1 00:00:02,560 --> 00:00:07,040 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:08,840 --> 00:00:13,040 Speaker 2: Hi Stacy Bradstone, Welcome to Everybody's business. Thank you so 3 00:00:13,119 --> 00:00:15,600 Speaker 2: much for filling in for Max Chafkin as he has 4 00:00:15,880 --> 00:00:17,639 Speaker 2: whisked off to the Alps. 5 00:00:17,680 --> 00:00:20,279 Speaker 3: From what I understand, right, and not as a competitor, 6 00:00:20,360 --> 00:00:22,119 Speaker 3: I don't think, but as. 7 00:00:21,920 --> 00:00:24,520 Speaker 2: A spectator, yeah, I think he is actually going to 8 00:00:24,560 --> 00:00:26,239 Speaker 2: see some Olympic events. 9 00:00:26,040 --> 00:00:26,639 Speaker 4: And he's messed. 10 00:00:26,680 --> 00:00:30,000 Speaker 3: A crazy week, right, just a brutal week and a 11 00:00:30,040 --> 00:00:31,320 Speaker 3: reckoning in the world of AI. 12 00:00:31,640 --> 00:00:35,199 Speaker 2: Yes, investors in a lot of big software companies, including 13 00:00:35,240 --> 00:00:39,360 Speaker 2: Salesforce Oracle Service, now they have been kind of swept 14 00:00:39,440 --> 00:00:42,760 Speaker 2: up in this panic that's happening in the industry. And 15 00:00:43,040 --> 00:00:45,239 Speaker 2: even while all of this is happening and all these 16 00:00:45,280 --> 00:00:48,760 Speaker 2: reckonings are coming down, there is still no question in 17 00:00:48,800 --> 00:00:52,559 Speaker 2: anybody's mind that there is a lot of opportunity and 18 00:00:52,720 --> 00:00:54,200 Speaker 2: money to be made in AI. 19 00:00:54,400 --> 00:00:54,560 Speaker 4: Right. 20 00:00:54,600 --> 00:00:57,840 Speaker 3: And speaking of wealth, there's something surprising happening in the 21 00:00:57,880 --> 00:01:01,640 Speaker 3: conversations about it. California, New York City are having a 22 00:01:01,720 --> 00:01:04,640 Speaker 3: kind of brutal debate over how we tax wealth. 23 00:01:05,000 --> 00:01:09,360 Speaker 5: People who earn money pay very high taxes, whereas people 24 00:01:09,400 --> 00:01:12,279 Speaker 5: who have money don't. 25 00:01:12,600 --> 00:01:14,920 Speaker 3: That's ray Mattoff and Stacy. We're going to speak with 26 00:01:14,920 --> 00:01:17,639 Speaker 3: her today about the way we tax or don't tax 27 00:01:17,680 --> 00:01:19,040 Speaker 3: the very rich in this country. 28 00:01:19,560 --> 00:01:21,800 Speaker 2: And after that we're going to switch gears a little 29 00:01:21,840 --> 00:01:24,280 Speaker 2: bit because before Max left, he and I had a 30 00:01:24,280 --> 00:01:28,440 Speaker 2: conversation about Generation Alpha. That is the topic of the 31 00:01:28,560 --> 00:01:31,680 Speaker 2: latest issue of BusinessWeek. Particularly. We tend to think of 32 00:01:31,760 --> 00:01:35,000 Speaker 2: Jen Alpha's as a very on screen generation, but as 33 00:01:35,040 --> 00:01:37,959 Speaker 2: it turns out, there are a lot more skeptical than 34 00:01:37,959 --> 00:01:38,600 Speaker 2: we might think. 35 00:01:39,400 --> 00:01:41,920 Speaker 4: Don't do scroll kigs horrible. 36 00:01:44,760 --> 00:01:48,760 Speaker 2: This is Everybody's business from Bloomberg BusinessWeek. I'm Stacey Banicksmith. 37 00:01:48,280 --> 00:01:49,800 Speaker 4: And I'm Brad Banickstone. 38 00:01:50,680 --> 00:01:53,960 Speaker 2: I welcome you into the Vanik Clan for this week's discussion. 39 00:01:54,000 --> 00:01:56,880 Speaker 2: We're going to fire up the LM and look at 40 00:01:56,920 --> 00:02:04,639 Speaker 2: the effect of AI on the economy. But first, Brad, 41 00:02:04,800 --> 00:02:07,920 Speaker 2: let's take a look at the headlines. As we mentioned, 42 00:02:07,960 --> 00:02:11,440 Speaker 2: we're seeing a different kind of AI panic. One by one, 43 00:02:11,639 --> 00:02:14,679 Speaker 2: sector after sector is being pushed by this sell off 44 00:02:14,680 --> 00:02:15,680 Speaker 2: in the markets. 45 00:02:15,400 --> 00:02:20,280 Speaker 3: Right travel services, financial services, legal services, software as a service. 46 00:02:20,520 --> 00:02:24,040 Speaker 3: It's all being slowly eaten away by fears that AI 47 00:02:24,120 --> 00:02:26,600 Speaker 3: tools are going to render these companies useless. 48 00:02:26,760 --> 00:02:29,240 Speaker 2: I mean, what's so interesting to me about this is 49 00:02:29,960 --> 00:02:32,799 Speaker 2: that we really don't know how things are going to 50 00:02:32,840 --> 00:02:36,080 Speaker 2: shake out yet. I mean, these are just very early days. 51 00:02:36,240 --> 00:02:39,480 Speaker 2: But the panic seems to be about the speculation, almost 52 00:02:39,520 --> 00:02:42,240 Speaker 2: as much as all the exuberants was about the speculation. 53 00:02:42,360 --> 00:02:45,400 Speaker 4: I totally agree it's vibes based, as we. 54 00:02:45,360 --> 00:02:48,040 Speaker 2: Say on this vibes based, yes. 55 00:02:47,720 --> 00:02:52,200 Speaker 3: Right, I mean, we know AI automates routine work. They 56 00:02:52,240 --> 00:02:55,680 Speaker 3: can handle workflows and coding, But I mean the idea 57 00:02:55,760 --> 00:03:01,320 Speaker 3: that it displaces data, governance, security, compl clients, vendor support, 58 00:03:01,360 --> 00:03:05,000 Speaker 3: all the things that these companies Oracle Salesforce Service now 59 00:03:05,480 --> 00:03:08,040 Speaker 3: do so well. I mean, it feels far fetched to 60 00:03:08,080 --> 00:03:11,200 Speaker 3: me and more a market reaction than an underlying reality. 61 00:03:11,600 --> 00:03:13,960 Speaker 2: I feel like we're seeing this effective AI in so 62 00:03:14,040 --> 00:03:15,880 Speaker 2: many parts of the economy, though I feel like it's 63 00:03:15,919 --> 00:03:18,800 Speaker 2: the same exact thing in the job market. There's just 64 00:03:18,880 --> 00:03:21,239 Speaker 2: so much speculation about I mean, I think there's a 65 00:03:21,320 --> 00:03:23,960 Speaker 2: enormous amount of promise. You're really in the heart of 66 00:03:23,960 --> 00:03:26,480 Speaker 2: it where you are, Brady, But there's so much promise 67 00:03:26,560 --> 00:03:29,600 Speaker 2: and excitement over what AI can do, and so much 68 00:03:29,639 --> 00:03:32,799 Speaker 2: fear about what it's going to do as well. It's 69 00:03:32,840 --> 00:03:36,800 Speaker 2: just really interesting to me kind of the emotional arc 70 00:03:37,360 --> 00:03:41,080 Speaker 2: of AI in our economy right now. And it's easy 71 00:03:41,120 --> 00:03:44,040 Speaker 2: to write off vibes I think as being sort of 72 00:03:44,080 --> 00:03:49,080 Speaker 2: silly or ephemeral, But I mean, we're talking about billions 73 00:03:49,120 --> 00:03:53,200 Speaker 2: of dollars being like sucked out of the economy because 74 00:03:53,240 --> 00:03:56,360 Speaker 2: of fears or just pumped into the economy because of excitement. 75 00:03:56,360 --> 00:03:57,360 Speaker 2: It's a strange time. 76 00:03:57,480 --> 00:03:59,680 Speaker 3: It's a weird moment, and part of it is the 77 00:03:59,720 --> 00:04:02,280 Speaker 3: fear of kind of AI disruption, and part of it 78 00:04:02,360 --> 00:04:06,360 Speaker 3: is simply the sheer scale of the capital investments that 79 00:04:06,440 --> 00:04:09,680 Speaker 3: are being made as these companies build out data centers, 80 00:04:10,160 --> 00:04:15,040 Speaker 3: enter into costly partnerships with companies like Nvidia, or simply 81 00:04:15,080 --> 00:04:17,880 Speaker 3: do the work to build up their own AI agents 82 00:04:17,920 --> 00:04:20,120 Speaker 3: and try to integrate them into their core products. 83 00:04:20,320 --> 00:04:22,520 Speaker 2: It reminds me of back when I was a reporter 84 00:04:22,560 --> 00:04:25,880 Speaker 2: at Marketplace. One of my beats was big data, back 85 00:04:25,880 --> 00:04:28,480 Speaker 2: when big data was a was a beat, And what 86 00:04:28,560 --> 00:04:30,960 Speaker 2: everyone kept saying to me over and over was did 87 00:04:30,960 --> 00:04:33,400 Speaker 2: you ever see Minority Report? Of course, do you remember 88 00:04:33,440 --> 00:04:35,520 Speaker 2: this When Tom Cruise is running through the mall and 89 00:04:35,560 --> 00:04:38,360 Speaker 2: there are all these holograms being projected by these different 90 00:04:38,360 --> 00:04:42,320 Speaker 2: brand personalized They're like it's time to replace your whatever 91 00:04:42,440 --> 00:04:45,359 Speaker 2: Nike Pegasus or like would you like a Rolex or 92 00:04:45,680 --> 00:04:48,960 Speaker 2: whatever it is. And everyone kept saying that is happening, 93 00:04:49,120 --> 00:04:52,120 Speaker 2: like that is just around the corner, and it never happened, 94 00:04:52,120 --> 00:04:54,520 Speaker 2: Like it still hasn't really happened. I mean it happened 95 00:04:54,520 --> 00:04:56,760 Speaker 2: in a different way. And I think about that moment 96 00:04:56,800 --> 00:05:00,120 Speaker 2: all the time right now, because I feel like that 97 00:05:00,279 --> 00:05:03,479 Speaker 2: is happening with AI. But there's so much money behind 98 00:05:03,520 --> 00:05:06,400 Speaker 2: it now and so many market forces behind it. It 99 00:05:06,440 --> 00:05:09,039 Speaker 2: seems like it's really kind of shaking the foundations of 100 00:05:09,040 --> 00:05:13,200 Speaker 2: our economy in a really profound way. And you know, 101 00:05:13,240 --> 00:05:16,719 Speaker 2: in another development this week read these AI companies are 102 00:05:16,800 --> 00:05:19,480 Speaker 2: now setting their sites, of course, on deeper pockets the 103 00:05:19,600 --> 00:05:23,560 Speaker 2: US government. I feel like all big business eventually turns 104 00:05:23,600 --> 00:05:27,360 Speaker 2: its gate. It's like the Jupiter of the finance world, 105 00:05:27,400 --> 00:05:30,520 Speaker 2: right is the largest gravitational pull. Everybody wants a US 106 00:05:30,600 --> 00:05:35,400 Speaker 2: government contract. But now there is a lot of excitement 107 00:05:35,440 --> 00:05:41,400 Speaker 2: and investment around developing autonomous weapons and also using AI 108 00:05:41,440 --> 00:05:44,280 Speaker 2: and service of kind of mass surveillance. And now there's 109 00:05:44,279 --> 00:05:47,520 Speaker 2: a big discussion about putting protections in place around that 110 00:05:47,920 --> 00:05:48,440 Speaker 2: as well. 111 00:05:48,560 --> 00:05:51,279 Speaker 3: Right this week we saw anthropic talking to the US 112 00:05:51,360 --> 00:05:55,880 Speaker 3: government about extending its claud contracts, SpaceX talking about competing 113 00:05:55,920 --> 00:06:00,400 Speaker 3: in a Pentagon contest to produce voice control autonomous drown 114 00:06:00,680 --> 00:06:05,279 Speaker 3: swarming technology, and Stacy. The interesting thing here is how 115 00:06:05,800 --> 00:06:09,520 Speaker 3: at odds these potential relationships are with some of the 116 00:06:09,520 --> 00:06:12,880 Speaker 3: core values that fueled at least some of the AI 117 00:06:12,960 --> 00:06:16,559 Speaker 3: companies and Thropic of course, you know Open AI, who's 118 00:06:16,600 --> 00:06:20,680 Speaker 3: founding mission was to benefit humanity. They're going to the Pentagon. 119 00:06:21,320 --> 00:06:23,880 Speaker 3: They're trying to draw some lines around the relationship. I 120 00:06:23,880 --> 00:06:25,280 Speaker 3: don't know how successful that will be. 121 00:06:25,720 --> 00:06:28,680 Speaker 2: Boys control drones is very frightening because I feel like 122 00:06:28,720 --> 00:06:32,200 Speaker 2: when I have tried to interact with AI via voice controls, 123 00:06:32,279 --> 00:06:37,440 Speaker 2: it just doesn't often go that well. And the stakes 124 00:06:37,440 --> 00:06:39,320 Speaker 2: in this case are really low. It's like, you know, 125 00:06:39,680 --> 00:06:43,520 Speaker 2: a recipe for chicken or something, but if we're talking 126 00:06:43,520 --> 00:06:48,120 Speaker 2: about like drone strikes, it just seems like the Department 127 00:06:48,160 --> 00:06:49,760 Speaker 2: of War needs to get it right. 128 00:06:50,080 --> 00:06:50,599 Speaker 4: And Stacy. 129 00:06:50,640 --> 00:06:55,200 Speaker 3: One more development this week, NPR hosts David Green suing 130 00:06:55,279 --> 00:06:57,880 Speaker 3: Google for using a likeness of his voice and it's 131 00:06:57,960 --> 00:07:03,560 Speaker 3: product notebook LM. Now you know you're a longtime radio personality. 132 00:07:03,839 --> 00:07:07,680 Speaker 3: David Dreine says that is his voice. It says intonations 133 00:07:07,760 --> 00:07:08,720 Speaker 3: and filler words. 134 00:07:08,880 --> 00:07:09,880 Speaker 4: What do you think? 135 00:07:10,320 --> 00:07:10,520 Speaker 6: You know? 136 00:07:10,680 --> 00:07:12,960 Speaker 2: This is interesting? I mean, I feel like there's quite 137 00:07:13,000 --> 00:07:16,640 Speaker 2: a bit of crossover here between you know, the debate 138 00:07:16,640 --> 00:07:20,880 Speaker 2: happening in Hollywood over people's likenesses. I do think it's true. 139 00:07:20,920 --> 00:07:24,480 Speaker 2: I mean, this happened at NPR in other iterations as well. 140 00:07:24,520 --> 00:07:27,360 Speaker 2: I remember there was a bunch of excitement over an 141 00:07:27,400 --> 00:07:31,160 Speaker 2: AI launch that used a voice that sounded very similar 142 00:07:31,160 --> 00:07:33,920 Speaker 2: to Steven Skeeep's voice, and it was a podcast that 143 00:07:33,960 --> 00:07:36,000 Speaker 2: would generate itself if you said, like, hey, I want 144 00:07:36,000 --> 00:07:40,440 Speaker 2: to learn about you know, any fiber and the importance 145 00:07:40,480 --> 00:07:42,560 Speaker 2: of fiber in your diet in a podcast form, and 146 00:07:42,560 --> 00:07:45,520 Speaker 2: then they would have an en Scipion like voice interviewing 147 00:07:45,640 --> 00:07:49,280 Speaker 2: a reporter and it would just immediately generate it. So 148 00:07:50,600 --> 00:07:52,640 Speaker 2: when I was at NPR, we were both sort of 149 00:07:52,680 --> 00:07:54,760 Speaker 2: delighted and excited by this because it was just so 150 00:07:54,840 --> 00:07:56,600 Speaker 2: funny how fast it was able to put it together. 151 00:07:56,640 --> 00:08:01,040 Speaker 2: But it did feel kind of terrifying. And the point 152 00:08:01,080 --> 00:08:02,600 Speaker 2: that I had a colleague make, and I think this 153 00:08:02,680 --> 00:08:05,200 Speaker 2: is a really good one, and to answer your question, 154 00:08:05,480 --> 00:08:09,080 Speaker 2: is that you know the reason they're using stevens Keep's 155 00:08:09,160 --> 00:08:11,320 Speaker 2: voice or David Green's voice is because there's a lot 156 00:08:11,360 --> 00:08:14,400 Speaker 2: of sort of authority in that voice, and that's from 157 00:08:14,440 --> 00:08:18,280 Speaker 2: a lot of years of reporting and you know, trying 158 00:08:18,280 --> 00:08:20,720 Speaker 2: to get it right and a lot of hours and 159 00:08:20,960 --> 00:08:23,240 Speaker 2: time and investment went into that credibility. 160 00:08:23,320 --> 00:08:26,040 Speaker 3: And we should say, Google insists it's a paid actor, 161 00:08:26,280 --> 00:08:28,760 Speaker 3: but it's hard to believe it's a total coincidence. 162 00:08:28,800 --> 00:08:30,560 Speaker 2: It is hard to believe it's a total quincience. I mean, 163 00:08:30,600 --> 00:08:33,560 Speaker 2: this happened with us. Scarlett Johansson's voice too, write like 164 00:08:33,600 --> 00:08:37,160 Speaker 2: they were they appropriated that. I mean, I think because 165 00:08:37,160 --> 00:08:40,120 Speaker 2: we have associations with these voices, and I feel like 166 00:08:40,280 --> 00:08:43,199 Speaker 2: for us as humans, like we hear voices before we're 167 00:08:43,200 --> 00:08:45,840 Speaker 2: even born, Like this is very primal for us, and 168 00:08:45,840 --> 00:08:49,200 Speaker 2: we have very emotional associations with voices. It is a 169 00:08:49,240 --> 00:08:52,160 Speaker 2: little tricky when an AI can just generate a voice 170 00:08:52,200 --> 00:08:54,600 Speaker 2: you trust. I mean, imagine if it's like a family 171 00:08:54,640 --> 00:08:58,640 Speaker 2: member or you know, someone you you absolutely look up to, 172 00:08:58,720 --> 00:09:01,359 Speaker 2: or someone you absolutely hate, and just like the emotions 173 00:09:01,360 --> 00:09:04,760 Speaker 2: that get evoked around that voice telling you something. I 174 00:09:04,760 --> 00:09:08,800 Speaker 2: think it is quite powerful and is definitely worth a look, 175 00:09:08,840 --> 00:09:11,360 Speaker 2: and I'm glad this lawsuit is happening because I think 176 00:09:11,400 --> 00:09:14,000 Speaker 2: it will force a deeper dive because in this country, 177 00:09:14,040 --> 00:09:23,920 Speaker 2: like that's how things happen, right via litigation. Bradstone, you 178 00:09:23,960 --> 00:09:28,559 Speaker 2: have a big story running in this issue of BusinessWeek. 179 00:09:28,600 --> 00:09:31,040 Speaker 2: Can you talk a little bit about it. It's about taxes, 180 00:09:31,280 --> 00:09:34,720 Speaker 2: but it's super exciting and interesting. I feel like some 181 00:09:34,720 --> 00:09:35,880 Speaker 2: people don't always think that about it. 182 00:09:35,920 --> 00:09:39,360 Speaker 3: Nothing more interesting than taxes, right. I wrote the opening 183 00:09:39,480 --> 00:09:42,000 Speaker 3: essay of our March issue, how to Tax a Trillionaire. 184 00:09:42,080 --> 00:09:45,440 Speaker 3: You may have heard Stacy California tearing itself to pieces 185 00:09:45,480 --> 00:09:48,560 Speaker 3: over a proposal a one time tax of five percent 186 00:09:48,720 --> 00:09:51,760 Speaker 3: on wealthy families with over one point one billion dollars 187 00:09:51,800 --> 00:09:55,120 Speaker 3: in assets. This has not even qualified for the ballot yet, 188 00:09:55,160 --> 00:09:58,520 Speaker 3: but politicians are coming out for and against. Billions are 189 00:09:58,520 --> 00:10:01,439 Speaker 3: being raised by super packs fight it. People have threatened 190 00:10:01,440 --> 00:10:04,400 Speaker 3: to leave the state and that's it. Famous founders Larry Page, 191 00:10:04,440 --> 00:10:09,040 Speaker 3: Sergey Brin, Mark Zuckerberg buying homes and establishing residences outside 192 00:10:09,080 --> 00:10:09,440 Speaker 3: the state. 193 00:10:09,720 --> 00:10:12,880 Speaker 2: This is a fascinating topic and certainly one that has 194 00:10:12,960 --> 00:10:16,079 Speaker 2: been really top of mind, I think for the last 195 00:10:16,080 --> 00:10:18,480 Speaker 2: few years now, as people have discussed wealth and the 196 00:10:18,480 --> 00:10:23,280 Speaker 2: disparity between the wealthy and lower income people getting wider 197 00:10:23,320 --> 00:10:25,600 Speaker 2: in this country. And we are very lucky to have 198 00:10:26,000 --> 00:10:29,079 Speaker 2: someone you spoke with for your article. Ray Madoff, professor 199 00:10:29,120 --> 00:10:32,360 Speaker 2: at Boston College Law School and author of The Second Estate, 200 00:10:32,600 --> 00:10:36,120 Speaker 2: How the Tax Code Made in American Aristocracy. Ray, welcome 201 00:10:36,160 --> 00:10:37,280 Speaker 2: to everybody's business. 202 00:10:37,840 --> 00:10:39,640 Speaker 5: Thank you so much. It's a real pleasure to be 203 00:10:39,679 --> 00:10:40,360 Speaker 5: here with both of you. 204 00:10:40,920 --> 00:10:43,000 Speaker 3: So, Ray, you wrote the book on how we tax 205 00:10:43,080 --> 00:10:46,120 Speaker 3: or how we don't tax billionaires. I really relied on 206 00:10:46,240 --> 00:10:48,840 Speaker 3: you as I reported out this story. So tell us 207 00:10:48,840 --> 00:10:51,560 Speaker 3: what do you think of wealth tax proposals like the 208 00:10:51,600 --> 00:10:52,760 Speaker 3: one in California. 209 00:10:52,880 --> 00:10:57,400 Speaker 5: It's interesting because wealth tax proposals are in some ways 210 00:10:57,679 --> 00:11:01,760 Speaker 5: an obvious solution to the current situation. The current problem 211 00:11:01,760 --> 00:11:05,560 Speaker 5: that we have now is that the wealthiest Americans have 212 00:11:05,760 --> 00:11:10,360 Speaker 5: found many easily available effective ways to avoid the income tax. 213 00:11:10,600 --> 00:11:12,840 Speaker 5: And when they avoid the federal income tax, they also 214 00:11:12,880 --> 00:11:17,320 Speaker 5: avoid the state income tax. And so wealth taxes seem 215 00:11:17,400 --> 00:11:21,400 Speaker 5: to provide the perfect response to this problem, which is fine, 216 00:11:21,480 --> 00:11:25,280 Speaker 5: let's just tax their wealth. The problem is, like a 217 00:11:25,320 --> 00:11:28,920 Speaker 5: lot of solutions, the devil is in the details. They 218 00:11:29,000 --> 00:11:32,480 Speaker 5: might work in theory, but I am very concerned about 219 00:11:32,520 --> 00:11:34,319 Speaker 5: their ability to work in practice. 220 00:11:34,559 --> 00:11:36,480 Speaker 2: So this might seem like kind of an obvious question, 221 00:11:36,640 --> 00:11:39,240 Speaker 2: but I think it is quite interesting when we talk 222 00:11:39,240 --> 00:11:43,520 Speaker 2: about taxing someone's wealth as opposed to their income. What 223 00:11:43,559 --> 00:11:46,000 Speaker 2: do we mean and why is this a solution that 224 00:11:46,040 --> 00:11:48,600 Speaker 2: people like to talk about when dealing with the wealth 225 00:11:48,720 --> 00:11:50,240 Speaker 2: or the income gap in the US. 226 00:11:50,600 --> 00:11:53,880 Speaker 5: Yeah, And I think the answer is because of the 227 00:11:54,480 --> 00:11:56,560 Speaker 5: failure to tax income. I'm going to start on the 228 00:11:56,600 --> 00:11:58,840 Speaker 5: income side, because I think that's the tax that most 229 00:11:58,840 --> 00:11:59,959 Speaker 5: people are most familiar with. 230 00:12:00,280 --> 00:12:00,480 Speaker 4: Right. 231 00:12:00,720 --> 00:12:03,320 Speaker 5: Most people who are well off are well off because 232 00:12:03,360 --> 00:12:07,320 Speaker 5: they get salaries and other forms of taxable income. And 233 00:12:07,559 --> 00:12:10,920 Speaker 5: the more taxable income you get, the higher taxes you pay. 234 00:12:11,360 --> 00:12:14,680 Speaker 5: The thing is for our richest Americans, all these guys 235 00:12:14,720 --> 00:12:19,400 Speaker 5: in Silicon Valley, they have found ways of avoiding taxable income, 236 00:12:19,720 --> 00:12:22,080 Speaker 5: and they do it by following what I call the 237 00:12:22,160 --> 00:12:26,079 Speaker 5: tax avoidance playbook. And the first step is they avoid salaries. 238 00:12:26,120 --> 00:12:28,680 Speaker 5: So all these guys that are like, you know, the 239 00:12:28,800 --> 00:12:33,160 Speaker 5: greatest of all time, they're taking extremely modest salaries. So 240 00:12:33,240 --> 00:12:36,680 Speaker 5: Jeff Bezos gets a salary of eighty two thousand dollars, 241 00:12:36,920 --> 00:12:40,640 Speaker 5: so low that he actually qualified for the child tax credit, 242 00:12:40,840 --> 00:12:43,400 Speaker 5: which he took. And you know, and he never takes 243 00:12:43,440 --> 00:12:47,400 Speaker 5: more than that. And it's not just tax and it's 244 00:12:47,440 --> 00:12:49,920 Speaker 5: not because he's just a modest, humble guy, right, it's 245 00:12:49,920 --> 00:12:54,080 Speaker 5: because he knows that salaries are for suckers, because salaries 246 00:12:54,120 --> 00:12:56,800 Speaker 5: are subject to lots of taxes. They are subject to 247 00:12:56,800 --> 00:13:01,920 Speaker 5: both income taxes and payroll taxes, and together those taxes 248 00:13:01,920 --> 00:13:05,400 Speaker 5: are frequently, you know, over fifty percent. So they don't 249 00:13:05,440 --> 00:13:07,640 Speaker 5: want anything to do with that. And so what they 250 00:13:07,679 --> 00:13:10,439 Speaker 5: do is they don't take salaries and instead they rely 251 00:13:10,880 --> 00:13:14,120 Speaker 5: on the growing value of their stock. And the growth 252 00:13:14,200 --> 00:13:17,600 Speaker 5: in value of their stock is extraordinary. Bezos again probably 253 00:13:17,640 --> 00:13:19,440 Speaker 5: on his own, his stock has probably gone up one 254 00:13:19,480 --> 00:13:22,080 Speaker 5: hundred and fifty billion dollars just since twenty twenty three, 255 00:13:22,280 --> 00:13:26,400 Speaker 5: So you're talking about massive growth of wealth. The thing 256 00:13:26,520 --> 00:13:31,360 Speaker 5: is that growth of wealth also avoids taxes because we 257 00:13:31,480 --> 00:13:35,480 Speaker 5: don't tax growing wealth until the property is sold. And 258 00:13:35,640 --> 00:13:38,960 Speaker 5: our wealthiest Americans have found a way to access this 259 00:13:39,120 --> 00:13:43,360 Speaker 5: property without actually selling it. And what that way is 260 00:13:43,360 --> 00:13:46,480 Speaker 5: is that they use it as collateral to borrow money. 261 00:13:46,679 --> 00:13:50,600 Speaker 5: And all of our richest Americans have borrowed huge amounts 262 00:13:50,600 --> 00:13:54,439 Speaker 5: of money to support their most lavish lifestyles. And what 263 00:13:54,480 --> 00:13:56,560 Speaker 5: it means is that they are able to live off 264 00:13:56,559 --> 00:14:00,160 Speaker 5: of this money without paying any taxes on it. Or 265 00:14:00,160 --> 00:14:03,960 Speaker 5: a state like California, and they have no salaries, they 266 00:14:03,960 --> 00:14:07,600 Speaker 5: have no capital gains, they have no income, and yet 267 00:14:07,640 --> 00:14:11,280 Speaker 5: they have massive amounts of wealth, and so of course 268 00:14:11,400 --> 00:14:13,800 Speaker 5: the natural thing is to say, well, let's just tax 269 00:14:13,840 --> 00:14:16,520 Speaker 5: them on their wealth. We know they have hundreds of 270 00:14:16,559 --> 00:14:20,600 Speaker 5: billions of dollars, so let's tax their wealth much like 271 00:14:20,640 --> 00:14:23,840 Speaker 5: one would tax a house. Right, a house is tax 272 00:14:24,080 --> 00:14:27,320 Speaker 5: not because it produces income, but based on the value 273 00:14:27,400 --> 00:14:29,760 Speaker 5: of the house. And that's what they're trying to do 274 00:14:29,840 --> 00:14:33,280 Speaker 5: in California and in other places that have proposed adopting 275 00:14:33,360 --> 00:14:36,680 Speaker 5: a wealth tax. It would be basically a five percent 276 00:14:36,800 --> 00:14:41,360 Speaker 5: tax on all the property interests owned by the various 277 00:14:41,400 --> 00:14:43,760 Speaker 5: taxpayers who fall into this group, which I think it's 278 00:14:43,760 --> 00:14:46,440 Speaker 5: a billion dollars is the current proposed cutoff for the 279 00:14:46,480 --> 00:14:47,960 Speaker 5: California tex And. 280 00:14:47,840 --> 00:14:50,080 Speaker 3: So, Ray, let's talk about the California tax. I mean, 281 00:14:50,160 --> 00:14:53,400 Speaker 3: why then is that a bad idea? If it is, 282 00:14:53,440 --> 00:14:56,320 Speaker 3: I mean, we're seeing a lot of billionaires taking their 283 00:14:56,360 --> 00:15:01,080 Speaker 3: toys and leaving the state Nevada, Miami, bat Florida. And 284 00:15:01,120 --> 00:15:03,440 Speaker 3: by the way, the reason this is proposed is that 285 00:15:03,480 --> 00:15:06,200 Speaker 3: the healthcare union, the largest healthcare union in the state, 286 00:15:06,520 --> 00:15:08,800 Speaker 3: looked at the state budget, saw that the One Big 287 00:15:08,840 --> 00:15:11,760 Speaker 3: Beautiful Bill Act is going to open up a massive 288 00:15:11,840 --> 00:15:15,040 Speaker 3: hole in the state's medical budget and thought, this is 289 00:15:15,120 --> 00:15:18,800 Speaker 3: a you know, a reservoir of perhaps untapped wealth that 290 00:15:18,880 --> 00:15:22,040 Speaker 3: we can access. So, you know, are these state led 291 00:15:22,480 --> 00:15:24,160 Speaker 3: measures just a bad idea. 292 00:15:24,600 --> 00:15:27,520 Speaker 5: Yeah, there's a couple of problems with them. As I say, 293 00:15:27,640 --> 00:15:33,000 Speaker 5: they are a totally understandable idea in theory, particularly when 294 00:15:33,040 --> 00:15:36,400 Speaker 5: you're talking about people who own publicly traded stock and 295 00:15:36,440 --> 00:15:40,000 Speaker 5: we can easily see at least what that stock is worth. 296 00:15:40,760 --> 00:15:44,800 Speaker 5: But there's a number of practical problems, particularly for states. 297 00:15:44,920 --> 00:15:47,840 Speaker 5: One problem is, as we're already seeing, is that people 298 00:15:47,920 --> 00:15:50,800 Speaker 5: can leave the state. Now California is trying to get 299 00:15:50,840 --> 00:15:52,960 Speaker 5: around it with this bill because they said anyone who 300 00:15:53,000 --> 00:15:55,400 Speaker 5: is a citizen on January first, I think that was 301 00:15:55,440 --> 00:15:58,400 Speaker 5: the cutoff date, they are still going to be subject 302 00:15:58,440 --> 00:16:01,200 Speaker 5: to this tax even if they reloak. But I'd say 303 00:16:01,200 --> 00:16:05,880 Speaker 5: a bigger problem comes with valuation, and that's because when 304 00:16:05,960 --> 00:16:08,680 Speaker 5: we have publicly traded stock, we can see that type 305 00:16:08,680 --> 00:16:11,360 Speaker 5: of value, but lots of wealth is held not in 306 00:16:11,400 --> 00:16:13,880 Speaker 5: publicly traded stock, and a lot of it is held, 307 00:16:13,920 --> 00:16:17,160 Speaker 5: for example, in partnership interests that are highly complex like 308 00:16:17,520 --> 00:16:21,400 Speaker 5: seven hundred levels d partnerships owning partnerships and very very 309 00:16:21,400 --> 00:16:25,040 Speaker 5: difficult to track that value, and then add all the 310 00:16:25,120 --> 00:16:27,760 Speaker 5: other types of things that people own. And the problem 311 00:16:27,880 --> 00:16:33,160 Speaker 5: is for states is that states normally piggyback their systems 312 00:16:33,200 --> 00:16:36,680 Speaker 5: on the federal government. Right, the federal government figures out 313 00:16:36,720 --> 00:16:39,040 Speaker 5: what your adjusted gross income is, and then the state 314 00:16:39,200 --> 00:16:42,320 Speaker 5: just rides on that. With these wealth taxes, states are 315 00:16:42,360 --> 00:16:44,680 Speaker 5: going to have to on their own put in all 316 00:16:44,720 --> 00:16:48,480 Speaker 5: that they need to try to track value, and it's 317 00:16:48,560 --> 00:16:51,600 Speaker 5: going to be a highly complex endeavor. And if we 318 00:16:51,600 --> 00:16:54,120 Speaker 5: were to do it large scale, like on the national level, 319 00:16:54,360 --> 00:16:56,920 Speaker 5: I think it would incentivize a lot of our wealthiest 320 00:16:56,960 --> 00:17:01,320 Speaker 5: Americans to stay out of the publicly try and instead 321 00:17:01,360 --> 00:17:04,840 Speaker 5: to stay in privately held business interests. And we already 322 00:17:04,840 --> 00:17:07,800 Speaker 5: see that now where a lot of private businesses are 323 00:17:07,800 --> 00:17:09,920 Speaker 5: not going public, and this would give them one more 324 00:17:09,960 --> 00:17:13,400 Speaker 5: reason to not go public. But when businesses pull out 325 00:17:13,400 --> 00:17:15,879 Speaker 5: of the public market, that's not good for all of 326 00:17:15,960 --> 00:17:18,760 Speaker 5: us who depend on the public market for our retirement 327 00:17:18,800 --> 00:17:19,680 Speaker 5: and other savings. 328 00:17:20,280 --> 00:17:22,280 Speaker 2: I'm curious because I know a lot of countries have 329 00:17:22,359 --> 00:17:25,240 Speaker 2: tried a wealth tax because I love how you said 330 00:17:25,280 --> 00:17:27,320 Speaker 2: salaries are for suckers. And it's true that a lot 331 00:17:27,400 --> 00:17:30,800 Speaker 2: of the wealthiest people, especially you know, generational wealth, it 332 00:17:30,840 --> 00:17:35,120 Speaker 2: gets tied up in properties, yachts, coin collections, things like that. 333 00:17:35,520 --> 00:17:37,760 Speaker 2: So a lot of countries have tried to get at this, 334 00:17:37,920 --> 00:17:41,800 Speaker 2: like France and Austria and Finland, they have all dropped 335 00:17:41,880 --> 00:17:45,240 Speaker 2: this wealth tax, like, they all backed away from it. 336 00:17:45,359 --> 00:17:47,199 Speaker 2: Are the reasons that you're laying out why? I mean, 337 00:17:47,280 --> 00:17:50,080 Speaker 2: did they have the same difficulty in assessing how much 338 00:17:50,080 --> 00:17:52,960 Speaker 2: wealth was actually there? And people potentially moving? 339 00:17:53,560 --> 00:17:58,040 Speaker 5: I think it's very difficult to capture everybody's wealth, the 340 00:17:58,080 --> 00:18:01,520 Speaker 5: wealthy of the wealthiest people, I do think, And in Europe, 341 00:18:01,520 --> 00:18:03,720 Speaker 5: in particularly, you have a lot of problems with people 342 00:18:03,760 --> 00:18:07,280 Speaker 5: moving because of course you have freedom of movement, but 343 00:18:07,440 --> 00:18:11,000 Speaker 5: without a unified system of taxation and so of course 344 00:18:11,080 --> 00:18:15,120 Speaker 5: people can easily move to lower tax jurisdiction. So it's 345 00:18:15,160 --> 00:18:18,480 Speaker 5: particularly problematic in Europe. And you know, I think that 346 00:18:18,560 --> 00:18:20,879 Speaker 5: if one we're going to have a wealth tax system, 347 00:18:20,960 --> 00:18:22,640 Speaker 5: it is going to involve sort of a whole new 348 00:18:22,640 --> 00:18:25,280 Speaker 5: way of thinking about things that frankly, at least in 349 00:18:25,280 --> 00:18:28,720 Speaker 5: the United States, is kind of anathema to our way 350 00:18:28,720 --> 00:18:31,439 Speaker 5: of thinking, just in terms of basic privacy. Right, if 351 00:18:31,440 --> 00:18:36,080 Speaker 5: people were forced to disclose every single thing they owned, 352 00:18:36,240 --> 00:18:38,840 Speaker 5: I think that a lot of Americans, even those who 353 00:18:38,880 --> 00:18:41,760 Speaker 5: weren't subject to the tax, might feel that that is 354 00:18:42,160 --> 00:18:45,439 Speaker 5: too invasive of people's privacy. So I worry about that 355 00:18:45,520 --> 00:18:45,920 Speaker 5: as well. 356 00:18:46,400 --> 00:18:49,879 Speaker 3: Ray, why are the politics around wealth taxes and taxing 357 00:18:49,920 --> 00:18:53,520 Speaker 3: the wealthy? Well, why are they so tricky, so hard fought, 358 00:18:53,680 --> 00:18:56,720 Speaker 3: so bitterly emotional at something that we're seeing right now 359 00:18:56,720 --> 00:18:57,480 Speaker 3: in California. 360 00:18:57,600 --> 00:19:00,280 Speaker 5: Well, I mean, of course, one reason is that the 361 00:19:00,320 --> 00:19:03,160 Speaker 5: wealthy of a lot of firepower, right, and so now 362 00:19:03,200 --> 00:19:05,280 Speaker 5: you're coming after them, and they have a lot to 363 00:19:05,280 --> 00:19:08,120 Speaker 5: say about it. So we've been seeing this more and more, 364 00:19:08,240 --> 00:19:12,280 Speaker 5: where the wealthiest are throwing their weight around in ways 365 00:19:12,320 --> 00:19:17,440 Speaker 5: that I think culturally they were previously probably less inclined 366 00:19:17,440 --> 00:19:20,159 Speaker 5: to do. Right, they would be concerned about the wealthy 367 00:19:20,200 --> 00:19:23,160 Speaker 5: throwing around their power, that this is maybe anti democratic, 368 00:19:23,480 --> 00:19:26,280 Speaker 5: But we're not in that age today. We may be 369 00:19:26,359 --> 00:19:28,520 Speaker 5: in the future, but right now we're in the age 370 00:19:28,520 --> 00:19:32,639 Speaker 5: that is embracing throw around your weight. Look out for 371 00:19:32,720 --> 00:19:35,840 Speaker 5: number one and it's almost like the greed is good. 372 00:19:35,880 --> 00:19:38,280 Speaker 5: You know, they say that every forty years a time 373 00:19:38,800 --> 00:19:41,199 Speaker 5: repeats itself, and so this is this is greed as 374 00:19:41,240 --> 00:19:43,920 Speaker 5: good to the nth degree. I think in the era 375 00:19:44,040 --> 00:19:45,720 Speaker 5: that we're living in right now. 376 00:19:45,520 --> 00:19:49,160 Speaker 2: I mean, do you think that taxing trillionaires or taxing 377 00:19:49,440 --> 00:19:53,840 Speaker 2: this super wealthy is that something that is potentially doable? 378 00:19:54,400 --> 00:19:58,920 Speaker 5: So I think the first answer is to stop focusing 379 00:19:59,119 --> 00:20:05,119 Speaker 5: on that we're taxing trillionaires, we're taxing billionaires, because I 380 00:20:05,160 --> 00:20:08,399 Speaker 5: think that type of framing makes it sound like the 381 00:20:08,560 --> 00:20:12,040 Speaker 5: rich are already paying a lot of taxes and now 382 00:20:12,040 --> 00:20:14,879 Speaker 5: we're going to impose extra burdens on them, And so 383 00:20:14,960 --> 00:20:18,000 Speaker 5: then it pushes us to have these kind of conversations 384 00:20:18,320 --> 00:20:20,800 Speaker 5: that are like, you know, our rich people good or 385 00:20:20,840 --> 00:20:23,239 Speaker 5: bad for society? Do they bring jobs or do they 386 00:20:23,320 --> 00:20:25,520 Speaker 5: you know, all of this stuff. But that's really beside 387 00:20:25,520 --> 00:20:28,280 Speaker 5: the point. I think the bigger problem is that the 388 00:20:28,400 --> 00:20:32,920 Speaker 5: public at large has been duped about who pays taxes 389 00:20:33,119 --> 00:20:36,480 Speaker 5: and how much taxes the wealthy actually pay. And so 390 00:20:36,920 --> 00:20:40,240 Speaker 5: I think what's better is to say, you know, wealthy 391 00:20:40,280 --> 00:20:43,520 Speaker 5: people need to pay taxes just like the rest of us, 392 00:20:43,680 --> 00:20:45,960 Speaker 5: not that they need extra taxes that we're going to 393 00:20:46,000 --> 00:20:48,920 Speaker 5: specifically impose on them, But they need to We need 394 00:20:48,960 --> 00:20:53,479 Speaker 5: to adjust our rules because right now, our rules allow 395 00:20:53,560 --> 00:20:58,719 Speaker 5: the wealthy to acquire just exorbitant amounts of wealth entirely 396 00:20:58,800 --> 00:21:00,760 Speaker 5: tax free, and for them it's optional. 397 00:21:00,840 --> 00:21:00,919 Speaker 6: Right. 398 00:21:01,000 --> 00:21:03,040 Speaker 5: That's why you have to wonder, like, why do we 399 00:21:03,119 --> 00:21:06,879 Speaker 5: hear things like when Elon Musk says, you know, should 400 00:21:06,880 --> 00:21:09,320 Speaker 5: I pay taxes or shouldn't I pay taxes? Right, he 401 00:21:09,320 --> 00:21:14,119 Speaker 5: asked his Twitter viewers, or Warren Buffett says, well, I 402 00:21:14,160 --> 00:21:17,160 Speaker 5: think I do better by not paying taxes, not paying 403 00:21:17,200 --> 00:21:20,040 Speaker 5: down the national debt, and instead giving to my philanthropy. 404 00:21:20,480 --> 00:21:23,399 Speaker 5: Somebody who earns a salary cannot make that decision that 405 00:21:23,440 --> 00:21:26,919 Speaker 5: they're going to not pay taxes and instead donate to charity. 406 00:21:26,960 --> 00:21:30,000 Speaker 5: So why are we letting our wealthy treat taxes as 407 00:21:30,000 --> 00:21:32,640 Speaker 5: an option rather than as an obligation that we all 408 00:21:32,680 --> 00:21:33,280 Speaker 5: have to share. 409 00:21:33,560 --> 00:21:35,879 Speaker 2: Is there any country that's really done a really good 410 00:21:36,000 --> 00:21:38,520 Speaker 2: job of this or is it just really tricky to 411 00:21:38,600 --> 00:21:41,320 Speaker 2: tax people who have a lot of resources. 412 00:21:41,560 --> 00:21:43,680 Speaker 5: I don't think it's really tricky to tax I don't 413 00:21:43,680 --> 00:21:47,119 Speaker 5: think that's the actual problem. We easily could tax our 414 00:21:47,160 --> 00:21:51,320 Speaker 5: wealthiest Americans by adopting one role that was proposed by 415 00:21:51,320 --> 00:21:55,320 Speaker 5: both Barack Obama and Richard Nixon, which was an odd 416 00:21:55,359 --> 00:21:58,960 Speaker 5: pairing right, which was that we tax these gains at 417 00:21:59,040 --> 00:22:02,920 Speaker 5: whenever the property is transferred instead of requiring sale. Right, 418 00:22:03,000 --> 00:22:06,399 Speaker 5: we should say when these people transfer their property by gifts, 419 00:22:06,440 --> 00:22:09,000 Speaker 5: which they're doing a lot of gifting or a death, 420 00:22:09,080 --> 00:22:11,960 Speaker 5: they're going to recognize the gains then. And then the 421 00:22:12,040 --> 00:22:13,760 Speaker 5: other thing that we need to do is to tax 422 00:22:13,800 --> 00:22:17,359 Speaker 5: inheritances by pulling them into the income tax system, because 423 00:22:17,400 --> 00:22:21,240 Speaker 5: inheritances right now, are you know? The current estate tax 424 00:22:21,280 --> 00:22:24,919 Speaker 5: system is so deeply flawed it's not even a tax system. 425 00:22:25,200 --> 00:22:27,200 Speaker 5: And then I think we could also adjust the rules 426 00:22:27,200 --> 00:22:29,800 Speaker 5: of philanthropy, and then we'd have a system that I 427 00:22:29,840 --> 00:22:33,240 Speaker 5: think does a pretty good job of treating everybody the same, 428 00:22:33,280 --> 00:22:36,520 Speaker 5: bringing everybody into the tax system, and requiring everyone to 429 00:22:36,640 --> 00:22:39,120 Speaker 5: contribute to supporting the costs of government. 430 00:22:39,280 --> 00:22:40,520 Speaker 4: Ray before we let you go. 431 00:22:40,760 --> 00:22:43,679 Speaker 3: I mean, these these failures in the tax code have 432 00:22:43,720 --> 00:22:47,520 Speaker 3: been around for decades. Warren Buffett wrote the famous twenty 433 00:22:47,640 --> 00:22:50,520 Speaker 3: eleven New York Times hotbed pointing out that a secretary 434 00:22:50,560 --> 00:22:53,760 Speaker 3: paid a higher tax rate than he did, So I mean, 435 00:22:53,840 --> 00:22:56,399 Speaker 3: is there any reason to think that maybe this California 436 00:22:56,440 --> 00:23:00,679 Speaker 3: ballot proposition, despite its flaws, becomes a kind of inciting 437 00:23:00,720 --> 00:23:03,080 Speaker 3: moment where we can have a kind of more clear 438 00:23:03,119 --> 00:23:06,760 Speaker 3: eyed and rational discussion about how the rich pay taxes. 439 00:23:07,680 --> 00:23:11,320 Speaker 5: Absolutely, because I think one great thing about this California 440 00:23:11,359 --> 00:23:13,919 Speaker 5: and frankly the other states that are doing it, is 441 00:23:13,960 --> 00:23:17,159 Speaker 5: that it's really shining a light on the fact that 442 00:23:17,200 --> 00:23:21,080 Speaker 5: the wealthiest Americans are in fact not paying taxes and 443 00:23:21,200 --> 00:23:25,040 Speaker 5: don't have to pay taxes, and so this this moves 444 00:23:25,080 --> 00:23:28,760 Speaker 5: the needle forward, right instead of having confusion like are 445 00:23:28,800 --> 00:23:31,199 Speaker 5: the rich paying a lot of taxes or not? You 446 00:23:31,240 --> 00:23:34,960 Speaker 5: don't really see those discussions. Mostly people say, oh, yeah, 447 00:23:35,000 --> 00:23:36,760 Speaker 5: the rich aren't paying taxes, and how are we going 448 00:23:36,800 --> 00:23:39,720 Speaker 5: to address it as a problem. So I actually think, well, 449 00:23:39,720 --> 00:23:43,919 Speaker 5: I'm not in particular favor of this wealth tax. I 450 00:23:43,960 --> 00:23:47,000 Speaker 5: think it is a very positive change for getting a 451 00:23:47,040 --> 00:23:50,600 Speaker 5: fairer tax system because it's opening up conversations just like 452 00:23:50,680 --> 00:23:54,520 Speaker 5: this where we actually see how the wealthy avoid taxes 453 00:23:54,600 --> 00:23:57,880 Speaker 5: because they avoid taxes on their salaries and on their 454 00:23:57,880 --> 00:23:59,640 Speaker 5: gains and on their inheritances. 455 00:24:00,080 --> 00:24:04,200 Speaker 3: So, Stacy, my takeaway is that we're the suckers earning salaries. 456 00:24:04,440 --> 00:24:05,760 Speaker 4: I know their taxes. 457 00:24:06,080 --> 00:24:09,480 Speaker 2: That's going to that's going to haunt. The salaries are 458 00:24:09,480 --> 00:24:10,800 Speaker 2: for suckers, is going to hant. 459 00:24:11,200 --> 00:24:11,560 Speaker 4: Hooray. 460 00:24:11,720 --> 00:24:15,719 Speaker 3: Thank you for bringing that to our attentions, and thanks 461 00:24:15,760 --> 00:24:18,560 Speaker 3: for being here as a guest on everybody's business. 462 00:24:18,800 --> 00:24:20,640 Speaker 5: Thank you so much, wonderful being here. 463 00:24:20,680 --> 00:24:30,240 Speaker 2: Thank you. Okay, Brad, let us set the trillionaires aside 464 00:24:30,400 --> 00:24:33,760 Speaker 2: for the moment to talk about a slightly different topic, 465 00:24:33,880 --> 00:24:39,880 Speaker 2: although another cohort that does command an enormous economic power. 466 00:24:39,760 --> 00:24:45,200 Speaker 3: With perhaps just as much mystique as the trillionaire's Jim Alpha. Stacy, 467 00:24:45,280 --> 00:24:48,560 Speaker 3: So kids between the ages of I guess is you 468 00:24:48,600 --> 00:24:52,480 Speaker 3: know just born and around sixteen. We have a whole 469 00:24:52,480 --> 00:24:55,480 Speaker 3: package and the current issue of Business Week about Generation 470 00:24:55,600 --> 00:24:58,159 Speaker 3: Alpha as a potent economic force. 471 00:24:58,600 --> 00:25:01,479 Speaker 2: One of the really surprising things about Gen Alpha is 472 00:25:01,560 --> 00:25:03,800 Speaker 2: that even though most of them aren't earning their own 473 00:25:03,880 --> 00:25:06,960 Speaker 2: money yet, a lot of them are commanding a lot 474 00:25:07,000 --> 00:25:09,640 Speaker 2: of money or wielding a lot of economic power within 475 00:25:09,640 --> 00:25:12,800 Speaker 2: their families. I mean, I know you have children, Brad, 476 00:25:12,920 --> 00:25:15,760 Speaker 2: or how much control do they have over how your 477 00:25:15,760 --> 00:25:16,280 Speaker 2: family spends? 478 00:25:16,359 --> 00:25:18,639 Speaker 3: They're a little older, they're not Jen Alpha, but I 479 00:25:18,640 --> 00:25:21,879 Speaker 3: would say Stacy they have all the control and really, 480 00:25:22,080 --> 00:25:22,760 Speaker 3: oh yeah. 481 00:25:22,600 --> 00:25:24,680 Speaker 2: Over like where you guys go on vacation, what you eat? 482 00:25:24,800 --> 00:25:26,320 Speaker 2: We just say streaming service. 483 00:25:26,760 --> 00:25:27,920 Speaker 4: Let's just say they're formidable. 484 00:25:28,200 --> 00:25:31,000 Speaker 3: But the thing ahead, you know, Jen Alpha, they get 485 00:25:31,040 --> 00:25:36,359 Speaker 3: interested earlier in cultural trends, in beauty products and influencers, 486 00:25:36,720 --> 00:25:41,000 Speaker 3: and so they are a force that companies have to understand. 487 00:25:41,359 --> 00:25:45,159 Speaker 2: Well, Brad, before Max whisked off to the Olympics, we 488 00:25:45,200 --> 00:25:48,120 Speaker 2: did have a conversation about Gen Alpha. Both of us 489 00:25:48,160 --> 00:25:51,880 Speaker 2: wrote articles for the Gen Alpha issue and Max actually 490 00:25:52,240 --> 00:25:55,440 Speaker 2: talked to his children for the story, and we learned 491 00:25:55,440 --> 00:25:59,119 Speaker 2: all kinds of things about this generation. It's economic muscle 492 00:25:59,240 --> 00:26:01,920 Speaker 2: and also some of the traits that it's starting to show, which, 493 00:26:01,920 --> 00:26:06,320 Speaker 2: of course companies and people everywhere are very interested. 494 00:26:05,920 --> 00:26:07,960 Speaker 4: In, very curious to hear what you found out. 495 00:26:08,200 --> 00:26:09,119 Speaker 2: Let's roll the tape. 496 00:26:09,560 --> 00:26:12,119 Speaker 6: I am a, as you know, Stacy, very serious journalist, 497 00:26:12,560 --> 00:26:14,880 Speaker 6: and so in preparation for this segment, I went out 498 00:26:15,000 --> 00:26:18,520 Speaker 6: and I did some reporting. I gathered some important tape 499 00:26:18,600 --> 00:26:21,320 Speaker 6: with some important Gen Alphas that I know. This is 500 00:26:21,320 --> 00:26:26,000 Speaker 6: my daughter Alice, her best friend Olive, and then my 501 00:26:26,359 --> 00:26:31,560 Speaker 6: son saw these are ages eleven, ten and nine. So 502 00:26:31,960 --> 00:26:34,520 Speaker 6: the sweet spot of gen Alpha, and I wanted to 503 00:26:34,560 --> 00:26:37,560 Speaker 6: just ask them, okay, like, what do you guys think 504 00:26:37,720 --> 00:26:40,120 Speaker 6: is cool? Because to your post, this. 505 00:26:40,119 --> 00:26:41,320 Speaker 2: Is a million corporations. 506 00:26:41,359 --> 00:26:45,919 Speaker 7: They're asking us a very eensive question, discretionary spending. What 507 00:26:46,160 --> 00:26:50,040 Speaker 7: I have is so valuable, like the CEOs of some 508 00:26:50,080 --> 00:26:52,320 Speaker 7: of the most important and valuable. 509 00:26:51,960 --> 00:26:56,840 Speaker 2: Companies selling giving it to us for free on everybody's generous. 510 00:26:56,600 --> 00:26:57,560 Speaker 4: So let's give a listen. 511 00:26:57,680 --> 00:27:00,760 Speaker 6: This is sort of a quick focus group on some 512 00:27:01,000 --> 00:27:04,440 Speaker 6: trends that are big or not big among the alphas. 513 00:27:04,760 --> 00:27:06,800 Speaker 4: All right, Minecraft and. 514 00:27:06,840 --> 00:27:10,359 Speaker 8: Roadblocks road Minecraft's okay. 515 00:27:10,359 --> 00:27:14,560 Speaker 6: Taylor Swift bad Bunny good artist kid Rock? 516 00:27:16,320 --> 00:27:17,040 Speaker 8: How would I know? 517 00:27:17,640 --> 00:27:20,240 Speaker 4: Pokemon millennials? 518 00:27:20,840 --> 00:27:21,800 Speaker 2: What I don't know? 519 00:27:22,920 --> 00:27:31,440 Speaker 4: iPads okay, TikTok, don't do scroll kids, horrible, cyber trucks, 520 00:27:31,760 --> 00:27:33,560 Speaker 4: garbage trucks. 521 00:27:33,560 --> 00:27:45,960 Speaker 8: Six seven, it's over cats eye as sucks, skinny jeans t. 522 00:27:45,359 --> 00:27:48,080 Speaker 2: Gnarly is gnarly good or bad? 523 00:27:48,080 --> 00:27:49,240 Speaker 4: You didn't catch that reference. 524 00:27:49,320 --> 00:27:52,840 Speaker 6: That's it gets from a cat's eye song called Gnarly. 525 00:27:53,240 --> 00:27:57,880 Speaker 4: And it's also big and gnarly. It could be good 526 00:27:57,960 --> 00:27:58,240 Speaker 4: or bad. 527 00:27:58,240 --> 00:28:00,880 Speaker 6: It means it means awesome, it means gross, it means 528 00:28:00,920 --> 00:28:03,000 Speaker 6: all the things they love Bobati, though I can tell 529 00:28:03,000 --> 00:28:07,320 Speaker 6: you now, I gotta say, so you reacted to my 530 00:28:07,480 --> 00:28:12,439 Speaker 6: kids talking about technology and saying that you know Instagram, 531 00:28:12,520 --> 00:28:14,760 Speaker 6: and I'll have said the same thing, you know Instagram, 532 00:28:14,760 --> 00:28:15,760 Speaker 6: taktok poison. 533 00:28:15,520 --> 00:28:16,359 Speaker 2: Poison for your brain. 534 00:28:16,480 --> 00:28:17,360 Speaker 4: So I wrote about this. 535 00:28:17,359 --> 00:28:18,000 Speaker 2: It's not wrong. 536 00:28:18,040 --> 00:28:20,600 Speaker 4: I wrote about this in the latest sits Business Week. 537 00:28:20,520 --> 00:28:25,680 Speaker 6: And I really think that this idea that alphas are 538 00:28:25,720 --> 00:28:28,560 Speaker 6: the most online generation. You see this show up all 539 00:28:28,560 --> 00:28:31,879 Speaker 6: the time. It even shows up sometimes in surveys. I 540 00:28:31,920 --> 00:28:34,399 Speaker 6: don't know that that's totally true, or it may be 541 00:28:34,600 --> 00:28:37,919 Speaker 6: missing a part of the story, because it's true that 542 00:28:38,080 --> 00:28:41,120 Speaker 6: although alphas do have a lot of screen time, and 543 00:28:41,360 --> 00:28:43,680 Speaker 6: you brought up COVID this this time where all these 544 00:28:43,800 --> 00:28:47,600 Speaker 6: kids were just like basically plugged into screens twenty four 545 00:28:47,600 --> 00:28:51,959 Speaker 6: to seven, but they've also kind of internalized a lot 546 00:28:52,000 --> 00:28:55,640 Speaker 6: of the skepticism about screens that their parents have as well. 547 00:28:55,720 --> 00:28:57,760 Speaker 4: And I hear that in my own house. 548 00:28:57,760 --> 00:28:59,440 Speaker 6: And this is the thing I wanted to write about, 549 00:28:59,440 --> 00:29:03,920 Speaker 6: which is like I read a lot about parents and 550 00:29:04,000 --> 00:29:06,560 Speaker 6: children getting into fights about screen time, and the way 551 00:29:06,600 --> 00:29:10,200 Speaker 6: it's always described is like a parent saying that I 552 00:29:10,240 --> 00:29:12,600 Speaker 6: am in a big fight with my kid about screen time. 553 00:29:12,640 --> 00:29:15,240 Speaker 6: They will not get off TikTok at the dining room table. 554 00:29:15,560 --> 00:29:17,200 Speaker 6: And these kids are often a little bit older than 555 00:29:17,200 --> 00:29:19,880 Speaker 6: my kids. But the big fight in my house over 556 00:29:19,920 --> 00:29:22,920 Speaker 6: screen time is my kids like yelling at me, and 557 00:29:22,960 --> 00:29:25,320 Speaker 6: they're the ones being like, get off your phone, deck, 558 00:29:25,360 --> 00:29:27,600 Speaker 6: get off your phone. And I really think and it 559 00:29:27,640 --> 00:29:29,720 Speaker 6: shows up in some of the surveys. So there's some 560 00:29:29,840 --> 00:29:34,080 Speaker 6: Pew data about kids feelings about social media. And a 561 00:29:34,080 --> 00:29:37,480 Speaker 6: few years ago, like three years ago, it was kids 562 00:29:37,520 --> 00:29:41,560 Speaker 6: thought that social media was basically good and it is 563 00:29:41,640 --> 00:29:44,880 Speaker 6: totally flipped where now the numbers say just the opposite. 564 00:29:44,920 --> 00:29:46,400 Speaker 4: I should pull this up really quick. 565 00:29:46,760 --> 00:29:51,320 Speaker 6: Twenty twenty two, they as teenagers, is social media mostly 566 00:29:51,320 --> 00:29:54,120 Speaker 6: good or mostly bad for people your age? And at 567 00:29:54,160 --> 00:29:58,000 Speaker 6: the time, thirty two percent said that it was mostly bad, 568 00:29:58,080 --> 00:30:01,120 Speaker 6: twenty four percent said that was mostly good, so slightly negative. 569 00:30:01,320 --> 00:30:06,040 Speaker 6: Today eleven percent mostly good, forty eight percent mostly bad. 570 00:30:06,080 --> 00:30:09,120 Speaker 6: So basically a lot of kids are at least aware 571 00:30:09,160 --> 00:30:12,520 Speaker 6: of this. That doesn't necessarily mean that they're not doing it. 572 00:30:12,840 --> 00:30:15,760 Speaker 6: But I think this is something that big companies are 573 00:30:15,840 --> 00:30:20,160 Speaker 6: going to have to reckon with, not only because kids 574 00:30:20,240 --> 00:30:23,320 Speaker 6: may not be quite as brain poisoned as their parents. Like, 575 00:30:23,360 --> 00:30:27,680 Speaker 6: I think our generation, especially maybe people a little younger 576 00:30:27,760 --> 00:30:30,720 Speaker 6: than you and I who really grew up on the Internet. 577 00:30:31,200 --> 00:30:33,400 Speaker 6: I think we are the ones maybe who have like 578 00:30:33,480 --> 00:30:37,840 Speaker 6: the least healthy habits around screens, whereas some of these 579 00:30:37,920 --> 00:30:41,040 Speaker 6: quote unquote digital natives are actually maybe a little bit 580 00:30:41,080 --> 00:30:45,600 Speaker 6: better able to kind of compartmentalize. And then you also 581 00:30:45,760 --> 00:30:48,760 Speaker 6: have you know, all of these countries are passing laws now. 582 00:30:48,840 --> 00:30:52,360 Speaker 6: So Australia just passed a rule saying kids under sixteen 583 00:30:52,360 --> 00:30:55,080 Speaker 6: are not algy social media. That Spain is doing it, 584 00:30:55,160 --> 00:30:56,800 Speaker 6: the UK is doing it, a lot of US states 585 00:30:56,840 --> 00:31:00,040 Speaker 6: are doing it. There is a shift happening, and I 586 00:31:00,040 --> 00:31:01,680 Speaker 6: don't think any of us really know where it's going 587 00:31:01,720 --> 00:31:01,920 Speaker 6: to go. 588 00:31:02,720 --> 00:31:07,160 Speaker 2: I wonder what AI is going to throw into this mix, 589 00:31:07,240 --> 00:31:10,080 Speaker 2: because I do think just the way people are interacting 590 00:31:10,080 --> 00:31:13,719 Speaker 2: with AI now, maybe not not such young kids, but 591 00:31:13,760 --> 00:31:17,600 Speaker 2: maybe older alphas, because people have like very personal conversations 592 00:31:17,600 --> 00:31:19,000 Speaker 2: with AI or asked advice. 593 00:31:19,280 --> 00:31:21,040 Speaker 6: Yeah, when I was reporting this story, I talked to 594 00:31:21,160 --> 00:31:24,840 Speaker 6: John Heit, who is the author of The Anxious Generation, 595 00:31:24,920 --> 00:31:29,000 Speaker 6: which is this best selling book. He's an NYU social psychologist, 596 00:31:29,480 --> 00:31:33,320 Speaker 6: and he's like the guy who created a lot of 597 00:31:33,360 --> 00:31:36,720 Speaker 6: the kind of conversation going on right now around screen time, 598 00:31:36,920 --> 00:31:42,200 Speaker 6: and he says essentially that AI is like social media, 599 00:31:42,240 --> 00:31:44,640 Speaker 6: but a million times worse, because part of the problem 600 00:31:44,720 --> 00:31:47,640 Speaker 6: with social media for kids and for development is that 601 00:31:47,880 --> 00:31:51,520 Speaker 6: it kind of like takes kids away from like human connections. 602 00:31:51,800 --> 00:31:54,800 Speaker 6: But with AI, there's no connection at all. It's just 603 00:31:55,240 --> 00:31:56,240 Speaker 6: a bot making. 604 00:31:56,400 --> 00:31:57,800 Speaker 2: Connecting, but maybe not with a human. 605 00:31:58,000 --> 00:32:00,160 Speaker 6: Yeah, and so you know, he's told me, you know, 606 00:32:00,200 --> 00:32:02,760 Speaker 6: I think it's the worst way you could possibly bring 607 00:32:02,840 --> 00:32:03,360 Speaker 6: up a kid. 608 00:32:04,160 --> 00:32:06,640 Speaker 4: I do think those concerns are out there. 609 00:32:06,880 --> 00:32:10,000 Speaker 6: And unlike with social media, where there was like a 610 00:32:10,040 --> 00:32:13,800 Speaker 6: ten year period where pretty much tech companies did whatever 611 00:32:13,840 --> 00:32:18,360 Speaker 6: they wanted. They were marketing Facebook and Instagram to very 612 00:32:18,400 --> 00:32:20,640 Speaker 6: young children, and there was an effort that was that 613 00:32:21,120 --> 00:32:23,280 Speaker 6: it kind of got derailed, but they even wanted to go, 614 00:32:23,560 --> 00:32:24,880 Speaker 6: you know, younger than thirteen. 615 00:32:24,920 --> 00:32:26,920 Speaker 4: They were gonna have like nine year olds. 616 00:32:26,600 --> 00:32:29,719 Speaker 6: On on these social media platforms, which when you think 617 00:32:29,760 --> 00:32:31,400 Speaker 6: about it, I don't know, as a parent, it seems 618 00:32:31,440 --> 00:32:34,080 Speaker 6: kind of crazy. The conversation now is very different. I 619 00:32:34,080 --> 00:32:36,880 Speaker 6: also will say when I talk to my kids about AI, 620 00:32:37,280 --> 00:32:38,240 Speaker 6: they don't like AI. 621 00:32:38,360 --> 00:32:39,800 Speaker 4: They think it's dumb, and. 622 00:32:39,920 --> 00:32:43,200 Speaker 6: Maybe this is partly because because they're you know, they're 623 00:32:43,240 --> 00:32:46,080 Speaker 6: my kids, and they hear my a skepticism. But I 624 00:32:46,080 --> 00:32:47,920 Speaker 6: don't know that that's totally true. I think a lot 625 00:32:48,000 --> 00:32:50,200 Speaker 6: of kids are actually kind of aware of the limitation. 626 00:32:50,280 --> 00:32:53,120 Speaker 6: I was talking the other day with my daughter Alice 627 00:32:53,160 --> 00:32:55,400 Speaker 6: and one of her friends, and they were saying, oh, 628 00:32:55,440 --> 00:32:57,040 Speaker 6: it would have been so great to grow up in 629 00:32:57,120 --> 00:32:59,000 Speaker 6: the eighties. And I was like, why, why would it 630 00:32:59,080 --> 00:33:00,680 Speaker 6: be so great to grow up in the eighties, and 631 00:33:00,720 --> 00:33:03,760 Speaker 6: they said, well, you could go to movie theaters and 632 00:33:04,080 --> 00:33:07,240 Speaker 6: talking about these kind of retro experiences. Alice is super 633 00:33:07,280 --> 00:33:10,320 Speaker 6: into CDs, which is funny, and then she goes, yeah, 634 00:33:10,360 --> 00:33:13,600 Speaker 6: your generation's so lucky, and I said why and she goes, well, 635 00:33:13,640 --> 00:33:17,440 Speaker 6: you haven't had your brains poisoned by AI. And I said, well, Alice, 636 00:33:17,440 --> 00:33:20,560 Speaker 6: you don't have to use AI, and she goes, it's everywhere. 637 00:33:20,840 --> 00:33:23,160 Speaker 6: I try to search for a fat frog on Google 638 00:33:23,200 --> 00:33:24,600 Speaker 6: and I get a bunch of AI. She was really 639 00:33:24,600 --> 00:33:27,160 Speaker 6: disturbed by the fact that the Google results for fat 640 00:33:27,200 --> 00:33:28,560 Speaker 6: frog was AI. 641 00:33:29,000 --> 00:33:31,040 Speaker 2: I now want a Google fat frog. But I think 642 00:33:31,080 --> 00:33:34,600 Speaker 2: she's right in that. I mean, because companies are adopting it, 643 00:33:34,600 --> 00:33:37,280 Speaker 2: it may be hard to not use it, and then 644 00:33:37,320 --> 00:33:40,000 Speaker 2: when you start using it, it may be hard to 645 00:33:40,080 --> 00:33:42,600 Speaker 2: not kind of veer into a more personal relationship. But 646 00:33:43,240 --> 00:33:45,440 Speaker 2: also maybe there's more of an awareness now than there 647 00:33:45,560 --> 00:33:47,680 Speaker 2: was when social media started, because that was such a 648 00:33:47,720 --> 00:33:51,520 Speaker 2: new thing, and maybe there wasn't as much of an awareness. Also, 649 00:33:52,240 --> 00:33:55,080 Speaker 2: I think because you were connecting with other people, maybe 650 00:33:55,080 --> 00:33:57,840 Speaker 2: there was less of a warning flag's going off, because 651 00:33:57,920 --> 00:34:00,120 Speaker 2: I mean, there have been like a million movies and 652 00:34:00,160 --> 00:34:02,120 Speaker 2: books about Rise of the Robots. 653 00:34:02,480 --> 00:34:07,440 Speaker 6: I do think that the kind of screen anxiety that 654 00:34:07,520 --> 00:34:11,320 Speaker 6: the Jonathan Heyde view of the world is seeping into kids. 655 00:34:11,400 --> 00:34:14,319 Speaker 6: When I called him, he told me, you know, if 656 00:34:14,320 --> 00:34:16,400 Speaker 6: you had called me three or four weeks ago, I 657 00:34:16,440 --> 00:34:19,160 Speaker 6: would have told you your kids are freaks. But he 658 00:34:19,280 --> 00:34:21,839 Speaker 6: had actually just released like a kid's version of his book. 659 00:34:21,840 --> 00:34:25,240 Speaker 6: It's called The Amazing Generation. It's a graphic novel and it's, 660 00:34:25,360 --> 00:34:27,600 Speaker 6: you know, surprisingly, it's sold pretty well, and there are 661 00:34:27,640 --> 00:34:30,959 Speaker 6: all these Amazon reviews of kids being like, I. 662 00:34:30,880 --> 00:34:33,399 Speaker 4: Hope I never get a smartphone and things like that. 663 00:34:33,640 --> 00:34:37,080 Speaker 6: So it may be that kids really have these kind 664 00:34:37,120 --> 00:34:40,440 Speaker 6: of retro values or maybe just absorbing from us, the parents. 665 00:34:40,880 --> 00:34:43,839 Speaker 2: I feel like there can be a gap between knowing 666 00:34:43,880 --> 00:34:45,799 Speaker 2: what's good for you and doing what's good for you, 667 00:34:46,000 --> 00:34:51,200 Speaker 2: and AI makes certain things so easy, including writing papers, 668 00:34:51,280 --> 00:34:55,280 Speaker 2: doing research. I feel like that's going to be really 669 00:34:55,360 --> 00:34:58,080 Speaker 2: hard to I mean, it's like it's so awesome to 670 00:34:58,120 --> 00:35:00,440 Speaker 2: have a flip phone, or it's awesome to g scale 671 00:35:00,480 --> 00:35:02,960 Speaker 2: your phone until you are on deadline. 672 00:35:03,000 --> 00:35:04,480 Speaker 6: I'm so glad you brought that up, because even in 673 00:35:04,520 --> 00:35:08,520 Speaker 6: this Pew survey where kids are saying it's bad for 674 00:35:08,600 --> 00:35:11,640 Speaker 6: their peers, they don't think they are using it badly. 675 00:35:11,760 --> 00:35:13,760 Speaker 4: So there is a bit of a Now. 676 00:35:14,640 --> 00:35:17,440 Speaker 2: I'm personally not addicted to it. I feel like it's 677 00:35:17,480 --> 00:35:19,279 Speaker 2: like the thing with the glass of wine. It's like, 678 00:35:19,680 --> 00:35:21,080 Speaker 2: I mean, I have a glass of wine every night, 679 00:35:21,080 --> 00:35:22,200 Speaker 2: but that's totally different. 680 00:35:22,280 --> 00:35:25,319 Speaker 6: But you know what, like these public health campaigns, they 681 00:35:25,360 --> 00:35:28,240 Speaker 6: work sometimes, And as I have been. 682 00:35:28,080 --> 00:35:30,640 Speaker 2: Thinking, say no to drugs work no. 683 00:35:30,560 --> 00:35:32,880 Speaker 4: But say no to smoking absolutely worked. 684 00:35:33,040 --> 00:35:33,840 Speaker 2: I mean eventually. 685 00:35:34,000 --> 00:35:34,200 Speaker 1: Yeah. 686 00:35:34,760 --> 00:35:37,680 Speaker 6: And when I've thought about the conversations that I have 687 00:35:37,920 --> 00:35:41,120 Speaker 6: at the dinner table with my kids around screen time, 688 00:35:41,440 --> 00:35:44,480 Speaker 6: they really really remind me of conversations I had with 689 00:35:44,560 --> 00:35:47,960 Speaker 6: my parents, members of my parents' generation about cigarettes, where 690 00:35:48,320 --> 00:35:52,640 Speaker 6: I was getting all of this kind of anti tobacco 691 00:35:53,120 --> 00:35:55,479 Speaker 6: information at school and coming home and being like. 692 00:35:55,600 --> 00:35:58,760 Speaker 4: You shouldn't small, you know, oh my god, And that worked. 693 00:35:58,800 --> 00:36:01,440 Speaker 6: I mean, you look at the generational shift on smoking 694 00:36:01,480 --> 00:36:02,760 Speaker 6: and it's been profound. 695 00:36:02,800 --> 00:36:05,200 Speaker 2: Like a member of the generational shift on smoking had 696 00:36:05,200 --> 00:36:06,520 Speaker 2: to do with taxes. 697 00:36:06,680 --> 00:36:08,480 Speaker 4: Sure, but it has made a difference. 698 00:36:08,480 --> 00:36:11,200 Speaker 6: And talking to John Hate about this, what he said 699 00:36:11,280 --> 00:36:13,520 Speaker 6: is and where he kind of compared it. He said, 700 00:36:13,560 --> 00:36:14,920 Speaker 6: you know, one of the things I think that really 701 00:36:15,000 --> 00:36:19,400 Speaker 6: worked on cigarette smoking was in the late nineties, the 702 00:36:19,520 --> 00:36:22,680 Speaker 6: sort of anti tobacco groups. They started sort of demonizing 703 00:36:22,680 --> 00:36:26,000 Speaker 6: the tobacco industry and saying it wasn't really about your health, 704 00:36:26,080 --> 00:36:30,080 Speaker 6: it was about these tobacco companies are manipulating you. They 705 00:36:30,360 --> 00:36:32,800 Speaker 6: are selling you an addictive product, they are making money 706 00:36:32,800 --> 00:36:35,280 Speaker 6: off of you. And I think there's some research showing 707 00:36:35,320 --> 00:36:39,200 Speaker 6: that that marketing that happened in the late nineties was effective. 708 00:36:39,600 --> 00:36:42,839 Speaker 6: And he thinks that some of the messaging around tech 709 00:36:42,880 --> 00:36:46,440 Speaker 6: that's pretty similar. That's all about, you know, Mark Zuckerberg 710 00:36:46,520 --> 00:36:48,040 Speaker 6: is trying to addict you to your phone or whatever, 711 00:36:48,080 --> 00:36:50,440 Speaker 6: just like you heard in my daughter and her friend's statement, 712 00:36:50,480 --> 00:36:51,439 Speaker 6: like it's poison there. 713 00:36:51,560 --> 00:36:55,799 Speaker 4: They're tricking you. Like that sense of a big company getting. 714 00:36:55,560 --> 00:36:59,320 Speaker 6: One over on you is a message that maybe could 715 00:36:59,440 --> 00:37:07,960 Speaker 6: potential breakthrough among among teens and younger kids. 716 00:37:10,360 --> 00:37:12,920 Speaker 2: Brad, it is that time in the show when we 717 00:37:12,960 --> 00:37:15,399 Speaker 2: talk about underrated stories of the week, and you brought 718 00:37:15,480 --> 00:37:17,319 Speaker 2: us an underrated story. What is there. 719 00:37:17,400 --> 00:37:18,360 Speaker 4: Sorry for us? 720 00:37:18,840 --> 00:37:22,880 Speaker 3: Well, Stacy, is Stephen Colbert really ever underrated? I? 721 00:37:22,880 --> 00:37:25,920 Speaker 2: I like him. I think he is very often underrated. 722 00:37:26,200 --> 00:37:26,719 Speaker 4: I do too. 723 00:37:27,160 --> 00:37:29,520 Speaker 3: I think we'll be feeling the reverberations from this week's 724 00:37:29,520 --> 00:37:32,719 Speaker 3: events for a long time. First, on Monday, he wanted 725 00:37:32,800 --> 00:37:34,880 Speaker 3: us a program The Late Show. As you probably heard, 726 00:37:35,120 --> 00:37:39,040 Speaker 3: and said lawyers at CBS, his bosses had blocked him 727 00:37:39,040 --> 00:37:42,320 Speaker 3: from airing an interview with US Senate candidate from Texas, 728 00:37:42,520 --> 00:37:43,520 Speaker 3: James Tallerico. 729 00:37:43,840 --> 00:37:47,600 Speaker 2: Yes, and from what I understand, he still did get 730 00:37:47,600 --> 00:37:50,120 Speaker 2: the interview out into the world. He uploaded it on 731 00:37:50,160 --> 00:37:54,160 Speaker 2: YouTube and it has been viewed seven million times. 732 00:37:54,440 --> 00:37:57,160 Speaker 1: That I was told, in some uncertain terms that not 733 00:37:57,200 --> 00:37:59,279 Speaker 1: only could I not have him on, I could not 734 00:37:59,440 --> 00:38:05,000 Speaker 1: mention me not having him on. And because my network 735 00:38:05,080 --> 00:38:08,840 Speaker 1: clearly doesn't want us to talk about this, let's talk about. 736 00:38:08,600 --> 00:38:11,800 Speaker 4: This, Stacy. This is a three way battle. 737 00:38:11,880 --> 00:38:16,280 Speaker 3: Federal Communications Commission Chair Brendan Carr, who you might remember 738 00:38:16,360 --> 00:38:20,000 Speaker 3: as Jimmy Kimmel's Foyle, Yes, is trying to enforce those 739 00:38:20,040 --> 00:38:23,160 Speaker 3: old equal time rules on the public airwaves, so if 740 00:38:23,200 --> 00:38:25,200 Speaker 3: you have one candidate, you need to give time to 741 00:38:25,239 --> 00:38:26,000 Speaker 3: their opposition. 742 00:38:26,640 --> 00:38:28,360 Speaker 4: CBS is saying they didn't. 743 00:38:28,120 --> 00:38:31,120 Speaker 3: Force Talerico off the air and simply insists they gave 744 00:38:31,120 --> 00:38:34,640 Speaker 3: the late show options for how to fulfill those equal 745 00:38:34,680 --> 00:38:38,440 Speaker 3: time obligations. And Cobert, who is set to end a 746 00:38:38,480 --> 00:38:41,040 Speaker 3: show on May, I think he just doesn't. 747 00:38:40,760 --> 00:38:42,720 Speaker 4: Give af at this point. 748 00:38:44,200 --> 00:38:46,439 Speaker 3: He went on the air again this week and said 749 00:38:46,480 --> 00:38:49,520 Speaker 3: every word of a script was approved by CBS lawyers, 750 00:38:50,040 --> 00:38:52,160 Speaker 3: and he's fighting well. 751 00:38:52,200 --> 00:38:54,239 Speaker 2: I mean, I have to say the big winner in 752 00:38:54,320 --> 00:38:57,839 Speaker 2: all of this is James Talerico, who says after this 753 00:38:58,280 --> 00:39:02,239 Speaker 2: interview went viral on YouTube, his campaign raised two and 754 00:39:02,280 --> 00:39:05,480 Speaker 2: a half million dollars in twenty four hours, which is 755 00:39:05,640 --> 00:39:06,960 Speaker 2: just mind blowing. 756 00:39:07,200 --> 00:39:10,120 Speaker 3: And that's a way I think the story could be underrated. 757 00:39:10,760 --> 00:39:14,680 Speaker 3: He's competing for Senator John Cornyn seat. He is studying 758 00:39:14,719 --> 00:39:19,640 Speaker 3: to be a Presbyterian minister. He went on Ezra Klein's podcast, 759 00:39:19,960 --> 00:39:23,320 Speaker 3: you can kind of see the Democrats falling in love 760 00:39:23,719 --> 00:39:26,759 Speaker 3: with Tallarico and this incident this week is only going 761 00:39:26,800 --> 00:39:27,880 Speaker 3: to raise his profile. 762 00:39:28,360 --> 00:39:31,040 Speaker 2: I also feel like there's something maybe a larger theme 763 00:39:31,080 --> 00:39:33,600 Speaker 2: going on here too, but about the media and the 764 00:39:33,600 --> 00:39:36,400 Speaker 2: Trump administration. I mean, we just had huge layoffs at 765 00:39:36,400 --> 00:39:41,640 Speaker 2: the Washington Post. Like you said, Jimmy Kimmels also had 766 00:39:41,680 --> 00:39:45,080 Speaker 2: a big run in with the administration. It's really interesting 767 00:39:45,080 --> 00:39:48,040 Speaker 2: to see the administration like quite directly engaging with the 768 00:39:48,080 --> 00:39:50,080 Speaker 2: media in a lot of cases. Although it's unclear if 769 00:39:50,120 --> 00:39:54,799 Speaker 2: that actually happens here, it's definitely a theme right now right. 770 00:39:54,840 --> 00:39:57,080 Speaker 3: I mean, the question is are they trying to enforce 771 00:39:57,200 --> 00:39:59,799 Speaker 3: fairness on the public airways or is this a part 772 00:39:59,800 --> 00:40:02,839 Speaker 3: of and agenda? And I think that question has all 773 00:40:02,880 --> 00:40:06,400 Speaker 3: sorts of impacts, including in the battle over Warner Brothers, 774 00:40:06,640 --> 00:40:08,880 Speaker 3: which could go to Netflix, could go to Paramount and 775 00:40:08,920 --> 00:40:10,320 Speaker 3: of course owned CNN. 776 00:40:10,680 --> 00:40:13,120 Speaker 4: So this is the only beginning of this kind of fight. 777 00:40:18,680 --> 00:40:21,600 Speaker 2: This show is produced by Stacy Wong and Jasmine JT. 778 00:40:21,719 --> 00:40:22,000 Speaker 3: Green. 779 00:40:22,239 --> 00:40:26,400 Speaker 2: Magnus Hendrickson is our supervising producer, Sam Rogan handles engineering, 780 00:40:26,440 --> 00:40:30,520 Speaker 2: and Dave Purcell factchecks. Special thanks to Jeff Muscus, Julia Rubin, 781 00:40:30,640 --> 00:40:33,359 Speaker 2: Maria Ling, and Angel Reccio. If you have a minute. 782 00:40:33,400 --> 00:40:35,680 Speaker 2: Please rate and review the show. It means a lot 783 00:40:35,719 --> 00:40:37,600 Speaker 2: to us. And if you have a story that should 784 00:40:37,640 --> 00:40:40,720 Speaker 2: be our business, send us an email. Everybody's at Bloomberg 785 00:40:40,760 --> 00:40:44,040 Speaker 2: dot net. That's everybody's with an s at Bloomberg dot net. 786 00:40:44,560 --> 00:40:46,520 Speaker 2: Thank you for listening, and see you next week.