1 00:00:00,240 --> 00:00:02,480 Speaker 1: This is Bloomberg Wall Street Week. 2 00:00:02,480 --> 00:00:04,400 Speaker 2: I mean may not have an overall recession, We're having 3 00:00:04,400 --> 00:00:06,720 Speaker 2: a rolling recession to kind of roll looks pretty strongly 4 00:00:06,720 --> 00:00:07,320 Speaker 2: it is when it comes. 5 00:00:07,240 --> 00:00:09,840 Speaker 1: To jobs, the financial stories that shape our world. 6 00:00:09,960 --> 00:00:13,640 Speaker 2: Three major regional bank failures send shockwaves through the banking system. 7 00:00:13,680 --> 00:00:15,480 Speaker 2: We're all trying to figure out what to make of 8 00:00:15,600 --> 00:00:17,000 Speaker 2: generative AI. 9 00:00:16,920 --> 00:00:19,320 Speaker 1: Through the eyes of the most influential voices. 10 00:00:19,440 --> 00:00:22,400 Speaker 2: Welcome down, Doctor Paul Krugman, Ryan moynihan, Bank of America, 11 00:00:22,560 --> 00:00:25,279 Speaker 2: deebro Lair of the Paulson Institute, well then Hubbard of 12 00:00:25,280 --> 00:00:26,280 Speaker 2: the Columbia Business School. 13 00:00:26,280 --> 00:00:30,120 Speaker 1: Bloomberg Wall Street Week with David Weston from Bloomberg Radio. 14 00:00:30,400 --> 00:00:33,720 Speaker 2: Harvard President leaves a war in the Middle East, stays 15 00:00:33,840 --> 00:00:36,960 Speaker 2: and Santa takes his rally with him on his sleigh. 16 00:00:37,520 --> 00:00:40,839 Speaker 2: This is Bloomberg Wall Street Week. I'm David Weston, this 17 00:00:40,880 --> 00:00:43,960 Speaker 2: week's secial contributor to Larry Summers and the US jobs numbers. 18 00:00:44,280 --> 00:00:49,000 Speaker 3: It's certainly increasingly possible that we'll have that much valleyhed 19 00:00:49,240 --> 00:00:53,880 Speaker 3: soft landing as rare as those who have been historically. 20 00:00:54,240 --> 00:00:57,200 Speaker 2: And David Otter of MIT on what to expect from 21 00:00:57,240 --> 00:00:58,320 Speaker 2: Generative AI. 22 00:00:58,920 --> 00:01:01,160 Speaker 4: Part of that on a game that's so called you 23 00:01:01,160 --> 00:01:03,800 Speaker 4: know AI, give it in will actually be squandered on 24 00:01:04,280 --> 00:01:04,960 Speaker 4: AI defense. 25 00:01:17,720 --> 00:01:20,399 Speaker 2: Global Wall Street got the new year underway this week 26 00:01:20,480 --> 00:01:23,039 Speaker 2: with big changes at the top of Harvard. 27 00:01:23,360 --> 00:01:27,240 Speaker 5: The Harvard Crimson reporting that Claudine Gay will resign today. 28 00:01:27,360 --> 00:01:30,360 Speaker 5: And keep in mind she was Harvard's first black president. 29 00:01:30,640 --> 00:01:32,920 Speaker 5: She just took the post up in July, so this 30 00:01:32,959 --> 00:01:36,279 Speaker 5: is the shortest tenure in Harvard's history, just six months 31 00:01:36,680 --> 00:01:37,399 Speaker 5: and two days. 32 00:01:37,520 --> 00:01:40,440 Speaker 2: While things in the Middle East showed little signs of changing, 33 00:01:40,520 --> 00:01:41,840 Speaker 2: at least for the better. 34 00:01:42,080 --> 00:01:45,720 Speaker 6: I think as events unfold, we're likely to see more escalation, 35 00:01:46,440 --> 00:01:49,160 Speaker 6: stepped up attacks, and as a result, the market's going 36 00:01:49,200 --> 00:01:51,960 Speaker 6: to sort of be dragged back to this Polish Middle 37 00:01:52,000 --> 00:01:53,000 Speaker 6: East risk. 38 00:01:53,000 --> 00:01:55,760 Speaker 2: And Bob Ayer's challenges A Disney stretched into the new 39 00:01:55,840 --> 00:01:59,080 Speaker 2: year as Nelson Pelts continued to challenge his leadership, even 40 00:01:59,120 --> 00:02:02,160 Speaker 2: as another active Blackwells came to his defense. 41 00:02:02,920 --> 00:02:04,720 Speaker 5: This is going to be a really contentious fight I 42 00:02:04,760 --> 00:02:06,200 Speaker 5: think between False and Disney. 43 00:02:06,240 --> 00:02:09,880 Speaker 1: He obviously does definitely want to put himself on the board. 44 00:02:09,919 --> 00:02:12,160 Speaker 5: He definitely wants to see Jay Rizzulu on the board. 45 00:02:12,360 --> 00:02:15,480 Speaker 2: The Federal Reserve released its minutes from the December meeting 46 00:02:15,560 --> 00:02:18,959 Speaker 2: showing a cautious approach, with members talking about the possibility 47 00:02:18,960 --> 00:02:23,320 Speaker 2: of holding for longer than expected, cutting or even raising rates. 48 00:02:23,639 --> 00:02:26,240 Speaker 7: I think we do have to pay a very careful 49 00:02:26,240 --> 00:02:28,919 Speaker 7: attention to that tug of war between what markets are 50 00:02:28,960 --> 00:02:31,920 Speaker 7: seeing in terms of FED easing and whatnot in what 51 00:02:31,960 --> 00:02:33,800 Speaker 7: the macro data are suggesting. 52 00:02:35,480 --> 00:02:38,240 Speaker 2: And then on Friday, US jobs numbers came out stronger 53 00:02:38,280 --> 00:02:41,040 Speaker 2: than expected, pointing to a surprising strength in the economy, 54 00:02:41,360 --> 00:02:44,120 Speaker 2: only to be countered by ISM numbers ninety minutes later 55 00:02:44,120 --> 00:02:47,320 Speaker 2: suggesting some slowing. The markets took all this into account 56 00:02:47,320 --> 00:02:49,600 Speaker 2: and decided that Santa had after all gone back to 57 00:02:49,680 --> 00:02:51,760 Speaker 2: the North Pole and taken his rally with him, with 58 00:02:51,840 --> 00:02:53,480 Speaker 2: the S and P five hundred down one and a 59 00:02:53,480 --> 00:02:55,200 Speaker 2: half percent for the first week of the new year, 60 00:02:55,320 --> 00:02:57,600 Speaker 2: ending at forty six to ninety seven, which is still 61 00:02:57,720 --> 00:02:59,959 Speaker 2: nicely above the forty five hundred number of the bloomer 62 00:03:00,240 --> 00:03:02,840 Speaker 2: El's are predicting for the median. At the year end, 63 00:03:03,080 --> 00:03:05,800 Speaker 2: the NASDAG gave up three and a quarter percent, while 64 00:03:05,840 --> 00:03:08,320 Speaker 2: the yield on the tenure decided to peek its head 65 00:03:08,400 --> 00:03:11,360 Speaker 2: back above four percent, ending the week up over eleven 66 00:03:11,400 --> 00:03:14,320 Speaker 2: basing spoints at four point five to take us through 67 00:03:14,360 --> 00:03:16,640 Speaker 2: the start of the year. Welcome back now, David Bianco, 68 00:03:16,680 --> 00:03:19,760 Speaker 2: he's DWS Chief Investment Officer for the Americas. Welcome back, 69 00:03:19,760 --> 00:03:20,840 Speaker 2: great to have you, happy news. 70 00:03:20,680 --> 00:03:22,280 Speaker 8: Happy new year. That's great to be here for the 71 00:03:22,280 --> 00:03:22,880 Speaker 8: first Friday. 72 00:03:23,200 --> 00:03:25,799 Speaker 2: So Friday was a bit of a whiplash, at least 73 00:03:25,800 --> 00:03:27,799 Speaker 2: for me, because we had those jobs numbers come out. 74 00:03:27,919 --> 00:03:29,440 Speaker 2: The markets seemed to know what to do about that. 75 00:03:29,480 --> 00:03:31,680 Speaker 2: They didn't like it very much, and then the sm 76 00:03:31,720 --> 00:03:34,240 Speaker 2: numbers came out, turn right around. What did we take 77 00:03:34,280 --> 00:03:34,600 Speaker 2: out of this? 78 00:03:35,600 --> 00:03:38,360 Speaker 9: Well, the week, first week of the year, and not 79 00:03:38,440 --> 00:03:42,640 Speaker 9: a great start. Many investors are calling for us to 80 00:03:42,640 --> 00:03:45,960 Speaker 9: pay attention to the January indicator the first several days, 81 00:03:46,000 --> 00:03:48,960 Speaker 9: first five days of the year. Often investors say that's 82 00:03:48,960 --> 00:03:51,160 Speaker 9: the way the rest of the year will go. Not 83 00:03:51,240 --> 00:03:54,120 Speaker 9: a great start, but it's just a start to the year. 84 00:03:54,160 --> 00:03:55,920 Speaker 9: We'll see how things play out. 85 00:03:56,400 --> 00:03:57,400 Speaker 8: The first data, as. 86 00:03:57,240 --> 00:04:00,960 Speaker 9: You said, key data, job market data for SUMBER and 87 00:04:01,120 --> 00:04:05,200 Speaker 9: the manufacturing and the service ism. The way I see 88 00:04:05,200 --> 00:04:08,920 Speaker 9: it is that the job market is absolutely solid. Another 89 00:04:09,040 --> 00:04:10,800 Speaker 9: month of more than two hundred, tw hundred and sixteen 90 00:04:10,800 --> 00:04:16,000 Speaker 9: thousand jobs created on the establishment survey, and we still 91 00:04:16,040 --> 00:04:20,160 Speaker 9: see strong wage growth, more than four percent. 92 00:04:20,680 --> 00:04:22,440 Speaker 8: Sequentially and year on year. 93 00:04:23,120 --> 00:04:25,600 Speaker 9: And another interesting thing is that not only did the 94 00:04:25,680 --> 00:04:29,400 Speaker 9: unemployment rate stay at three point seven percent, among the 95 00:04:29,440 --> 00:04:33,840 Speaker 9: lowest in many many decades, we saw something interesting where 96 00:04:33,880 --> 00:04:38,320 Speaker 9: it looks like nearly seven hundred thousand people who recently 97 00:04:38,480 --> 00:04:42,159 Speaker 9: entered the labor market decided for whatever reason, to exit it. 98 00:04:42,600 --> 00:04:46,080 Speaker 9: So the participation rate is sixty two point five percent, 99 00:04:46,560 --> 00:04:50,880 Speaker 9: well above the lows during the pandemic, but still below 100 00:04:51,800 --> 00:04:54,680 Speaker 9: the sixty three percent level before the pandemic. It's a 101 00:04:54,720 --> 00:04:58,960 Speaker 9: full employment economy. We're still creating jobs, mostly on the 102 00:04:58,960 --> 00:05:01,640 Speaker 9: service side of the economy. Manufacturing is still weak, but 103 00:05:01,680 --> 00:05:04,720 Speaker 9: it's definitely a full employment economy with no slack in my. 104 00:05:04,720 --> 00:05:08,120 Speaker 2: View, Does that give the FED permission to cut anytime soon? 105 00:05:08,160 --> 00:05:09,760 Speaker 2: And we came out of last year with a lot 106 00:05:09,760 --> 00:05:13,440 Speaker 2: of momentum, basically with anticipated cuts perhaps even early in 107 00:05:13,480 --> 00:05:16,599 Speaker 2: the new year. Given those jobs numbers and the numbers 108 00:05:16,600 --> 00:05:18,360 Speaker 2: we're getting right now, does it give the permission that 109 00:05:18,400 --> 00:05:20,240 Speaker 2: have FED any permission to cut at this point? 110 00:05:20,400 --> 00:05:25,039 Speaker 9: Not yet. I think the disinflation that we've seen during 111 00:05:25,200 --> 00:05:28,279 Speaker 9: twenty twenty three and it more needs to occur in 112 00:05:28,320 --> 00:05:31,560 Speaker 9: twenty twenty four has opened the door to cuts beginning 113 00:05:32,080 --> 00:05:34,600 Speaker 9: in twenty twenty four. We think the first one will 114 00:05:34,640 --> 00:05:38,560 Speaker 9: be in June, and should be no earlier than June, 115 00:05:38,920 --> 00:05:42,440 Speaker 9: and it would just be so odd. There's no historical 116 00:05:42,440 --> 00:05:46,840 Speaker 9: precedent since nineteen sixty of the FED cutting when unemployments 117 00:05:46,880 --> 00:05:50,480 Speaker 9: below four percent. The stock market is basically at all 118 00:05:50,600 --> 00:05:53,320 Speaker 9: time highs. 119 00:05:53,360 --> 00:05:54,839 Speaker 8: There's no reason for them to rush it. 120 00:05:54,880 --> 00:05:56,840 Speaker 9: And the more the markets try to rush the FED 121 00:05:56,880 --> 00:05:59,080 Speaker 9: to cut, the more I think the FED should make 122 00:05:59,120 --> 00:05:59,640 Speaker 9: markets wait. 123 00:06:00,040 --> 00:06:02,559 Speaker 2: Numbers were getting indicate that the fourth quarter was probably 124 00:06:02,560 --> 00:06:04,560 Speaker 2: stronger in growth than a lot of people were anticipated. 125 00:06:04,560 --> 00:06:06,719 Speaker 2: As a product matter, what is driving this economy at 126 00:06:06,720 --> 00:06:09,280 Speaker 2: this point, because it is stronger than most people anticipated, 127 00:06:09,760 --> 00:06:11,360 Speaker 2: stronger than most of the rest of the world at 128 00:06:11,360 --> 00:06:12,000 Speaker 2: this point. 129 00:06:12,320 --> 00:06:15,440 Speaker 9: Well, the fourth quarter, still yet to fully be reported, 130 00:06:16,279 --> 00:06:20,279 Speaker 9: is slower than the third quarter, and we expect the 131 00:06:20,279 --> 00:06:23,039 Speaker 9: first quarter of this year to be even slower. So 132 00:06:23,080 --> 00:06:25,479 Speaker 9: there is a clear slowdown in the job creation on 133 00:06:25,520 --> 00:06:28,920 Speaker 9: the services side. On the consumption side, there is a slowdown, 134 00:06:29,240 --> 00:06:33,440 Speaker 9: but less slowly than anybody would have thought. Including nos, 135 00:06:34,800 --> 00:06:41,600 Speaker 9: consumption stay strong. Lifestyle is sticky. People have a powerful 136 00:06:41,680 --> 00:06:44,400 Speaker 9: we talk about pent up savings, but the wealth effect 137 00:06:44,920 --> 00:06:47,320 Speaker 9: that has come from the stock market, and maybe a 138 00:06:47,320 --> 00:06:49,680 Speaker 9: little bit of confidence that by the spring the housing 139 00:06:49,720 --> 00:06:54,480 Speaker 9: market starts to recover in terms of activity. People feel 140 00:06:54,520 --> 00:06:57,080 Speaker 9: really good about their balance sheets and they have their jobs. 141 00:06:57,200 --> 00:06:59,960 Speaker 2: Let's talk about the nineties. Are we're embarking on a 142 00:07:00,080 --> 00:07:01,880 Speaker 2: time like the nineties and ninety is pretty interesting? 143 00:07:02,240 --> 00:07:02,400 Speaker 3: Yeah. 144 00:07:02,400 --> 00:07:04,320 Speaker 9: At the start of twenty twenty four, I actually find 145 00:07:04,320 --> 00:07:07,680 Speaker 9: myself thinking about the nineteen nineties quite a bit. Some 146 00:07:07,760 --> 00:07:09,720 Speaker 9: are wondering if it's the end of nineteen nineties as 147 00:07:09,720 --> 00:07:12,040 Speaker 9: it was twenty twenty three like nineteen ninety nine, and 148 00:07:12,160 --> 00:07:14,560 Speaker 9: are we going to have a popping of a tech bubble. 149 00:07:15,840 --> 00:07:17,840 Speaker 9: I don't think so, but there's a rest The equity 150 00:07:17,880 --> 00:07:20,440 Speaker 9: market has some tough years. I had given the gains 151 00:07:20,480 --> 00:07:22,160 Speaker 9: of the past few years, and then if you go 152 00:07:22,200 --> 00:07:24,120 Speaker 9: the way back to the early the start of the 153 00:07:24,200 --> 00:07:27,960 Speaker 9: nineteen nineties, nineteen ninety there are some issues on the 154 00:07:27,960 --> 00:07:30,640 Speaker 9: table where inflation not as bad as we had recently, 155 00:07:30,680 --> 00:07:33,600 Speaker 9: but inflation was a problem Greenspan had to do something 156 00:07:33,600 --> 00:07:36,520 Speaker 9: about it in ninety four. But also the deficit was 157 00:07:36,560 --> 00:07:39,880 Speaker 9: a problem in the early nineties, and we have yet 158 00:07:39,880 --> 00:07:42,680 Speaker 9: to do anything about the deficit. And a lot of 159 00:07:42,680 --> 00:07:46,400 Speaker 9: people talk about nineteen ninety five being a good analogy 160 00:07:46,480 --> 00:07:49,240 Speaker 9: for this year because of the soft landing. That may 161 00:07:49,280 --> 00:07:52,360 Speaker 9: be the case, but we have an election this year, 162 00:07:52,440 --> 00:07:55,160 Speaker 9: we have a deficit to deal with, and we have 163 00:07:55,560 --> 00:07:58,560 Speaker 9: plenty of geopolitical concerns that are much more adverse than 164 00:07:58,560 --> 00:07:59,480 Speaker 9: the case in the nineties. 165 00:08:00,120 --> 00:08:01,960 Speaker 2: Call By in nineteen eighty five, we did have the 166 00:08:02,000 --> 00:08:03,920 Speaker 2: Carter tax plan that was starting to address on those 167 00:08:03,920 --> 00:08:04,720 Speaker 2: fiscal questions. 168 00:08:05,360 --> 00:08:06,640 Speaker 8: Clinton, Yeah, Clinton. 169 00:08:06,440 --> 00:08:11,360 Speaker 9: Yeah, Yeah, that's right. So Clinton, to his credit, and 170 00:08:11,400 --> 00:08:15,760 Speaker 9: don't forget, this was a big election issue in nineteen 171 00:08:15,800 --> 00:08:16,520 Speaker 9: ninety two. 172 00:08:17,440 --> 00:08:21,200 Speaker 8: The deficit, And in. 173 00:08:20,360 --> 00:08:24,280 Speaker 9: The middle of nineteen ninety three, Clinton with Congress passed 174 00:08:25,040 --> 00:08:27,640 Speaker 9: tax hikes that took effect in ninety three and played 175 00:08:27,640 --> 00:08:30,720 Speaker 9: off in nineteen ninety four fully and they put together 176 00:08:30,760 --> 00:08:33,959 Speaker 9: a plan to reduce the deficit over the nineteen nineties, 177 00:08:33,960 --> 00:08:36,200 Speaker 9: as they successfully did, and we went to surplus. And 178 00:08:36,280 --> 00:08:39,560 Speaker 9: then in nineteen ninety four, with the midterm elections and 179 00:08:39,600 --> 00:08:42,040 Speaker 9: the Republicans come into power, a lot more was done 180 00:08:42,080 --> 00:08:45,520 Speaker 9: to improve the fiscal situation and improve spending. 181 00:08:45,600 --> 00:08:47,240 Speaker 2: So, David, let's talk about how you're going to make 182 00:08:47,280 --> 00:08:49,280 Speaker 2: money the rest of this year. You've already said that 183 00:08:49,360 --> 00:08:52,880 Speaker 2: you think the evaluations are robust and big tech we 184 00:08:52,960 --> 00:08:54,640 Speaker 2: are there places you think that maybe they're not quite 185 00:08:54,640 --> 00:08:56,600 Speaker 2: as robust, maybe we're missing some things. 186 00:08:57,200 --> 00:08:59,000 Speaker 9: Well, I do scour over the equity market all the 187 00:08:59,000 --> 00:09:04,120 Speaker 9: time to find some the best opportunities. We store are 188 00:09:04,200 --> 00:09:07,959 Speaker 9: bullish on big banks. We see the best value at 189 00:09:07,960 --> 00:09:09,480 Speaker 9: the big banks in the US, and they're doing very 190 00:09:09,520 --> 00:09:12,479 Speaker 9: well the past several weeks as the recession fear. 191 00:09:14,040 --> 00:09:15,000 Speaker 8: As dissipated. 192 00:09:15,840 --> 00:09:20,160 Speaker 9: But I also like big biotech and pharmaceuticals because there 193 00:09:20,320 --> 00:09:24,719 Speaker 9: I see strong long term growth potential that is at 194 00:09:24,760 --> 00:09:30,439 Speaker 9: a very un demanding valuation right now. So tech companies, 195 00:09:30,559 --> 00:09:34,560 Speaker 9: they're great, but the valuations are so demanding that even 196 00:09:34,559 --> 00:09:36,640 Speaker 9: if these companies do wonderful things, they might not live 197 00:09:36,720 --> 00:09:40,199 Speaker 9: up to the expectations of investors, particularly over the short term. 198 00:09:40,679 --> 00:09:43,400 Speaker 9: And I'm looking for companies where there is that big 199 00:09:43,800 --> 00:09:48,079 Speaker 9: upside optionality that investors are not pricing. 200 00:09:48,360 --> 00:09:50,320 Speaker 8: We see that pharmaceuticals and biotech. 201 00:09:50,600 --> 00:09:53,160 Speaker 2: What about pharma schools. What's going on specifical with pharma schools? 202 00:09:53,160 --> 00:09:56,000 Speaker 2: So and for example, Pfizer's had a bit of a struggle, Yeah. 203 00:09:55,880 --> 00:09:58,040 Speaker 8: Yeah, Pfiser's definitely had a bit of a struggle. 204 00:09:58,080 --> 00:09:59,960 Speaker 9: And then on the opposite end you've got names like 205 00:10:00,400 --> 00:10:04,120 Speaker 9: Ela Lilly which are going gangbusters, and then everything in 206 00:10:04,160 --> 00:10:06,959 Speaker 9: between and then the companies are going through We've known 207 00:10:07,000 --> 00:10:11,200 Speaker 9: this a transition period from old on patent drugs to 208 00:10:11,360 --> 00:10:12,360 Speaker 9: the new pipeline. 209 00:10:12,440 --> 00:10:13,199 Speaker 8: It takes time. 210 00:10:13,960 --> 00:10:16,440 Speaker 9: You never know which in the pipeline is going to 211 00:10:16,440 --> 00:10:19,280 Speaker 9: be the hit and when. Like I said, the valuations 212 00:10:19,280 --> 00:10:21,120 Speaker 9: are really on demanding. Now we're going into an election 213 00:10:21,240 --> 00:10:23,760 Speaker 9: year and a lot of investors are shy to buy 214 00:10:24,400 --> 00:10:27,160 Speaker 9: healthcare stocks during an election year. I might be a 215 00:10:27,200 --> 00:10:30,880 Speaker 9: little bit cautious on some managed care prescription drug benefit managers, 216 00:10:30,920 --> 00:10:35,520 Speaker 9: but the innovators in the space, the medicine makers, this 217 00:10:35,600 --> 00:10:38,880 Speaker 9: is what we need, and I hope the policy makers 218 00:10:38,920 --> 00:10:40,400 Speaker 9: allow these companies. 219 00:10:39,920 --> 00:10:41,480 Speaker 8: To reach for the stars. 220 00:10:41,760 --> 00:10:43,760 Speaker 2: Thank you so much. Great to have you with us always, 221 00:10:43,800 --> 00:10:49,880 Speaker 2: as David Bianco of DWS. Coming up, we go over 222 00:10:49,920 --> 00:10:52,040 Speaker 2: those jobs numbers out at the end of the week 223 00:10:52,080 --> 00:10:56,600 Speaker 2: with our special contributor Larry Summers of Harvard. That's next 224 00:10:56,720 --> 00:10:58,319 Speaker 2: on Wall three Week on Bloomberg. 225 00:11:02,000 --> 00:11:06,200 Speaker 1: This is Bloomberg Wall Street Week with David Weston from 226 00:11:06,320 --> 00:11:09,080 Speaker 1: Bloomberg Radio. 227 00:11:14,080 --> 00:11:16,400 Speaker 2: This is Wall Street Week. I'm David Weston. We're now 228 00:11:16,480 --> 00:11:19,520 Speaker 2: joined by our special betur Larry Summers of Harvard's. So, Larry, 229 00:11:19,679 --> 00:11:21,920 Speaker 2: thank you so much for being with us. We got 230 00:11:21,920 --> 00:11:24,160 Speaker 2: those jobs numbers at the end of the week on Friday. 231 00:11:24,200 --> 00:11:26,440 Speaker 2: They were significally better than expecto. There were some down 232 00:11:27,040 --> 00:11:29,800 Speaker 2: revisions for the prior month. At the same time, IM 233 00:11:29,880 --> 00:11:31,560 Speaker 2: numbers came in a little softer. What do you make 234 00:11:31,600 --> 00:11:35,440 Speaker 2: of these jobs numbers and particularly perhaps the wage numbers, David. 235 00:11:35,080 --> 00:11:38,120 Speaker 3: Look, I think we're in the same kind of pattern 236 00:11:38,280 --> 00:11:44,000 Speaker 3: we've been in for us some time. As of right now, 237 00:11:44,080 --> 00:11:51,280 Speaker 3: the economy looks pretty strong and inflation looks relatively under control, 238 00:11:52,040 --> 00:11:55,040 Speaker 3: but there's a lot going on underneath the surface, and 239 00:11:55,120 --> 00:12:04,560 Speaker 3: there are still substantial risks with my three scenarios paradigm, 240 00:12:05,000 --> 00:12:10,439 Speaker 3: some risk of a downturn. We still keep not seeing 241 00:12:10,480 --> 00:12:16,040 Speaker 3: it at all in the employment numbers. In the data 242 00:12:16,080 --> 00:12:20,600 Speaker 3: on GDP, there's this big gap between total income and 243 00:12:20,679 --> 00:12:24,680 Speaker 3: total output that makes things hard to read, and there's 244 00:12:24,720 --> 00:12:28,400 Speaker 3: some worrying developments some of the business surveys like that 245 00:12:28,520 --> 00:12:34,760 Speaker 3: ism and in some of the credit data. So I 246 00:12:34,800 --> 00:12:37,840 Speaker 3: think it's possible that the economy will go into recession 247 00:12:38,000 --> 00:12:42,839 Speaker 3: in delayed response to monetary policy. That looks less likely 248 00:12:42,880 --> 00:12:46,640 Speaker 3: to me that I might have fought some months ago. 249 00:12:47,360 --> 00:12:52,079 Speaker 3: It's certainly increasingly possible that we'll have that much valuehooed 250 00:12:52,320 --> 00:12:57,800 Speaker 3: soft landing, as rare as those have been historically, and 251 00:12:57,840 --> 00:13:02,040 Speaker 3: I think there's a risk that people are still underestimating 252 00:13:02,760 --> 00:13:09,680 Speaker 3: given the very worrisome fiscal prospect of the country, given 253 00:13:09,720 --> 00:13:16,200 Speaker 3: the recent easing, quite substantial in financial conditions, given still 254 00:13:16,360 --> 00:13:20,640 Speaker 3: tight and the wage numbers again are not running right now, 255 00:13:21,000 --> 00:13:25,080 Speaker 3: today's number not running at a rate that's consistent with 256 00:13:25,320 --> 00:13:32,400 Speaker 3: the two percent inflation target, given the uncertainties in geopolitics 257 00:13:32,520 --> 00:13:38,160 Speaker 3: that could point the problems in supply chains. My gut 258 00:13:38,400 --> 00:13:44,800 Speaker 3: is still that the market is underestimating the inflation risks 259 00:13:44,880 --> 00:13:51,160 Speaker 3: in the current situation, and therefore probably overestimating the amount 260 00:13:51,280 --> 00:13:54,720 Speaker 3: of FED cutting that is going to take place. But 261 00:13:54,800 --> 00:13:57,679 Speaker 3: it's a fairly close call, and the FED is certainly 262 00:13:57,720 --> 00:14:05,680 Speaker 3: doing the right thing by being entirely vigilant and signaling 263 00:14:06,240 --> 00:14:12,000 Speaker 3: that it is very much going to be data dependent 264 00:14:15,160 --> 00:14:21,640 Speaker 3: going forward. Right here, I do read the continued strength 265 00:14:21,720 --> 00:14:27,120 Speaker 3: of the economy in the face of what's happened to rates, 266 00:14:27,960 --> 00:14:32,280 Speaker 3: as suggesting either that the neutral rate has risen substantially, 267 00:14:33,480 --> 00:14:38,280 Speaker 3: or as suggesting that the economy is less sensitive to 268 00:14:38,400 --> 00:14:42,600 Speaker 3: interest rates than we might have thought. Either one of 269 00:14:42,640 --> 00:14:48,240 Speaker 3: those considerations will suggest a bit less urgency to rate 270 00:14:48,320 --> 00:14:55,800 Speaker 3: cutting than many people suppose at the current moment. 271 00:14:56,200 --> 00:14:58,120 Speaker 2: Larry, we had a major development in something that you've 272 00:14:58,120 --> 00:15:00,720 Speaker 2: talked about in this program more than once, and that 273 00:15:01,000 --> 00:15:04,600 Speaker 2: is at Harvard, where you are a tenured professor, were 274 00:15:04,680 --> 00:15:07,400 Speaker 2: president there, but more generally at college campuses that we 275 00:15:07,440 --> 00:15:12,080 Speaker 2: saw the resignation of Cardinay from Harvard as president. I 276 00:15:12,160 --> 00:15:14,040 Speaker 2: wonder what you make of it, now that we're getting, 277 00:15:14,040 --> 00:15:17,160 Speaker 2: perhaps somewhat past the worst of the conflict, what are 278 00:15:17,160 --> 00:15:19,920 Speaker 2: the larger lessons we should learn, what can be done 279 00:15:19,960 --> 00:15:22,000 Speaker 2: in terms of reformation by the universities. 280 00:15:22,080 --> 00:15:27,600 Speaker 3: Otherwise, David, I think this is a time of testing 281 00:15:27,720 --> 00:15:34,680 Speaker 3: for universities, certainly unlike any other, certainly since the Vietnam 282 00:15:34,720 --> 00:15:40,160 Speaker 3: War period, and perhaps even going beyond that. Some of 283 00:15:40,200 --> 00:15:46,760 Speaker 3: our leading universities are under investigation, both from Republicans in 284 00:15:46,800 --> 00:15:53,880 Speaker 3: the House of Representatives and from the Education Department of 285 00:15:53,960 --> 00:15:59,200 Speaker 3: the Biden demonstration. Biden administration. You're seeing a degree of 286 00:16:00,360 --> 00:16:05,320 Speaker 3: divisiveness on campus I haven't seen since I first got 287 00:16:05,360 --> 00:16:13,520 Speaker 3: to the Harvard campus in nineteen seventy five. So I 288 00:16:13,560 --> 00:16:19,400 Speaker 3: think there's going to be a very profound challenge of 289 00:16:20,000 --> 00:16:28,880 Speaker 3: finding a vital center. Universities must stand up to some 290 00:16:29,040 --> 00:16:33,840 Speaker 3: of the vitriolic forces on the populist right that seem 291 00:16:33,920 --> 00:16:39,200 Speaker 3: to be in favor of everything up to book burning 292 00:16:39,880 --> 00:16:47,880 Speaker 3: in support of enforcing some very particular risk vision on universities. 293 00:16:48,760 --> 00:16:51,360 Speaker 3: At the same time, I don't think there's any question 294 00:16:52,160 --> 00:16:59,560 Speaker 3: that they have been threatened from within by stifling orthodoxies 295 00:17:00,120 --> 00:17:05,560 Speaker 3: have led to the cancelation of speakers that have led 296 00:17:05,720 --> 00:17:16,160 Speaker 3: to people being discomforted discomforted by discussing issues like crime, 297 00:17:16,600 --> 00:17:24,520 Speaker 3: like education except in particular prescribed ways. And it's going 298 00:17:24,600 --> 00:17:28,960 Speaker 3: to be the challenge of university leaders to find a 299 00:17:29,000 --> 00:17:37,080 Speaker 3: way between those twin abhorrent polls. I have to say 300 00:17:37,119 --> 00:17:44,600 Speaker 3: that this goes way beyond any individual. I think universities 301 00:17:44,680 --> 00:17:50,280 Speaker 3: have in many cases, including at Harvard, been failed by 302 00:17:50,320 --> 00:17:57,840 Speaker 3: their trustees. At Harvard we call the group the corporation, and. 303 00:17:57,800 --> 00:18:02,840 Speaker 10: In many ways it is their job above all to 304 00:18:02,960 --> 00:18:09,280 Speaker 10: maintain a healthy interface between the university and the broader society. 305 00:18:09,840 --> 00:18:12,040 Speaker 2: Larry, if we cast our minds back to November of 306 00:18:12,040 --> 00:18:15,480 Speaker 2: twenty sixteen, there were a lot of concerns about President 307 00:18:15,520 --> 00:18:17,880 Speaker 2: Trump when it became clear that he had been elected, 308 00:18:17,960 --> 00:18:20,119 Speaker 2: and in fact, you remember, the markets really went south, 309 00:18:20,400 --> 00:18:24,159 Speaker 2: very dramatically initially, but then they rebounded. And if you 310 00:18:24,240 --> 00:18:27,199 Speaker 2: look basically on the track record of the Trump presidency, 311 00:18:27,320 --> 00:18:29,679 Speaker 2: just from the point of view of investors as well 312 00:18:29,680 --> 00:18:33,000 Speaker 2: as the economy, it is not a terrible record. I 313 00:18:33,040 --> 00:18:34,680 Speaker 2: think it's fair to say. I mean, the markets did 314 00:18:34,720 --> 00:18:39,479 Speaker 2: reasonably well, there was employment created, there was a GDP growth. 315 00:18:39,800 --> 00:18:42,320 Speaker 2: So is it possible that we might overreact to the 316 00:18:42,359 --> 00:18:44,600 Speaker 2: possibility of a Trump two point zero? 317 00:18:45,359 --> 00:18:50,800 Speaker 3: You know, there's an old saying, fool me once, shame 318 00:18:50,840 --> 00:18:55,560 Speaker 3: on you. Fool me twice, shame on me. That's going 319 00:18:55,640 --> 00:18:57,480 Speaker 3: to be the way the rest of the world is 320 00:18:57,520 --> 00:19:01,040 Speaker 3: going to see it. The rest of the world, which 321 00:19:01,080 --> 00:19:05,600 Speaker 3: has had so much faith in the United States for 322 00:19:05,720 --> 00:19:10,720 Speaker 3: all their resentments, and so many have been so reliant 323 00:19:11,400 --> 00:19:16,480 Speaker 3: for so long, were prepared to see a first TERMP 324 00:19:16,680 --> 00:19:21,879 Speaker 3: term as an aberration. But after ninety one indictments, after 325 00:19:21,920 --> 00:19:27,680 Speaker 3: the events of January sixth, that is not how they 326 00:19:27,680 --> 00:19:31,439 Speaker 3: will see a second term that is not how they 327 00:19:31,480 --> 00:19:36,560 Speaker 3: will ever see America again. That will represent a loss 328 00:19:37,119 --> 00:19:41,440 Speaker 3: of the moral authority that the United States has had 329 00:19:42,000 --> 00:19:45,880 Speaker 3: since it won the Cold War, since it won the 330 00:19:45,920 --> 00:19:50,240 Speaker 3: Second World War, and that will, I think, make for 331 00:19:50,320 --> 00:19:53,240 Speaker 3: a much less stable world. 332 00:19:53,359 --> 00:19:56,000 Speaker 2: Okay, Larry, thank you very much for all those thoughts. 333 00:19:56,359 --> 00:19:58,200 Speaker 2: As our special contribute here on Wall Street Week, he 334 00:19:58,280 --> 00:20:02,800 Speaker 2: is Larry Summers of Harvard. Coming up, twenty twenty four 335 00:20:02,840 --> 00:20:05,280 Speaker 2: may just be the year when we figure out how 336 00:20:05,359 --> 00:20:08,640 Speaker 2: big generative AI could be. We'll talk with an economist 337 00:20:08,680 --> 00:20:11,400 Speaker 2: who's done early important work on what it could mean 338 00:20:11,440 --> 00:20:14,960 Speaker 2: for the labor market, David Otter of MIT. That's next 339 00:20:15,000 --> 00:20:16,680 Speaker 2: on Wall Street Week on Bloomberg. 340 00:20:18,040 --> 00:20:22,280 Speaker 1: This is Bloomberg Wall Street Week with David Weston from 341 00:20:22,400 --> 00:20:25,080 Speaker 1: Bloomberg Radio. 342 00:20:29,760 --> 00:20:32,240 Speaker 2: This is Wall Street Week. I'm David Weston. The new 343 00:20:32,320 --> 00:20:34,600 Speaker 2: year will bring with it a presidential election in the 344 00:20:34,720 --> 00:20:38,400 Speaker 2: United States with potentially very different approaches to the economy 345 00:20:38,440 --> 00:20:41,000 Speaker 2: weighing in the balance. Here on Wall Street Week, we're 346 00:20:41,000 --> 00:20:43,760 Speaker 2: going to cover the election by focusing specifically on what 347 00:20:43,920 --> 00:20:46,920 Speaker 2: it could mean for the economy and for investors. So 348 00:20:46,960 --> 00:20:50,720 Speaker 2: we ask Bloomberg International Economics and Policy courspondent Michael McKee 349 00:20:51,000 --> 00:20:53,520 Speaker 2: to start the conversation by laying out what we know 350 00:20:53,680 --> 00:20:56,560 Speaker 2: at this point about the approaches of the two front runners, 351 00:20:56,760 --> 00:20:59,119 Speaker 2: President Biden and former President Trump. 352 00:21:00,640 --> 00:21:04,000 Speaker 11: It's been thirty two years since political strategist James Carvel 353 00:21:04,160 --> 00:21:07,399 Speaker 11: hammered home the idea that when it comes to presidential elections, 354 00:21:07,920 --> 00:21:11,639 Speaker 11: it's the economy stupid. But in twenty twenty four, is 355 00:21:11,640 --> 00:21:15,680 Speaker 11: it entering this election year Compared with election year's past. 356 00:21:15,920 --> 00:21:19,720 Speaker 11: The economy is growing by around four percent, the most 357 00:21:19,880 --> 00:21:23,800 Speaker 11: since two thousand and three, With one exception. Unemployment is 358 00:21:23,840 --> 00:21:26,719 Speaker 11: the lowest it's been entering an election year since nineteen 359 00:21:26,800 --> 00:21:28,639 Speaker 11: sixty eight, when a lot of men were employed by 360 00:21:28,640 --> 00:21:31,840 Speaker 11: the US Army in Vietnam. The exception was twenty twenty, 361 00:21:32,000 --> 00:21:35,520 Speaker 11: when COVID doubled the jobless rate between January and election 362 00:21:35,640 --> 00:21:38,600 Speaker 11: day in November. Inflation is higher than any year since 363 00:21:38,720 --> 00:21:41,400 Speaker 11: two thousand and seven, but it's been cut in half 364 00:21:41,480 --> 00:21:43,840 Speaker 11: over the last twelve months and should be close to 365 00:21:43,840 --> 00:21:47,680 Speaker 11: the election year average by November by the carvill yardstick, 366 00:21:47,920 --> 00:21:51,240 Speaker 11: it's somewhat surprising that President Joe Biden isn't far ahead 367 00:21:51,280 --> 00:21:54,240 Speaker 11: in the polls. It may be that voters haven't shaken 368 00:21:54,280 --> 00:21:57,359 Speaker 11: off the COVID pandemic. Yet they're comparing the economy of 369 00:21:57,400 --> 00:22:00,399 Speaker 11: the past three years to where it was under Trump 370 00:22:00,400 --> 00:22:03,560 Speaker 11: in twenty nineteen, and they're not focused on what Trump 371 00:22:03,680 --> 00:22:08,919 Speaker 11: is promising. Draconian changes. He wants across the board tariff increases, 372 00:22:08,960 --> 00:22:13,480 Speaker 11: which would raise prices for just about everything, threatening inflation. 373 00:22:14,040 --> 00:22:18,000 Speaker 11: Remember when the US raises tariff's, Americans, not foreigners pay 374 00:22:18,000 --> 00:22:22,639 Speaker 11: the difference. Trump is talking about massive deportation of illegal aliens, 375 00:22:22,680 --> 00:22:26,280 Speaker 11: which would hit the labor market hard. On employment, particularly 376 00:22:26,320 --> 00:22:30,359 Speaker 11: in lower wage service sectors, would rise. He would renew 377 00:22:30,480 --> 00:22:34,680 Speaker 11: and expand tax cuts expiring in twenty twenty five, increasing 378 00:22:34,680 --> 00:22:37,840 Speaker 11: the deficit. The good news for President Biden is the 379 00:22:37,880 --> 00:22:42,160 Speaker 11: economic outlook remains bright. If inflation keeps falling, interest rates 380 00:22:42,200 --> 00:22:45,959 Speaker 11: are expected to follow, and that would stimulate faster growth 381 00:22:46,240 --> 00:22:50,679 Speaker 11: and higher stock prices. The Biden camp is betting people 382 00:22:50,800 --> 00:22:54,600 Speaker 11: will notice. The bad news is this year it may 383 00:22:54,640 --> 00:22:58,320 Speaker 11: not be the economy stupid and Wall Street may not care. 384 00:22:58,960 --> 00:23:00,920 Speaker 11: The S and P five hundre it rose twenty four 385 00:23:00,960 --> 00:23:04,520 Speaker 11: percent under Biden last year, but it rose twenty nine 386 00:23:04,640 --> 00:23:08,560 Speaker 11: percent under Trump in twenty nineteen, so this election may 387 00:23:08,600 --> 00:23:13,760 Speaker 11: turn not on pocketbook issues, but personalities. Not that personalities 388 00:23:13,800 --> 00:23:17,120 Speaker 11: are all bad. The nineteen ninety two election brought Larry 389 00:23:17,200 --> 00:23:18,640 Speaker 11: Summers into government. 390 00:23:19,440 --> 00:23:24,080 Speaker 2: David, the generative Artificial intelligence was one of the hottest 391 00:23:24,119 --> 00:23:26,840 Speaker 2: topics for investors in twenty twenty three and looks to 392 00:23:26,880 --> 00:23:29,240 Speaker 2: be the same in twenty twenty four. There's much we 393 00:23:29,359 --> 00:23:32,359 Speaker 2: don't know about what it could ultimately mean, including about 394 00:23:32,359 --> 00:23:34,960 Speaker 2: the effect on productivity and growth in the labor market. 395 00:23:35,200 --> 00:23:38,120 Speaker 2: David Otter, he is MIT Professor of Economics, has done 396 00:23:38,160 --> 00:23:41,240 Speaker 2: some of the earliest seminal work on this subject, and 397 00:23:41,240 --> 00:23:43,320 Speaker 2: we welcome now to Wall Street Week. So Professor, thanks 398 00:23:43,320 --> 00:23:45,000 Speaker 2: so much for being with us. As I say, it's 399 00:23:45,080 --> 00:23:47,679 Speaker 2: really early going and we don't know a lot. But 400 00:23:48,000 --> 00:23:50,840 Speaker 2: what do we think we might know about productivity and growth, 401 00:23:50,880 --> 00:23:53,320 Speaker 2: because that's what investors seem to be most interested in. 402 00:23:53,720 --> 00:23:56,600 Speaker 4: Thanks very much for inviting me. What you said is correct. 403 00:23:56,680 --> 00:23:59,359 Speaker 4: We don't know very much about the pro TV consequences. 404 00:24:00,040 --> 00:24:03,680 Speaker 4: It's easy to project enormous potential gains, but we would 405 00:24:03,680 --> 00:24:06,720 Speaker 4: have made the same projection about the computer era of 406 00:24:06,760 --> 00:24:08,800 Speaker 4: the last four years, and in fact growth has been 407 00:24:08,840 --> 00:24:12,800 Speaker 4: relatively disappointing, especially for the last fifteen years. So I 408 00:24:12,800 --> 00:24:16,240 Speaker 4: think there's enormous upside potential, but sometimes that potential doesn't 409 00:24:16,240 --> 00:24:19,439 Speaker 4: turn into reality, and you know, we will spend some 410 00:24:19,480 --> 00:24:21,920 Speaker 4: of the productivity of AI dealing with the problems that 411 00:24:22,000 --> 00:24:27,879 Speaker 4: AI creates, including hoscination, including vulnerabilities, cyber attacks, and so 412 00:24:28,359 --> 00:24:30,920 Speaker 4: part of that gain that so called you know, AI 413 00:24:30,960 --> 00:24:34,360 Speaker 4: dividend will actually be squandered on AI defense. 414 00:24:34,920 --> 00:24:37,360 Speaker 2: Talking about productivity and growth them is sort of talking 415 00:24:37,400 --> 00:24:39,560 Speaker 2: about whether the pie gets bigger overall? What about how 416 00:24:39,600 --> 00:24:42,359 Speaker 2: we divide up the pie that is distributionally, particularly in 417 00:24:42,400 --> 00:24:44,600 Speaker 2: the labor market, because you've done some work there based 418 00:24:44,640 --> 00:24:47,880 Speaker 2: on past history, but what we think might happen with jobs, 419 00:24:47,920 --> 00:24:50,119 Speaker 2: who gets better jobs, who gets worse jobs. 420 00:24:50,320 --> 00:24:53,240 Speaker 4: So the period we're concluding now, the computer era, the 421 00:24:53,240 --> 00:24:55,679 Speaker 4: traditional computer era, has been one of rising inequality, and 422 00:24:55,720 --> 00:24:57,399 Speaker 4: we think that computing has had a lot to do 423 00:24:57,480 --> 00:25:00,800 Speaker 4: with that because it's been very complementary to decision makers, 424 00:25:01,520 --> 00:25:04,520 Speaker 4: you know, to lawyers and doctors and marketers and people 425 00:25:04,560 --> 00:25:09,320 Speaker 4: who basically use information and analysis to make high stakes, 426 00:25:09,480 --> 00:25:12,560 Speaker 4: one off decisions. It's displaced a lot of workers from 427 00:25:12,600 --> 00:25:14,879 Speaker 4: production work, from office work, and sort of pushed them 428 00:25:14,880 --> 00:25:19,600 Speaker 4: down into less expert jobs in food service, cleaning, security, entertainment, recreation, 429 00:25:19,920 --> 00:25:23,440 Speaker 4: and those are socially valuable work, but it's paid poorly 430 00:25:23,840 --> 00:25:28,200 Speaker 4: because it doesn't require specialized expertise. And so computing, as 431 00:25:28,240 --> 00:25:31,720 Speaker 4: we understand it has actually not been that great for 432 00:25:31,800 --> 00:25:35,880 Speaker 4: growth and really created a lot of inquality. I think 433 00:25:35,920 --> 00:25:39,320 Speaker 4: AI has the potential to work quite quite differently. 434 00:25:39,880 --> 00:25:42,280 Speaker 2: As you talk, it sounds to me there's another distributional 435 00:25:42,320 --> 00:25:46,040 Speaker 2: potential effect here people, for example, receiving medical care, which 436 00:25:46,080 --> 00:25:49,000 Speaker 2: is far from equally divided in this country, and goodness 437 00:25:49,000 --> 00:25:51,399 Speaker 2: knows around the world. Is the potential that more people 438 00:25:51,400 --> 00:25:53,800 Speaker 2: will have access to better healthcare in the United States 439 00:25:53,840 --> 00:25:54,560 Speaker 2: and around the world. 440 00:25:54,800 --> 00:25:57,280 Speaker 4: It's a great question. So I do think there's a 441 00:25:57,280 --> 00:26:01,440 Speaker 4: lot of super expensive services that or expenses specifically because 442 00:26:01,480 --> 00:26:03,480 Speaker 4: they're provided by highly paid experts. So that would be 443 00:26:03,520 --> 00:26:05,719 Speaker 4: in education, that would be in healthcare, that would be 444 00:26:05,800 --> 00:26:08,120 Speaker 4: in architecture and design, that would be in software development, 445 00:26:08,440 --> 00:26:13,520 Speaker 4: and AI could make those things more accessible. I think 446 00:26:13,520 --> 00:26:17,600 Speaker 4: that's going to have that has potentially enormous benefits both 447 00:26:17,720 --> 00:26:20,879 Speaker 4: in rich industrialized countries like the United States and potentially 448 00:26:20,920 --> 00:26:23,000 Speaker 4: even more so in the developing world, where that type 449 00:26:23,000 --> 00:26:27,479 Speaker 4: of expertise is even more scarce. How we do that, 450 00:26:27,600 --> 00:26:30,120 Speaker 4: of course, depends a lot on our institutions, right, So 451 00:26:31,040 --> 00:26:34,600 Speaker 4: the good scenario is the price of medical care comes down, 452 00:26:34,600 --> 00:26:38,160 Speaker 4: it becomes more broadly available that we allocate it more efficiently. 453 00:26:38,359 --> 00:26:41,200 Speaker 4: The bad scenario is basically, if you're wealthy, you see 454 00:26:41,240 --> 00:26:43,399 Speaker 4: a highly paid doctor, and if you're not wealthy, you 455 00:26:43,440 --> 00:26:47,000 Speaker 4: see a machine. So we shouldn't count on the technology 456 00:26:47,040 --> 00:26:50,720 Speaker 4: to solve our problems for us. It opens possibilities, but 457 00:26:50,800 --> 00:26:53,520 Speaker 4: how we use them is really a societal choice. And 458 00:26:53,600 --> 00:26:55,480 Speaker 4: just to give you a very stark example of this, 459 00:26:55,600 --> 00:26:59,320 Speaker 4: you know, in the nineteen forties scientists figure out how 460 00:26:59,400 --> 00:27:04,480 Speaker 4: to harness controlled nuclear fission that has two really powerful uses. 461 00:27:04,840 --> 00:27:07,240 Speaker 4: One is for energy generation and the other is for 462 00:27:07,400 --> 00:27:11,240 Speaker 4: a nuclear weapons. North Korea is a country that has 463 00:27:11,400 --> 00:27:15,879 Speaker 4: lots and lots offensive nuclear weapons, but no nuclear power plants. Japan, 464 00:27:16,200 --> 00:27:19,560 Speaker 4: the only country against which offensive nuclear weapons has ever 465 00:27:19,600 --> 00:27:23,920 Speaker 4: been used, has no nuclear weapons and dozens of nuclear 466 00:27:23,920 --> 00:27:27,720 Speaker 4: power plants. So AI is a bit like nuclear energy, 467 00:27:27,760 --> 00:27:30,280 Speaker 4: but in some ways more powerful and certainly more applicable. 468 00:27:30,520 --> 00:27:33,199 Speaker 4: We can use it for really good things and for 469 00:27:33,359 --> 00:27:36,000 Speaker 4: really destructive things, and already both of those are current. 470 00:27:37,080 --> 00:27:38,879 Speaker 2: And finally, Professor, let's come back to where we started. 471 00:27:39,000 --> 00:27:41,879 Speaker 2: The uncertainty about AI right now, because one of the 472 00:27:41,880 --> 00:27:44,160 Speaker 2: things I've learned from you and from others is this 473 00:27:44,200 --> 00:27:46,760 Speaker 2: is not just a matter of degree, but perhaps of kind. 474 00:27:46,920 --> 00:27:49,879 Speaker 2: That is to say, basically, with automation, people who are 475 00:27:50,280 --> 00:27:52,399 Speaker 2: really expert in this know how it works. They know 476 00:27:52,400 --> 00:27:55,080 Speaker 2: what the rules are that the computers are following AI 477 00:27:55,240 --> 00:27:57,880 Speaker 2: generative AI, as I understand, we literally don't know how 478 00:27:57,920 --> 00:27:59,760 Speaker 2: it works and never will know how it works. It 479 00:27:59,760 --> 00:28:01,880 Speaker 2: does know how it works itself. What does that say 480 00:28:01,880 --> 00:28:04,200 Speaker 2: about our ability to predict where it's going and how 481 00:28:04,240 --> 00:28:04,880 Speaker 2: to manage it? 482 00:28:05,119 --> 00:28:08,120 Speaker 4: So your point is nexcellent one. Just to slightly clarify, 483 00:28:08,720 --> 00:28:11,439 Speaker 4: we understand, or you know, computer scientist understand mathematically what 484 00:28:11,440 --> 00:28:14,160 Speaker 4: it's doing. But in any given instance, it's like a child. 485 00:28:14,200 --> 00:28:16,919 Speaker 4: It's learned some lessons. What it will actually you know, 486 00:28:16,960 --> 00:28:18,600 Speaker 4: it's read some things and encounters some things. What will 487 00:28:18,600 --> 00:28:21,680 Speaker 4: actually do on any given occasion is extremely hard to predict. 488 00:28:21,800 --> 00:28:23,840 Speaker 4: You'd have to know everything it's ever been exposed to. 489 00:28:24,680 --> 00:28:27,840 Speaker 4: So that makes it actually a lot like human experts 490 00:28:27,840 --> 00:28:30,880 Speaker 4: in some ways, because we ourselves a unpredictable in the sense. 491 00:28:30,920 --> 00:28:33,520 Speaker 4: But it means that when we interact with AI, we 492 00:28:33,600 --> 00:28:37,320 Speaker 4: need to learn how to treat it not as authoritative 493 00:28:37,960 --> 00:28:41,720 Speaker 4: but as a guide or support to decision making, and 494 00:28:42,080 --> 00:28:43,680 Speaker 4: that's really critical a professor. 495 00:28:43,720 --> 00:28:46,480 Speaker 2: Does that necessarily lead to regulation, that is to say, 496 00:28:46,640 --> 00:28:50,080 Speaker 2: the government telling us when we should and shouldn't use 497 00:28:50,120 --> 00:28:52,200 Speaker 2: AI because we don't want to use it the wrong way? 498 00:28:52,640 --> 00:28:55,000 Speaker 4: I think it leads to a couple of types of regulation. 499 00:28:55,440 --> 00:28:58,200 Speaker 4: One of them is safety regulation. But we're actually pretty 500 00:28:58,240 --> 00:29:00,080 Speaker 4: good at that. You can't buy our toaster of and 501 00:29:00,160 --> 00:29:04,280 Speaker 4: that doesn't meet energy standards and fire proofness standards. And 502 00:29:04,320 --> 00:29:06,720 Speaker 4: so when we're using AI and specific applications like in 503 00:29:07,240 --> 00:29:11,360 Speaker 4: aircraft or in medicine or in cars, the government should 504 00:29:11,640 --> 00:29:14,720 Speaker 4: and I think will regulate that and so absolutely. But 505 00:29:14,760 --> 00:29:16,520 Speaker 4: there's two other forms of regulation that I think we 506 00:29:16,560 --> 00:29:21,120 Speaker 4: are much harder. One is AI you know desperately, you know, 507 00:29:21,320 --> 00:29:25,680 Speaker 4: chips away or let me say, but differently, AI really 508 00:29:25,720 --> 00:29:29,040 Speaker 4: threatens the foundation of our intellectual property system or our 509 00:29:29,080 --> 00:29:32,120 Speaker 4: copyright laws. They just weren't built in anticipation of machines 510 00:29:32,160 --> 00:29:35,400 Speaker 4: that would absorb and then memorize and not exactly reproduce 511 00:29:35,480 --> 00:29:38,920 Speaker 4: but pretty much replicate what's already there. So that's an issue, 512 00:29:38,960 --> 00:29:41,840 Speaker 4: and I really think there's a real threat to you know, 513 00:29:41,880 --> 00:29:45,520 Speaker 4: to newspapers to create, to illustrators, to artists, to actors. 514 00:29:46,080 --> 00:29:49,640 Speaker 4: That needs to be negotiated and set properly in law, 515 00:29:49,760 --> 00:29:52,360 Speaker 4: in bargaining. And we've already seen the screenwriters skill do that, 516 00:29:52,400 --> 00:29:55,160 Speaker 4: the actors skill do that. But that's only the very beginning. 517 00:29:55,200 --> 00:29:57,040 Speaker 2: Professor, Thank you so much for joining us on Wall Street. 518 00:29:57,080 --> 00:29:57,800 Speaker 1: MAK really appreciate. 519 00:29:57,960 --> 00:30:00,160 Speaker 2: That's David, author of MIT. 520 00:30:01,920 --> 00:30:02,440 Speaker 1: Coming up. 521 00:30:02,560 --> 00:30:04,560 Speaker 2: Why pay for the cow when you can get the 522 00:30:04,640 --> 00:30:10,520 Speaker 2: milk for free? Just ask Michigan coach Jim Harbaugh. That's 523 00:30:10,640 --> 00:30:12,560 Speaker 2: next down Wall Street Week on Bloomberg. 524 00:30:14,040 --> 00:30:18,240 Speaker 1: This is Bloomberg Wall Street Week with David Weston from 525 00:30:18,360 --> 00:30:21,040 Speaker 1: Bloomberg Radio. 526 00:30:25,760 --> 00:30:28,720 Speaker 2: Finally, one more thought. They say you get what you 527 00:30:28,840 --> 00:30:32,000 Speaker 2: pay for. According to Wikipedia, it's an expression of the 528 00:30:32,040 --> 00:30:35,240 Speaker 2: so called common law of business balance, though no one 529 00:30:35,280 --> 00:30:38,320 Speaker 2: seems to know exactly where it came from. One follower 530 00:30:38,360 --> 00:30:41,360 Speaker 2: of this supposed rule of business balance is Warren Buffett, 531 00:30:41,600 --> 00:30:44,479 Speaker 2: at least after his partner Charlie Munger persuaded him it 532 00:30:44,520 --> 00:30:46,360 Speaker 2: was better to pay a fair price for a great 533 00:30:46,360 --> 00:30:48,800 Speaker 2: company than to pay a great price. For just a 534 00:30:48,800 --> 00:30:52,360 Speaker 2: fair company, and his Messrs Buffett and Munger proved paying 535 00:30:52,440 --> 00:30:55,280 Speaker 2: up for great assets and talent most of the time 536 00:30:55,600 --> 00:30:57,960 Speaker 2: is the way to go, like for those who stepped 537 00:30:58,000 --> 00:31:00,160 Speaker 2: up in twenty twenty three and paid full price for 538 00:31:00,200 --> 00:31:03,760 Speaker 2: big tech stocks when others were insisting they were overvalued. 539 00:31:04,160 --> 00:31:06,960 Speaker 2: As we know, in the end, the Magnificent seven proved 540 00:31:06,960 --> 00:31:10,240 Speaker 2: to be worth every penny, at least in twenty twenty three. 541 00:31:10,440 --> 00:31:12,520 Speaker 4: I think a lot of these names have a lot 542 00:31:12,520 --> 00:31:13,520 Speaker 4: of growth in. 543 00:31:13,440 --> 00:31:14,920 Speaker 9: Them over the long term. 544 00:31:15,120 --> 00:31:19,320 Speaker 12: However, in the short term profit taking happens, it's good 545 00:31:19,320 --> 00:31:21,320 Speaker 12: to lock in some of those great returns that we 546 00:31:21,360 --> 00:31:22,880 Speaker 12: saw in twenty twenty three. 547 00:31:23,320 --> 00:31:25,520 Speaker 2: And one of the big tech companies that certainly got 548 00:31:25,600 --> 00:31:28,560 Speaker 2: what it paid for was Microsoft with its thirteen billion 549 00:31:28,600 --> 00:31:32,000 Speaker 2: dollar investment in open Ai, which despite a bit of 550 00:31:32,040 --> 00:31:34,880 Speaker 2: trouble along the way, is now valued at something like 551 00:31:34,960 --> 00:31:38,480 Speaker 2: one hundred billion dollars. We continue to be committed to 552 00:31:38,520 --> 00:31:41,240 Speaker 2: open Ai, and we continue to be committed to Sam 553 00:31:41,280 --> 00:31:43,960 Speaker 2: and Greg and the team, or in respect your where 554 00:31:44,000 --> 00:31:46,920 Speaker 2: they are. Hollywood writers did their best last year to 555 00:31:46,960 --> 00:31:49,920 Speaker 2: show us all that if we want their best creative output, 556 00:31:50,040 --> 00:31:52,960 Speaker 2: the students will have to pay full value, and in 557 00:31:53,000 --> 00:31:54,720 Speaker 2: the end they made their point. 558 00:31:55,000 --> 00:31:56,960 Speaker 3: This deal is the very best deal that could be 559 00:31:57,040 --> 00:31:59,960 Speaker 3: negotiated at this time, even with the use of all 560 00:32:00,040 --> 00:32:02,440 Speaker 3: the leverage that we generated from having a strike for 561 00:32:02,480 --> 00:32:03,880 Speaker 3: one hundred and eighteen days. 562 00:32:04,000 --> 00:32:06,719 Speaker 2: And while we were in Hollywood, Warner Brothers didn't scrimp 563 00:32:06,760 --> 00:32:09,400 Speaker 2: when it put together the Barbie Movie, as the budget 564 00:32:09,440 --> 00:32:12,640 Speaker 2: ballooned to one hundred and forty five million dollars and 565 00:32:12,680 --> 00:32:15,320 Speaker 2: it certainly got what it paid for and then some, 566 00:32:15,720 --> 00:32:18,760 Speaker 2: with global box office receipts somewhere north of one point 567 00:32:18,800 --> 00:32:22,920 Speaker 2: four billion dollars. Of course, paying top dollar doesn't always 568 00:32:22,960 --> 00:32:26,400 Speaker 2: guarantee you'll make money on the deal. Just ask Elon Musk, 569 00:32:26,440 --> 00:32:29,520 Speaker 2: who paid forty four billion dollars for Twitter, renamed it 570 00:32:29,840 --> 00:32:32,760 Speaker 2: X and now admits it's worth about half that. While 571 00:32:32,800 --> 00:32:35,640 Speaker 2: others think he may be optimistic. 572 00:32:35,280 --> 00:32:39,120 Speaker 7: We've just seen a huge erasure of value from X 573 00:32:39,160 --> 00:32:40,120 Speaker 7: since Elon took over. 574 00:32:40,600 --> 00:32:43,160 Speaker 2: And at this point it's far from certain whether Steve 575 00:32:43,200 --> 00:32:45,680 Speaker 2: Cohen will get his money's worth from the Mets, what 576 00:32:45,800 --> 00:32:48,000 Speaker 2: with a two point four billion dollar price to egg, 577 00:32:48,120 --> 00:32:50,960 Speaker 2: the hundreds of millions he's committed to the largest payroll 578 00:32:51,120 --> 00:32:53,719 Speaker 2: in Major League Baseball and his plan to put another 579 00:32:53,800 --> 00:32:57,880 Speaker 2: eight billion dollars into developing fifty acres around City Field. 580 00:32:58,280 --> 00:33:00,920 Speaker 2: Now it's the Los Angeles Dodgers, and to hope their 581 00:33:00,960 --> 00:33:04,320 Speaker 2: new star pitcher, Shohei Otani will be worth their record 582 00:33:04,440 --> 00:33:07,440 Speaker 2: seven hundred million dollars, they've promised to pay him, Which 583 00:33:07,480 --> 00:33:10,360 Speaker 2: takes us to the one place left, at least in sports, 584 00:33:10,400 --> 00:33:13,040 Speaker 2: where you can have a multi billion dollar business and 585 00:33:13,200 --> 00:33:16,520 Speaker 2: effectively not pay at all for those doing the real work. 586 00:33:16,880 --> 00:33:20,720 Speaker 2: College football, where players give their all throughout the fall 587 00:33:20,840 --> 00:33:24,960 Speaker 2: every Saturday, risking life and limb for exactly zero pay, 588 00:33:25,560 --> 00:33:29,600 Speaker 2: something that Michigan coach Jim Harbaugh says has to change. 589 00:33:29,800 --> 00:33:38,480 Speaker 12: What I don't understand is how the NCAA television networks, conferences, universities, 590 00:33:39,160 --> 00:33:43,400 Speaker 12: and coaches can continue to pull in millions and in 591 00:33:43,440 --> 00:33:48,120 Speaker 12: some cases billions of dollars in revenue off the efforts 592 00:33:48,200 --> 00:33:53,000 Speaker 12: of college student athletes across the country without providing enough 593 00:33:53,000 --> 00:33:56,560 Speaker 12: opportunity to share in the ever increase in revenues. 594 00:33:56,960 --> 00:34:00,400 Speaker 2: Now, let's see whether Hawballs players win that national champceanship 595 00:34:00,400 --> 00:34:04,560 Speaker 2: on Monday, even without pay Go Blue. That does it. 596 00:34:04,600 --> 00:34:06,760 Speaker 2: For this episode of Wall Street Week, I'm David Weston 597 00:34:06,920 --> 00:34:07,640 Speaker 2: see you next week.