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The REAL Reason Companies Have Stopped Hiring

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The REAL Reason Companies Have Stopped Hiring

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0:00

I mean, one of the most important

0:02

subjects at the moment in society is

0:04

artificial intelligence.

0:06

And we you probably saw recently Eric

0:07

Schmidt did a commencement speech in

0:09

front of thousands of students and every

0:10

time he said the word

0:11

>> yeah.

0:11

>> Every time he said the word AI, um, one

0:13

of the things that Anthropic, who are

0:14

one of the leading AI companies, said

0:16

recently is that entry-level jobs are at

0:18

risk. And I've got this graph here

0:20

showing the decline of entry-level job

0:23

postings. I believe it was on LinkedIn,

0:25

um, pulled from somewhere. It shows that

0:28

they're consistently dropping and

0:29

dropping and dropping. AI is I think

0:32

about it so often. I was up late last

0:34

night trying to think through some of

0:35

this stuff because Anthropic released a

0:37

report yesterday showing that the AI

0:39

models will be able to improve

0:40

themselves theoretically in the future

0:42

and what this might mean.

0:45

How disruptive do you think AI is going

0:46

to be as it relates to job losses?

0:48

>> You know, I don't think Bernie Sanders'

0:50

latest idea is terrible.

0:51

>> The US will own 50% of all the AI

0:53

companies.

0:53

>> It is absolutely true that AI has

0:56

monetizing for free humanity's

1:00

intellectual property. And a few people

1:02

are going to directly benefit from that.

1:04

And I think that,

1:05

um, in the same way that Norway created

1:08

a sovereign wealth fund with this

1:10

enormous asset that they had, uh,

1:12

creating a sovereign wealth fund with

1:14

50% of the value created by AI and

1:18

recycling that into, uh,

1:20

I think it's unclear exactly how those

1:22

benefits should be should be recycled,

1:24

but trying to find a way to make some of

1:27

that value a cushion for the disruption

1:30

that it will inevitably cause, I don't

1:32

think that's a crazy idea.

1:34

>> It's a good idea for China and the US.

1:36

>> Yes.

1:37

Yes.

1:38

>> They're not for anywhere else

1:39

necessarily. It's not going to help

1:40

Senegal or

1:42

Southampton much.

1:43

>> No, in fact, it'll damage a lot of those

1:44

places. You know, like the Philippines

1:47

has benefited enormously by being the

1:49

outsourced back office, uh, for a lot of

1:52

small businesses that AI can now do a

1:54

lot of those those, uh, those jobs. Um,

1:57

one of the things that I always come

1:59

back to is the idea that say the UK has

2:01

5.7 million businesses, we have a

2:03

million unemployed people. We need 1/5

2:06

of the businesses to employ one person.

2:09

AI does actually make your business

2:11

better. Like AI is really good at

2:12

helping you with your marketing. AI is

2:14

great at helping you do legal contracts.

2:16

There are 100 ways that AI could

2:18

actually make 5.7 million businesses a

2:21

little bit better to the point where

2:23

they want to hire someone. And if we can

2:25

incentivize those things to happen,

2:27

businesses are trained on how to use AI

2:29

to their advantage, and tax breaks for

2:31

small businesses that are hiring. And we

2:33

will you know, that there's actually 5.7

2:35

million businesses and a million

2:36

unemployed people. That's a good there's

2:38

a good match there.

2:39

>> Uh you know, a lot of people have been

2:41

talking about AI agents.

2:43

And what an AI agent can do for anyone

2:45

that doesn't know is it can go on your

2:47

computer and it can get any task you

2:48

want done on the computer. Um whether

2:51

that's you know, editing tasks or

2:52

whether it's you know, manual data entry

2:54

tasks. Whatever it is, it can click

2:56

around on the computer and do things. A

2:58

lot of the entry-level roles we're often

3:00

given are that kind of work. I think my

3:02

entry-level entry-level job after I

3:04

dropped out of university was kind of

3:05

doing that kind of thing. There was also

3:07

a little bit of a sales component where

3:08

I'd cold call people. Um AI can now do

3:11

the cold calls, too. And increasingly,

3:12

if we just play the rate of development

3:14

forward, we'll be able to do those

3:15

things. So, if these businesses get more

3:17

and more efficient, um again, it comes

3:19

back to this entry-level point is

3:22

what what role will entry-level team

3:25

members have in these kind of companies?

3:27

>> So, what's interesting for me, I have a

3:29

group of companies, small businesses,

3:31

dynamic small businesses. We've

3:32

implemented AI in all of them, and as a

3:35

result, we've hired people.

3:36

>> Who have you hired?

3:37

>> So, entry-level people?

3:38

>> We've hired some entry-level people who

3:40

are augmented by AI, so they become more

3:42

valuable because of AI. But like things

3:44

like appointment setting, we've ended up

3:46

hiring more sales people because we get

3:48

more appointments. We we use it with our

3:50

marketing, and we end up hiring people

3:52

who can actually have those final

3:54

conversations with people. At the very

3:56

core of my organizations, we have an AI

3:58

layer and the AI layer has context and

4:01

skills and models and security layer,

4:03

right? All all in there and it spits out

4:05

amazing information and data and reports

4:08

and tells us who to talk to and why to

4:10

talk to them and what to talk to them

4:11

about. All these things are happening

4:12

because of AI.

4:13

>> But it doesn't get around the point that

4:14

like if you think about Uber, Dara has

4:16

been pretty clear that the 9 million

4:17

drivers they have, I think it is, are

4:19

going to leave their jobs in the future.

4:21

If you think about the the other sort of

4:23

white collar professions we've

4:24

described, they those roles won't won't

4:27

exist in the future. Well, I should say

4:29

those roles will be will be will be

4:30

changed.

4:31

>> Changed. Correct. If I put on my more

4:33

optimistic hat, it the thing is is that

4:36

all businesses operate in a competitive

4:38

environment and there are two ways to

4:41

compete.

4:42

One is to be cheaper, the other is to be

4:45

better.

4:46

Right? And the thing about AI

4:49

is that yeah, there are tasks that you

4:53

can automate away,

4:55

but one person

4:58

with good AI tools may be able to do the

5:01

job of five.

5:02

>> Mhm.

5:03

>> Right? [clears throat]

5:03

And yeah, you could eliminate that job

5:06

or you could keep that person, give them

5:08

the right tools and out compete your

5:10

competitors.

5:11

>> The right tools.

5:12

>> The right tools.

5:13

>> I think there's an assumption that will

5:14

>> I mean, this is of course what happened

5:15

with computers, right? I mean, I'm I am

5:18

older than you guys. So, I remember I

5:20

remember when calculators hit.

5:23

You had to be there to realize how

5:25

freaked out people were about

5:28

calculators.

5:29

Right? Like people were talking about

5:31

like well, what are the accountants

5:32

going to do and

5:34

and and will kids learn math anymore? I

5:36

mean, it was it was like extremely

5:39

controversial to bring a calculator to

5:42

to to school. And then along came

5:45

computers and the truth is that

5:47

computers didn't reduce the amount of

5:49

work that people did. They increased the

5:51

amount of work that people did. And I do

5:53

believe that there are ways in which AI

5:55

is probably going to do that. And so,

5:57

the job loss may not be as apocalyptic

6:00

as it now feels like it may be because

6:03

again, at the end of the day, you have

6:06

two ways to choose to compete. If you

6:09

you know, you can get rid of somebody

6:12

and do X, but you could keep that person

6:14

and have them do 5X and outcompete, you

6:17

know, your competitors in another

6:19

dimension. I think that that will be

6:21

something that people are likely to do.

6:23

Doctors are just going to be better

6:25

doctors.

6:25

>> I think I I definitely agree that

6:27

there's going to be this sort of

6:28

augmentation of certain individuals. I

6:30

think maybe the difference between like

6:32

calculators or computers versus this is

6:35

AI is coming into a technological

6:38

economy

6:39

and it is coming in with instant scale.

6:43

In a way that when Anthropic shipped

6:45

their new model last week, it went to

6:48

all of us at once, everywhere in the

6:50

world. We were all boom, step changed.

6:53

With computers, I remember the day that

6:55

like my dad ordered the first computer

6:56

for our house, and we waited for weeks

6:58

and weeks and weeks, and then we got it.

6:59

It was super expensive to get one. We

7:01

unboxed I remember us all stood around

7:03

it looking at and it was like this

7:04

Windows 95 machine that had like no

7:06

memory on it.

7:07

Um so, the distribution the sort of

7:08

disruption was much slower. The pace is

7:12

is much slower.

7:13

>> Right.

7:13

>> And I understand that like with my with

7:16

our team, there's no intent We have no

7:17

intention at all to let anybody go

7:19

because of AI. We're reskilling people,

7:21

training people. However, would we end

7:24

up hiring less people, especially in the

7:27

near term than we would have otherwise?

7:29

I think that's maybe conceivable.

7:31

>> Yeah.

7:31

>> Um and a lot of companies I think are in

7:32

that position. Well, I actually was

7:33

speaking to someone yesterday and they

7:34

said, "We're just letting the natural

7:36

attrition in our call center

7:39

take care of the shift." Which means

7:43

they they have they lose 25% of people

7:45

from their call center naturally.

7:47

They're just not hiring other people

7:48

back in. And actually Klarna's CEO said

7:50

the same thing. He said, "We're just

7:51

letting the attrition take care of it."

7:52

>> I'll give you another example though,

7:54

just to counter that. Um I work with a

7:56

husband and wife couple in the north of

7:58

England who they had a little video

8:01

production agency and like one or two

8:04

people who did a little bit of

8:06

contracting with them.

8:07

Uh they used AI to create a piece of

8:09

software. And that piece of software

8:11

uh helps automate script writing and a

8:13

few of the things that they do. Um they

8:16

launched a waiting list for this. They

8:17

got 5 and 1/2 thousand people to join

8:19

the waiting list. They then signed up

8:20

their first 1500 clients to a piece of

8:23

software that cost almost nothing for

8:24

them to build in 4 months. Um and now

8:26

they're hiring a team of 10 people. And

8:29

this is a husband and wife who had a

8:31

small constrained business who are now

8:34

uh building out a bigger business. And

8:36

this is something that could never have

8:38

happened. They haven't had to raise

8:40

billion

8:42

millions of dollars. They haven't had to

8:44

hire 30 40 people. So this this tiny

8:47

little SAS opportunity is suddenly

8:49

possible because of AI. And it would

8:50

take take that AI away and that

8:53

fast growth dynamic little businesses is

8:55

>> Yeah, I think anecdotally I could come

8:57

up with lots of examples as well where

8:58

particular people are highly

8:59

entrepreneurial. They come across an

9:00

opportunity. But there's this broad if

9:02

you just zoom out on the way that people

9:04

generate value in the economy at the

9:05

moment, so much of that's going to

9:07

change and it's going to be quite quick,

9:08

it feels like.

9:09

>> Of totally.

9:10

>> And I don't know what you do about like

9:11

what do you do about that sudden shift?

9:13

>> Well this this happened in the Jevons

9:14

paradox. The person who had a tractor

9:17

displaced a hundred people who were in

9:19

the field. And those hundred people went

9:21

into the city looking for work all at

9:23

once. And it was Charles Dickens wrote

9:26

The Tale of Two Cities. He wrote

9:28

Oliver Twist. Guess who else came out of

9:31

Jevons paradox? Our good friend Karl

9:33

Marx who came up with the most toxic

9:35

ideas ever created and written down.

9:37

Right? He came off the back of the

9:38

Jevons paradox.

9:39

>> do you do about it?

9:41

>> Uh UBI?

9:42

>> I'm not a big fan of UBI at the moment.

9:44

>> Isn't that kind of what this 50% Bernie

9:46

Sanders thing would do?

9:47

>> Well, it's it's sovereign wealth fund,

9:48

basically. But you have to find a way to

9:51

help manage through this transition, and

9:53

you have to, I think, depend on the

9:55

value create Look, the the whole the the

9:58

whole valuation that it AI is predicated

10:01

on

10:02

is job disruption.

10:04

>> Yes. You can't

10:05

>> You can't get to those numbers unless

10:06

you're displacing lots of jobs.

10:08

>> Exactly.

10:09

>> And and if that's true, then we should

10:13

grab some of that value that is created

10:16

and recycle it into the economy to try

10:18

to cushion the disruption that it

10:20

creates.

10:20

>> This is a bit of a socialist idea idea,

10:22

right?

10:22

>> I don't call that socialism.

10:24

>> What do you call that?

10:24

>> I don't know. Just common sense?

10:26

>> But wouldn't that broadly apply to all

10:28

all companies and rich people if there's

10:30

if they are disrupting the economy and

10:32

taking an unfair share of that

10:34

disruption? Should we not just grab and

10:36

recycle back in?

10:37

>> But that's the That is the basis upon

10:39

which every high-functioning democracy

10:40

in the in the world operates. I mean,

10:43

every high-functioning democracy in the

10:45

world has progressive taxation, labor

10:47

standards,

10:48

>> There's a difference between

10:49

>> seizing private property, uh which would

10:52

be a socialist way of doing things and a

10:54

communist way of doing things,

10:56

and

10:57

owning strategic assets, which

11:00

>> Which are private property.

11:01

>> So, for example, the the Dubai

11:03

government owns the uh physical hotel

11:07

buildings that uh that run Dubai, and it

11:10

leases those out to hotel operators, but

11:13

it keeps money in its sovereign wealth

11:14

fund because it says, basically, a big

11:17

part of Dubai is that we own these kind

11:19

of land assets.

11:20

>> So, do you think we should go and take a

11:23

a portion of these companies?

11:24

>> Well, the difference was that the Dubai

11:26

government actually developed those

11:27

assets.

11:28

>> Right, but we're we're already too far

11:29

down the the with within a capitalist

11:31

society like the United

11:32

>> might say we might say that data is the

11:34

new oil and data is a common good and it

11:36

is a common asset that has been um

11:38

sequestered uh illegitimately by these

11:41

companies. So, therefore, you're not

11:42

seizing what they created. You're You're

11:44

basically saying, "I'm sorry, but you

11:46

need to pay a license back to this

11:48

sovereign wealth fund because you're

11:50

using a common asset that you were able

11:52

to essentially seize

11:54

>> it from You stole it from Africans and

11:56

British people. You stole it from people

11:57

in Australia. You stole it from people

11:59

in Canada.

12:00

>> The biggest issue that we're having is

12:01

that we're actually the nature of the

12:03

entire economy is changing. So, this

12:05

happened 250 years ago where the nature

12:08

of the economy was land and we had an

12:09

economic system called feudalism and

12:11

colonialism. And then the nature of the

12:14

economy was industrialization

12:16

and we had a economic system called

12:18

socialism and capitalism. And now the

12:20

nature of the economy is actually

12:22

fundamentally changing. So, in

12:23

economics, there's four factors of

12:24

production: land, labor, capital,

12:25

enterprise. We're now swinging like a

12:27

pendulum from land through capital,

12:30

labor, and now we're actually in an

12:31

enterprise economy and we need some sort

12:34

of economic system that reflects the

12:35

reality of how money and wealth is made

12:37

at the

12:37

>> that? Is that go to open AI, take 50% of

12:40

that company,

12:42

and then pay out the profits of that 50%

12:45

to the people?

12:46

>> I'm always skeptical of any socialist

12:48

ideas. If it comes from Bernie Sanders,

12:50

I'm skeptical.

12:50

>> Okay, but Bernie Sanders is not a

12:51

socialist.

12:52

>> Like he he he he he he he he he he he he

12:53

he he he he he he

12:54

>> He he says he's a socialist.

12:55

>> Socialism is his word.

12:57

>> Socialist No, socialism is

13:00

the you know, the government owning all

13:02

the means of production, right? The

13:04

Look, the there are a million forms of

13:06

capitalism,

13:07

right? We have we i- i- i- i- i- i- i-

13:08

i- i- i- i- i- i- i- i- Every country

13:10

operates slightly differently. And there

13:13

I don't think that Bernie Sanders is

13:16

saying

13:17

that we should abandon markets.

13:20

What he is saying is we should manage

13:23

markets for the public benefit, not

13:26

exclusively for the benefit of the

13:28

owners of capital. And I think that's

13:30

really different.

13:31

>> with like an Amazon, they're using the

13:33

roads.

13:34

>> Yeah.

13:35

>> And the infrastructure.

13:36

>> Correct.

13:36

>> So, would you go take 50% of those

13:39

companies as well for public benefit and

13:41

then pay it out to

13:43

>> No, but

13:43

>> the citizens.

13:44

>> We effectively do take part of them in

13:47

the form of taxes, right? Now Now Now

13:49

the taxes that we impose on those

13:51

companies, I would argue and

13:53

Dan may may agree are insufficient.

13:56

>> Mhm.

13:56

>> They do not accurately reflect the value

14:00

that we give them.

14:02

They don't return equal value that we

14:04

>> increase the taxes on companies like

14:06

Amazon, you both agree?

14:07

>> Uh well, Amazon is very successfully

14:10

avoiding taxes.

14:11

>> Yes.

14:11

>> Um

14:12

>> So, would you agree to increase the tax

14:13

>> we need to have we need to close tax

14:15

loopholes. We need to make sure that

14:16

they're paying taxes like all other

14:18

companies uh that operate within the

14:20

economy.

14:20

>> Like the guy at the pub that you're

14:22

talking about pays, right?

14:24

>> Exactly. Exactly.

14:25

>> And and the retailers and all that sort

14:27

of stuff who are in competition with

14:28

Amazon.

14:29

>> Right.

14:29

>> Look, one of the biggest issues that we

14:30

have is we have widespread incompetence

14:32

in government, and I'll give you a quick

14:34

stat on this.

14:35

In the UK government, you are 10 times

14:37

more likely to die than to be fired for

14:40

poor performance, and the UK government

14:43

fires people at 1/600 the rate as normal

14:46

businesses for incompetence. So, we have

14:49

an accumulation of massive incompetence

14:51

in government. So, the idea you can come

14:53

up we can come up with all the best

14:55

ideas under the sun at this table. We

14:57

have a fundamentally incompetent set of

15:01

people who have misaligned incentives.

15:06

Uh we have basically a revolving door

15:08

between

15:09

financial industrial complex, technology

15:11

industrial complex, and then

15:13

>> Well, the you Singaporean government,

15:14

they basically said that we're going to

15:17

have a very high degree of meritocracy

15:19

in government that essentially we

15:21

promote and fire based on outcomes and

15:23

merit merit.

15:25

>> Singapore is a miracle of governance.

15:27

>> Amazing governance.

15:27

>> It's a It's a miracle of governance, but

15:29

it is a very small place.

15:31

>> Yeah, totally.

15:33

>> Perhaps the only place in the history of

15:34

planet Earth that has benefited from

15:38

uh a well-meaning dictator, right? It's

15:41

It's It's

15:42

It's an astonishing story of capability,

15:45

competence, for- foresight.

15:48

>> Um so, what is the solution with this AI

15:50

revolution? It's I think we all agree

15:52

that there's going to be job disruption.

15:54

And there's going to be a new type of

15:55

job. There's going to be probably a

15:57

delta of people transitioning to those

15:59

new types of jobs.

16:00

Um I I've said this before, but I even

16:02

noticed that within our recruitment

16:03

processes now, we are really looking for

16:05

people that have a certain set of

16:06

skills.

16:07

>> We always ask.

16:08

>> And it's harder and harder and harder to

16:09

find those people.

16:11

Um

16:11

>> Well, that's training. That's education

16:13

and training.

16:13

>> It is.

16:14

>> The

16:14

The school system needs to produce

16:16

people that you would want to hire.

16:18

>> Yeah, and that takes a lot of time.

16:20

>> When I ask the question, "How deep are

16:21

you in the AI rabbit hole?" And anyone

16:23

who says, "Oh, a lot." I'm like, "Okay,

16:25

join the team."

16:26

>> And And also, if you think about

16:27

humanoid robots, Elon Musk's pay packet

16:30

mandates him to deliver millions of

16:32

humanoid robots, or else he doesn't get

16:33

his big pay packet. We think about

16:35

robotics and humanoid robots coming

16:37

through. We watched the other day Figure

16:39

AI release this video showing a humanoid

16:41

robot sorting packages on a production

16:43

line for 8 days straight, beating a

16:46

human sorting those packages on the

16:47

production line by car in Los Angeles

16:50

now drives itself, and as do the taxis,

16:52

and there's a huge race to make

16:54

autonomous vehicles. Um I'm sure there's

16:57

new jobs created, and I understand in

16:58

foresight it's hard to understand what

16:59

those will be. Um I assume there'll be

17:01

more human jobs, more sales jobs.

17:03

>> My only thing that I can say is that it

17:05

the future is small businesses. It's

17:08

It's small teams of 10 people making

17:10

YouTube channels. It's small teams of 10

17:11

people making software. It's like the

17:14

When you You millions and millions of

17:16

little small businesses. Everyone's

17:18

happier.

17:18

>> But if you read what Anthropic released

17:20

yesterday, they're making the claim that

17:22

actually we're getting to a point where

17:23

it will be an individual with a

17:27

team of agents who can now make a

17:28

trillion-dollar company without hiring a

17:30

single person.

17:31

And actually when you said about making

17:33

software, making that they would they

17:35

might argue that that will be agents

17:36

making that software. Anthropic said

17:38

that the amount of code each individual

17:40

is producing on their own is eight

17:42

times. And this one particular quote

17:43

which I actually screenshotted on my

17:44

phone last night that comes from an

17:45

engineer at Anthropic

17:47

who was saying they feel useless because

17:49

now they they say they haven't written a

17:51

line of code in months and months and

17:52

months. This Anthropic engineer was

17:54

basically saying like, "I come to work.

17:55

This agent writes the code for me, and I

17:57

kind of sit and watch, and I feel

17:59

useless."

18:00

Um so all those examples you gave

18:03

>> Okay, but what would happen in that

18:04

situation is you would have a massive

18:06

deflationary effect. The cost of if if

18:08

there was one person doing all sorts of

18:10

things in the economy, then the cost of

18:12

that would go to the cost of the

18:13

electricity to run it, right? So,

18:15

massive deflationary. And then the

18:18

question becomes, "Well, what does

18:19

everyone do, right? What do we all do?"

18:20

>> Yeah.

18:21

>> We do human things, right? Humans always

18:23

come up with things to do with each

18:24

other. Uh like if I was to tell my

18:26

grandfather that there is a job called a

18:28

personal trainer who takes you to the

18:30

gym and counts your reps, right? My

18:32

grandfather would go, "That's insane."

18:34

And I say, "Oh, there's 50,000 personal

18:36

trainers in gyms all over the country."

18:38

So, there are always these crazy new

18:41

jobs that get created. I look at what

18:42

trust fund kids do, right? Cuz a lot of

18:44

trust fund kids, they go they they don't

18:46

have to worry about money, and they

18:47

don't have to worry about resources, and

18:48

they go find something to do, and it's

18:50

always weird.

18:51

>> We're going to traverse through, you

18:53

know, potentially the jobs we have now

18:55

involuntarily

18:57

go through this transition moment where

18:59

I think history's quite clear on what

19:00

happens in these transition moments. It

19:02

gets ugly. It gets ugly.

19:04

>> Yeah.

19:04

>> And then we'll come to, you know, what

19:06

what I'm hearing is that you're saying

19:07

that we will come to some kind of utopia

19:09

on the other end of this.

19:10

>> No.

19:11

>> No.

19:11

>> No.

19:12

No, I don't think I don't think there's

19:14

going to be utopia.

19:15

>> What do you think?

19:16

>> look, I I don't think utopias exist. I

19:18

do think that markets are the greatest

19:20

social technology ever invented for

19:23

creating prosperity and for ennobling

19:25

the human spirit. But that is not

19:27

because markets are efficient allocators

19:29

of scarce resources, which is the

19:30

conventional view. Markets are an

19:33

evolutionary system that enables groups

19:35

of people to come together and solve

19:36

complex problems. And solutions to human

19:39

problems is what prosperity actually is.

19:43

It isn't GDP or money. And the best

19:46

world that you can build, I think on

19:48

Earth,

19:49

is a market economy

19:52

governed by a robust democracy that

19:55

robustly includes all citizens in that

19:59

economy. And your your answer is small

20:01

business, and I'm I'm 100% behind you,

20:04

and I I wish you all the success. My

20:08

answer is that a lot of people are going

20:10

to end up working for large companies

20:12

and or medium companies, and that we

20:14

have to ensure or my part of the answer

20:16

is that we have to have standards in

20:19

place to ensure that those companies

20:23

treat people well enough so that they

20:25

can

20:26

be dignified participants in both the

20:29

society and the economy. And that will

20:32

require

20:34

innovation in laws and rules and all

20:37

sorts of mechanisms to enable that, but

20:39

that there is no alternative if you want

20:42

to live in a decent society. And and but

20:46

the high-order bit for me, and the

20:48

reason I work on economics, is that the

20:50

existing economic paradigm basically

20:53

says markets are perfectly efficient, we

20:55

should just let them run, and you know,

20:58

what comes will come.

21:00

>> If you love the Diary of a CEO brand and

21:01

you watch this channel, please do me a

21:03

huge favor, become part of the 15% of

21:06

the viewers on this channel that have

21:08

hit the subscribe button. It helps us

21:10

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Interactive Summary

The video features a discussion on the disruptive potential of artificial intelligence on the job market, debating whether AI will primarily lead to mass unemployment or facilitate human augmentation and business growth. The speakers explore various perspectives, including the possibility of sovereign wealth funds managed by the government to mitigate disruption, the impact on entry-level roles, and historical parallels to technological shifts like computers and the Jevons paradox.

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