WEBVTT - One Big Beautiful Bill, Wine Tariffs, Wearable Technology, Monetary Policy & AI

0:00:02.720 --> 0:00:07.240
<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news.

0:00:20.320 --> 0:00:23.400
<v Speaker 2>This is Wall Street Week. I'm David Western, bringing you

0:00:23.520 --> 0:00:27.480
<v Speaker 2>stories of capitalism, the wine industry, brace us for another

0:00:27.640 --> 0:00:30.640
<v Speaker 2>round of tariffs on imports to the United States, Why

0:00:30.800 --> 0:00:36.000
<v Speaker 2>being a domestic producer won't necessarily help, and artificial intelligence

0:00:36.040 --> 0:00:39.320
<v Speaker 2>could change the fundamentals of our economy and give central

0:00:39.320 --> 0:00:43.159
<v Speaker 2>banks new tools to monitor and manage it. Plus the

0:00:43.240 --> 0:00:47.279
<v Speaker 2>growing business of wellness wearables and whether they really can

0:00:47.440 --> 0:00:51.400
<v Speaker 2>help us live longer, healthier lives. But we start with

0:00:51.440 --> 0:00:54.880
<v Speaker 2>the profound changes President Trump is bringing or promising to

0:00:54.920 --> 0:00:57.840
<v Speaker 2>bring to us all from the one big, beautiful bill

0:00:58.080 --> 0:01:01.720
<v Speaker 2>to more tariffs. He says, our only day, we welcome

0:01:01.760 --> 0:01:04.320
<v Speaker 2>back our special contributor Larry Summers to tell us what

0:01:04.400 --> 0:01:07.080
<v Speaker 2>is likely to have long lasting effects.

0:01:09.120 --> 0:01:12.199
<v Speaker 3>David, it has to be recognized that it's a big

0:01:12.280 --> 0:01:17.360
<v Speaker 3>legislative accomplishment. It's a larger bill passed sooner than other

0:01:17.440 --> 0:01:21.040
<v Speaker 3>presidents have achieved. But I don't think it's going to

0:01:21.120 --> 0:01:24.000
<v Speaker 3>take the country in the right direction. I think it's

0:01:24.080 --> 0:01:29.160
<v Speaker 3>going to grow our budget deficits in the future very substantially.

0:01:29.240 --> 0:01:34.200
<v Speaker 3>And you're already seeing some market reaction to that. And

0:01:34.240 --> 0:01:37.760
<v Speaker 3>I think that what it does to our social safety

0:01:37.800 --> 0:01:42.680
<v Speaker 3>net is really going to be devastating relative to the

0:01:42.720 --> 0:01:45.639
<v Speaker 3>path the country would have been on if you look

0:01:46.160 --> 0:01:48.320
<v Speaker 3>at cutbacks.

0:01:47.680 --> 0:01:49.240
<v Speaker 4>In the social safety net.

0:01:49.320 --> 0:01:53.680
<v Speaker 3>There were cutbacks in the welfare reform bill that was

0:01:53.760 --> 0:01:58.000
<v Speaker 3>passed during Bill Clinton's presidency. There were cutbacks made by

0:01:58.400 --> 0:02:02.880
<v Speaker 3>President Reagan and his original tax and budget legislation. This

0:02:02.960 --> 0:02:07.200
<v Speaker 3>is the largest cutback in the social safety net that

0:02:07.480 --> 0:02:14.440
<v Speaker 3>anybody has been able to find, and it's coming at

0:02:14.480 --> 0:02:18.480
<v Speaker 3>a time when we appear to be on our trajectory

0:02:19.080 --> 0:02:26.320
<v Speaker 3>to massive cutbacks in spending on scientific research, massive cutbacks

0:02:26.320 --> 0:02:35.040
<v Speaker 3>in support for the arts and humanities, maximum cutbacks in

0:02:35.720 --> 0:02:41.480
<v Speaker 3>support for foreign assistance programs, including ones on which large

0:02:41.560 --> 0:02:45.959
<v Speaker 3>numbers of Aige patients in Africa are dependent for their

0:02:46.440 --> 0:02:53.880
<v Speaker 3>life saving medicines. So this is legislation that, to my mind,

0:02:54.440 --> 0:02:59.080
<v Speaker 3>both compromises our capacity to defend ourselves as a country

0:02:59.200 --> 0:03:04.520
<v Speaker 3>because of all of the debt, and frankly compromises what

0:03:04.600 --> 0:03:08.520
<v Speaker 3>makes our country worth defending in terms of being a

0:03:08.600 --> 0:03:12.399
<v Speaker 3>humane force in terms of the world, in terms of

0:03:12.480 --> 0:03:18.000
<v Speaker 3>our sense of national community and protecting everybody, in terms

0:03:18.120 --> 0:03:22.320
<v Speaker 3>of some of our greatest contributions to humanity in both

0:03:22.360 --> 0:03:27.919
<v Speaker 3>the sciences and the arts, and so I think this

0:03:28.000 --> 0:03:34.320
<v Speaker 3>is a very troubling piece of legislation in ways that

0:03:34.480 --> 0:03:38.200
<v Speaker 3>go beyond the problematic immediate economics.

0:03:38.560 --> 0:03:41.000
<v Speaker 2>This one big, beautiful bill is one part of a

0:03:41.040 --> 0:03:44.240
<v Speaker 2>more sweeping plan that President Trump has for I think

0:03:44.280 --> 0:03:47.720
<v Speaker 2>it's fair to say really redoing the American economy. And

0:03:47.840 --> 0:03:50.960
<v Speaker 2>yet we don't see much reaction yet from the economy

0:03:51.000 --> 0:03:52.920
<v Speaker 2>in the numbers. And I'll give you an example in

0:03:53.000 --> 0:03:54.840
<v Speaker 2>the tariffs. A lot of talk about tariffs, a lot

0:03:54.840 --> 0:03:57.120
<v Speaker 2>of fear about tariffs, and yet if you look at

0:03:57.120 --> 0:04:00.200
<v Speaker 2>the CPI numbers, the PPI numbers are coming out, they

0:04:00.240 --> 0:04:03.080
<v Speaker 2>don't indicate the inflation that most economists predicted.

0:04:03.520 --> 0:04:06.320
<v Speaker 4>I think it's early days.

0:04:07.280 --> 0:04:10.520
<v Speaker 3>It may be that there are a set of other

0:04:10.680 --> 0:04:18.080
<v Speaker 3>developments going on through artificial intelligence, through technology that are

0:04:18.600 --> 0:04:24.719
<v Speaker 3>exerting a deflationary force. It may be that people, given

0:04:24.880 --> 0:04:29.440
<v Speaker 3>all the huge uncertainties about tariffs, are waiting to see

0:04:29.480 --> 0:04:35.160
<v Speaker 3>how it shakes out before they establish their new price structures.

0:04:35.800 --> 0:04:39.919
<v Speaker 3>It may be that for a time it's possible for

0:04:40.000 --> 0:04:44.720
<v Speaker 3>the people in the middle to eat the tariff increases

0:04:44.880 --> 0:04:50.320
<v Speaker 3>in order to try to get market share. I agree,

0:04:50.400 --> 0:04:54.760
<v Speaker 3>I agree with you, David, I would have expected more inflation,

0:04:55.040 --> 0:04:58.320
<v Speaker 3>and what you have always have to do as an

0:04:58.360 --> 0:05:03.400
<v Speaker 3>economist is watch the data and be prepared to change

0:05:03.400 --> 0:05:07.600
<v Speaker 3>your mind. But for now, I think that I wouldn't

0:05:07.600 --> 0:05:11.160
<v Speaker 3>want to rush to a judgment that these tariffs are

0:05:11.160 --> 0:05:17.120
<v Speaker 3>innocuous for inflation. I think the more likely thing is

0:05:17.320 --> 0:05:20.320
<v Speaker 3>that they're going to be somewhat more delayed.

0:05:21.360 --> 0:05:23.520
<v Speaker 4>In their impact.

0:05:24.040 --> 0:05:29.800
<v Speaker 3>Certainly, there have been many careful studies that compared the

0:05:29.839 --> 0:05:32.920
<v Speaker 3>sectors that were tarifted and the sectors that were not

0:05:33.120 --> 0:05:37.640
<v Speaker 3>tariffed during the president's first term and found the tariffs

0:05:37.640 --> 0:05:44.320
<v Speaker 3>did translate into higher prices. So I would rather wait

0:05:44.360 --> 0:05:48.600
<v Speaker 3>and see on this. I think that's the approach that

0:05:48.640 --> 0:05:53.760
<v Speaker 3>the Felleral Reserve is taking, and I think, frankly that

0:05:54.000 --> 0:05:56.200
<v Speaker 3>is the right approach.

0:05:56.400 --> 0:05:59.040
<v Speaker 2>I mean, we've really seen a move up in the

0:05:59.080 --> 0:06:03.120
<v Speaker 2>thirty year yield. We're above five percent relatively constantly. Now

0:06:03.279 --> 0:06:05.479
<v Speaker 2>there are some who are concerned about exactly what that's

0:06:05.560 --> 0:06:08.800
<v Speaker 2>telling us about inflation expectations and term premium.

0:06:08.880 --> 0:06:11.440
<v Speaker 4>David. You know, I look at the.

0:06:13.040 --> 0:06:16.760
<v Speaker 3>Ten year market relative to the twenty year or thirty

0:06:16.839 --> 0:06:22.360
<v Speaker 3>year market as a sign of where the markets see

0:06:23.040 --> 0:06:26.400
<v Speaker 3>very long term rates going over the very long term

0:06:26.480 --> 0:06:31.920
<v Speaker 3>what market participants call the forward rate, and we now

0:06:32.040 --> 0:06:37.479
<v Speaker 3>have forward rates on regular bonds that are well above

0:06:38.600 --> 0:06:44.760
<v Speaker 3>five percent, and forward rates on tips on bonds linked

0:06:44.839 --> 0:06:49.200
<v Speaker 3>to inflation that are well above three percent. And those

0:06:49.240 --> 0:06:55.839
<v Speaker 3>are ominous indicators about our nation's credibility over the medium term.

0:06:56.240 --> 0:07:00.280
<v Speaker 3>They're ominous indicators with respect to the government's ability.

0:07:00.440 --> 0:07:04.480
<v Speaker 4>To issue long term debt.

0:07:04.680 --> 0:07:10.680
<v Speaker 3>They're ominous indicators with respect to the deficit because if

0:07:10.720 --> 0:07:15.000
<v Speaker 3>you look at the projections people quote from the Congressional

0:07:15.000 --> 0:07:19.880
<v Speaker 3>Budget Office from other places, they're building in much lower

0:07:20.320 --> 0:07:24.160
<v Speaker 3>interest rate assumptions. So I think if you look at

0:07:24.240 --> 0:07:28.640
<v Speaker 3>what's happened to bond markets, if you look at what's

0:07:28.680 --> 0:07:32.920
<v Speaker 3>happened to the dollar, you have to view our nation's

0:07:32.960 --> 0:07:40.240
<v Speaker 3>fiscal situation with considerable trepidation and concern.

0:07:40.520 --> 0:07:43.560
<v Speaker 2>While the government grapples with all that debt it's taking on,

0:07:43.800 --> 0:07:47.080
<v Speaker 2>consumers and small businesses have their own responses to Trump

0:07:47.120 --> 0:07:50.920
<v Speaker 2>administration policies, as Bank of America Chairman and CEO Brian

0:07:50.960 --> 0:07:52.920
<v Speaker 2>moynihan explained.

0:07:53.240 --> 0:07:55.760
<v Speaker 5>So if you look on the consumer side, and our

0:07:55.920 --> 0:07:59.320
<v Speaker 5>seventy million consumers who engage with the economy every day

0:07:59.600 --> 0:08:03.000
<v Speaker 5>and through their accounts and in their it's spend the

0:08:03.080 --> 0:08:06.560
<v Speaker 5>cash and everything about four trillion, five trillion dollars a year.

0:08:07.160 --> 0:08:10.440
<v Speaker 5>That grew up four percent plus the second quarter twenty

0:08:10.440 --> 0:08:13.000
<v Speaker 5>five or the second course of twenty four. So they

0:08:13.200 --> 0:08:15.440
<v Speaker 5>because they're employed and because wage growth, and that's not

0:08:15.640 --> 0:08:19.000
<v Speaker 5>every single consumer, it's but in the large, in the main,

0:08:19.400 --> 0:08:22.600
<v Speaker 5>they are continuing to grow and spend more and that

0:08:22.800 --> 0:08:25.600
<v Speaker 5>helps the economy. And so you're seeing in some of

0:08:25.600 --> 0:08:29.320
<v Speaker 5>the moderate income households there's a little bit of cheff

0:08:29.520 --> 0:08:31.800
<v Speaker 5>moving around to different things. You're seeing people trade from

0:08:31.800 --> 0:08:35.480
<v Speaker 5>wanting another less planes, more cruises earlier, that's leveling out now,

0:08:35.559 --> 0:08:37.680
<v Speaker 5>a lot more going to movies because the movies are good.

0:08:37.920 --> 0:08:40.680
<v Speaker 5>But the end of the day, they're spending discretion necessary

0:08:40.679 --> 0:08:44.040
<v Speaker 5>about the same percentage they traditionally spent. They've got money

0:08:44.080 --> 0:08:46.839
<v Speaker 5>in the accounts, they're employed, and the wage growth has

0:08:46.880 --> 0:08:50.120
<v Speaker 5>been relatively strong, and you know, so they're pretty good shape.

0:08:50.120 --> 0:08:52.680
<v Speaker 5>The credit quality is good. They have equity in their homes,

0:08:53.080 --> 0:08:56.280
<v Speaker 5>they're rate financing the mortgage, so consert is pretty good.

0:08:56.280 --> 0:08:57.959
<v Speaker 5>When you go to small businesses, that's more of the

0:08:58.040 --> 0:09:01.240
<v Speaker 5>question small medium sized businesses, because is the interest rate

0:09:01.320 --> 0:09:04.640
<v Speaker 5>environment hits them harder because they borrow on lines of

0:09:04.640 --> 0:09:07.160
<v Speaker 5>credit short term for a lot of their activities, and

0:09:07.240 --> 0:09:10.559
<v Speaker 5>that rate went up substantially. And anythink about the if

0:09:10.559 --> 0:09:12.600
<v Speaker 5>I'm one hundred million dollar company, a fifty million dollar

0:09:12.640 --> 0:09:14.920
<v Speaker 5>company here in North Carolina, and I'm engaging in the

0:09:14.920 --> 0:09:20.120
<v Speaker 5>world finance, I'm importing goods and manufacturing them, further manufacturing,

0:09:20.120 --> 0:09:22.679
<v Speaker 5>I'm selling them. You know, it got pretty interesting here

0:09:22.720 --> 0:09:24.559
<v Speaker 5>trying to figure out all the trade and terriffs. So

0:09:24.600 --> 0:09:26.920
<v Speaker 5>I think the certainly on the tax rate helps them,

0:09:27.520 --> 0:09:29.920
<v Speaker 5>meaning the big beautiful bill passing and the tax rate,

0:09:30.040 --> 0:09:31.800
<v Speaker 5>that's a very good thing. The alternative would have not

0:09:31.840 --> 0:09:35.400
<v Speaker 5>been good if their tax rates would change. A satisfactory

0:09:35.400 --> 0:09:38.640
<v Speaker 5>resolution to the trade so that they could learn the

0:09:38.679 --> 0:09:40.480
<v Speaker 5>rules of the road over the next thirty sixty ninety

0:09:40.559 --> 0:09:42.960
<v Speaker 5>days and get their plans for next year put together.

0:09:43.320 --> 0:09:46.120
<v Speaker 5>And I think ultimately they're going We've got the satisfactory

0:09:46.120 --> 0:09:49.040
<v Speaker 5>resolution on immigration and population growth. Because the end the day,

0:09:49.240 --> 0:09:52.920
<v Speaker 5>when I'm hearing more from the construction companies, farming companies,

0:09:53.280 --> 0:09:56.600
<v Speaker 5>and travel entertainment type companies, is I'm starting to worry

0:09:56.600 --> 0:10:01.400
<v Speaker 5>about I'm starting to struggle with labor availability and that's

0:10:02.160 --> 0:10:04.079
<v Speaker 5>that we got to make sure they have the workers

0:10:04.120 --> 0:10:09.199
<v Speaker 5>because they will supply great service economy continue to grow up.

0:10:09.240 --> 0:10:12.280
<v Speaker 2>Next, we've been hearing about those tariffs coming our way

0:10:12.360 --> 0:10:15.360
<v Speaker 2>since President Trump returned to office, But where will it

0:10:15.440 --> 0:10:18.680
<v Speaker 2>really affect us in our daily lives? It turns out

0:10:18.880 --> 0:10:21.440
<v Speaker 2>that those of us who drink wine could be on

0:10:21.520 --> 0:10:22.400
<v Speaker 2>the front lines.

0:10:23.720 --> 0:10:25.920
<v Speaker 6>Where you going to find champagne? Where are you going

0:10:25.920 --> 0:10:28.600
<v Speaker 6>to find shout enough to pop? Where you're going to

0:10:28.600 --> 0:10:30.720
<v Speaker 6>find kyanti? You're not going to find it in Oregon

0:10:30.800 --> 0:10:37.360
<v Speaker 6>or California.

0:10:41.080 --> 0:10:44.880
<v Speaker 2>This is a story about bottled poetry. That's what Robert

0:10:44.960 --> 0:10:47.920
<v Speaker 2>Lewis Stevenson called wine, and it's something that many of

0:10:48.000 --> 0:10:51.320
<v Speaker 2>us enjoy regularly, but also something that may be a

0:10:51.360 --> 0:10:54.160
<v Speaker 2>good deal harder to get a hold of if President

0:10:54.160 --> 0:10:57.199
<v Speaker 2>Trump follows through with the tariff threats he's made against

0:10:57.240 --> 0:10:58.199
<v Speaker 2>the European Union.

0:11:00.120 --> 0:11:03.040
<v Speaker 7>We've been taking advantage for many, many years by god.

0:11:02.880 --> 0:11:06.600
<v Speaker 8>Be's vote quote friend in voe, and frankly, the friends

0:11:06.640 --> 0:11:08.520
<v Speaker 8>have been worse than the bos in renegages.

0:11:09.600 --> 0:11:12.560
<v Speaker 2>A new deadline and a new threat. The US could

0:11:12.559 --> 0:11:15.440
<v Speaker 2>impose a thirty percent tariff on imported wine from the

0:11:15.480 --> 0:11:19.320
<v Speaker 2>European Union if no deal is struck by August first,

0:11:19.840 --> 0:11:21.080
<v Speaker 2>we have worked.

0:11:20.720 --> 0:11:23.640
<v Speaker 9>And now are ready to respond with countermeasures.

0:11:23.720 --> 0:11:25.480
<v Speaker 4>It's been a mess.

0:11:26.240 --> 0:11:30.040
<v Speaker 2>In New York, importer Victor Schwartz has spent nearly forty

0:11:30.160 --> 0:11:33.880
<v Speaker 2>years supplying restaurants and wine shops with hand picked bottles

0:11:33.920 --> 0:11:38.800
<v Speaker 2>from small European vineyards. Now tariffs threaten to upend the business.

0:11:39.440 --> 0:11:41.880
<v Speaker 6>That was ten percent, and they threatened fifty percent.

0:11:42.160 --> 0:11:44.040
<v Speaker 2>How different is the effect on your business of a

0:11:44.080 --> 0:11:45.040
<v Speaker 2>twenty versus a ten.

0:11:45.559 --> 0:11:48.600
<v Speaker 6>I mean, in our industry, end of the day, we

0:11:48.720 --> 0:11:52.840
<v Speaker 6>might make five percent as a net profit, five to

0:11:52.880 --> 0:11:56.720
<v Speaker 6>ten percent, So obviously we can't afford ten percent. We

0:11:56.760 --> 0:12:00.920
<v Speaker 6>can't afford twenty percent. But twenty percent is really egregious.

0:12:01.720 --> 0:12:05.679
<v Speaker 6>Twenty percent, I mean, think about what that does. God,

0:12:05.720 --> 0:12:08.400
<v Speaker 6>you know it makes a twenty dollars wine, you know,

0:12:08.480 --> 0:12:11.160
<v Speaker 6>twenty five dollars basically, because you know, there's kind of

0:12:11.160 --> 0:12:13.800
<v Speaker 6>a multiplier effect as it goes through the system. You know,

0:12:13.960 --> 0:12:16.840
<v Speaker 6>it's it's a much bigger impact. And don't forget when

0:12:16.880 --> 0:12:20.440
<v Speaker 6>when we raise a price, it's not as if the

0:12:21.160 --> 0:12:23.280
<v Speaker 6>consumer just accepts it.

0:12:23.640 --> 0:12:27.160
<v Speaker 2>Where do American customers for wine go if they decide

0:12:27.160 --> 0:12:29.320
<v Speaker 2>the price is too high. I'm not going to buy that.

0:12:29.880 --> 0:12:32.120
<v Speaker 6>Where you're going to find champagne, where you're going to

0:12:32.160 --> 0:12:35.360
<v Speaker 6>find shot enough to pop, where you're gonna find Kyanti,

0:12:35.480 --> 0:12:37.599
<v Speaker 6>You're not going to find it in Oregon or California.

0:12:37.760 --> 0:12:40.960
<v Speaker 6>A Finger Lakes wine, let's just be clear, is nothing

0:12:41.080 --> 0:12:45.559
<v Speaker 6>like a Napa Valley wine, nothing like a wine from

0:12:45.640 --> 0:12:49.440
<v Speaker 6>southern Italy or northern Italy or the center of Spain,

0:12:49.520 --> 0:12:53.480
<v Speaker 6>et cetera. My gist is is that these products are

0:12:53.520 --> 0:12:57.800
<v Speaker 6>so connected to their place, and that's what's wonderful and

0:12:57.840 --> 0:13:01.360
<v Speaker 6>interesting about wine. Otherwise, to be the wine company of

0:13:01.400 --> 0:13:03.840
<v Speaker 6>the world and it will come out of a spigot,

0:13:04.600 --> 0:13:08.880
<v Speaker 6>red white rose and sparkling done right. But that's not

0:13:08.920 --> 0:13:10.880
<v Speaker 6>why we love wine.

0:13:11.280 --> 0:13:15.040
<v Speaker 2>And Americans do love their wine. In twenty twenty three,

0:13:15.200 --> 0:13:18.560
<v Speaker 2>we consumed just under nine hundred million gallons of it,

0:13:18.920 --> 0:13:21.640
<v Speaker 2>more than any other country in the world, with a

0:13:21.720 --> 0:13:25.640
<v Speaker 2>value of over one hundred and seven billion dollars. More

0:13:25.679 --> 0:13:28.480
<v Speaker 2>than a third of that is shipped in from abroad,

0:13:28.480 --> 0:13:32.360
<v Speaker 2>making tariffs a real issue for importers, but those in

0:13:32.400 --> 0:13:35.079
<v Speaker 2>the business say it's not just the imports that will

0:13:35.120 --> 0:13:40.520
<v Speaker 2>be hit, it's the entire wine ecosystem. Quartan Ben Anif

0:13:40.720 --> 0:13:44.120
<v Speaker 2>is president of the US Wine Trade Alliance. He has

0:13:44.120 --> 0:13:47.760
<v Speaker 2>a shop in Tribeca that sells fine wine, which typically

0:13:47.800 --> 0:13:50.000
<v Speaker 2>goes for over twenty dollars per bottle.

0:13:51.679 --> 0:13:54.840
<v Speaker 10>Distributors and importers, even those by the way, that represent

0:13:55.120 --> 0:13:59.120
<v Speaker 10>US domestic wines about seventy five percent of their revenue

0:13:59.120 --> 0:14:03.320
<v Speaker 10>comes from wine. So that's one of the really interesting

0:14:03.360 --> 0:14:06.840
<v Speaker 10>things about this on the tariffront, all of the major

0:14:06.880 --> 0:14:11.160
<v Speaker 10>domestic wine producing organizations, from Wine Institute to NAPA Valley

0:14:11.200 --> 0:14:14.400
<v Speaker 10>mint Ners to Wine America, they're all against tariffs on

0:14:14.440 --> 0:14:20.680
<v Speaker 10>imported wine because they understand their domestic growers. Their producers

0:14:21.280 --> 0:14:24.640
<v Speaker 10>rely on healthy wine distributors for access to market.

0:14:25.520 --> 0:14:29.480
<v Speaker 2>Put another way, because state laws prevent domestic vineyards from

0:14:29.520 --> 0:14:34.280
<v Speaker 2>supplying restaurants and wine shops, they need distributors, and the

0:14:34.320 --> 0:14:39.160
<v Speaker 2>distributors rely critically on selling imports alongside their domestic wines.

0:14:40.000 --> 0:14:43.560
<v Speaker 2>That's why those who import fine wines like Victor Schwartz,

0:14:43.720 --> 0:14:46.200
<v Speaker 2>and those who sell it to US like Ben Anniff,

0:14:46.640 --> 0:14:49.800
<v Speaker 2>have no doubt that tariffs will cripple their business selling

0:14:49.840 --> 0:14:53.360
<v Speaker 2>both foreign and domestic wines. But there's another part of

0:14:53.400 --> 0:14:57.280
<v Speaker 2>the business, the value wine business, where a bottle or

0:14:57.320 --> 0:15:02.840
<v Speaker 2>its equivalent typically costs less than a LIE, and producers

0:15:02.880 --> 0:15:06.600
<v Speaker 2>for this segment, like Stuart Spencer in California's Central Valley,

0:15:07.040 --> 0:15:10.560
<v Speaker 2>say they need protection from multinational companies bringing in cheap,

0:15:10.920 --> 0:15:15.240
<v Speaker 2>subsidized imports that force American growers out of business.

0:15:16.440 --> 0:15:18.760
<v Speaker 7>There is a lot of what we call bulk wine

0:15:18.800 --> 0:15:21.840
<v Speaker 7>coming in in these big twenty foot bladder containers, and

0:15:21.880 --> 0:15:24.000
<v Speaker 7>it is this bulk wine that is really undercut in

0:15:24.040 --> 0:15:25.280
<v Speaker 7>California grapegrowers.

0:15:26.120 --> 0:15:28.640
<v Speaker 2>There's a lot of talk about the difference between free

0:15:28.640 --> 0:15:33.080
<v Speaker 2>trade and fair trade. From your experience as a grower,

0:15:33.120 --> 0:15:37.120
<v Speaker 2>but also from your dealing with Lodi, there are unfairnesses

0:15:37.280 --> 0:15:39.040
<v Speaker 2>in some of the exports to the United States.

0:15:40.080 --> 0:15:42.600
<v Speaker 7>I mean it's a completely unfair market. I mean we

0:15:42.640 --> 0:15:46.400
<v Speaker 7>are competing in a global marketplace. The European Union spends

0:15:46.440 --> 0:15:49.240
<v Speaker 7>you know, over two billion year between EU money and

0:15:49.880 --> 0:15:53.960
<v Speaker 7>member state money propping up their wine sector. They are

0:15:54.000 --> 0:15:58.240
<v Speaker 7>not only paying growers to inventnors to distill access wine

0:15:58.280 --> 0:15:59.920
<v Speaker 7>and buy it up, but they're also paying them to

0:16:00.040 --> 0:16:02.760
<v Speaker 7>plant new vineyards. And they spend hundreds of millions of

0:16:02.760 --> 0:16:05.200
<v Speaker 7>dollars in market promotion all around the world. And the

0:16:05.280 --> 0:16:08.320
<v Speaker 7>US is the number one target market. They also have

0:16:08.440 --> 0:16:11.520
<v Speaker 7>trade barriers, so it gets really complex when you get

0:16:11.560 --> 0:16:13.360
<v Speaker 7>in the weeds. But we are not playing on a

0:16:13.440 --> 0:16:14.320
<v Speaker 7>level field.

0:16:14.560 --> 0:16:18.360
<v Speaker 2>Last year, California wineries, which make nearly ninety percent of

0:16:18.440 --> 0:16:21.800
<v Speaker 2>US wine, we're stuck with more than five hundred thousand

0:16:21.920 --> 0:16:26.200
<v Speaker 2>excess tons of grapes. Now seventy seven million gallons of

0:16:26.240 --> 0:16:28.800
<v Speaker 2>wine are sitting in storage tanks.

0:16:28.520 --> 0:16:30.400
<v Speaker 7>And you can still see some of the grapes on

0:16:30.480 --> 0:16:33.720
<v Speaker 7>the vines. We have thousands of acres of grapes that

0:16:33.760 --> 0:16:36.840
<v Speaker 7>are being torn out right now, and we have small

0:16:36.880 --> 0:16:39.600
<v Speaker 7>farms and family businesses that are up for sale because

0:16:39.640 --> 0:16:43.400
<v Speaker 7>there's just not a prospect for them moving forward. My

0:16:43.480 --> 0:16:45.320
<v Speaker 7>family's been in this for fifty years, and I talked

0:16:45.320 --> 0:16:47.640
<v Speaker 7>to old timers that been in it for multi generations,

0:16:47.640 --> 0:16:49.800
<v Speaker 7>and they've never seen it as challenging as we are.

0:16:49.920 --> 0:16:50.160
<v Speaker 8>Now.

0:16:50.760 --> 0:16:53.120
<v Speaker 7>Seventy percent of all wine sales in this country is

0:16:53.160 --> 0:16:56.280
<v Speaker 7>controlled by about a handful of five to six large

0:16:56.360 --> 0:17:00.960
<v Speaker 7>multinational companies. They're bringing wine in bulk, blending it in

0:17:01.000 --> 0:17:04.320
<v Speaker 7>with California wine up to twenty five percent and calling

0:17:04.359 --> 0:17:08.440
<v Speaker 7>American appellation it's a federal loophole. We have, you know,

0:17:08.880 --> 0:17:11.679
<v Speaker 7>millions of gallons filled up in tanks right now in

0:17:11.680 --> 0:17:15.000
<v Speaker 7>California that don't have a home. But simultaneously, twenty four

0:17:15.000 --> 0:17:18.119
<v Speaker 7>million gallons of bulk wine is poured into California, coming

0:17:18.160 --> 0:17:21.399
<v Speaker 7>in at super low prices and undercutting the California grapegrower.

0:17:21.880 --> 0:17:24.800
<v Speaker 2>Are you in favor of the tariffs the President Trump

0:17:24.840 --> 0:17:25.919
<v Speaker 2>is talking about.

0:17:25.720 --> 0:17:27.959
<v Speaker 7>Well, I think if I was to speak to our

0:17:28.080 --> 0:17:30.880
<v Speaker 7>seven hundred grape growers that I represent, I think many

0:17:30.880 --> 0:17:33.240
<v Speaker 7>of them would support the tariffs to help level the

0:17:33.280 --> 0:17:35.960
<v Speaker 7>playing field. And I think what we would really hope

0:17:36.080 --> 0:17:39.040
<v Speaker 7>is that would bring these other trading partners to the

0:17:39.080 --> 0:17:42.480
<v Speaker 7>table to negotiate fair trade. The challenge we see with

0:17:42.520 --> 0:17:44.760
<v Speaker 7>what's going on with a lot of the trade negotiations

0:17:44.800 --> 0:17:47.360
<v Speaker 7>now is wine is just upon in a larger story

0:17:47.680 --> 0:17:50.160
<v Speaker 7>and the issues are about bigger issues. But I think

0:17:50.240 --> 0:17:52.639
<v Speaker 7>none of us, you know, want to see tariffs in

0:17:52.800 --> 0:17:55.360
<v Speaker 7>place permanently. I think what we really want to see

0:17:55.440 --> 0:17:56.800
<v Speaker 7>is really free and fair trade.

0:17:57.960 --> 0:18:02.920
<v Speaker 2>Some domestic producers kicking californ or complain about unfairness from

0:18:03.040 --> 0:18:08.480
<v Speaker 2>Europe because there are subsidies given to vineyards over in Europe.

0:18:09.119 --> 0:18:11.320
<v Speaker 2>Are tariff's an effective way to deal with that problem?

0:18:11.680 --> 0:18:14.240
<v Speaker 10>I feel really, really really bad for those guys. But

0:18:14.400 --> 0:18:16.560
<v Speaker 10>a tariff is not going to solve their problem. Farmers

0:18:16.600 --> 0:18:19.920
<v Speaker 10>that grow grapes to sell until, for instance, grocery store

0:18:19.960 --> 0:18:24.000
<v Speaker 10>boxed wine, and that's terrific for them. It's a great

0:18:24.000 --> 0:18:28.040
<v Speaker 10>product for certain customers. The demand for those products is collapsing.

0:18:28.560 --> 0:18:31.239
<v Speaker 10>You know, people aren't buying bulk wine the way they

0:18:31.280 --> 0:18:31.520
<v Speaker 10>used to.

0:18:33.840 --> 0:18:37.000
<v Speaker 2>Whether tariffs could give some relief to bulk wine producers

0:18:37.119 --> 0:18:40.600
<v Speaker 2>or not, they certainly would have unintended effects on the

0:18:40.640 --> 0:18:44.440
<v Speaker 2>American economy overall. You have spent some of your time

0:18:44.480 --> 0:18:48.960
<v Speaker 2>down in Washington trying to explain to lawmakers policymakers exactly

0:18:48.960 --> 0:18:52.280
<v Speaker 2>what this would mean for the wine business. What would

0:18:52.359 --> 0:18:54.720
<v Speaker 2>you want them to understand that maybe they don't understand

0:18:54.800 --> 0:18:57.200
<v Speaker 2>right now about the business and the effects of tariffs.

0:18:57.480 --> 0:19:01.000
<v Speaker 10>The United States has been talking about their concerns with

0:19:01.040 --> 0:19:04.960
<v Speaker 10>respect to a trade deficit. We import more European wines

0:19:05.080 --> 0:19:07.879
<v Speaker 10>than we sell American wines Europe. But the reality is

0:19:08.080 --> 0:19:11.879
<v Speaker 10>we have a huge economic surplus on the sale of

0:19:11.920 --> 0:19:15.119
<v Speaker 10>European wines in the United States. You know, we import

0:19:15.160 --> 0:19:18.400
<v Speaker 10>about five point three billion dollars worth of wine from

0:19:18.400 --> 0:19:23.159
<v Speaker 10>the European Union into the United States. But American businesses

0:19:23.240 --> 0:19:27.560
<v Speaker 10>make almost twenty three billion dollars from the sale of

0:19:27.560 --> 0:19:31.920
<v Speaker 10>those products, making a big margin on wine. For a restaurant,

0:19:31.960 --> 0:19:35.760
<v Speaker 10>it is not a luxury, it is an absolute necessity

0:19:35.920 --> 0:19:37.520
<v Speaker 10>for their very survival.

0:19:37.760 --> 0:19:41.439
<v Speaker 2>If in fact, tariff's do get imposed, what are the

0:19:41.920 --> 0:19:44.439
<v Speaker 2>likely long term effects in the wine business?

0:19:44.560 --> 0:19:48.879
<v Speaker 10>Contraction? And then you know what that means. Contraction means

0:19:49.920 --> 0:19:53.280
<v Speaker 10>American businesses closing and firing all their employees.

0:19:53.480 --> 0:19:56.800
<v Speaker 2>What about the uncertainty itself quite apart from the tariffs.

0:19:57.040 --> 0:19:59.800
<v Speaker 10>I mean, I'll tell you I had phone calls from

0:20:00.320 --> 0:20:03.800
<v Speaker 10>you know, wine distributors who said, you know, my grandfather

0:20:03.960 --> 0:20:07.920
<v Speaker 10>started this business. We were in terrific shape and growing

0:20:07.960 --> 0:20:11.800
<v Speaker 10>and hiring in January, and now I might have to

0:20:11.840 --> 0:20:14.719
<v Speaker 10>decide if I'm going to close the doors in two weeks.

0:20:15.080 --> 0:20:18.360
<v Speaker 10>You know, when they're they're put into this position when

0:20:18.359 --> 0:20:21.159
<v Speaker 10>their choice is either to pay a tariff that they

0:20:21.160 --> 0:20:25.040
<v Speaker 10>cannot afford because these these are small businesses, or don't

0:20:25.040 --> 0:20:28.080
<v Speaker 10>bring in wine. Don't bring in the wine that represents

0:20:28.600 --> 0:20:31.040
<v Speaker 10>seventy five percent of the revenue for your next three

0:20:31.119 --> 0:20:33.440
<v Speaker 10>or six months. You know, we had restaurants from South

0:20:33.440 --> 0:20:37.520
<v Speaker 10>Florida say, in the summertime, we need sancer and rose.

0:20:37.920 --> 0:20:41.280
<v Speaker 10>That's what keeps our businesses alive. And there really is

0:20:41.920 --> 0:20:44.080
<v Speaker 10>no substitute for these products.

0:20:43.840 --> 0:20:45.160
<v Speaker 6>And one of our favorite.

0:20:45.760 --> 0:20:49.199
<v Speaker 2>So in your wine store you have Bordeaux. If you

0:20:49.240 --> 0:20:52.120
<v Speaker 2>can't get the Bordeaux, will the customer say that's okay,

0:20:52.160 --> 0:20:52.880
<v Speaker 2>I'll take the cab.

0:20:53.280 --> 0:20:54.400
<v Speaker 10>The answer, flat lay is.

0:20:54.359 --> 0:20:56.520
<v Speaker 6>Now we talk about terror.

0:20:56.560 --> 0:20:56.760
<v Speaker 4>War.

0:20:57.480 --> 0:20:59.879
<v Speaker 6>It's a word that gets bandied about. It sounds fan

0:21:00.000 --> 0:21:02.359
<v Speaker 6>and see it's forign, but it really well, it means

0:21:02.680 --> 0:21:05.920
<v Speaker 6>terrowar land terror and it just means the place, right,

0:21:05.960 --> 0:21:10.680
<v Speaker 6>it's just geography. Part of terrawar is the human element,

0:21:10.960 --> 0:21:14.160
<v Speaker 6>the culture, the civilization, the people, the people who've been

0:21:14.320 --> 0:21:19.040
<v Speaker 6>on this piece of land in southern Italy for multiple generations.

0:21:19.240 --> 0:21:22.359
<v Speaker 6>They cook certain kinds of food, they make certain kinds

0:21:22.400 --> 0:21:25.960
<v Speaker 6>of wine that go with those foods. And it's very specific, right,

0:21:26.240 --> 0:21:28.960
<v Speaker 6>I mean, don't you love to drink an Italian wine

0:21:28.960 --> 0:21:31.199
<v Speaker 6>when you're having your spaghetti and meat sauce.

0:21:32.160 --> 0:21:35.040
<v Speaker 2>Schwartz is trying to hold off the administration as the

0:21:35.119 --> 0:21:38.760
<v Speaker 2>lead plaintiff in a lawsuit challenging the tariffs. The US

0:21:38.840 --> 0:21:42.119
<v Speaker 2>Court of International Trade ruled in his favor, but the

0:21:42.160 --> 0:21:45.280
<v Speaker 2>appeals Court stayed the injunction to give itself time to

0:21:45.320 --> 0:21:49.280
<v Speaker 2>hear the case. If the tariff's going to effect four

0:21:49.440 --> 0:21:54.040
<v Speaker 2>European wines August one, how long will it take before

0:21:54.119 --> 0:21:55.320
<v Speaker 2>we see it in our lives.

0:21:56.440 --> 0:21:58.879
<v Speaker 10>I think you'll start to see it pretty quickly. You know,

0:22:00.320 --> 0:22:03.919
<v Speaker 10>the first tariffed wines only have only now started to

0:22:03.960 --> 0:22:07.600
<v Speaker 10>come in, so distributors have still been selling through some

0:22:07.880 --> 0:22:09.880
<v Speaker 10>wines that didn't have tariffs on them. You're gonna start

0:22:09.880 --> 0:22:12.119
<v Speaker 10>seeing those prices come now. You're gonna start seeing a

0:22:12.160 --> 0:22:14.800
<v Speaker 10>lot less choice. You know, there are importers and distributors

0:22:14.880 --> 0:22:17.320
<v Speaker 10>that have halted all of their shipments because they're not

0:22:17.320 --> 0:22:19.280
<v Speaker 10>sure they can afford to bring them in now. At

0:22:19.320 --> 0:22:22.760
<v Speaker 10>the same time, they have no substitutes for them. They're

0:22:22.760 --> 0:22:25.920
<v Speaker 10>not buying more domestic wine, for instance, they can't afford

0:22:25.960 --> 0:22:28.280
<v Speaker 10>to they need to sell these European wines in order

0:22:28.280 --> 0:22:31.600
<v Speaker 10>to buy more American wine. In a nutshell, American businesses

0:22:31.760 --> 0:22:34.879
<v Speaker 10>are incredibly good at selling European wine and they support

0:22:35.000 --> 0:22:36.840
<v Speaker 10>huge numbers of jobs in the United States. So some

0:22:36.920 --> 0:22:39.520
<v Speaker 10>of the most famous importers actually got into the business

0:22:39.840 --> 0:22:42.920
<v Speaker 10>because they were in France or Italy during World War two,

0:22:42.960 --> 0:22:45.080
<v Speaker 10>said oh my god, I love this. This is what

0:22:45.160 --> 0:22:47.920
<v Speaker 10>I do want to do with my life, and their

0:22:47.960 --> 0:22:51.920
<v Speaker 10>classic American entrepreneurial success stories. As a matter of fact,

0:22:52.040 --> 0:22:54.719
<v Speaker 10>many of the most famous European wines in the world.

0:22:55.240 --> 0:23:00.800
<v Speaker 10>They're famous today because they were discovered by American wine

0:22:59.840 --> 0:23:03.639
<v Speaker 10>and they were brought back. They tasted ten thousand wines,

0:23:03.680 --> 0:23:05.720
<v Speaker 10>said these three are the best, and they were right.

0:23:06.040 --> 0:23:07.879
<v Speaker 10>Funny story. One of the first guys to do that,

0:23:07.880 --> 0:23:09.879
<v Speaker 10>by the way, was Thomas Jefferson. You know, he went

0:23:09.920 --> 0:23:13.320
<v Speaker 10>to Burgundy. He bought Mohersche and Mahrsokudor for he and

0:23:13.359 --> 0:23:15.760
<v Speaker 10>George Washington. He bought Chateau de Kem for he and

0:23:15.760 --> 0:23:17.680
<v Speaker 10>George Washington, and today those are still some of the

0:23:17.720 --> 0:23:20.040
<v Speaker 10>greatest wines on the planet. He had a pretty good paltte,

0:23:20.040 --> 0:23:20.280
<v Speaker 10>I think.

0:23:21.000 --> 0:23:25.840
<v Speaker 2>And now, ironically American's affinity for European wines, nurtured by

0:23:25.840 --> 0:23:29.440
<v Speaker 2>the likes of George Washington and Thomas Jefferson, may be

0:23:29.640 --> 0:23:33.359
<v Speaker 2>challenged by the most recent occupant of their high office

0:23:34.200 --> 0:23:36.679
<v Speaker 2>and perhaps make it more difficult for us to enjoy

0:23:36.720 --> 0:23:40.640
<v Speaker 2>that bottled poetry they discovered two hundred and fifty years

0:23:40.640 --> 0:23:48.639
<v Speaker 2>ago in Fine French wines up next. From our wrists

0:23:48.720 --> 0:23:51.840
<v Speaker 2>to our fingers, everyone seems to be wearing some device

0:23:51.920 --> 0:23:55.240
<v Speaker 2>to monitor how healthy our habits are. We visit the

0:23:55.320 --> 0:24:10.160
<v Speaker 2>wonderful world of Whoop to see what's really possible. This

0:24:10.280 --> 0:24:13.879
<v Speaker 2>is a story about the Fountain of Youth. Since long

0:24:13.960 --> 0:24:17.520
<v Speaker 2>before Ponce de Leon supposedly got lost looking for it

0:24:17.560 --> 0:24:21.199
<v Speaker 2>in the swamps of Florida in fifteen thirteen, humans have

0:24:21.280 --> 0:24:23.920
<v Speaker 2>been on a quest for a longer and healthier life,

0:24:24.359 --> 0:24:27.919
<v Speaker 2>leading to everything from exercise regimens to diet crazes to

0:24:27.960 --> 0:24:32.200
<v Speaker 2>weight loss drugs. Now, as in everything else, big tech

0:24:32.480 --> 0:24:35.679
<v Speaker 2>is in the game. But our elaborate wellness device is

0:24:35.760 --> 0:24:39.080
<v Speaker 2>really worth it? Or does the path longevity boil down

0:24:39.119 --> 0:24:41.919
<v Speaker 2>to just a few fundamental principles.

0:24:44.200 --> 0:24:47.400
<v Speaker 8>Wearable technology and the sensors that we have today will

0:24:47.440 --> 0:24:49.879
<v Speaker 8>continue to unlock new capabilities.

0:24:50.400 --> 0:24:53.359
<v Speaker 11>Eventually we will write a point where we can really

0:24:53.400 --> 0:24:58.480
<v Speaker 11>monitor our processes and intervene early on before a disease

0:24:58.520 --> 0:24:59.160
<v Speaker 11>could develop.

0:25:00.200 --> 0:25:02.639
<v Speaker 9>Something on your body. It starts to say a lot

0:25:02.680 --> 0:25:03.480
<v Speaker 9>about who you are.

0:25:05.320 --> 0:25:09.040
<v Speaker 1>We think that wearables are a key to the MAHA

0:25:09.080 --> 0:25:12.600
<v Speaker 1>agenda making America healthy again, and we are going to

0:25:13.080 --> 0:25:16.399
<v Speaker 1>My vision is at every American and is wearing a

0:25:16.400 --> 0:25:17.919
<v Speaker 1>wearable within four years.

0:25:18.800 --> 0:25:22.440
<v Speaker 2>Health and Human Services Secretary Robert F. Kennedy Junior's goal

0:25:22.640 --> 0:25:26.959
<v Speaker 2>might seem ambitious, but the market for global wellness wearables

0:25:27.200 --> 0:25:31.359
<v Speaker 2>is on the rise. Data firm IDC expects global revenues

0:25:31.359 --> 0:25:34.199
<v Speaker 2>to grow from sixty three billion dollars last year to

0:25:34.320 --> 0:25:37.560
<v Speaker 2>nearly seventy eight billion dollars by twenty twenty nine.

0:25:38.200 --> 0:25:42.000
<v Speaker 12>With wearable technology, you need to build something that's either

0:25:42.119 --> 0:25:43.920
<v Speaker 12>cool or invisible.

0:25:43.359 --> 0:25:44.200
<v Speaker 9>We like to say.

0:25:44.960 --> 0:25:48.280
<v Speaker 2>Will Ahmed is the founder and CEO of Whoop, one

0:25:48.280 --> 0:25:51.680
<v Speaker 2>of the major players in the wellness wearable field. As

0:25:51.720 --> 0:25:54.600
<v Speaker 2>of its last funding round in twenty twenty one, it

0:25:54.720 --> 0:25:58.399
<v Speaker 2>was valued at three point six billion dollars. Will first

0:25:58.440 --> 0:26:01.040
<v Speaker 2>came up with the idea during his time as captain

0:26:01.160 --> 0:26:02.639
<v Speaker 2>of Harvard's squash team.

0:26:03.440 --> 0:26:07.920
<v Speaker 12>Who builds wearable technology that's really designed to improve performance

0:26:08.000 --> 0:26:10.720
<v Speaker 12>and health. The company was founded out of the Harvard

0:26:10.720 --> 0:26:14.600
<v Speaker 12>Innovation Lab twelve years ago. We started with the world's

0:26:14.680 --> 0:26:19.360
<v Speaker 12>best athletes, where we were really designing high performance technology

0:26:19.440 --> 0:26:21.600
<v Speaker 12>to replace what at the time was a lot of

0:26:21.640 --> 0:26:26.360
<v Speaker 12>medical technology. An electrocardiogram, a PSG machine, the gold standard

0:26:26.359 --> 0:26:30.320
<v Speaker 12>for sleep, a chest strap, which measures heart rate during exercise.

0:26:30.720 --> 0:26:34.800
<v Speaker 12>This is the original prototype that was built in twenty twelve.

0:26:35.080 --> 0:26:38.280
<v Speaker 12>Now it looks ridiculous in a million ways, but it

0:26:38.320 --> 0:26:42.080
<v Speaker 12>could measure this thing called heart rate variability from the wrist,

0:26:42.320 --> 0:26:45.840
<v Speaker 12>which was a breakthrough. We wanted to take these sophisticated

0:26:45.880 --> 0:26:49.399
<v Speaker 12>but antiquated pieces of technology and put them in a

0:26:49.480 --> 0:26:52.800
<v Speaker 12>much smaller form factor, and the business has really evolved

0:26:53.440 --> 0:26:57.640
<v Speaker 12>quite beautifully from being a very high performance athletic product

0:26:58.000 --> 0:27:01.320
<v Speaker 12>to now being a tool that many people are using

0:27:01.600 --> 0:27:02.399
<v Speaker 12>to live longer.

0:27:02.960 --> 0:27:06.800
<v Speaker 2>While wellness wearables today are heavily focused on new technology

0:27:06.840 --> 0:27:09.480
<v Speaker 2>that can measure heart health, it was more than one

0:27:09.560 --> 0:27:12.720
<v Speaker 2>hundred years ago when the idea for the pedometer was

0:27:12.760 --> 0:27:16.240
<v Speaker 2>first patented. Poehler raised the stakes in the eighties with

0:27:16.280 --> 0:27:19.800
<v Speaker 2>the first wireless heart rate monitor, but it was fitbit

0:27:20.040 --> 0:27:24.160
<v Speaker 2>in the early two thousands it took the industry mainstream. Today,

0:27:24.240 --> 0:27:28.400
<v Speaker 2>the wellness wearables arena is crowded, attracting billions in investment

0:27:28.520 --> 0:27:30.639
<v Speaker 2>and spawning new startups regularly.

0:27:31.119 --> 0:27:34.280
<v Speaker 8>Wearables today are nearly ubiquitous. I think, certainly when I

0:27:34.359 --> 0:27:36.199
<v Speaker 8>go out and about, I do see people with an

0:27:36.240 --> 0:27:39.720
<v Speaker 8>Apple watch, a whoop, an aura. We do see people

0:27:39.720 --> 0:27:43.119
<v Speaker 8>wearing with various devices out in the world today.

0:27:43.800 --> 0:27:46.919
<v Speaker 2>Alex Morgan is a partner in Cosla Ventures, where he

0:27:46.960 --> 0:27:51.320
<v Speaker 2>focuses on investment in emerging biotech, healthcare, and data science.

0:27:51.680 --> 0:27:55.359
<v Speaker 8>For many wearables, the competitive landscape is a challenge. We

0:27:55.480 --> 0:27:59.320
<v Speaker 8>certainly saw in some of the first generation of activity

0:27:59.359 --> 0:28:02.720
<v Speaker 8>based wearables that were many companies that were all measuring

0:28:02.800 --> 0:28:05.840
<v Speaker 8>activity and heart rate and it was very hard to

0:28:05.920 --> 0:28:09.879
<v Speaker 8>compete with a product that really didn't provide unique information

0:28:09.960 --> 0:28:12.760
<v Speaker 8>and it was much more about brand and packaging and

0:28:12.800 --> 0:28:15.400
<v Speaker 8>perhaps influencer And there are ways that you can win

0:28:15.520 --> 0:28:19.680
<v Speaker 8>in a competitive landscape with better branding, better marketing, better

0:28:19.720 --> 0:28:24.119
<v Speaker 8>access to influencers. We tend to look for technology that

0:28:24.240 --> 0:28:29.240
<v Speaker 8>is unique, often protectable with IP that offers unique benefit,

0:28:29.400 --> 0:28:31.320
<v Speaker 8>and that is something that we particularly look for.

0:28:32.359 --> 0:28:36.760
<v Speaker 2>Samsung recently released the Galaxy Watch eight, offering new health

0:28:36.840 --> 0:28:41.560
<v Speaker 2>tracking capabilities. In late twenty twenty four, Apple announced its

0:28:41.640 --> 0:28:45.560
<v Speaker 2>latest smartwatch with advanced features like a sleep apnea detector.

0:28:46.200 --> 0:28:50.560
<v Speaker 2>But not every company is successful. Amazon discontinued its Halo

0:28:50.720 --> 0:28:54.320
<v Speaker 2>fitness band in twenty twenty three, underscoring the challenge of

0:28:54.440 --> 0:28:58.360
<v Speaker 2>entering this market without a clear edge. With multiple devices

0:28:58.360 --> 0:29:01.640
<v Speaker 2>to choose from. How does one brand set itself apart

0:29:01.680 --> 0:29:05.160
<v Speaker 2>from the pack? Wearables have become popular in various ways.

0:29:05.400 --> 0:29:07.840
<v Speaker 2>How do you compare what's your market niche?

0:29:07.960 --> 0:29:11.480
<v Speaker 12>So we've designed the product to be worn very easily

0:29:12.800 --> 0:29:17.560
<v Speaker 12>in whatever location you want. And what does that ultimately achieve, Well,

0:29:17.560 --> 0:29:20.120
<v Speaker 12>it achieves a solution where you can be collecting this

0:29:20.200 --> 0:29:24.680
<v Speaker 12>health data twenty four to seven and continuous data is

0:29:24.800 --> 0:29:26.320
<v Speaker 12>ultimately what makes.

0:29:27.080 --> 0:29:28.720
<v Speaker 9>Our tool so successful.

0:29:29.160 --> 0:29:32.200
<v Speaker 12>You know, A real challenge I think with other products

0:29:32.240 --> 0:29:34.760
<v Speaker 12>that came before Whoop is they would give you these

0:29:34.800 --> 0:29:38.320
<v Speaker 12>sort of snapshots along the way. We collect an enormous

0:29:38.360 --> 0:29:41.920
<v Speaker 12>amount of data on the human body, physiological data. It's

0:29:41.960 --> 0:29:44.880
<v Speaker 12>really accurate. We've tuned the sensors to be really accurate.

0:29:45.400 --> 0:29:46.360
<v Speaker 12>But what that also.

0:29:46.200 --> 0:29:48.360
<v Speaker 9>Means is we're not going to do a thousand other things.

0:29:48.760 --> 0:29:54.040
<v Speaker 12>Right, We're not a smart watch, we're not doing phone calls.

0:29:54.160 --> 0:29:55.720
<v Speaker 12>You know, you're not going to call an uber with

0:29:55.800 --> 0:29:57.360
<v Speaker 12>your Whoop. But at the end of the day, we

0:29:57.360 --> 0:30:00.240
<v Speaker 12>don't spend that much time thinking about competition. Were just

0:30:00.280 --> 0:30:02.920
<v Speaker 12>incredibly focused on how do we drive health outcomes?

0:30:03.600 --> 0:30:07.040
<v Speaker 2>So, how does a wearable company help drive health outcomes?

0:30:07.800 --> 0:30:12.400
<v Speaker 2>For Whoop it's about differentiating itself through technology, using sophisticated

0:30:12.400 --> 0:30:17.080
<v Speaker 2>biometric monitoring and data collection for more actionable health insights.

0:30:17.720 --> 0:30:20.560
<v Speaker 2>Its most recent models are the Whoop five point zero

0:30:20.760 --> 0:30:21.959
<v Speaker 2>and Whoop MG.

0:30:23.000 --> 0:30:25.360
<v Speaker 12>It's got a fourteen day battery life, it's got more

0:30:25.400 --> 0:30:29.400
<v Speaker 12>accurate sensing. The Whoop MG has medical clearances, so it's

0:30:29.400 --> 0:30:35.360
<v Speaker 12>able to do ECG monitoring, AFIB detection, blood pressure insights.

0:30:35.880 --> 0:30:39.600
<v Speaker 12>So these are all really powerful innovations that frankly just

0:30:39.600 --> 0:30:40.440
<v Speaker 12>didn't exist.

0:30:40.760 --> 0:30:44.400
<v Speaker 8>Whatever wearable technology is doing to measure or interact with

0:30:44.440 --> 0:30:48.800
<v Speaker 8>an individual, the accelerating ability of a machine learning to

0:30:49.000 --> 0:30:52.800
<v Speaker 8>improve the capability of that measurement or that intervention is

0:30:52.840 --> 0:30:55.280
<v Speaker 8>only accelerating. We are translating to face where there are

0:30:55.360 --> 0:31:01.360
<v Speaker 8>wearable technologies that aren't just providing insights but actually provide interventions.

0:31:01.400 --> 0:31:04.200
<v Speaker 8>They're actually therapeutic in some way, And I think that

0:31:04.760 --> 0:31:08.000
<v Speaker 8>is going to accelerate the current adoption even more because

0:31:08.040 --> 0:31:12.840
<v Speaker 8>I do think that most people, most customers, don't necessarily

0:31:12.880 --> 0:31:15.720
<v Speaker 8>want insights. Most people want solutions to problems that they have,

0:31:16.560 --> 0:31:22.320
<v Speaker 8>whether it's problems sleeping, problems with depression, concerns about wait wellness.

0:31:22.320 --> 0:31:26.400
<v Speaker 2>Wearables have certainly become popular, but are they a good business?

0:31:27.000 --> 0:31:30.000
<v Speaker 2>And what takes a wearable from being nice to have

0:31:30.520 --> 0:31:32.320
<v Speaker 2>to being a half to have.

0:31:33.000 --> 0:31:36.160
<v Speaker 8>When we evaluate a company, there's no single way we

0:31:36.200 --> 0:31:41.120
<v Speaker 8>evaluate it. So sometimes we invest in unique technology. And

0:31:41.160 --> 0:31:44.240
<v Speaker 8>that's actually the majority of my time trying to identify

0:31:44.960 --> 0:31:49.120
<v Speaker 8>unique technology that is crossing over into being productizable and

0:31:49.200 --> 0:31:53.400
<v Speaker 8>translatable into products that we believe will provide real value

0:31:53.520 --> 0:31:56.040
<v Speaker 8>to customers in patients. And that's I think one of

0:31:56.080 --> 0:31:58.360
<v Speaker 8>the first things we want to do, is this product

0:31:58.480 --> 0:32:01.840
<v Speaker 8>or technology really able to help people in a potentially

0:32:01.880 --> 0:32:06.000
<v Speaker 8>powerful way. Another technology that I'm really excited about that's

0:32:06.040 --> 0:32:08.920
<v Speaker 8>being used is a company called Flow Neuroscience.

0:32:09.040 --> 0:32:09.880
<v Speaker 4>So this is on.

0:32:09.880 --> 0:32:13.479
<v Speaker 8>The market in the UK and Europe. Over ten thousand

0:32:13.480 --> 0:32:16.440
<v Speaker 8>people a month use it and it also uses a

0:32:16.840 --> 0:32:21.360
<v Speaker 8>gentle electric stimulation to treat mild to modern depression and

0:32:21.440 --> 0:32:22.680
<v Speaker 8>general anxiety disorder.

0:32:23.600 --> 0:32:25.080
<v Speaker 4>Numerous clinical trials.

0:32:24.800 --> 0:32:27.960
<v Speaker 8>Have shown benefit, so in some of the more recent

0:32:27.960 --> 0:32:32.000
<v Speaker 8>clinical trials about sixteen percent improvement and remission and depressive

0:32:32.000 --> 0:32:34.760
<v Speaker 8>symptoms compared to twenty percent in placebo. So the ideal

0:32:34.920 --> 0:32:39.760
<v Speaker 8>startup for US is a technology that provides unique, powerful,

0:32:39.840 --> 0:32:43.560
<v Speaker 8>patient and customer benefit in some way. They're able to say,

0:32:43.680 --> 0:32:47.120
<v Speaker 8>here's an innovation in technology that is crossing over from

0:32:47.160 --> 0:32:52.520
<v Speaker 8>basic science and research and moving into an opportunity to

0:32:52.560 --> 0:32:55.200
<v Speaker 8>go out and help many people that have a particular

0:32:55.240 --> 0:32:58.880
<v Speaker 8>problem and able through that in a unique and special way. Certainly,

0:32:59.640 --> 0:33:02.680
<v Speaker 8>there are are people using things like continuous glucose monitoring

0:33:02.920 --> 0:33:04.960
<v Speaker 8>that you may not know that they're using, but if

0:33:04.960 --> 0:33:07.760
<v Speaker 8>you ask someone with diabetes, that is probably how they

0:33:07.760 --> 0:33:10.760
<v Speaker 8>may be managing it today if you're intolindependent diabetic. So

0:33:11.240 --> 0:33:14.080
<v Speaker 8>I would say that it has crossed the chasm into

0:33:14.120 --> 0:33:16.720
<v Speaker 8>being something that's speculative into being a product that's just

0:33:16.800 --> 0:33:19.080
<v Speaker 8>part of the everyday lives for many Americans.

0:33:19.280 --> 0:33:21.280
<v Speaker 12>We're now in fifty markets. I think one of the

0:33:21.320 --> 0:33:23.840
<v Speaker 12>biggest changes for Whoop in the last two years is

0:33:23.880 --> 0:33:26.800
<v Speaker 12>going from being almost entirely a US business to being

0:33:26.800 --> 0:33:30.440
<v Speaker 12>in global business that obviously introduces new challenges, but also

0:33:31.040 --> 0:33:35.120
<v Speaker 12>enormous growth. And so we've seen the business growing considerably

0:33:35.320 --> 0:33:38.520
<v Speaker 12>in the last twelve months, seventy percent year over year growth,

0:33:38.520 --> 0:33:39.720
<v Speaker 12>which is really exciting.

0:33:40.360 --> 0:33:42.880
<v Speaker 2>We don't have the data yet to show that wearables

0:33:42.920 --> 0:33:46.760
<v Speaker 2>like whoop will actually make us healthier, much less, live longer,

0:33:47.400 --> 0:33:49.920
<v Speaker 2>and some believe the path to the fountain of youth

0:33:50.120 --> 0:33:53.200
<v Speaker 2>ultimately means doing the things our mothers have taught us

0:33:53.320 --> 0:33:54.400
<v Speaker 2>through the generations.

0:33:55.120 --> 0:33:57.600
<v Speaker 11>The secret of healthy life is very simple and it

0:33:57.640 --> 0:34:00.760
<v Speaker 11>doesn't require an industry to maintain it. Ignore all that

0:34:00.880 --> 0:34:06.400
<v Speaker 11>noise and focus on these five fundamental components from diet

0:34:06.920 --> 0:34:09.399
<v Speaker 11>to exercise, stress, sleep, and so on.

0:34:09.840 --> 0:34:14.480
<v Speaker 2>Albert Laslo Barabasi is a network science physicist. He believes

0:34:14.480 --> 0:34:18.200
<v Speaker 2>wearables may help users stay healthy, but there's no secret

0:34:18.360 --> 0:34:19.960
<v Speaker 2>about the keys to success.

0:34:20.840 --> 0:34:22.960
<v Speaker 11>As long as you focus on these basics and you

0:34:23.040 --> 0:34:27.600
<v Speaker 11>make sure that these are guaranteed, you are actually setting

0:34:27.640 --> 0:34:31.480
<v Speaker 11>yourself up for a healthy lifestyle. Everything else is more

0:34:31.560 --> 0:34:34.239
<v Speaker 11>or less an intervention that is trying to correct the

0:34:34.360 --> 0:34:39.680
<v Speaker 11>problem because these have not been probably observed. Certainly, having

0:34:39.719 --> 0:34:43.000
<v Speaker 11>access to all the data points about us does give

0:34:43.120 --> 0:34:46.120
<v Speaker 11>us a sense of control, and I think that sense

0:34:46.120 --> 0:34:49.440
<v Speaker 11>of control fails when we realize that we don't know

0:34:49.480 --> 0:34:52.880
<v Speaker 11>how to correct that. And we're all going to encounter

0:34:52.960 --> 0:34:56.280
<v Speaker 11>that moment in our lives where the numbers are flashing

0:34:56.360 --> 0:34:58.960
<v Speaker 11>and showing that something is out of balance.

0:34:59.600 --> 0:35:02.439
<v Speaker 2>Where do wearables need to go from here? If they're

0:35:02.480 --> 0:35:07.839
<v Speaker 2>to become proactive health companions? Not surprisingly artificial intelligence may

0:35:07.880 --> 0:35:09.120
<v Speaker 2>be part of the answer.

0:35:09.920 --> 0:35:13.240
<v Speaker 12>We've used artificial intelligence for a decade to really improve

0:35:13.280 --> 0:35:16.440
<v Speaker 12>our algorithms for sensing, and the result I think is

0:35:16.560 --> 0:35:18.799
<v Speaker 12>being able to demonstrate in the market we're the most

0:35:18.800 --> 0:35:22.360
<v Speaker 12>performance product. We still have the world's best athletes that

0:35:22.440 --> 0:35:26.520
<v Speaker 12>were whoop, we have medically approved features, and we have

0:35:26.560 --> 0:35:29.560
<v Speaker 12>consumers that swear by our accuracy. You don't really get

0:35:29.560 --> 0:35:33.080
<v Speaker 12>those combination of things if the underlying data isn't really good.

0:35:33.600 --> 0:35:36.560
<v Speaker 11>Eventually we will write to a point where we can really

0:35:36.640 --> 0:35:41.680
<v Speaker 11>monitor our processes and intervene early on before a disease

0:35:41.719 --> 0:35:44.239
<v Speaker 11>could develop. One way to think about it is that

0:35:44.320 --> 0:35:47.480
<v Speaker 11>every single disease that I will have throughout my lifetime

0:35:47.600 --> 0:35:51.360
<v Speaker 11>is already bit in me developing because I already born

0:35:51.440 --> 0:35:54.919
<v Speaker 11>with all the mutations and all the defects that will

0:35:54.960 --> 0:36:00.440
<v Speaker 11>eventually just develop themselves and manifest themselves with age. Is

0:36:00.480 --> 0:36:04.200
<v Speaker 11>how can we capture that early and how can correct

0:36:04.200 --> 0:36:08.360
<v Speaker 11>that before it's too late? And in that respect, wearable

0:36:08.440 --> 0:36:11.239
<v Speaker 11>technologies as well as the many monitoring devices that the

0:36:11.280 --> 0:36:17.279
<v Speaker 11>technology is making possible eventually will be the answer. Are

0:36:17.320 --> 0:36:19.759
<v Speaker 11>they the answer right now? Not necessarily.

0:36:20.080 --> 0:36:22.759
<v Speaker 8>We are translating to face where there are wearable technologies

0:36:23.000 --> 0:36:27.960
<v Speaker 8>that aren't just providing insights but actually providing interventions. They're

0:36:28.000 --> 0:36:29.680
<v Speaker 8>actually therapeutic in some way.

0:36:29.800 --> 0:36:32.240
<v Speaker 12>If we look at the next few years, right, health

0:36:32.280 --> 0:36:36.239
<v Speaker 12>monitoring will start by enabling individuals and being kind of

0:36:36.239 --> 0:36:39.480
<v Speaker 12>a continuation of that doctor's office, and I think in

0:36:39.520 --> 0:36:43.000
<v Speaker 12>the long run it'll ultimately replace the doctor's office.

0:36:43.440 --> 0:36:45.960
<v Speaker 2>At the point where wearables can replace our visits to

0:36:45.960 --> 0:36:49.440
<v Speaker 2>the doctor, or even make those visits a bit less frequent,

0:36:50.000 --> 0:36:52.920
<v Speaker 2>they will truly move from the nice to the necessary

0:36:52.960 --> 0:36:55.439
<v Speaker 2>for us all, and that could lead to a sort

0:36:55.440 --> 0:36:59.520
<v Speaker 2>of technological fountain of youth found not in the swamps

0:36:59.520 --> 0:37:04.080
<v Speaker 2>of Florida, but right on your wrist coming up. Some

0:37:04.120 --> 0:37:06.680
<v Speaker 2>of us may be worried about artificial intelligence coming for

0:37:06.800 --> 0:37:10.399
<v Speaker 2>our jobs, but does that include all those economists at

0:37:10.400 --> 0:37:23.000
<v Speaker 2>the Federal Reserve that's next on Wall Street Week. This

0:37:23.120 --> 0:37:26.799
<v Speaker 2>is a story about an invisible hand guiding the economy. No,

0:37:27.200 --> 0:37:30.200
<v Speaker 2>not the invisible hand of self interest that Adam Smith

0:37:30.239 --> 0:37:33.200
<v Speaker 2>wrote about in the Wealth of Nations. This invisible hand

0:37:33.320 --> 0:37:36.600
<v Speaker 2>is much more modern. It's that artificial intelligence we keep

0:37:36.640 --> 0:37:40.000
<v Speaker 2>hearing so much about. Our special contributor. Larry Summers is

0:37:40.040 --> 0:37:43.080
<v Speaker 2>a macroeconomist who also sits on the board of Open AI.

0:37:43.719 --> 0:37:46.800
<v Speaker 2>Who better to ask what AI could mean for Adam

0:37:46.840 --> 0:37:47.960
<v Speaker 2>Smith's economy.

0:37:49.640 --> 0:37:52.040
<v Speaker 3>My guess is that this is going to raise the

0:37:52.080 --> 0:37:55.799
<v Speaker 3>neutral rate of interest over time, both because of the

0:37:55.880 --> 0:37:58.480
<v Speaker 3>massive investment that's going to need to take place in

0:37:58.600 --> 0:38:03.440
<v Speaker 3>data centers and because of the acceleration.

0:38:03.520 --> 0:38:05.920
<v Speaker 4>In the rate of growth.

0:38:06.000 --> 0:38:10.400
<v Speaker 3>So I think the so called our star is likely

0:38:10.480 --> 0:38:16.759
<v Speaker 3>to be higher, perhaps even considerably higher, because of AI.

0:38:17.760 --> 0:38:21.000
<v Speaker 3>I think it's possible that it's going to be a

0:38:21.040 --> 0:38:28.000
<v Speaker 3>disinflationary force because of acceleration of productivity growth, as the

0:38:28.040 --> 0:38:33.360
<v Speaker 3>Internet was during the nineteen nineties.

0:38:33.719 --> 0:38:37.680
<v Speaker 2>The economic potential of AI varies widely, with some saying

0:38:37.719 --> 0:38:41.280
<v Speaker 2>that it can disrupt jobs, whole industries, and even pose

0:38:41.400 --> 0:38:42.880
<v Speaker 2>existential challenges.

0:38:43.200 --> 0:38:46.600
<v Speaker 11>It's not yet like replacing jobs in the way to

0:38:46.680 --> 0:38:48.239
<v Speaker 11>the degree that people thought it was going to.

0:38:48.320 --> 0:38:50.239
<v Speaker 9>Of course jobs will change, and of course some jobs

0:38:50.239 --> 0:38:51.160
<v Speaker 9>will totally go away.

0:38:51.280 --> 0:38:53.960
<v Speaker 13>It really is an existential threat. Some people say this

0:38:54.040 --> 0:38:56.880
<v Speaker 13>is just science fiction, and until fairly recently I believed

0:38:56.880 --> 0:38:58.839
<v Speaker 13>it was a long way off. Now I think it's

0:38:58.960 --> 0:39:02.520
<v Speaker 13>quite likely that sometime in the next twenty years these

0:39:02.520 --> 0:39:04.839
<v Speaker 13>things will get smarter than us and we really need

0:39:04.880 --> 0:39:06.080
<v Speaker 13>to worry about what happens.

0:39:06.080 --> 0:39:08.640
<v Speaker 2>Then, So let me ask you about one particular perhaps

0:39:08.719 --> 0:39:11.360
<v Speaker 2>rule of thumb or rule, and that is the relationship

0:39:11.360 --> 0:39:13.680
<v Speaker 2>between inflation on the one hand and unemployment on the other,

0:39:14.040 --> 0:39:17.000
<v Speaker 2>which has been an important issue for the Federal Reserve,

0:39:17.040 --> 0:39:19.799
<v Speaker 2>for example, with its dual mandate to address both of those.

0:39:19.880 --> 0:39:22.240
<v Speaker 2>Do you think it could change that relationship?

0:39:22.760 --> 0:39:28.399
<v Speaker 3>It certainly could, and you can make arguments in both directions.

0:39:28.520 --> 0:39:33.560
<v Speaker 3>Perhaps the more flexible economy means that rates of inflation

0:39:33.800 --> 0:39:38.480
<v Speaker 3>or prices will be more sensitive to demand and unemployment

0:39:39.560 --> 0:39:47.960
<v Speaker 3>than they were before. Perhaps the more rapid underlying productivity

0:39:48.200 --> 0:39:54.719
<v Speaker 3>growth will mean that there's less sensitivity because when there's

0:39:54.760 --> 0:39:57.799
<v Speaker 3>an increase in demand, the economy will be able to

0:39:57.840 --> 0:40:04.560
<v Speaker 3>accommodate it more easily because there's more capacity fundamentally in

0:40:04.600 --> 0:40:09.000
<v Speaker 3>the economy. I think it's difficult to know, and if

0:40:09.000 --> 0:40:12.600
<v Speaker 3>I had to guess, the effects that I described on

0:40:12.680 --> 0:40:16.279
<v Speaker 3>the neutral interest rate and so forth are probably going

0:40:16.360 --> 0:40:20.240
<v Speaker 3>to be more salient than any change in the slope

0:40:20.440 --> 0:40:25.560
<v Speaker 3>of the Phillips curve of that relationship you referred to

0:40:26.280 --> 0:40:34.680
<v Speaker 3>between inflation and unemployment. But nobody can be confident in

0:40:34.719 --> 0:40:37.200
<v Speaker 3>their judgments about this kind of thing.

0:40:37.840 --> 0:40:40.920
<v Speaker 2>There's the uncertainty about what AI could mean for the economy,

0:40:41.360 --> 0:40:43.600
<v Speaker 2>but there are also questions about what it could mean

0:40:43.640 --> 0:40:47.080
<v Speaker 2>for central banks trying to set monetary policy and how

0:40:47.080 --> 0:40:49.960
<v Speaker 2>it could change the way they gather and analyze data

0:40:50.000 --> 0:40:53.239
<v Speaker 2>about the economy. Sasha Stefan of the Frankfort School of

0:40:53.239 --> 0:40:57.320
<v Speaker 2>Finance has studied the ways AI might change monetary policy

0:40:57.360 --> 0:40:59.440
<v Speaker 2>transmission specifically.

0:40:59.480 --> 0:41:02.200
<v Speaker 14>And this is all the most common or most natural

0:41:02.239 --> 0:41:06.080
<v Speaker 14>thing people are thinking about here is it will improve forecasting.

0:41:06.120 --> 0:41:07.920
<v Speaker 14>And I think this is sort of where everybody's interested.

0:41:08.280 --> 0:41:10.840
<v Speaker 14>How our interest rates going how does the economy develop

0:41:10.880 --> 0:41:14.160
<v Speaker 14>going forward? How is inflation going forward? So here we're

0:41:14.200 --> 0:41:16.440
<v Speaker 14>going to see a lot already happening in terms of

0:41:16.680 --> 0:41:18.840
<v Speaker 14>I and I think here there's also a lot to

0:41:18.920 --> 0:41:19.920
<v Speaker 14>learn going forward.

0:41:20.560 --> 0:41:23.320
<v Speaker 2>Is it likely to make forecasting more accurate? Do you think?

0:41:24.080 --> 0:41:25.200
<v Speaker 14>I think definitely.

0:41:25.360 --> 0:41:25.520
<v Speaker 8>So.

0:41:25.880 --> 0:41:29.640
<v Speaker 14>I think one dimension of AI is basically increasing the

0:41:29.719 --> 0:41:34.480
<v Speaker 14>toolbox and the methodologies, improving on the methodologies thereby also

0:41:34.520 --> 0:41:39.040
<v Speaker 14>making forecasting much more precise. Also basically using models to

0:41:39.200 --> 0:41:43.239
<v Speaker 14>use existing data and use them in completely novel ways. Right, So,

0:41:43.280 --> 0:41:45.640
<v Speaker 14>how can we use bond market data? How can we

0:41:45.719 --> 0:41:48.480
<v Speaker 14>use loan market data. So we can employ these models

0:41:48.880 --> 0:41:52.000
<v Speaker 14>to look at things that we haven't been able to

0:41:52.040 --> 0:41:54.600
<v Speaker 14>do before. We can look at websites, we can use

0:41:55.320 --> 0:42:01.200
<v Speaker 14>images from satellites, we can use social media. Right, So,

0:42:01.400 --> 0:42:04.359
<v Speaker 14>actually I have a study, a recent one in which

0:42:04.400 --> 0:42:08.799
<v Speaker 14>we try to use AI and Twitter or x in

0:42:08.880 --> 0:42:13.080
<v Speaker 14>order to generate an index about what do individuals like

0:42:13.200 --> 0:42:16.480
<v Speaker 14>households have an idea about how inflation is going to

0:42:16.520 --> 0:42:18.839
<v Speaker 14>develop going forward? Right, So, this is what we call

0:42:18.880 --> 0:42:22.719
<v Speaker 14>inflation expectations, and this is something where central banks, the

0:42:22.760 --> 0:42:26.000
<v Speaker 14>Federal Reserve but also the European Central Banks are looking

0:42:26.080 --> 0:42:28.719
<v Speaker 14>much more closely at compared to what we call like

0:42:28.800 --> 0:42:31.880
<v Speaker 14>realize inflation what we have. So, what do actually people

0:42:31.960 --> 0:42:36.360
<v Speaker 14>households expect in terms of inflation going forward? Because this

0:42:36.480 --> 0:42:39.319
<v Speaker 14>is going to affect how they're going to behave, what

0:42:39.400 --> 0:42:41.879
<v Speaker 14>kinds of products are they going to buy, what kinds

0:42:41.920 --> 0:42:45.520
<v Speaker 14>of sort of how are they going to save going forward?

0:42:45.600 --> 0:42:47.560
<v Speaker 14>And also firms are going to be affected by that

0:42:47.640 --> 0:42:50.480
<v Speaker 14>because they see if customers don't buy, the shelves are

0:42:50.480 --> 0:42:54.160
<v Speaker 14>going to remain full and they basically report a completely

0:42:54.160 --> 0:42:56.000
<v Speaker 14>different bottom or top line going forward.

0:42:56.040 --> 0:42:58.359
<v Speaker 2>What are the risks of expanding out the data that way,

0:42:58.440 --> 0:43:01.000
<v Speaker 2>I mean a large language models and larger based on

0:43:01.120 --> 0:43:04.680
<v Speaker 2>what human beings have generated, and human beings are not perfect,

0:43:05.000 --> 0:43:07.520
<v Speaker 2>and you can get hallucinations that way. What are the risks,

0:43:07.520 --> 0:43:10.160
<v Speaker 2>particularly as you go to things like social media for example.

0:43:10.080 --> 0:43:13.799
<v Speaker 14>X information sensitivity is always run right, which means that

0:43:14.640 --> 0:43:18.240
<v Speaker 14>if new information arises that can cause maybe a complete

0:43:18.280 --> 0:43:21.120
<v Speaker 14>meltdown of the market. Stocks are going to be sold,

0:43:21.280 --> 0:43:24.000
<v Speaker 14>And of course AI makes it even more likely that

0:43:24.120 --> 0:43:26.880
<v Speaker 14>these risks are actually or these new information is actually

0:43:26.880 --> 0:43:31.920
<v Speaker 14>going to emerge, right. But also another risk is, for example, interconnectedness,

0:43:31.920 --> 0:43:36.560
<v Speaker 14>and AI also will connect institutions more going forward, there

0:43:36.640 --> 0:43:39.000
<v Speaker 14>might be shared data, there might be shared platforms that

0:43:39.080 --> 0:43:42.560
<v Speaker 14>might increase interconnectedness. So if one domino drops, the others

0:43:42.640 --> 0:43:46.080
<v Speaker 14>might actually drop as well. So amplification of existing risks

0:43:46.120 --> 0:43:50.480
<v Speaker 14>is definitely one problem. Another problem that's very frequently mentioned

0:43:50.520 --> 0:43:52.920
<v Speaker 14>if you talk to practitioners in this field is also

0:43:53.719 --> 0:43:55.719
<v Speaker 14>a kind of what we call a model bias. Right,

0:43:55.800 --> 0:43:59.239
<v Speaker 14>So what happens if we use data that has been

0:43:59.320 --> 0:44:02.080
<v Speaker 14>generated by a model that has all better been falls

0:44:02.120 --> 0:44:04.920
<v Speaker 14>to begin with, and then we continue to use their

0:44:05.040 --> 0:44:08.160
<v Speaker 14>data going forward, there will be so colled perpetuation of

0:44:08.440 --> 0:44:12.160
<v Speaker 14>these biases going forward, and like garbage in garbage out.

0:44:12.080 --> 0:44:15.280
<v Speaker 2>We hear from some experts in AI that we're getting

0:44:15.280 --> 0:44:17.439
<v Speaker 2>to a point, maybe past a point where we don't

0:44:17.480 --> 0:44:20.120
<v Speaker 2>actually know how it works. It's a black box in

0:44:20.160 --> 0:44:23.399
<v Speaker 2>that sense. If that's true, how can a center back

0:44:23.440 --> 0:44:25.600
<v Speaker 2>rely on it? How can it verify it or certify

0:44:25.640 --> 0:44:28.799
<v Speaker 2>it to make sure that it's making correct inferences.

0:44:28.840 --> 0:44:31.319
<v Speaker 14>That's an absolute important point. This is on the one end,

0:44:31.320 --> 0:44:34.359
<v Speaker 14>this is definitely a risk, right because if things go wrong,

0:44:34.480 --> 0:44:38.240
<v Speaker 14>the question, the trust that might be there quickly goes away,

0:44:38.400 --> 0:44:40.800
<v Speaker 14>and then the things might even be worth going forward.

0:44:41.080 --> 0:44:45.920
<v Speaker 14>One of the potential powerful applications of AI for central

0:44:45.960 --> 0:44:52.120
<v Speaker 14>banks is to not replace necessarily, but to complement the

0:44:52.280 --> 0:44:56.239
<v Speaker 14>professional forecasting that the central banks usually rely on. They

0:44:56.280 --> 0:44:58.759
<v Speaker 14>usually do on a quarterly basis. Ask a lot of

0:44:58.760 --> 0:45:02.239
<v Speaker 14>professionals and investm banks and other institutions as to what

0:45:02.280 --> 0:45:06.080
<v Speaker 14>do they expect the economy to develop going forward, specifically

0:45:06.120 --> 0:45:09.279
<v Speaker 14>when it comes to inflation, and now it might be

0:45:09.320 --> 0:45:14.480
<v Speaker 14>actually possible to set up an AI model that exactly

0:45:14.640 --> 0:45:19.480
<v Speaker 14>does that. So it basically it is trained on the individual,

0:45:19.520 --> 0:45:23.759
<v Speaker 14>it's trained on the cvs of the professional forecasters, how

0:45:23.800 --> 0:45:26.319
<v Speaker 14>they have actually voted, or what they have done in

0:45:26.600 --> 0:45:31.000
<v Speaker 14>previous forecasts, that they did, what is their job, what

0:45:31.160 --> 0:45:34.799
<v Speaker 14>they learned, and then asked the model instead of the forecaster,

0:45:35.080 --> 0:45:38.279
<v Speaker 14>And the existing research already tells us that there is

0:45:38.320 --> 0:45:40.719
<v Speaker 14>a high degree of overlap in terms of what the

0:45:40.760 --> 0:45:45.600
<v Speaker 14>professional forecast actually would tell him or herself and what

0:45:45.680 --> 0:45:48.919
<v Speaker 14>the model actually sells. Right, But then the one risk,

0:45:48.960 --> 0:45:51.279
<v Speaker 14>and now coming back to your question, is that how

0:45:51.280 --> 0:45:55.640
<v Speaker 14>can we actually make sure that the model actually uses

0:45:55.719 --> 0:45:58.360
<v Speaker 14>only the information that is available at the time of

0:45:58.400 --> 0:46:02.239
<v Speaker 14>a forecast itself is a train basically on information that

0:46:02.280 --> 0:46:05.120
<v Speaker 14>it should not know because it actually happened afterwards.

0:46:05.200 --> 0:46:07.719
<v Speaker 2>Well, I wonder about the systemic risk because not being

0:46:07.719 --> 0:46:12.800
<v Speaker 2>a conputer science, it's possible that AI could spot relationships

0:46:13.000 --> 0:46:15.239
<v Speaker 2>that otherwise humans might miss. I mean, so you have

0:46:15.280 --> 0:46:18.520
<v Speaker 2>something like Silicon Valley Bank in the United States. Is

0:46:18.560 --> 0:46:23.440
<v Speaker 2>it possible AI would have spotted imbalances earlier that humans.

0:46:23.080 --> 0:46:26.759
<v Speaker 14>Missed, specifically with a Silicon value bank, it would have

0:46:27.400 --> 0:46:30.480
<v Speaker 14>recognized this because it's also interesting that people did not

0:46:30.600 --> 0:46:33.480
<v Speaker 14>realize this because it was obvious to be to be clear,

0:46:34.200 --> 0:46:37.280
<v Speaker 14>because actually all the publicly available data was pointing exactly

0:46:37.320 --> 0:46:39.759
<v Speaker 14>at that, but no, you're absolutely right. So these kind

0:46:39.840 --> 0:46:44.640
<v Speaker 14>of systemically important banks, also other banks risks emerging based

0:46:44.680 --> 0:46:48.520
<v Speaker 14>on for example, liquidity consideration might be detected much much

0:46:48.560 --> 0:46:52.000
<v Speaker 14>earlier compared to what the regulator or supervisor might actually

0:46:52.080 --> 0:46:52.839
<v Speaker 14>might actually see.

0:46:52.960 --> 0:46:56.560
<v Speaker 2>And what we need human beings economists presumably to check

0:46:56.640 --> 0:46:59.160
<v Speaker 2>what's going on to make corrections, because you can have

0:46:59.320 --> 0:47:02.319
<v Speaker 2>hallucination in any model, and if you don't correct them,

0:47:02.320 --> 0:47:04.040
<v Speaker 2>as I understand, they just compound.

0:47:04.320 --> 0:47:07.160
<v Speaker 14>I think this is exactly one danger that people might

0:47:07.239 --> 0:47:10.200
<v Speaker 14>actually try to rely on AI and these models too

0:47:10.280 --> 0:47:14.520
<v Speaker 14>much and think, Okay, these models actually know what's going

0:47:14.600 --> 0:47:15.040
<v Speaker 14>to happen.

0:47:15.440 --> 0:47:20.120
<v Speaker 4>But the idea how to assess these.

0:47:20.040 --> 0:47:22.960
<v Speaker 14>Outcomes or these outputs, that's a crucial one. And this

0:47:23.080 --> 0:47:26.600
<v Speaker 14>means I think also for us as not only as economists,

0:47:26.600 --> 0:47:28.920
<v Speaker 14>but also as educators, we need to make sure that

0:47:29.000 --> 0:47:32.560
<v Speaker 14>people understand the underlying theory and economics actually in order

0:47:32.600 --> 0:47:35.799
<v Speaker 14>to evaluate is that what the model actually tells me,

0:47:36.120 --> 0:47:39.040
<v Speaker 14>is this something that's actually plausible or something that's not right?

0:47:39.120 --> 0:47:41.319
<v Speaker 14>So I think that puts a lot of pressure on

0:47:41.320 --> 0:47:44.360
<v Speaker 14>on us also as educators, but then also on the

0:47:44.400 --> 0:47:47.400
<v Speaker 14>different institutions, do they actually train the people right going forward.

0:47:49.120 --> 0:47:50.839
<v Speaker 2>That does it for us Here at Wall Street Week,

0:47:51.040 --> 0:47:54.000
<v Speaker 2>I'm David Weston. See you next week for more stories

0:47:54.040 --> 0:48:00.640
<v Speaker 2>of capitalism.