old tariffs, 276 00:14:38,800 --> 00:14:42,240 Speaker 5: and then we do it all again. Meanwhile, no one 277 00:14:42,320 --> 00:14:45,280 Speaker 5: knows what anything costs. It's very confusing. The thing that 278 00:14:45,360 --> 00:14:49,000 Speaker 5: I've wondered, or that I've been wondering, is who are 279 00:14:49,040 --> 00:14:52,280 Speaker 5: these people who are like challenging that the businesses that 280 00:14:52,320 --> 00:14:55,360 Speaker 5: are that are challenging the Trump's tariffs, Like, what are 281 00:14:55,400 --> 00:14:56,440 Speaker 5: they going through? 282 00:14:56,800 --> 00:14:58,720 Speaker 2: I'm so glad that you asked this question. 283 00:14:59,120 --> 00:15:01,720 Speaker 4: Obviously, the tariff have been incredibly hard on all kinds 284 00:15:01,760 --> 00:15:05,560 Speaker 4: of businesses, especially small businesses, and we're very lucky to 285 00:15:05,600 --> 00:15:08,080 Speaker 4: have or Zohar with us. He's the co founder of 286 00:15:08,120 --> 00:15:10,680 Speaker 4: Burlap and Baryl, a single origin spice company. 287 00:15:10,760 --> 00:15:12,840 Speaker 10: Ori, welcome, Hey, great to be here. 288 00:15:13,480 --> 00:15:13,760 Speaker 8: Now. 289 00:15:14,320 --> 00:15:16,520 Speaker 4: We invited you on the show because in fact, there 290 00:15:16,520 --> 00:15:18,560 Speaker 4: are a couple of small businesses that are suing the 291 00:15:18,560 --> 00:15:21,800 Speaker 4: Trump administration over this latest round of tariffs, and one 292 00:15:21,840 --> 00:15:24,920 Speaker 4: of those businesses is your business is Burlap and Baryl. 293 00:15:25,160 --> 00:15:25,360 Speaker 10: Yeah. 294 00:15:25,440 --> 00:15:28,600 Speaker 11: This is actually our second lawsuit against the tariffs so far. So, 295 00:15:28,640 --> 00:15:30,400 Speaker 11: as you mentioned, there have been kind of three kind 296 00:15:30,400 --> 00:15:32,200 Speaker 11: of waves, three regimes of tariffs. 297 00:15:32,360 --> 00:15:33,600 Speaker 10: The first one the APA. 298 00:15:33,360 --> 00:15:37,240 Speaker 11: Tariffs where which got refunded, and we just got a 299 00:15:37,320 --> 00:15:39,200 Speaker 11: kind of refund for all the tariffs that we paid 300 00:15:39,400 --> 00:15:40,360 Speaker 11: plus interest. 301 00:15:40,160 --> 00:15:43,040 Speaker 5: Because those tuck it down or were the tariffs on 302 00:15:43,080 --> 00:15:45,280 Speaker 5: the big board right where where were the penguins, We're 303 00:15:45,280 --> 00:15:48,720 Speaker 5: gonna get tariffed and every That was the round one. 304 00:15:48,680 --> 00:15:51,240 Speaker 11: And the penguins got their tariffs back as long as 305 00:15:51,240 --> 00:15:51,760 Speaker 11: they filed. 306 00:15:52,640 --> 00:15:53,920 Speaker 12: You know, with. 307 00:15:53,880 --> 00:15:55,680 Speaker 2: Immigrant they're not great with paperwork. 308 00:15:56,920 --> 00:15:58,840 Speaker 11: But we got those tariffs back with interest, which was 309 00:15:58,880 --> 00:16:01,680 Speaker 11: just like a very expensive exercise for the American tariffs 310 00:16:01,680 --> 00:16:04,760 Speaker 11: and things that really increased prices and the government ended 311 00:16:04,800 --> 00:16:06,880 Speaker 11: up having to pay it all back with interest. The 312 00:16:06,960 --> 00:16:09,520 Speaker 11: second round came the same day that the Supreme Court 313 00:16:09,600 --> 00:16:11,800 Speaker 11: struck down the EPA tariffs, the Section one twenty two, 314 00:16:12,160 --> 00:16:14,160 Speaker 11: which was based on a nineteen seventy four kind of 315 00:16:14,200 --> 00:16:16,600 Speaker 11: bill around America moving off of the gold standard and 316 00:16:16,640 --> 00:16:18,920 Speaker 11: all that stuff said in some cases. 317 00:16:18,760 --> 00:16:21,080 Speaker 10: The president can push through tariffs. 318 00:16:21,240 --> 00:16:23,400 Speaker 11: We sued on that and we won at the Court 319 00:16:23,400 --> 00:16:26,080 Speaker 11: of International Trade, and now that's going through the appeal process. 320 00:16:26,360 --> 00:16:29,160 Speaker 11: And then as soon as these temporary six month tariffs expired, 321 00:16:29,480 --> 00:16:32,520 Speaker 11: the government introduced three oh one tariffs and so we 322 00:16:32,560 --> 00:16:35,960 Speaker 11: suit on those also, So we just were small business. 323 00:16:37,240 --> 00:16:39,320 Speaker 11: I don't know why it's up to small businesses to 324 00:16:39,400 --> 00:16:42,120 Speaker 11: kind of hold the government accountable with all the kind 325 00:16:42,120 --> 00:16:44,680 Speaker 11: of enterprise in America, but it was really important to 326 00:16:44,760 --> 00:16:46,640 Speaker 11: us to kind of take a stand against these tariffs 327 00:16:46,680 --> 00:16:48,520 Speaker 11: that didn't make any sense to us, made things more 328 00:16:48,560 --> 00:16:50,760 Speaker 11: expensive for American customers, and just seemed to not go 329 00:16:50,800 --> 00:16:53,280 Speaker 11: through any of the right channels for passing tariffs and 330 00:16:53,280 --> 00:16:55,560 Speaker 11: for actually managing economic policy here in the US. 331 00:16:55,880 --> 00:16:59,320 Speaker 4: So you are a spice company, I am imagining you 332 00:16:59,360 --> 00:17:02,440 Speaker 4: import a lot of what you sell. Can you maybe 333 00:17:02,560 --> 00:17:05,239 Speaker 4: run down some of the things that you sell and 334 00:17:05,280 --> 00:17:08,400 Speaker 4: how they've been affected by the tariffs and what that's 335 00:17:08,480 --> 00:17:09,199 Speaker 4: kind of meant for you. 336 00:17:09,440 --> 00:17:12,240 Speaker 11: Yeah, So we are a ten year old social enterprise, 337 00:17:12,480 --> 00:17:15,320 Speaker 11: Burlap and Barrel. We import spices directly from small holder 338 00:17:15,359 --> 00:17:17,919 Speaker 11: farmers all around the world. Our best selling one is 339 00:17:17,920 --> 00:17:21,000 Speaker 11: our royal cinnamon that comes from Vietnam, a true Vietnamese cinnamon. 340 00:17:21,160 --> 00:17:24,600 Speaker 11: But we import spices from about thirty different countries, all 341 00:17:24,640 --> 00:17:25,600 Speaker 11: based on where they grow. 342 00:17:25,680 --> 00:17:27,639 Speaker 10: So we have herbs the province from Provence. 343 00:17:28,040 --> 00:17:30,400 Speaker 11: We bring in really incredible garlic and onion powder from 344 00:17:30,400 --> 00:17:33,800 Speaker 11: Central Vietnam. It's kind of ancestral home and cuman from 345 00:17:33,840 --> 00:17:36,440 Speaker 11: Afghanistan and all over the world. So that's been our business, 346 00:17:36,480 --> 00:17:39,040 Speaker 11: is working with small holder farmers to bring in spices 347 00:17:39,080 --> 00:17:41,720 Speaker 11: directly from the farm and bring them to American home cooks. 348 00:17:42,119 --> 00:17:44,000 Speaker 11: We bring in about ten percent of our spices from 349 00:17:44,040 --> 00:17:46,760 Speaker 11: the US. We bring in really great Chileias from California, 350 00:17:47,000 --> 00:17:50,399 Speaker 11: actually salt from upstate New York wild ramps and all that. 351 00:17:50,440 --> 00:17:51,760 Speaker 10: So we do import. 352 00:17:51,680 --> 00:17:53,520 Speaker 11: Everything that we need to import, but we also buy 353 00:17:53,520 --> 00:17:56,680 Speaker 11: domestically everything that grows domestically, and yet we're still kind 354 00:17:56,720 --> 00:17:58,840 Speaker 11: of paying this broad ranges of tariffs on things that 355 00:17:58,880 --> 00:18:00,840 Speaker 11: there really is no domestic industry here for. 356 00:18:01,280 --> 00:18:02,960 Speaker 4: Can you talk a little bit about the cost of 357 00:18:03,000 --> 00:18:06,440 Speaker 4: the tariffs for your business since Liberation Day? 358 00:18:06,440 --> 00:18:07,520 Speaker 2: Like, what does this cost you? 359 00:18:08,040 --> 00:18:10,240 Speaker 11: Yeah, so we've paid hundreds of thousands of dollars in 360 00:18:10,280 --> 00:18:14,080 Speaker 11: tariffs so far, and it's on things that don't grow 361 00:18:14,080 --> 00:18:16,199 Speaker 11: in the US. So initially tariffs we were paying on 362 00:18:16,240 --> 00:18:18,560 Speaker 11: cinnamon and black pepper corns, both of which don't grow 363 00:18:18,560 --> 00:18:21,200 Speaker 11: in the US. Since then, there's been about four hundred 364 00:18:21,240 --> 00:18:23,720 Speaker 11: and seventy one I believe carve outs of the tariff 365 00:18:23,840 --> 00:18:26,639 Speaker 11: which just shows you this is kind of a shoddy framework. 366 00:18:27,560 --> 00:18:29,440 Speaker 3: Okay, right, it's for all this stuff. 367 00:18:29,480 --> 00:18:31,040 Speaker 11: So now we don't pay tariffs on cinnamon and black 368 00:18:31,040 --> 00:18:33,560 Speaker 11: pepper anymore, but we still do pay on herbs like 369 00:18:33,600 --> 00:18:36,240 Speaker 11: herbs of province, which you know, yes, can do herbs 370 00:18:36,240 --> 00:18:39,159 Speaker 11: grow in America? Absolutely? Can you get herbs of province 371 00:18:39,200 --> 00:18:41,919 Speaker 11: in America? Not exactly. We bring in our Vietnamese cinnamon 372 00:18:41,960 --> 00:18:45,440 Speaker 11: from Vietnam, we bring in garlic from also from Vietnam, 373 00:18:45,480 --> 00:18:48,760 Speaker 11: and we do bring some stuff in domestically, but the 374 00:18:48,760 --> 00:18:51,239 Speaker 11: tariffs are still this kind of very broad instrument that 375 00:18:51,280 --> 00:18:53,840 Speaker 11: are kind of increasing costs for us. And as a 376 00:18:53,840 --> 00:18:56,560 Speaker 11: small business, we can't bring in herbs of province not 377 00:18:56,600 --> 00:18:58,679 Speaker 11: from Provence, we can't bring in all these spices not 378 00:18:58,720 --> 00:19:01,040 Speaker 11: from their kind of origin, and so we find ourselves 379 00:19:01,080 --> 00:19:03,520 Speaker 11: in this kind of ironic, kind of tough spot where 380 00:19:03,960 --> 00:19:06,400 Speaker 11: the only place where we can cut costs is domestically. 381 00:19:06,640 --> 00:19:07,639 Speaker 10: How can we kind of save. 382 00:19:07,560 --> 00:19:10,440 Speaker 11: Money on our innovation, on our hiring, on our shipping speed, 383 00:19:10,480 --> 00:19:13,480 Speaker 11: on our corrigate costs for our boxes. So it's had 384 00:19:13,480 --> 00:19:15,919 Speaker 11: this kind of backwards impact on our business, has been 385 00:19:15,960 --> 00:19:19,040 Speaker 11: pulling investment domestically while We're still kind of doubling down 386 00:19:19,160 --> 00:19:22,080 Speaker 11: on our partner Farmers Abroad because that's our only option. 387 00:19:22,760 --> 00:19:25,640 Speaker 3: Or how do you wind up being the one who sues? 388 00:19:25,720 --> 00:19:30,119 Speaker 5: Like are there groups that are fighting these tariffs that 389 00:19:30,200 --> 00:19:32,960 Speaker 5: are going out looking for plaintifs or like did you 390 00:19:33,280 --> 00:19:34,119 Speaker 5: go seek somebody? 391 00:19:34,119 --> 00:19:34,199 Speaker 12: Like? 392 00:19:34,200 --> 00:19:35,960 Speaker 3: How does this? How does this kind of thing actually happen? 393 00:19:36,320 --> 00:19:38,399 Speaker 11: So that's a great question. We have a legal partner 394 00:19:38,440 --> 00:19:41,240 Speaker 11: here called the Liberty Justice Center. They're the ones that 395 00:19:41,240 --> 00:19:43,680 Speaker 11: are actually bringing the legal might for this and also 396 00:19:43,720 --> 00:19:46,000 Speaker 11: footing the bill because you know, taking a court, a 397 00:19:46,040 --> 00:19:47,560 Speaker 11: case of the Supreme Court, as they did with the 398 00:19:47,600 --> 00:19:50,440 Speaker 11: AIPA tariffs in one is literally millions of dollars in 399 00:19:50,480 --> 00:19:53,199 Speaker 11: litigation for that case, we actually saw, we. 400 00:19:53,440 --> 00:19:54,000 Speaker 10: Looked at suing. 401 00:19:54,000 --> 00:19:55,440 Speaker 11: We said, we don't know what we're doing here, we're 402 00:19:55,440 --> 00:19:57,920 Speaker 11: not legal experts. We ended up filing an amaricus brief, 403 00:19:57,920 --> 00:20:00,159 Speaker 11: a kind of friend of the court document to so 404 00:20:00,200 --> 00:20:03,200 Speaker 11: Liberty Justice Center said, who is this company and what's 405 00:20:03,240 --> 00:20:05,160 Speaker 11: their deal? And so we got in touch with them, 406 00:20:05,200 --> 00:20:07,640 Speaker 11: and then when they were when the one twenty two 407 00:20:07,640 --> 00:20:09,480 Speaker 11: tariffs came out, they said, hey, are you willing to 408 00:20:09,480 --> 00:20:11,560 Speaker 11: actually step up and be the plaintiff here and then 409 00:20:11,560 --> 00:20:13,320 Speaker 11: again for the three oh one tariffs. So we found 410 00:20:13,320 --> 00:20:15,439 Speaker 11: this really lovely partnership us being able to do what 411 00:20:15,480 --> 00:20:17,679 Speaker 11: we do best, which is being a small business that 412 00:20:17,840 --> 00:20:20,280 Speaker 11: kind of is showing that the impact of the tariffs 413 00:20:20,320 --> 00:20:23,280 Speaker 11: on everyday Americans and kind of talking about the legal 414 00:20:23,320 --> 00:20:25,120 Speaker 11: frameworks and the hoops that we have to jump through, 415 00:20:25,280 --> 00:20:27,600 Speaker 11: and then with their kind of legal expertise and might 416 00:20:27,720 --> 00:20:30,240 Speaker 11: being able to actually litigate this case properly to the 417 00:20:30,280 --> 00:20:32,800 Speaker 11: highest extent, which we have no business doing ourselves. 418 00:20:33,200 --> 00:20:36,480 Speaker 2: Why did you decide to do this? Because this does 419 00:20:36,520 --> 00:20:38,960 Speaker 2: take time and energy away. I think you're you're quite 420 00:20:38,960 --> 00:20:39,880 Speaker 2: a small business. 421 00:20:40,040 --> 00:20:43,600 Speaker 4: You have a lot on your plate, Like why devote 422 00:20:43,680 --> 00:20:45,840 Speaker 4: some time and energy to lawsuits? 423 00:20:46,440 --> 00:20:49,400 Speaker 11: So during Liberation Day, we made kind of two promises 424 00:20:49,440 --> 00:20:51,200 Speaker 11: to our customers. We said, we're not going to pass 425 00:20:51,240 --> 00:20:53,439 Speaker 11: the tariff costs onto our partner farmers, and we're not 426 00:20:53,480 --> 00:20:56,040 Speaker 11: going to increase cost to Americans. Costs are already high, 427 00:20:56,080 --> 00:20:58,840 Speaker 11: inflation is already out of control. And we got a 428 00:20:58,840 --> 00:21:01,520 Speaker 11: really strong reception for that. People were really looking for 429 00:21:01,600 --> 00:21:03,560 Speaker 11: somebody to step into this void. 430 00:21:03,760 --> 00:21:05,879 Speaker 10: And make a statement. Everybody else has been kind of 431 00:21:05,960 --> 00:21:06,800 Speaker 10: worried scared. 432 00:21:06,840 --> 00:21:09,200 Speaker 11: There have been you know, boards of directors and public 433 00:21:09,240 --> 00:21:11,280 Speaker 11: shareholders and all of that stuff. There's been a really 434 00:21:11,359 --> 00:21:13,919 Speaker 11: big void, and I think people are worried about retaliation 435 00:21:14,320 --> 00:21:16,920 Speaker 11: and are worried about their businesses getting hurt. We saw 436 00:21:16,960 --> 00:21:19,080 Speaker 11: this as as the right moment, and internally we kind 437 00:21:19,080 --> 00:21:21,240 Speaker 11: of discussed this as a kind of like Patagonia moment 438 00:21:21,440 --> 00:21:23,400 Speaker 11: where we've seen a lot of other companies that really 439 00:21:23,440 --> 00:21:27,200 Speaker 11: inspired by use legal action to kind of shape shape policy, 440 00:21:27,440 --> 00:21:29,440 Speaker 11: not just for themselves, like we're not going to get, 441 00:21:29,600 --> 00:21:31,560 Speaker 11: you know, any punitive fees from this, We're going to 442 00:21:31,640 --> 00:21:32,240 Speaker 11: change the law. 443 00:21:32,440 --> 00:21:34,280 Speaker 10: And so this is something we've been really proud of. 444 00:21:34,440 --> 00:21:37,040 Speaker 11: We got the win on the one twenty two tariffs 445 00:21:37,040 --> 00:21:39,600 Speaker 11: at the Court of International Trade, and that only emboldened 446 00:21:39,640 --> 00:21:41,520 Speaker 11: us to bring a second lawsuit once the three oh 447 00:21:41,560 --> 00:21:43,800 Speaker 11: one tariffs were were kind of introduced, or you. 448 00:21:43,760 --> 00:21:46,040 Speaker 5: Brought up prospect of retaliation as maybe one of the 449 00:21:46,040 --> 00:21:49,600 Speaker 5: reasons why the business community in general kind of went 450 00:21:49,600 --> 00:21:51,720 Speaker 5: along with this without a lot of without speaking up 451 00:21:51,760 --> 00:21:53,560 Speaker 5: too much. You know, the fear is if you if 452 00:21:53,560 --> 00:21:55,840 Speaker 5: you're a big company, if you're an investor, maybe you're 453 00:21:55,840 --> 00:21:59,600 Speaker 5: attempting to a merger or something like that, and you're worried, like, oh, 454 00:21:59,800 --> 00:22:02,879 Speaker 5: is is when the FTC goes to evaluate this merger, 455 00:22:02,920 --> 00:22:05,240 Speaker 5: are they gonna get a call from somebody and you 456 00:22:05,280 --> 00:22:07,920 Speaker 5: know whatever, some kind of some somehow this will hurt 457 00:22:07,920 --> 00:22:10,880 Speaker 5: some other part of their business. There's this other area 458 00:22:11,000 --> 00:22:13,520 Speaker 5: of retaliation that I'm wondering about and wondering if you 459 00:22:13,600 --> 00:22:17,879 Speaker 5: thought about, which is kind of consumer backlash to fighting 460 00:22:17,920 --> 00:22:20,960 Speaker 5: the Trump administration. You know, we saw especially towards the 461 00:22:21,040 --> 00:22:23,200 Speaker 5: end of the Biden administration and then even in the 462 00:22:23,240 --> 00:22:27,040 Speaker 5: beginning of the Trump administration. Trump has power to direct 463 00:22:27,440 --> 00:22:29,000 Speaker 5: consumer rage and so on. 464 00:22:29,040 --> 00:22:30,520 Speaker 3: He's gone after the NFL. 465 00:22:30,800 --> 00:22:34,719 Speaker 5: You know, he will periodically sort of truth social about 466 00:22:34,800 --> 00:22:37,840 Speaker 5: some company. And I think a lot of big companies, 467 00:22:37,840 --> 00:22:41,000 Speaker 5: like big consumer facing companies, really live in fear of 468 00:22:41,040 --> 00:22:45,280 Speaker 5: that of Trump going out and saying this company is bad. 469 00:22:45,400 --> 00:22:48,639 Speaker 5: They are woke, and and then you know, half of America, 470 00:22:48,680 --> 00:22:51,720 Speaker 5: the MAGA part of America, will basically boycott them and 471 00:22:51,760 --> 00:22:53,639 Speaker 5: will have you know what happened to bud Light, And 472 00:22:53,640 --> 00:22:56,639 Speaker 5: we saw this happen a bunch of times over the 473 00:22:56,680 --> 00:22:59,879 Speaker 5: last I don't know, five years or so. What how 474 00:23:00,000 --> 00:23:02,480 Speaker 5: what did you think about the consumer reaction to that. 475 00:23:03,119 --> 00:23:05,600 Speaker 11: So if that leads us into a true social post like, 476 00:23:05,680 --> 00:23:08,080 Speaker 11: welcome it. We're happy to have the conversation. We're a 477 00:23:08,160 --> 00:23:11,280 Speaker 11: crunchy liberal business, you know, just for me and my 478 00:23:11,320 --> 00:23:13,840 Speaker 11: co founders, like personal beliefs. This is really in across 479 00:23:13,880 --> 00:23:16,479 Speaker 11: the aisle issue that we kind of both align on, 480 00:23:16,520 --> 00:23:18,480 Speaker 11: and so it's been also really lovely to find people 481 00:23:18,520 --> 00:23:21,560 Speaker 11: that the head of the Liberty Justice Center voted for 482 00:23:21,600 --> 00:23:22,680 Speaker 11: Trump three times. 483 00:23:22,880 --> 00:23:24,560 Speaker 10: We voted for Trump zero times. 484 00:23:24,640 --> 00:23:26,600 Speaker 11: But we both kind of agree on this issue that 485 00:23:26,720 --> 00:23:28,840 Speaker 11: we're that this is worth fighting for and worth kind 486 00:23:28,840 --> 00:23:31,080 Speaker 11: of standing up for on behalf of small businesses and 487 00:23:31,119 --> 00:23:32,080 Speaker 11: American consumers. 488 00:23:32,840 --> 00:23:36,080 Speaker 2: Have you heard from your customers about this at all? 489 00:23:36,720 --> 00:23:39,840 Speaker 11: We have gotten a lot of kudoses from other folks 490 00:23:39,880 --> 00:23:42,040 Speaker 11: in the industry because there's so many other small food 491 00:23:42,119 --> 00:23:45,040 Speaker 11: companies that are doing this, because businesses are really struggling 492 00:23:45,040 --> 00:23:47,200 Speaker 11: with this, and there's some existential kind of questions for 493 00:23:47,240 --> 00:23:49,880 Speaker 11: a lot of businesses that are being caused by these tariffs. 494 00:23:50,240 --> 00:23:52,480 Speaker 11: From our customers, we've also gotten a lot of kudoses 495 00:23:52,480 --> 00:23:55,280 Speaker 11: and wins. We've gotten also some messages saying, hey, keep 496 00:23:55,320 --> 00:23:56,680 Speaker 11: politics out of my spices. 497 00:23:56,720 --> 00:23:57,720 Speaker 10: I don't care about. 498 00:23:57,440 --> 00:24:00,000 Speaker 11: This and we've tried really hard to be like, we're 499 00:24:00,080 --> 00:24:03,240 Speaker 11: where if you love America and want to buy American spices, 500 00:24:03,440 --> 00:24:05,600 Speaker 11: guess what. We work with a bunch of American spice 501 00:24:05,640 --> 00:24:08,000 Speaker 11: farmers and here are there're spices you can do that. 502 00:24:08,359 --> 00:24:10,560 Speaker 11: So we're really trying to not kind of split the 503 00:24:10,600 --> 00:24:12,800 Speaker 11: audience or go one way or the other. We're trying 504 00:24:12,800 --> 00:24:15,600 Speaker 11: to say, what's going to help Americans eat eat well, 505 00:24:15,920 --> 00:24:17,960 Speaker 11: bring in greens from all over the world. And by 506 00:24:18,000 --> 00:24:21,080 Speaker 11: the way, spices love tropical and subtropical environments. We have 507 00:24:21,200 --> 00:24:23,120 Speaker 11: so many amazing things that we can grow in America. 508 00:24:23,359 --> 00:24:24,879 Speaker 11: Spices are not one of those things. 509 00:24:26,080 --> 00:24:28,080 Speaker 2: Thank you so much for talking with us or and 510 00:24:28,240 --> 00:24:28,680 Speaker 2: good luck. 511 00:24:28,720 --> 00:24:30,919 Speaker 4: Please we hope you can come back and talk with 512 00:24:30,960 --> 00:24:32,160 Speaker 4: us again about how things are going. 513 00:24:32,520 --> 00:24:32,800 Speaker 10: Thank you. 514 00:24:32,840 --> 00:24:42,800 Speaker 11: I'm looking forward to it. 515 00:24:42,880 --> 00:24:46,240 Speaker 5: Stacey, it's been a while, but it's that time for 516 00:24:46,320 --> 00:24:49,680 Speaker 5: our recurring segment this week in prediction markets. 517 00:24:49,800 --> 00:24:50,720 Speaker 3: I know you love the sting. 518 00:24:50,920 --> 00:24:52,639 Speaker 2: I've been waiting for the sting. 519 00:24:58,720 --> 00:25:00,520 Speaker 5: But you know what, We've got a lot to talk 520 00:25:00,560 --> 00:25:04,440 Speaker 5: about because Calshe is the big prediction market company, is 521 00:25:04,440 --> 00:25:07,919 Speaker 5: fighting with Wisconsin. There's also just so much news around 522 00:25:07,920 --> 00:25:11,280 Speaker 5: this space and politics but before we even get there, 523 00:25:11,520 --> 00:25:14,800 Speaker 5: we often go out into the world and ask people 524 00:25:15,119 --> 00:25:19,240 Speaker 5: how these kind of abstract economic concepts we've been talking 525 00:25:19,240 --> 00:25:21,320 Speaker 5: about on this show affect them in their real life. 526 00:25:21,359 --> 00:25:24,240 Speaker 3: We hadn't actually done that for prediction markets yet. 527 00:25:24,840 --> 00:25:26,440 Speaker 2: Yes, well, Jasmine JT. 528 00:25:26,600 --> 00:25:30,119 Speaker 4: Green remedy that you went out onto the mean streets 529 00:25:30,119 --> 00:25:33,120 Speaker 4: of New York and talk to people about what their 530 00:25:33,160 --> 00:25:36,760 Speaker 4: relationship is with call she polymarket and all of the 531 00:25:36,800 --> 00:25:37,920 Speaker 4: betting markets of the world. 532 00:25:38,520 --> 00:25:42,800 Speaker 13: Do you use prediction markets? Why do you use them? 533 00:25:43,560 --> 00:25:48,000 Speaker 14: Are more well versed in pop culture than I am 534 00:25:48,119 --> 00:25:51,320 Speaker 14: in like terms of like crypto and finance. Betting on 535 00:25:51,440 --> 00:25:55,159 Speaker 14: who's gonna win Love Island is more plausible for me 536 00:25:55,400 --> 00:25:58,640 Speaker 14: because it's easier for me to analyze. 537 00:25:59,119 --> 00:26:03,280 Speaker 13: So I'm curious, like, what are your thoughts on prediction 538 00:26:03,400 --> 00:26:08,080 Speaker 13: markets entering in the election process. 539 00:26:08,119 --> 00:26:12,040 Speaker 14: Definitely something that is like a cannon worms we do 540 00:26:12,040 --> 00:26:15,080 Speaker 14: not want to open. Not only will it influence people 541 00:26:15,119 --> 00:26:18,480 Speaker 14: on who's more popular during an election, it can sway 542 00:26:18,600 --> 00:26:21,840 Speaker 14: votes for sure, especially if you have money on the line. 543 00:26:22,119 --> 00:26:22,960 Speaker 2: People would just. 544 00:26:23,280 --> 00:26:26,119 Speaker 10: Not be thinking for themselves. 545 00:26:25,600 --> 00:26:27,880 Speaker 14: On coffee you or not putting your bid on who 546 00:26:27,880 --> 00:26:30,680 Speaker 14: you want to win. It's on who you think will win. 547 00:26:31,040 --> 00:26:34,200 Speaker 15: People who maybe would have the money to be gambling, 548 00:26:34,520 --> 00:26:38,640 Speaker 15: are sometimes people who don't feel as inclined to vote anyway. 549 00:26:38,920 --> 00:26:43,600 Speaker 15: Maybe in a political context, I think that it would 550 00:26:43,640 --> 00:26:46,760 Speaker 15: discourage voting, which I think is really important and we 551 00:26:46,800 --> 00:26:49,160 Speaker 15: should be encouraging that in any way. 552 00:26:49,160 --> 00:26:52,280 Speaker 12: Shape and form a gambling market for politicians more than 553 00:26:52,280 --> 00:26:56,840 Speaker 12: we already have seems probably part like problematic and would 554 00:26:56,960 --> 00:27:00,680 Speaker 12: discourage working class people from participating. 555 00:27:00,200 --> 00:27:02,560 Speaker 2: And voting more than maybe they already feel. 556 00:27:03,080 --> 00:27:05,119 Speaker 1: And I just see the ads on the subway and 557 00:27:05,160 --> 00:27:05,760 Speaker 1: on YouTube. 558 00:27:06,000 --> 00:27:08,120 Speaker 10: I don't use them. I don't gamble at all. 559 00:27:08,240 --> 00:27:10,239 Speaker 1: That seems like it would open the space for some 560 00:27:10,280 --> 00:27:13,399 Speaker 1: sort of corruption. What's it called in boxing when somebody 561 00:27:13,400 --> 00:27:15,680 Speaker 1: takes a fall? I mean, it seems like you could 562 00:27:15,760 --> 00:27:19,320 Speaker 1: you could set up something like that for an election, right. 563 00:27:20,359 --> 00:27:23,199 Speaker 5: You know? My favorite boxing term is is like is 564 00:27:23,280 --> 00:27:28,000 Speaker 5: tomato can, which is like the person who if you're like, 565 00:27:28,080 --> 00:27:30,560 Speaker 5: if you want a boxer to win about and beat 566 00:27:30,600 --> 00:27:33,199 Speaker 5: somebody up, you get a tomato can to get beat up. 567 00:27:34,000 --> 00:27:37,920 Speaker 5: Oh sorry, okay, apropos of nothing. I feel like the 568 00:27:38,560 --> 00:27:40,720 Speaker 5: people that JAS been talked to were in on this. 569 00:27:40,880 --> 00:27:44,919 Speaker 5: They were all over the main point of this segment, 570 00:27:44,960 --> 00:27:48,920 Speaker 5: which is all about the ways in which prediction markets 571 00:27:49,040 --> 00:27:53,479 Speaker 5: might affect the political system, might even manipulate the political system. 572 00:27:53,760 --> 00:27:55,960 Speaker 5: And we have a great person to talk to about this, 573 00:27:56,359 --> 00:28:00,359 Speaker 5: Bloomberg reporter Denisa Setkova. She is here right now now 574 00:28:00,760 --> 00:28:04,320 Speaker 5: she covers prediction markets here here with us. Denisa, great 575 00:28:04,359 --> 00:28:04,760 Speaker 5: to have. 576 00:28:04,640 --> 00:28:05,800 Speaker 16: You, Thanks for having me. 577 00:28:05,960 --> 00:28:08,600 Speaker 17: So what happened is wiscons in Wisconsin, is that the 578 00:28:08,680 --> 00:28:13,160 Speaker 17: Wisconsin election officials warren voters in the state that they 579 00:28:13,200 --> 00:28:16,280 Speaker 17: cannot bet on prediction market on the same vote they 580 00:28:16,520 --> 00:28:18,600 Speaker 17: cast their bout on and that made this. 581 00:28:18,720 --> 00:28:19,720 Speaker 16: Qualify the vote. 582 00:28:19,920 --> 00:28:23,800 Speaker 17: So obviously that raised a lot of issues. So we 583 00:28:23,840 --> 00:28:25,840 Speaker 17: have one of the biggest platforms Kushi. They have a 584 00:28:25,960 --> 00:28:29,159 Speaker 17: very strong social media presence. They're really advocating for a 585 00:28:29,160 --> 00:28:32,359 Speaker 17: lot of topics. They took on social media saying that 586 00:28:32,480 --> 00:28:36,239 Speaker 17: this is not good for voters and this is some 587 00:28:36,320 --> 00:28:40,880 Speaker 17: kind of voter suppression. The reason behind with Wisconsin election 588 00:28:40,920 --> 00:28:43,480 Speaker 17: officials for pretty simple. They were like, there is this woe. 589 00:28:43,760 --> 00:28:46,080 Speaker 17: It's been written one hundred and seventy years ago. 590 00:28:46,240 --> 00:28:49,880 Speaker 5: Denis is referring to an eighteen forty nine law basically 591 00:28:49,920 --> 00:28:51,760 Speaker 5: says a bunch of things of who is an eligible 592 00:28:51,760 --> 00:28:54,680 Speaker 5: to vote. Felons are not eligible to vote in Wisconsin. 593 00:28:54,800 --> 00:28:57,840 Speaker 5: You got to be eighteen of voting Wisconsin. But of 594 00:28:57,920 --> 00:29:01,120 Speaker 5: the one of the eighteen forty nine provisions of this 595 00:29:01,400 --> 00:29:03,800 Speaker 5: is that if you have placed a bet on the 596 00:29:03,880 --> 00:29:05,600 Speaker 5: vote that you are going to cast, you are not 597 00:29:05,600 --> 00:29:06,160 Speaker 5: allowed to vote. 598 00:29:06,200 --> 00:29:07,440 Speaker 3: That's like a conflict of interest. 599 00:29:07,680 --> 00:29:12,120 Speaker 5: And Wisconsin basically just put out an advisory saying, hey, guys, 600 00:29:12,160 --> 00:29:15,160 Speaker 5: we've seen a lot of ads for this thing called 601 00:29:15,400 --> 00:29:16,040 Speaker 5: like these. 602 00:29:15,880 --> 00:29:17,120 Speaker 3: Things called prediction markets. 603 00:29:17,160 --> 00:29:20,160 Speaker 5: Just a little reminder, do not bet on the Wisconsin 604 00:29:20,200 --> 00:29:22,960 Speaker 5: election if you hope to vote in Wisconsin. And Calshi 605 00:29:23,040 --> 00:29:25,920 Speaker 5: has basically gone to the mats. What are they saying 606 00:29:25,920 --> 00:29:27,400 Speaker 5: you need some election suppression. 607 00:29:27,520 --> 00:29:30,720 Speaker 17: Yeah, they're saying voter suppression. They're saying that your vote 608 00:29:30,760 --> 00:29:35,280 Speaker 17: might be disqualified. What their stance is, First, election prediction 609 00:29:35,360 --> 00:29:39,320 Speaker 17: markets and election bets are regulated by the federal government 610 00:29:39,440 --> 00:29:41,640 Speaker 17: is in their case, the CFTC. So they're like, it's 611 00:29:41,680 --> 00:29:44,400 Speaker 17: not up to state's decide. There is a massive lego 612 00:29:44,440 --> 00:29:47,280 Speaker 17: betto about that. It's mostly about sports. We can talk 613 00:29:47,320 --> 00:29:49,760 Speaker 17: about it for hours. But that's their first thing. The 614 00:29:49,800 --> 00:29:52,880 Speaker 17: second thing they say is like, oh, actually, young voters 615 00:29:52,920 --> 00:29:55,240 Speaker 17: placing bets on prediction markets is good for us. It 616 00:29:55,280 --> 00:29:56,760 Speaker 17: means that a lot of those people who are maybe 617 00:29:56,760 --> 00:29:59,680 Speaker 17: not interested in elections will be a lot more interested now, 618 00:30:00,040 --> 00:30:03,800 Speaker 17: and we are encouraging voter turnover. You can judge whether 619 00:30:03,840 --> 00:30:06,520 Speaker 17: this is true or not, but this is the case. 620 00:30:06,560 --> 00:30:09,320 Speaker 17: They're federally regulated and they're doing nothing bad because they're 621 00:30:09,360 --> 00:30:11,200 Speaker 17: encouraging young people to care about politics. 622 00:30:11,840 --> 00:30:15,600 Speaker 4: Is there evidence that having prediction markets involved in an 623 00:30:15,640 --> 00:30:17,920 Speaker 4: election does mess with the election? I mean, we've talked 624 00:30:17,960 --> 00:30:20,920 Speaker 4: about a lot on the show, as with sports, with 625 00:30:21,120 --> 00:30:24,040 Speaker 4: athletes maybe doing certain things or not doing certain things 626 00:30:24,040 --> 00:30:26,520 Speaker 4: because they had money on the line. Is there evidence 627 00:30:26,560 --> 00:30:29,880 Speaker 4: that could possibly enter into the equation with an election? 628 00:30:30,240 --> 00:30:32,880 Speaker 17: I mean, majority of the cases we've seen a prediction 629 00:30:32,960 --> 00:30:36,160 Speaker 17: market that have been connected with elections, that can be 630 00:30:36,160 --> 00:30:38,760 Speaker 17: connected with manipulation, that can be connected with desider trading 631 00:30:38,760 --> 00:30:42,480 Speaker 17: have been all about politics. We saw obviously Trump's teleprompter 632 00:30:42,880 --> 00:30:45,479 Speaker 17: person being blamed for insider trading. 633 00:30:45,600 --> 00:30:48,520 Speaker 16: This case is currently being under jurisdiction. 634 00:30:48,600 --> 00:30:51,480 Speaker 17: But then we also have the famous case of the 635 00:30:51,560 --> 00:30:56,000 Speaker 17: US soldier betting on Maduro's ulster. We have cause specifically 636 00:30:56,040 --> 00:31:00,000 Speaker 17: banning political candidates for betting on their races. 637 00:31:00,040 --> 00:31:02,320 Speaker 16: There have been three people. It was kind of simple cases. 638 00:31:02,400 --> 00:31:05,360 Speaker 17: You know, I bet five hundred doors on my campaign, 639 00:31:05,480 --> 00:31:07,760 Speaker 17: I filmed the TikTok, and then eventually you get banned. 640 00:31:07,960 --> 00:31:10,080 Speaker 17: We also have a great story in the Bloomberg terminal 641 00:31:10,280 --> 00:31:15,360 Speaker 17: about Romania how one trader placed one million in the 642 00:31:15,400 --> 00:31:18,800 Speaker 17: span of six days over one presidential candidate and really 643 00:31:18,840 --> 00:31:23,200 Speaker 17: boosted their olds. So clearly in smaller markets are less liquid, 644 00:31:23,880 --> 00:31:26,840 Speaker 17: we have seen the case that indeed people place big 645 00:31:26,880 --> 00:31:29,960 Speaker 17: bets that really change the oats. And then that obviously 646 00:31:30,120 --> 00:31:33,000 Speaker 17: follows a lot of social media news and other coverage 647 00:31:33,040 --> 00:31:34,160 Speaker 17: that can influence the vote. 648 00:31:34,240 --> 00:31:36,920 Speaker 5: Yeah, that story also on of course Bloomberg dot Com 649 00:31:36,920 --> 00:31:40,080 Speaker 5: by Liam Vaughan, super interesting, also, Stacy, not just this 650 00:31:40,160 --> 00:31:43,840 Speaker 5: Romanian election that Denitza is talking about, but the governor's 651 00:31:43,920 --> 00:31:47,640 Speaker 5: race in California. There were suggestions that you know, sort 652 00:31:47,640 --> 00:31:51,080 Speaker 5: of one of the fringier candidates that some ally or 653 00:31:51,080 --> 00:31:54,240 Speaker 5: somebody looking to boost one of these candidates had placed 654 00:31:54,360 --> 00:31:56,480 Speaker 5: you know, tens of thousands of dollars worth of bets 655 00:31:56,560 --> 00:31:59,880 Speaker 5: as like instead of like buying advertising. To answer your question, 656 00:32:00,000 --> 00:32:02,760 Speaker 5: I think the answer is, yeah, it could have an impact. 657 00:32:02,800 --> 00:32:05,120 Speaker 5: I think there's some question about like how big that 658 00:32:05,200 --> 00:32:06,000 Speaker 5: impact would be. 659 00:32:06,280 --> 00:32:08,720 Speaker 4: Well, I do remember this conversation coming up, not around 660 00:32:08,840 --> 00:32:12,320 Speaker 4: prediction markets, but around polling and polling results in Trump 661 00:32:12,360 --> 00:32:16,360 Speaker 4: won when the polls showed Hillary Clinton winning by such 662 00:32:16,360 --> 00:32:18,400 Speaker 4: a huge margin, and there was a lot of speculation 663 00:32:18,440 --> 00:32:20,200 Speaker 4: that maybe voter stayed home because of that or it 664 00:32:20,200 --> 00:32:23,680 Speaker 4: did affect voter actions. I remember thinking a lot about 665 00:32:23,680 --> 00:32:26,880 Speaker 4: that and how influential polls are, and it does make sense, 666 00:32:26,960 --> 00:32:31,040 Speaker 4: especially in smaller elections, if you could sway the polls 667 00:32:31,160 --> 00:32:34,640 Speaker 4: enough to get reported on that, you could potentially at 668 00:32:34,720 --> 00:32:37,720 Speaker 4: least get people talking about you, and you know in politics, 669 00:32:37,720 --> 00:32:40,200 Speaker 4: that can make a big difference for sure. 670 00:32:40,200 --> 00:32:42,920 Speaker 17: And those platforms are everywhere, like you can see it 671 00:32:42,960 --> 00:32:44,440 Speaker 17: on the subway. It was a big thing in the 672 00:32:44,440 --> 00:32:47,360 Speaker 17: New York City mirror election. And another important aspect is 673 00:32:47,360 --> 00:32:50,600 Speaker 17: that those companies have big partnership with medias, So you're 674 00:32:50,600 --> 00:32:54,560 Speaker 17: gonna turn on TV, watch CNN and potentially see cowshields 675 00:32:54,600 --> 00:32:57,720 Speaker 17: or polar market alts, depending on the partnership. They're entering 676 00:32:57,840 --> 00:33:02,000 Speaker 17: our mainstream just daily life lives, and that changes everything. 677 00:33:02,160 --> 00:33:05,600 Speaker 17: And also, like the twenty twenty four election was a 678 00:33:05,600 --> 00:33:08,520 Speaker 17: big turning moment for them because both of the prediction 679 00:33:08,600 --> 00:33:12,520 Speaker 17: market platforms were giving a lead to Trump winning the election. 680 00:33:12,800 --> 00:33:14,719 Speaker 17: And I feel as though a lot of people are 681 00:33:14,720 --> 00:33:16,600 Speaker 17: saying they were more accurate. 682 00:33:16,360 --> 00:33:17,720 Speaker 16: Than posts when it comes to the election. 683 00:33:18,040 --> 00:33:22,000 Speaker 17: So there is also like the truth machine accurate polling, 684 00:33:22,160 --> 00:33:24,680 Speaker 17: prediction market and go as well as just like it's 685 00:33:24,800 --> 00:33:26,600 Speaker 17: probably exciting for a lot of people to put their 686 00:33:26,640 --> 00:33:27,760 Speaker 17: money and say I was right. 687 00:33:28,120 --> 00:33:30,080 Speaker 5: It's kind of funny that cal She's like, this is 688 00:33:30,200 --> 00:33:34,280 Speaker 5: voter suppression. They're trying to take the vote away from 689 00:33:34,560 --> 00:33:37,360 Speaker 5: you know, hard working gambling Americans who just want to 690 00:33:37,520 --> 00:33:40,160 Speaker 5: gamble on their elections. 691 00:33:39,560 --> 00:33:42,400 Speaker 2: The American dream. They just want to vote and place 692 00:33:42,440 --> 00:33:43,720 Speaker 2: their bet on who's. 693 00:33:43,480 --> 00:33:44,000 Speaker 3: Going to open. 694 00:33:44,160 --> 00:33:47,760 Speaker 5: Yeah, but I do think like in the context of 695 00:33:47,800 --> 00:33:51,400 Speaker 5: the way that calsi and also as Deniza knows, many 696 00:33:51,400 --> 00:33:54,400 Speaker 5: of these crypto companies are trying to kind of create 697 00:33:54,400 --> 00:34:00,280 Speaker 5: a voting block of like young pro crypto pro didiction 698 00:34:00,400 --> 00:34:03,320 Speaker 5: markets and so on, Like they see this as a 699 00:34:03,400 --> 00:34:06,400 Speaker 5: political force. And I'm kind of curious, you know, having 700 00:34:06,480 --> 00:34:08,960 Speaker 5: followed the sort of crypto industry and the way that 701 00:34:09,040 --> 00:34:12,600 Speaker 5: they kind of you know, got behind Trump during the 702 00:34:12,680 --> 00:34:15,560 Speaker 5: twenty four election. Are there any of the same dynamics 703 00:34:15,560 --> 00:34:18,120 Speaker 5: that play here with prediction markets are there, Like prediction 704 00:34:18,280 --> 00:34:21,400 Speaker 5: market enthusiasts who feel passionate about this are the people 705 00:34:21,400 --> 00:34:24,319 Speaker 5: like threatening to leave Wisconsin or demonstrate at the state 706 00:34:24,360 --> 00:34:27,319 Speaker 5: capital or do anything, you know, in response to this. 707 00:34:27,480 --> 00:34:29,719 Speaker 17: I haven't seen this particular case, but I know in 708 00:34:29,719 --> 00:34:34,120 Speaker 17: previous because there's similar lawsuits about sports betting in different states, 709 00:34:34,120 --> 00:34:36,879 Speaker 17: and I've seen people threaten to leave states so they 710 00:34:36,880 --> 00:34:39,920 Speaker 17: can actually use prediction markets if something happens. 711 00:34:40,640 --> 00:34:43,320 Speaker 16: So indeed, I can see how if this case evolves, 712 00:34:43,360 --> 00:34:45,600 Speaker 16: people might be talking about it more and more. 713 00:34:46,040 --> 00:34:48,960 Speaker 17: But I think the comparison to crypto is very important, 714 00:34:49,120 --> 00:34:51,799 Speaker 17: very similar. Of course, we have a lot of people 715 00:34:51,840 --> 00:34:54,640 Speaker 17: from the Trump's family getting involved in both platforms, both 716 00:34:54,680 --> 00:34:58,800 Speaker 17: polymarket and Koushi. We even had Trump Media look into 717 00:34:58,920 --> 00:35:01,399 Speaker 17: launching a prediction market. So there are a lot of 718 00:35:01,719 --> 00:35:04,320 Speaker 17: political parallels here, a lot of things we should think about. 719 00:35:04,760 --> 00:35:08,759 Speaker 17: And obviously the current CFTC and the general White House 720 00:35:08,800 --> 00:35:11,640 Speaker 17: administration has been very supportive of prediction market. A big 721 00:35:11,680 --> 00:35:15,239 Speaker 17: part of why those lawsuits are so contested and it 722 00:35:15,280 --> 00:35:18,040 Speaker 17: takes so long is because the CFTC is standing behind 723 00:35:18,239 --> 00:35:20,920 Speaker 17: those firms and in this case, because CAUSHI is the 724 00:35:20,920 --> 00:35:24,759 Speaker 17: big CFTC US based one and it's saying we regulate this. 725 00:35:24,960 --> 00:35:26,759 Speaker 17: These are our markets and we're going to take care 726 00:35:26,760 --> 00:35:29,320 Speaker 17: of them. It's not up to the states to the side. 727 00:35:29,360 --> 00:35:32,280 Speaker 17: So the political force of this is very important. Politics 728 00:35:32,280 --> 00:35:35,600 Speaker 17: are important. Elections are the essence of this. It's what 729 00:35:35,680 --> 00:35:38,680 Speaker 17: you tell people. It's what they've been telling for ages 730 00:35:38,719 --> 00:35:40,880 Speaker 17: that we were right about twenty twenty four and we 731 00:35:40,880 --> 00:35:44,160 Speaker 17: will continue to be the best aggregator of information for elections, 732 00:35:44,440 --> 00:35:46,240 Speaker 17: economy and other important topics. 733 00:35:46,680 --> 00:35:49,279 Speaker 4: So, Denita, I just have one last question I want 734 00:35:49,320 --> 00:35:51,319 Speaker 4: to make sure to ask you, which is you've been 735 00:35:51,400 --> 00:35:54,880 Speaker 4: covering this for a long time, looking at this issue. 736 00:35:54,880 --> 00:36:00,520 Speaker 4: How serious is this? If you were deciding Wisconsin v. Kaushi, Like, 737 00:36:00,600 --> 00:36:03,040 Speaker 4: what what would you call? 738 00:36:03,239 --> 00:36:06,000 Speaker 17: Wow, that's a great owner of my career. It's a 739 00:36:06,280 --> 00:36:08,719 Speaker 17: complicated case. I think there are two aspects. They are 740 00:36:08,760 --> 00:36:12,160 Speaker 17: the aspect for manipulation, whether if in fact I'm a 741 00:36:12,200 --> 00:36:15,800 Speaker 17: foreign agent or in fact someone wants to interfere in election. 742 00:36:15,960 --> 00:36:17,759 Speaker 17: If I have the money and desire to do that, 743 00:36:17,800 --> 00:36:20,960 Speaker 17: and I have access to prediction market, how important my 744 00:36:21,080 --> 00:36:23,400 Speaker 17: actions might be if also I have some other parties 745 00:36:23,440 --> 00:36:24,840 Speaker 17: and reason to boost a candidate. 746 00:36:25,360 --> 00:36:26,840 Speaker 16: Maybe perhaps that's giving. 747 00:36:26,600 --> 00:36:29,719 Speaker 17: Me means to do that. And the second big thing 748 00:36:29,840 --> 00:36:32,759 Speaker 17: is insider trading. What if I have information about this 749 00:36:33,040 --> 00:36:36,400 Speaker 17: which obviously election walls are very very strong, there are 750 00:36:36,440 --> 00:36:39,360 Speaker 17: a lot of protections about about counting. But if I 751 00:36:39,400 --> 00:36:41,759 Speaker 17: have an incentive to do that, I may benefit a 752 00:36:41,800 --> 00:36:44,440 Speaker 17: lot of money. And you know, maybe I have information, 753 00:36:44,520 --> 00:36:46,640 Speaker 17: maybe I pass it on someone. It just opens a 754 00:36:46,640 --> 00:36:49,399 Speaker 17: big network of people that may profit from that. 755 00:36:49,719 --> 00:36:53,520 Speaker 16: And the last thing is just elections is very complicated topic. 756 00:36:53,520 --> 00:36:56,960 Speaker 17: There are so many contested topics, and just adding money 757 00:36:56,960 --> 00:37:00,000 Speaker 17: to that equation and adding to like chances of many 758 00:37:00,480 --> 00:37:03,280 Speaker 17: the insider trading, I think it completely complicates the future 759 00:37:03,320 --> 00:37:06,800 Speaker 17: of how we contest elections and talk about this topic. 760 00:37:07,400 --> 00:37:08,520 Speaker 3: We're going to keep following this. 761 00:37:08,600 --> 00:37:12,080 Speaker 5: We'll have to have you back for a future segment 762 00:37:12,200 --> 00:37:13,480 Speaker 5: of this weekend Prediction Markets. 763 00:37:13,480 --> 00:37:14,600 Speaker 3: Really great having you see soon. 764 00:37:14,719 --> 00:37:17,840 Speaker 4: Thanks for having Medanita, and also if you have thoughts 765 00:37:17,920 --> 00:37:20,280 Speaker 4: on this, please send us an email. 766 00:37:20,320 --> 00:37:21,920 Speaker 2: I feel like this is an interesting. 767 00:37:21,760 --> 00:37:24,680 Speaker 3: If you're if you have been disenfranchised by this. 768 00:37:24,800 --> 00:37:27,359 Speaker 4: Yes, and you feel like your voter's rights have been 769 00:37:27,400 --> 00:37:30,360 Speaker 4: suppressed because you could not place your bed on Calshi. 770 00:37:30,400 --> 00:37:32,640 Speaker 5: Well, are you already placed it? It's too late now 771 00:37:32,719 --> 00:37:35,840 Speaker 5: you're now you're looking at a felon. Well, you have to, 772 00:37:36,080 --> 00:37:38,399 Speaker 5: you just wouldn't be able to vote. I'm not sure 773 00:37:38,440 --> 00:37:39,680 Speaker 5: what the enforcement mechanism. 774 00:37:39,719 --> 00:37:43,440 Speaker 4: Yeah, I was gonna say. 775 00:37:49,280 --> 00:37:51,400 Speaker 5: This show is produced by Jasmine J. T. Green and 776 00:37:51,400 --> 00:37:55,160 Speaker 5: Stacey Wong. Mangus Hendrickson is a supervising producer. Sam Rogan 777 00:37:55,239 --> 00:37:58,480 Speaker 5: handles engineering and Dave Purcell fact checks. Special thanks to 778 00:37:58,520 --> 00:38:01,520 Speaker 5: Jeff Muscus, Julia Rubin and if you have a minute, 779 00:38:01,600 --> 00:38:02,680 Speaker 5: please rate and review the show. 780 00:38:02,719 --> 00:38:03,600 Speaker 3: It'll mean a lot to us. 781 00:38:03,680 --> 00:38:05,720 Speaker 5: And if you have a story that should be our business, 782 00:38:05,960 --> 00:38:08,680 Speaker 5: email us at Everybody's at bloomer dot net. That's everybody 783 00:38:08,800 --> 00:38:10,880 Speaker 5: with an ass at Bloomberg dot net. Thank you for 784 00:38:10,960 --> 00:38:12,160 Speaker 5: listening and we will see 785 00:38:12,200 --> 00:38:17,879 Speaker 10: You next week.