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Economist: The AI Bears Are Asking The Wrong Questions

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Economist: The AI Bears Are Asking The Wrong Questions

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1522 segments

0:00

Do you think that discussion of a bubble

0:02

or the possibility of there being a

0:04

bubble is the wrong discussion? Maybe

0:07

there are there is something more

0:09

important, more significant that you

0:10

think people should be talking about

0:12

instead.

0:12

>> I think it's the wrong discussion. I

0:14

don't like the word bubble. Were

0:15

automobiles a bubble in the 1920s?

0:18

Again, a lot of the companies failed.

0:20

They were not the best companies. Could

0:22

you imagine companies whether AI or not

0:24

today failing because of Middle Eastern

0:26

war, war with Russia, mistakes from the

0:29

Fed, halfozen other reasons? Of course

0:31

you can. So things can fail. It doesn't

0:34

mean they were bubbles to begin with. A

0:36

bubble to begin with is something like

0:37

the South Sea bubble or the Dutch tulip

0:39

bulbs that just made no sense. This is

0:42

not that. I think the key question is

0:44

just how much will society accept the

0:46

changes coming from AI.

0:51

>> Today's number 40. That's the percentage

0:54

of Americans who think listening to

0:55

audio books does not count as reading.

0:58

Ed true story. I recently had a book

1:01

fall on my head, but you know, I have no

1:03

one to blame but my shelf.

1:06

>> We're back. We're back, baby.

1:13

Tell me everything about your vacation.

1:16

>> Uh, it was I I

1:17

>> I'm not interested.

1:22

>> I started

1:25

jump to the punch line too quickly. You

1:27

got to give it a second. Let me get

1:28

going.

1:28

>> Go ahead. What did you do? I am sort of

1:30

interested. What did you do? Where'd you

1:32

I was in Munich or actually just outside

1:34

of Munich in Amadingan uh for a friend's

1:38

wedding which was incredible in Bavaria.

1:41

Uh then I drove I rented a car with my

1:45

girlfriend, drove down the autob barn

1:48

into Kitsule in Austria. Spent a week in

1:51

Kitsb hiking, chilling, going to the

1:55

spa. It was probably I think it was the

1:58

best vacation uh of my life. I've been

2:01

sort of pondering on it, but I think I

2:02

think it's my number one.

2:04

>> Wow.

2:04

>> Uh and then I spent the weekend in

2:06

London and I decided, you know what? I

2:09

need to see the opening match of the

2:11

Premier League. So, I went to the

2:12

Chelsea game and sat in the front row

2:15

and watched Chelsea beat Fulham. So, I'm

2:19

feeling very good. I miss it. I mean, I

2:21

love this podcast. I love doing this

2:22

with you, but I I I

2:25

could have maybe taken a few more weeks

2:26

off, but I'm feeling very good. I feel

2:28

ready. Ready for the year. Oh, that's

2:30

great. Yeah, you sound you sound

2:31

energized.

2:33

>> How about you?

2:34

>> Yeah, August was good. I dropped my

2:37

kid off at school. Nothing screams

2:39

confident masculinity like crying in a

2:42

your car when your son walks out of Best

2:44

Buy with his own mini fridge. Um

2:48

but uh yeah, it's um yeah, it's that was

2:52

the big deal was dropping my kid off at

2:54

school. What are your takeaways having

2:56

dropped your first son off at college?

2:58

Well, the way you summarize it is your

3:00

life gets smaller so theirs can get

3:02

bigger and it's just um you you you're a

3:07

tide pool of emotions because everything

3:08

just sort of hits you all at once and

3:10

there was all these things you were

3:11

going to do that you didn't get a chance

3:12

to do. I had all these you know we did a

3:15

lot. I think I was more present than

3:16

most dads but you know I had thought oh

3:18

we I got to take my son to Alaska. I

3:20

want to buy a car and restore with him

3:21

and I want to take him to, you know,

3:24

Latin America and I wanted him to come

3:26

on tour with me uh on one of my speaking

3:29

gig things. And all you think about is

3:31

all the me cuz I'm a kind of a

3:33

glass half empty kind of guy, but all

3:34

you think about is the you were

3:35

supposed to do that you didn't. But

3:39

um he makes it a little bit easier not

3:41

to be sad because I think of myself as

3:43

this spiritual loving guy and he's

3:45

literally like I I got this dad and

3:47

shoving me out of the room after about 7

3:49

minutes. And also I mean quite frankly I

3:53

didn't want to make it about me so I

3:55

thought I keep it together that like

3:56

your 18-year-old does not need the

3:58

emotional baggage of his father like

4:00

singing Cats in the Cradle over and over

4:02

in his head. Um, so yeah, I tried to I

4:06

held it together. He'd be proud of me. I

4:08

didn't cry and we just fixed up his dorm

4:12

room and we thread the needle between a

4:14

comfortable nice dorm room and one of

4:16

these ridiculous real housewives of Palm

4:18

Beach things where they turn it into the

4:19

Brett's Carlton Charlottesville.

4:22

So we went to Target. I'm like, I'm not

4:24

going to buy anything nice. You can get

4:26

anything you want, but it's coming from

4:27

Target. And then the moment I lost it

4:31

was actually after we dropped him and I

4:34

was back at the hotel and I was sitting

4:36

there and I noticed this car stop at the

4:39

dorm or the business school, the law

4:41

schools next to where we were staying

4:43

and this mom got out on the driver's

4:45

side and then a kid got out of the back

4:49

seat and then the dad got out of the

4:50

passenger seat and then they hugged,

4:54

they embraced and the dad immediately

4:55

had to walk away and he started crying

4:58

and I realized it was their own drop off

5:01

and then I just lost my So,

5:03

whoever that dad was losing it on the

5:05

sidewalk kind of did my like express my

5:09

emotions for me. Are you surprised by

5:12

the significance of dropping the kid off

5:16

at college? Like I know people talk

5:17

about it and I know it's like you know

5:19

empty nest what is it syndrome? Empty

5:22

nest whatever the feeling is called. I

5:24

know it's a thing, but I I wonder if

5:28

it's more of a thing than you expected.

5:31

>> First off, I think I think it's it's

5:33

difficult and a big moment for a lot of

5:35

people. And it's just so different now.

5:38

My drop off was my mom gave me like my

5:41

mom gave me an iron, a used iron, and

5:42

said, "Here, you're going to need this."

5:44

That was my big drop off was she left an

5:46

iron on the kitchen table for me to take

5:48

to college. That was the emotional drop

5:50

off. There was my drop off in 19, you

5:53

know, '92, 82. Uh, this is a much bigger

5:58

deal. You know, drop off is a much

6:00

bigger deal now. For me, I think I

6:04

Well, it just marks a different point in

6:06

your life where your kids are no longer

6:08

at home. And the the thing I'm wrestling

6:11

with a little bit on an existential

6:13

level is I've always described my

6:15

purpose as raising, you know, preparing

6:18

my my sons for others. And it's been a

6:22

nice source of purpose for me. And now

6:24

you kind of worry like, okay, am I going

6:26

to have a purpose moving forward? So, it

6:29

is it marks time. It's like basically

6:31

now really all I have to look forward to

6:33

is the ass cancer. Ed,

6:35

>> don't lie. You've been looking forward

6:36

to that for years.

6:38

Yeah, I've been talking about a lot.

6:40

Look, it's a it's a you'll see it's it's

6:42

it's impossible to explain until it

6:44

actually happens to you. But I tried to

6:47

hold it together such that again as as I

6:50

I didn't want to do what I always do and

6:52

that's turn it turn it to me and he

6:53

seems happy. I speak to my boys every

6:55

day which makes things easier for me. So

6:57

I talk to him about his classes and

6:59

what's going on.

7:00

>> Oh, that's good. And also it's just it's

7:02

a great everything that I'd hope for in

7:05

terms of UVA is what it's out of central

7:08

casting. You know the this campus is

7:10

great. The kids seem really smart and

7:12

nice and you know he's having a great

7:16

time and so that makes it easier. So

7:19

we'll see. We'll see.

7:21

>> Sounds like you're not sure what you

7:22

make of it yet.

7:23

>> I'm an emotional tidepool. I don't know.

7:24

I don't know how to process it all is

7:26

the bottom line.

7:27

>> I'm like what are your takeaways?

7:30

Yeah, I know.

7:31

>> Process things now.

7:33

>> Yeah. No, I don't I don't I don't have

7:36

>> Well, we'll check in on it for sure. I

7:37

appreciate that. Yeah,

7:40

>> it's an interesting time. Well, now that

7:43

we got the life advice or life

7:45

reflections out of the way, we have a

7:47

very, very interesting discussion with

7:49

someone who we've want to have on the

7:50

show for a while now. So, don't miss it.

7:54

We've been away on break for the past

7:56

two weeks and in that time there have

7:58

been a ton of developments in the world

8:00

of AI. One of the biggest was the

8:03

hacking of hugging face by rogue agents

8:06

from open AI. But beyond that breaking

8:09

news, there are still some lingering

8:10

questions about AI that are keeping the

8:13

market on edge. For example, are we in a

8:16

bubble? How will AI reshape the job

8:19

market? and is the massive spending that

8:21

we're seeing from these companies

8:22

actually sustainable? So, to help us

8:25

make sense of it all, we are turning to

8:26

someone who a lot of the other experts

8:28

we've had on this show often listen to.

8:30

He has consistently been named one of

8:32

the most influential economists and

8:34

thinkers in the world. And he has been

8:36

described as quote the man who wants to

8:39

know everything. So here is our

8:41

conversation with Tyler Cowan,

8:43

economist, author, podcaster, and chair

8:46

of the Marta Center at George Mason

8:49

University. Tyler, uh, great to be

8:52

joined by you today. Uh, very excited to

8:55

get into this conversation. I'd love to

8:57

start with some questions about the AI

9:01

bubble, whether or not we are in one.

9:03

And I would especially love to start

9:04

with uh a clip from a an interview that

9:09

went viral recently. This was from the

9:12

Diary of a CEO's interview with uh Ed

9:15

Zitron, who has become famously one of

9:18

AI's biggest critics. Um I'm going to

9:21

play you what he said about AI and I

9:24

want to get your reactions to start this

9:26

off.

9:26

>> I think generative AI is at its heart

9:29

con. I don't think it is sold as honest

9:32

software. I think that they overstate

9:35

both what it can do, what it will do,

9:37

and the underlying financials to the

9:39

point that they are misleading the

9:40

entire world. And they're actively

9:42

exploiting the weaknesses in journalism,

9:44

in our economies, and indeed within the

9:47

responsible parties with sellside

9:48

analysts, governments, and all over the

9:50

shop.

9:50

>> The word con is a strong word.

9:52

>> Yeah. I mean what do you call something

9:55

where from the very beginning they've

9:56

sold it in the terms of magic as this

9:59

thing that will replace all jobs that

10:00

will cure cancer as all of these things

10:02

and when you look at it it's boring

10:04

cloud software that's extremely

10:06

expensive and unprofitable and also

10:08

unreliable at its core.

10:10

>> You are a worldrenowned economist.

10:12

You've written uh a lot about AI. You

10:15

also uh serve on anthropics economic

10:18

advisory council. So you think about

10:19

this stuff a lot. Um, what do you make

10:22

of those comments? Do you agree with

10:24

them?

10:24

>> AI is like magic in many ways. There are

10:27

many, many tasks where it does better

10:29

than humans. It doesn't mean it will

10:31

take away your job because your job

10:33

involves the physical world as well in

10:35

dealing with people. But for

10:37

intellectual tasks, it's a truly

10:39

remarkable achievement, one of the top

10:41

in the history of mankind. There's a

10:43

tweet circulating on Twitter about all

10:45

of Ed Citroen's wrong predictions so

10:47

far. Open AAI just hit a billion dollars

10:50

of revenue from ads. The revenue to date

10:53

for anthropic and open AI has been

10:55

incredible. There's also Grock, Meta,

10:58

other companies, the Chinese waiting in

11:00

the wings. I'm not saying every company

11:02

will make it. There were plenty of car

11:04

companies in the 1920s. They're not

11:06

mostly around today, but cars are a big

11:09

big thing and AI is too. When you think

11:11

about this idea of the circularity of

11:14

the AI ecosystem,

11:16

this idea and this is something that

11:18

Zitran has talked about um that you have

11:23

a lot of these companies, these big tech

11:24

companies that are investing in

11:26

anthropic and open AI and then open AI

11:29

and anthropic and then turning around

11:31

and spending those dollars uh on compute

11:34

that is sold to them by basically their

11:37

investors. Um and the fact that you know

11:40

open anthropic have made up such a

11:42

significant portion of these big tech

11:45

companies AI revenue for example

11:46

Microsoft 70% of their AI revenue last

11:49

year came from open AI does that element

11:52

of it concern you not the technology but

11:56

the way that the technology is uh being

12:00

sold right now

12:01

>> new things bootstrap themselves all the

12:03

time you can think of Nvidia as a kind

12:05

of lender or buyer of last resort for

12:08

the sector. You could say the same about

12:10

Microsoft, arguably Google, maybe Meta

12:13

as well. There's a lot of capital in the

12:15

sector that increases its long run

12:17

chances of making it. Again, the point

12:19

is not that every single company will

12:21

prosper, but the stuff works. There's no

12:24

reason to be skeptical, per se, about

12:26

the economic future of AI. If one of

12:29

those companies were to fail, because

12:30

you're saying, you know, maybe these

12:33

companies won't all make it out alive.

12:36

Is that not quite a significant

12:39

statement if if it's not

12:42

a certainty that some of these AI labs

12:45

wouldn't make it uh out of this or that

12:48

they wouldn't prosper or succeed at the

12:50

valuations that we're seeing? Looking at

12:52

how systemic they have become to our

12:54

economy,

12:56

is that not something that worries you?

12:57

>> It's a super competitive sector. You

12:59

could say in a way we should hope they

13:01

don't all make it. That some of them

13:02

have much better products than the

13:04

others. Are there economic costs to

13:06

companies going out of business? Of

13:08

course, the companies themselves are not

13:10

very heavily financed by debt. You could

13:13

say there's other parts of the supply

13:15

chain, data centers and the like, or

13:17

people investing in those that are

13:18

financed by debt that could have some

13:20

bad macro consequences. But again, every

13:23

new technology we've had, including the

13:25

internet, including cars, including

13:27

railroads, there are ups and downs to

13:29

the cycle. Not every company makes it.

13:31

the really good stuff basically works

13:33

and it sticks around with us forever

13:35

like the railroads do. Do I worry about

13:38

day-to-day volatility? Of course, but

13:40

keep it in perspective, right? Every

13:42

sector has had this. Uh you have to ask

13:45

yourself, does the product work? And the

13:47

answer here is a very clear yes.

13:49

>> It says we saw the dot implosion again.

13:52

Um going with your analogy like you know

13:55

there's value here and there will be ups

13:57

and downs. Do you think that that is a

14:00

scenario that is

14:02

probable, possible.

14:04

Um, do you think that that is something

14:06

that is should be uh talked about?

14:09

>> It's possible, but there are big

14:11

differences. So, revenue growth for the

14:13

current AI companies looks much better

14:16

than what we saw before the dotcom

14:18

bubble burst, right? The degree of

14:20

capitalization in the sector is much

14:21

better and much stronger. Just our

14:24

confidence in the technology. So, a lot

14:26

of things are possible. Again,

14:28

volatility would not in the slightest

14:30

surprise me. It's been a historical

14:33

regularity. Uh, Pets.com went under, but

14:36

you can buy pet food online all day long

14:39

if you want, and that's the world we're

14:40

headed for with AI.

14:42

>> Do you think that discussion of a bubble

14:44

or the possibility of there being a

14:46

bubble is the wrong discussion? Do you

14:49

think that maybe there are there is

14:52

something more important, more

14:53

significant that you think we that

14:55

people should be talking about instead?

14:56

I think it's the wrong discussion. I

14:58

don't like the word bubble. You know,

15:00

were automobiles a bubble in the 1920s?

15:03

Again, a lot of the companies failed.

15:04

They were not the best companies. Could

15:07

you imagine companies, whether AI or

15:09

not, today failing because of Middle

15:11

Eastern war, war with Russia, mistakes

15:14

from the Fed, half dozen other reasons?

15:15

Of course, you can. So, things can fail.

15:18

It doesn't mean they were bubbles to

15:20

begin with. A bubble to begin with is

15:21

something like the South Sea bubble or

15:23

the Dutch tulip bulbs that just made no

15:25

sense. This is not that. I think the key

15:28

question is just how much will society

15:31

accept the changes coming from AI. That

15:33

is indeed a very open question. We might

15:36

decide to stop or halt or slow down

15:37

those changes. And there I think we

15:39

should be very agnostic.

15:41

>> I'll put forward a thesis and you tell

15:42

me where you think we have a right or

15:44

wrong. You mentioned the automobile

15:46

market. It feels to me that an apt

15:48

analogy would be that the frontier

15:51

models are German automobile

15:52

manufacturers. higher price, prestige,

15:56

better technology, larger margins, and

15:59

that the openweight Chinese models are

16:01

more like the Korean or the Japanese

16:03

auto market that end up putting more

16:05

cars or AI in the hands of of users

16:09

around the world. Would you do you feel

16:11

that's an accurate description? Do you

16:13

feel that the market is kind of

16:14

bifurcating?

16:15

>> Open- source models make frontier models

16:17

easier to use. You use frontier models

16:20

for the frontier tasks and you use open-

16:23

source models for simpler tasks. So it

16:26

doesn't have to be either or. Uh right

16:29

now the best proprietary models are

16:31

better for tough tasks. That makes a big

16:34

difference using Fable 5. You can do

16:36

many things that you cannot do with the

16:38

Chinese open-source models. I think

16:41

China also is more likely to get scared

16:43

of its own AI than America is. So

16:46

there's no guarantee progress on the

16:48

Chinese front will continue. So again,

16:50

there's a lot of competition, but the

16:52

idea that American business is just

16:54

going to wholescale rush to Chinese

16:56

models and abandon the best American

16:58

models, I don't expect that. So looking

17:00

at the market dynamics or I've read that

17:04

2 and a.5 trillion in capex so far about

17:08

revenues of 150 billion and in all the

17:11

technologies we've talked about

17:12

railroads the internet the grid highways

17:17

the technology often times survives

17:19

evaluations this just feels eerily

17:22

reminiscent of all these other

17:24

innovations where you get above a

17:25

certain level of GDP spend on capex and

17:28

you have a pretty serious correction

17:30

regardless of the viability or the

17:33

importance of the technology doesn't I

17:34

mean you're an economist you look at

17:36

economic cycles this feels eerily

17:38

reminiscent of those different

17:41

innovations where the technology

17:42

survived the valuations again a

17:44

correction wouldn't surprise me but keep

17:46

in mind this technology has advanced

17:49

much more quickly than the others were

17:51

in a much wealthier world debt plays a

17:54

much less significant role in this

17:56

sector there's massive capitalization in

17:58

the sector

17:59

due to the major tech companies who

18:02

would love to be able to buy up a great

18:03

proprietary model if it came to that. So

18:06

in all those ways, this is not like for

18:09

instance the railroads. But again, I

18:11

absolutely expect big ups and downs. No

18:13

one should be surprised by that. As you

18:15

point out, that's the norm in history.

18:19

We'll be right back after the break. And

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19:43

>> We're back with Profy Markets. Let's

19:45

talk a little bit about the labor

19:46

markets and that is the kind of

19:49

idiocracy scenario where these tools

19:51

result in such an incredible increase in

19:53

productivity that we can afford to just

19:55

pay everyone to stay home and their jobs

19:57

go away. When I look at the labor

19:59

market, what I see is a market where you

20:01

wouldn't know AI existed if you didn't

20:03

know it existed. I don't I challenge

20:05

anyone to discern

20:08

where this chaos in the labor market is

20:10

supposedly manifesting. curious to get

20:12

your predictions or sense for the

20:15

intersection between AI and the labor

20:17

market and where the the market appears

20:19

to be getting it right or wrong about

20:20

this somewhat of a catastrophizing

20:23

around the labor markets.

20:24

>> I agree with what you just said. I think

20:26

in programming it's quite noticeable,

20:28

but there's some very recent papers, one

20:30

by John Hartley, and you just don't see

20:32

it in the numbers. Some modest amount of

20:35

jobs might be going away because of AI.

20:37

Some modest amount of jobs might be

20:39

created because of AI. Those two numbers

20:41

appear to roughly balance. AI will

20:44

spread over time a lot more slowly than

20:46

AI advocates often seem to think and I

20:49

think labor markets will be pretty

20:51

stable. The only thing you said that

20:53

seemed unusual to me or I would maybe

20:57

I wonder everyone's talking about kind

20:59

of a a supply crisis or that we don't

21:02

have the infrastructure or the supply

21:04

chain to support the increase in demand

21:06

and it looks to me as if on the front

21:07

end several players that were

21:10

anticipating more demand whether it's

21:12

Meta or X have immediately pivoted their

21:15

infrastructure where they're now leasing

21:17

out their supply because they haven't

21:19

been able to create the demand they had

21:21

initially anticipated. Do you think

21:23

there's a a chance that we might go from

21:25

what is anticipated being a supply

21:28

crisis to a front-end demand crisis

21:30

where there just a small number of

21:31

players creating front-end demand?

21:33

>> There's some data that have come out

21:34

from the two main companies on how many

21:37

tokens people are using per month and

21:39

that number has just been going crazy

21:41

through the roof.

21:42

>> So, I don't think there'll be a demand

21:43

crisis. At some point, there may be an

21:45

energy sector crisis. Right now, the US

21:48

has a huge share of all the world's

21:50

compute. There's no guarantee we keep

21:52

that position. So, to build out compute,

21:55

secure the supply of chips largely

21:57

through Taiwan, make sure that over time

21:59

we increase our own energy and number of

22:02

data centers against strong political

22:05

opposition. Those are big challenges. I

22:08

think we'll squeak by on all those

22:09

fronts, but again, you could definitely

22:11

see things going wrong.

22:13

All you would need is one decision from

22:15

the Chinese Communist Party and to

22:17

invade Taiwan, we'd be living in a very

22:19

different world, right?

22:20

>> On the demand for tokens, which is true,

22:23

I mean the to the the demand is is going

22:25

up significantly. Uh, one of the

22:29

criticisms or at least the concerns

22:30

though is that that token usage or that

22:32

token demand is currently being

22:35

subsidized by the AI AI labs. I mean

22:38

Anthropic, OpenAI, they are losing money

22:40

on every prompt that a user uh puts in

22:44

to the system. And so I think there is a

22:47

concern that if we were to not subsidize

22:50

this, if Silicon Valley, if VCs, if big

22:54

tech uh were not to basically support

22:58

the business models of OpenAI and

23:01

anthropic, then maybe it would be

23:03

different. maybe the the cost of tokens

23:06

uh of token usage would be higher and

23:09

people would be less inclined to use as

23:11

many tokens as they're using today. Um

23:14

what do you make of of those concerns?

23:17

Do you think that they're valid

23:20

>> in the short run? The price may well

23:22

need to go up for the reasons you

23:24

mentioned and we already see what is

23:26

possibly some rationing of compute. But

23:28

that said, if you look at data, how much

23:30

has the price of tokens fallen since,

23:32

say, GBT4? I forget the number, but it's

23:36

more than 100x. So, we're doing very

23:39

well on making the systems more

23:40

efficient. And we'll see, you know,

23:42

which curve outraes which other curve,

23:44

but it's not that there's no progress in

23:46

making the systems more efficient.

23:47

There's been incredible progress. But in

23:50

the short run, should the price go up?

23:51

Probably. But aren't costs going higher

23:54

for these companies? I mean, but my

23:57

understanding is that it's I mean, it's

23:58

hard to know because they're not public

23:59

companies. We can't look at their

24:01

audited financials, but my understanding

24:03

is that anthropic and open AI are

24:05

spending more uh each year.

24:08

>> Better model costs more. Yeah.

24:10

>> Right. Which would assume I mean to me

24:13

that means that we're not necessarily

24:16

going in the right direction in terms of

24:17

making this a an a profitable business

24:20

that is necessarily sustainable. To me,

24:22

it seems like we're technically going in

24:25

the wrong direction if we're talking

24:26

about profitability, which is we're

24:28

losing more money.

24:29

>> Well, I I'm not advising anyone to buy

24:30

any particular asset. But the worst case

24:33

scenario is that capital gives a massive

24:35

subsidy to consumers and we end up still

24:38

having the model and someone else buys

24:39

it. That's a great outcome for an

24:41

egalitarian say. I don't think that will

24:44

happen. I think the companies will do

24:45

fine. There's a reason why people talk

24:47

about anthropic at two trillion. I'm not

24:49

sure what the current number is for Open

24:51

AI, but I think it's over a trillion.

24:54

Uh, those are guesses, but those are

24:56

smart people with real money on the

24:58

line, and they're saying the companies

24:59

are worth trillions. On average, we

25:01

should believe them.

25:02

>> Why should we believe them in your view?

25:04

>> Because it's their own money on the

25:05

line. Once things go public, you'll have

25:07

the chance to short them, right? Uh,

25:10

you're free to do that. I'm free to do

25:12

that. I have no plan to do that

25:13

whatsoever. The way you really make

25:15

money in markets is to go long. I

25:17

believe in America. I believe in tech. I

25:20

think artificial intelligence works.

25:22

Again, I have no favorite horse in terms

25:24

of which particular company and I

25:26

definitely think they're not all going

25:27

to make it. But again, some of the big

25:29

ones really will. I guess just from the

25:31

economics perspective, you know,

25:34

regardless of whether someone wants to

25:36

go long or short because of how

25:39

dependent the US economy seems to have

25:42

become on AI or at least the AI

25:44

buildout, the amount that AI is that S&P

25:48

earnings growth is dependent on AI, uh

25:51

the amount that the entire stock market

25:53

is increasingly dependent on AI and and

25:57

the extent to which the ecosystem itself

25:59

does depend on those two companies does

26:02

that not make it bigger than

26:06

you know some will win some will lose

26:09

isn't it does I mean aren't we all

26:11

implicated whether we're long or short

26:13

or not well for one thing I don't think

26:15

the US economy is as dependent on AI as

26:18

those numbers indicate as you said

26:20

yourself it hasn't affected that many

26:22

jobs so there's a lot of money flows but

26:24

if somehow AI did not magically exist

26:27

the transformers paper had never been

26:29

written that money would flow somewhere

26:31

else and you would still have a lot of

26:32

GDP from some other set of activities.

26:35

So we're investing more in AI and less

26:37

in other places. That's a gamble of

26:39

course. Uh but it's wrong to think that

26:42

AI is currently this massive net

26:44

contribution to US GDP and that we would

26:47

have nothing else if it weren't there.

26:49

So in that sense we're pretty robust.

26:53

Now there's a transition issue. People

26:55

are expecting AI to do well. If that all

26:57

turned out to be horribly wrong, there'd

26:59

be a lot of disappointment, big capital

27:00

losses. Some of those losers have taken

27:03

out a lot of debt. There'd be solveny

27:04

issues. That'd be a big mess, right? But

27:07

as messes go, I don't even think it

27:09

would be close to the worst we've seen.

27:11

Not close, say, to 2008. What is your

27:14

biggest concern with AI then? I I mean

27:19

I'd be interested to hear what you're

27:20

optimistic about, but also, you know, if

27:23

it's if it's not a market event, some

27:27

sort of crash, some sort of correction,

27:28

that seems to be what a lot of people

27:29

are concerned about with AI right now.

27:32

What is it for you? What do you worry

27:34

about? What should people be talking

27:36

about more?

27:36

>> I think we see this already and it's how

27:38

disoriented people feel. The notion that

27:41

you cannot say to your kid or grandkid,

27:43

here's what you should do for a living.

27:45

Here's how you prepare for it. Here's a

27:47

more or less guaranteed path to success

27:49

if you're smart and you work hard. I've

27:52

grown up with that my whole life. People

27:54

like those asurances. I don't think they

27:57

exist in the same way they used to.

27:59

There could be someone else equipped

28:00

with AI or an AI equipped firm that

28:03

could out compete you. And who really

28:05

can be a consulting partner or a lawyer

28:08

or do the right thing in medicine and

28:10

you know excel at an Ivy League school

28:12

and walk into a job where they end up

28:14

earning $2 million a year and living in

28:16

Manhattan in a nice apartment. I think

28:18

those paths are now up for grabs. I

28:21

think there's a lot more opportunity for

28:22

the world as a whole, but there's a big

28:25

status and somewhat income disruption

28:27

for what is a favored class of people

28:30

and they don't know how to deal with it.

28:31

What they do is they keep on running

28:33

opeds in the New York Times about how

28:34

terrible this is. But they're not going

28:37

to stop it. At the very least, there's

28:39

Chinese open source. And I think so many

28:42

parts of human life, whether it's

28:43

entertainment or religion or just your

28:46

own conception of your intelligence,

28:48

it's going to change. And how we deal

28:50

with that, it's up to us. But

28:53

historically, we're not always good at

28:55

dealing with radical change. Do you

28:56

think that that could be potentially a

28:58

good thing to have a shakeup in the way

29:01

that you're describing?

29:02

>> Yes, but again, people don't like it and

29:03

the mere fact that people don't like it

29:05

is discomfort and that's a bad thing.

29:08

Then you have to ask, what will the

29:09

politics of this be? I don't have any

29:12

specific predictions. I just could see

29:14

it getting ugly and restrictionist and

29:16

polarizing. That would hardly be a big

29:18

surprise.

29:20

So again, you already see this with the

29:22

data centers. So I have big concerns.

29:24

>> Yeah. Trump recently put out a tweet on

29:26

data centers. I don't have the quote

29:28

right here in front of me, but he

29:30

basically said that if you try to stop

29:33

data centers, talking about this data

29:36

center backlash that we're seeing that's

29:37

becoming very very uh politically

29:40

popular in America right now, then

29:42

you're getting in your own way. That's a

29:44

recipe to become poorer, that we should

29:45

be pro- data centers. What do you make

29:47

of his comments and what do you make of

29:49

the politicization of AI and data

29:53

centers in America right now?

29:54

>> Well, it's one of these small number of

29:56

issues where I completely agree with

29:57

Trump. So, while I'm glad he's saying

30:01

it, I worry that Trump embracing the

30:02

cause does not in every way help it.

30:05

>> Fortunately, America has 50 states and I

30:08

think you'll always find at least five

30:09

governors willing to cut a deal. And a

30:12

lot of these governors seem to say very

30:13

anti anti-data center things and then

30:16

they go ahead and they still want the

30:17

deals. What they're saying or announcing

30:19

is not really binding. Like Josh Shapiro

30:21

in Pennsylvania, West Virginia is

30:23

welcoming data centers. There's a place

30:25

in southern Ohio. I think it was written

30:27

up in the New York Times today. So I

30:30

think it will happen, but it will be

30:31

very costly and there'll be lots of

30:33

bargaining and lots of politics. But

30:35

again, that's part of the beauty of

30:36

federalism. There are indeed 50 states

30:39

and other countries that are

30:40

federalistic, you know, Germany, Brazil,

30:43

uh they don't have close to 50 states.

30:45

It's a big advantage for America right

30:47

now.

30:47

>> Do you think that it's unreasonable to

30:49

be anti- data center? Do you think there

30:52

are merits to the arguments that

30:54

building data centers is a bad thing or

30:57

not at all?

30:58

>> I live in Northern Virginia right next

31:00

to Lowden County, which is ground zero

31:03

for data centers for the entire world.

31:06

It's the wealthiest county per capita in

31:08

the whole United States. The data

31:10

centers pay, I think, half of the

31:12

property taxes. There's no actual

31:14

problem. The cost of power, electricity

31:17

there, it's about at national averages.

31:19

It's actually slightly better. So, I'm

31:21

reluctant to say there are no valid

31:24

concerns. Oh, maybe you think they're

31:26

ugly or there's some slight humming

31:27

noise or but man, they don't create a

31:30

lot of traffic. They pay the bills. They

31:32

make your place wealthy. We've been

31:34

wanting re-industrialization for a long

31:36

time. Labor unions typically support

31:39

them. I say let's go ahead and do this.

31:42

What would the message do you think the

31:45

message should be uh to Americans? What

31:48

should if you were trying to make an

31:52

argument and trying to convince people

31:53

as to why data centers are ultimately a

31:55

good thing? Um how would you change the

31:59

messaging right now? Because clearly

32:00

it's not working for most people. I

32:03

don't think any messaging is working. I

32:05

think people don't trust their own

32:06

elites for reasons like COVID in 2008.

32:10

That's understandable. You can't

32:11

overturn those perceptions. Uh maybe

32:14

just talking about it less and having it

32:15

happen in a few places and stop trying

32:18

to persuade everyone. Some issues the

32:20

more you talk about it, you know, the

32:21

bigger the deeper in you dig yourself.

32:24

>> So you could try bribing citizens again

32:27

with 50 states. Let's try that in one or

32:29

two places. But sometimes that makes it

32:31

worse. the people say, "Hey, if this is

32:33

so great, why do you need to bribe me?"

32:35

But you could try it. I think some

32:36

states are trying that.

32:38

>> I think Meta is trying it. I think

32:39

they're paying out local communities to

32:41

get them on board. Reminds me of my

32:43

favorite movie, There Will Be Blood. Um,

32:46

I will pass it back to Scott. There's

32:48

two trains of thought and one is that a

32:51

small number of people and investors who

32:55

either own these assets or have the

32:58

ability to leverage AI to the advantage

33:00

of their enterprise are going to

33:01

aggregate a disproportionate amount of

33:03

the spoils resulting in greater income

33:05

inequality.

33:06

And then another line of thinking which

33:09

it feels like

33:11

I is incumbent in some of your comments

33:15

that this will attack the incumbents

33:18

and and be good or actually be a bit of

33:22

an equalizer for other less qualified or

33:25

less traditionally certified uh

33:27

professions. Do you come out on either

33:30

side of the spectrum there about what

33:32

you anticipate happening? I think the

33:34

biggest losers will be parts of the

33:36

upper upper middle class as I call them.

33:38

Now I love the upper upper middle class.

33:40

I'm a part of it. So it's the

33:42

professionals who do intellectual work

33:46

and those people are not going to

33:47

starve. They may have much lower status.

33:50

They may earn much less. Maybe they

33:52

can't cluster in Manhattan or San

33:54

Francisco. Uh by their own standards

33:56

their lives might be worse. I think big

33:58

winners will be teenagers, very small

34:01

companies, people who master AI, a lot

34:04

of immigrants, people from unusual

34:06

places like Eastern Europe or Turkey who

34:09

were never so bought into the old ways

34:11

of doing things and decide, hey, I can

34:14

get ahead by starting a company, two or

34:16

three humans and a bunch of AI agents,

34:18

and they make it work. Those people will

34:20

be very wealthy. They'll have to work

34:22

incredibly hard, but they're going to

34:24

challenge people across the board. So

34:26

there's pluses and minuses to all of

34:28

that, but there will be amazing

34:30

opportunities. But the people who now

34:32

have influence in America, I could call

34:34

them your listeners, will hate it on

34:36

that

34:37

>> incumbents. You said something I want to

34:38

double click on. Teenagers.

34:40

>> I uh direct a philanthropic fund and I

34:43

see many applications from teenagers,

34:45

often as young as 15, who are starting

34:48

companies with AI agents. Whether those

34:51

companies succeed this time around, I'm

34:54

not sure. But they are learning

34:55

incredible amounts. They are learning

34:57

things you cannot learn at Harvard or

34:59

Princeton. And I think they'll be the

35:01

wealthy people and the successful people

35:03

of the future. Teenagers. Yes.

35:06

They have no stake in the established

35:08

order. And they're learning these things

35:10

from scratch. And they just do it by

35:11

experimentation. Again, there's no one

35:13

to teach them to some extent. They teach

35:15

each other. I think we take for granted

35:17

that every

35:19

technological innovation or disruption

35:21

results in a small number of companies

35:23

that are able to capture trillions of

35:26

dollars in shareholder value. But

35:29

there's also been industries where the

35:31

the technological or the technical

35:34

uh results have been extraordinary. I

35:36

think of jet transportation, vaccines,

35:39

the PC where I don't think you I think

35:42

you could argue that they weren't able

35:44

whatever it was distribution or capital

35:46

weren't able to sequester shareholder

35:48

value to a small number of companies

35:50

that the big winner was us if you will.

35:52

I'm sitting here in LA. I think the

35:54

biggest the biggest the most accreative

35:57

technology of my life is jet

35:59

transportation and yet I think on

36:01

average in aggregate airlines and jet

36:03

manufacturers are just barely a break

36:05

even year uh uh to date. Do you think

36:09

it's possible that that the winners

36:11

might be all of us but we in fact

36:13

overstate the industry's ability to

36:15

capture shareholder value for a small

36:17

number of companies?

36:18

>> I think it's likely. I mean, it's funny

36:20

to me the same people who say it's all a

36:22

bubble turn around and five minutes

36:24

later, you know, want to say, "Oh,

36:26

income inequality will go up massively

36:28

because the companies will learn so

36:29

much." Truly fundamental technologies

36:32

like the printing press, fire, language,

36:35

they tend to be enjoyed by everyone, at

36:37

least over time. So, there's a lot of

36:40

medications. They're expensive at first,

36:42

then they become cheaper. I think that's

36:44

what we'll see with AI that eventually

36:46

through energy innovation will get token

36:48

costs down and it will be pretty cheap

36:51

and the people who benefit the most

36:53

might be people in Africa who right now

36:56

don't have access to quality services of

36:58

legal advice healthc care diagnosis and

37:00

so on and they'll be getting it very

37:02

soon or some are starting to get it

37:04

already they could be the very biggest

37:06

winners

37:06

>> you mentioned education I think a lot

37:08

about higher ed and I would argue that

37:10

higher ed has never been more important

37:11

and at the same I'm I agree with you

37:14

that there's an opportunity for younger

37:16

people to sort of skip the certification

37:18

line and start a company on little or no

37:22

capital that would have previously just

37:24

been not possible. Do you when you look

37:27

at higher education

37:29

um I see applications going up. I see in

37:33

my view college and critical thinking

37:35

becoming more important and then a lot

37:37

of people think that higher education is

37:40

going to be massively disrupted about by

37:42

AI. What are your thoughts on AI as it

37:44

relates to higher education?

37:45

>> I'm in higher education. I see schools

37:47

and universities that do that that are

37:49

doing very little or nothing to adjust

37:51

to the new reality. They just complain

37:54

about students cheating. They don't

37:56

rethink that they need to be teaching

37:57

very different things. On average, the

37:59

students often know more about AI agents

38:01

than their professors do. So what are

38:04

the professors supposed to teach? I

38:06

think it's a huge mess. I agree with

38:08

your view that education has never been

38:10

more important. But the role of actually

38:13

existing institutions in that is highly

38:16

uncertain. In the short run, they'll

38:18

become more and more about networking or

38:20

golf courses or marriage markets or

38:22

dating. That's fine in fact, but radical

38:26

changes are needed. And so far, I really

38:28

do not see those coming.

38:30

>> We'll be right back. And for even more

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39:53

>> We're back with Profy Markets.

39:55

>> What one or two industries do you think

39:57

will undergo the greatest shift both to

40:01

the upside and the downside from from

40:04

the penetration of AI?

40:05

>> Well, programming clearly has been

40:07

accelerated the most, right? There's a

40:09

lot of evidence for that. It's not a

40:11

hypothetical.

40:12

And I don't think humans will disappear

40:14

from programming, but they've already

40:16

taken on a fundamentally different role.

40:18

They're more like imprearios

40:21

and they're consulted in the meantime

40:22

like, oh, is this going in the proper

40:24

loop? Is the work actually being done?

40:26

Is this the thing I asked it to do? Over

40:28

time, more and more of that will be AIS

40:31

themselves monitoring. Uh, but that's

40:33

the clearest example of a very positive

40:36

change. Uh, the biggest negative I just

40:38

think will be cyber security. There'll

40:40

be a lot more hacks. There's plenty of

40:42

evidence for this already. Those cost

40:45

the world a lot. We'll spend more on

40:46

cyber security. Uh it won't be fixed

40:51

quickly and I think it's a very real

40:53

concern. We need a national

40:54

international effort to really firm up

40:57

all of our major institutions as quickly

40:59

as possible. But there's so many

41:01

institutions and relatively speaking so

41:04

little expertise. It's going to be a

41:06

very tough slog. It feels like we've

41:07

always been on the precipice of

41:10

this huge era of innovation in

41:13

healthcare that we keep getting seduced

41:16

by this age of discovery where we're

41:18

going to see an acceleration in

41:20

pharmaceutical innovation treatments.

41:23

Have you thought about AI's improvement

41:25

of healthc care outcomes? Do you think

41:27

it's overhyped, underhyped? What are

41:28

your thoughts?

41:29

>> I think about this a lot. In my view,

41:31

it's underhyped. I would make the point,

41:33

you know, the phrase AI, we think we

41:35

know what we mean, but in a number of

41:37

contexts, it's not that well defined. If

41:39

we just call it computational biology,

41:42

it already gave us the mRNA vaccine

41:44

against COVID in two days. That was an

41:47

amazing breakthrough that probably saved

41:49

millions of lives. So AI broadly

41:52

construed, I think over the next 40

41:54

years, we'll beat back many of the

41:57

things that kill people. At least I

41:59

think we'll live to 100. Scott, whether

42:01

you and I do, I'm less certain. This

42:04

anthropic notion that it will all come

42:06

in a few years time I think is badly

42:08

off. There's just a lot of testing and

42:10

also regulation and trials and

42:12

procedures that we both need to go

42:15

through, but at the very least we have

42:17

to go through. So for me, it's more like

42:19

a 20 to 40year project. But there's

42:21

already significant progress against say

42:23

pancreatic cancer. That too came from

42:26

computational biology. It's not from

42:28

Claude or OpenAI, but it's happening.

42:32

People don't really fully grasp this.

42:34

So, Ed, please save accordingly. You may

42:37

live to 100 and don't buy a motorcycle.

42:41

>> I want to talk about what what I'm

42:43

worried is one of the really big

42:44

downsides that doesn't get much

42:45

attention, and that is loneliness. And

42:48

that is some of the deepest pocketed,

42:50

most talented companies are using AI to

42:53

further sequester people, especially

42:55

young men, from their relationships and

42:58

their kind of offline lives. And that

43:01

we're going to end up with perfect

43:04

gaming, perfect entertainment, perfect

43:07

faximile of some sort of sexual

43:09

experience with porn.

43:12

And that the real the real downside or

43:14

the danger of AI is going to be uh

43:17

loneliness. And I read that 20 to 30

43:19

year old males are spending less time

43:21

outdoors in prison inmates. Do you worry

43:23

that we're evolving a new potentially a

43:25

new species of asocial

43:28

asexual youth?

43:29

>> I think we already had a loneliness

43:31

problem. We already had what you could

43:33

call a sex problem, a sex draw. Uh I

43:36

think our culture will adjust. People

43:38

don't want to be lonely. If you go to

43:40

Mexico, where I just was, the amount of

43:42

time people spend outside with each

43:44

other, it's much higher than in the

43:46

United States. We need to be more like

43:48

Mexico. Eventually, we'll get there. The

43:51

AI economic dividend will help pay for

43:54

that. But man, we actually have to do

43:56

it, right? It doesn't happen

43:57

automatically. So, do more things with

44:00

people. Coach little league or have

44:03

groups of people, you know, go on

44:05

picnics, whatever it has to be. date

44:07

more, ask women out more, whatever it

44:09

takes. We need a significant cultural

44:12

change very soon.

44:13

>> Tyler, if you were president or emperor

44:17

of America, if you had all the power,

44:20

um, what are some economic policies that

44:23

you would want to get done in America?

44:26

What are some of the problems that you

44:28

would want to address and how would you

44:29

like to address them?

44:30

>> Well, our current administration is

44:32

doing many things to make high-skilled

44:34

immigration much harder. I would do many

44:37

things to make it easier. Uh that is by

44:40

far the number one change I would make.

44:42

I think economists agree about that on

44:44

more or less a bipartisan basis.

44:47

We have potentially a fiscal crisis in

44:49

this country. My hope is that AI spurred

44:51

economic growth will get us out of it.

44:54

But the problem is assuming AI does very

44:56

well, take the most positive scenario as

44:59

it throws off these economic dividends,

45:01

politicians will spend those also.

45:03

They're just not responsible. So I don't

45:05

know how to get our government on a

45:07

responsible fiscal path. And even me as

45:11

dictator,

45:12

maybe as dictator I could do it, but I

45:14

don't see a feasible path from here to

45:16

there, you know, with either party or a

45:18

third party or anyway, the voters love

45:21

debt and deficits because it means they

45:23

consume a lot and pay lower taxes. It's

45:25

a big problem.

45:26

>> Do you think there's any way to solve

45:28

it? Um, is there any way that we would

45:32

ever get spending under control or is it

45:34

just pretty much a lost cause at this

45:37

point?

45:37

>> Well, we'll inflate away some of the

45:39

debt. I don't like that solution, but it

45:41

is partially effective in a funny

45:43

counterproductive sort of way. And then

45:46

my hope is politicians are asleep on the

45:48

AI dividend that it comes pulls us out

45:51

of our debt and deficits as it did in

45:54

the mid1 1990s by the way. and uh

45:57

politicians just aren't efficient enough

45:59

to be merrily spending it along the way

46:01

that it's a surprise to them. I think

46:03

it's quite possible that happens.

46:05

Certainly nothing close to guarantees,

46:07

but that's the most optimistic scenario.

46:10

>> Where does the US debt and US deficit

46:14

sit in terms of your concerns about US

46:17

the US economy and America's future?

46:20

Like how how far up the list does it

46:22

rank for you in terms of your largest

46:24

concerns? Well, it's in the top tier.

46:27

So, our debt is now about $40 trillion.

46:30

I understand our productive capacity is

46:32

very very high. We can carry that

46:34

amount, but at some point you have to

46:36

start paying parts of it back and we

46:38

just got keep on increasing the

46:40

percentage of our GDP or government

46:42

spending that goes to interest payments.

46:44

Real interest rates are much higher now

46:46

across the world. Our Fed is screwing up

46:48

somewhat.

46:50

We're in a very bad state. We've made

46:52

major mistakes. They were all own goals

46:55

not caused by say another major war for

46:57

the most part and we're going to suffer

47:00

for that. I sometimes say you know our

47:02

plan A is AI and we have no plan B.

47:05

>> Yeah. It often feels as though the AI

47:08

thing is sort of what a lot of our

47:10

leaders lean on as their I don't know

47:14

their bailout option. It's okay. We can

47:16

keep spending. we can keep continuing

47:17

down this seemingly very unsustainable

47:20

fiscal path because AI is going to help

47:23

us grow out of it. Um, but to your

47:26

point, I mean, it doesn't seem that

47:28

anyone is really taking this seriously

47:30

in Washington right now. What do you

47:32

make of the fact that Trump said as one

47:37

of his big policies, as one as part of

47:40

his platform that he would balance the

47:42

budget? He said it over and over again.

47:44

He seemed to convince a lot of people

47:46

that that was actually what he was going

47:48

to try to do. It was one of his uh

47:51

biggest points in his address to

47:53

Congress. Congress stands up and gives

47:55

them a round of applause and then

47:56

suddenly, yeah, we do get this news that

47:59

we've hit $40 trillion. Um what do you

48:03

make of that?

48:04

>> Well, it was all lies to begin with.

48:05

Anyone who believed it was a fool. For

48:07

one thing, we had a first term of Trump

48:09

right now. I don't blame him for CO.

48:11

That was unfortunate. But still there

48:13

was no effort made even before COVID to

48:16

address fiscal stability. And then Trump

48:18

had an earlier career as a businessman

48:20

where he was rampantly in debt and went

48:23

under a few times. So why expect fiscal

48:25

sanity from Trump or for that matter

48:28

from the Republicans or even the

48:30

Democrats today? Uh the real issue is

48:33

the voters want what we have and they

48:36

don't see there's a long run cost.

48:38

>> How would you grade the US economy right

48:41

now? uh given inflation, given

48:45

debt, but also given the fact that, you

48:47

know, GDP is growing, earnings are up,

48:49

AI is rolling on. Uh could you give it a

48:53

letter grade?

48:54

>> Overall, it's still pretty awesome, I

48:55

have to say. I know it sounds a little

48:57

crazy. Can I give it a B+? We're close

48:59

to full employment. We used to think

49:02

China would catch us in terms of

49:04

aggregate GDP. China's actually falling

49:07

behind. We've decisively pulled ahead of

49:09

Europe. Uh, we have problems. We're the

49:12

world leader in AI. We have by far the

49:14

best tech sector. We're shooting

49:16

ourselves in the foot 30 different ways.

49:20

Corporate earnings are great. Like you

49:21

said, stock market is more than fine. No

49:25

recession so far and it's full steam

49:27

ahead. That makes me nervous itself

49:30

because there are inevitably recessions

49:32

and corrections, but if you want a

49:34

grade, the grade is not a bad one. Are

49:36

you surprised by how long this things

49:40

have appeared to be I mean at least from

49:42

a market perspective how long the market

49:45

has been rallying uh how long it's been

49:48

since we've had a a serious recession.

49:51

>> Yes, I'm surprised I've lost a lot of

49:53

money. I should have been way more

49:54

heavily into equities. I was a fool.

49:57

Exante I don't feel it was a mistake but

50:00

expost I was way too worried.

50:01

>> What do you think was the cause of that?

50:04

Now, some of it is the prospects of AI,

50:06

but I just think there have been

50:08

fundamental transformations that favor

50:10

countries with scale. And the only

50:13

countries with real scale are the US and

50:15

China, maybe someday India. And that's

50:18

kept us going and been an extra uh kick

50:21

in the pants in a positive way. And our

50:24

tech sector has done great. And this is

50:26

still the number one place to go for

50:28

talented people. And there's this other

50:30

fundamental change in the global economy

50:32

that I had underestimated. And that is

50:34

how quickly the notion of I want to move

50:36

to the US and start a business spread.

50:39

It's always been a thing but it just

50:42

came to more parts of the world more

50:44

quickly than I would have thought. I

50:46

mean look at the number of people from

50:48

India who are either CEOs or done

50:50

startups that have just done great. How

50:52

quickly that spread again surprised me

50:55

in a very positive way. the high-skilled

50:57

uh immigration debate that you talk

50:59

about and Trump's it appeared that he

51:02

was interested in it and then kind of

51:05

went back on that and you said that you

51:07

would be a lot more welcoming. Um what

51:10

are the dynamics you think are driving

51:11

that? I think a lot of people believe

51:12

that it's largely racism. I think a lot

51:16

of people think that. Um but perhaps

51:18

also this idea that we don't want uh to

51:21

be recruiting people from other nations

51:23

to come in and and take jobs that should

51:25

be for Americans. Uh what do you make of

51:28

of sort of the political dynamics at

51:31

play there? I believe Trump outsourced

51:33

that policy to Steven Miller and that

51:36

Steven Miller genuinely believes that if

51:38

you push out all these foreigners,

51:41

what you might call nativeborn white

51:43

Americans will rise to the occasion and

51:45

do all the kinds of great things like

51:46

they did in the 1950s and60s.

51:50

And uh it will be good for this country

51:52

to go back somewhat to how we were

51:55

culturally, ethnically, linguistically

51:58

in terms of religion, Christianity.

52:01

uh I don't think you can get back to

52:02

that earlier world. I think the idea of

52:05

attracting more and more of the best

52:06

foreigners and that they in many ways

52:08

embody American values in the true sense

52:12

at least as well as our nativeorns do is

52:14

a more promising path forward. But look,

52:17

it's a disagreement and I just think uh

52:19

the Trumpers have very strange cultural

52:21

views without really much evidence

52:23

behind them and they've ended up being

52:26

very nasty to a lot of foreigners and

52:28

we're just we're really not getting

52:30

anything for it.

52:31

>> Do you think would it be a fair

52:32

characterization to say that you believe

52:34

that at least a significant part portion

52:38

of our economic policy has been driven

52:40

by

52:42

nivism

52:43

bordering on racism? our immigration

52:46

policy. Yes.

52:47

>> Does that concern you?

52:48

>> Well, it's my number one worry. It's the

52:49

number one thing I would change. So, I

52:52

think it's very bad. My fear is the

52:55

Democrats won't reverse it. I know they

52:57

say they will, but I'm not sure they

52:59

mean it. And immigration is often an

53:02

issue they would just rather not talk

53:03

about. So, lurking in the background is

53:06

this risk that it may be somewhat

53:09

permanent. If you imagine a world where

53:11

AI looking back in retrospect is

53:14

increasing productivity does not create

53:17

the types of the upside's much greater

53:19

than the downside. What do you think are

53:22

the biggest sources of friction from

53:24

here to there? Is it too much

53:27

regulation, too little? Is it uh

53:30

insufficient power grid? Is it uh cyber

53:34

security threats? You know, lack of

53:37

cooperation. What do you see as the

53:39

biggest obstacles to this kind of brave

53:42

new world of AI?

53:43

>> I think the biggest obstacle is just at

53:46

the institutional level, people really

53:48

don't know how to use it. We all

53:50

freelance with AI. We ask it questions,

53:53

can write things for you. It can solve

53:55

problems for you. So you have a company

53:58

or a nonprofit whatever for each

54:00

individual uses blog or chat GPP. They

54:04

become more productive. But the idea

54:06

that you have business flows at the

54:08

institutional level where AI contributes

54:11

significantly to productivity, we're way

54:13

behind on that except again for

54:15

programming. And I think that will take

54:17

a long time. There's no one really who

54:19

can teach it to you. It may happen by

54:21

having startups slowly replace incumbent

54:24

firms because startups will are more

54:26

likely to be AI native and start with

54:29

small numbers of people and do things

54:30

with AI from the beginning. But try

54:33

going into some big company and telling

54:34

people they need to change everything

54:36

they do. You know, good luck with that.

54:38

I think that's by far the biggest

54:40

barrier. I don't doubt we'll

54:41

overregulate it at some point, but we

54:43

overregulate everything. Like we America

54:46

actually can deal with that within

54:48

reason. Uh just like, hey, what do we do

54:51

next is the biggest problem.

54:53

>> And when you think about when you try to

54:57

Do you have kids, Tyler?

54:59

>> Yes. one daughter, she's 36, two

55:01

grandkids, a third on the way.

55:02

>> Okay. So, imagine, and you referenced

55:04

this earlier, imagine your grandkids are

55:08

going into junior high and high school,

55:09

and you're trying to prepare them given

55:12

what I thought you said was really

55:14

powerful about the traditional paths are

55:16

no longer guaranteed or they just look

55:19

more curved and less, you know, quite

55:21

frankly, more opaque.

55:23

What skills would you emphasize that

55:27

young people develop? And there's no way

55:30

to futureproof yourself, but make it

55:32

most likely that you in fact have um or

55:36

can register prosperity. What how would

55:38

you how would you coach young people

55:40

thinking about the skills they need to

55:42

acquire?

55:42

>> I get this question multiple times every

55:44

day. I never feel I have great answers,

55:48

but one thing many people can do is just

55:50

keep current on AI. That's no guarantee

55:53

of anything, but it's better than

55:55

falling behind. It does involve a lot

55:58

does take a lot of involvement because

55:59

it changes all the time. But being

56:03

curious, learning initiative, and

56:05

learning how to retrain yourself and

56:07

learning how to network, those have

56:09

always been important, but I think

56:11

they're truly the skills of the future.

56:13

So, I would encourage anyone, whether my

56:16

grandkids or not, to invest in those.

56:18

Like right now, everyone has the perfect

56:19

cover letter, right? So you apply it

56:22

means nothing like the system's broken.

56:24

Who is it who can vouch for you? So

56:26

networks and connections are far more

56:28

important. Learn how to do that. Learn

56:30

charisma. Learn how to command a room.

56:32

Learn how to give a talk.

56:34

>> Tyler Cowan is an economist, author, and

56:36

podcaster at the Marta Center at George

56:38

Mason University. As the faculty

56:40

director of the Marta Center, Tyler

56:42

co-created Marginal Revolution

56:44

University, a free online economics

56:46

education platform that has reached

56:48

millions. He's also founded Emergent

56:51

Ventures, a multi-million dollar fund to

56:53

support underrated people and projects.

56:55

Tyler has blogged every day at Model

56:58

Revolution since 2003, helping to make

56:59

it one of the most widely read economics

57:01

blogs in the world. He is the

57:03

bestselling author of nearly 20 books

57:05

and has been a regular columnist at the

57:08

New York Times, Bloomberg, and now the

57:10

Free Press. Tyler, we really appreciate

57:13

your time. Thank you.

57:14

>> Thanks, Tyler.

57:14

>> My pleasure. Thank you.

57:17

Thank you for listening to Prof Markets

57:19

from Prof Media. If you liked what you

57:21

heard, give us a follow. We'll be off

57:23

for Labor Day, but join us for a fresh

57:25

take on markets on Tuesday.

Interactive Summary

The video features a conversation between the hosts and economist Tyler Cowen. They discuss the current state of AI, addressing concerns about a potential market bubble, the sustainability of AI spending, and the impact on labor markets. Cowen argues that while market volatility and company failures are to be expected, the technology itself is transformative. The discussion also covers the societal challenges brought by AI, such as workforce disruption, the importance of data centers, and the necessity for young people to adapt to a changing landscape. Finally, they touch on broader economic policy, specifically the need for increased high-skilled immigration and the challenges of the current U.S. fiscal trajectory.

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