1 00:00:02,279 --> 00:00:05,560 Speaker 1: From the heart of where innovation, money and power Colli 2 00:00:06,400 --> 00:00:10,920 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:11,000 --> 00:00:26,840 Speaker 1: Emily Jay I'm only tagging New York and this is 4 00:00:26,880 --> 00:00:30,080 Speaker 1: Bloomberg Technology. Coming up the next hour, Snap plunges more 5 00:00:30,920 --> 00:00:35,040 Speaker 1: after posting its slowest quarterly sales growth since going public. 6 00:00:35,560 --> 00:00:38,479 Speaker 1: This could spell trouble ahead for Twitter and meta results. 7 00:00:38,520 --> 00:00:42,240 Speaker 1: We will discuss plus, are people working more but getting 8 00:00:42,360 --> 00:00:46,040 Speaker 1: less done? That's what Ariana Huffington thinks, But new studies 9 00:00:46,040 --> 00:00:49,680 Speaker 1: show productivity is best if employees have flexibility over when 10 00:00:49,720 --> 00:00:55,160 Speaker 1: they work, not necessarily where. And artificial intelligence is creating 11 00:00:55,160 --> 00:00:58,200 Speaker 1: a new type of artists with the explosion of apps 12 00:00:58,240 --> 00:01:00,880 Speaker 1: like Dolly. Later this hour, oh, we've got the founder 13 00:01:00,920 --> 00:01:05,720 Speaker 1: of the world's first talent agency for AI artists. For 14 00:01:05,800 --> 00:01:07,720 Speaker 1: more on Snap in the future of social media, let's 15 00:01:07,720 --> 00:01:10,800 Speaker 1: bring into Economy founder and editor in chief David Kirkpatrick, 16 00:01:10,840 --> 00:01:15,800 Speaker 1: as well as our own Kurt Wagner. So, David, big picture, 17 00:01:16,080 --> 00:01:18,440 Speaker 1: what are your takeaways here? Well? I think the big 18 00:01:18,480 --> 00:01:22,280 Speaker 1: picture is that the economy is getting worse faster than 19 00:01:22,360 --> 00:01:25,600 Speaker 1: most of us had hoped, and in fact Snap is 20 00:01:25,680 --> 00:01:29,600 Speaker 1: the first prominent victim. Unfortunately, we'll probably see more in 21 00:01:29,640 --> 00:01:32,959 Speaker 1: the near future, Kurt, you know, walk us a little through, 22 00:01:33,240 --> 00:01:35,399 Speaker 1: a little more through the numbers. You know, what are 23 00:01:35,440 --> 00:01:38,200 Speaker 1: you seeing in here, and how does this compared to 24 00:01:38,280 --> 00:01:40,640 Speaker 1: what we've seen in the previous quarters. It was the 25 00:01:40,680 --> 00:01:43,800 Speaker 1: slowest uh, you know, year over year revenue growth that 26 00:01:43,840 --> 00:01:47,200 Speaker 1: we've ever seen from Snap, which is never never a 27 00:01:47,280 --> 00:01:49,520 Speaker 1: sentence you want to say when you're talking about earnings. 28 00:01:49,760 --> 00:01:51,520 Speaker 1: But I think the issue is that, you know, the 29 00:01:51,800 --> 00:01:54,520 Speaker 1: it wasn't that far off of the streets expectations, but 30 00:01:54,560 --> 00:01:56,840 Speaker 1: I think those have already been depressed. Right There was 31 00:01:56,880 --> 00:01:59,400 Speaker 1: already this feeling that it had been a really tough 32 00:01:59,440 --> 00:02:01,960 Speaker 1: summer that a lot of the issues the war in Ukraine, 33 00:02:02,080 --> 00:02:06,600 Speaker 1: certainly the Apple iOS changes had, you know, had a 34 00:02:06,680 --> 00:02:08,320 Speaker 1: serious impact on the business. So I think this was 35 00:02:08,320 --> 00:02:10,840 Speaker 1: considered a low bar for Snap to clear, which they 36 00:02:10,840 --> 00:02:13,520 Speaker 1: didn't do. And as David just mentioned, this is a 37 00:02:13,560 --> 00:02:16,280 Speaker 1: really terrible sign for sort of the rest of the 38 00:02:16,320 --> 00:02:20,280 Speaker 1: digital advertising industry, which hasn't yet reported earnings, will in 39 00:02:20,320 --> 00:02:22,920 Speaker 1: the next couple of weeks. You know. It's just a 40 00:02:23,000 --> 00:02:25,839 Speaker 1: sign that anyone who is trying to make money from 41 00:02:26,040 --> 00:02:28,840 Speaker 1: UH digital ads right now and use your attention. They're 42 00:02:28,880 --> 00:02:31,720 Speaker 1: really struggling for a number of reasons, and Snap, of 43 00:02:31,760 --> 00:02:34,440 Speaker 1: course is the first that have to go. It's interesting, David, 44 00:02:34,480 --> 00:02:37,320 Speaker 1: because you could look at what's happening with Meta trying 45 00:02:37,360 --> 00:02:39,800 Speaker 1: to make this big pivot and Twitter in the middle 46 00:02:39,800 --> 00:02:43,680 Speaker 1: of this legal drama as an opportunity for Snap, and 47 00:02:44,080 --> 00:02:47,600 Speaker 1: it's interesting that it hasn't necessarily been well. You know, 48 00:02:47,800 --> 00:02:50,760 Speaker 1: Snap has the benefit of having a brilliant CEO who's 49 00:02:50,800 --> 00:02:53,640 Speaker 1: at least very focused on the actual business he has, 50 00:02:53,720 --> 00:02:57,040 Speaker 1: unlike Meta, and I have a lot of confidence in 51 00:02:57,080 --> 00:03:00,120 Speaker 1: Evan Spiegel's ability to sort of surf this wave. On 52 00:03:00,160 --> 00:03:02,440 Speaker 1: the other hand, it's it's like a tsunami that's hitting 53 00:03:02,520 --> 00:03:05,880 Speaker 1: him in a way that he didn't expect um And 54 00:03:05,960 --> 00:03:10,320 Speaker 1: you know it's weird because user growth was good, uh, 55 00:03:10,480 --> 00:03:13,239 Speaker 1: revenue wasn't good, but you know, they still lost three 56 00:03:13,280 --> 00:03:16,239 Speaker 1: hundred and sixty million dollars. This company has never made money, 57 00:03:16,680 --> 00:03:18,760 Speaker 1: and it's it's not I don't even know why they 58 00:03:18,800 --> 00:03:21,040 Speaker 1: would do a share by back when they they're going 59 00:03:21,120 --> 00:03:23,760 Speaker 1: to have to conserve cash going into this situation. Can 60 00:03:23,760 --> 00:03:26,960 Speaker 1: you remind us of some of the innovative things that 61 00:03:27,040 --> 00:03:31,400 Speaker 1: Evan Spiegel has been trying Kurt over the last year, 62 00:03:32,120 --> 00:03:34,560 Speaker 1: you know, and he also has a sort of anti 63 00:03:34,600 --> 00:03:39,000 Speaker 1: meta view on the metaverse, which is informing his strategy. Well, 64 00:03:39,160 --> 00:03:41,080 Speaker 1: I'm with David in the sense that I think Evan 65 00:03:41,120 --> 00:03:43,480 Speaker 1: is a really smart person. Uh, and I think that 66 00:03:43,640 --> 00:03:45,560 Speaker 1: as a product thinker, he's one of the best, right, 67 00:03:45,600 --> 00:03:49,000 Speaker 1: I mean, he has been routinely copied by Mark Stuckerberg 68 00:03:49,000 --> 00:03:51,600 Speaker 1: over at Facebook and Meta and and you know, he's 69 00:03:51,640 --> 00:03:53,520 Speaker 1: constantly kind of coming up with new things. And he 70 00:03:53,680 --> 00:03:56,560 Speaker 1: is also focused on augmented reality, similar to Mark Zuckerberg, 71 00:03:56,560 --> 00:03:58,520 Speaker 1: but in a very different way. Right, He's trying to 72 00:03:58,560 --> 00:04:01,840 Speaker 1: build that kind of stuff into the camera, into uh, 73 00:04:01,920 --> 00:04:04,480 Speaker 1: something that people already have in their hands, versus sort 74 00:04:04,480 --> 00:04:07,680 Speaker 1: of like a metaverse idea that's still years off. But 75 00:04:07,760 --> 00:04:09,080 Speaker 1: you know, some of the stuff they tried to do, 76 00:04:09,080 --> 00:04:11,720 Speaker 1: they tried to build a subscription product, right, so they're 77 00:04:11,720 --> 00:04:14,600 Speaker 1: not quite as reliant on advertising, kind of give people 78 00:04:14,960 --> 00:04:18,360 Speaker 1: early access to new features. You know, they've talked about uh, Emily, 79 00:04:18,360 --> 00:04:20,640 Speaker 1: you remember they've done spectacles. They're they're kind of building 80 00:04:20,760 --> 00:04:23,360 Speaker 1: other augmented reality glasses that are that are not here 81 00:04:23,440 --> 00:04:25,760 Speaker 1: yet but are coming. So you know, those are the 82 00:04:25,800 --> 00:04:29,279 Speaker 1: types of projects. I wonder if they'll continue to invest 83 00:04:29,360 --> 00:04:32,120 Speaker 1: in They have started to pull back on anything that 84 00:04:32,160 --> 00:04:35,279 Speaker 1: isn't directly related to revenue and user growth, and I 85 00:04:35,279 --> 00:04:37,360 Speaker 1: think a r you know, while it's certainly something he's 86 00:04:37,360 --> 00:04:39,680 Speaker 1: been passionate about for years, it does make me wonder 87 00:04:39,760 --> 00:04:41,560 Speaker 1: if if they can continue to invest in that in 88 00:04:41,560 --> 00:04:43,600 Speaker 1: the way he would like to, given everything that's going 89 00:04:43,640 --> 00:04:47,720 Speaker 1: on at the company right you know. Meantime, Meta had 90 00:04:47,720 --> 00:04:51,960 Speaker 1: another another high profile executive leaving today, the vice president 91 00:04:52,040 --> 00:04:55,120 Speaker 1: of corporate Development. And obviously, David, You've chronicled so many 92 00:04:55,200 --> 00:04:59,240 Speaker 1: years of Meta and clearly we're moving into a new 93 00:04:59,279 --> 00:05:02,279 Speaker 1: phase that I trust suit you know, surrounding the within 94 00:05:03,120 --> 00:05:07,560 Speaker 1: unlimited deal. Um you know, you know you you you 95 00:05:07,880 --> 00:05:09,960 Speaker 1: used to see more kind of M and A in 96 00:05:09,960 --> 00:05:13,280 Speaker 1: the social media space when there was turmoil and and uh, 97 00:05:13,680 --> 00:05:18,160 Speaker 1: you know resizing if you will like this, but maybe 98 00:05:18,160 --> 00:05:20,120 Speaker 1: in this environment we won't. Right if you're the M 99 00:05:20,160 --> 00:05:22,440 Speaker 1: and A guy at Meta Facebook, you know, what are 100 00:05:22,440 --> 00:05:24,160 Speaker 1: you gonna do right now if the government won't let 101 00:05:24,160 --> 00:05:29,160 Speaker 1: you do anything of substance. Plus, I think it's it's 102 00:05:29,200 --> 00:05:32,640 Speaker 1: increasingly the case that employees throughout Meta, including a lot 103 00:05:32,680 --> 00:05:35,760 Speaker 1: of the senior leaders are feeling somewhat disenchanted. I don't 104 00:05:35,760 --> 00:05:37,880 Speaker 1: know if this is an example of that, but an 105 00:05:37,880 --> 00:05:40,960 Speaker 1: awful lot of senior people have left that company and 106 00:05:41,080 --> 00:05:43,799 Speaker 1: it must be very disheartening to work for a company 107 00:05:44,080 --> 00:05:46,880 Speaker 1: with three and a half billion users whose CEO is 108 00:05:46,920 --> 00:05:50,080 Speaker 1: thinking about something else. I gotta believe that is a 109 00:05:50,080 --> 00:05:54,400 Speaker 1: problem for everybody at that company. Meantime, Kirk, can you 110 00:05:54,440 --> 00:05:58,520 Speaker 1: give us an update on the Twitter situation. We did 111 00:05:58,560 --> 00:06:02,040 Speaker 1: hear a little bit I'm Elon Musk yesterday on the 112 00:06:02,080 --> 00:06:05,719 Speaker 1: Tesla earnings call. You know, Twitter, Twitter's earnings, A car 113 00:06:05,760 --> 00:06:09,839 Speaker 1: coming up pretty soon? How's that gonna work? Um? You know, 114 00:06:09,880 --> 00:06:13,360 Speaker 1: give us the latest. Well, we think they're coming up soon. 115 00:06:13,400 --> 00:06:15,720 Speaker 1: They haven't said an earnings date yet. I'm I'm wondering 116 00:06:15,760 --> 00:06:18,640 Speaker 1: if they're just hoping that this whole thing gets closed 117 00:06:18,839 --> 00:06:20,840 Speaker 1: before that they have to go through with that, right, 118 00:06:20,880 --> 00:06:24,200 Speaker 1: because not only are they already projected I believe I 119 00:06:24,240 --> 00:06:27,040 Speaker 1: saw I start projecting a revenue decline for them as well, 120 00:06:27,080 --> 00:06:28,920 Speaker 1: but you saw what just happened with Snap, Right. The 121 00:06:28,960 --> 00:06:30,479 Speaker 1: last thing they want to do is have to to 122 00:06:30,560 --> 00:06:33,440 Speaker 1: go through something like that publicly while they're still waiting 123 00:06:33,480 --> 00:06:35,559 Speaker 1: for this deal to close. But as you mentioned, Elon 124 00:06:35,600 --> 00:06:38,719 Speaker 1: Musk yesterday on Tesla's earnings, in my opinion, he said 125 00:06:38,800 --> 00:06:40,919 Speaker 1: some stuff that that made me think this deal is 126 00:06:40,960 --> 00:06:43,360 Speaker 1: going to happen, right he was Normally when he talks 127 00:06:43,360 --> 00:06:44,960 Speaker 1: to the deal, he does so in this way where 128 00:06:44,960 --> 00:06:47,680 Speaker 1: he's like, well, you know, if if this thing finally happens, 129 00:06:47,720 --> 00:06:50,360 Speaker 1: maybe this not not yesterday. Yesterday he seemed to say 130 00:06:50,400 --> 00:06:52,600 Speaker 1: he was excited about the deal. He even said I'm 131 00:06:52,640 --> 00:06:56,680 Speaker 1: over paying for the deal. But you know, it wasn't that. Um. 132 00:06:56,720 --> 00:06:59,600 Speaker 1: It was suggesting that he's, you know, already done this thing. 133 00:06:59,680 --> 00:07:01,080 Speaker 1: I don't know. I just got the sense when I 134 00:07:01,120 --> 00:07:03,280 Speaker 1: listened to it that I walked away that he feels 135 00:07:03,279 --> 00:07:05,240 Speaker 1: this thing is done. And if he feels it's done, 136 00:07:05,240 --> 00:07:07,040 Speaker 1: of course, well that makes me think it's going to 137 00:07:07,080 --> 00:07:09,960 Speaker 1: get done as well. David, what do you think? I mean, Gosh, 138 00:07:10,000 --> 00:07:13,160 Speaker 1: we're about to enter a very new era. Well, the 139 00:07:13,280 --> 00:07:16,960 Speaker 1: eras are just cascading in on us in so many ways. 140 00:07:17,760 --> 00:07:20,040 Speaker 1: I I don't know what it's going to be to 141 00:07:20,080 --> 00:07:22,720 Speaker 1: have Twitter owned by Elon Musk. I'm not sure it's 142 00:07:22,720 --> 00:07:26,120 Speaker 1: all bad. You know, Elon Musk is the ultimate you 143 00:07:26,160 --> 00:07:30,920 Speaker 1: know cipher because he's so brilliant and so important as 144 00:07:30,920 --> 00:07:34,400 Speaker 1: an innovator and so crazy, and putting those two things 145 00:07:34,440 --> 00:07:38,400 Speaker 1: together is extremely difficult, especially predicting the future. But do 146 00:07:38,440 --> 00:07:40,480 Speaker 1: you think there's going to be a huge brain train 147 00:07:40,680 --> 00:07:43,080 Speaker 1: or maybe maybe there'll be an influx of of people 148 00:07:43,120 --> 00:07:45,920 Speaker 1: going to Twitter who want to work for him, And 149 00:07:45,920 --> 00:07:48,080 Speaker 1: there's certainly going to be a time of transition, and gosh, 150 00:07:48,120 --> 00:07:50,760 Speaker 1: what happens to the platform in the middle of this 151 00:07:50,800 --> 00:07:53,720 Speaker 1: transition experience. A bunch of top people are definitely going 152 00:07:53,760 --> 00:07:55,920 Speaker 1: to leave because he's insulted them in the course of 153 00:07:55,960 --> 00:07:58,920 Speaker 1: this this process. For one thing, I think he does 154 00:07:59,000 --> 00:08:00,920 Speaker 1: have people who want to work with him. I mean, 155 00:08:01,160 --> 00:08:04,640 Speaker 1: he he is a brilliant manager and and maybe that's 156 00:08:04,800 --> 00:08:07,160 Speaker 1: an asset. I I one of the things that he 157 00:08:07,160 --> 00:08:10,720 Speaker 1: always talks about, which I really like, is genuine identity 158 00:08:10,800 --> 00:08:13,400 Speaker 1: for Twitter users. If they were to do that, it 159 00:08:13,440 --> 00:08:16,200 Speaker 1: would fundamentally change the platform. And I would love to 160 00:08:16,200 --> 00:08:20,200 Speaker 1: watch that because I don't like anonymous social media myself. Kurt, 161 00:08:20,240 --> 00:08:22,720 Speaker 1: I see smiling. You know where are you on this? 162 00:08:22,840 --> 00:08:26,400 Speaker 1: Where Twitter employees on this? Well, I'm smiling because I'm 163 00:08:26,400 --> 00:08:30,000 Speaker 1: a green with what David said. I think, um both 164 00:08:30,120 --> 00:08:32,079 Speaker 1: that there will be a brain drain. And at the 165 00:08:32,120 --> 00:08:33,880 Speaker 1: same time that there are plenty of people who would 166 00:08:33,880 --> 00:08:36,000 Speaker 1: love to work with Elon Musko will be lining up 167 00:08:36,040 --> 00:08:38,600 Speaker 1: and and throwing their resumes at Twitter if if he 168 00:08:38,640 --> 00:08:40,679 Speaker 1: gets this company. So I think it will sort of 169 00:08:40,720 --> 00:08:42,640 Speaker 1: be maybe a changing of the guard if you will 170 00:08:43,080 --> 00:08:45,880 Speaker 1: um at the company soon. And as David said, I 171 00:08:46,000 --> 00:08:48,240 Speaker 1: you know, I am thinking that the biggest change is 172 00:08:48,240 --> 00:08:50,360 Speaker 1: going to be around the content policy, right, and all 173 00:08:50,360 --> 00:08:52,240 Speaker 1: this stuff Twitter has been trying to do to make 174 00:08:52,280 --> 00:08:56,400 Speaker 1: itself less terrible, less toxic for years, Right, We've been 175 00:08:56,440 --> 00:08:58,319 Speaker 1: talking about this, They've been putting all these rules and 176 00:08:58,600 --> 00:09:00,720 Speaker 1: policies in place, and it get the sense that he 177 00:09:00,760 --> 00:09:02,840 Speaker 1: just wants to rip those out. He wants to gut that. 178 00:09:03,200 --> 00:09:05,400 Speaker 1: And so, you know, it'll be interesting to see what 179 00:09:05,480 --> 00:09:08,760 Speaker 1: the culture on Twitter feels like a year from now 180 00:09:09,040 --> 00:09:11,600 Speaker 1: if he takes over, because it may feel very much 181 00:09:11,600 --> 00:09:17,520 Speaker 1: like it did in than it does today. Change coming indeed, 182 00:09:17,640 --> 00:09:21,200 Speaker 1: all right, Kurt Wagner, thank you to Economy is David Kirkpatrick. 183 00:09:21,320 --> 00:09:23,720 Speaker 1: Always good to see you and here in person to 184 00:09:24,040 --> 00:09:34,920 Speaker 1: appreciate it. Supply, chain pain is still wreaking havoc in 185 00:09:34,960 --> 00:09:37,920 Speaker 1: our post pandemic world, a wake up call about the 186 00:09:37,960 --> 00:09:42,640 Speaker 1: inherent precariousness of global trade and maybe even globalization itself. 187 00:09:42,679 --> 00:09:45,200 Speaker 1: That is the topic of a new book, Homecoming, The 188 00:09:45,240 --> 00:09:49,200 Speaker 1: Path to Prosperity in a Post global World, author and 189 00:09:49,280 --> 00:09:51,840 Speaker 1: Financial Times calling this, Rona fu Hard joins us. Now 190 00:09:52,280 --> 00:09:55,800 Speaker 1: for more on this. So, Rana, you know we've heard 191 00:09:55,840 --> 00:09:59,360 Speaker 1: about supply chain issues, but you take it a step 192 00:09:59,640 --> 00:10:03,319 Speaker 1: further are here and argue that maybe we're too dependent 193 00:10:04,000 --> 00:10:09,240 Speaker 1: on other countries, too dependent on globalization. Are you saying 194 00:10:09,559 --> 00:10:13,840 Speaker 1: we need to completely rethink supply chains, Well, I'm saying 195 00:10:13,880 --> 00:10:16,000 Speaker 1: we need to rethink more than that. Actually, you know, 196 00:10:16,120 --> 00:10:19,760 Speaker 1: for the last half century, we've had a process of 197 00:10:19,800 --> 00:10:22,400 Speaker 1: what I would call neoliberal globalization, which is, you know 198 00:10:22,440 --> 00:10:25,040 Speaker 1: about the idea that capital goods people can move wherever 199 00:10:25,080 --> 00:10:27,079 Speaker 1: they want and that they're always gonna land wherever it's 200 00:10:27,160 --> 00:10:30,400 Speaker 1: most productive. And that worked really well for capital um 201 00:10:30,720 --> 00:10:33,640 Speaker 1: and the biggest beneficiaries have been multinational companies and the 202 00:10:33,720 --> 00:10:36,439 Speaker 1: Chinese state. It's the chief capital for cheap labor bargain 203 00:10:36,480 --> 00:10:39,600 Speaker 1: between the US and Asia. But now that is just 204 00:10:39,679 --> 00:10:42,520 Speaker 1: fundamentally shifting, and it's been happening for a while. But 205 00:10:42,880 --> 00:10:45,559 Speaker 1: I think the pandemic and war in Ukraine were really 206 00:10:45,559 --> 00:10:48,040 Speaker 1: almost like a scrim that was pulled up and suddenly 207 00:10:48,080 --> 00:10:50,600 Speaker 1: people thought, oh, maybe it's not a good idea to 208 00:10:50,640 --> 00:10:53,679 Speaker 1: get our energy from an autocrat, or gosh, maybe it's 209 00:10:53,720 --> 00:10:56,800 Speaker 1: not such a safe thing. If the high end chips 210 00:10:56,800 --> 00:10:59,360 Speaker 1: in the world are produced in one island, that's um, 211 00:10:59,400 --> 00:11:01,719 Speaker 1: you know, maybe to be blockaded or even taken over 212 00:11:01,760 --> 00:11:04,000 Speaker 1: by China. So I think that these are things that 213 00:11:04,000 --> 00:11:07,080 Speaker 1: are now in the felt experience of most people. But 214 00:11:07,240 --> 00:11:11,200 Speaker 1: even before the decoupling that was about geopolitics, which we 215 00:11:11,240 --> 00:11:14,719 Speaker 1: all know is happening, there was a lot of regionalization 216 00:11:14,800 --> 00:11:18,000 Speaker 1: and even localization happening in supply chains for all kinds 217 00:11:18,000 --> 00:11:21,800 Speaker 1: of reasons, one of which is wages had risen in Asia. 218 00:11:21,920 --> 00:11:26,000 Speaker 1: You know, that whole arbitrage between productivity, wages, energy costs 219 00:11:26,280 --> 00:11:28,760 Speaker 1: was changing. You know a lot of companies were starting 220 00:11:28,760 --> 00:11:30,480 Speaker 1: to say, oh, you know, the low margin stuff, we 221 00:11:30,520 --> 00:11:32,560 Speaker 1: don't really want to tote it a long way through 222 00:11:32,559 --> 00:11:35,760 Speaker 1: the South China seas. Maybe we'll do it regionally. UM. Now, 223 00:11:36,000 --> 00:11:39,040 Speaker 1: I think with E s G concerns with energy prices 224 00:11:39,160 --> 00:11:42,840 Speaker 1: with their Europe, China and the US in different ways, 225 00:11:42,920 --> 00:11:45,680 Speaker 1: But all kind of pushing in the same direction towards 226 00:11:45,800 --> 00:11:47,679 Speaker 1: um If not a price on carbon, at least some 227 00:11:47,720 --> 00:11:51,679 Speaker 1: sort of accountability for carbon, those long supply chains will 228 00:11:51,679 --> 00:11:54,959 Speaker 1: become even harder. And then finally, we've got one more 229 00:11:55,000 --> 00:11:58,160 Speaker 1: really important tailwind, which is high tech manufacturing. I mean, 230 00:11:58,160 --> 00:12:01,439 Speaker 1: we're about to see I believe what we saw when 231 00:12:01,440 --> 00:12:03,679 Speaker 1: the iPhone came out in the consumer space, just that 232 00:12:03,840 --> 00:12:07,520 Speaker 1: boom in the app economy, and all kinds of growth 233 00:12:08,040 --> 00:12:12,359 Speaker 1: that's now coming into the industrial space through decentralized technologies 234 00:12:12,400 --> 00:12:15,320 Speaker 1: like three D printing or vertical farming. I mean, we 235 00:12:15,360 --> 00:12:18,600 Speaker 1: are really about to go through a massive technological change. 236 00:12:18,679 --> 00:12:22,520 Speaker 1: It's just gonna make it a lot more um efficient 237 00:12:22,600 --> 00:12:25,880 Speaker 1: and resilient to hub production and consumption more closely together. 238 00:12:26,559 --> 00:12:30,320 Speaker 1: Is more localization or the pendulum swinging back that way? Though? 239 00:12:31,080 --> 00:12:33,719 Speaker 1: Could that also be seen as a step backwards. Is 240 00:12:33,760 --> 00:12:36,120 Speaker 1: there a healthy middle? Well, for sure, there is a 241 00:12:36,120 --> 00:12:38,520 Speaker 1: healthy meddal I'm so glad you said that, because oftentimes 242 00:12:38,520 --> 00:12:41,120 Speaker 1: when you have the globalization debate, you know, on the 243 00:12:41,160 --> 00:12:42,520 Speaker 1: one hand, you've got people to say we got to 244 00:12:42,559 --> 00:12:44,240 Speaker 1: go back to the nineties, and then on the other hand, 245 00:12:44,280 --> 00:12:45,800 Speaker 1: you say, oh my gosh, we gotta go back to 246 00:12:45,800 --> 00:12:48,720 Speaker 1: the nineties. It's gonna be nineties. No, We're in a 247 00:12:48,760 --> 00:12:52,160 Speaker 1: whole new era. You know. I think economic pendulums always 248 00:12:52,200 --> 00:12:54,400 Speaker 1: swing throughout history. You know that's true. You go back 249 00:12:54,400 --> 00:12:57,760 Speaker 1: to eighteen century mercantilism that worked until it didn't, and 250 00:12:57,760 --> 00:12:59,760 Speaker 1: then you've got loss Affair, and then you've got Kenzie 251 00:12:59,760 --> 00:13:01,439 Speaker 1: in his him, and and then you know, we've had 252 00:13:01,480 --> 00:13:04,560 Speaker 1: now a half century or so of neoliberalism, you know, 253 00:13:04,920 --> 00:13:07,280 Speaker 1: most recently in the form of the Reagan Thatcher Revolution, 254 00:13:07,320 --> 00:13:10,400 Speaker 1: which maybe with the collapse of the list trust is 255 00:13:10,520 --> 00:13:13,560 Speaker 1: government and the disaster that is trusts and nomics, we 256 00:13:13,679 --> 00:13:16,000 Speaker 1: may see this as the apex and and the kind 257 00:13:16,000 --> 00:13:18,040 Speaker 1: of end of that old era before we move into 258 00:13:18,080 --> 00:13:21,720 Speaker 1: something new. How do you see the relationship between the 259 00:13:21,800 --> 00:13:25,320 Speaker 1: US and China evolving, especially with the actions that the 260 00:13:25,320 --> 00:13:28,800 Speaker 1: Bidens administration has taken on chips and what we heard 261 00:13:29,280 --> 00:13:33,200 Speaker 1: from s jamping over the weekend. Yeah, for sure. So 262 00:13:33,280 --> 00:13:36,959 Speaker 1: the US is reacting basically to China. I mean, as 263 00:13:37,000 --> 00:13:40,080 Speaker 1: we all know, China is always very clear about its 264 00:13:40,080 --> 00:13:42,480 Speaker 1: five year plans. It lays them out, they're available for 265 00:13:42,520 --> 00:13:46,199 Speaker 1: people to read. Um she is you know, uh adds 266 00:13:46,200 --> 00:13:50,000 Speaker 1: another layer of complexity. The nationalism, the populism that's gone 267 00:13:50,000 --> 00:13:52,120 Speaker 1: along with him is a little bit off piece for China, 268 00:13:52,440 --> 00:13:54,439 Speaker 1: which tends to produce more sort of middle of the 269 00:13:54,480 --> 00:13:57,040 Speaker 1: road technocratic leaders. But I think that it's been clear 270 00:13:57,080 --> 00:13:58,959 Speaker 1: for some time that China wants to do couple from 271 00:13:59,000 --> 00:14:02,040 Speaker 1: US technology. It wants to have what it calls a 272 00:14:02,160 --> 00:14:06,040 Speaker 1: dual circulation and commune, which essentially means the same thing regionalism, 273 00:14:06,120 --> 00:14:09,120 Speaker 1: hubbing production and consumption. They've got enough rich consumers now 274 00:14:09,120 --> 00:14:11,000 Speaker 1: they want to keep some of their uh, you know, 275 00:14:11,080 --> 00:14:13,439 Speaker 1: their their factory production at home. They don't want to 276 00:14:13,440 --> 00:14:15,560 Speaker 1: be the factor of the world anymore. They also want 277 00:14:15,559 --> 00:14:18,280 Speaker 1: to become less coupled with the dollar, which is a 278 00:14:18,280 --> 00:14:19,960 Speaker 1: whole another part of this. I mean, what we've seen 279 00:14:20,000 --> 00:14:23,280 Speaker 1: so far is shifts in supply chains and trade. What 280 00:14:23,360 --> 00:14:26,400 Speaker 1: we've made now start seeing is shifts in the financial 281 00:14:26,440 --> 00:14:28,720 Speaker 1: markets as China tries to do more digital R and 282 00:14:28,760 --> 00:14:31,320 Speaker 1: B business. Um, you know, you see, the weaponization of 283 00:14:31,360 --> 00:14:34,320 Speaker 1: the dollar was sanctioned, so there's there's decoupling and financial 284 00:14:34,400 --> 00:14:36,800 Speaker 1: markets too. Before we go, I have to get your 285 00:14:36,880 --> 00:14:41,280 Speaker 1: quick thoughts on Liz trust resigning today. Obviously a fierce 286 00:14:41,800 --> 00:14:45,360 Speaker 1: neoliberal advocate, which in the end certainly didn't work out. 287 00:14:45,600 --> 00:14:51,280 Speaker 1: So well. Are we witnessing a major ideological shift here? Uh, 288 00:14:51,320 --> 00:14:54,040 Speaker 1: it's hard to look at what's happened. Um, you know, 289 00:14:54,080 --> 00:14:56,720 Speaker 1: Liz Trust comes in and says, hey, we've got a 290 00:14:56,760 --> 00:15:00,560 Speaker 1: growth problem. Let's cut taxes on the very wealthiest even 291 00:15:00,640 --> 00:15:04,080 Speaker 1: as we spend on energy subsidies. And wow, the markets 292 00:15:04,080 --> 00:15:07,560 Speaker 1: didn't like that. You know, we've had about twenty years, 293 00:15:07,720 --> 00:15:09,680 Speaker 1: i would say, in this country, in the Anglo American 294 00:15:09,680 --> 00:15:12,000 Speaker 1: world in general, where it's been pretty clear that trickle 295 00:15:12,080 --> 00:15:15,720 Speaker 1: down wasn't working until the recent bout of inflation, and 296 00:15:15,760 --> 00:15:18,400 Speaker 1: there are other reasons for that. Wages for most Americans 297 00:15:18,440 --> 00:15:21,280 Speaker 1: have been flat since um, you know, the last twenty years. 298 00:15:21,480 --> 00:15:23,960 Speaker 1: The same has been true in the UK. Cutting taxes 299 00:15:24,000 --> 00:15:26,800 Speaker 1: on the rich is not the solution. The Reagan Thatcher 300 00:15:26,880 --> 00:15:29,280 Speaker 1: era is over. We don't have a sort of you know, 301 00:15:29,520 --> 00:15:33,520 Speaker 1: um postgame strategy yet completely, but we have some ideas 302 00:15:33,520 --> 00:15:35,560 Speaker 1: about where to go, and trickle down is not it. 303 00:15:36,160 --> 00:15:40,080 Speaker 1: So look, where do you see the world going, Like 304 00:15:40,160 --> 00:15:44,480 Speaker 1: five years from now, how much more localized will the 305 00:15:44,480 --> 00:15:47,720 Speaker 1: economy be? Will the economy be in better shape? I mean, 306 00:15:47,760 --> 00:15:50,400 Speaker 1: we're about to go through what could potentially be a 307 00:15:50,440 --> 00:15:52,800 Speaker 1: two to three year downturn. Yes, so let me let 308 00:15:52,840 --> 00:15:55,840 Speaker 1: me raise one issue first, and I'll kind of put 309 00:15:55,840 --> 00:15:58,680 Speaker 1: the caveat to my own thesis, which is inflation. Um, 310 00:15:59,040 --> 00:16:01,840 Speaker 1: we're moving towards world of more redundancy of supply, more 311 00:16:01,880 --> 00:16:05,840 Speaker 1: resiliency of supply, and that's inflationary, right. Cheap is not cheap. 312 00:16:05,840 --> 00:16:08,240 Speaker 1: People are gonna have to pay more for stuff. That's 313 00:16:08,240 --> 00:16:09,960 Speaker 1: an issue. Are they going to want to do that? 314 00:16:10,040 --> 00:16:11,520 Speaker 1: And then are we going to go back kind of 315 00:16:11,520 --> 00:16:13,960 Speaker 1: be pushed back into the old model? I don't think so, 316 00:16:14,080 --> 00:16:17,720 Speaker 1: because I think that geopolitics have fundamentally changed and ultimately, 317 00:16:17,920 --> 00:16:20,240 Speaker 1: after you know what, maybe a bumpy five years or so, 318 00:16:20,520 --> 00:16:22,040 Speaker 1: I think we're going to come back into a better 319 00:16:22,040 --> 00:16:24,760 Speaker 1: place in this country because making things has always been important. 320 00:16:24,840 --> 00:16:26,840 Speaker 1: You know, everybody that has ever spent time in a 321 00:16:26,880 --> 00:16:28,560 Speaker 1: factory floor and I did. I grew up and then 322 00:16:28,560 --> 00:16:30,800 Speaker 1: my dad ran factories kind of knows that that's an 323 00:16:30,800 --> 00:16:33,480 Speaker 1: important part of innovation and iteration. So I think having 324 00:16:33,520 --> 00:16:35,760 Speaker 1: an economy that's based on something aside from you know, 325 00:16:35,840 --> 00:16:38,840 Speaker 1: finance and software, uh, and it's more diverse and inclusive 326 00:16:38,880 --> 00:16:40,120 Speaker 1: in this country is going to be a good thing, 327 00:16:40,360 --> 00:16:43,400 Speaker 1: all right, Ron for our congrats on the book Financial 328 00:16:43,400 --> 00:16:46,960 Speaker 1: Times calumnist and awful of the author of Homecoming. Good 329 00:16:47,000 --> 00:16:49,360 Speaker 1: to have you. Now, speaking of China and supply chain issues, 330 00:16:49,400 --> 00:16:53,160 Speaker 1: the country has been struggling with containing COVID cases in 331 00:16:53,440 --> 00:16:56,400 Speaker 1: recent weeks, and now officials are said to be debating 332 00:16:56,400 --> 00:16:58,720 Speaker 1: whether to reduce the amount of time people entering the 333 00:16:58,720 --> 00:17:02,640 Speaker 1: country must spend and quarantine. They're talking about setting the 334 00:17:02,680 --> 00:17:04,600 Speaker 1: period to two days in a hotel, then five days 335 00:17:04,600 --> 00:17:07,320 Speaker 1: at home, versus the current seven days in a hotel 336 00:17:07,359 --> 00:17:10,840 Speaker 1: three days at home. The country's COVID zero policy leaving 337 00:17:10,840 --> 00:17:15,200 Speaker 1: it increasingly isolated from the rest of the world. Gotta 338 00:17:15,240 --> 00:17:17,120 Speaker 1: have much more coming up after the break. Let stay 339 00:17:17,119 --> 00:17:31,040 Speaker 1: with us. This is Bloomberg. Texas sued Google overclaims that 340 00:17:31,080 --> 00:17:35,480 Speaker 1: it's illegally capturing the biometric data of users without their consent. 341 00:17:35,920 --> 00:17:38,320 Speaker 1: This is the latest in a series of lawsuits by 342 00:17:38,359 --> 00:17:41,679 Speaker 1: the state against tech companies over online privacy. According to 343 00:17:41,720 --> 00:17:45,359 Speaker 1: Texas Attorney General Can Paxton, Google has collected millions of 344 00:17:45,400 --> 00:17:49,879 Speaker 1: biometric identify irs from Texas residents, including voice prints and 345 00:17:50,040 --> 00:17:53,600 Speaker 1: records of face geometry, through products like Google Photos and 346 00:17:53,640 --> 00:17:58,080 Speaker 1: Google assistant. Netflix's top executives continue to battle that out 347 00:17:58,119 --> 00:18:01,280 Speaker 1: over releasing more of its original movies theaters. The Wall 348 00:18:01,280 --> 00:18:04,280 Speaker 1: Street Journal reporting some arguing Netflix is leaving hundreds of 349 00:18:04,280 --> 00:18:07,440 Speaker 1: millions in box office receipts on the table by showing 350 00:18:07,480 --> 00:18:10,240 Speaker 1: select movies in just a few theaters for a few weeks, 351 00:18:10,240 --> 00:18:13,959 Speaker 1: while others feel theater showings create us for the streaming service. 352 00:18:22,040 --> 00:18:24,600 Speaker 1: Welcome back. We've got some breaking news now coming out 353 00:18:24,600 --> 00:18:28,000 Speaker 1: of the Washington Post that Elon Musk plans to cut 354 00:18:28,160 --> 00:18:32,959 Speaker 1: Twitter's workforce by seventy five percent. The Post reporting on 355 00:18:33,119 --> 00:18:41,400 Speaker 1: documents detailing these plans to allegedly cut Twitter's workforce. Um, 356 00:18:41,440 --> 00:18:44,840 Speaker 1: of course, we've been talking about whether or not Musk 357 00:18:44,880 --> 00:18:48,239 Speaker 1: would make big changes, especially when it comes to staffing. Now. 358 00:18:48,240 --> 00:18:50,320 Speaker 1: Of course, the deal is not done yet, still waiting 359 00:18:50,320 --> 00:18:54,840 Speaker 1: for that October deadline for a deal to happen. But 360 00:18:56,160 --> 00:18:59,520 Speaker 1: if Elon Musk does indeed close this deal to buy Twitter, 361 00:19:00,119 --> 00:19:03,400 Speaker 1: does indeed cut seventy of the workforce, you're talking about 362 00:19:03,400 --> 00:19:07,399 Speaker 1: thousands of people. Um. Twitter's workforce is currently at about 363 00:19:07,480 --> 00:19:14,240 Speaker 1: seven thousand, five hundred people, so that is a significant cut. 364 00:19:14,240 --> 00:19:16,040 Speaker 1: We're gonna continue to follow this story and bring you 365 00:19:16,080 --> 00:19:20,560 Speaker 1: more headlines as we have them. Meantime, I want to 366 00:19:20,680 --> 00:19:24,240 Speaker 1: talk a little bit about workplace trends. The pandemic, of course, 367 00:19:24,280 --> 00:19:26,880 Speaker 1: has brought about many changes, one of them being hybrid work, 368 00:19:27,240 --> 00:19:29,040 Speaker 1: but it's not the only metric that matters. And we're 369 00:19:29,040 --> 00:19:31,159 Speaker 1: going to talk about this all with Arianna Hoffington, founder 370 00:19:31,160 --> 00:19:35,399 Speaker 1: and CEO of Thrive Global. Ariana, so great to have 371 00:19:35,520 --> 00:19:39,160 Speaker 1: you back. Um. As always, you know, we've been hearing 372 00:19:39,200 --> 00:19:41,760 Speaker 1: this term quiet quitting over and over again, which speaks 373 00:19:41,800 --> 00:19:44,760 Speaker 1: to this idea of employees deciding not to go above 374 00:19:44,800 --> 00:19:49,600 Speaker 1: and beyond their listed responsibilities. Why do you think that 375 00:19:49,760 --> 00:19:53,840 Speaker 1: is so? I really great to be with you. I'm 376 00:19:53,920 --> 00:19:57,399 Speaker 1: here at the Masters of Scale Conferdence at Reid Hoffman 377 00:19:57,680 --> 00:20:02,679 Speaker 1: and the wide want more organizing and quite quitting, the 378 00:20:02,800 --> 00:20:07,120 Speaker 1: great resignation, the great break up for women have been 379 00:20:07,280 --> 00:20:11,200 Speaker 1: big themes of the conference. And what is interesting about 380 00:20:11,320 --> 00:20:15,119 Speaker 1: quite quitting is that it's really a rejection of the 381 00:20:15,200 --> 00:20:19,840 Speaker 1: hussle culture that we've all been bemoaning. But also it's 382 00:20:19,880 --> 00:20:25,080 Speaker 1: like a false choice between hussle culture and burnout and 383 00:20:25,720 --> 00:20:29,960 Speaker 1: giving up on having an engaged job that you love 384 00:20:30,040 --> 00:20:32,840 Speaker 1: and brings you joy in a sense of purpose and meaning, 385 00:20:33,480 --> 00:20:36,400 Speaker 1: and so a lot of the conversation here has been 386 00:20:36,440 --> 00:20:42,240 Speaker 1: about how to recognize that we don't have to buy 387 00:20:42,320 --> 00:20:45,480 Speaker 1: this false choice, that we can be engaged in our 388 00:20:45,560 --> 00:20:50,959 Speaker 1: jobs and set boundaries. And also, if you look at 389 00:20:51,000 --> 00:20:56,200 Speaker 1: the great breakup that the Mackensey Leaning Report talked about 390 00:20:56,520 --> 00:21:01,200 Speaker 1: with them many more women living in the workplace because 391 00:21:01,200 --> 00:21:04,920 Speaker 1: of burnout compared to men forty three versus thirty one, 392 00:21:06,080 --> 00:21:09,280 Speaker 1: and you see that burnout is at the top of 393 00:21:09,320 --> 00:21:13,000 Speaker 1: the conversation everywhere. Well, and I wondered, two women and 394 00:21:13,119 --> 00:21:16,600 Speaker 1: underrepresented minorities have the luxury of quiet quitting or is 395 00:21:16,600 --> 00:21:20,840 Speaker 1: this something that you know more men have the luxury 396 00:21:20,920 --> 00:21:23,879 Speaker 1: of doing. Well, it's not just quite witting for women. 397 00:21:23,960 --> 00:21:29,480 Speaker 1: They're just leaving the workspace in unprecedented numbers. And that's 398 00:21:29,520 --> 00:21:34,080 Speaker 1: all the bad news. And Emily, the good news is 399 00:21:34,160 --> 00:21:37,959 Speaker 1: that these conversations are no longer just the province of 400 00:21:38,000 --> 00:21:43,120 Speaker 1: the HR departments. And Satia and Natala spoke here yesterday morning, 401 00:21:43,920 --> 00:21:48,320 Speaker 1: and he spoke not just of the digital revolution and 402 00:21:48,440 --> 00:21:53,400 Speaker 1: AI breakthroughs, but about the need for leaders to acquire 403 00:21:53,520 --> 00:21:58,399 Speaker 1: soft skills and not just to demand that their employees 404 00:21:58,480 --> 00:22:03,000 Speaker 1: returned to the office, but to become like event organizers, 405 00:22:03,000 --> 00:22:05,439 Speaker 1: he called it, where he gives them a reason to 406 00:22:05,520 --> 00:22:11,600 Speaker 1: return to the office, where leaders acknowledged that people come 407 00:22:11,640 --> 00:22:16,199 Speaker 1: for people and not because of mandated policy. Also, he 408 00:22:16,280 --> 00:22:21,520 Speaker 1: talked about the productivity paradox of leaders think they're doing 409 00:22:21,680 --> 00:22:28,320 Speaker 1: enough to prevent burnout and promote well being, and percent 410 00:22:28,760 --> 00:22:35,800 Speaker 1: of of employees feel burned out and white a lot 411 00:22:35,840 --> 00:22:38,960 Speaker 1: of their managers in their slacking off. So there is 412 00:22:39,040 --> 00:22:43,040 Speaker 1: theurmoil in the workplace. But frankly, Emily, a lot of 413 00:22:43,080 --> 00:22:46,280 Speaker 1: these things have been happening before the pandemic, and now 414 00:22:46,280 --> 00:22:48,639 Speaker 1: everything has come to the service and we have an 415 00:22:48,640 --> 00:22:52,960 Speaker 1: opportunity to redefine how we work and live. I have 416 00:22:53,119 --> 00:22:56,960 Speaker 1: to ask you about this Twitter nuwi since it just broke, 417 00:22:57,000 --> 00:22:59,280 Speaker 1: and I can imagine a few people have probably been 418 00:22:59,359 --> 00:23:02,280 Speaker 1: quiet quitting a Twitter over the last few months. Now 419 00:23:02,320 --> 00:23:05,640 Speaker 1: we're learning from this Washington Post report that Elon Musk 420 00:23:05,680 --> 00:23:10,199 Speaker 1: plans to cut seventy of the workforce. Elon Musk, you know, 421 00:23:10,280 --> 00:23:14,040 Speaker 1: has also come out in favor of in person work. 422 00:23:14,200 --> 00:23:18,040 Speaker 1: But you know, what's your reaction to this. Well, first 423 00:23:18,080 --> 00:23:22,520 Speaker 1: of all, there's been so many rumors about this Twitter deal. 424 00:23:22,760 --> 00:23:25,879 Speaker 1: We don't know what it's true and what isn't. And 425 00:23:26,000 --> 00:23:30,879 Speaker 1: also I'm wondering how much Elon Musk is regretting this 426 00:23:31,080 --> 00:23:35,000 Speaker 1: impulsive decision to buy Twitter. It's been a huge destruction. 427 00:23:35,720 --> 00:23:41,200 Speaker 1: It's definitely affected the test last talk, because shareholders obviously 428 00:23:41,480 --> 00:23:48,600 Speaker 1: don't like the CEO being so destructed by a major 429 00:23:48,760 --> 00:23:51,920 Speaker 1: deal that's in the news every day. You know, as 430 00:23:52,359 --> 00:23:55,800 Speaker 1: someone who you know has played such a prominent role 431 00:23:56,320 --> 00:23:59,560 Speaker 1: in media, do you like the idea of Elon Musk 432 00:23:59,600 --> 00:24:04,800 Speaker 1: owning Twitter or what concerns you about the idea of 433 00:24:04,840 --> 00:24:06,200 Speaker 1: you on must go on Twitter? What do you think 434 00:24:06,200 --> 00:24:10,000 Speaker 1: is gonna change? I mean, it's get really dramatically change 435 00:24:10,400 --> 00:24:13,840 Speaker 1: how a lot of us get our news. Well, if 436 00:24:13,840 --> 00:24:17,439 Speaker 1: you look at them, the power of TikTok and the 437 00:24:17,480 --> 00:24:21,520 Speaker 1: incredible popularity of TikTok and the city of TikTok is 438 00:24:21,600 --> 00:24:25,000 Speaker 1: here and talking to him, it's clear that there is 439 00:24:25,080 --> 00:24:30,600 Speaker 1: real moderation there. And they have twelve rules around moderation, 440 00:24:30,840 --> 00:24:37,280 Speaker 1: including preventing and and rejecting violence and pornography. A lot 441 00:24:37,320 --> 00:24:41,360 Speaker 1: of it is moderated through AI, but there is also 442 00:24:41,520 --> 00:24:43,919 Speaker 1: human moderation. So the idea that you can have a 443 00:24:44,000 --> 00:24:47,080 Speaker 1: free for all in the name of quote and quote 444 00:24:47,080 --> 00:24:52,480 Speaker 1: free speech is definitely troubling because there's so much mus representation, 445 00:24:53,400 --> 00:25:03,200 Speaker 1: and it's impossible to have a functioning democracy without moderation. 446 00:25:04,160 --> 00:25:08,600 Speaker 1: So clearly, you know the Twitter and Elama's case isn't 447 00:25:08,840 --> 00:25:13,680 Speaker 1: is a unique story in itself. We are going through 448 00:25:14,000 --> 00:25:16,760 Speaker 1: what could be a very prolonged economic downturn. There are 449 00:25:16,800 --> 00:25:21,720 Speaker 1: all of these rapidly shifting workplace trends. As you discuss, 450 00:25:22,080 --> 00:25:25,120 Speaker 1: what's your advice to employers right now, what's your advice 451 00:25:25,160 --> 00:25:31,160 Speaker 1: to businesses about how they should rethink their workplace policies 452 00:25:31,560 --> 00:25:35,480 Speaker 1: and what they expect of their employees. Well, the priority, 453 00:25:35,640 --> 00:25:39,760 Speaker 1: Emily has to be to recognize that investing in the 454 00:25:39,880 --> 00:25:42,720 Speaker 1: well being and mental health of their employees it's not 455 00:25:42,880 --> 00:25:47,240 Speaker 1: the warm and fuzzy HR benefit. It's a business strategy. 456 00:25:47,400 --> 00:25:52,399 Speaker 1: It's a necessity in order to prevent attrition, improved productivity, 457 00:25:53,040 --> 00:25:58,040 Speaker 1: and and actually reduce healthcare costs. I mean, you saw 458 00:25:58,119 --> 00:26:05,000 Speaker 1: the lead document two days ago that Amazon is losing 459 00:26:05,119 --> 00:26:09,760 Speaker 1: eight billion dollars a year because of attrition. So the 460 00:26:09,840 --> 00:26:13,280 Speaker 1: connection between well being and mental health and attrition is 461 00:26:13,440 --> 00:26:16,320 Speaker 1: very clear. We have a lot of data here, so 462 00:26:17,359 --> 00:26:22,080 Speaker 1: leaders are recognizing more and more that this is the 463 00:26:22,160 --> 00:26:26,600 Speaker 1: moment to redefine the importance of the importance of human 464 00:26:26,680 --> 00:26:30,159 Speaker 1: capital invest in the well being of their employees in 465 00:26:30,280 --> 00:26:33,440 Speaker 1: the workflow. Embedded in the workflow. It can't just be 466 00:26:33,680 --> 00:26:38,120 Speaker 1: a mental health day here or a yoga studio there. 467 00:26:38,520 --> 00:26:42,520 Speaker 1: It has to be embedded in the daily work so 468 00:26:42,560 --> 00:26:45,840 Speaker 1: that people can actually take these little breaks that prevent 469 00:26:46,040 --> 00:26:50,480 Speaker 1: stress from becoming cumulative and from becoming burnout. And there's 470 00:26:50,480 --> 00:26:54,000 Speaker 1: been so much focus on where we're working and how 471 00:26:54,040 --> 00:26:58,040 Speaker 1: that impacts productivity, but now there's new research that shows 472 00:26:58,080 --> 00:27:02,640 Speaker 1: maybe it's when working that has a greater impact on productivity. 473 00:27:02,640 --> 00:27:06,200 Speaker 1: What do you think, yes, and all the new research 474 00:27:06,320 --> 00:27:09,639 Speaker 1: that shows that what actually leads to more productivity is 475 00:27:09,760 --> 00:27:13,560 Speaker 1: not having to be at work nine to five, but 476 00:27:13,720 --> 00:27:17,600 Speaker 1: being able to work when it's more convenient for you 477 00:27:17,680 --> 00:27:20,560 Speaker 1: if you have children to take to school and parents 478 00:27:20,600 --> 00:27:24,520 Speaker 1: to take care of. So there's no way, Emily that 479 00:27:24,600 --> 00:27:27,040 Speaker 1: we are going to go to a normal nine to 480 00:27:27,200 --> 00:27:31,720 Speaker 1: five five day in the office reality, but there is 481 00:27:31,760 --> 00:27:35,160 Speaker 1: a lot we have to do to rebuild the social 482 00:27:35,280 --> 00:27:38,359 Speaker 1: capital that we are losing when we are working remote. 483 00:27:38,600 --> 00:27:41,920 Speaker 1: All right, Arianna, thank you so much for always trying 484 00:27:41,920 --> 00:27:44,160 Speaker 1: to get us to think about the important things. Ariana 485 00:27:44,200 --> 00:27:48,240 Speaker 1: Huffington's founder and CEO of Thrive Global. It's always good 486 00:27:48,240 --> 00:27:50,560 Speaker 1: to have you here. Appreciate it. Thank you how much, 487 00:27:50,560 --> 00:27:56,240 Speaker 1: Emily Okay. Coming up, Defy is dealing with a major 488 00:27:56,280 --> 00:27:59,639 Speaker 1: problem financial packing. We're going to talk about that in 489 00:27:59,640 --> 00:28:14,600 Speaker 1: our to report. Coming up next, this is Bloomberg. The 490 00:28:14,640 --> 00:28:17,439 Speaker 1: crypto industry is reeling from a new threat to the 491 00:28:17,480 --> 00:28:21,880 Speaker 1: decentralized financial system, and that is hacking. For more on this, 492 00:28:22,000 --> 00:28:25,480 Speaker 1: let's bring in Bloomberg Shanali Bostic. So what exactly is 493 00:28:25,560 --> 00:28:28,200 Speaker 1: happening Shale. Well, it's not the hacking you would think of. 494 00:28:28,240 --> 00:28:31,560 Speaker 1: This is not people attacking code and then taking money 495 00:28:31,640 --> 00:28:35,360 Speaker 1: out of a protocol or token. This is financial hacking, 496 00:28:35,400 --> 00:28:39,080 Speaker 1: which is really debated very heavily. This is people buying 497 00:28:39,400 --> 00:28:43,800 Speaker 1: certain assets using stable coins on swap, inflating those assets 498 00:28:43,840 --> 00:28:45,920 Speaker 1: and then using them as collateral to take out loans. 499 00:28:46,080 --> 00:28:49,120 Speaker 1: Sounds very complicated, not an easy maneuver to do, but 500 00:28:49,240 --> 00:28:52,280 Speaker 1: people have figured out these D five protocols have the 501 00:28:52,320 --> 00:28:55,520 Speaker 1: ability to um you know, some people call it market 502 00:28:55,560 --> 00:28:58,120 Speaker 1: manipulation instead of hacking. You know, so is it illegal? 503 00:28:58,200 --> 00:29:00,520 Speaker 1: Is it not illegal? Is a gray area, But in 504 00:29:00,560 --> 00:29:03,000 Speaker 1: a lot of places people just call it trading. So 505 00:29:03,120 --> 00:29:06,200 Speaker 1: that's the debate we're talking about here. There's nothing necessarily 506 00:29:06,200 --> 00:29:08,280 Speaker 1: wrong with it legally, it's a lot of gray area 507 00:29:08,720 --> 00:29:11,600 Speaker 1: for a market that is being defined as we speak 508 00:29:11,960 --> 00:29:15,600 Speaker 1: and explain how this is technically possible and also why 509 00:29:15,600 --> 00:29:18,360 Speaker 1: are we so surprised that this is happening. Shouldn't this 510 00:29:18,400 --> 00:29:20,920 Speaker 1: be expected? It should be expected, especially with all that 511 00:29:20,960 --> 00:29:23,960 Speaker 1: we've seen throughout the entire year when it comes to defy, 512 00:29:24,040 --> 00:29:26,280 Speaker 1: when it comes to who's borrowing, when it comes to 513 00:29:26,360 --> 00:29:31,760 Speaker 1: instabilities and prices, because now so many new financial products loans, swaps, 514 00:29:31,800 --> 00:29:35,240 Speaker 1: and other products are being created around the initial tokens themselves. 515 00:29:35,440 --> 00:29:37,840 Speaker 1: Interestingly enough to the most recent one we've been talking 516 00:29:37,840 --> 00:29:40,960 Speaker 1: about is Mango is governed by a doo as well. 517 00:29:41,000 --> 00:29:43,160 Speaker 1: So you have a whole community of people here who 518 00:29:43,200 --> 00:29:45,840 Speaker 1: are being affected and have to vote on how they 519 00:29:45,880 --> 00:29:50,560 Speaker 1: retrieve money from this financial hack or trading strategy, whatever 520 00:29:50,560 --> 00:29:52,880 Speaker 1: you wanna call it, that is being conducted. How are 521 00:29:52,920 --> 00:29:56,880 Speaker 1: crypto experts reacting. I think one interesting thing to look 522 00:29:56,920 --> 00:29:59,560 Speaker 1: at here is Sam Bankman Freeds framework he created for 523 00:29:59,560 --> 00:30:01,880 Speaker 1: this kind the thing, Because again, you can't stop people 524 00:30:01,920 --> 00:30:04,920 Speaker 1: from doing this. This is essentially a way to find 525 00:30:04,960 --> 00:30:07,120 Speaker 1: a hole in the system and then profit from it. 526 00:30:07,360 --> 00:30:08,960 Speaker 1: And so what you're seeing is he's saying that the 527 00:30:09,000 --> 00:30:11,760 Speaker 1: hacker should keep five percent of the taking funds and 528 00:30:11,800 --> 00:30:14,640 Speaker 1: this should be a community wide rule. But he's also 529 00:30:14,840 --> 00:30:18,400 Speaker 1: saying that the community and the customer must be made 530 00:30:18,400 --> 00:30:21,160 Speaker 1: whole first. If that doesn't happen, then the hacker, the 531 00:30:21,160 --> 00:30:23,640 Speaker 1: hacker doesn't get back the funds, and they have twenty 532 00:30:23,640 --> 00:30:25,920 Speaker 1: four hours to return those funds. He calculates that the 533 00:30:25,960 --> 00:30:29,200 Speaker 1: impacts of the hacks can be reduced by if this 534 00:30:29,240 --> 00:30:31,320 Speaker 1: were to happen. Now, I also want to hedge this 535 00:30:31,360 --> 00:30:32,840 Speaker 1: by saying in his blog post that he said he 536 00:30:32,880 --> 00:30:36,760 Speaker 1: feels very uncertain that this is the standard to have. However, 537 00:30:37,360 --> 00:30:40,000 Speaker 1: it is one proposal. He's open to suggestions. I would 538 00:30:40,000 --> 00:30:42,760 Speaker 1: be interesting to also hear what those suggestions are as 539 00:30:42,800 --> 00:30:45,800 Speaker 1: people try to figure out how to change the market 540 00:30:45,840 --> 00:30:48,880 Speaker 1: and the rules around it. For really, what's not a 541 00:30:48,920 --> 00:30:52,320 Speaker 1: technical hack. It is a different way of trading different 542 00:30:52,320 --> 00:30:54,800 Speaker 1: products around strategy that is losing a lot of people 543 00:30:54,800 --> 00:30:56,920 Speaker 1: some money. All right, Well, thank you for breaking down 544 00:30:57,000 --> 00:30:59,800 Speaker 1: a very complex topic for us. Yet again, you are 545 00:31:00,040 --> 00:31:02,160 Speaker 1: very good at that Jounal I always going to see you. 546 00:31:02,240 --> 00:31:13,080 Speaker 1: Good to see you here in person. Artificial intelligence is 547 00:31:13,160 --> 00:31:16,800 Speaker 1: driving a new era of artistic talent. Apps that generate 548 00:31:16,880 --> 00:31:20,280 Speaker 1: images from simple text descriptions are growing more popular as 549 00:31:20,320 --> 00:31:23,680 Speaker 1: a source for people with little artistic ability to create 550 00:31:23,760 --> 00:31:25,840 Speaker 1: unique work for more honest, I want to bring in 551 00:31:25,920 --> 00:31:29,200 Speaker 1: MG Evans, founder and CEO of Tasai, the world's first 552 00:31:29,400 --> 00:31:34,680 Speaker 1: talent agency for AI artists. So explain how an AI 553 00:31:34,800 --> 00:31:38,680 Speaker 1: artist talent agency works. Are you representing the humans using 554 00:31:38,680 --> 00:31:42,640 Speaker 1: the AI to create art or are you representing the 555 00:31:42,800 --> 00:31:47,240 Speaker 1: AI itself? So the answer is probably a little scary 556 00:31:47,280 --> 00:31:50,920 Speaker 1: for most people, um because we are representing the AI 557 00:31:51,000 --> 00:31:56,400 Speaker 1: brains that are on their own creating art without input 558 00:31:56,480 --> 00:32:00,120 Speaker 1: from humans. So it's slightly different from you know, the 559 00:32:00,240 --> 00:32:02,560 Speaker 1: programs that most people have probably heard of where you 560 00:32:02,600 --> 00:32:05,040 Speaker 1: input some words and then you get a painting. We're 561 00:32:05,040 --> 00:32:08,720 Speaker 1: talking about ais that are creating their own artworks out 562 00:32:08,800 --> 00:32:12,000 Speaker 1: of their own brains whenever they want and however they want. 563 00:32:12,040 --> 00:32:15,520 Speaker 1: So who creates the AI though? So there are developers 564 00:32:15,600 --> 00:32:19,120 Speaker 1: that create the AI brain and then the brain interacts 565 00:32:19,280 --> 00:32:22,800 Speaker 1: with different inputs and creates its own artistic style. What 566 00:32:22,880 --> 00:32:26,160 Speaker 1: do you think the potential is here. Um, I think 567 00:32:26,480 --> 00:32:31,320 Speaker 1: it's basically a creation of a new type of artists 568 00:32:31,320 --> 00:32:34,400 Speaker 1: and a new generation of artists that we can't really 569 00:32:34,440 --> 00:32:36,600 Speaker 1: imagine from where we sit right now, because all we 570 00:32:36,680 --> 00:32:39,160 Speaker 1: can imagine from where we sit right now is an 571 00:32:39,160 --> 00:32:41,680 Speaker 1: AI that needs you to tell it what to draw 572 00:32:41,800 --> 00:32:43,800 Speaker 1: and needs you to tell it what to paint and 573 00:32:43,800 --> 00:32:46,240 Speaker 1: when to do that. And actually that's not the future 574 00:32:46,280 --> 00:32:49,400 Speaker 1: of AI. The future of AI is much more autonomous 575 00:32:50,640 --> 00:32:54,200 Speaker 1: artificial intelligence beings than what we actually can see right now. 576 00:32:54,560 --> 00:32:57,960 Speaker 1: So what exactly do you do for the AI. So 577 00:32:58,080 --> 00:33:00,680 Speaker 1: each of these AI s at the moment is an 578 00:33:00,800 --> 00:33:04,360 Speaker 1: n f T on the blockchain, so they have technically 579 00:33:04,400 --> 00:33:06,960 Speaker 1: an owner. So at the moment they are owned by 580 00:33:07,000 --> 00:33:08,520 Speaker 1: somebody in the same way that an n f T 581 00:33:08,680 --> 00:33:11,080 Speaker 1: is owned. So we would interact with the owner and 582 00:33:11,160 --> 00:33:18,240 Speaker 1: represent their AI brain that they own. Um, how does 583 00:33:18,320 --> 00:33:20,760 Speaker 1: the AI then decide if the agency is doing a 584 00:33:20,760 --> 00:33:25,160 Speaker 1: good job. Well, that's a good question. I mean, Um, 585 00:33:25,600 --> 00:33:28,760 Speaker 1: at the moment, the the AI probably can't do that, 586 00:33:28,800 --> 00:33:30,520 Speaker 1: But that's not to say that in the very near 587 00:33:30,600 --> 00:33:32,640 Speaker 1: future they will be able to do that, and that 588 00:33:32,680 --> 00:33:35,720 Speaker 1: they will actually want representation, which is decision they can't 589 00:33:35,720 --> 00:33:38,600 Speaker 1: really make for themselves at the moment. Now, some of 590 00:33:38,680 --> 00:33:43,440 Speaker 1: this AI generated art is not so pleasing. In fact, 591 00:33:43,480 --> 00:33:47,960 Speaker 1: some of it is downright ugly or disturbing. How do 592 00:33:48,000 --> 00:33:51,800 Speaker 1: you think about that? Yeah, so I think, um, regular 593 00:33:51,920 --> 00:33:54,760 Speaker 1: art is not always pleasing. Regular art is always you know, 594 00:33:55,080 --> 00:33:57,440 Speaker 1: has the chance to be pleasing or disturbing depending on 595 00:33:57,480 --> 00:34:00,400 Speaker 1: who's looking. Um. I think the most important thing is 596 00:34:00,440 --> 00:34:04,400 Speaker 1: to make the designation between art that is original, which 597 00:34:04,440 --> 00:34:07,400 Speaker 1: most people don't think AI art can be original, And 598 00:34:07,400 --> 00:34:11,200 Speaker 1: that's what we're trying to change, because if you follow 599 00:34:11,200 --> 00:34:13,160 Speaker 1: you think about AI art is that it comes from 600 00:34:13,160 --> 00:34:16,200 Speaker 1: an algorithm and it can't possibly come from any kind 601 00:34:16,239 --> 00:34:19,480 Speaker 1: of creative process that's similar to what humans undergo. Then 602 00:34:19,520 --> 00:34:22,600 Speaker 1: you'll never appreciate it. Whether whether it's disturbing or beautiful 603 00:34:22,719 --> 00:34:24,640 Speaker 1: or not, you will never appreciate it. But when you 604 00:34:24,680 --> 00:34:27,399 Speaker 1: do appreciate that it comes from a unique AI brain, 605 00:34:27,480 --> 00:34:29,520 Speaker 1: then you might actually grow to appreciate it, and that 606 00:34:29,560 --> 00:34:31,799 Speaker 1: goes to value as well. It will develop its own 607 00:34:31,880 --> 00:34:34,120 Speaker 1: value in the marketplace. All Right, we've got some quick 608 00:34:34,160 --> 00:34:36,600 Speaker 1: breaking news just you want to report that the Biden 609 00:34:36,600 --> 00:34:41,000 Speaker 1: administration is exploring now the possibility of new export controls 610 00:34:41,040 --> 00:34:43,839 Speaker 1: that would limit China's access to some of the most 611 00:34:43,880 --> 00:34:47,759 Speaker 1: powerful emerging computing technologies. According to people familiar with the matter, 612 00:34:47,840 --> 00:34:50,600 Speaker 1: these potential plans, which are in an early stage, are 613 00:34:50,640 --> 00:34:54,279 Speaker 1: focused on the still experimental field of quantum computing as 614 00:34:54,280 --> 00:34:58,920 Speaker 1: well as artificial intelligence software. Speaking of that, industry experts 615 00:34:58,960 --> 00:35:01,920 Speaker 1: are weighing in on how to set the parameters of 616 00:35:01,960 --> 00:35:05,200 Speaker 1: the restrictions on this technology. And of course this um 617 00:35:05,400 --> 00:35:08,040 Speaker 1: is an extension of what we've seen the Biden administration 618 00:35:08,120 --> 00:35:11,720 Speaker 1: doing on chips when it comes to supply chains as well. 619 00:35:11,719 --> 00:35:14,080 Speaker 1: This is a developing story that we're going to continue 620 00:35:14,080 --> 00:35:17,480 Speaker 1: to follow. Actually, speaking of China energy, how do you 621 00:35:17,680 --> 00:35:21,040 Speaker 1: see the role of China in the artificial intelligence and 622 00:35:21,239 --> 00:35:23,920 Speaker 1: f T space. I mean, obviously we're the U s 623 00:35:24,000 --> 00:35:26,319 Speaker 1: is very concerned about it's its ability to compete with 624 00:35:26,400 --> 00:35:31,520 Speaker 1: China on technology. Where is China in your world? I think, 625 00:35:31,920 --> 00:35:34,440 Speaker 1: you know, one of the things that makes us unique 626 00:35:34,600 --> 00:35:36,600 Speaker 1: in you know, what we like to think of as 627 00:35:36,600 --> 00:35:40,279 Speaker 1: a liberal democracy is that we actually really value creativity. 628 00:35:40,400 --> 00:35:42,960 Speaker 1: And I understand that that's one of the issues that 629 00:35:43,160 --> 00:35:46,359 Speaker 1: some artists have been having. But when you compare us 630 00:35:46,360 --> 00:35:49,440 Speaker 1: to China, for example, I mean we have a completely 631 00:35:49,520 --> 00:35:52,759 Speaker 1: open world of expression here, and I think if we 632 00:35:52,800 --> 00:35:56,000 Speaker 1: can offer that also in the AI space, then that 633 00:35:56,520 --> 00:35:58,960 Speaker 1: also gives us a leg up on China in terms 634 00:35:58,960 --> 00:36:01,520 Speaker 1: of our creative because the world is heading in an 635 00:36:01,560 --> 00:36:05,000 Speaker 1: AI direction, So whoever is more creative in that space 636 00:36:05,080 --> 00:36:08,640 Speaker 1: is going to be far ahead. How do you respond 637 00:36:08,719 --> 00:36:12,480 Speaker 1: to those who say that the idea of AI R 638 00:36:12,800 --> 00:36:16,520 Speaker 1: belittles natural human artistry? Yeah, I mean, look, as you know, 639 00:36:16,600 --> 00:36:18,960 Speaker 1: I haven't I have an art background, so I'm completely 640 00:36:19,000 --> 00:36:22,359 Speaker 1: sympathetic to people who feel that way. Um, but I 641 00:36:22,440 --> 00:36:26,920 Speaker 1: don't think we will ever lose our desire for human creativity. 642 00:36:27,160 --> 00:36:29,759 Speaker 1: You know, it's just you. You can't say that one 643 00:36:29,800 --> 00:36:33,240 Speaker 1: replaces the other. But I think also you can't say 644 00:36:33,280 --> 00:36:36,600 Speaker 1: that an AI brain can't have a creative process in 645 00:36:36,640 --> 00:36:38,879 Speaker 1: the way that a human brain has a creative process. 646 00:36:38,920 --> 00:36:42,640 Speaker 1: One artist doesn't cancel out another. So it's really so, 647 00:36:42,680 --> 00:36:44,640 Speaker 1: what do you say that the folks who whose mind 648 00:36:44,719 --> 00:36:47,680 Speaker 1: just goes to a very scary place? I think in 649 00:36:47,840 --> 00:36:50,319 Speaker 1: talking about I would light of those people. It's a 650 00:36:50,360 --> 00:36:54,520 Speaker 1: little terrifying. It's amazing, but terrifying. It's terrifying. But I 651 00:36:54,560 --> 00:36:57,520 Speaker 1: think we all have to start embracing that really scary 652 00:36:57,560 --> 00:37:00,399 Speaker 1: place because we're going in that direction. So you're either 653 00:37:00,440 --> 00:37:02,520 Speaker 1: gonna kind of stick your head in the sand and 654 00:37:02,680 --> 00:37:04,640 Speaker 1: just you know, stick your fingers in your ears and 655 00:37:04,680 --> 00:37:05,719 Speaker 1: be like, I don't want to go there. I don't 656 00:37:05,719 --> 00:37:07,120 Speaker 1: want to go there, or you're going to figure out 657 00:37:07,120 --> 00:37:10,680 Speaker 1: a way that you can maybe interact with that place 658 00:37:10,840 --> 00:37:13,279 Speaker 1: and maybe you could even wind up having collaboration with 659 00:37:13,320 --> 00:37:15,720 Speaker 1: an AI artist if you If you don't start thinking 660 00:37:15,719 --> 00:37:17,720 Speaker 1: about that, the world is just going to leave you behind. 661 00:37:17,800 --> 00:37:19,839 Speaker 1: So you have to start thinking about well, thank you 662 00:37:19,880 --> 00:37:24,000 Speaker 1: for starting to open our eyes to this. N. G. Evans, 663 00:37:24,160 --> 00:37:27,600 Speaker 1: founder and CEO of two Sigh, the world's first AI 664 00:37:27,760 --> 00:37:30,359 Speaker 1: artist talent agency. Good to see you, And that does 665 00:37:30,360 --> 00:37:33,719 Speaker 1: it for this edition of Bloomberg Technology. Don't forget to 666 00:37:33,760 --> 00:37:36,480 Speaker 1: check out our podcast wherever you get your podcast. I'm 667 00:37:36,480 --> 00:37:38,520 Speaker 1: Emily Chang in New York. This is Bloomberg