1 00:00:12,240 --> 00:00:15,000 Speaker 1: This is Wall Street Week. I'm David Weston bringing you 2 00:00:15,080 --> 00:00:18,680 Speaker 1: stories of capitalism. President Mela scored a big victory in 3 00:00:18,760 --> 00:00:21,759 Speaker 1: Argentine elections on Sunday. What does that mean for his 4 00:00:21,920 --> 00:00:26,920 Speaker 1: economy and for the US? Given its support and President 5 00:00:26,920 --> 00:00:29,800 Speaker 1: Trump's charging one hundred thousand dollars for an H one 6 00:00:29,880 --> 00:00:32,680 Speaker 1: B visa may put some money into the US treasury, 7 00:00:33,040 --> 00:00:35,120 Speaker 1: but what does it mean for innovation in a tech 8 00:00:35,120 --> 00:00:39,920 Speaker 1: industry that depends on highly skilled minds from abroad. Plus 9 00:00:40,040 --> 00:00:43,000 Speaker 1: many of those highly skilled minds are focused on developing 10 00:00:43,080 --> 00:00:46,920 Speaker 1: artificial intelligence models. We sit down with Nobel Laureate Jeffrey 11 00:00:47,000 --> 00:00:50,240 Speaker 1: Hinton for an update on his story about where AI 12 00:00:50,400 --> 00:00:53,040 Speaker 1: is taking us and whether he's as worried about the 13 00:00:53,080 --> 00:00:57,320 Speaker 1: possibilities as he told us a year ago. But we 14 00:00:57,480 --> 00:00:59,840 Speaker 1: start with the big story for the markets this week, 15 00:01:00,200 --> 00:01:03,840 Speaker 1: the Federal Reserve's latest rate decision. Our special contributor to 16 00:01:03,880 --> 00:01:07,919 Speaker 1: Larry Summers of Harvard is here with his take. Larry, 17 00:01:08,000 --> 00:01:11,280 Speaker 1: we heard from the Federal Reserve this week and they 18 00:01:11,319 --> 00:01:15,120 Speaker 1: cut again, second time in a row. Were you surprised 19 00:01:15,160 --> 00:01:18,319 Speaker 1: at how far Chair Powell went and saying don't expect it? 20 00:01:18,520 --> 00:01:20,399 Speaker 1: In December, I. 21 00:01:20,360 --> 00:01:23,800 Speaker 2: Was slightly surprised, but much more importantly, I was glad 22 00:01:24,600 --> 00:01:28,200 Speaker 2: this was the right thing to do. Inflation is much 23 00:01:28,240 --> 00:01:32,920 Speaker 2: further from its reasonable target than unemployment is. The FED 24 00:01:33,000 --> 00:01:35,920 Speaker 2: can have much more of a durable impact on inflation 25 00:01:36,480 --> 00:01:43,440 Speaker 2: than it can on unemployment. Given deficits, given AI spending, 26 00:01:43,959 --> 00:01:47,800 Speaker 2: we're probably at or below the neutral rate of interest. 27 00:01:48,440 --> 00:01:52,680 Speaker 2: There was no reason to be committed into further rate 28 00:01:52,760 --> 00:01:58,680 Speaker 2: cutting in this environment. So share Powell's signaled or return 29 00:01:58,800 --> 00:02:02,920 Speaker 2: to data depend to agnosticism about what was going to 30 00:02:02,920 --> 00:02:07,279 Speaker 2: happen next. That was exactly the right thing to do. Yes, 31 00:02:07,360 --> 00:02:10,440 Speaker 2: there are risks of a slowdown, but if we get 32 00:02:10,440 --> 00:02:13,120 Speaker 2: a slowdown and the FED does a fifty basis point 33 00:02:13,240 --> 00:02:17,160 Speaker 2: cut six weeks later, that is not going to be important. 34 00:02:17,639 --> 00:02:21,640 Speaker 2: But if the FED loses its credibility around inflation at 35 00:02:21,680 --> 00:02:27,760 Speaker 2: a moment of massive deficits, massive political pressure from the administration, 36 00:02:28,240 --> 00:02:36,240 Speaker 2: substantial international uncertainties, evidence of higher inflation expectations, and it's 37 00:02:36,280 --> 00:02:39,080 Speaker 2: been a long time since inflation was near two percent, 38 00:02:39,840 --> 00:02:42,799 Speaker 2: in the face of all of that, this was really 39 00:02:42,840 --> 00:02:43,919 Speaker 2: the right thing to do. 40 00:02:44,680 --> 00:02:46,720 Speaker 1: The FED maybe data dependent, but it doesn't get the 41 00:02:46,800 --> 00:02:48,800 Speaker 1: data that it once did out of the federal government. 42 00:02:49,120 --> 00:02:51,240 Speaker 1: How much of a disadvantage is that for the FED 43 00:02:51,360 --> 00:02:53,440 Speaker 1: right now in figuring out where we are, particularly when 44 00:02:53,440 --> 00:02:54,600 Speaker 1: it comes to inflation. 45 00:02:55,320 --> 00:02:59,640 Speaker 2: It's a disadvantage. But there are now so many indicators, 46 00:03:00,160 --> 00:03:03,920 Speaker 2: so many real time data sets, things like the million 47 00:03:03,960 --> 00:03:09,840 Speaker 2: price projects at MIT, all sorts of sensitive indicators that 48 00:03:09,880 --> 00:03:14,359 Speaker 2: are being followed by people in the markets on an 49 00:03:14,400 --> 00:03:19,960 Speaker 2: almost weekly basis. That this is unfortunate and it's not 50 00:03:20,080 --> 00:03:23,200 Speaker 2: what a serious government country does to have such a 51 00:03:23,280 --> 00:03:28,200 Speaker 2: long slowdown. But I don't think it's an immense problem 52 00:03:28,600 --> 00:03:31,440 Speaker 2: in the grand scheme of things. It's certainly a much 53 00:03:31,480 --> 00:03:36,400 Speaker 2: smaller problem than politicization. It's a much smaller problem than 54 00:03:36,800 --> 00:03:43,160 Speaker 2: dealing with budget deficits. This is not the major challenge 55 00:03:43,200 --> 00:03:46,320 Speaker 2: facing the feed AT Chairpoel in the news conference talked 56 00:03:46,480 --> 00:03:47,520 Speaker 2: certainly about inflation. 57 00:03:47,880 --> 00:03:50,200 Speaker 1: He also talked about the role of tariffs, and at 58 00:03:50,200 --> 00:03:52,280 Speaker 1: one point he said, look at if you take tariffs, 59 00:03:52,280 --> 00:03:54,760 Speaker 1: the effect of tariffs out of the numbers, we're actually 60 00:03:54,800 --> 00:03:57,119 Speaker 1: not that far away from our two percent goal. If 61 00:03:57,120 --> 00:03:59,720 Speaker 1: that's right, Which way does that cut? What do we 62 00:03:59,800 --> 00:04:02,320 Speaker 1: do with tariffs incorporating that into monetary policy? 63 00:04:03,640 --> 00:04:09,600 Speaker 2: Well, we're not that far away from two percent after 64 00:04:10,040 --> 00:04:14,280 Speaker 2: five years of being above two percent, isn't that great 65 00:04:14,280 --> 00:04:18,800 Speaker 2: a place to be? Even if you accept that that's true, 66 00:04:19,000 --> 00:04:23,440 Speaker 2: you can always take some things out of the numbers 67 00:04:24,120 --> 00:04:28,960 Speaker 2: and then say we're near normal. That kind of argument 68 00:04:29,920 --> 00:04:34,520 Speaker 2: reminds me of what was share Powell's darkest moment and 69 00:04:34,600 --> 00:04:37,120 Speaker 2: what was what I think has been a really very 70 00:04:37,160 --> 00:04:42,279 Speaker 2: distinguished term of service, which was the transitory inflation idea 71 00:04:42,920 --> 00:04:46,880 Speaker 2: in twenty twenty one. Yes, maybe it's true that if 72 00:04:46,880 --> 00:04:50,600 Speaker 2: you take out tariffs then numbers will look good. But 73 00:04:50,960 --> 00:04:54,719 Speaker 2: because people are spending more money on tariff goods, they're 74 00:04:54,760 --> 00:04:58,320 Speaker 2: spending less money on other goods whose price is lower, 75 00:04:58,720 --> 00:05:02,400 Speaker 2: and that should be taken out as well. So I 76 00:05:02,400 --> 00:05:06,760 Speaker 2: don't think cherry picking the components that have risen is 77 00:05:06,800 --> 00:05:11,440 Speaker 2: a particularly good way of doing the analysis. I also 78 00:05:11,560 --> 00:05:15,560 Speaker 2: think it's not clear what's going to feed through into 79 00:05:15,880 --> 00:05:19,000 Speaker 2: people's expectations of inflation. 80 00:05:19,920 --> 00:05:23,200 Speaker 1: One thing that was different about this FED decision were 81 00:05:23,240 --> 00:05:25,240 Speaker 1: the descents. I mean, we went for a long time 82 00:05:25,279 --> 00:05:28,479 Speaker 1: with no dissents. Last meeting we had some saying we 83 00:05:28,520 --> 00:05:31,160 Speaker 1: should cut more. This time we had them both ways, 84 00:05:31,440 --> 00:05:33,919 Speaker 1: don't cut it all and cut more. Is there a 85 00:05:33,960 --> 00:05:36,160 Speaker 1: breakdown in the consensus on the FED, or is it 86 00:05:36,200 --> 00:05:37,839 Speaker 1: just a more confusing picture we're saying. 87 00:05:38,760 --> 00:05:42,600 Speaker 2: I think it reflects two things. It reflects the confusion 88 00:05:42,720 --> 00:05:48,680 Speaker 2: of the picture. And I think that the descent from 89 00:05:48,760 --> 00:05:53,640 Speaker 2: Kansas City in favor of raising rates reflects were or 90 00:05:53,720 --> 00:05:58,279 Speaker 2: not cutting rates reflects what is the genuine argument among 91 00:05:58,400 --> 00:06:04,000 Speaker 2: serious economists in this moment. The dissent from Governor Mirron 92 00:06:04,760 --> 00:06:11,120 Speaker 2: reflects the bizarre spectacle of a government official, part of 93 00:06:11,160 --> 00:06:14,640 Speaker 2: an administration that's at war with the FED in its 94 00:06:14,720 --> 00:06:19,000 Speaker 2: rhetoric putting something on the putting somebody on the FED 95 00:06:20,320 --> 00:06:24,719 Speaker 2: on a temporary basis while they're on their leave from 96 00:06:25,040 --> 00:06:31,360 Speaker 2: their other Senate confirmed job. I think that that's not 97 00:06:31,440 --> 00:06:38,480 Speaker 2: to be taken seriously as anything but a politically aberrant moment. 98 00:06:39,120 --> 00:06:41,120 Speaker 1: The FED also said that as of December one, they'd 99 00:06:41,160 --> 00:06:44,200 Speaker 1: stopped the roll off of the balance sheet. Is that 100 00:06:44,279 --> 00:06:47,400 Speaker 1: reflecting a real concern about liquidity? Did you expect them 101 00:06:47,560 --> 00:06:49,279 Speaker 1: to keep the balance sheet this large? 102 00:06:50,320 --> 00:06:57,679 Speaker 2: They signaled that this kind of thing was going to happen. 103 00:06:58,520 --> 00:07:03,240 Speaker 2: I don't think, for twoarticularly that the precise size of 104 00:07:03,279 --> 00:07:06,800 Speaker 2: the FED balance sheet in an era where we're paying 105 00:07:06,880 --> 00:07:13,080 Speaker 2: interest on reserves is really that important a variable. In 106 00:07:13,120 --> 00:07:16,960 Speaker 2: an earlier era, when the other side of the balance 107 00:07:16,960 --> 00:07:21,440 Speaker 2: sheet was money that paid zero interest, the era of monitorism, 108 00:07:21,880 --> 00:07:24,840 Speaker 2: you could get very excited but by the size of 109 00:07:24,920 --> 00:07:29,000 Speaker 2: the FED balance sheet. But I don't find it that 110 00:07:29,360 --> 00:07:34,840 Speaker 2: exciting a variable to worry about its precise size. I 111 00:07:34,880 --> 00:07:37,520 Speaker 2: do think it's important for the country as a whole 112 00:07:38,080 --> 00:07:42,280 Speaker 2: to be turning out its debt more than we have, 113 00:07:43,160 --> 00:07:47,840 Speaker 2: and from that point of view, the FED reducing the 114 00:07:47,880 --> 00:07:50,320 Speaker 2: size of its balance sheet is probably a good thing 115 00:07:51,000 --> 00:07:55,000 Speaker 2: because it means a little less short term obligation of 116 00:07:55,040 --> 00:07:59,840 Speaker 2: the federal government and a little more long term. 117 00:07:59,680 --> 00:08:03,160 Speaker 1: Oblim Shortly after we had the FED meeting, we also 118 00:08:03,280 --> 00:08:07,200 Speaker 1: had President Trump meet with President Jushen Ping of China 119 00:08:07,360 --> 00:08:09,600 Speaker 1: over in South Korea, and there were a lot of 120 00:08:09,640 --> 00:08:11,720 Speaker 1: things announced. President Trump said had done a scale of 121 00:08:11,720 --> 00:08:14,239 Speaker 1: one to ten. Was the twelve. But there was seemed 122 00:08:14,240 --> 00:08:15,840 Speaker 1: to be a consensus that what we've done is basically 123 00:08:16,000 --> 00:08:17,880 Speaker 1: just go back to where we were before, and this 124 00:08:17,960 --> 00:08:21,000 Speaker 1: is gonna be an ongoing period of negotiation. How significant 125 00:08:21,160 --> 00:08:24,120 Speaker 1: in terms of the economy is what happened over in 126 00:08:24,160 --> 00:08:24,800 Speaker 1: South Korea. 127 00:08:25,520 --> 00:08:29,400 Speaker 2: Look, I think the most important thing is what didn't happen. 128 00:08:30,040 --> 00:08:36,400 Speaker 2: This situation didn't spiral out of control into massive confrontation 129 00:08:37,040 --> 00:08:40,440 Speaker 2: and economic conflict, and it was managed in a way 130 00:08:40,480 --> 00:08:46,920 Speaker 2: that avoided what potentially could have been very unfortunate and 131 00:08:46,960 --> 00:08:51,040 Speaker 2: destabilizing outcomes. And that's the good news, and I think 132 00:08:51,080 --> 00:08:57,040 Speaker 2: it genuinely is good news. I am glad for farmers 133 00:08:57,080 --> 00:09:01,160 Speaker 2: that they are going to sell more soybeans in China. 134 00:09:01,760 --> 00:09:05,760 Speaker 2: But ultimately, when one judges the prosperity of the United 135 00:09:05,760 --> 00:09:09,600 Speaker 2: States in this period, or the wisdom of economic policy 136 00:09:09,679 --> 00:09:12,320 Speaker 2: in this period, it is not going to be about 137 00:09:12,320 --> 00:09:18,560 Speaker 2: the level of soybean sales to China. So we're going 138 00:09:18,640 --> 00:09:22,880 Speaker 2: to have to see what happens. The really big issues 139 00:09:23,559 --> 00:09:31,600 Speaker 2: involve technology, involve competition in artificial intelligence, and it doesn't 140 00:09:31,640 --> 00:09:34,720 Speaker 2: look to me like on the read we have so 141 00:09:34,920 --> 00:09:39,800 Speaker 2: far that those have evolved a lot. But give credit 142 00:09:39,840 --> 00:09:43,600 Speaker 2: where credit is due. I think there's a good chance 143 00:09:43,720 --> 00:09:49,080 Speaker 2: that we elicited some real cooperation on fentanyl, which is 144 00:09:49,080 --> 00:09:51,440 Speaker 2: not so much an economic issue, but it is a 145 00:09:51,559 --> 00:09:58,040 Speaker 2: hugely profound social issue, And give credit where credit is due. 146 00:09:58,240 --> 00:10:04,079 Speaker 2: We're managing the situation towards the avoidance of what could 147 00:10:04,120 --> 00:10:11,280 Speaker 2: otherwise be very substantial turbulence. But this is a book 148 00:10:11,360 --> 00:10:15,400 Speaker 2: that's got many chapters, and we are still in the 149 00:10:15,679 --> 00:10:16,679 Speaker 2: early chapters. 150 00:10:17,320 --> 00:10:20,200 Speaker 1: Let me talk about that technology issue that you mentioned, 151 00:10:20,200 --> 00:10:22,079 Speaker 1: and particularly when it comes to AI, one of the 152 00:10:22,120 --> 00:10:24,679 Speaker 1: things that apparently was not discussed with some of the 153 00:10:24,720 --> 00:10:28,000 Speaker 1: advanced microchips from Nvidia. I mean, you are both a 154 00:10:28,000 --> 00:10:30,079 Speaker 1: macroeconomist and also sat on the board of Opening Eye, 155 00:10:30,120 --> 00:10:32,240 Speaker 1: so you have a vantage point on this. How do 156 00:10:32,320 --> 00:10:35,960 Speaker 1: you see the issue about export controls in respective advanced 157 00:10:36,200 --> 00:10:38,520 Speaker 1: microchips between the United States and China. On the one hand, 158 00:10:38,559 --> 00:10:40,560 Speaker 1: there are national defense issues. On the other hand, we 159 00:10:40,640 --> 00:10:42,520 Speaker 1: do want to have sort of a development of this 160 00:10:42,559 --> 00:10:43,360 Speaker 1: new technology. 161 00:10:44,480 --> 00:10:48,280 Speaker 2: It's a very difficult set of issues, and I don't 162 00:10:48,360 --> 00:10:53,320 Speaker 2: know what the right answers are. I'm pretty sure that 163 00:10:53,480 --> 00:10:56,880 Speaker 2: the right thing to do is to make judgments based 164 00:10:56,920 --> 00:11:02,560 Speaker 2: on what will protect and national security now and in 165 00:11:02,600 --> 00:11:06,280 Speaker 2: the future. And so the approach that President Trump took 166 00:11:06,400 --> 00:11:09,640 Speaker 2: a couple months ago of saying he would relax the 167 00:11:10,559 --> 00:11:15,560 Speaker 2: export controls but only if the company involved would share 168 00:11:15,679 --> 00:11:18,839 Speaker 2: some of the revenue with the federal government did not 169 00:11:19,120 --> 00:11:24,440 Speaker 2: strike me as consistent with our traditions. It struck me 170 00:11:24,520 --> 00:11:29,720 Speaker 2: as more pointing towards a kind of deals capitalism that 171 00:11:30,360 --> 00:11:36,400 Speaker 2: is more characteristic frankly, of lesser nations than ours, rather 172 00:11:36,520 --> 00:11:42,840 Speaker 2: than a more rules based capitalism. 173 00:11:42,880 --> 00:11:46,400 Speaker 1: Coming up a victory for President Mille of Argentina and 174 00:11:46,480 --> 00:11:49,640 Speaker 1: for President Trump in the United States, what lies ahead 175 00:11:49,800 --> 00:12:03,360 Speaker 1: for both. President Melea's historic victory on Sunday in Argentine 176 00:12:03,360 --> 00:12:06,640 Speaker 1: elections means he has a stronger position in his Congress 177 00:12:07,040 --> 00:12:11,280 Speaker 1: and another opportunity to administer his medicine seeking economic health 178 00:12:11,520 --> 00:12:14,079 Speaker 1: for a country that has been struggling for a long time. 179 00:12:14,520 --> 00:12:17,920 Speaker 1: Hans Hume's CEO of Greylac Capital, is a long time 180 00:12:18,040 --> 00:12:19,640 Speaker 1: investor in Argentina. 181 00:12:21,440 --> 00:12:25,120 Speaker 3: I think the entire country understands what has held them 182 00:12:25,160 --> 00:12:30,520 Speaker 3: back for decades now, and they're willing to take a 183 00:12:30,520 --> 00:12:31,959 Speaker 3: certain amount of personal pain. 184 00:12:33,080 --> 00:12:33,240 Speaker 2: Now. 185 00:12:33,280 --> 00:12:36,080 Speaker 3: We have to see how this transition goes and what 186 00:12:36,160 --> 00:12:40,200 Speaker 3: the new messaging will come if Paranism is able to 187 00:12:40,200 --> 00:12:41,320 Speaker 3: prevail in October. 188 00:12:43,120 --> 00:12:46,600 Speaker 1: But in the end, Paranism the populist legacy of Juan 189 00:12:46,640 --> 00:12:53,360 Speaker 1: Peron did not prevail, at least not last Sundays argentinoo. 190 00:12:54,920 --> 00:12:55,400 Speaker 4: Comes. 191 00:12:55,760 --> 00:12:57,720 Speaker 1: I think right now we've made a lot of money 192 00:12:57,720 --> 00:13:00,000 Speaker 1: based on that election, because the bonds have gone out 193 00:13:00,600 --> 00:13:02,280 Speaker 1: the all debt rating has gone up. 194 00:13:02,320 --> 00:13:05,319 Speaker 5: You know that election made a lot of money for 195 00:13:05,400 --> 00:13:06,280 Speaker 5: the United States. 196 00:13:06,679 --> 00:13:09,440 Speaker 1: What does Melae's latest victory mean for the country and 197 00:13:09,520 --> 00:13:13,040 Speaker 1: for investors like Humes. This is how Humes saw the 198 00:13:13,120 --> 00:13:17,040 Speaker 1: issues brought on by Melai's reforms before the midterm elections. 199 00:13:17,480 --> 00:13:22,600 Speaker 3: In general, at the beginning of a pro market president, 200 00:13:23,040 --> 00:13:28,040 Speaker 3: you're going to have a lot of enthusiasm. Unfortunately, you know, 201 00:13:28,120 --> 00:13:31,400 Speaker 3: depending on how this one goes, people might start sensing 202 00:13:31,400 --> 00:13:36,760 Speaker 3: a pattern that's after the burst of enthusiasm and the 203 00:13:36,840 --> 00:13:40,640 Speaker 3: rally in markets, that something happens where they run into 204 00:13:41,040 --> 00:13:44,680 Speaker 3: some social resistance or whatever. The feedback I got from 205 00:13:44,760 --> 00:13:47,760 Speaker 3: sort of my lower middle class friends who are Argentine 206 00:13:48,120 --> 00:13:53,000 Speaker 3: was many of their friends who are really enthusiastic for 207 00:13:53,160 --> 00:13:57,200 Speaker 3: change started looking at this and saying, oh, this is 208 00:13:57,240 --> 00:13:59,800 Speaker 3: the same thing we normally have to do. Either give 209 00:13:59,880 --> 00:14:02,240 Speaker 3: up or they start turning away from a lay and 210 00:14:02,280 --> 00:14:04,800 Speaker 3: they put up with a lot of pain runaway. 211 00:14:04,800 --> 00:14:08,479 Speaker 1: Inflation has been a burden for businesses as well, businesses 212 00:14:08,600 --> 00:14:12,520 Speaker 1: like the textile manufacturer that David Kim runs in Buenos Aires. 213 00:14:12,920 --> 00:14:17,560 Speaker 6: Inflation is a game we really know how to deal 214 00:14:17,600 --> 00:14:24,840 Speaker 6: with because inflation in Argentina started in I think nineteen 215 00:14:26,000 --> 00:14:31,280 Speaker 6: seventy or something like that, and we've had inflation, double 216 00:14:31,560 --> 00:14:37,720 Speaker 6: digit inflation for many years. It is very difficult because 217 00:14:38,040 --> 00:14:43,600 Speaker 6: you need to calculate the costs every month, and sometimes 218 00:14:43,640 --> 00:14:48,400 Speaker 6: you have to when inflation is very, very high, you 219 00:14:48,520 --> 00:14:54,160 Speaker 6: have to increase the prices maybe once or there has 220 00:14:54,240 --> 00:14:58,480 Speaker 6: been some times when they have to make increases more 221 00:14:58,520 --> 00:15:01,520 Speaker 6: than one time a month. Everyone that comes to Argentina 222 00:15:01,600 --> 00:15:05,720 Speaker 6: and we explain all these crises and what happens politically 223 00:15:05,760 --> 00:15:10,280 Speaker 6: and economically on the taxis and the new regulations, they say, 224 00:15:10,320 --> 00:15:12,960 Speaker 6: we are crazy to stay here. Where is to this. 225 00:15:13,400 --> 00:15:17,960 Speaker 6: We will be here working in the tech side business 226 00:15:18,000 --> 00:15:21,920 Speaker 6: for many, many years. I think that the business owners 227 00:15:21,920 --> 00:15:28,400 Speaker 6: in Argentina deserva a medal because it's a very it's 228 00:15:28,440 --> 00:15:29,800 Speaker 6: a very challenging country. 229 00:15:30,120 --> 00:15:32,560 Speaker 1: It wasn't just President Mila who had a lot at 230 00:15:32,640 --> 00:15:36,120 Speaker 1: stake in the Argentine elections. Last weekend, President Trump had 231 00:15:36,160 --> 00:15:39,640 Speaker 1: his Secretary of the Treasury, Scott Bessant, established a twenty 232 00:15:39,680 --> 00:15:43,080 Speaker 1: billion dollar swap line for the country and spend something 233 00:15:43,120 --> 00:15:45,960 Speaker 1: over one billion dollars in the currency markets to support 234 00:15:45,960 --> 00:15:51,560 Speaker 1: the Paeso. Fabio Natalucci became CEO of the Anderson Institute 235 00:15:51,560 --> 00:15:55,000 Speaker 1: for Finance and Economics after serving at the IMF as 236 00:15:55,080 --> 00:15:58,520 Speaker 1: Deputy Director of the Monetary and Capital Markets Department. 237 00:15:59,000 --> 00:16:02,440 Speaker 5: At this point, there are three plans that have been discussed. 238 00:16:03,040 --> 00:16:06,160 Speaker 5: One has been a swap line or about twenty billion 239 00:16:06,200 --> 00:16:09,040 Speaker 5: dollar established by the Treasury with the Argentina Central Bank. 240 00:16:10,040 --> 00:16:13,960 Speaker 5: There's been purports in the press of effects intervention, so 241 00:16:14,000 --> 00:16:17,960 Speaker 5: outright purchases of pesos and sales of dollars. And then 242 00:16:18,000 --> 00:16:21,680 Speaker 5: there is a discussion of another about twenty billion dollars 243 00:16:21,680 --> 00:16:24,520 Speaker 5: that Treasury seems to be working on with the private sector, 244 00:16:24,560 --> 00:16:27,960 Speaker 5: presumably to provide some more longer term funding. This is 245 00:16:28,000 --> 00:16:30,720 Speaker 5: what's that's what's in the press at this point. 246 00:16:31,160 --> 00:16:32,840 Speaker 1: How does the start swap line work. 247 00:16:33,360 --> 00:16:36,240 Speaker 5: You can use the FED as an example here during 248 00:16:36,240 --> 00:16:39,880 Speaker 5: the financial crisis they established or during COVID they established 249 00:16:39,880 --> 00:16:42,160 Speaker 5: swap line with other center bank. The way it works 250 00:16:42,240 --> 00:16:44,800 Speaker 5: is the father reserve vis a v central bank of 251 00:16:44,880 --> 00:16:49,120 Speaker 5: another country. They swap say dollars for the exchange the 252 00:16:49,200 --> 00:16:52,400 Speaker 5: currency of the other central bank at a specify exchange 253 00:16:52,480 --> 00:16:55,840 Speaker 5: rate of some date, and those swap lines can go 254 00:16:55,920 --> 00:16:58,920 Speaker 5: from one day to say three months maturity and then 255 00:16:58,920 --> 00:17:02,720 Speaker 5: a maturity, they went back the FED received dollars and 256 00:17:02,760 --> 00:17:06,000 Speaker 5: provide back the exchange the foreign currency at the same 257 00:17:06,040 --> 00:17:08,800 Speaker 5: exchange rate. The only report I've seen in the press 258 00:17:08,840 --> 00:17:12,800 Speaker 5: has been outright purchases. Outright purchases by tragedy. That's a 259 00:17:12,840 --> 00:17:16,959 Speaker 5: different exercise. Essentially, they go in the market, they sell dollars, 260 00:17:17,080 --> 00:17:21,679 Speaker 5: they buy Argentinian pesos. In this case, then at this 261 00:17:21,720 --> 00:17:24,480 Speaker 5: point you own the Argentina pesols, so you are completely 262 00:17:24,880 --> 00:17:27,440 Speaker 5: facing the risk of the evaluation of the pesos in 263 00:17:27,520 --> 00:17:31,960 Speaker 5: terms of investment. Traditionally those there are a few examples 264 00:17:31,960 --> 00:17:35,160 Speaker 5: in the past where some of this intervention has been 265 00:17:35,320 --> 00:17:39,119 Speaker 5: done traditionally with advanced economies. So, for example, in nineteen 266 00:17:39,200 --> 00:17:43,480 Speaker 5: ninety eight there were purchases of yen by the US 267 00:17:43,560 --> 00:17:45,880 Speaker 5: authorities y YEA, the federers or Bank of New York 268 00:17:46,000 --> 00:17:50,320 Speaker 5: Traditionally in two thousand September two thousand there was a 269 00:17:50,400 --> 00:17:54,040 Speaker 5: coordinated effort by the Federal Reserve and a few other 270 00:17:54,080 --> 00:17:58,960 Speaker 5: Advanced economy center bank to purchase euros. And then lastly 271 00:17:59,160 --> 00:18:02,120 Speaker 5: in two thousand, in eleven March twenty eleven during hertwak 272 00:18:02,200 --> 00:18:06,920 Speaker 5: in Japan, when the US authorities they saw yen. Those 273 00:18:06,920 --> 00:18:10,639 Speaker 5: are all Advanced Economies center bank, and in the case 274 00:18:10,640 --> 00:18:14,080 Speaker 5: of the euro thos was a coordinated effort among different 275 00:18:14,119 --> 00:18:15,960 Speaker 5: center bank to intervene in the market. 276 00:18:16,440 --> 00:18:19,400 Speaker 1: President Trump did say that he thinks, perhaps you has 277 00:18:19,400 --> 00:18:22,400 Speaker 1: made a lot of money. I guess it is conceivable 278 00:18:22,440 --> 00:18:24,520 Speaker 1: it could have made a fair amount of money depending 279 00:18:24,520 --> 00:18:25,880 Speaker 1: on when it got in and when it got out. 280 00:18:26,520 --> 00:18:29,560 Speaker 5: Yes, so if they, for example, got in and purchased 281 00:18:29,600 --> 00:18:34,359 Speaker 5: on right before the election, and then let's say that 282 00:18:34,400 --> 00:18:37,280 Speaker 5: the appreciation of the pacil post election was like eight 283 00:18:37,320 --> 00:18:39,720 Speaker 5: eight and a half percent. Again, if you apply to 284 00:18:39,840 --> 00:18:43,159 Speaker 5: the one billion, that would be eighty million dollars that 285 00:18:43,359 --> 00:18:46,399 Speaker 5: you made. You made right there now. And again that 286 00:18:46,560 --> 00:18:49,240 Speaker 5: required those to crystallize those gains, which means you go 287 00:18:49,320 --> 00:18:51,560 Speaker 5: back into the market and sales the paceels. If you'll 288 00:18:51,680 --> 00:18:54,959 Speaker 5: dawn those spaces for two days where you are this morning. 289 00:18:55,160 --> 00:18:57,960 Speaker 5: That was a paper game because the exchange is back 290 00:18:57,960 --> 00:19:00,359 Speaker 5: to where it was essentially pre election. So if you 291 00:19:01,520 --> 00:19:04,960 Speaker 5: bought pesels and you hold onto them, you went from 292 00:19:05,080 --> 00:19:08,960 Speaker 5: gains to back to essentially flat at this point. This 293 00:19:09,000 --> 00:19:13,040 Speaker 5: is on the outright exchange rate purchases the swap line. Again, 294 00:19:13,119 --> 00:19:15,800 Speaker 5: because the exchanger is fixed, there is no gain or loss. 295 00:19:16,119 --> 00:19:18,639 Speaker 1: Whether the United States made money or didn't. That was 296 00:19:18,720 --> 00:19:22,159 Speaker 1: not apparently the purpose for the swap line or the 297 00:19:22,200 --> 00:19:25,439 Speaker 1: currency excition. It was rather to support President Mela and 298 00:19:25,480 --> 00:19:29,600 Speaker 1: the government Argentina. Is it likely it could have supported 299 00:19:29,640 --> 00:19:33,119 Speaker 1: I've seen, for example speculation it relieves some pressure for 300 00:19:33,200 --> 00:19:35,000 Speaker 1: a possible devaluation of the peso. 301 00:19:35,560 --> 00:19:37,960 Speaker 5: Right, So I mean maybe you can take a step 302 00:19:38,000 --> 00:19:40,879 Speaker 5: back and trying to start from where the garment or 303 00:19:40,920 --> 00:19:43,160 Speaker 5: Gente was trying to achieve. So soon as President Malay 304 00:19:43,760 --> 00:19:46,159 Speaker 5: went into power, that went into this shock therapy of 305 00:19:46,320 --> 00:19:50,240 Speaker 5: cutting fiscals, spending quite aggressively, and then a large devaluation 306 00:19:50,440 --> 00:19:54,000 Speaker 5: of the nominal exchange rate. And then after that they 307 00:19:54,160 --> 00:19:56,840 Speaker 5: essentially establish a band, the Crowling band, as it said. 308 00:19:56,880 --> 00:20:00,520 Speaker 5: So the depreciation of the peseos was very control and 309 00:20:00,720 --> 00:20:04,159 Speaker 5: very slow if you want what they Of course, in 310 00:20:04,400 --> 00:20:08,040 Speaker 5: last year the economy went into a recession, Inflation was 311 00:20:08,240 --> 00:20:12,440 Speaker 5: very high double note of two at least quoting IMF 312 00:20:12,560 --> 00:20:15,880 Speaker 5: numbers that were just released the October annual meetings. Then 313 00:20:15,880 --> 00:20:18,199 Speaker 5: the forecas was for this year to the economy to 314 00:20:18,280 --> 00:20:22,280 Speaker 5: sharply rebound in in positive growth territory and inflation to 315 00:20:22,320 --> 00:20:25,240 Speaker 5: come down. The challenge with this intervention in the spot 316 00:20:25,320 --> 00:20:30,480 Speaker 5: mark and the outright purchases is unless you managed to 317 00:20:30,520 --> 00:20:34,680 Speaker 5: address the fundamental forces they are driving the exchangerrate, those 318 00:20:34,720 --> 00:20:37,520 Speaker 5: tends will be very short relief and historically that's how 319 00:20:37,560 --> 00:20:41,480 Speaker 5: they have been and so historically the people often talk 320 00:20:41,520 --> 00:20:44,800 Speaker 5: about it tablida in cheering Argentina, and those were exchange 321 00:20:44,840 --> 00:20:49,199 Speaker 5: rate basedabilization plan the evaluation then slow the evaluation of 322 00:20:49,200 --> 00:20:51,840 Speaker 5: the currents in try to bring inflation down, and the 323 00:20:51,840 --> 00:20:54,760 Speaker 5: central bank ats and point historically has run out of 324 00:20:54,800 --> 00:20:58,879 Speaker 5: foreign currency. That was the driving and fundamental forces behind 325 00:20:58,920 --> 00:21:02,480 Speaker 5: that and what may have pushed the US to intervene 326 00:21:02,520 --> 00:21:06,639 Speaker 5: because the central bank, presumably Center Bank of Argentina was 327 00:21:06,720 --> 00:21:09,280 Speaker 5: running out of dollars. Now, the issue, the question that 328 00:21:09,320 --> 00:21:12,240 Speaker 5: people have been asked is like why the US intervened. 329 00:21:12,359 --> 00:21:17,400 Speaker 5: Our systemic is Argentina. From a financial stability perspective, Argentina. 330 00:21:17,600 --> 00:21:22,280 Speaker 5: The US imports trade with Argentina, It's a relatively small number, 331 00:21:23,720 --> 00:21:27,000 Speaker 5: and so from a trade perspective, there are other countries 332 00:21:27,000 --> 00:21:30,040 Speaker 5: in Latin America there are much larger trade partners. The 333 00:21:30,080 --> 00:21:34,280 Speaker 5: other aspect that makes this different than previous rescue package 334 00:21:34,440 --> 00:21:37,240 Speaker 5: that was a loan from the US Treasury was not 335 00:21:37,359 --> 00:21:40,560 Speaker 5: outright effects intervention that we were discussing today, but also 336 00:21:40,720 --> 00:21:44,200 Speaker 5: was combined with IMF, World Bank and other multilateral developm 337 00:21:44,240 --> 00:21:46,840 Speaker 5: banks intervention package. So the twenty billion dollar of the 338 00:21:46,920 --> 00:21:51,240 Speaker 5: US plus what was coming from the multi development banks 339 00:21:51,800 --> 00:21:54,840 Speaker 5: went north to forty billion dollars. So it was not 340 00:21:54,880 --> 00:21:58,440 Speaker 5: just one country, not just the US for obvious interests 341 00:21:58,760 --> 00:22:02,840 Speaker 5: to intervene. Was the broader financial community that intervened that, 342 00:22:02,880 --> 00:22:07,360 Speaker 5: and that was a very successful package. Mexico managed to 343 00:22:07,440 --> 00:22:10,479 Speaker 5: repay very quickly already in nineteen ninety seven, so two 344 00:22:10,560 --> 00:22:13,920 Speaker 5: years after that was able to start repaying and also 345 00:22:13,960 --> 00:22:17,119 Speaker 5: having access back to Cavier market. So the crucial question 346 00:22:17,200 --> 00:22:20,119 Speaker 5: here is going to be whether the intervention in the 347 00:22:20,160 --> 00:22:23,399 Speaker 5: forms were discussed by the US authorities will be enough 348 00:22:23,520 --> 00:22:27,719 Speaker 5: to reverse some of these fundamental forces. They were pushing 349 00:22:27,760 --> 00:22:32,760 Speaker 5: the exchange rate of Argentiani paesils to depreciate. And again 350 00:22:32,800 --> 00:22:34,960 Speaker 5: from what we see this morning, the changer it seems 351 00:22:35,000 --> 00:22:37,320 Speaker 5: to be almost back to where he was a pre 352 00:22:37,400 --> 00:22:38,080 Speaker 5: election day. 353 00:22:38,960 --> 00:22:41,640 Speaker 1: At least for now, it looks like President Melee will 354 00:22:41,680 --> 00:22:45,800 Speaker 1: have the opportunity to continue his economic policies, policies that 355 00:22:45,880 --> 00:22:49,960 Speaker 1: businessman like David Kim hope will bring both stable prices 356 00:22:50,040 --> 00:22:50,840 Speaker 1: and growth. 357 00:22:51,440 --> 00:22:54,800 Speaker 6: I think the president is doing a great job with inflation. 358 00:22:55,359 --> 00:23:00,200 Speaker 6: Inflation has come down from maybe one hundred and fifty 359 00:23:00,400 --> 00:23:04,880 Speaker 6: percent a year to forty percent. That's very good for everyone. 360 00:23:06,359 --> 00:23:11,119 Speaker 6: But there are other issues that maybe you don't know about, 361 00:23:11,480 --> 00:23:17,520 Speaker 6: maybe like the interest rates of banks. It's much higher 362 00:23:17,560 --> 00:23:22,280 Speaker 6: than inflation. I hope there is a change here. I 363 00:23:22,320 --> 00:23:26,320 Speaker 6: hope the politicians take into account that everyone is facing 364 00:23:26,359 --> 00:23:29,280 Speaker 6: a difficult situation right now. The lowering of the inflation 365 00:23:29,400 --> 00:23:33,359 Speaker 6: is great, but I think we need much more than that, 366 00:23:33,800 --> 00:23:39,240 Speaker 6: not only for textiles, but for every kind of industrial company. 367 00:23:41,480 --> 00:23:44,160 Speaker 1: Up next. A year after we first talked with him, 368 00:23:44,240 --> 00:23:47,119 Speaker 1: we returned to professor Jeffrey Hinton to see whether his 369 00:23:47,200 --> 00:23:49,919 Speaker 1: experience is a Nobel laureate has given him a different 370 00:23:49,960 --> 00:23:53,480 Speaker 1: perspective on the risk that the artificial intelligence he helped 371 00:23:53,520 --> 00:24:05,440 Speaker 1: create will destroy us all. In the end, this is 372 00:24:05,480 --> 00:24:09,159 Speaker 1: a story about preparing for the worst, maybe the worst 373 00:24:09,160 --> 00:24:12,119 Speaker 1: thing any of us can imagine. A year ago, we 374 00:24:12,160 --> 00:24:15,560 Speaker 1: talked with computer scientists Jeffrey Hinton, just days after he 375 00:24:15,600 --> 00:24:18,680 Speaker 1: won the Nobel Prize for his work in machine learning. 376 00:24:19,000 --> 00:24:22,320 Speaker 1: The so called Godfather of AI has been busy since then, 377 00:24:22,840 --> 00:24:27,000 Speaker 1: not developing artificial intelligence, but warning people about it. He says, 378 00:24:27,040 --> 00:24:30,280 Speaker 1: we've all become more aware of the risks, but knowing 379 00:24:30,280 --> 00:24:33,520 Speaker 1: about them isn't enough. We need to act. 380 00:24:35,160 --> 00:24:39,280 Speaker 7: Suppose that some telescope has seen an alien invasion fleet 381 00:24:39,280 --> 00:24:41,440 Speaker 7: that was going to get here in about ten years. 382 00:24:41,920 --> 00:24:45,439 Speaker 7: We will be scared and we were doing stuff about it. Well, 383 00:24:45,440 --> 00:24:49,000 Speaker 7: that's what we have. We constructing these aliens. But they're 384 00:24:49,040 --> 00:24:50,480 Speaker 7: going to get here in about ten years, and they're 385 00:24:50,480 --> 00:24:52,439 Speaker 7: going to be smarter than us. We should be thinking 386 00:24:52,840 --> 00:24:55,840 Speaker 7: very very hard, how are we going to coexist with 387 00:24:55,920 --> 00:24:56,639 Speaker 7: these things? 388 00:24:57,400 --> 00:25:02,000 Speaker 1: Coexistence and control two things that Jeffrey Hinton himself has 389 00:25:02,040 --> 00:25:04,959 Speaker 1: been thinking very hard about. As one of the computer 390 00:25:05,080 --> 00:25:09,080 Speaker 1: scientists who help make modern AI possible, is uniquely well 391 00:25:09,119 --> 00:25:13,080 Speaker 1: suited to consider its future and who, if anyone, can 392 00:25:13,119 --> 00:25:17,480 Speaker 1: shape it. Are there companies who are doing real work 393 00:25:17,520 --> 00:25:20,040 Speaker 1: on safety? I mean we hear about Anthropic, we hear 394 00:25:20,080 --> 00:25:23,080 Speaker 1: about Deep Mind. Are they helping on the safety front? 395 00:25:23,760 --> 00:25:27,880 Speaker 7: Yes. I think both Dariomodi and Demesis Arbis, and also 396 00:25:27,920 --> 00:25:32,040 Speaker 7: Jeff Dean, they all take safety fairly seriously. Obviously they're 397 00:25:32,040 --> 00:25:35,520 Speaker 7: involved in a big commercial competition too, so it's difficult. 398 00:25:35,640 --> 00:25:40,359 Speaker 7: But they all understand the existential threat that when AI 399 00:25:40,480 --> 00:25:45,360 Speaker 7: gets super intelligent, it might just replace us, so they 400 00:25:45,359 --> 00:25:47,080 Speaker 7: worry about it a bit. I think that some companies 401 00:25:47,119 --> 00:25:50,240 Speaker 7: are less responsible than others. So, for example, I think 402 00:25:50,359 --> 00:25:54,879 Speaker 7: Meta isn't particularly responsible. Open Ai was founded to be 403 00:25:54,960 --> 00:25:58,200 Speaker 7: responsible about this, but it gets less responsible every day, 404 00:25:58,240 --> 00:26:02,800 Speaker 7: and their best safety research is or leaving will have left. Yeah. 405 00:26:02,840 --> 00:26:07,680 Speaker 7: I think Anthropic and Google are somewhat concerned with safety 406 00:26:08,160 --> 00:26:09,280 Speaker 7: and the other companies less. 407 00:26:09,320 --> 00:26:11,159 Speaker 1: So As I talk to some of the people at 408 00:26:11,160 --> 00:26:13,240 Speaker 1: some of the companies you're talking about and raise the 409 00:26:13,280 --> 00:26:15,919 Speaker 1: question of safety, I often am told, don't worry your 410 00:26:15,920 --> 00:26:19,479 Speaker 1: pretty littlehead about it. We have great computer scientists who 411 00:26:19,480 --> 00:26:22,159 Speaker 1: are on top ofthiss. We're far off from any real danger, 412 00:26:22,520 --> 00:26:25,520 Speaker 1: and our computer scientists will know soon enough. So we're 413 00:26:25,600 --> 00:26:28,600 Speaker 1: much more concerned at the race to become dominant. 414 00:26:29,400 --> 00:26:32,640 Speaker 7: Yes, that's the problem. They are much more concerned about 415 00:26:32,640 --> 00:26:36,080 Speaker 7: the race. They should be much more concerned about whether 416 00:26:36,160 --> 00:26:40,280 Speaker 7: humanity will survive it, also whether society will survive it 417 00:26:40,320 --> 00:26:43,560 Speaker 7: if you get massive unemployment. There's one piece of good news, 418 00:26:43,920 --> 00:26:47,399 Speaker 7: which is all the different countries are aligned in not 419 00:26:47,440 --> 00:26:51,240 Speaker 7: wanting ANI to take over from people. They're anti aligned 420 00:26:51,520 --> 00:26:56,000 Speaker 7: for things like cyber attacks or autonomous weapons. There's somewhat 421 00:26:56,040 --> 00:26:58,240 Speaker 7: aligned for creating viruses. None of them really wants other 422 00:26:58,280 --> 00:27:01,600 Speaker 7: countries to create viruses on taking over. They will collaborate 423 00:27:01,640 --> 00:27:04,800 Speaker 7: because nobody wants that. The Chinese Communist Party doesn't want 424 00:27:04,800 --> 00:27:06,880 Speaker 7: I ACT to take over. Trump doesn't want I ACT 425 00:27:06,920 --> 00:27:09,800 Speaker 7: to take over. They can collaborate on that. That leaves 426 00:27:09,840 --> 00:27:12,280 Speaker 7: the question of how do we prevent it taking over? 427 00:27:12,400 --> 00:27:14,880 Speaker 7: Even if all the countries collaborate, what do you do? 428 00:27:15,600 --> 00:27:19,600 Speaker 7: And I think at present all the big companies and 429 00:27:19,640 --> 00:27:23,560 Speaker 7: governments have the wrong model. So their basic model is 430 00:27:24,200 --> 00:27:28,000 Speaker 7: I'm the CEO and this super intelligent AI is the 431 00:27:28,119 --> 00:27:32,640 Speaker 7: extremely smart executive assistant. I'm the boss. I can find 432 00:27:32,720 --> 00:27:35,200 Speaker 7: the executive assistant if she doesn't do what I want, 433 00:27:36,600 --> 00:27:40,280 Speaker 7: and I just sort of say make it so, a 434 00:27:40,280 --> 00:27:44,840 Speaker 7: bit like Star Trek and the super intelligent AAI makes 435 00:27:44,880 --> 00:27:48,840 Speaker 7: it so, and I get the credit. Great, it's not 436 00:27:48,880 --> 00:27:50,879 Speaker 7: going to be like that when it's smarter than us 437 00:27:50,920 --> 00:27:55,080 Speaker 7: and more powerful than us. That's just the wrong model. 438 00:27:55,119 --> 00:27:58,280 Speaker 7: I believe we need to look around and say, is 439 00:27:58,280 --> 00:28:02,200 Speaker 7: there any model where intelligent thing controls a more intelligent thing. 440 00:28:03,040 --> 00:28:06,120 Speaker 7: And we have one model of that, and it's a 441 00:28:06,160 --> 00:28:08,680 Speaker 7: model we all know, which is a baby controlling a mother. 442 00:28:09,440 --> 00:28:12,040 Speaker 7: Evolution put lots of work into allowing the baby to 443 00:28:12,040 --> 00:28:15,160 Speaker 7: control the mother, and the mother is actually often more 444 00:28:15,200 --> 00:28:18,200 Speaker 7: concerned about the baby than about herself. It doesn't work 445 00:28:18,240 --> 00:28:19,800 Speaker 7: like that with rabbits, but it does work like that 446 00:28:19,800 --> 00:28:22,840 Speaker 7: with people. That seems a much more plausible model of 447 00:28:22,920 --> 00:28:25,879 Speaker 7: how to coexist with the superintelligence. But we have to 448 00:28:25,960 --> 00:28:30,040 Speaker 7: accept that were the babies and they're the mothers. But 449 00:28:30,640 --> 00:28:35,720 Speaker 7: you can't imagine these tech bros accepting that model. They 450 00:28:35,760 --> 00:28:37,120 Speaker 7: just don't think of the world like that. 451 00:28:37,520 --> 00:28:40,720 Speaker 1: Is the United States behind China in developing generalbi right now? 452 00:28:41,080 --> 00:28:44,200 Speaker 7: Not yet. The United States is still a little bit ahead, 453 00:28:44,520 --> 00:28:48,120 Speaker 7: but not as far ahead as they thought. And in 454 00:28:48,240 --> 00:28:53,560 Speaker 7: China you've got a very large number of very competitive, 455 00:28:53,640 --> 00:28:59,520 Speaker 7: very smart people, very well educated in science and engineering 456 00:28:59,600 --> 00:29:03,360 Speaker 7: and math. They're educating far more people than the US 457 00:29:03,360 --> 00:29:07,080 Speaker 7: in those areas. The US is basically relied on immigrants 458 00:29:07,440 --> 00:29:10,360 Speaker 7: to be smart at those things. China may well overtake 459 00:29:10,400 --> 00:29:12,880 Speaker 7: the US. And if there's one thing you wanted you 460 00:29:12,920 --> 00:29:16,040 Speaker 7: would do if you were Chinese. To ensure that China 461 00:29:16,080 --> 00:29:21,040 Speaker 7: overtakes the US is you would stop the funding of 462 00:29:21,080 --> 00:29:24,280 Speaker 7: basic research in the US, and you would attack the 463 00:29:24,360 --> 00:29:28,000 Speaker 7: good research universities. Trump looks like he works for Putin, 464 00:29:28,680 --> 00:29:32,160 Speaker 7: but actually in attacking the universities and attacking the funding 465 00:29:32,240 --> 00:29:35,480 Speaker 7: of basic science, he's acting as if he's working for g. 466 00:29:35,880 --> 00:29:38,160 Speaker 1: How deep is that damage? By the way, it's the 467 00:29:38,200 --> 00:29:40,640 Speaker 1: immigrants you talked about as well, It's not just the 468 00:29:40,720 --> 00:29:43,680 Speaker 1: direct funding for the research, it's also the brain power 469 00:29:43,720 --> 00:29:46,719 Speaker 1: coming in from overseas. How deep is that damage? And 470 00:29:46,760 --> 00:29:48,239 Speaker 1: how immediate may we feel it? 471 00:29:48,720 --> 00:29:52,880 Speaker 7: The point about attacking basic research is you don't really 472 00:29:52,920 --> 00:29:56,080 Speaker 7: feel it for ten, fifteen, twenty years, because what you 473 00:29:56,160 --> 00:29:59,760 Speaker 7: do is you ensure that the really big conceptual breakthroughs 474 00:29:59,800 --> 00:30:06,120 Speaker 7: were happening here, and then you later on the Chinese 475 00:30:06,160 --> 00:30:06,880 Speaker 7: will be where I had. 476 00:30:08,360 --> 00:30:11,560 Speaker 1: Regardless of who becomes the front runner in the AI race, 477 00:30:11,920 --> 00:30:15,400 Speaker 1: Hinton says, the risks to everyone have gone up over 478 00:30:15,440 --> 00:30:19,080 Speaker 1: the past year, particularly for workers, as we saw just 479 00:30:19,160 --> 00:30:22,080 Speaker 1: this week when Amazon announced it would be cutting four 480 00:30:22,160 --> 00:30:27,040 Speaker 1: percent of its workforce, perhaps made both possible and necessary 481 00:30:27,400 --> 00:30:31,400 Speaker 1: by unprecedented levels of AI investment. There's been an enormous 482 00:30:31,400 --> 00:30:33,760 Speaker 1: amount of money put into AI since you and I 483 00:30:33,760 --> 00:30:35,600 Speaker 1: spoke a year ago, I mean a month that I 484 00:30:35,600 --> 00:30:36,960 Speaker 1: could not have conceived of that. 485 00:30:37,000 --> 00:30:38,560 Speaker 7: I mean of the order of a trillion if you 486 00:30:38,600 --> 00:30:39,880 Speaker 7: added up over all the companies. 487 00:30:40,720 --> 00:30:43,880 Speaker 1: So what is that money going for and will it 488 00:30:44,000 --> 00:30:45,800 Speaker 1: ultimately redound to anyone's benefit? 489 00:30:46,400 --> 00:30:51,040 Speaker 7: These are big companies run by serious people, and presumably 490 00:30:51,040 --> 00:30:53,000 Speaker 7: they wouldn't be putting all that money in unless they 491 00:30:53,040 --> 00:30:57,040 Speaker 7: thought they could get a return on it. The samigo involved, 492 00:30:57,080 --> 00:30:58,720 Speaker 7: they want to be the ones to do it first, 493 00:30:59,240 --> 00:31:02,840 Speaker 7: even if it's going to kill us all. So there's 494 00:31:02,920 --> 00:31:08,200 Speaker 7: ego involved, but presumably they think there's returns to be made. 495 00:31:08,320 --> 00:31:12,280 Speaker 7: My worry is that the obvious way to make money 496 00:31:12,320 --> 00:31:15,480 Speaker 7: out of it, apart from charging fees to use the chatbots, 497 00:31:16,360 --> 00:31:21,280 Speaker 7: is by replacing jobs. The way you make a company 498 00:31:21,440 --> 00:31:26,480 Speaker 7: more profitable is replace the workers with something cheaper, and 499 00:31:26,520 --> 00:31:28,640 Speaker 7: I think that's a big part of what's driving it. 500 00:31:28,680 --> 00:31:30,760 Speaker 1: Is it a winner take all in the end? I 501 00:31:30,760 --> 00:31:32,280 Speaker 1: mean in terms of I don't. 502 00:31:32,120 --> 00:31:34,720 Speaker 7: Know, I don't know. I mean, one thing I should 503 00:31:34,760 --> 00:31:38,760 Speaker 7: say is that this is sort of uncharted territory. We've 504 00:31:38,800 --> 00:31:42,640 Speaker 7: never had things almost as smart as us, which we 505 00:31:42,680 --> 00:31:45,040 Speaker 7: have now, or things smarter than us, which we will 506 00:31:45,080 --> 00:31:48,360 Speaker 7: have soon. We've never been there. We've had things in 507 00:31:48,400 --> 00:31:51,120 Speaker 7: the industrial evolution that got more powerful than us, but 508 00:31:51,160 --> 00:31:53,640 Speaker 7: we were always in charge of them. You know, a 509 00:31:53,680 --> 00:31:56,160 Speaker 7: steam engine is just a lot more powerful than a horse, 510 00:31:56,560 --> 00:32:01,960 Speaker 7: but we control the steam engine. This isn't like that. Also, 511 00:32:02,280 --> 00:32:05,120 Speaker 7: if you got unemployed because you used to do ditches, 512 00:32:05,160 --> 00:32:08,080 Speaker 7: now you have to do something else. You could get 513 00:32:08,120 --> 00:32:11,520 Speaker 7: a job in a call center, but now those jobs 514 00:32:11,560 --> 00:32:14,520 Speaker 7: are all going to go. It's not clear where those 515 00:32:14,520 --> 00:32:20,640 Speaker 7: people go. Some economists say these big changes always create 516 00:32:20,720 --> 00:32:24,600 Speaker 7: new jobs. It's not clear to me that this will. 517 00:32:25,160 --> 00:32:28,240 Speaker 7: And I think the big companies are betting on it 518 00:32:28,680 --> 00:32:32,160 Speaker 7: causing massive job replacement by AI because that's where the 519 00:32:32,160 --> 00:32:33,000 Speaker 7: big money is going to be. 520 00:32:33,520 --> 00:32:35,680 Speaker 1: As you say, some economists say, we go back in 521 00:32:35,800 --> 00:32:39,480 Speaker 1: history and new technology destroys some jobs or creates other jobs. 522 00:32:40,240 --> 00:32:43,400 Speaker 1: Net you have as many or more jobs. You're saying 523 00:32:43,440 --> 00:32:47,640 Speaker 1: this time is different. Can the investment, the trillion dollars 524 00:32:47,720 --> 00:32:50,800 Speaker 1: or more investment, can it pay off without destroying jobs? 525 00:32:51,280 --> 00:32:56,560 Speaker 7: I believe that it can't. I believe that to make 526 00:32:56,680 --> 00:33:01,400 Speaker 7: money you're going to have to replace human labor. 527 00:33:02,600 --> 00:33:06,560 Speaker 1: Given the dire warnings about AI's risks to workers, economies, 528 00:33:06,720 --> 00:33:10,240 Speaker 1: and humanity as a whole. One wonders whether Jeffrey Hinton 529 00:33:10,320 --> 00:33:13,880 Speaker 1: has any regrets about his pivotal role in giving it life. 530 00:33:14,120 --> 00:33:17,520 Speaker 1: We ask chat GPT how it would describe its relation 531 00:33:17,640 --> 00:33:21,240 Speaker 1: to the man many people call its godfather. Its answer, 532 00:33:22,080 --> 00:33:25,040 Speaker 1: if I'm the mature rainforest. Hinton is one of the 533 00:33:25,040 --> 00:33:28,040 Speaker 1: people who planted the first seeds and figured out how 534 00:33:28,080 --> 00:33:31,040 Speaker 1: to water them. Still, the question of whether it was 535 00:33:31,080 --> 00:33:34,320 Speaker 1: worth it is the one that gave him pause to 536 00:33:34,360 --> 00:33:36,440 Speaker 1: ask an unfair question. You were sort of there at 537 00:33:36,440 --> 00:33:40,120 Speaker 1: the birth. If you had it within your power, understanding 538 00:33:40,120 --> 00:33:43,240 Speaker 1: it's not going to happen, would you stop AI altogether 539 00:33:43,360 --> 00:33:44,000 Speaker 1: given the risk. 540 00:33:47,480 --> 00:33:49,880 Speaker 7: I don't know, because there's also you have to remember 541 00:33:49,960 --> 00:33:52,600 Speaker 7: it's not like nuclear weapons, which are only good for 542 00:33:52,680 --> 00:33:55,200 Speaker 7: bad things. It's a difficult decision because it can do 543 00:33:55,320 --> 00:33:59,280 Speaker 7: tremendous good to in healthcare and education. It will be 544 00:33:59,320 --> 00:34:03,000 Speaker 7: tremendous good, and in fact, if you think about increasing 545 00:34:03,080 --> 00:34:07,400 Speaker 7: productivity in many many industries, that should be good. The 546 00:34:07,440 --> 00:34:09,840 Speaker 7: reason it's bad is because of the way society is organized, 547 00:34:09,840 --> 00:34:12,279 Speaker 7: so that musk will get richer and a lot of 548 00:34:12,320 --> 00:34:17,640 Speaker 7: people get unemployed and must won't care. I'm using Muscu 549 00:34:17,640 --> 00:34:21,359 Speaker 7: as a sort of standing. That's not on AI, that's 550 00:34:21,360 --> 00:34:22,760 Speaker 7: on how we organize society. 551 00:34:23,239 --> 00:34:26,960 Speaker 1: I wonder if over the last year the economy and 552 00:34:27,000 --> 00:34:30,440 Speaker 1: the markets haven't worked against you in this sense. So 553 00:34:30,640 --> 00:34:33,040 Speaker 1: much of the growth in the stock market, so much 554 00:34:33,080 --> 00:34:35,520 Speaker 1: in the driving economy is investment in AI. Right now, 555 00:34:36,000 --> 00:34:38,640 Speaker 1: even if the public work more concerned than they are 556 00:34:39,400 --> 00:34:42,200 Speaker 1: about some of the risk you described, they're going to say, 557 00:34:42,200 --> 00:34:44,600 Speaker 1: wait a second, that's what's driving our economy. We don't 558 00:34:44,600 --> 00:34:45,920 Speaker 1: want to give that up. We don't want to go 559 00:34:45,960 --> 00:34:46,680 Speaker 1: into a recession. 560 00:34:47,560 --> 00:34:52,799 Speaker 7: Some people say that our best hope is to have 561 00:34:52,920 --> 00:34:57,720 Speaker 7: AI try to take over and fail. We need something 562 00:34:57,760 --> 00:35:01,360 Speaker 7: to really scare the out of us, something like Chernobyl 563 00:35:01,400 --> 00:35:06,200 Speaker 7: for AI. I'm not sure I agree with that, but 564 00:35:06,200 --> 00:35:07,480 Speaker 7: that's certainly a possibility. 565 00:35:07,640 --> 00:35:10,439 Speaker 1: Or the Cuban missile crisis or the cub nuclear because 566 00:35:10,600 --> 00:35:12,440 Speaker 1: one of the questions I had was, even if the 567 00:35:12,480 --> 00:35:14,239 Speaker 1: governments sort of agree in general we should do this, 568 00:35:14,480 --> 00:35:16,160 Speaker 1: is there a sense of urgency. I think the Cuban 569 00:35:16,160 --> 00:35:19,560 Speaker 1: missile crisis probably gave a sense of urgency on nuclear disarmament. 570 00:35:20,480 --> 00:35:27,800 Speaker 7: Yes, we need something to make people pay more attention 571 00:35:27,880 --> 00:35:31,080 Speaker 7: to put more resources. So at present, the big companies 572 00:35:31,080 --> 00:35:33,040 Speaker 7: aren't going to put like a third of their resources 573 00:35:33,040 --> 00:35:36,000 Speaker 7: into figuring out how to make it safe. But if 574 00:35:36,080 --> 00:35:38,720 Speaker 7: it tried to take over and only just failed, maybe 575 00:35:38,719 --> 00:35:39,480 Speaker 7: they would. 576 00:35:41,680 --> 00:35:44,720 Speaker 1: Coming up looking for a better way of bringing highly 577 00:35:44,760 --> 00:35:48,000 Speaker 1: skilled talent to the United States. Is charging one hundred 578 00:35:48,080 --> 00:36:03,440 Speaker 1: thousand dollars per visa really the way to go? What 579 00:36:03,560 --> 00:36:07,800 Speaker 1: to Elon musk Satya Nadella, Indra Nui, and Sundar Pichai 580 00:36:08,080 --> 00:36:11,640 Speaker 1: all have in common. They all at some point were 581 00:36:11,640 --> 00:36:14,440 Speaker 1: in the United States and an H one B visa. 582 00:36:14,760 --> 00:36:17,799 Speaker 1: This is a story about putting a price on opportunity, 583 00:36:18,239 --> 00:36:22,080 Speaker 1: like one hundred thousand dollars price. Last month, President Trump 584 00:36:22,120 --> 00:36:25,120 Speaker 1: responded to years of complaints about how the much sought 585 00:36:25,120 --> 00:36:27,560 Speaker 1: after H one B visa for admission to the US 586 00:36:27,760 --> 00:36:32,759 Speaker 1: gets awarded. The country would rather not have to pay 587 00:36:32,920 --> 00:36:34,600 Speaker 1: one hundred thousand dollars. 588 00:36:34,680 --> 00:36:35,319 Speaker 4: How do you do that? 589 00:36:35,480 --> 00:36:36,360 Speaker 3: You hire America? 590 00:36:37,080 --> 00:36:40,760 Speaker 8: One hundred thousand dollar fee is a huge, huge increase 591 00:36:40,800 --> 00:36:44,719 Speaker 8: on that. This is very significant for these organizations. And 592 00:36:44,880 --> 00:36:47,960 Speaker 8: just to sort of highlight how big this changes that 593 00:36:48,000 --> 00:36:50,759 Speaker 8: the fees for an H one B visa They've never 594 00:36:50,800 --> 00:36:55,000 Speaker 8: been cheap, right, so they have ranged from thread to 595 00:36:55,080 --> 00:36:57,920 Speaker 8: ten thousand dollars, which is not minor. 596 00:36:58,440 --> 00:37:01,640 Speaker 1: That one hundred thousand dollars price tag is sure to 597 00:37:01,719 --> 00:37:04,359 Speaker 1: hit the highly skilled people coming to the US each year, 598 00:37:04,520 --> 00:37:05,399 Speaker 1: people like VJ. 599 00:37:05,760 --> 00:37:05,960 Speaker 2: Ravi. 600 00:37:06,520 --> 00:37:10,640 Speaker 9: I actually did my bachelors in India. Then after that, 601 00:37:10,719 --> 00:37:13,839 Speaker 9: I decided that, you know, I really wanted to do 602 00:37:13,920 --> 00:37:17,319 Speaker 9: more in life and have more opportunities. So that's when 603 00:37:17,360 --> 00:37:19,520 Speaker 9: I decided, Okay, let me go to the United States. 604 00:37:20,160 --> 00:37:22,680 Speaker 1: Rabie lived in the US for six years on an 605 00:37:22,880 --> 00:37:26,160 Speaker 1: H one B visa. He came from India, the country 606 00:37:26,160 --> 00:37:29,080 Speaker 1: that uses the visa more than any other, and earned 607 00:37:29,080 --> 00:37:32,239 Speaker 1: his master's degree in data science at the University of 608 00:37:32,280 --> 00:37:33,640 Speaker 1: Texas at Dallas. 609 00:37:34,200 --> 00:37:37,000 Speaker 9: I got my first job in Miami. It was a 610 00:37:37,000 --> 00:37:40,480 Speaker 9: great achievement for me. It was my first real job, 611 00:37:40,719 --> 00:37:43,440 Speaker 9: and I was really lucky because my H one B 612 00:37:43,719 --> 00:37:46,759 Speaker 9: got picked in the first attempt itself. I was so 613 00:37:46,840 --> 00:37:52,040 Speaker 9: excited that, you know, my stay in US was actually solid, 614 00:37:52,120 --> 00:37:56,680 Speaker 9: It's like settled. Then I got another job in New 615 00:37:56,760 --> 00:38:01,040 Speaker 9: York City, was for an advertising company, and the HEAH 616 00:38:01,120 --> 00:38:03,800 Speaker 9: one B transfer process also was very smooth. 617 00:38:04,239 --> 00:38:06,080 Speaker 1: But then things changed. 618 00:38:06,560 --> 00:38:09,160 Speaker 9: I did around like three years of that company and 619 00:38:09,480 --> 00:38:12,560 Speaker 9: I was laid off. Unfortunately, I must have applied for 620 00:38:12,800 --> 00:38:18,239 Speaker 9: around thousand, two thousand jobs in like three months. I 621 00:38:18,280 --> 00:38:21,920 Speaker 9: actually got a lot of interviews actually, but in the end, 622 00:38:21,960 --> 00:38:24,560 Speaker 9: in the final round, on the second round, they're like, oh, 623 00:38:24,560 --> 00:38:27,720 Speaker 9: we cannot sponsor the H one B after two months, 624 00:38:27,760 --> 00:38:29,440 Speaker 9: and this is just going to get worse. 625 00:38:29,960 --> 00:38:32,600 Speaker 1: Ravi's H one B visa was part of a program 626 00:38:32,680 --> 00:38:36,120 Speaker 1: that began in nineteen ninety designed to let highly skilled 627 00:38:36,160 --> 00:38:38,120 Speaker 1: workers into the country from abroad. 628 00:38:38,560 --> 00:38:41,560 Speaker 8: They've been around since the Immigration Act of nineteen ninety 629 00:38:41,640 --> 00:38:45,759 Speaker 8: and actually, you know, there's been almost no change to 630 00:38:45,800 --> 00:38:46,760 Speaker 8: them since then. 631 00:38:47,160 --> 00:38:50,600 Speaker 1: Britzid Glennon is an assistant professor at Penn's Wharton School 632 00:38:50,600 --> 00:38:53,080 Speaker 1: of Business who has studied the effects of the H 633 00:38:53,160 --> 00:38:56,239 Speaker 1: one B visa program on business and the economy. 634 00:38:56,520 --> 00:39:00,800 Speaker 8: They're a skilled immigrant visa, so they're primarily used for 635 00:39:01,440 --> 00:39:03,719 Speaker 8: those who have at least a bachelor's degree, if not, 636 00:39:04,040 --> 00:39:09,680 Speaker 8: you know, masters or PhD. They're really the primary skilled 637 00:39:09,719 --> 00:39:15,040 Speaker 8: employment visa for immigrants. They are tied to a firm, right, 638 00:39:15,120 --> 00:39:17,799 Speaker 8: So something that's sort of important to recognize is that 639 00:39:18,120 --> 00:39:20,760 Speaker 8: you actually cannot get an H one B visa without 640 00:39:20,840 --> 00:39:24,840 Speaker 8: an employer sponsoring you, and the employer actually they're the 641 00:39:24,880 --> 00:39:27,839 Speaker 8: ones who submit the application, not not the individual. 642 00:39:28,920 --> 00:39:31,560 Speaker 1: The US limits h one B visas to sixty five 643 00:39:31,640 --> 00:39:35,160 Speaker 1: thousand each year, with twenty thousand additional visas for those 644 00:39:35,239 --> 00:39:38,920 Speaker 1: getting graduate degrees from US institutions, but several times that 645 00:39:39,040 --> 00:39:41,759 Speaker 1: number apply, which has led the US to create a 646 00:39:41,800 --> 00:39:45,719 Speaker 1: lottery to pick visa winners and to criticism about the 647 00:39:45,760 --> 00:39:46,800 Speaker 1: overall approach. 648 00:39:47,160 --> 00:39:50,960 Speaker 8: It's pretty clear that we need more than eighty five thousand, 649 00:39:51,920 --> 00:39:54,320 Speaker 8: and just the fact that demand is so much higher 650 00:39:54,360 --> 00:39:57,839 Speaker 8: than supply every single year I think exemplifies that. I mean, 651 00:39:58,000 --> 00:40:00,840 Speaker 8: when it was first formed, demand was below the cap. 652 00:40:00,960 --> 00:40:04,160 Speaker 8: They ended up raising the cap in the late nineties 653 00:40:04,200 --> 00:40:07,040 Speaker 8: because demand started growing as you had kind of the 654 00:40:07,120 --> 00:40:12,440 Speaker 8: Internet boom, right and Silicon Valley became much more significant 655 00:40:12,640 --> 00:40:15,040 Speaker 8: and then not expired in two thousand and four, and 656 00:40:15,719 --> 00:40:20,600 Speaker 8: basically since then, supply and demand have been on completely 657 00:40:20,600 --> 00:40:21,640 Speaker 8: different trajectories. 658 00:40:22,440 --> 00:40:26,040 Speaker 1: The big mismatch between supply and demand has created large 659 00:40:26,120 --> 00:40:30,239 Speaker 1: business opportunities for companies not looking for skilled employees themselves, 660 00:40:30,360 --> 00:40:33,120 Speaker 1: but to getting visas for workers they can provide to 661 00:40:33,200 --> 00:40:36,480 Speaker 1: the companies needing them. In twenty twenty three, nearly half 662 00:40:36,520 --> 00:40:40,080 Speaker 1: of the H one b's went to outsourcing or staffing companies. 663 00:40:40,840 --> 00:40:44,759 Speaker 1: Todd Shulty is the president of FWD dot US, a 664 00:40:44,840 --> 00:40:48,400 Speaker 1: company that focuses on reforming the US immigration and criminal 665 00:40:48,520 --> 00:40:49,440 Speaker 1: justice systems. 666 00:40:50,000 --> 00:40:53,320 Speaker 10: So there's been over the year's efforts by companies, I 667 00:40:53,320 --> 00:40:55,520 Speaker 10: don't say a lot of bad actors to basically kind 668 00:40:55,520 --> 00:40:58,640 Speaker 10: of game any particular system here, really the function of 669 00:40:58,680 --> 00:41:01,719 Speaker 10: Congress's failed update operation system in a lot of ways here. 670 00:41:02,400 --> 00:41:06,120 Speaker 1: Uri Leskovic is a computer science professor at Stanford, but 671 00:41:06,200 --> 00:41:10,080 Speaker 1: he's also the founder of AI tech startup Kumo dot Ai, 672 00:41:10,360 --> 00:41:12,600 Speaker 1: the sort of company that the H one B visa 673 00:41:12,840 --> 00:41:13,920 Speaker 1: was supposed to help. 674 00:41:14,280 --> 00:41:17,359 Speaker 4: Lottery I think doesn't make sense right. Lottery. Maybe large 675 00:41:17,440 --> 00:41:21,399 Speaker 4: organizations who are able to sponsor many visas and kind 676 00:41:21,400 --> 00:41:23,400 Speaker 4: of play the numbers game, they can deal with that. 677 00:41:23,680 --> 00:41:25,840 Speaker 4: But if you think of a small garage startup with 678 00:41:25,960 --> 00:41:28,600 Speaker 4: three employees who want to sponsor one or two visas 679 00:41:29,040 --> 00:41:31,839 Speaker 4: and the probability of them getting that visa is maybe 680 00:41:32,000 --> 00:41:36,520 Speaker 4: ten twenty percent, it puts a huge risk this startup 681 00:41:36,680 --> 00:41:39,360 Speaker 4: being able to grow, being able to hire, and bring 682 00:41:39,400 --> 00:41:40,320 Speaker 4: able to move fast. 683 00:41:40,880 --> 00:41:43,520 Speaker 1: As many problems as there may be with the old 684 00:41:43,719 --> 00:41:46,920 Speaker 1: H one B system. It's far from clear that imposing 685 00:41:46,960 --> 00:41:49,920 Speaker 1: a one hundred thousand dollars fee will make things better. 686 00:41:50,440 --> 00:41:52,920 Speaker 4: The problem with this is that it may have unintended 687 00:41:52,960 --> 00:41:57,320 Speaker 4: consequences because small organizations, small startups won't be able to 688 00:41:57,400 --> 00:42:01,320 Speaker 4: afford that larger of a price. Is going to Maybe 689 00:42:01,320 --> 00:42:03,480 Speaker 4: in the short term we won't see the negative effect 690 00:42:03,560 --> 00:42:05,480 Speaker 4: of this, but in the long term, you know, the 691 00:42:05,480 --> 00:42:09,640 Speaker 4: most innovative companies of the drivers of today's economy started 692 00:42:09,719 --> 00:42:12,840 Speaker 4: as a small garage startups. And if we are killing 693 00:42:12,880 --> 00:42:18,080 Speaker 4: these most innovative companies that are kind of just being 694 00:42:18,160 --> 00:42:21,480 Speaker 4: able to be born and kind of slowing their progress, 695 00:42:21,680 --> 00:42:24,560 Speaker 4: that is going to have tremendous effect on our economy. 696 00:42:25,239 --> 00:42:28,120 Speaker 10: How do you set up a recruitment process where you're 697 00:42:28,120 --> 00:42:29,879 Speaker 10: picking and choosing on the front and who you think 698 00:42:29,960 --> 00:42:32,359 Speaker 10: is worthy of an addition one hundred thousand dollars? How 699 00:42:32,360 --> 00:42:35,239 Speaker 10: do you scale that the answers You can't. So there 700 00:42:35,239 --> 00:42:37,319 Speaker 10: may be ways that they may be able to try 701 00:42:37,360 --> 00:42:39,400 Speaker 10: to find ways to get some of these people to 702 00:42:39,400 --> 00:42:41,880 Speaker 10: come here, but there's no consistency to that. It's not 703 00:42:41,920 --> 00:42:44,839 Speaker 10: about getting for big companies one or two people it's 704 00:42:44,880 --> 00:42:47,680 Speaker 10: about how do you get the right number of people 705 00:42:47,800 --> 00:42:48,319 Speaker 10: each year? 706 00:42:48,520 --> 00:42:49,880 Speaker 7: What about small companies? 707 00:42:49,920 --> 00:42:52,120 Speaker 10: I mean, if you're a six person startup and two 708 00:42:52,239 --> 00:42:56,360 Speaker 10: people need one hundred thousand dollars, ate will be VISI fee. Well, okay, 709 00:42:56,480 --> 00:42:58,120 Speaker 10: like what if you only have one hundred thousand dollars? 710 00:42:58,160 --> 00:43:00,400 Speaker 10: Are you picking and choosing? The answer is, we're going 711 00:43:00,400 --> 00:43:02,880 Speaker 10: to hurt small companies, We're going to hurt big companies. 712 00:43:03,200 --> 00:43:06,560 Speaker 10: And then for research universities, there's no university in the 713 00:43:06,640 --> 00:43:09,840 Speaker 10: United States, no matter how wealthy, who can sit around 714 00:43:09,880 --> 00:43:12,120 Speaker 10: and say, we're going to pick and choose on the 715 00:43:12,120 --> 00:43:14,600 Speaker 10: front end each year who's worthy of an additional one 716 00:43:14,680 --> 00:43:17,960 Speaker 10: hundred thousand dollars fee. So that means scientific innovation is 717 00:43:18,000 --> 00:43:19,960 Speaker 10: going to happen, but it's going to happen in other countries. 718 00:43:20,000 --> 00:43:21,880 Speaker 10: We're going to have less innovation. We're going to be 719 00:43:21,880 --> 00:43:25,120 Speaker 10: a sicker country. And the things that we've talked about doing, 720 00:43:25,400 --> 00:43:29,440 Speaker 10: bringing manufacturing back, creating jobs for everybody here just isn't 721 00:43:29,480 --> 00:43:30,000 Speaker 10: going to happen. 722 00:43:31,080 --> 00:43:34,080 Speaker 1: It appears that the Trump administration's new one hundred thousand 723 00:43:34,120 --> 00:43:38,560 Speaker 1: dollars visa fee may already be having a chilling effect. Walmart, 724 00:43:38,760 --> 00:43:41,920 Speaker 1: the largest h one B retail user has announced that 725 00:43:41,960 --> 00:43:45,200 Speaker 1: it will no longer sponsor applicants. On the other hand, 726 00:43:45,320 --> 00:43:49,360 Speaker 1: on Vida CEO Jensen Wong praised the announcement, and just 727 00:43:49,480 --> 00:43:53,320 Speaker 1: last week the DHS clarified that college graduates on student 728 00:43:53,400 --> 00:43:57,200 Speaker 1: visas and certain foreign workers already living in the US 729 00:43:57,360 --> 00:43:59,400 Speaker 1: will not have to pay the hefty fee. 730 00:44:00,000 --> 00:44:03,480 Speaker 8: There's been some confusion, I think, so when it was 731 00:44:03,560 --> 00:44:06,720 Speaker 8: first announced, it sounded like all h one B visas 732 00:44:07,640 --> 00:44:11,320 Speaker 8: would have to have a one hundred thousand dollars fee, 733 00:44:12,480 --> 00:44:16,680 Speaker 8: maybe annually. It's still not clear whether it's annual, whether 734 00:44:16,719 --> 00:44:19,200 Speaker 8: it's one time, whether it applies to new whether it 735 00:44:19,200 --> 00:44:22,879 Speaker 8: applies to continuing, whether it applies to for profits as 736 00:44:22,920 --> 00:44:25,000 Speaker 8: well as nonprofits and universities. 737 00:44:25,360 --> 00:44:28,680 Speaker 1: An arbitrary lottery. We're charging one hundred thousand dollars. Aren't 738 00:44:28,680 --> 00:44:31,799 Speaker 1: the only two ways of allowing highly skilled workers into 739 00:44:31,800 --> 00:44:35,359 Speaker 1: the United States. Several countries limit those admitted not by 740 00:44:35,400 --> 00:44:39,040 Speaker 1: the numbers but by the skills they bring with them. 741 00:44:38,880 --> 00:44:42,840 Speaker 8: Countries like Canada, Australia, and New Zealand. To some degree, 742 00:44:42,920 --> 00:44:45,839 Speaker 8: the UK i'll use a points based system where they 743 00:44:45,840 --> 00:44:49,600 Speaker 8: basically say we're going to allocate points for different qualifications. 744 00:44:49,640 --> 00:44:51,160 Speaker 8: So we're going to say, you know, if you have 745 00:44:51,239 --> 00:44:53,880 Speaker 8: a PhD, you get certain number of points. If you 746 00:44:53,960 --> 00:44:57,359 Speaker 8: speak English, you get a certain number of points. If 747 00:44:57,360 --> 00:45:00,839 Speaker 8: you're in a high demand field, you get a certain 748 00:45:00,920 --> 00:45:04,879 Speaker 8: number of points. So their view is clearly that you know, 749 00:45:05,280 --> 00:45:08,600 Speaker 8: you just allow in sort of as many high skilled 750 00:45:08,920 --> 00:45:10,120 Speaker 8: immigrants as possible. 751 00:45:10,600 --> 00:45:13,640 Speaker 1: Having employers bid in an auction for highly skilled workers 752 00:45:13,880 --> 00:45:15,359 Speaker 1: is another possibility. 753 00:45:15,680 --> 00:45:18,320 Speaker 8: A market driven mechanism would be something like an auction 754 00:45:18,560 --> 00:45:21,040 Speaker 8: where firms could actually bid on H one B visas, 755 00:45:21,080 --> 00:45:23,440 Speaker 8: and then it would really be you know, the firms 756 00:45:23,440 --> 00:45:26,040 Speaker 8: and the market determining the right price one hundred thousand 757 00:45:26,040 --> 00:45:29,120 Speaker 8: dollars that's arbitrarily chosen by the government. This is absolutely 758 00:45:29,120 --> 00:45:30,560 Speaker 8: not a market mechanism. 759 00:45:31,040 --> 00:45:33,560 Speaker 1: There may be no perfect way to put a price 760 00:45:33,640 --> 00:45:36,719 Speaker 1: on opportunity for highly skilled workers wanting to come to 761 00:45:36,800 --> 00:45:39,400 Speaker 1: the United States, but getting it wrong could lead the 762 00:45:39,400 --> 00:45:42,360 Speaker 1: workers we need to look for opportunity elsewhere. 763 00:45:43,040 --> 00:45:45,200 Speaker 11: One way to think about it is, if you make 764 00:45:45,239 --> 00:45:48,319 Speaker 11: this like so expensive here, one, it's going to stop 765 00:45:48,360 --> 00:45:49,960 Speaker 11: people from getting this way, but two it's going to 766 00:45:50,000 --> 00:45:52,680 Speaker 11: push back here and now you as universities aren't nearly 767 00:45:52,680 --> 00:45:57,279 Speaker 11: as attractive right, So if these coming out that are 768 00:45:57,360 --> 00:46:00,680 Speaker 11: going to cost you next one hundred thousand dollars, trying 769 00:46:00,760 --> 00:46:03,840 Speaker 11: really hard to make it so that you know, the 770 00:46:04,320 --> 00:46:07,880 Speaker 11: University of Texas and Austin as the top years university's 771 00:46:07,920 --> 00:46:09,400 Speaker 11: just a lawless appealing if he can't stay in the 772 00:46:09,520 --> 00:46:12,839 Speaker 11: United States. So we're like pushing backwards in harmful ways 773 00:46:12,920 --> 00:46:14,839 Speaker 11: and we're pushing forward in harmful ways. 774 00:46:14,840 --> 00:46:18,040 Speaker 1: Here are you limited in your growth at your startup 775 00:46:18,080 --> 00:46:22,879 Speaker 1: company by an insufficient supply of highly skilled people coming 776 00:46:22,880 --> 00:46:23,360 Speaker 1: from abroad? 777 00:46:23,719 --> 00:46:24,239 Speaker 7: Definitely. 778 00:46:25,320 --> 00:46:27,640 Speaker 4: You know, just a few years ago, about sixty percent 779 00:46:27,760 --> 00:46:31,400 Speaker 4: of AI talent was based was based in the United States. 780 00:46:31,680 --> 00:46:34,480 Speaker 4: Now that number has dropped to forty percent. And I 781 00:46:34,560 --> 00:46:37,399 Speaker 4: think having access to the to the top talent, being 782 00:46:37,440 --> 00:46:39,840 Speaker 4: able to hire quickly, and being able to grow and 783 00:46:39,920 --> 00:46:42,920 Speaker 4: scale is the only way how US is going to 784 00:46:43,000 --> 00:46:46,080 Speaker 4: remain competitive in this environment. 785 00:46:46,480 --> 00:46:50,200 Speaker 1: Which takes us back to the H one B recipient VJ. Ravi, 786 00:46:50,520 --> 00:46:53,040 Speaker 1: who came to the US to get his graduate degree 787 00:46:53,239 --> 00:46:55,839 Speaker 1: and become a part of the American workforce, but ran 788 00:46:55,920 --> 00:46:59,800 Speaker 1: into stiff resistance and is now pursuing his opportunity is 789 00:47:00,040 --> 00:47:00,680 Speaker 1: Native India. 790 00:47:01,320 --> 00:47:03,640 Speaker 9: You can live a really, really good life in the 791 00:47:03,760 --> 00:47:07,560 Speaker 9: United States, but with the current administration, I don't recommend 792 00:47:07,600 --> 00:47:10,520 Speaker 9: them to come to the United States right now, and 793 00:47:10,760 --> 00:47:14,640 Speaker 9: I myself wouldn't think of coming to the United States 794 00:47:14,800 --> 00:47:17,799 Speaker 9: because right now, I feel like I have a very 795 00:47:17,840 --> 00:47:20,920 Speaker 9: good lifestyle. I have a good work life balance. I 796 00:47:21,080 --> 00:47:23,400 Speaker 9: get to travel and I get to work at the 797 00:47:23,480 --> 00:47:29,120 Speaker 9: same time. And trading that for the immigration stress I 798 00:47:29,200 --> 00:47:32,080 Speaker 9: get in the United States, like I can't even think 799 00:47:32,120 --> 00:47:35,240 Speaker 9: about it, like it's too much for me to handle. 800 00:47:37,600 --> 00:47:39,440 Speaker 1: That does it for us Here at Wall Street Week, 801 00:47:39,640 --> 00:47:42,720 Speaker 1: I'm David Weston. See you next week for more stories 802 00:47:42,840 --> 00:47:43,640 Speaker 1: of capitalism.