1 00:00:01,360 --> 00:00:04,120 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, along 2 00:00:04,120 --> 00:00:06,200 Speaker 1: with my co host of Bonnie Quinn. Every business day 3 00:00:06,240 --> 00:00:10,360 Speaker 1: we bring you interviews from CEOs, market pros, and Bloomberg experts, 4 00:00:10,400 --> 00:00:13,600 Speaker 1: along with essential market moving news. Find the Bloomberg Markets 5 00:00:13,600 --> 00:00:17,000 Speaker 1: Podcast on Apple podcast or wherever you listen to podcasts, 6 00:00:17,000 --> 00:00:20,720 Speaker 1: and on Bloomberg dot com. It is time now to 7 00:00:20,760 --> 00:00:24,160 Speaker 1: welcome Danielle di Martineau, boost CEO and director of Intelligence 8 00:00:24,160 --> 00:00:27,200 Speaker 1: at Quill Intelligence. Of course, Danielle's former advisor at the 9 00:00:27,280 --> 00:00:30,480 Speaker 1: Dallas Fed and also a Bloomberg opinion columnists and she's 10 00:00:30,480 --> 00:00:33,839 Speaker 1: based in Dallas. Danielle, what do you make of the 11 00:00:33,920 --> 00:00:37,000 Speaker 1: idea that we may not get stimulus before the election 12 00:00:37,440 --> 00:00:41,960 Speaker 1: while the pandemic lingers. So there's that, and that will 13 00:00:42,080 --> 00:00:47,080 Speaker 1: definitely put a pin in any kind of burgeoning recovery 14 00:00:47,120 --> 00:00:51,080 Speaker 1: that we're seeing. Well, I think that there are two 15 00:00:51,120 --> 00:00:55,200 Speaker 1: different factors at work in today's market. One of them 16 00:00:55,400 --> 00:00:58,400 Speaker 1: is that there's this underlying weakness that is going to 17 00:00:58,440 --> 00:01:02,320 Speaker 1: continue to play out and stay and local employment for example, 18 00:01:02,840 --> 00:01:06,399 Speaker 1: in in in families who are just getting by and 19 00:01:06,440 --> 00:01:10,959 Speaker 1: we're waiting patiently as as they could for that next 20 00:01:11,400 --> 00:01:15,640 Speaker 1: true stimulus package that provided them with a weekly jolt 21 00:01:16,000 --> 00:01:18,880 Speaker 1: of of income while they continue to wait out a 22 00:01:19,040 --> 00:01:23,600 Speaker 1: full and escape velocity, if you will, reopening of the 23 00:01:23,680 --> 00:01:26,479 Speaker 1: U S economy. The other thing I think that's at 24 00:01:26,520 --> 00:01:29,920 Speaker 1: play today, though, is the market trying to wrap its 25 00:01:29,920 --> 00:01:35,360 Speaker 1: head around quantitatively what the stop gap measures will accomplish. 26 00:01:35,600 --> 00:01:38,320 Speaker 1: There is a lot of money in Uncle Sam's checking account, 27 00:01:38,680 --> 00:01:42,399 Speaker 1: the Treasury General account, and money that can be can 28 00:01:42,440 --> 00:01:45,959 Speaker 1: be pulled upon. But what what will what will it 29 00:01:46,040 --> 00:01:50,240 Speaker 1: do to say, keep the airline workers on payrolls versus 30 00:01:50,320 --> 00:01:53,360 Speaker 1: the rest of the country that needs stimulus measures not 31 00:01:53,440 --> 00:01:57,320 Speaker 1: receiving them. What might do you can those checks come 32 00:01:57,320 --> 00:02:00,800 Speaker 1: out before election day? And most importantly, I think what's 33 00:02:00,880 --> 00:02:05,800 Speaker 1: driving trading today is rumblings on trading floors about Bill 34 00:02:05,840 --> 00:02:09,240 Speaker 1: Gates saying we might not need a vaccine. If what 35 00:02:09,440 --> 00:02:12,239 Speaker 1: treated President Trump is as good as it is, we 36 00:02:12,320 --> 00:02:15,120 Speaker 1: might be able to move past the pandemic with just 37 00:02:15,200 --> 00:02:20,280 Speaker 1: treatments in hand. So, Danielle, you know, the the administration 38 00:02:20,360 --> 00:02:23,960 Speaker 1: is touting uh, the declining unemployment rate, the fact that 39 00:02:24,000 --> 00:02:26,440 Speaker 1: the people are going back to work, But at the 40 00:02:26,520 --> 00:02:29,720 Speaker 1: same time we see big companies like the Walt Disney 41 00:02:29,760 --> 00:02:32,519 Speaker 1: Company talking about, you know, laying off an additional twenty 42 00:02:32,639 --> 00:02:36,480 Speaker 1: eight thousand employees. What is your sense as to the 43 00:02:36,639 --> 00:02:41,160 Speaker 1: underlying health of the employment market or lack there of 44 00:02:41,280 --> 00:02:45,480 Speaker 1: in the United States. Well, I think it's more important 45 00:02:45,560 --> 00:02:49,040 Speaker 1: to look past. Twenty eight thousand is a huge mass 46 00:02:49,120 --> 00:02:51,920 Speaker 1: layoff figure. It gates gets a lot of headlines, but 47 00:02:52,000 --> 00:02:55,000 Speaker 1: two thirds of those workers were part time, So the 48 00:02:55,160 --> 00:02:59,000 Speaker 1: economic the macroeconomic impact is not nearly as bad as 49 00:02:59,040 --> 00:03:01,160 Speaker 1: well as fargoes intent this morning that it was going 50 00:03:01,200 --> 00:03:03,960 Speaker 1: to be laying up and another seven hundred employees of 51 00:03:04,080 --> 00:03:08,239 Speaker 1: KPMG announcing that it would be laying off white collar 52 00:03:08,280 --> 00:03:12,160 Speaker 1: workers in tax and auditing and consulting UM. The list 53 00:03:12,200 --> 00:03:15,000 Speaker 1: goes on and on of companies that are beginning to 54 00:03:15,040 --> 00:03:19,600 Speaker 1: cut at headquarters salaried employees. If you looked at the 55 00:03:19,760 --> 00:03:23,880 Speaker 1: job openings data yesterday, the worst category by far was 56 00:03:24,040 --> 00:03:28,320 Speaker 1: business and professional services, and in Friday's Peril Report we 57 00:03:28,400 --> 00:03:31,640 Speaker 1: saw three consecutive months of losses again in business and 58 00:03:31,680 --> 00:03:35,440 Speaker 1: professional services. These are the highest paying positions that account 59 00:03:35,520 --> 00:03:39,000 Speaker 1: for the vast majority of US consumption, and they will 60 00:03:39,000 --> 00:03:42,720 Speaker 1: continue As these white collar job losses percolate through the economy. 61 00:03:42,920 --> 00:03:44,960 Speaker 1: That will continue to trickle down, but not in a 62 00:03:45,000 --> 00:03:48,040 Speaker 1: good way to the smaller businesses that are still holding 63 00:03:48,080 --> 00:03:53,080 Speaker 1: on but in need of their of their business. So, Danielle, 64 00:03:53,080 --> 00:03:56,520 Speaker 1: what happens next? How does the economy recover? How do 65 00:03:56,600 --> 00:03:59,440 Speaker 1: people get by? I mean what the federals are has 66 00:03:59,480 --> 00:04:01,800 Speaker 1: done as much as it can. There's possibly things that 67 00:04:01,880 --> 00:04:03,960 Speaker 1: can do. It says, it's toolbox is never empty. But 68 00:04:04,560 --> 00:04:09,080 Speaker 1: essentially this is a federal government issue. Does Joe Biden 69 00:04:09,080 --> 00:04:11,480 Speaker 1: need to get elected and then, you know, implement a 70 00:04:11,680 --> 00:04:16,480 Speaker 1: huge amount of stimulus. Well, I think the scenario that 71 00:04:16,600 --> 00:04:18,719 Speaker 1: the ladder of the two scenarios that you just painted 72 00:04:18,720 --> 00:04:21,400 Speaker 1: out has been playing out in the bond market for 73 00:04:21,440 --> 00:04:23,880 Speaker 1: the better part of a week now. We've seen bond 74 00:04:23,920 --> 00:04:26,200 Speaker 1: yields break out of a very tight range in which 75 00:04:26,240 --> 00:04:30,520 Speaker 1: they've been stuck anticipating some massive stimulus spending bill. Uh. 76 00:04:30,560 --> 00:04:34,760 Speaker 1: If Biden is victorious on on election day or in 77 00:04:34,760 --> 00:04:38,200 Speaker 1: the days that follow, the question I have though for 78 00:04:38,240 --> 00:04:41,440 Speaker 1: all politicians inside the Beltway is whether or not they're 79 00:04:41,440 --> 00:04:44,760 Speaker 1: going to be looking to implement some programs that have 80 00:04:44,839 --> 00:04:50,719 Speaker 1: proven successful in Germany, jobs, reskills, training, vocational training, infrastructure 81 00:04:50,800 --> 00:04:54,919 Speaker 1: spending more than throwing money at people who who need it. 82 00:04:54,960 --> 00:04:56,520 Speaker 1: And I'm not saying we should put people out on 83 00:04:56,560 --> 00:04:59,599 Speaker 1: the street by any means, but more than that, actually 84 00:04:59,720 --> 00:05:03,279 Speaker 1: pro biting means by which people can get back into 85 00:05:03,360 --> 00:05:06,840 Speaker 1: the workforce forcibly the way that it was done years 86 00:05:06,880 --> 00:05:09,400 Speaker 1: ago in the New Deal, when there were no bridges 87 00:05:09,400 --> 00:05:12,480 Speaker 1: and tunnels. Now we just have crumbling bridges and tunnels 88 00:05:12,560 --> 00:05:15,560 Speaker 1: and roads that need to be repaired. I would hope 89 00:05:15,560 --> 00:05:19,120 Speaker 1: that the Order of Business number one would be looking 90 00:05:19,240 --> 00:05:23,239 Speaker 1: to stimulus spending measures that not just make sure people 91 00:05:23,279 --> 00:05:25,880 Speaker 1: were put back on their feet, but also that gave 92 00:05:25,920 --> 00:05:29,839 Speaker 1: them job opportunities. So, Danielle, we heard from FED Chairman 93 00:05:29,880 --> 00:05:34,280 Speaker 1: pal You speaking yesterday at an economics conference calling for 94 00:05:34,560 --> 00:05:39,520 Speaker 1: fiscal stimulus. Yet again, um does Congress listen to to 95 00:05:40,000 --> 00:05:43,760 Speaker 1: FED chair people when FED chairman when they do speak 96 00:05:43,800 --> 00:05:48,880 Speaker 1: about fiscal stimulus, Well, congress is track record is pretty 97 00:05:49,080 --> 00:05:52,440 Speaker 1: is pretty spotty on that account. Bernanke spent years of 98 00:05:52,560 --> 00:05:56,320 Speaker 1: his career as head of the fed UH pleading with 99 00:05:56,400 --> 00:05:59,000 Speaker 1: Congress to do more on the fiscal side and to 100 00:05:59,080 --> 00:06:01,960 Speaker 1: be more creative on a fiscal side, and he got 101 00:06:01,960 --> 00:06:04,080 Speaker 1: the heisman time and again, which is why we ended 102 00:06:04,120 --> 00:06:07,359 Speaker 1: up having q E two and que three. Uh. The 103 00:06:07,440 --> 00:06:09,520 Speaker 1: problem I have with with Powell, though, is on a 104 00:06:09,520 --> 00:06:12,599 Speaker 1: more fundamental level, and that is that it appears that 105 00:06:12,760 --> 00:06:16,080 Speaker 1: most of the Fed's tools in the toolbox are broken. 106 00:06:16,520 --> 00:06:19,080 Speaker 1: And the one thing that that Powell knows he can 107 00:06:19,080 --> 00:06:22,880 Speaker 1: do if there's fresh treasury issuance in order to finance 108 00:06:23,320 --> 00:06:27,960 Speaker 1: stimulus spending, it is by those bonds via quantitative eavening 109 00:06:28,000 --> 00:06:31,760 Speaker 1: that filters back into the stock market. Daniel d Martino Booth, 110 00:06:31,760 --> 00:06:33,680 Speaker 1: thank you so much for joining us yet again. We 111 00:06:33,680 --> 00:06:37,080 Speaker 1: always appreciate your insights. Danielle de Martino Boots, CEO and 112 00:06:37,120 --> 00:06:41,080 Speaker 1: directive intelligence at Quill Intelligence, former advisor at the Dallas 113 00:06:41,120 --> 00:06:45,000 Speaker 1: Federal Reserve, and a Bloomberg Opinion columnists. Also you know 114 00:06:45,279 --> 00:06:49,520 Speaker 1: just extraordinary book. She's the author of fed Up, an 115 00:06:49,560 --> 00:06:54,679 Speaker 1: insider's take on why the Federal Reserve is bad for America. 116 00:06:55,400 --> 00:06:58,440 Speaker 1: It is time for Bloomberg Opinion on Bloomberg Radio. Tai 117 00:06:58,560 --> 00:07:02,039 Speaker 1: Kim Technology Commas for Bloomberg Opinion joins is here. There's 118 00:07:02,080 --> 00:07:06,039 Speaker 1: some significant news out recently. The House of Representatives out 119 00:07:06,040 --> 00:07:10,520 Speaker 1: with a report suggesting some key regulatory oversight provisions for 120 00:07:10,600 --> 00:07:15,120 Speaker 1: some of the biggest tech companies out there, including Apple, Google, Amazon, 121 00:07:15,360 --> 00:07:18,320 Speaker 1: and Facebook. Take Kim, thanks for joining us. We really 122 00:07:18,320 --> 00:07:20,640 Speaker 1: appreciate it. How it just give us a sense of 123 00:07:20,680 --> 00:07:24,760 Speaker 1: what the House report says and how worried does some 124 00:07:24,800 --> 00:07:28,760 Speaker 1: of these tech companies be. I think the technology companies 125 00:07:28,760 --> 00:07:32,520 Speaker 1: should be worried. Um, this report was four hundred fifty pages. 126 00:07:33,240 --> 00:07:36,560 Speaker 1: The subcommittee poured over one point three million documents, and 127 00:07:36,600 --> 00:07:39,520 Speaker 1: they really laid out the case and a pattern of 128 00:07:39,560 --> 00:07:42,360 Speaker 1: anti competite behavior by each and every one of these 129 00:07:42,360 --> 00:07:44,840 Speaker 1: big tech companies. And it kind of lays our role 130 00:07:44,920 --> 00:07:48,680 Speaker 1: map and a case for action over in that coming year. 131 00:07:48,760 --> 00:07:51,320 Speaker 1: And they gave a bunch of remedies. Some of them 132 00:07:51,480 --> 00:07:54,200 Speaker 1: more aggressive ones may not happen and buy pars in Congress, 133 00:07:54,200 --> 00:07:57,040 Speaker 1: but you never know what happens with the November election. 134 00:07:57,120 --> 00:07:59,800 Speaker 1: If there's a Democratic sweep, and I do think we're 135 00:07:59,800 --> 00:08:02,200 Speaker 1: gonna there's a good chance some of these remedies will 136 00:08:02,240 --> 00:08:05,040 Speaker 1: be pointed action in coming. Here do we have an 137 00:08:05,040 --> 00:08:09,280 Speaker 1: outline of the types of remedies Congress is looking for? Yeah, 138 00:08:09,280 --> 00:08:12,280 Speaker 1: they have like a dozen things in there. Um. The 139 00:08:12,320 --> 00:08:16,040 Speaker 1: most important one is a structural separation of any dominant 140 00:08:16,080 --> 00:08:21,360 Speaker 1: platform if they compete with other competitors on their business. UM. 141 00:08:21,400 --> 00:08:25,160 Speaker 1: Another big one is a shift of burdener proof. So 142 00:08:25,200 --> 00:08:28,640 Speaker 1: whenever of these big dominant platform big tech companies by 143 00:08:28,800 --> 00:08:30,920 Speaker 1: company in the future, UM, they're going to have to 144 00:08:30,960 --> 00:08:33,760 Speaker 1: prove that it's not anti competitive. So the burdener approof 145 00:08:33,760 --> 00:08:37,920 Speaker 1: will beyond the technology company to argue that it's not 146 00:08:38,000 --> 00:08:41,680 Speaker 1: anti competitors. So those are two big ones. UM. So 147 00:08:41,840 --> 00:08:44,320 Speaker 1: there are a lot of recommendations that they lay it out. 148 00:08:45,240 --> 00:08:48,240 Speaker 1: So tell you I think you know. Historically the United 149 00:08:48,280 --> 00:08:52,360 Speaker 1: States has taken a very light touch too big tech 150 00:08:52,400 --> 00:08:56,040 Speaker 1: in terms of regulations, I guess, preferring to foster innovation. 151 00:08:56,360 --> 00:08:58,920 Speaker 1: And we're gonna argue whether that's been positive or negative, 152 00:08:58,920 --> 00:09:02,040 Speaker 1: but certainly it's helped Silicon Valley. Is there a real 153 00:09:02,240 --> 00:09:07,600 Speaker 1: bipartisan support for significantly regulating these big tech companies like 154 00:09:07,679 --> 00:09:12,280 Speaker 1: an Amazon, like an Apple? Right now? There isn't bipart 155 00:09:12,760 --> 00:09:15,720 Speaker 1: support for the more aggressive remedies, but there is support 156 00:09:15,800 --> 00:09:19,400 Speaker 1: for certain things such as increasing funding for the antitrust 157 00:09:19,480 --> 00:09:23,319 Speaker 1: regulators DEDC and the Anti Trust Division the t o 158 00:09:23,440 --> 00:09:27,400 Speaker 1: j UM. But yes, there isn't like the Republicans aren't 159 00:09:27,400 --> 00:09:31,400 Speaker 1: a board for more of these uh progressive breakup actions. 160 00:09:32,480 --> 00:09:34,120 Speaker 1: Does any of this change if we get a change 161 00:09:34,120 --> 00:09:37,000 Speaker 1: in leadership or even you know, the change in the 162 00:09:37,040 --> 00:09:40,400 Speaker 1: Senate for example. I think so like if the Senate 163 00:09:40,520 --> 00:09:44,720 Speaker 1: changes and there's a Biden administration. Um, it was reported 164 00:09:44,760 --> 00:09:48,280 Speaker 1: earlier this week the Biden the Biden team was given 165 00:09:48,280 --> 00:09:50,760 Speaker 1: the heads up on this report. So I think if 166 00:09:50,760 --> 00:09:54,720 Speaker 1: we see a democratic administration, will see some action. Another 167 00:09:54,760 --> 00:09:58,680 Speaker 1: thing that the report outlined was UM potential limits on 168 00:09:58,720 --> 00:10:02,520 Speaker 1: self preferential behavi year by Google and Apple. So what 169 00:10:02,640 --> 00:10:06,680 Speaker 1: Google does is they kind of bolster their own services 170 00:10:06,679 --> 00:10:10,520 Speaker 1: on top of search results and potentially with either the 171 00:10:10,600 --> 00:10:14,600 Speaker 1: d o J, which actually is on the Trump administration, UM, 172 00:10:14,679 --> 00:10:17,440 Speaker 1: potentially putting out the report leader this week or next 173 00:10:17,440 --> 00:10:21,600 Speaker 1: week to go after Google in terms of the the antitrust lawsuit. UM, 174 00:10:21,640 --> 00:10:24,240 Speaker 1: that's another thing that that could be put in action. 175 00:10:24,400 --> 00:10:28,199 Speaker 1: And also Apples app Store. UM, I could see it 176 00:10:28,440 --> 00:10:33,480 Speaker 1: certain legislation to limit Apple from preferential treatment for their 177 00:10:33,960 --> 00:10:38,320 Speaker 1: apps and services. So tell you, I think even last year, 178 00:10:38,960 --> 00:10:42,880 Speaker 1: I believe it was when the Federal Trade Commission and 179 00:10:42,920 --> 00:10:46,160 Speaker 1: the Department of Justice kind of divvied up these big 180 00:10:46,200 --> 00:10:48,440 Speaker 1: tech companies and say, okay, you take a look, you 181 00:10:48,720 --> 00:10:50,959 Speaker 1: d J, you take a look at these companies. You 182 00:10:51,080 --> 00:10:53,560 Speaker 1: Federal Trade Commission, you take a look at these companies. 183 00:10:53,840 --> 00:10:57,040 Speaker 1: Is this report in concert with those investigations or is 184 00:10:57,080 --> 00:10:59,959 Speaker 1: it separate from them? And and how are they tied together? 185 00:11:00,040 --> 00:11:03,600 Speaker 1: If at all? So, I think they're pretty separate. This 186 00:11:03,720 --> 00:11:07,719 Speaker 1: was the House subcommittee doing their investigation. The d o 187 00:11:07,800 --> 00:11:10,560 Speaker 1: j it's is on their own path, and the most 188 00:11:10,600 --> 00:11:14,360 Speaker 1: imminent one is a lawsuit that's going to to Google 189 00:11:14,480 --> 00:11:18,640 Speaker 1: for their search engine and the dominance and the ad 190 00:11:18,679 --> 00:11:21,600 Speaker 1: platform business. But I do believe they're separate. But they 191 00:11:21,640 --> 00:11:24,760 Speaker 1: all they're all tied in together of greatest scrutiny of 192 00:11:24,840 --> 00:11:29,240 Speaker 1: big technology companies because I mean, everyone agrees that these 193 00:11:29,240 --> 00:11:33,280 Speaker 1: companies are just so dominant in their markets and something 194 00:11:33,320 --> 00:11:35,680 Speaker 1: needs to be done. And this four hundred fifty page 195 00:11:35,720 --> 00:11:37,960 Speaker 1: report really I think it is an important step because 196 00:11:37,960 --> 00:11:41,840 Speaker 1: the outlines the huge pattern of behavior. Uh Specifically, I 197 00:11:41,840 --> 00:11:44,720 Speaker 1: think the most egregious is Amazon in terms of how 198 00:11:44,760 --> 00:11:48,960 Speaker 1: they know aplied on individual seller data to inform their 199 00:11:48,960 --> 00:11:52,959 Speaker 1: private label business. So there's this great pattern behavior of 200 00:11:53,000 --> 00:11:56,760 Speaker 1: these companies using their market power. And I think this, 201 00:11:56,760 --> 00:12:00,480 Speaker 1: this report, this vast report, is really good step in 202 00:12:00,600 --> 00:12:04,000 Speaker 1: terms of going to the next level of actual actions 203 00:12:04,040 --> 00:12:06,800 Speaker 1: against these companies. So these companies, many of them, have 204 00:12:06,880 --> 00:12:12,560 Speaker 1: been dealing with or working with these types of issues. 205 00:12:12,640 --> 00:12:14,760 Speaker 1: Let's say, in Europe for a very very long time. 206 00:12:14,800 --> 00:12:17,440 Speaker 1: Margaret of s day Or was one of the most 207 00:12:17,600 --> 00:12:20,920 Speaker 1: fierce competition commissioners that the European Commission has ever seen. 208 00:12:21,080 --> 00:12:23,120 Speaker 1: And all of the companies that we're talking about how 209 00:12:23,160 --> 00:12:27,880 Speaker 1: to work with her, What lessons can they learn in 210 00:12:28,040 --> 00:12:30,560 Speaker 1: terms of how they deal with Congress? How will how 211 00:12:30,600 --> 00:12:33,720 Speaker 1: will you know what the US wants from these companies 212 00:12:33,760 --> 00:12:36,400 Speaker 1: differ from what the EU wanted and ultimately got from 213 00:12:36,400 --> 00:12:39,400 Speaker 1: most of these companies. So the EU is actually in 214 00:12:39,480 --> 00:12:43,000 Speaker 1: progress with a number of these antitrust probes. Also, they 215 00:12:43,080 --> 00:12:46,640 Speaker 1: started a few months ago invest seeing Apple and how 216 00:12:46,800 --> 00:12:50,400 Speaker 1: they require their in app purchasing and the fift cut. 217 00:12:50,520 --> 00:12:52,839 Speaker 1: So I think we're actually going to see a lot 218 00:12:52,840 --> 00:12:57,160 Speaker 1: of these actions come together at once, and the EU 219 00:12:57,240 --> 00:13:00,280 Speaker 1: is still involved and really working, especially on the Apples. 220 00:13:00,480 --> 00:13:03,200 Speaker 1: So I think we'll see a lot of these governments, 221 00:13:03,200 --> 00:13:05,240 Speaker 1: but they're all all on there are on all their 222 00:13:05,280 --> 00:13:09,640 Speaker 1: stuff tracks, like they're not really working together. Um, potentially 223 00:13:09,720 --> 00:13:11,839 Speaker 1: we'll see the state, the trained generals and the d 224 00:13:11,960 --> 00:13:13,480 Speaker 1: o J I think the d J is trying to 225 00:13:13,480 --> 00:13:17,400 Speaker 1: get this data trainee channels on board for their Google lawsuits, 226 00:13:17,400 --> 00:13:19,760 Speaker 1: so they're all on this epic tracks. But I do 227 00:13:19,840 --> 00:13:22,520 Speaker 1: think over the coming year, we're just going to see 228 00:13:22,559 --> 00:13:26,720 Speaker 1: more scrutiny action. You look at the stocks, the stocks 229 00:13:26,720 --> 00:13:29,000 Speaker 1: are not worried. Stocks are trading up, they're not trading 230 00:13:29,040 --> 00:13:33,720 Speaker 1: down on this news. Particularly. What does that tell you time, Um, 231 00:13:34,080 --> 00:13:36,400 Speaker 1: I think day to day it's it's it's tough to say. 232 00:13:36,480 --> 00:13:40,360 Speaker 1: I mean, I think this stuff is going to take 233 00:13:40,400 --> 00:13:43,679 Speaker 1: a long time to get legislated out, a year or 234 00:13:43,679 --> 00:13:46,400 Speaker 1: two at the earliest. I mean, this is not something 235 00:13:46,440 --> 00:13:48,319 Speaker 1: that you could flip on a switch and say, oh, 236 00:13:48,880 --> 00:13:50,880 Speaker 1: new Congress to kind of work on it. So it's 237 00:13:50,880 --> 00:13:54,200 Speaker 1: gonna take time. And I mean I don't really foresee 238 00:13:54,240 --> 00:13:57,240 Speaker 1: like vast breakup per se, but I do see on 239 00:13:57,280 --> 00:14:01,680 Speaker 1: the margin rule changes limiting acqua eficians, like I said, 240 00:14:01,720 --> 00:14:04,480 Speaker 1: the self preferential behavior and maybe prep and it's not 241 00:14:04,520 --> 00:14:07,679 Speaker 1: being compelled to give up the private business. So I'm 242 00:14:07,720 --> 00:14:10,120 Speaker 1: not saying that you know, they're earning power and gets 243 00:14:10,120 --> 00:14:13,680 Speaker 1: smashed because of their scrutiny, But I do think there 244 00:14:13,679 --> 00:14:16,199 Speaker 1: will be accents where there will be limits to their 245 00:14:16,240 --> 00:14:20,080 Speaker 1: behaviors and in terms of crushing competitors and things of that, 246 00:14:20,160 --> 00:14:22,320 Speaker 1: some of that action will will be under this also. 247 00:14:23,440 --> 00:14:26,880 Speaker 1: Take him, always a fascinating conversation. Take him as technology 248 00:14:26,960 --> 00:14:30,040 Speaker 1: columnists for Bloomberg Opinion, and we thank him for joining 249 00:14:30,080 --> 00:14:32,520 Speaker 1: us today. And you know, it really is interesting called 250 00:14:32,680 --> 00:14:36,120 Speaker 1: you preparing you know, a Digital Services Act, so an 251 00:14:36,160 --> 00:14:39,120 Speaker 1: actual act of regulation. And if you go on a 252 00:14:39,200 --> 00:14:42,880 Speaker 1: website for any of these companies in Europe at the moment, 253 00:14:42,880 --> 00:14:44,760 Speaker 1: you know, you have to answer a whole load of 254 00:14:45,080 --> 00:14:49,000 Speaker 1: information about you know, what you're allowing them to take 255 00:14:49,040 --> 00:14:50,800 Speaker 1: from you in terms of your privacy and so on. 256 00:14:50,880 --> 00:14:53,480 Speaker 1: You don't you don't typically get that yet in the US. 257 00:14:56,000 --> 00:14:57,880 Speaker 1: Let's get straight to our next guest. He needs, you know, 258 00:14:58,040 --> 00:15:03,000 Speaker 1: is political contributor and professor polit legal science at Iona College, Jennie. 259 00:15:03,080 --> 00:15:05,680 Speaker 1: A lot to talk about, not least the VP debate tonight, 260 00:15:05,720 --> 00:15:09,160 Speaker 1: but first let's talk about Nancy Pelosi trolling the President 261 00:15:09,320 --> 00:15:10,960 Speaker 1: on the view a few moments ago. Having had a 262 00:15:11,000 --> 00:15:14,240 Speaker 1: conversation this morning with Steve Mnuchen about airline aide that 263 00:15:14,280 --> 00:15:18,880 Speaker 1: apparently is going nowhere. Does Donald Trump bite before the 264 00:15:18,800 --> 00:15:22,239 Speaker 1: debate tonight? Does he make some kind of unilateral announcement 265 00:15:22,840 --> 00:15:26,640 Speaker 1: or something to do with stimulus. You know, I'm not 266 00:15:26,800 --> 00:15:31,440 Speaker 1: very good at predicting what Donald Trump will do. I 267 00:15:31,800 --> 00:15:34,240 Speaker 1: hesitate to do that, but if I had to guess, 268 00:15:34,280 --> 00:15:36,920 Speaker 1: I would say I do think he will respond. Um. 269 00:15:36,960 --> 00:15:39,440 Speaker 1: He was very very active on Twitter, as you know, 270 00:15:39,520 --> 00:15:42,360 Speaker 1: and you've been talking about all night, um and so 271 00:15:42,800 --> 00:15:45,880 Speaker 1: you know from yesterday late yesterday to into today. So 272 00:15:46,280 --> 00:15:49,120 Speaker 1: I would be surprised if he didn't respond. And of 273 00:15:49,160 --> 00:15:52,640 Speaker 1: course this does I have to say, this does work 274 00:15:52,680 --> 00:15:56,600 Speaker 1: to the President's advantage. He he wants to um, you know, 275 00:15:56,720 --> 00:16:01,479 Speaker 1: set this up as a debate between him and particularly 276 00:16:01,480 --> 00:16:04,840 Speaker 1: the Democratic leadership in the House, led by Nancy Pelosi. 277 00:16:04,960 --> 00:16:06,800 Speaker 1: So I think any chance he gets to do that, 278 00:16:06,880 --> 00:16:09,600 Speaker 1: he's going to do that. And this is a way 279 00:16:09,600 --> 00:16:12,120 Speaker 1: to energize his base. So I would be surprised if 280 00:16:12,160 --> 00:16:15,480 Speaker 1: he didn't respond. Genny, you know, I want to ask 281 00:16:15,520 --> 00:16:19,240 Speaker 1: you about what you think President trump strategy is here. 282 00:16:19,280 --> 00:16:21,480 Speaker 1: But every time I mentioned President Trump and strategy, Tim 283 00:16:21,520 --> 00:16:25,720 Speaker 1: O'Brien Bloomberg Opinion Calmness and long time Trump chronicle or 284 00:16:25,760 --> 00:16:28,600 Speaker 1: tells me that the president does not have a strategy. 285 00:16:28,640 --> 00:16:31,560 Speaker 1: But what do you think his strategy is here so 286 00:16:31,600 --> 00:16:38,280 Speaker 1: close to the election, seemingly handing the opposition of victory. Yeah, 287 00:16:38,280 --> 00:16:39,840 Speaker 1: and I would have to say, you just made me 288 00:16:39,920 --> 00:16:42,320 Speaker 1: chuckle because Tim is so right about that, and I 289 00:16:42,360 --> 00:16:45,080 Speaker 1: would never ever disagree with him on anything to do 290 00:16:45,120 --> 00:16:47,600 Speaker 1: with Trump. Um, and I do think he's right. There 291 00:16:47,640 --> 00:16:50,480 Speaker 1: does not seem to be a strategy. And in this case, 292 00:16:50,520 --> 00:16:53,320 Speaker 1: when we were getting these tweets last night, these mixed 293 00:16:53,360 --> 00:16:57,640 Speaker 1: messages about the stimulus package, I was scratching my head 294 00:16:57,680 --> 00:17:00,360 Speaker 1: to try to figure out what could the thing king be. 295 00:17:00,680 --> 00:17:04,160 Speaker 1: For most people running for office, the opportunity to invest 296 00:17:04,280 --> 00:17:06,880 Speaker 1: money into the pockets of the people voting for them 297 00:17:07,119 --> 00:17:09,879 Speaker 1: would be something they would jump at. So the idea 298 00:17:09,920 --> 00:17:12,280 Speaker 1: that the President took that off the table when it 299 00:17:12,320 --> 00:17:14,480 Speaker 1: seemed they were, you know, getting much closer in the 300 00:17:14,560 --> 00:17:17,800 Speaker 1: last few days was absolutely baffling from a sort of 301 00:17:17,840 --> 00:17:22,000 Speaker 1: electoral campaign political strategy perspective. And then to your point, 302 00:17:22,040 --> 00:17:24,760 Speaker 1: I had Tim running in my head saying, Okay, well 303 00:17:24,760 --> 00:17:27,920 Speaker 1: maybe there is no strategy here. So you know, it's 304 00:17:27,960 --> 00:17:30,120 Speaker 1: really really hard to tell what the president. The most 305 00:17:30,200 --> 00:17:32,600 Speaker 1: I can say is, on the one hand, he makes 306 00:17:32,640 --> 00:17:35,600 Speaker 1: a case about walking away from the table when you're negotiating, 307 00:17:35,600 --> 00:17:36,879 Speaker 1: you have to be prepared to do that, and that 308 00:17:36,920 --> 00:17:39,160 Speaker 1: seems to be what he did last night. And then 309 00:17:39,160 --> 00:17:41,240 Speaker 1: he walked back right up to the table a few 310 00:17:41,280 --> 00:17:44,240 Speaker 1: hours later. So you know, we're getting these again mixed 311 00:17:44,280 --> 00:17:46,879 Speaker 1: messages from the president, in which case he can always 312 00:17:46,960 --> 00:17:49,439 Speaker 1: declare victory, and that seems to be sort of par 313 00:17:49,640 --> 00:17:51,600 Speaker 1: for the course with him. If there is a deal, 314 00:17:51,640 --> 00:17:54,440 Speaker 1: he can declare victory. If there's not, he can say, see, 315 00:17:54,480 --> 00:17:56,679 Speaker 1: I told you so, and I walked away before you know, 316 00:17:56,760 --> 00:17:59,280 Speaker 1: this thing didn't work. Let's I'll forget that this is 317 00:17:59,280 --> 00:18:02,800 Speaker 1: a very very ill man right now as well. And 318 00:18:02,840 --> 00:18:06,240 Speaker 1: while you know, officially he had no symptoms yesterday, he's 319 00:18:06,320 --> 00:18:09,880 Speaker 1: on huge doses of you know, very strong chemicals and 320 00:18:10,320 --> 00:18:13,280 Speaker 1: you know apparently at some point that will start to 321 00:18:13,280 --> 00:18:14,720 Speaker 1: wear off in the next day or two, after the 322 00:18:14,800 --> 00:18:17,640 Speaker 1: fifth dose of de severe. How much do you think 323 00:18:17,680 --> 00:18:23,119 Speaker 1: that that is coloring his stands on things right now? Yeah, 324 00:18:23,160 --> 00:18:25,919 Speaker 1: I mean, this is the million dollar question. And I 325 00:18:25,960 --> 00:18:28,040 Speaker 1: don't think we know, as you just said that his 326 00:18:28,160 --> 00:18:30,880 Speaker 1: doctors are saying that he's showing no symptoms, and yet 327 00:18:30,880 --> 00:18:33,800 Speaker 1: we hear from doctor to you know, say that this 328 00:18:34,000 --> 00:18:37,159 Speaker 1: absolutely can cause you to have a reaction, and that 329 00:18:37,240 --> 00:18:39,720 Speaker 1: can be in you know, some kind of psychological way 330 00:18:39,720 --> 00:18:42,040 Speaker 1: as well. So I think the honest answer is that 331 00:18:42,160 --> 00:18:45,520 Speaker 1: none of us know that said um, even if the 332 00:18:45,560 --> 00:18:48,560 Speaker 1: President wasn't on these medicines, I'm not sure any of 333 00:18:48,600 --> 00:18:51,919 Speaker 1: us would be surprised by the tweeting and the decisions 334 00:18:51,960 --> 00:18:54,359 Speaker 1: made in the last twenty four hours visa VI or 335 00:18:54,400 --> 00:18:57,679 Speaker 1: the statements made not decisions visa be some kind of 336 00:18:57,680 --> 00:19:01,399 Speaker 1: stimulus package. I'm not sure what the answer to that is. 337 00:19:01,480 --> 00:19:04,000 Speaker 1: We hope that he is physically and mentally fine and 338 00:19:04,040 --> 00:19:07,000 Speaker 1: that we as the American public, are getting honest answers 339 00:19:07,119 --> 00:19:09,440 Speaker 1: from his doctors. And I don't think after this weekend 340 00:19:09,680 --> 00:19:12,679 Speaker 1: we can be confident about that. Jenny, we do have 341 00:19:12,720 --> 00:19:17,600 Speaker 1: a vice presidential debate this evening from Salt Lake City. Uh. 342 00:19:17,880 --> 00:19:20,520 Speaker 1: You know, typically we don't spend pay too much attention 343 00:19:20,560 --> 00:19:24,199 Speaker 1: to these VP debates, but given the ages of the 344 00:19:24,280 --> 00:19:27,640 Speaker 1: two president, the president and the vice president former Vice 345 00:19:27,640 --> 00:19:31,080 Speaker 1: President Biden, seems a little bit more relevant, doesn't it. 346 00:19:31,080 --> 00:19:34,919 Speaker 1: It absolutely does. I think in an ideal situation, you know, 347 00:19:35,160 --> 00:19:38,880 Speaker 1: the vice presidential nominees for two men in their seventies 348 00:19:38,960 --> 00:19:42,000 Speaker 1: would be a big deal, as you mentioned. And then 349 00:19:42,000 --> 00:19:45,080 Speaker 1: of course we're in a much different situation, not ideal, 350 00:19:45,119 --> 00:19:47,719 Speaker 1: in the midst of a pandemic, with a president who 351 00:19:47,800 --> 00:19:50,720 Speaker 1: we've just been talking about has been diagnosed is currently 352 00:19:50,960 --> 00:19:55,119 Speaker 1: under treatment, we understand, and a former vice president whose 353 00:19:55,320 --> 00:19:58,919 Speaker 1: health has been called into question at numerous times, you know, 354 00:19:58,960 --> 00:20:02,280 Speaker 1: throughout the campaign. So both of those things give this 355 00:20:02,359 --> 00:20:05,440 Speaker 1: sort of vice presidential debate, which normally gets a rather 356 00:20:05,560 --> 00:20:08,000 Speaker 1: small audience. I think it's going to get a lot 357 00:20:08,040 --> 00:20:10,680 Speaker 1: more attention tonight for that reason. And then, of course, 358 00:20:10,720 --> 00:20:13,160 Speaker 1: just a week ago we have the you know, sort 359 00:20:13,200 --> 00:20:15,639 Speaker 1: of stunning presidential debate where we didn't get a lot 360 00:20:15,680 --> 00:20:18,720 Speaker 1: of answers in terms of policies. So I think we're 361 00:20:18,760 --> 00:20:22,320 Speaker 1: really looking for president vice President Pence to sort of 362 00:20:22,359 --> 00:20:24,840 Speaker 1: play clean up for the president and to sort of 363 00:20:24,840 --> 00:20:27,119 Speaker 1: fill in some of those gaps that were left and 364 00:20:27,200 --> 00:20:30,119 Speaker 1: try to get a you know, a you know, some 365 00:20:30,280 --> 00:20:33,080 Speaker 1: scoring here for the Republicans in terms of doing a 366 00:20:33,080 --> 00:20:35,400 Speaker 1: better job. Because of course, polls show that the president 367 00:20:35,440 --> 00:20:38,719 Speaker 1: did not do well according to voters after that last debate. 368 00:20:39,560 --> 00:20:41,600 Speaker 1: So what does sont of they Kamala Harris have to 369 00:20:41,640 --> 00:20:45,040 Speaker 1: do to avoid making a mistake Denny, I think what 370 00:20:45,119 --> 00:20:47,359 Speaker 1: she's got to do is focus like a laser beam 371 00:20:47,440 --> 00:20:50,240 Speaker 1: on COVID. I think she's got to prosecute the case, 372 00:20:50,320 --> 00:20:52,479 Speaker 1: but do it in a, you know, not a terribly 373 00:20:52,520 --> 00:20:55,520 Speaker 1: stringent way, but bring more evidence forward, if you will, 374 00:20:55,960 --> 00:20:58,760 Speaker 1: that they have not done well. These are the the 375 00:20:58,800 --> 00:21:01,639 Speaker 1: American public in terms of managing this crisis, that is 376 00:21:01,680 --> 00:21:04,199 Speaker 1: the pandemic. I think if she can do that for 377 00:21:04,240 --> 00:21:07,720 Speaker 1: a sustained period of time, put Pence on the defensive 378 00:21:07,800 --> 00:21:11,000 Speaker 1: trying to defend you know, in many cases what the 379 00:21:11,040 --> 00:21:14,320 Speaker 1: administration has done here, she will have succeeded, provided, as 380 00:21:14,359 --> 00:21:17,600 Speaker 1: you mentioned, she doesn't make any mistakes, and it's gonna 381 00:21:17,680 --> 00:21:19,680 Speaker 1: be tough. She we haven't seen her in a lot 382 00:21:19,720 --> 00:21:22,199 Speaker 1: of one on one debates like this, so we're not 383 00:21:22,320 --> 00:21:25,359 Speaker 1: quite sure she's a great prosecutor. She was very good 384 00:21:25,400 --> 00:21:28,000 Speaker 1: in the multi person debate, but this is a different 385 00:21:28,040 --> 00:21:31,280 Speaker 1: format and Vice President Pence is good at this format, 386 00:21:31,280 --> 00:21:33,680 Speaker 1: and I think he doesn't get enough credit for being 387 00:21:33,720 --> 00:21:37,119 Speaker 1: successful in this venue. No, thank you so much for 388 00:21:37,280 --> 00:21:39,919 Speaker 1: joining us. Once again. We appreciate your thoughts here as 389 00:21:39,960 --> 00:21:43,880 Speaker 1: we get ready for the vice presidential debate. Jeniso, political 390 00:21:43,920 --> 00:21:47,760 Speaker 1: contributor for Bloomberg News also professor of political science at 391 00:21:47,800 --> 00:21:51,840 Speaker 1: iona at College. We always appreciate her thoughts here again, So, Vanni, 392 00:21:52,200 --> 00:21:53,720 Speaker 1: you know the markets are going to be you know, 393 00:21:53,720 --> 00:21:55,840 Speaker 1: they seem to be not obviously not focused on the 394 00:21:55,880 --> 00:21:59,720 Speaker 1: debate tonight, but certainly focused on uh Twitter and the 395 00:22:00,040 --> 00:22:01,520 Speaker 1: it's coming out of the White House as it relates 396 00:22:01,560 --> 00:22:04,879 Speaker 1: to fiscal stimus. Is it on again? Is it off again? Um? 397 00:22:04,920 --> 00:22:07,720 Speaker 1: I just don't know. And you know, at some point 398 00:22:07,960 --> 00:22:09,800 Speaker 1: the focus will turn to the debate. It it maybe 399 00:22:09,800 --> 00:22:12,040 Speaker 1: an hour before the debate, but at some point the president, 400 00:22:12,200 --> 00:22:15,040 Speaker 1: you know, won't be able to keep the limelight if 401 00:22:15,040 --> 00:22:17,080 Speaker 1: he does indeed take it today. Will you be watching tonight, 402 00:22:17,119 --> 00:22:19,440 Speaker 1: Paul I will? I will. I'm be flipping back between 403 00:22:19,480 --> 00:22:22,280 Speaker 1: the Yankee game and the debate, so we'll happen to see. 404 00:22:22,880 --> 00:22:25,080 Speaker 1: But there are other important things going on. Is that 405 00:22:25,119 --> 00:22:27,399 Speaker 1: what you're saying? Well, the Yankees, Yeah, they usually get 406 00:22:27,440 --> 00:22:29,199 Speaker 1: top billing for me, so we'll see. But this will 407 00:22:29,240 --> 00:22:32,520 Speaker 1: be important, so I think everybody will be paying attention 408 00:22:32,520 --> 00:22:38,520 Speaker 1: to it. Well, there's another hurricane bearing down on the 409 00:22:38,560 --> 00:22:42,920 Speaker 1: southern coast of America, and it is just another storm 410 00:22:42,960 --> 00:22:47,879 Speaker 1: in a extraordinary year of disasters. UH certainly copped capped 411 00:22:47,880 --> 00:22:51,240 Speaker 1: off by the COVID uh pandemic. Team Rubicon is a 412 00:22:51,280 --> 00:22:56,080 Speaker 1: nonprofit veteran lead disaster response organization. You have about hundred 413 00:22:56,160 --> 00:22:58,800 Speaker 1: seventy full time employees a hundred thirties thousand volunteers and 414 00:22:58,840 --> 00:23:02,960 Speaker 1: they have been busy this year in disaster relieve. Jake Would, 415 00:23:03,240 --> 00:23:07,160 Speaker 1: founder and CEO of Team Rubicant, joins us here. Jake 416 00:23:07,200 --> 00:23:09,160 Speaker 1: tell us a little bit about Team Rubican, kind of 417 00:23:09,320 --> 00:23:12,280 Speaker 1: where this came from and kind of where your focuses 418 00:23:12,800 --> 00:23:17,320 Speaker 1: uh in an epic. Yeah, well, thank you for having 419 00:23:17,359 --> 00:23:19,879 Speaker 1: me on to share the story. Team Rubicon were a 420 00:23:19,920 --> 00:23:23,680 Speaker 1: nonprofit organization that was founded about eleven years ago in 421 00:23:23,720 --> 00:23:26,879 Speaker 1: the aftermath of the Haiti earthquake. Um I had served 422 00:23:26,880 --> 00:23:29,840 Speaker 1: in the Marine Corps served in Iraq and Afghanistan. Following 423 00:23:29,840 --> 00:23:32,800 Speaker 1: the earthquake, I led a team of veterans and doctors 424 00:23:32,840 --> 00:23:35,560 Speaker 1: down the Court of Prince to help with the response 425 00:23:35,560 --> 00:23:38,000 Speaker 1: effort down there, and we realized that these men and 426 00:23:38,040 --> 00:23:40,720 Speaker 1: women who have served in uniform overseas had a lot 427 00:23:40,720 --> 00:23:43,480 Speaker 1: of skills and experiences that were applicable in disaster zones. 428 00:23:44,200 --> 00:23:47,000 Speaker 1: So in the decades since, we've built up uh, you know, 429 00:23:47,080 --> 00:23:51,080 Speaker 1: a really incredible organization that leverages military veterans and first 430 00:23:51,160 --> 00:23:55,000 Speaker 1: responders to go into disaster zones and humanitarian crises, you know, 431 00:23:55,040 --> 00:23:57,280 Speaker 1: like we've been seeing throughout I mean, you mentioned the 432 00:23:57,359 --> 00:24:00,919 Speaker 1: hurricane season. We've got Hurricane Delta, which is an upgrade 433 00:24:01,040 --> 00:24:03,920 Speaker 1: to a Category force and a slam in the southeast Louisiana. 434 00:24:04,280 --> 00:24:06,879 Speaker 1: You know, this is one of many major hurricanes that 435 00:24:06,880 --> 00:24:09,399 Speaker 1: have hit the US already this year. And all of 436 00:24:09,440 --> 00:24:12,280 Speaker 1: this in the midst of of COVID nineteen. I mean, 437 00:24:12,320 --> 00:24:16,040 Speaker 1: it's it's been a year fraught with disasters and prices, 438 00:24:16,080 --> 00:24:18,280 Speaker 1: and and Team Rubican has been their serving communities along 439 00:24:18,320 --> 00:24:22,639 Speaker 1: the way. So, Jake, how has COVID nineteen changed the 440 00:24:22,760 --> 00:24:25,359 Speaker 1: environment for you all? I imagine you may have gotten 441 00:24:25,680 --> 00:24:28,560 Speaker 1: you know, extra volunteers in some ways if people were 442 00:24:28,600 --> 00:24:30,960 Speaker 1: at home doing nothing and felt like they wanted to 443 00:24:30,680 --> 00:24:32,600 Speaker 1: to get out there and do something, if they didn't 444 00:24:32,680 --> 00:24:36,679 Speaker 1: at all, or what have you. But also keeping everybody safe. Yeah, well, 445 00:24:36,720 --> 00:24:39,720 Speaker 1: we made a commitment early into OVID nineteen. We made 446 00:24:39,760 --> 00:24:42,000 Speaker 1: two commitments. One we were going to step into that 447 00:24:42,080 --> 00:24:45,520 Speaker 1: crisis aggressively, and we were gonna assist communities to get 448 00:24:45,520 --> 00:24:47,640 Speaker 1: through the pandemic, and we've been doing that. We've been 449 00:24:47,640 --> 00:24:52,040 Speaker 1: doing that by sending medical providers to Navajo Nation, We've 450 00:24:52,080 --> 00:24:56,760 Speaker 1: been sending up mobile testing sites, We've been distributing PPE 451 00:24:57,080 --> 00:25:00,200 Speaker 1: for the entire city of Chicago, and we flood did 452 00:25:00,200 --> 00:25:04,000 Speaker 1: food banks across the country with thousands of volunteers to 453 00:25:04,080 --> 00:25:07,119 Speaker 1: support their efforts. But we also did it through the 454 00:25:07,200 --> 00:25:09,920 Speaker 1: lens that we were always going to keep our volunteer safe, 455 00:25:10,000 --> 00:25:13,720 Speaker 1: and so we very quickly developed the necessary protocols, ensured 456 00:25:13,760 --> 00:25:17,159 Speaker 1: that we had the necessary PPE to keep our volunteers safe. 457 00:25:17,600 --> 00:25:19,760 Speaker 1: And the one thing that we realized early was that 458 00:25:19,800 --> 00:25:23,280 Speaker 1: Mother Nature didn't care about COVID nineteen and we never 459 00:25:23,320 --> 00:25:26,080 Speaker 1: predicted that we'd have a storm season quite like we've had, 460 00:25:26,520 --> 00:25:27,760 Speaker 1: But we knew that we were going to have to 461 00:25:27,760 --> 00:25:30,639 Speaker 1: continue to respond to natural disasters in the midst of this. 462 00:25:31,280 --> 00:25:33,720 Speaker 1: So that has required us to rework all of our 463 00:25:33,760 --> 00:25:37,880 Speaker 1: disaster response protocols, ranging from how we fly in volunteers, 464 00:25:37,960 --> 00:25:42,200 Speaker 1: how they transport in vehicles, how they sleep at night, um, 465 00:25:42,240 --> 00:25:44,399 Speaker 1: the types of equipment that they have to take h 466 00:25:44,600 --> 00:25:47,040 Speaker 1: into these homes that they're helping to recover from the storms. 467 00:25:47,720 --> 00:25:51,760 Speaker 1: And so, yes, we have seen an influx of new volunteers, 468 00:25:51,800 --> 00:25:54,960 Speaker 1: but we've also seen a dramatic decrease in funding. Um, 469 00:25:55,000 --> 00:25:57,720 Speaker 1: you know this issue, you know, the economy, the broader 470 00:25:57,840 --> 00:26:01,120 Speaker 1: macro economic trends that we're seeing are are creating real 471 00:26:01,160 --> 00:26:04,119 Speaker 1: headwinds for the organization. You know that I think is 472 00:26:04,160 --> 00:26:06,560 Speaker 1: coupled with kind of the uncertainty of the election and 473 00:26:06,600 --> 00:26:09,680 Speaker 1: all of the money that's being diverted into both sides 474 00:26:10,440 --> 00:26:13,600 Speaker 1: of the Democrats and Republicans. And then finally the rise 475 00:26:13,680 --> 00:26:17,919 Speaker 1: of social justice as an issue that's pre eminent many Americans. Uh, 476 00:26:18,040 --> 00:26:22,120 Speaker 1: the unfortunate reality is that public support for these disasters 477 00:26:22,160 --> 00:26:25,679 Speaker 1: has waned. So Jack, let's let's go there a little bit. 478 00:26:25,720 --> 00:26:27,600 Speaker 1: I mean, I would I would think your resources are 479 00:26:27,800 --> 00:26:31,240 Speaker 1: beyond stretched in a year like with COVID and this 480 00:26:31,560 --> 00:26:35,840 Speaker 1: extraordinary storm season that's impacted the United States. Kind of 481 00:26:36,000 --> 00:26:40,520 Speaker 1: how are you funding your operations? Well, you know, our 482 00:26:40,560 --> 00:26:44,480 Speaker 1: funding is all uh private philanthropy. So it's it's corporate funding, 483 00:26:44,480 --> 00:26:47,160 Speaker 1: it's foundations and as individual giving. We don't take any 484 00:26:47,160 --> 00:26:50,080 Speaker 1: government money and we don't charge the homeowners that we 485 00:26:50,119 --> 00:26:52,800 Speaker 1: assist for the services that we provide, and so we 486 00:26:52,880 --> 00:26:57,399 Speaker 1: really rely on these these institutions and these individuals to 487 00:26:57,400 --> 00:26:59,399 Speaker 1: the fund our efforts. And as I said, you know, 488 00:26:59,680 --> 00:27:04,280 Speaker 1: people pocketbooks are are stretched. We have extraordinarily high unemployment 489 00:27:04,760 --> 00:27:09,840 Speaker 1: many sectors of the economy, the core of corporations. Uh 490 00:27:09,880 --> 00:27:12,080 Speaker 1: you know, despite where the you know, the Doubt and 491 00:27:12,119 --> 00:27:14,639 Speaker 1: the Nashtac are sitting. You know, many of these companies 492 00:27:14,640 --> 00:27:17,440 Speaker 1: stock prices are still pummeled. That's that's been an impact 493 00:27:17,480 --> 00:27:19,960 Speaker 1: to our bottom line because they have fewer dollars available 494 00:27:19,960 --> 00:27:22,840 Speaker 1: for philanthropy. And so yes, we you know, we're having 495 00:27:22,840 --> 00:27:25,280 Speaker 1: to kind of clench our jaw here and find creative 496 00:27:25,320 --> 00:27:28,400 Speaker 1: ways to to flex into these operations and not leave 497 00:27:28,440 --> 00:27:32,680 Speaker 1: these communities behind. And it's it's challenging. Tell us how 498 00:27:33,240 --> 00:27:38,080 Speaker 1: very clearly j people can donate. Well, if anybody wants 499 00:27:38,080 --> 00:27:39,800 Speaker 1: to support our work, they can go to Team root 500 00:27:39,840 --> 00:27:43,359 Speaker 1: becon USA dot org. You know, five dollars, five dollars, 501 00:27:43,359 --> 00:27:46,600 Speaker 1: anything in between, anything above, uh, you know, will will 502 00:27:46,680 --> 00:27:49,159 Speaker 1: maximize the impact that that that money can have in 503 00:27:49,160 --> 00:27:51,680 Speaker 1: the community. Uh. You know, if you want to volunteer, 504 00:27:52,080 --> 00:27:54,520 Speaker 1: that's your most precious resource, your time. We'd love to 505 00:27:54,520 --> 00:27:57,159 Speaker 1: have you and even just sharing the word of what 506 00:27:57,200 --> 00:27:59,840 Speaker 1: you're hearing and the work that we're doing can go along. 507 00:28:00,080 --> 00:28:02,440 Speaker 1: So we'd encourage people to follow us on social media 508 00:28:02,440 --> 00:28:05,040 Speaker 1: and share the story of Team Rubicon. Team Rubicon dot 509 00:28:05,119 --> 00:28:08,160 Speaker 1: org and Jake, if people did want to volunteer, what 510 00:28:08,320 --> 00:28:14,120 Speaker 1: are your criteria? It's Team Rubicon USA dot org and 511 00:28:14,320 --> 00:28:16,520 Speaker 1: anybody is eligible to volunteer as long as they're over 512 00:28:16,520 --> 00:28:19,240 Speaker 1: the age of eighteen. Um. We you don't have to 513 00:28:19,280 --> 00:28:22,320 Speaker 1: be a military veteran. It certainly makes up the bulk 514 00:28:22,359 --> 00:28:24,640 Speaker 1: of our volunteers, but we take people of all stripes. 515 00:28:25,280 --> 00:28:27,919 Speaker 1: Uh and uh. You know, we're just looking for you know, 516 00:28:27,960 --> 00:28:30,360 Speaker 1: great American citizens who are looking to help their neighbors. 517 00:28:31,280 --> 00:28:34,119 Speaker 1: Team Rubicon USA dot org. I'll say that one more time, 518 00:28:34,160 --> 00:28:37,439 Speaker 1: Team Rubicon USA dot org. Jake, thanks for sharing your 519 00:28:37,480 --> 00:28:40,080 Speaker 1: story with us today and we will definitely continue to 520 00:28:40,160 --> 00:28:44,440 Speaker 1: follow your movements throughout the country and stay safe. And 521 00:28:44,800 --> 00:28:47,320 Speaker 1: I know that if anybody can, you guys can much 522 00:28:47,400 --> 00:28:51,320 Speaker 1: much appreciated. That is Jake would, founder and CEO of 523 00:28:51,400 --> 00:28:56,240 Speaker 1: Team Rubicon. Thanks for listening to the Boomberg Markets podcast. 524 00:28:56,400 --> 00:28:59,760 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts 525 00:28:59,880 --> 00:29:03,440 Speaker 1: or whatever podcast platform you prefer. I'm Bonnie Quinn. I'm 526 00:29:03,480 --> 00:29:06,080 Speaker 1: on Twitter at Bonnie Quinn and I'm Paul Sweeney. I'm 527 00:29:06,120 --> 00:29:08,760 Speaker 1: on Twitter at pt Sweeney. Before the podcast, you can 528 00:29:08,800 --> 00:29:11,040 Speaker 1: always catch us worldwide at Bloomberg Radio