1 00:00:02,000 --> 00:00:05,360 Speaker 1: From the heart of where innovation, money and power callive 2 00:00:06,120 --> 00:00:10,640 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:10,680 --> 00:00:27,520 Speaker 1: Emily Jay. I'memily check in San Francisco, and this is 4 00:00:27,520 --> 00:00:31,760 Speaker 1: Bloomberg Technology. Coming up in the next hour. Twitter begins layoffs, 5 00:00:31,800 --> 00:00:35,120 Speaker 1: reportedly cutting the PR team from roughly ninety people to 6 00:00:35,280 --> 00:00:38,800 Speaker 1: just two and more, and Musk says the company is 7 00:00:38,840 --> 00:00:42,800 Speaker 1: under stress from a massive drop in revenue as advertisers 8 00:00:42,880 --> 00:00:46,840 Speaker 1: hit pause. Plus Expedience CEO joins us to talk about 9 00:00:46,840 --> 00:00:50,120 Speaker 1: the travel rebound and plans to take on Airbnb after 10 00:00:50,159 --> 00:00:53,560 Speaker 1: reporting record revenue. Will I keep up in a recession? 11 00:00:54,840 --> 00:00:58,120 Speaker 1: And Bloomberg analyze more than one million tweets and Facebook 12 00:00:58,120 --> 00:01:00,960 Speaker 1: posts from hundreds of midterm elections candidates who said they 13 00:01:01,000 --> 00:01:05,800 Speaker 1: believed somewhat or fully that the election was stolen from 14 00:01:05,840 --> 00:01:09,200 Speaker 1: former President Trump. Turns out, amplification of the so called 15 00:01:09,200 --> 00:01:13,440 Speaker 1: big lie on social media drives engagement. We're gonna get 16 00:01:13,440 --> 00:01:14,720 Speaker 1: to all of that in a moment, but first I 17 00:01:14,720 --> 00:01:16,319 Speaker 1: want to get to Twitter now and the slow of 18 00:01:16,360 --> 00:01:20,320 Speaker 1: companies pulling their advertising from the platform. Bloomberg's Alex Barrinka 19 00:01:20,480 --> 00:01:23,119 Speaker 1: has been following it all for us, so Alex Elon 20 00:01:23,200 --> 00:01:25,480 Speaker 1: Musk has said there's been a massive drop in revenue. 21 00:01:26,000 --> 00:01:31,480 Speaker 1: He blames it on activist activist groups pressuring advertisers over 22 00:01:31,560 --> 00:01:35,919 Speaker 1: content moderation issues, even though nothing has changed yet. Who's 23 00:01:36,000 --> 00:01:41,680 Speaker 1: leaving Audias, leaving GM is leaving either leaving really big 24 00:01:41,760 --> 00:01:44,720 Speaker 1: names are leaving, Emily. And to your point there, Elon, 25 00:01:44,800 --> 00:01:48,120 Speaker 1: with tweeting yesterday you did a poll thing what you 26 00:01:48,200 --> 00:01:52,640 Speaker 1: advertise or stand behind free speech or political correctness, those 27 00:01:52,640 --> 00:01:54,560 Speaker 1: are the only two choice of that. Emily actually think 28 00:01:54,560 --> 00:01:56,240 Speaker 1: that's probably a little bit of a false choice for 29 00:01:56,320 --> 00:01:59,360 Speaker 1: these brands. They are looking at Twitter as the plates 30 00:01:59,400 --> 00:02:02,000 Speaker 1: to put dons and find some return on that advent. 31 00:02:02,200 --> 00:02:04,680 Speaker 1: That return is going to be kind of number one 32 00:02:04,760 --> 00:02:08,519 Speaker 1: in their minds. As we've seen um Twitter the business 33 00:02:08,680 --> 00:02:11,560 Speaker 1: kind of you know, convulsing over the last week, with 34 00:02:11,919 --> 00:02:15,240 Speaker 1: laying off about half of the workforce, with questions around 35 00:02:15,280 --> 00:02:18,640 Speaker 1: who is leading different departments, and with Elon trying to 36 00:02:18,720 --> 00:02:22,320 Speaker 1: counter that by assuring advertisers that they will be moderating 37 00:02:22,560 --> 00:02:25,800 Speaker 1: content on the platform. It seems like a lot of 38 00:02:25,800 --> 00:02:28,600 Speaker 1: these big names are deciding right now to take a pause. 39 00:02:29,120 --> 00:02:32,160 Speaker 1: And I would say this is a pretty problematic thing 40 00:02:32,200 --> 00:02:34,680 Speaker 1: for Twitter. You'll remember the last earnings report they had, 41 00:02:34,720 --> 00:02:38,000 Speaker 1: they actually saw revenue decline from a year prior in 42 00:02:38,040 --> 00:02:41,480 Speaker 1: that quarter. And now Ellen is taking a company that 43 00:02:41,639 --> 00:02:45,000 Speaker 1: is private and will have about a billion dollar interest 44 00:02:45,040 --> 00:02:48,360 Speaker 1: bill every year for the debt that they used to 45 00:02:48,400 --> 00:02:51,760 Speaker 1: take this company private. So advertisers here are the lifeblood. 46 00:02:51,960 --> 00:02:54,720 Speaker 1: Ellen's coming in with um a little bit of perhaps 47 00:02:55,040 --> 00:02:58,239 Speaker 1: sauciness at them for leaving the platform, but they will 48 00:02:58,280 --> 00:03:02,520 Speaker 1: absolutely need those dollars who forward. All right, So we're 49 00:03:02,520 --> 00:03:06,960 Speaker 1: talking Volkswagen Fiser General Mills. Let's talk about the layoffs. 50 00:03:07,000 --> 00:03:11,000 Speaker 1: Employees started getting emails early, early in the morning that 51 00:03:11,040 --> 00:03:14,680 Speaker 1: they were being terminated, cools getting let go. Is it 52 00:03:14,840 --> 00:03:18,600 Speaker 1: that thirty seven hundred number that we've been reporting right now? 53 00:03:18,639 --> 00:03:22,080 Speaker 1: It seems like it is inching toward that number. And 54 00:03:22,160 --> 00:03:24,560 Speaker 1: you have some teams like you mentioned at the top, 55 00:03:24,639 --> 00:03:27,920 Speaker 1: like the communications team, that have been completely gutted, losing 56 00:03:28,360 --> 00:03:32,000 Speaker 1: about eighty eight of their ninety employees. So you have 57 00:03:32,160 --> 00:03:34,320 Speaker 1: folks kind of all the way across the board, and Emily. 58 00:03:34,400 --> 00:03:36,880 Speaker 1: One of the reasons why advertisers might actually be pausing, 59 00:03:37,160 --> 00:03:40,000 Speaker 1: it's sort of related to how this is being handled. 60 00:03:40,440 --> 00:03:43,280 Speaker 1: It is typical in a acquisition or in a change 61 00:03:43,280 --> 00:03:45,400 Speaker 1: of leadership for the new leaders to come in to 62 00:03:45,480 --> 00:03:47,600 Speaker 1: kind of take a survey of the land and to 63 00:03:47,920 --> 00:03:50,200 Speaker 1: kind of approach these things a little bit differently. The 64 00:03:50,200 --> 00:03:52,680 Speaker 1: way that Ellen has come in with these kind of 65 00:03:52,760 --> 00:03:56,840 Speaker 1: emails sometimes overnight for employees and UM, what some employees 66 00:03:56,840 --> 00:03:58,960 Speaker 1: are looking at is kind of a coin flip has 67 00:03:59,000 --> 00:04:01,680 Speaker 1: injected a lot of UM, someone call it chaos into 68 00:04:01,720 --> 00:04:04,320 Speaker 1: the business. So we're seeing the cuts across the board. 69 00:04:04,560 --> 00:04:08,680 Speaker 1: There are some areas he's staying and urging UM perhaps 70 00:04:08,800 --> 00:04:13,040 Speaker 1: for that advertise advertiser audience, that he is bringing the 71 00:04:13,080 --> 00:04:16,719 Speaker 1: tools back online for content moderation UM, and areas like 72 00:04:16,760 --> 00:04:19,760 Speaker 1: that that he has put make care to reference in 73 00:04:19,800 --> 00:04:22,120 Speaker 1: the last forty eight hours. But it does seem like 74 00:04:22,440 --> 00:04:25,520 Speaker 1: it's pretty broad based across the company and in terms 75 00:04:25,520 --> 00:04:29,839 Speaker 1: of word that those head count cuts are coming from. Meantime, 76 00:04:29,880 --> 00:04:33,320 Speaker 1: Twitter is being sued uh in a class action lawsuit 77 00:04:33,680 --> 00:04:39,039 Speaker 1: by employees who say their termination is wrongful or that 78 00:04:39,080 --> 00:04:41,800 Speaker 1: at least under California employment law, he can't make big 79 00:04:41,880 --> 00:04:45,560 Speaker 1: changes like this before sixty days have passed. Can you 80 00:04:45,600 --> 00:04:49,039 Speaker 1: explain the lawsuit to us and how good of a 81 00:04:49,080 --> 00:04:52,920 Speaker 1: case they have? Sure in the state of California. We're 82 00:04:53,000 --> 00:04:55,120 Speaker 1: we're rebooth our Emily right now, there's something called a 83 00:04:55,200 --> 00:04:59,000 Speaker 1: war notice where employers have to give a sixty day 84 00:04:59,040 --> 00:05:01,919 Speaker 1: notice before be off above a certain threshold of people. 85 00:05:02,120 --> 00:05:05,400 Speaker 1: That Twitter is certainly clearing that threshold. This is a 86 00:05:05,480 --> 00:05:08,240 Speaker 1: lawyer who's bringing this class action suit, who actually has 87 00:05:08,600 --> 00:05:11,839 Speaker 1: let a suit against Musk before over a similar matter 88 00:05:12,000 --> 00:05:16,039 Speaker 1: for layoffs at Tesla. You'll remember, um, he elon must 89 00:05:16,040 --> 00:05:18,640 Speaker 1: hold our very own editor in chief that he saw 90 00:05:18,680 --> 00:05:21,120 Speaker 1: that suit is trivial. Um, so you can imagine what 91 00:05:21,240 --> 00:05:24,480 Speaker 1: he how he might perceive this suit today. That lawyer 92 00:05:24,560 --> 00:05:27,880 Speaker 1: did come back, uh, just this afternoon and say that 93 00:05:27,960 --> 00:05:31,159 Speaker 1: she's happy to see that some of the severance packages 94 00:05:31,200 --> 00:05:34,120 Speaker 1: are actually paying out employees over the number of day 95 00:05:34,200 --> 00:05:38,160 Speaker 1: some employees over the number of days that are legally required. Um. 96 00:05:38,320 --> 00:05:40,520 Speaker 1: So it seems like there could still be some activity 97 00:05:40,520 --> 00:05:43,800 Speaker 1: on that case, but certainly with the swiftness of the 98 00:05:43,839 --> 00:05:46,120 Speaker 1: decision that was made, there are a lot of questions 99 00:05:46,200 --> 00:05:49,279 Speaker 1: raised around legality, both here in the state of California 100 00:05:49,360 --> 00:05:51,159 Speaker 1: and you can probably imagine in some of the other 101 00:05:51,160 --> 00:05:56,680 Speaker 1: countries where Twitter has offices as well. All Right, Alex Brenka. 102 00:05:56,720 --> 00:05:59,440 Speaker 1: I'm sure there'll be lots of news more and more 103 00:05:59,520 --> 00:06:01,560 Speaker 1: over the Again, thank you so much for bringing us 104 00:06:01,560 --> 00:06:04,960 Speaker 1: the very latest. Will continue to watch your reporting. Zooming 105 00:06:04,960 --> 00:06:07,520 Speaker 1: out to the tech space at large. Now, things not 106 00:06:07,600 --> 00:06:10,760 Speaker 1: looking much better, the Nasdaq one hundred dropping more than 107 00:06:10,800 --> 00:06:14,200 Speaker 1: five percent this week as the sector veils from economic uncertainty. 108 00:06:14,240 --> 00:06:15,719 Speaker 1: We're gonna get more on the bigger picture here with 109 00:06:15,720 --> 00:06:20,200 Speaker 1: Bloomberg's Emily Grafeo. Emily, how is tech weighing on overall markets? 110 00:06:20,240 --> 00:06:23,440 Speaker 1: It's not just Twitter, but Apple, Amazon, where we're also 111 00:06:23,520 --> 00:06:27,479 Speaker 1: seeing significant changes in strategy when it comes to spending 112 00:06:27,480 --> 00:06:30,960 Speaker 1: and hiring. We are seeing these stocks falling, but in 113 00:06:31,040 --> 00:06:34,120 Speaker 1: terms of how much they're impacting the overall market, I 114 00:06:34,160 --> 00:06:37,440 Speaker 1: think that story is really beginning to change as the 115 00:06:37,480 --> 00:06:41,359 Speaker 1: Federal Reserve raises interest rates. I was actually looking at 116 00:06:41,600 --> 00:06:44,760 Speaker 1: just how much um these tech stocks and the movements 117 00:06:44,760 --> 00:06:48,640 Speaker 1: in these stocks impact the broader SMP five hundred. For 118 00:06:48,760 --> 00:06:51,680 Speaker 1: a really long time. In the last two years, the 119 00:06:51,800 --> 00:06:55,200 Speaker 1: narrative has been, you know, these megacat tech stocks make 120 00:06:55,279 --> 00:06:58,080 Speaker 1: up such a large portion of the SMP five hundred, 121 00:06:58,120 --> 00:07:02,080 Speaker 1: we can't see the market gain without the strength there. 122 00:07:02,279 --> 00:07:04,960 Speaker 1: But if you look at the month of October UM, 123 00:07:05,279 --> 00:07:08,960 Speaker 1: four out of the five largest mega cap tech stocks 124 00:07:09,040 --> 00:07:12,280 Speaker 1: in the SMP five hundred posted a negative return, and 125 00:07:12,320 --> 00:07:15,560 Speaker 1: we saw the SMP five hundred gain about eight percent, 126 00:07:15,960 --> 00:07:19,360 Speaker 1: So the equal weighted index was even higher, almost ten 127 00:07:19,480 --> 00:07:22,840 Speaker 1: percent there. So it is starting to seem like investors 128 00:07:22,880 --> 00:07:25,720 Speaker 1: can play the broader stock market and they don't need 129 00:07:25,760 --> 00:07:28,800 Speaker 1: that tech strength like they did before. And we're really 130 00:07:28,800 --> 00:07:31,720 Speaker 1: starting to see that this federal reserve tightening is weighing 131 00:07:31,800 --> 00:07:36,520 Speaker 1: on these big tech companies. What are money managers saying 132 00:07:36,560 --> 00:07:40,160 Speaker 1: about this? Are they getting skittish? It's interesting. I was 133 00:07:40,200 --> 00:07:43,400 Speaker 1: actually at an investing conference last week and I have 134 00:07:43,560 --> 00:07:46,320 Speaker 1: to say, Emily, there weren't a lot of conversations about 135 00:07:46,560 --> 00:07:49,480 Speaker 1: where can I invest in tech? The questions were more about, 136 00:07:49,760 --> 00:07:52,360 Speaker 1: you know, where the value stocks? Um, how can I 137 00:07:52,400 --> 00:07:56,200 Speaker 1: position my fixed income portfolio. I was talking with Jan 138 00:07:56,320 --> 00:07:58,920 Speaker 1: von Eck, he's the CEO of van Eck Funds. We 139 00:07:58,920 --> 00:08:01,520 Speaker 1: were talking a little bit of out technology stocks. He 140 00:08:01,600 --> 00:08:05,400 Speaker 1: said he probably wouldn't go overweight, but the valuations have 141 00:08:05,600 --> 00:08:09,560 Speaker 1: come down in that sector, so he said that is attractive. 142 00:08:09,720 --> 00:08:12,840 Speaker 1: But um, when you look at overall money managers, they 143 00:08:12,880 --> 00:08:16,920 Speaker 1: are thinking about value stocks more than just Oh my gosh, 144 00:08:16,920 --> 00:08:20,720 Speaker 1: I need Apple overweight in my portfolio. There is some 145 00:08:20,840 --> 00:08:24,000 Speaker 1: fear that the federal reserve tightening is going away on 146 00:08:24,040 --> 00:08:26,800 Speaker 1: the stocks more than it already has, and that earnings 147 00:08:26,800 --> 00:08:31,120 Speaker 1: do have to come down even more. All right, Emily, 148 00:08:31,640 --> 00:08:34,760 Speaker 1: thank you so much for zooming out. Bloomberg's Emily graffo 149 00:08:34,880 --> 00:08:46,400 Speaker 1: so much to continue to watch the Fed trying to 150 00:08:46,440 --> 00:08:50,040 Speaker 1: tamp down affordability, but people continue to pay top dollar 151 00:08:50,360 --> 00:08:54,960 Speaker 1: for experiences. Expedia posted record quarterly revenue and third quarter 152 00:08:54,960 --> 00:08:58,600 Speaker 1: bookings free cash flow for the first nine months three 153 00:08:58,679 --> 00:09:03,480 Speaker 1: point one billion dollars, more than double levels. Expedia CEO 154 00:09:03,600 --> 00:09:08,280 Speaker 1: and vice chair Peter Kern joins me. Now, so, uh, Peter, 155 00:09:08,480 --> 00:09:10,560 Speaker 1: let's talk about the bigger picture here. It looks like 156 00:09:10,600 --> 00:09:13,960 Speaker 1: people are continuing to spend on travel. I know we 157 00:09:14,040 --> 00:09:17,599 Speaker 1: had some hurricanes that interrupted some of the flow, but 158 00:09:17,679 --> 00:09:20,880 Speaker 1: outside of that, how good was the summer travel season? 159 00:09:21,960 --> 00:09:24,600 Speaker 1: The summer travel season was great, Emily. You know, it 160 00:09:24,760 --> 00:09:27,240 Speaker 1: was everything I think most of us expected, which was 161 00:09:27,320 --> 00:09:30,320 Speaker 1: tons of pent up demand anywhere in the world where 162 00:09:30,320 --> 00:09:32,800 Speaker 1: people could travel. Of course, there's parts of the world 163 00:09:32,840 --> 00:09:36,080 Speaker 1: still even now, in an apac and other places where 164 00:09:36,080 --> 00:09:38,760 Speaker 1: it's still quite difficult to travel. So there is more 165 00:09:38,800 --> 00:09:41,440 Speaker 1: to come in terms of opening up world travel. But 166 00:09:41,760 --> 00:09:44,960 Speaker 1: the summer was great. Business has continued to be quite strong, 167 00:09:45,000 --> 00:09:49,280 Speaker 1: and demand really hasn't ebbed since then. So you know, 168 00:09:49,360 --> 00:09:53,280 Speaker 1: everything so far looks pretty good, notwithstanding all the macroeconomic 169 00:09:53,320 --> 00:09:55,800 Speaker 1: warriors that you talk about all day. So um, so 170 00:09:55,800 --> 00:09:59,040 Speaker 1: we're feeling pretty good about things. But if we had 171 00:09:59,080 --> 00:10:02,240 Speaker 1: into a recession, I mean, I know people are spending 172 00:10:02,280 --> 00:10:04,959 Speaker 1: money on travel to this point, who's to say that 173 00:10:04,960 --> 00:10:06,720 Speaker 1: people aren't going to say, oh, maybe I should take 174 00:10:06,760 --> 00:10:09,840 Speaker 1: a maybe I shouldn't take that vacation, or let's just 175 00:10:10,200 --> 00:10:16,080 Speaker 1: you know, drive um to a vacation rental nearby. Yeah, listen, 176 00:10:16,120 --> 00:10:19,160 Speaker 1: I think, uh, macroeconomics will be what they will be. 177 00:10:19,320 --> 00:10:22,560 Speaker 1: I think so far what's been demonstrated is that while 178 00:10:22,559 --> 00:10:25,439 Speaker 1: there has have been a few cracks and other categories, 179 00:10:25,480 --> 00:10:28,720 Speaker 1: travel hasn't cracked. I think partly because people have missed 180 00:10:28,720 --> 00:10:31,079 Speaker 1: it so much during COVID and they've realized how much 181 00:10:31,120 --> 00:10:34,760 Speaker 1: they want those experiences more generally. Uh, And we've seen 182 00:10:34,760 --> 00:10:37,160 Speaker 1: corporate travels start to come back and other pieces start 183 00:10:37,200 --> 00:10:39,760 Speaker 1: to come back. So I think, you know, we have 184 00:10:39,880 --> 00:10:42,560 Speaker 1: some good running room, but there's nothing to say that 185 00:10:42,600 --> 00:10:45,520 Speaker 1: people can start to change their minds. But remember, you know, 186 00:10:45,600 --> 00:10:49,040 Speaker 1: global travels a two plus trillion dollar industry, so this 187 00:10:49,160 --> 00:10:51,840 Speaker 1: isn't a zero sum game. And we're a growth company. 188 00:10:51,880 --> 00:10:54,440 Speaker 1: We're trying to build our base of members, build our 189 00:10:54,480 --> 00:10:58,720 Speaker 1: business up, offer great new tools for travelers, great new benefits. 190 00:10:58,760 --> 00:11:01,480 Speaker 1: So we believe there's ample reason for us to continue 191 00:11:01,520 --> 00:11:04,280 Speaker 1: to attract travelers. And even if they're trading down a 192 00:11:04,320 --> 00:11:07,120 Speaker 1: little bit or making slightly different adjustments to their travel, 193 00:11:07,200 --> 00:11:10,320 Speaker 1: we think they're still gonna want to travel. Do you 194 00:11:10,400 --> 00:11:13,400 Speaker 1: think that there's something fundamentally different in terms of how 195 00:11:13,440 --> 00:11:17,240 Speaker 1: people approach travel? You know, this isn't just a few 196 00:11:17,280 --> 00:11:19,720 Speaker 1: vacations they wanted to get out of their system, but 197 00:11:19,920 --> 00:11:23,280 Speaker 1: as a whole new frame of mind. Well, I think 198 00:11:23,320 --> 00:11:25,800 Speaker 1: you know, anytime you have an existential threat to life 199 00:11:25,840 --> 00:11:28,800 Speaker 1: on the planet, people probably respond with a little bit 200 00:11:28,800 --> 00:11:30,240 Speaker 1: of like, I want to live, I want to go 201 00:11:30,320 --> 00:11:32,560 Speaker 1: see the things I want to see. Uh. You know 202 00:11:32,559 --> 00:11:35,439 Speaker 1: there are people, uh my age and older who are 203 00:11:35,640 --> 00:11:37,960 Speaker 1: at a point where they're saying, you know, I only 204 00:11:38,000 --> 00:11:39,720 Speaker 1: have so many trips left in my life, you know, 205 00:11:39,880 --> 00:11:41,440 Speaker 1: so there's a lot to get out of there. And 206 00:11:41,480 --> 00:11:44,000 Speaker 1: I think COVID made us all reassess that. So I 207 00:11:44,040 --> 00:11:46,800 Speaker 1: wouldn't chalk this up to you know, hybrid work or 208 00:11:46,840 --> 00:11:49,640 Speaker 1: other things. I think it's really just, uh, people are 209 00:11:49,679 --> 00:11:52,920 Speaker 1: realizing that experiences or what make life great and travel 210 00:11:53,040 --> 00:11:55,120 Speaker 1: is where we get all that. So, you know, you 211 00:11:55,160 --> 00:11:56,839 Speaker 1: and I have talked about it before. We all want 212 00:11:56,840 --> 00:11:59,880 Speaker 1: to travel. Everybody wants to travel, and I think, Sir 213 00:12:00,000 --> 00:12:02,679 Speaker 1: and Way, we haven't used up that desire yet. You know, 214 00:12:02,760 --> 00:12:05,360 Speaker 1: in five years from now, has everyone gotten out of 215 00:12:05,400 --> 00:12:07,400 Speaker 1: their system? Maybe, but I don't think we've burned it 216 00:12:07,400 --> 00:12:12,439 Speaker 1: off in you know, eight months or twelve months. Airbnb 217 00:12:12,640 --> 00:12:14,679 Speaker 1: had a tough quarter at least if you look at 218 00:12:14,679 --> 00:12:18,640 Speaker 1: it from a market's perspective. Unlike the positive reaction we're 219 00:12:18,640 --> 00:12:21,959 Speaker 1: seeing from investor investors to your results. What do you 220 00:12:22,000 --> 00:12:26,880 Speaker 1: think happening there? You know, I'm not exactly sure what's happening, 221 00:12:26,960 --> 00:12:30,480 Speaker 1: but I think part of what we observed in what 222 00:12:30,559 --> 00:12:32,920 Speaker 1: we've seen with Airbnb is, you know, they are much 223 00:12:32,960 --> 00:12:37,240 Speaker 1: broader company. They appeal to much more, you know, room rentals, 224 00:12:37,280 --> 00:12:40,000 Speaker 1: parts of home rentals. We don't do that, um and 225 00:12:40,080 --> 00:12:42,360 Speaker 1: I think the scale of that business is such that 226 00:12:42,360 --> 00:12:45,079 Speaker 1: that is a market that may be seeing more weakness 227 00:12:45,520 --> 00:12:47,400 Speaker 1: from the lower end of the market. We as a 228 00:12:47,440 --> 00:12:49,720 Speaker 1: business or somewhat less exposed to that. In our verbo 229 00:12:49,760 --> 00:12:52,600 Speaker 1: brands were whole home. We tend to be middle and 230 00:12:52,679 --> 00:12:57,320 Speaker 1: upper market really the same in our main travel brands, 231 00:12:57,360 --> 00:13:00,800 Speaker 1: so we haven't seen those same cracks. But I think 232 00:13:00,840 --> 00:13:04,720 Speaker 1: if you're exposed significantly to the broad global you know, 233 00:13:04,840 --> 00:13:08,160 Speaker 1: lower end, you are probably going to be under somewhat 234 00:13:08,200 --> 00:13:10,679 Speaker 1: more pressure. But you know, we think they'll do fine. 235 00:13:11,280 --> 00:13:14,600 Speaker 1: FCS of course as a challenge globally as well. Again, 236 00:13:14,640 --> 00:13:17,280 Speaker 1: we're heavily weighted towards North America, which is great since 237 00:13:17,320 --> 00:13:20,600 Speaker 1: the dollar is strong, but if you're waited differently, that 238 00:13:20,679 --> 00:13:24,560 Speaker 1: can have a bunch of different impacts on you. Well. 239 00:13:24,679 --> 00:13:26,640 Speaker 1: A d r s are still average daily rates, still 240 00:13:26,679 --> 00:13:30,880 Speaker 1: above pre pandemic levels, but Airbnb, some of your competitors, 241 00:13:30,880 --> 00:13:33,520 Speaker 1: expecting those to moderate. Then there could also be this 242 00:13:33,640 --> 00:13:38,160 Speaker 1: change in the business mix. Are you expecting any softness 243 00:13:38,160 --> 00:13:41,720 Speaker 1: going into next year? You know, we haven't seen it yet. 244 00:13:42,040 --> 00:13:45,280 Speaker 1: Uh and uh. Again, the makeup of our business mixes 245 00:13:45,360 --> 00:13:49,360 Speaker 1: are are somewhat different, but UM hotels are certainly certainly 246 00:13:49,400 --> 00:13:51,319 Speaker 1: the big chains we're talking about holding a d R 247 00:13:51,400 --> 00:13:53,880 Speaker 1: s Uh. You know, hotels so far have been willing 248 00:13:53,880 --> 00:13:58,440 Speaker 1: to be less full in favor of holding price. Uh. 249 00:13:58,600 --> 00:14:01,480 Speaker 1: Does that last forever? Do some hotels change what they do? 250 00:14:01,679 --> 00:14:05,560 Speaker 1: Hard to know. But again, while demands stays strong, which 251 00:14:05,559 --> 00:14:08,000 Speaker 1: it is now, I don't think there's any you know, 252 00:14:08,160 --> 00:14:10,480 Speaker 1: end in sight to prices being up. And they're not 253 00:14:10,559 --> 00:14:14,240 Speaker 1: just up, they're considerably up since pre pandemic levels, and 254 00:14:14,280 --> 00:14:17,400 Speaker 1: that probably will hold. In the home rental business, it's 255 00:14:17,400 --> 00:14:20,240 Speaker 1: a little more violatile because you have single owners and 256 00:14:20,240 --> 00:14:23,120 Speaker 1: there's a little more price pressure sometimes on some of them. 257 00:14:23,160 --> 00:14:25,840 Speaker 1: But certainly in the hotel industry, the airline industry, I 258 00:14:25,880 --> 00:14:30,360 Speaker 1: think I think prices will still be high. So last 259 00:14:30,400 --> 00:14:34,200 Speaker 1: quick question, Verbo, give us the picture of supply and 260 00:14:34,360 --> 00:14:39,720 Speaker 1: demand given what you've seen, you know, going into next year. Yeah, well, 261 00:14:39,800 --> 00:14:42,840 Speaker 1: demand has remained quite strong for us, and other than 262 00:14:42,880 --> 00:14:45,760 Speaker 1: the hurricane which you mentioned at the beginning. Uh, you know, 263 00:14:45,840 --> 00:14:50,360 Speaker 1: we we've seen strength, you know, throughout COVID and since 264 00:14:50,440 --> 00:14:54,720 Speaker 1: COVID has somewhat subsided. Uh, we're very bullish on next year. 265 00:14:55,280 --> 00:14:57,720 Speaker 1: We've got you know, Verbo is going to become part 266 00:14:57,720 --> 00:15:01,080 Speaker 1: of our our global loyalty plan or and key loyalty 267 00:15:01,120 --> 00:15:03,040 Speaker 1: plan that's rolling out next year, and that's going to 268 00:15:03,120 --> 00:15:06,240 Speaker 1: be a great opportunity for Verbo members to participate in 269 00:15:06,280 --> 00:15:09,440 Speaker 1: our other brands and our other members Expedia, Hotels, etcetera, 270 00:15:09,680 --> 00:15:12,480 Speaker 1: to really participate in Verbo. So we see a lot 271 00:15:12,480 --> 00:15:15,360 Speaker 1: of opportunity there, and the supply side, we think there's 272 00:15:15,360 --> 00:15:17,640 Speaker 1: plenty of room to grow. We are being more aggressive 273 00:15:17,640 --> 00:15:20,080 Speaker 1: in that space and we expect to add, you know, 274 00:15:20,120 --> 00:15:22,960 Speaker 1: a bunch of supplies. So so we feel really good 275 00:15:23,000 --> 00:15:25,160 Speaker 1: about the brand, good about its part in our family 276 00:15:25,200 --> 00:15:28,640 Speaker 1: of brands, and certainly more opportunity for us as we 277 00:15:28,720 --> 00:15:34,440 Speaker 1: consolidate those loyalty plans. Peter current CEO of Expedia and 278 00:15:34,520 --> 00:15:35,920 Speaker 1: vice chair Peter are always good to have you here. 279 00:15:35,960 --> 00:15:40,080 Speaker 1: Thank you so much for joining us. Coming up, cyber 280 00:15:40,120 --> 00:15:43,280 Speaker 1: attacks continuing to surge an increasingly digital world. We're going 281 00:15:43,320 --> 00:15:47,320 Speaker 1: to dive into some new data from Rubric about what 282 00:15:47,360 --> 00:15:50,960 Speaker 1: companies should do to protect themselves. That's next. This is Bloomberg. 283 00:16:02,200 --> 00:16:05,440 Speaker 1: Cyber tags are picking up this according a new data 284 00:16:05,600 --> 00:16:09,040 Speaker 1: from the cloud data management and security company Rubric. I 285 00:16:09,080 --> 00:16:11,960 Speaker 1: want to bring in CEO and co founder People Sinha 286 00:16:12,040 --> 00:16:15,080 Speaker 1: now for more on their new reports. So you found 287 00:16:15,120 --> 00:16:20,880 Speaker 1: that of companies reported a breach, that is a staggering number. 288 00:16:21,800 --> 00:16:25,880 Speaker 1: Walk that out for us a bit that is actually 289 00:16:25,960 --> 00:16:31,280 Speaker 1: validates our thesis. We were suspecting that almost all of 290 00:16:31,280 --> 00:16:35,000 Speaker 1: the organizations in the world has already been infiltrated, and 291 00:16:35,040 --> 00:16:39,320 Speaker 1: what people reported was that percent of the companies had 292 00:16:40,520 --> 00:16:44,240 Speaker 1: once at least one cyber breach. And what is also 293 00:16:44,320 --> 00:16:48,200 Speaker 1: interesting is that seventy percent of the organization said that 294 00:16:48,240 --> 00:16:52,080 Speaker 1: they would pay for ransomware to get rid of this problem. 295 00:16:52,320 --> 00:16:57,720 Speaker 1: That's how low the confidences. So how our companies responding 296 00:16:57,760 --> 00:17:01,960 Speaker 1: to these threats? Are they ready? I don't think everyone 297 00:17:02,080 --> 00:17:05,639 Speaker 1: is ready. Um, even though there is a partnership private 298 00:17:05,720 --> 00:17:10,119 Speaker 1: and public Biden administration put together a zero trust framework. 299 00:17:10,640 --> 00:17:13,920 Speaker 1: Companies are looking at it, they're spending money, they're getting prepared. 300 00:17:14,320 --> 00:17:17,320 Speaker 1: But this problem is a huge. Ransomware is the single 301 00:17:17,400 --> 00:17:20,399 Speaker 1: largest threat to our economy, and everybody is saying that, 302 00:17:20,440 --> 00:17:22,600 Speaker 1: how do I keep my business going? What do I 303 00:17:22,840 --> 00:17:26,359 Speaker 1: make sure do to make sure that we are not 304 00:17:26,480 --> 00:17:30,800 Speaker 1: only preventing and detecting these attacks, but also create resiliency 305 00:17:30,880 --> 00:17:33,200 Speaker 1: where in spite of an attack, I can keep going. 306 00:17:35,520 --> 00:17:40,280 Speaker 1: So there's an ongoing war on Ukraine. You've got instability 307 00:17:40,440 --> 00:17:43,199 Speaker 1: at Twitter, which is a major platform. You've got midterm 308 00:17:43,240 --> 00:17:46,440 Speaker 1: elections coming up here in the United States. Are you 309 00:17:46,520 --> 00:17:49,600 Speaker 1: expecting the threats to ratch it up? And how do 310 00:17:49,680 --> 00:17:55,280 Speaker 1: companies respond? Creds are definitely increasing geopolitical situation, you have 311 00:17:56,000 --> 00:17:59,399 Speaker 1: uh Nason estate actors that are taking sides. You have 312 00:18:00,080 --> 00:18:04,719 Speaker 1: again mid term coming up, that we have cyber warfare 313 00:18:05,240 --> 00:18:08,439 Speaker 1: going on, I think, and in this situation, businesses have 314 00:18:08,520 --> 00:18:11,439 Speaker 1: to really think that attacks will happen. There is no 315 00:18:11,520 --> 00:18:14,080 Speaker 1: way to prevent it. How do they keep going in 316 00:18:14,160 --> 00:18:16,880 Speaker 1: spite of an attack? How do they create a resiliency plan, 317 00:18:17,119 --> 00:18:19,399 Speaker 1: how do they make sure that they recover from it? 318 00:18:20,119 --> 00:18:22,479 Speaker 1: And that's where companies are investing money and we are 319 00:18:22,520 --> 00:18:27,800 Speaker 1: seeing in our own market where recovery ability to identify 320 00:18:28,119 --> 00:18:30,480 Speaker 1: what part of the data was impacted, and how to 321 00:18:30,520 --> 00:18:34,080 Speaker 1: get rid of a bad content and recover good content 322 00:18:34,160 --> 00:18:39,520 Speaker 1: fast is what is everyone is focused on. Is public 323 00:18:39,560 --> 00:18:43,679 Speaker 1: private engagement between for example, the Biden and administration and 324 00:18:43,680 --> 00:18:46,360 Speaker 1: the private sector. Is that helping or do we need 325 00:18:46,400 --> 00:18:50,359 Speaker 1: to see more? We definitely need to see more here. 326 00:18:50,800 --> 00:18:53,480 Speaker 1: But it is a great first step because what happens 327 00:18:53,560 --> 00:18:57,720 Speaker 1: is that there is a natural hesitation and sharing data 328 00:18:57,760 --> 00:19:00,520 Speaker 1: and setting information between companies because no wants to come 329 00:19:00,560 --> 00:19:03,040 Speaker 1: across saying that, hey, you got attacked, we didn't have 330 00:19:03,119 --> 00:19:05,919 Speaker 1: the right defenses. But when the government comes into the 331 00:19:05,960 --> 00:19:09,560 Speaker 1: picture and creates a framework of information sharing, what kind 332 00:19:09,560 --> 00:19:12,199 Speaker 1: of attack has happened, how do you recover from it? 333 00:19:12,320 --> 00:19:15,560 Speaker 1: What kind of preventive measures you take? That really helps 334 00:19:15,600 --> 00:19:19,640 Speaker 1: companies get more confident, and confidence is what is required. 335 00:19:19,720 --> 00:19:22,879 Speaker 1: I mean, our study also found that a third of 336 00:19:22,960 --> 00:19:26,680 Speaker 1: the board have no confidence that their companies can recover 337 00:19:27,440 --> 00:19:34,560 Speaker 1: from a cyber incident. Okay, Wow, staggering new data um Work, 338 00:19:34,680 --> 00:19:37,480 Speaker 1: CEO and co founder of People Sindha People. Thank you 339 00:19:37,560 --> 00:19:49,359 Speaker 1: so much for sharing all of that with us. Welcome 340 00:19:49,359 --> 00:19:51,879 Speaker 1: back to Flomark Technology. I'm emily changing in San Francisco. 341 00:19:51,960 --> 00:19:55,320 Speaker 1: Let's get back to Elon Musk's Twitter takeover and what 342 00:19:55,400 --> 00:19:57,760 Speaker 1: it means for the future of free speech and content 343 00:19:57,840 --> 00:20:01,720 Speaker 1: moderation on the platform. My next guest has direct insight 344 00:20:01,800 --> 00:20:03,960 Speaker 1: into this after meeting with Elon Musk a few days 345 00:20:03,960 --> 00:20:06,320 Speaker 1: ago to talk about it for Sean Robinson is the 346 00:20:06,359 --> 00:20:10,879 Speaker 1: president of the racial justice organization Color of Change, and 347 00:20:10,920 --> 00:20:12,879 Speaker 1: he joins me now Rishan, thank you so much for 348 00:20:12,920 --> 00:20:15,840 Speaker 1: taking the time to join us. So how did the 349 00:20:15,880 --> 00:20:19,160 Speaker 1: meeting with Ellen go? Did it leave you hopeful or 350 00:20:19,160 --> 00:20:22,679 Speaker 1: with more concerns? Well, the meeting that we had on 351 00:20:22,720 --> 00:20:27,240 Speaker 1: Tuesday actually was UM BOTHUM, a good opportunity for us 352 00:20:27,280 --> 00:20:29,600 Speaker 1: to have a conversation, and and we walked out of 353 00:20:29,640 --> 00:20:35,040 Speaker 1: the meeting UM really focusing on UM hopeful actually that 354 00:20:35,240 --> 00:20:38,080 Speaker 1: his actions actually connected with the words in the meeting, 355 00:20:38,400 --> 00:20:42,119 Speaker 1: because he made three commitments in that meeting. UM commitments 356 00:20:42,160 --> 00:20:46,119 Speaker 1: around election integrity, commitments around the re platforming and ensuring 357 00:20:46,160 --> 00:20:49,280 Speaker 1: that will be a transparent process before anyone has been 358 00:20:49,280 --> 00:20:52,159 Speaker 1: re platform that has been UM taken off for the 359 00:20:52,240 --> 00:20:56,320 Speaker 1: egregious violation that anyone is the platform for, and then 360 00:20:56,320 --> 00:20:59,000 Speaker 1: talking about sort of the content moderation council he'd have 361 00:20:59,119 --> 00:21:02,359 Speaker 1: moving forward. He talked about agreeing with the sentiments and 362 00:21:02,400 --> 00:21:04,840 Speaker 1: the concerns that those of us in the civil rights 363 00:21:04,880 --> 00:21:08,080 Speaker 1: community brought up during that meeting. And we left the 364 00:21:08,119 --> 00:21:12,640 Speaker 1: meeting UM really wondering what would come next. And at 365 00:21:12,760 --> 00:21:15,800 Speaker 1: one thirty in the morning the next day, UM he 366 00:21:15,920 --> 00:21:19,480 Speaker 1: tweeted out UM tagging us in Matt tweet talking about 367 00:21:19,520 --> 00:21:23,120 Speaker 1: the meeting and making those commitments more public, But over 368 00:21:23,160 --> 00:21:26,360 Speaker 1: the last couple of days, we have seen him truly 369 00:21:26,960 --> 00:21:31,720 Speaker 1: and systematically dismantle the very infrastructure that would make those 370 00:21:31,760 --> 00:21:35,720 Speaker 1: commitments actually real. So the firing of safety and trust 371 00:21:36,240 --> 00:21:41,080 Speaker 1: um capacity inside of Twitter makes it impossible for him 372 00:21:41,119 --> 00:21:44,560 Speaker 1: to actually deliver on the commitments and promises that he 373 00:21:44,640 --> 00:21:47,639 Speaker 1: made in the meeting. So you know, the thing is 374 00:21:47,640 --> 00:21:50,320 Speaker 1: not just about your words, it's about your actions, and 375 00:21:50,400 --> 00:21:56,119 Speaker 1: actions are key here, and you are taking action by 376 00:21:56,600 --> 00:21:59,880 Speaker 1: h highlighting that move in your tweet. You tweeted. Elon 377 00:22:00,119 --> 00:22:03,280 Speaker 1: fired the entire team that identified the Twitter algorithm that 378 00:22:03,320 --> 00:22:06,840 Speaker 1: amplifies right wing voices over others. Not the first time 379 00:22:06,880 --> 00:22:10,840 Speaker 1: we've seen staff, particularly black employees, punished for flagging how 380 00:22:10,880 --> 00:22:17,359 Speaker 1: their companies products enable and amplify racism. Now, Musk today 381 00:22:17,520 --> 00:22:19,600 Speaker 1: said there's been a massive drop in revenue given this 382 00:22:19,640 --> 00:22:23,960 Speaker 1: pause from advertisers, even though according to him, nothing has 383 00:22:24,040 --> 00:22:27,919 Speaker 1: changed about content moderation. Yet, what do you say to 384 00:22:27,960 --> 00:22:32,359 Speaker 1: the folks who say, let's give Elon Musk sometime before 385 00:22:32,400 --> 00:22:35,520 Speaker 1: we make these dramatic moves. Yeah, well that's what we get. 386 00:22:35,560 --> 00:22:38,240 Speaker 1: We met with Elon Musk, and Elon Musk came out 387 00:22:38,800 --> 00:22:43,359 Speaker 1: um and made promises publicly and men UM right after 388 00:22:43,400 --> 00:22:46,520 Speaker 1: those promises, almost before the eight was dried on their promises, 389 00:22:46,840 --> 00:22:50,280 Speaker 1: he began to dismantle the very infrastruction that keep those 390 00:22:50,280 --> 00:22:53,119 Speaker 1: promises in place. Look, I want to be clear. Elon 391 00:22:53,200 --> 00:22:57,159 Speaker 1: Musk actually also met with advertisers. He met with coalitions 392 00:22:57,160 --> 00:23:02,000 Speaker 1: of folks working in advertising, and in the conversations UM 393 00:23:02,080 --> 00:23:04,359 Speaker 1: he made promises to them. He talked to them about 394 00:23:04,359 --> 00:23:08,480 Speaker 1: how content moderation was incredibly important and how he valued 395 00:23:08,520 --> 00:23:11,879 Speaker 1: content moderation. And then he went and he let go 396 00:23:11,960 --> 00:23:16,240 Speaker 1: of seventy of the staff that works on content moderation. 397 00:23:16,560 --> 00:23:20,280 Speaker 1: So the advertisers that are leaving are leaving because they 398 00:23:20,320 --> 00:23:23,320 Speaker 1: are concerned that their brands are gonna be next to 399 00:23:23,480 --> 00:23:26,800 Speaker 1: a product that the CEO in charge of it can't 400 00:23:26,840 --> 00:23:29,919 Speaker 1: be trusted, can't be trusted to deliver on their promises, 401 00:23:30,359 --> 00:23:33,800 Speaker 1: act acts in deeply erratic ways, and we'll put their 402 00:23:33,840 --> 00:23:38,119 Speaker 1: brands in harm's way. And so, as someone who's done 403 00:23:38,119 --> 00:23:40,680 Speaker 1: this work for a long time, has worked to hold 404 00:23:40,720 --> 00:23:46,200 Speaker 1: corporations accountable, to help them meet their actions with their words, 405 00:23:46,359 --> 00:23:49,240 Speaker 1: and to hold them accountable to that UM, I have 406 00:23:49,440 --> 00:23:53,439 Speaker 1: never seen so many advertisers not have to be convinced 407 00:23:53,800 --> 00:23:57,680 Speaker 1: not have to be pushed hard around UM the sort 408 00:23:57,680 --> 00:24:01,200 Speaker 1: of decisions that they are making right now, and quite frankly, 409 00:24:01,760 --> 00:24:05,159 Speaker 1: Um Elon Musk Um did have an opportunity when he 410 00:24:05,200 --> 00:24:09,600 Speaker 1: came in here UM to um actually move things forward. 411 00:24:09,640 --> 00:24:12,600 Speaker 1: Twitter was not a perfect company, Titter was not Twitter 412 00:24:12,720 --> 00:24:16,760 Speaker 1: was not doing everything well before Elon musk took over. 413 00:24:17,080 --> 00:24:20,320 Speaker 1: But what he has done is actually dismantled the type 414 00:24:20,359 --> 00:24:24,200 Speaker 1: of infrastructure that actually had to be increased in order 415 00:24:24,240 --> 00:24:27,159 Speaker 1: for the company to sort of live up to any 416 00:24:27,200 --> 00:24:31,000 Speaker 1: type of commitment to deal with the misinformation, the disinformation, 417 00:24:31,320 --> 00:24:36,240 Speaker 1: the amplification of hate and incitement of violence that has 418 00:24:36,359 --> 00:24:40,919 Speaker 1: become part of these platforms, UM currents, UM sort of 419 00:24:41,040 --> 00:24:46,760 Speaker 1: engagement and its legacy. Risad. The reason that this is 420 00:24:46,880 --> 00:24:50,600 Speaker 1: so important is because people of color, people in marginalized communities, 421 00:24:50,640 --> 00:24:55,840 Speaker 1: women face a disproportionate amount of harassment and hate online. 422 00:24:55,840 --> 00:24:59,840 Speaker 1: Can you explain why this matters, why this matters for 423 00:25:00,160 --> 00:25:07,920 Speaker 1: people who use Twitter, how he restructures and reframes the site. Well, yeah, 424 00:25:08,040 --> 00:25:10,520 Speaker 1: I mean, essentially what we're dealing with right now is 425 00:25:10,800 --> 00:25:14,359 Speaker 1: not just Twitter, but all the technology companies are essentially 426 00:25:14,400 --> 00:25:19,280 Speaker 1: self regulated companies and self regulated companies are unregulated company. Now, 427 00:25:19,720 --> 00:25:23,640 Speaker 1: if we think about other industries, right, the our seatbelts 428 00:25:23,960 --> 00:25:27,000 Speaker 1: are not necessarily safe in our cars are not necessarily 429 00:25:27,040 --> 00:25:30,640 Speaker 1: safe because of the benevolence of the auto industry alone. 430 00:25:30,920 --> 00:25:35,800 Speaker 1: They are safe because there's infrastructure, accountability standards UM. And 431 00:25:35,880 --> 00:25:38,199 Speaker 1: so when you think about sort of the ways in 432 00:25:38,240 --> 00:25:41,879 Speaker 1: which the business models work of social media platforms, what 433 00:25:42,040 --> 00:25:46,280 Speaker 1: gets amplified UM. What UM is sort of the incentive 434 00:25:46,280 --> 00:25:50,919 Speaker 1: structure of of what drives profits, how advertising is placed 435 00:25:51,040 --> 00:25:54,080 Speaker 1: up against certain types of content and not other type 436 00:25:54,080 --> 00:25:57,520 Speaker 1: of content, and how that type of content then gets prioritized. 437 00:25:57,880 --> 00:26:01,560 Speaker 1: You watch a set a certain section of choices that 438 00:26:01,600 --> 00:26:05,119 Speaker 1: are made that are far beyond freedom of speech. Freedom 439 00:26:05,160 --> 00:26:07,359 Speaker 1: of speech is not the same as freedom to be 440 00:26:07,400 --> 00:26:11,600 Speaker 1: amplified freedom of reach. And so to the extent that 441 00:26:11,800 --> 00:26:14,359 Speaker 1: UM when you see that companies are making these type 442 00:26:14,400 --> 00:26:18,320 Speaker 1: of choices, and then you look at the overwhelming body 443 00:26:18,320 --> 00:26:21,200 Speaker 1: of research that shows UM just you know, you can 444 00:26:21,280 --> 00:26:24,439 Speaker 1: look at a University of recent University of Cambridge study 445 00:26:24,440 --> 00:26:27,160 Speaker 1: that actually looks at who's getting more reach and who's 446 00:26:27,200 --> 00:26:29,520 Speaker 1: not getting more reach. If you see look at even 447 00:26:29,560 --> 00:26:32,640 Speaker 1: the safety and trust teams inside of Twitter that we're 448 00:26:32,640 --> 00:26:37,400 Speaker 1: pushing for more visibility and transparency around the algorithms. Those 449 00:26:37,440 --> 00:26:40,880 Speaker 1: people who have now been UM let go. We know 450 00:26:41,119 --> 00:26:45,199 Speaker 1: that UM the impact is clear that consequences for the 451 00:26:45,280 --> 00:26:49,600 Speaker 1: communities can be life or death in terms of how 452 00:26:49,760 --> 00:26:52,560 Speaker 1: how people are targeted, how people are exploited, how people 453 00:26:52,560 --> 00:26:54,520 Speaker 1: are put in harm's way, and when you have an 454 00:26:54,600 --> 00:26:58,320 Speaker 1: unaccountable billionaire running this company that feels he doesn't have 455 00:26:58,440 --> 00:27:01,800 Speaker 1: to listen to anyone. The best that we have is 456 00:27:01,840 --> 00:27:04,639 Speaker 1: the type of activism that holds those that seek to 457 00:27:04,760 --> 00:27:08,280 Speaker 1: enable this platform, enable this leader accountable. And that's what 458 00:27:08,359 --> 00:27:10,680 Speaker 1: we have to do. We have to speak truth to power. 459 00:27:10,760 --> 00:27:12,760 Speaker 1: We have to hold folks accountable, and we also have 460 00:27:12,840 --> 00:27:16,400 Speaker 1: to invite those who have a stake in this, even 461 00:27:16,400 --> 00:27:19,840 Speaker 1: if they don't see themselves as activists who believe in democracy, 462 00:27:20,040 --> 00:27:23,160 Speaker 1: who believe in fairness, to actually speak up and put 463 00:27:23,200 --> 00:27:27,159 Speaker 1: their hand on the scale as well. Now, last question, 464 00:27:27,320 --> 00:27:30,359 Speaker 1: the reason, you know, the timing is critical. We're heading 465 00:27:30,359 --> 00:27:34,159 Speaker 1: into a mid term election in just a few days. 466 00:27:34,560 --> 00:27:36,280 Speaker 1: You know, talk to us about the importance of that 467 00:27:36,359 --> 00:27:38,160 Speaker 1: given you know, we're about to talk about a story 468 00:27:38,160 --> 00:27:44,720 Speaker 1: about mid term candidates amplifying misinformation, getting the most engagement. Now, well, 469 00:27:44,760 --> 00:27:47,960 Speaker 1: that's and that's not an accident. Right. The what we're 470 00:27:48,000 --> 00:27:52,800 Speaker 1: seeing in terms of missing disinformation is not UM a 471 00:27:52,960 --> 00:27:56,560 Speaker 1: car accidenty right, It's not just something that happens. It's manufactured. 472 00:27:56,960 --> 00:28:02,440 Speaker 1: And when the tech platforms choose growth in profit over safety, 473 00:28:02,480 --> 00:28:06,439 Speaker 1: integrity and security, they create an incentive structure where people 474 00:28:06,480 --> 00:28:08,800 Speaker 1: believe that they're gonna benefit from it and that there 475 00:28:08,800 --> 00:28:10,520 Speaker 1: will be rewards for it and there will not be 476 00:28:10,640 --> 00:28:13,760 Speaker 1: consequences for it. And so when I think about even 477 00:28:13,840 --> 00:28:17,240 Speaker 1: some of the changes that have been announced more recently, right, 478 00:28:17,440 --> 00:28:21,240 Speaker 1: the eight dollars per um per month, which can seem 479 00:28:21,280 --> 00:28:24,359 Speaker 1: almost fair on its face that um Elon Musk is 480 00:28:24,440 --> 00:28:27,560 Speaker 1: charging for verification, Well, if you're not going to verify 481 00:28:27,840 --> 00:28:31,000 Speaker 1: the identity, which he has not committed to, although he 482 00:28:31,040 --> 00:28:34,080 Speaker 1: did talk about verification of identity on the call that 483 00:28:34,119 --> 00:28:37,360 Speaker 1: we had on Tuesday. But all of the information coming 484 00:28:37,400 --> 00:28:39,080 Speaker 1: out now is that they will not have time to 485 00:28:39,160 --> 00:28:42,880 Speaker 1: develop a verification UM system before they roll it out. 486 00:28:43,320 --> 00:28:47,360 Speaker 1: They can have folks claiming to be verified UM and 487 00:28:47,400 --> 00:28:52,640 Speaker 1: then renaming themselves CNN or Bloomberg renaming their names UM 488 00:28:52,760 --> 00:28:56,640 Speaker 1: under UM. The ausipicies of the Georgia's Secretary of State 489 00:28:56,920 --> 00:28:59,840 Speaker 1: and then making claims about the election under a very 490 00:29:00,040 --> 00:29:03,840 Speaker 1: high verified blue check because verification can be bought now 491 00:29:03,960 --> 00:29:07,480 Speaker 1: and not actually have some set level of accountability. We 492 00:29:07,680 --> 00:29:12,280 Speaker 1: watched after Elon Musk brought Twitter, the rise in the 493 00:29:12,400 --> 00:29:15,200 Speaker 1: use of the inn word because his followers believed that 494 00:29:15,280 --> 00:29:18,160 Speaker 1: they could now say that they could now move hateful 495 00:29:18,240 --> 00:29:20,760 Speaker 1: language on the platform because he would support it. We 496 00:29:20,840 --> 00:29:24,600 Speaker 1: have seen the increase of Q ANDN language in terms 497 00:29:24,680 --> 00:29:28,760 Speaker 1: on the platforms since he decided he was gonna buy 498 00:29:28,760 --> 00:29:32,720 Speaker 1: it back in April. Um over fifty of the counts 499 00:29:32,760 --> 00:29:36,800 Speaker 1: from mid October to now have UM that have been 500 00:29:36,840 --> 00:29:41,040 Speaker 1: amplifying Q and on um uh words and Q and 501 00:29:41,160 --> 00:29:45,880 Speaker 1: on phrases have have come on since Elon Musk announced 502 00:29:45,880 --> 00:29:48,479 Speaker 1: that he was gonna buy this buy this company. And 503 00:29:48,520 --> 00:29:52,080 Speaker 1: so we have watchful sort of the people around him, 504 00:29:52,120 --> 00:29:54,480 Speaker 1: the people who are fans of his, the people who 505 00:29:54,480 --> 00:29:57,480 Speaker 1: are supporting him, act out in ways. And then we've 506 00:29:57,560 --> 00:30:02,200 Speaker 1: watched Elon Musk validate that even his own behavior on 507 00:30:02,240 --> 00:30:07,880 Speaker 1: this platform, from amplifying an anti gay conspiracy theory against 508 00:30:08,000 --> 00:30:11,360 Speaker 1: Nancy Pelosi's husband to other things that he has tweeted 509 00:30:11,360 --> 00:30:14,320 Speaker 1: out since he has bought this company makes us all 510 00:30:14,400 --> 00:30:17,920 Speaker 1: have the question is he truly serious about leading this 511 00:30:18,040 --> 00:30:20,680 Speaker 1: company and and and a color Change. We have dealt 512 00:30:20,680 --> 00:30:24,760 Speaker 1: deeply with tech CEOs and signals across the board, and 513 00:30:24,840 --> 00:30:28,560 Speaker 1: I've never seen someone respond this way, So everyone should 514 00:30:28,600 --> 00:30:33,160 Speaker 1: be concerned. All right. Uh, to be fair, he did 515 00:30:33,200 --> 00:30:35,480 Speaker 1: delete that tweet, but you're right did come out in 516 00:30:35,520 --> 00:30:38,360 Speaker 1: the first place. Rashad Robinson, thanks for talking to us 517 00:30:38,400 --> 00:30:41,959 Speaker 1: about why this matters so much, President of Color of Change, 518 00:30:42,360 --> 00:30:58,320 Speaker 1: Thank you for stopping by for today's crypto report. We're 519 00:30:58,320 --> 00:31:02,480 Speaker 1: focusing on the web fundraising landscape of the top blockchain 520 00:31:02,600 --> 00:31:06,120 Speaker 1: venture capitalists. Bloom Shinali Bossik is in New York sale. 521 00:31:06,200 --> 00:31:08,120 Speaker 1: Thank you so much, Emily. I'm joined now by poly 522 00:31:08,240 --> 00:31:11,560 Speaker 1: Chain Capital general partner Naraj Pant. Polly Chain was created 523 00:31:11,560 --> 00:31:14,600 Speaker 1: in two dozen sixteen by Olaf Carson. We the third 524 00:31:14,640 --> 00:31:18,440 Speaker 1: employee at coin base. You know, Nag, Thank you so 525 00:31:18,560 --> 00:31:20,960 Speaker 1: much for your time, because you are seeing that you know, 526 00:31:21,080 --> 00:31:24,440 Speaker 1: little rally here and not just Bitcoin, You're seeing it 527 00:31:24,480 --> 00:31:27,000 Speaker 1: in a lot of alt coins. And I'd love your 528 00:31:27,200 --> 00:31:31,240 Speaker 1: perspective here in terms of how long that really holds 529 00:31:31,280 --> 00:31:33,280 Speaker 1: at a time that's been so volatile and whether that 530 00:31:33,320 --> 00:31:38,960 Speaker 1: even matters. Yeah, thank you Shinali. UM. I think the 531 00:31:38,960 --> 00:31:42,480 Speaker 1: big thing that we're focused on, you know, seeing sort 532 00:31:42,520 --> 00:31:45,400 Speaker 1: of how the markets have changed, is UM looking for 533 00:31:46,120 --> 00:31:50,360 Speaker 1: progress with with user adoption. I think our interest is 534 00:31:50,400 --> 00:31:55,280 Speaker 1: seeing the cryptocurrency space expand even more than it has today, 535 00:31:55,480 --> 00:31:59,000 Speaker 1: and we're excited to look at new UM, any new traction, 536 00:31:59,040 --> 00:32:01,640 Speaker 1: any new adoption, and so we hope that that kind 537 00:32:01,640 --> 00:32:04,000 Speaker 1: of takes place over the next couple of years as 538 00:32:04,000 --> 00:32:06,880 Speaker 1: we're investing into new companies. I'm kind of curious as 539 00:32:06,920 --> 00:32:09,240 Speaker 1: so what types of new investments you're willing to make 540 00:32:09,360 --> 00:32:12,840 Speaker 1: at this phase. Are there things you would avoid? Kind 541 00:32:12,840 --> 00:32:15,080 Speaker 1: of given the changes you're seeing in the market at large. 542 00:32:16,640 --> 00:32:20,720 Speaker 1: UM our strategy has remained relatively similar UM through both 543 00:32:20,760 --> 00:32:24,440 Speaker 1: bull and bear markets. UM. We've been around since and 544 00:32:24,480 --> 00:32:28,280 Speaker 1: have seen a number of different cycles, and what's important 545 00:32:28,320 --> 00:32:33,240 Speaker 1: to us is investing and hopefully generational companies and protocols 546 00:32:33,280 --> 00:32:36,600 Speaker 1: that I know we think can stand the test of time. UM. 547 00:32:36,640 --> 00:32:40,880 Speaker 1: We invest sort of across the space everywhere, from consumer 548 00:32:40,960 --> 00:32:45,080 Speaker 1: to infrastructure. UM. We think especially now, there's a lot 549 00:32:45,120 --> 00:32:50,560 Speaker 1: of exciting opportunities for infrastructure given the sort of slow 550 00:32:50,600 --> 00:32:53,280 Speaker 1: down in the markets. UM, we think this is a 551 00:32:53,320 --> 00:32:56,400 Speaker 1: good time for developers to come in and prepare for 552 00:32:56,520 --> 00:33:00,440 Speaker 1: the next wave of usage and adoption such that we 553 00:33:00,480 --> 00:33:04,560 Speaker 1: can really let a lot of people use usecryptocurrencies. I'm 554 00:33:04,640 --> 00:33:07,280 Speaker 1: kind of curious here in terms of what you see 555 00:33:07,520 --> 00:33:11,800 Speaker 1: in terms of jobs and investing in new people in 556 00:33:11,920 --> 00:33:14,120 Speaker 1: different spaces in this industry. You know, it was just 557 00:33:14,120 --> 00:33:16,440 Speaker 1: a couple of days ago that we've reported that Galaxy 558 00:33:16,840 --> 00:33:20,160 Speaker 1: Digital would be cutting a significant amount of its workforce. 559 00:33:20,520 --> 00:33:22,440 Speaker 1: Do you think that the industry still faces a lot 560 00:33:22,480 --> 00:33:26,680 Speaker 1: more pain when it comes to the workforce. UM. I 561 00:33:26,720 --> 00:33:31,880 Speaker 1: think we're lucky in that One important exciting trend about 562 00:33:31,920 --> 00:33:35,040 Speaker 1: a lot of crypto companies is that they don't require 563 00:33:35,040 --> 00:33:38,240 Speaker 1: as many employees to run. I think where we see 564 00:33:38,440 --> 00:33:42,360 Speaker 1: a lot of large Web two companies UM struggle is 565 00:33:42,400 --> 00:33:45,479 Speaker 1: that they often overhire and hire a lot more than 566 00:33:45,520 --> 00:33:48,080 Speaker 1: they need to run the service. I think a great 567 00:33:48,160 --> 00:33:50,480 Speaker 1: part of the Web three space is that many of 568 00:33:50,520 --> 00:33:53,920 Speaker 1: these protocols and companies are are run on Ethereum or 569 00:33:53,960 --> 00:33:57,880 Speaker 1: run on another large protocol and allows these teams to 570 00:33:57,960 --> 00:34:00,800 Speaker 1: operate a lot more leanly and and just with less 571 00:34:00,800 --> 00:34:04,000 Speaker 1: people overall. UM. So, while we still want to be 572 00:34:04,040 --> 00:34:07,800 Speaker 1: cautious in our approach and advising all our portfolio companies 573 00:34:07,840 --> 00:34:12,480 Speaker 1: not to be too um braws and about hiring and 574 00:34:12,520 --> 00:34:15,160 Speaker 1: spending UM. We do think that this is a great 575 00:34:15,200 --> 00:34:18,040 Speaker 1: sort of structural change in the way that Web three 576 00:34:18,040 --> 00:34:20,600 Speaker 1: companies are relative to to sort of Web two companies. 577 00:34:20,640 --> 00:34:23,400 Speaker 1: I'm glad you brought up Ethereum in that answer, because 578 00:34:23,440 --> 00:34:25,880 Speaker 1: I'm curious about what you think about Ethereum post emerge 579 00:34:26,080 --> 00:34:28,360 Speaker 1: and what does it mean in terms of its competition 580 00:34:28,360 --> 00:34:32,400 Speaker 1: when it comes to Bitcoin. We're seeing a lot of 581 00:34:32,440 --> 00:34:37,160 Speaker 1: exciting development happened on the on the Ethereum blockchain, both 582 00:34:37,160 --> 00:34:41,680 Speaker 1: from Ethereum itself, seeing the new East to Merge happened successfully, 583 00:34:42,120 --> 00:34:46,600 Speaker 1: seeing developers continuing to build applications, continuing to see a 584 00:34:46,680 --> 00:34:50,520 Speaker 1: lot of demand for everything from defied and f T 585 00:34:50,840 --> 00:34:54,799 Speaker 1: s UM and even transactions. And we're seeing a lot 586 00:34:54,840 --> 00:34:59,400 Speaker 1: of interesting opportunities being built around ethereum um. This includes 587 00:34:59,440 --> 00:35:03,239 Speaker 1: things like um what are called Layer two's roll ups 588 00:35:03,280 --> 00:35:07,920 Speaker 1: that allow you to scale transaction capacity even further UM, 589 00:35:07,960 --> 00:35:12,319 Speaker 1: seeing new privacy applications being built and and overall also 590 00:35:12,360 --> 00:35:16,720 Speaker 1: seeing a lot of traction from traditional companies hoping to 591 00:35:16,880 --> 00:35:19,960 Speaker 1: tap into the web through market and Ethereum and it's 592 00:35:19,960 --> 00:35:22,640 Speaker 1: sort of related projects is the way for these companies 593 00:35:22,680 --> 00:35:26,120 Speaker 1: to do that. So we're overall very happy and excited 594 00:35:26,120 --> 00:35:29,320 Speaker 1: about developer adoption and continue to track it very closely 595 00:35:29,520 --> 00:35:32,720 Speaker 1: on on Ethereum. Earlier this year we did see a 596 00:35:32,719 --> 00:35:35,680 Speaker 1: wave of companies that got into liquidity issues or had 597 00:35:35,760 --> 00:35:38,839 Speaker 1: to pause withdrawals. You had exposure to at least one 598 00:35:38,880 --> 00:35:41,319 Speaker 1: of them, right coin flex. What was there to be 599 00:35:41,440 --> 00:35:46,400 Speaker 1: learned from all of that this year? I think, Uh, 600 00:35:47,480 --> 00:35:49,400 Speaker 1: these are good lessons to learn for the for the 601 00:35:49,400 --> 00:35:55,080 Speaker 1: space overall. I think, UM, they teach these companies risk management, 602 00:35:55,680 --> 00:35:58,719 Speaker 1: and I think in some ways the failures we saw 603 00:35:58,760 --> 00:36:01,120 Speaker 1: in the space, we're not because as a web three 604 00:36:01,120 --> 00:36:05,240 Speaker 1: protocols and the smart contracts didn't work or anything like that, 605 00:36:05,520 --> 00:36:08,560 Speaker 1: but they were a failure of the meat space agreements, 606 00:36:08,600 --> 00:36:12,640 Speaker 1: you know, the real world legal contracts attesting to a 607 00:36:12,800 --> 00:36:15,840 Speaker 1: u M or attesting to UM proof of funds or 608 00:36:15,880 --> 00:36:18,640 Speaker 1: anything like that. In a number of cases UM, that 609 00:36:18,760 --> 00:36:21,680 Speaker 1: was what really failed UM. And so in some ways 610 00:36:21,719 --> 00:36:24,680 Speaker 1: it's highlighting systemic risks that exists not only in the 611 00:36:24,760 --> 00:36:27,640 Speaker 1: in the crypto financial space, but in the broader financial 612 00:36:27,640 --> 00:36:31,520 Speaker 1: industry as a whole, So I think it overalls strengthenings 613 00:36:31,560 --> 00:36:36,279 Speaker 1: both defy but also the crypto and financial space as 614 00:36:36,280 --> 00:36:39,839 Speaker 1: a whole. That's probably chained Capital's partner near agepan Take. 615 00:36:39,920 --> 00:36:41,520 Speaker 1: Thank you so much for your time. Back to you 616 00:36:41,520 --> 00:36:47,600 Speaker 1: in San franciscanly Shinios, thank you so much. Coming up, 617 00:36:48,360 --> 00:36:52,240 Speaker 1: as the mid terms are fast approaching, what's the impact 618 00:36:52,360 --> 00:36:56,799 Speaker 1: of misinformation still running on checked online, like the falsehood 619 00:36:57,120 --> 00:37:01,560 Speaker 1: that Donald Trump won election? Our social media companies doing 620 00:37:01,600 --> 00:37:17,640 Speaker 1: about it. We're going to talk about that next, all right, 621 00:37:17,640 --> 00:37:19,640 Speaker 1: don't want to continue our conversation now about the mid 622 00:37:19,800 --> 00:37:23,600 Speaker 1: terms and content moderation, and not just on Twitter, We're 623 00:37:23,640 --> 00:37:27,359 Speaker 1: also talking about Facebook and YouTube and other platforms. After 624 00:37:27,400 --> 00:37:31,280 Speaker 1: Bloomberg analyzed hundreds of candidates social media posts and found 625 00:37:31,680 --> 00:37:37,080 Speaker 1: rampant misinformation, Bloomberg's Jack Gillum poured through it all and 626 00:37:37,160 --> 00:37:40,080 Speaker 1: joins us now for more on his research, Jack, what 627 00:37:40,160 --> 00:37:46,640 Speaker 1: did you find about candidates amplifying misinformation, specifically the big lie? 628 00:37:47,400 --> 00:37:51,280 Speaker 1: How many of them are actually doing this? So emily, 629 00:37:51,320 --> 00:37:53,040 Speaker 1: we took a look at all of the republic and 630 00:37:53,040 --> 00:37:56,800 Speaker 1: candidates running for not just Congress but Secretary of State, 631 00:37:56,840 --> 00:38:00,359 Speaker 1: which oversees the vote count governor's attorneys general in all 632 00:38:00,400 --> 00:38:03,160 Speaker 1: the states across the country, and we found a hundred 633 00:38:03,160 --> 00:38:06,799 Speaker 1: and sixty candidates have been pushing what use called the 634 00:38:06,840 --> 00:38:09,960 Speaker 1: big live this is this you know, false theory or 635 00:38:09,960 --> 00:38:12,840 Speaker 1: this this this conspiracy theory and theory almost that Donald 636 00:38:12,840 --> 00:38:15,960 Speaker 1: Trump won the election, that Joe Biden is a diligiti 637 00:38:16,000 --> 00:38:18,279 Speaker 1: and president um. And So what we did is we 638 00:38:18,320 --> 00:38:20,920 Speaker 1: wanted to look at how these candidates running for office, 639 00:38:20,960 --> 00:38:23,200 Speaker 1: some of whom very well might went on Tuesday night, 640 00:38:24,000 --> 00:38:28,640 Speaker 1: actually pushed the meshes on platforms, especially now that Twitter 641 00:38:28,719 --> 00:38:31,640 Speaker 1: has a new owner, Facebook might not be labeling all 642 00:38:31,640 --> 00:38:33,359 Speaker 1: these ads, and we wanted to get a closer look 643 00:38:33,360 --> 00:38:37,760 Speaker 1: at what was really happening. So how did the companies 644 00:38:37,880 --> 00:38:42,320 Speaker 1: respond when you went to them with this? So Twitter 645 00:38:42,400 --> 00:38:45,120 Speaker 1: did not respond for comment. UM. We're not sure if 646 00:38:45,160 --> 00:38:48,600 Speaker 1: that's because the communications team either some folks were laid 647 00:38:48,640 --> 00:38:50,480 Speaker 1: off in the massive wayoffs has been happening in the 648 00:38:50,560 --> 00:38:54,960 Speaker 1: last day. UM. Facebook essentially said, look, we deal with 649 00:38:55,000 --> 00:38:57,160 Speaker 1: the you know, in their view, I guess the larger 650 00:38:57,200 --> 00:39:01,080 Speaker 1: issues preventing people from voting, violence, those sorts of things, 651 00:39:01,080 --> 00:39:04,120 Speaker 1: and that they run ads really encouraging people to vote 652 00:39:04,120 --> 00:39:07,399 Speaker 1: for and to say that, look, there's really not election misinformation. 653 00:39:07,480 --> 00:39:10,080 Speaker 1: This is the real deal. Um. But I think the 654 00:39:10,160 --> 00:39:12,680 Speaker 1: real questions you're going forward is why a lot of 655 00:39:12,680 --> 00:39:14,759 Speaker 1: these ads weren't flagged. And we did, in fact find 656 00:39:14,840 --> 00:39:18,080 Speaker 1: one ad by carry Lake, the Republican nominate for governor 657 00:39:18,120 --> 00:39:21,000 Speaker 1: of Arizona, where one of her false election claims was 658 00:39:21,040 --> 00:39:24,520 Speaker 1: actually flagged by Facebook, but the majority, in fact, almost 659 00:39:24,560 --> 00:39:29,719 Speaker 1: all the other ones we found were not. So just 660 00:39:29,840 --> 00:39:33,879 Speaker 1: three days to go before the election, how are you 661 00:39:33,960 --> 00:39:38,919 Speaker 1: expecting potential, you know, amplification of this to ramp up 662 00:39:39,440 --> 00:39:42,840 Speaker 1: before November eight? I mean, it's no secret that social 663 00:39:42,880 --> 00:39:45,880 Speaker 1: media is an important avenue that hundreds of millions of 664 00:39:45,880 --> 00:39:49,760 Speaker 1: Americans used. It's no secret also by that extent that Russia, 665 00:39:50,200 --> 00:39:53,040 Speaker 1: you know, really tried to hijack that in seen ahead 666 00:39:53,040 --> 00:39:55,640 Speaker 1: of that election. Um. I think this is going to 667 00:39:55,719 --> 00:39:57,600 Speaker 1: be an interesting thing to watch, is that we have 668 00:39:58,160 --> 00:40:00,440 Speaker 1: a new ownership at Twitter and what they're going to 669 00:40:00,480 --> 00:40:03,440 Speaker 1: do in terms of content moderation. We have Facebook that 670 00:40:03,520 --> 00:40:05,839 Speaker 1: has not labeled a lot of these ads that are 671 00:40:05,880 --> 00:40:09,480 Speaker 1: clear pieces of misinformation about election. I think it's going 672 00:40:09,520 --> 00:40:13,000 Speaker 1: to be a real interesting picture of how that misinformation 673 00:40:13,080 --> 00:40:15,160 Speaker 1: might play out in terms of votes, by the way, 674 00:40:15,200 --> 00:40:17,760 Speaker 1: not just being cast on Tuesday, but in the states 675 00:40:17,760 --> 00:40:20,759 Speaker 1: like Arizona with mail and balloting and early voting are 676 00:40:20,800 --> 00:40:25,440 Speaker 1: going on right now. So you know, what are you 677 00:40:25,440 --> 00:40:29,640 Speaker 1: expecting to happen next here, especially as you know these 678 00:40:29,640 --> 00:40:33,160 Speaker 1: elections are happening the ad industry and turmoil. These companies, 679 00:40:33,200 --> 00:40:35,520 Speaker 1: whether it's because of Elon Mosk or you know, a 680 00:40:35,520 --> 00:40:40,640 Speaker 1: broader economic slowdown, are kind of scrambling for revenue. I 681 00:40:40,640 --> 00:40:42,759 Speaker 1: think I think that's a good question, Emily. I think 682 00:40:42,760 --> 00:40:44,920 Speaker 1: what we're going to happen here is that you have 683 00:40:45,280 --> 00:40:46,880 Speaker 1: these companies that are going to have to grapple with 684 00:40:46,920 --> 00:40:50,280 Speaker 1: a serious issue of misinformation. It's one that has taken 685 00:40:50,800 --> 00:40:53,520 Speaker 1: hold in the Republican Party that we found in this 686 00:40:53,600 --> 00:40:56,799 Speaker 1: analysis again, so we'll just see what's going to happen 687 00:40:56,840 --> 00:41:01,840 Speaker 1: to come Tuesday. Jack Gillub, thank you so much for 688 00:41:01,920 --> 00:41:04,120 Speaker 1: your reporting. And that does it for this edition of 689 00:41:04,120 --> 00:41:06,719 Speaker 1: Bloomberg Technology. I'm Emily changing in San Francisco. Have a 690 00:41:06,760 --> 00:41:10,839 Speaker 1: wonderful weekend everyone. Brendan Carr will join us next week. 691 00:41:11,440 --> 00:41:12,200 Speaker 1: This is Bloomberg