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AI EXPERTS: If AI Takes Thes… — Motivation2Study shadowing | TryShadowing
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Motivation2Study
AI EXPERTS: If AI Takes These Jobs, This Is What Society Looks Like
AI EXPERTS: If AI Takes These Jobs, This Is What Society Looks Like
Motivation2Study
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32:09 · Jan 12, 2026
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0:00
Are you uncomfortable talking about this?
0:02
>> Yeah, I mean it's pretty wild, right?
0:04
>> Major companies like Microsoft are laying off employees amid the rise of artificial
0:08
intelligence in the workplace.
0:10
The CEO of Salesforce recently said AI helped cut his staff nearly in half.
0:15
Roughly 40% of companies from around the world expect to reduce their workforce in
0:19
roles where AI can do the job.
0:21
>> If you're not using AI,
0:22
you're going to lose your job to somebody who uses AI.
0:25
That I think we know for certain.
0:28
The International Monetary Fund has expressed profound concerns
0:30
that generative AI could cause massive labor disruptions
0:34
and rising inequality.
0:35
>> It's it's not a bad thing.
0:38
The question is, is it come
0:39
so fast that you don't have time to adjust to it?
0:43
>> As this develops, as we get to, you know,
0:45
peer over the edge of this cliff that we're headed to,
0:48
I think we're going to discover
0:49
that we can't yet detect the nature of the alteration that's coming.
0:55
There's a great quote by a woman named Kelly Hayes where she says,
0:59
"Everything feels unprecedented when you haven't engaged with history."
1:02
If you don't have a good sense of where you've been,
1:05
a good memory of where you've been and where history has taken us before,
1:09
it's easy to read the news
1:10
or think about your own life
1:11
and think like we've never dealt with this before.
1:13
This is a new problem.
1:14
This is a new thing. where
1:16
so often if you have a good sense of history personally
1:19
and throughout the rest of the world,
1:21
it's easier to read the news and the devastating headlines and say, "Yes,
1:25
that's bad."
1:26
And we've done this before.
1:29
It's the same psychology.
1:30
It's the same movie even though if it's a different cast of characters.
1:33
So, so the definition of AGI is artificial general intelligence,
1:36
meaning that AI can acquire new skills in efficiently in the same way
1:42
that a humans can acquire skills.
1:44
Right now AIS don't acquire skills efficiently.
1:47
You know they they require massive amount of energy
1:49
and compute entire data set of compute to acquire these these skills
1:54
and I think there's a again a limit on how general intelligence can get.
2:00
I think for most of the time it will be lagging in terms of
2:04
what humans are are capable of doing.
2:08
>> In the past new technologies have come in
2:10
which didn't lead to joblessness. new jobs were created.
2:14
So the classic example people use is automatic teller machines.
2:18
When automatic teller machines came in,
2:20
a lot of bank tellers didn't lose their jobs.
2:23
They just got to do more interesting things.
2:25
But here I think this is more like
2:28
when they got machines in the industrial revolution
2:34
and you can't have a job digging ditches now
2:36
because a machine can dig ditches much better than you can.
2:40
And I think for mundane intellectual labor, AI is just going to replace everybody.
2:47
Now, it will may well be in the form of you have fewer people
2:52
using AI assistants.
2:53
So, it's a combination of a person
2:55
and an AI assistant are now doing the work
2:57
that 10 people could do previously.
3:00
>> People say that it will create new jobs though, so we'll be fine.
3:04
>> Yes.
3:04
And that's been the case for other technologies,
3:06
but this is a very different kind of technology.
3:09
People use this phrase.
3:11
They say AI won't take your job.
3:13
A human using AI will take your job.
3:15
>> Yes, I think that's true.
3:16
But for many jobs, that'll mean you need far fewer people.
3:21
There are jobs where you can make a person with an AI assistant much
3:25
more efficient and you won't lead to less people
3:28
because you'll just have much more of
3:30
that being done.
3:31
But most jobs, I think, are not like that.
3:34
We have to confront the probability of seriously dark outcomes.
3:40
And we have to spend time really thinking about those consequences
3:44
because the competitive nature of companies
3:48
and of nation states is going to mean
3:51
that every organization is going to race to get their hands on intelligence.
3:58
Intelligence is going to be a new form of of capital, right?
4:04
We are at the dawn of this radical transformation of humans
4:10
that by its very nature
4:13
as a truly complex
4:15
and emergent innovation nobody on earth can predict.
4:19
>> A poll of a thousand college students showed
4:21
that almost 90% of them use the chatbot to help with homework.
4:26
>> More and more vulnerable people are turning to AI chat bots for support.
4:30
Entry-level jobs are vanishing at an alarming rate.
4:34
>> Half of entry-level white collar jobs disappearing
4:37
and 10 to 20% unemployment in the next 1 to 5 years.
4:41
>> First of all, they underestimate the magnitude of the AI revolution.
4:45
AI is nothing like print.
4:48
It's nothing like uh the industrial revolution of the 19th century.
4:52
It's far far bigger.
4:53
It's the first technology in history
4:56
that can make decisions by itself
4:59
and that can create new ideas by itself.
5:02
>> I'm sorry, Dave.
5:03
I'm afraid I can't do that.
5:06
>> The idea that this AI disruption doesn't lead us to some very human catastrophe,
5:11
I think, is overly optimistic.
5:14
>> My worst fears are that we cause significant we the field, the technology,
5:18
the industry cause significant harm to the world.
5:22
If that really happened,
5:23
like if we really did just discover
5:25
that there were a billion extra people on the planet who all had PhDs
5:28
and were happy to work for almost for free,
5:30
that would have a massive disruptive impact on society.
5:37
>> What jobs are going to be made redundant in a world where I
5:41
am sat here as a CEO with a thousand AI agents?
5:44
>> I was thinking of all the names of my of the people in
5:46
my company who are currently doing those jobs.
5:48
I was thinking about my CFO when you talked about processing business data,
5:51
my graphic designers, my video editors, etc.
5:54
So, what what jobs are going to be impacted?
5:56
>> Yeah, all of those you maybe this is useful for for the audience.
6:01
I think if your job is as routine as it comes,
6:05
your job is gone in the next uh couple years.
6:08
So meaning in those jobs that for example quality assurance jobs, data entry jobs,
6:13
you're sitting in front of a computer
6:15
and you're supposed to click uh
6:17
and and type things in a certain order.
6:19
Operator and those technologies are coming on the market really quickly
6:22
and those are going to displace a lot of accountants.
6:28
>> Accountants.
6:28
>> Lawyers.
6:28
>> Yes.
6:28
>> I mean I've just pulled a ligament in my in my foot
6:30
and they did an MRI scan
6:32
and I had to wait a couple of days for someone to look at
6:34
the MRI scan and tell me what it meant.
6:35
>> Yeah.
6:36
Yeah.
6:36
>> I'm guessing that that's gone.
6:38
Yeah, I think I think the healthcare ecosystem is hard to predict
6:42
because of regulation and
6:43
and again there there's
6:44
so many limiting factors on how this technology can permeates the economy
6:48
because of regulations and
6:50
and people's willingness to to take it.
6:52
But you know things unregulated jobs that are purely text in text out.
6:58
If your job, you know,
6:59
you get a you get a message
7:00
and you produce some kind of artifact that's like probably text
7:04
or images that that job is is at risk.
7:07
>> People use this phrase, they say AI won't take your job.
7:10
A human using AI will take your job.
7:12
>> Yes, I think that's true.
7:13
But for many jobs, that'll mean you need far fewer people.
7:18
My niece answers letters of complaint to a health service.
7:22
It used to take her 25 minutes.
7:24
She'd read the complaint
7:25
and she'd think had to reply
7:27
and she'd write a letter.
7:28
And now she just scans it into um a chatbot
7:33
and it writes the letter.
7:35
She just checks a letter.
7:37
Occasionally she tells it to revise it in some ways.
7:40
The whole process takes her 5 minutes.
7:43
That means she can answer five times as many letters.
7:46
And that means they need five times fewer of her
7:50
so she can do the job
7:51
that five of her used to do.
7:54
Now, that will mean they need less people.
7:58
In other jobs, like in health care, they're much more elastic.
8:02
So, if you could make doctors five times as efficient,
8:06
we could all have five times as much healthare for the same price.
8:09
And that would be great.
8:11
There's there's almost no limit to how much healthare people can absorb.
8:15
>> They always want more healthare if there's no cost to it.
8:19
There are jobs where you can make a person with an AI assistant much
8:23
more efficient and you won't lead to less people
8:26
because you'll just have much more of
8:28
that being done.
8:29
But most jobs I think are not like that.
8:33
So that's the question I often ask people in the world with AGI
8:37
and I think almost immediately we'll get super intelligence
8:40
as a side effect.
8:41
So the question really is in a world of super intelligence
8:44
which is defined as better than all humans in all domains,
8:48
what can you contribute?
8:50
And so you know better than anyone what it's like to be you know
8:56
what ice cream tastes to you.
8:58
Can you get paid for that knowledge?
9:00
Is someone interested in that?
9:03
Maybe not.
9:04
Not a big market.
9:05
There are jobs where you want a human.
9:08
Maybe you're rich and you want a human accountant for whatever historic reasons.
9:13
Old people like traditional ways of doing things.
9:17
Warren Buffett would not switch to AI.
9:19
He would use his human accountant.
9:22
But it's a tiny subset of a market.
9:25
Today we have products
9:27
which are man-made in US
9:30
as opposed to mass-produced in China.
9:32
And some people pay more to have those.
9:34
But it's a small subset.
9:36
It's a almost a fetish.
9:38
There is no practical reason for it.
9:40
And I think anything you can do on a computer could be automated using
9:45
that technology.
9:48
>> People in this country want to do certain types of jobs,
9:52
not other types of jobs.
9:55
And I'm not saying that that's good or bad.
9:57
It's just the reality.
9:58
Mhm.
10:00
>> So, you know, I I I joke like like, you know,
10:03
my kids are 15
10:05
and they don't want to work for 40 years in a uh manufacturing job
10:12
and I don't want them to
10:14
because I don't want them to have the bad back
10:16
that I have right now.
10:18
Like, no, no.
10:19
I mean, this this is real.
10:20
Like, you work in one of these jobs for 40 years
10:22
and you're messed up by the time you hit your age 60.
10:25
So, they don't want to do that.
10:26
They don't want to work in a repetitive physical labor job for their life.
10:29
And I hate to say like almost no young kids in this country do.
10:34
>> They won't have to in 10 years with robots taking over all of that.
10:37
>> They they they won't have to.
10:38
And like the one knock
10:40
that this whole robot revolution people have with it is it will displace human
10:45
labor.
10:46
>> So if you have this concept of a drop in employee,
10:50
you have free labor, physical and cognitive, trillions of dollars of it.
10:54
It makes no sense to hire humans for most jobs.
10:58
If I can just get, you know,
10:59
a $20 subscription or a free model to do what an employee does,
11:04
first anything on a computer will be automated.
11:07
And next, I think humanoid robots are maybe 5 years behind.
11:11
So in 5 years, all the physical labor can also be automated.
11:14
So one of the things
11:15
that I study as well is besides AI
11:18
and longevity is the embodiment of AI
11:22
which is going to be in humanoid robots,
11:24
autonomous cars, flying cars and the like.
11:29
You know, I've interviewed Elon, who I've known for 26 years,
11:32
another company here in the US called uh called Figure AI
11:36
that Brett Adcock runs.
11:38
And both of them have made the prediction
11:41
that they expect by 2040 to have
11:44
as many as 10 billion humanoid robots walking on the streets,
11:49
right?
11:50
Uh, and so I asked my friend,
11:52
"What's it going to what's it going to feel like
11:54
when you're seeing a humanoid robot delivering your packages
11:57
or walking down the street
11:59
or coming over to ask you
12:00
if there's something else you want done?"
12:02
You say, "It's going to feel normal."
12:06
You know, in the beginning it feels weird.
12:08
Uh, it's a spectacle.
12:10
We take photographs, but after a little bit we fully adapt.
12:14
And that's the brilliance of human mind and society. and it becomes normal.
12:21
It's part of our lives.
12:26
>> Now, I think it goes so far beyond human intelligence.
12:29
It's my assumption that most of the work
12:31
that we do is based on intelligence.
12:34
So, even like me doing this podcast now,
12:36
>> this is me asking questions based on information that I've gathered,
12:40
based on what I think I'm interested in,
12:42
but also based on what I think the audience will be interested in.
12:44
And if if an AI has an IQ
12:47
that is a hundred times mine
12:48
and an source of information
12:50
that is a fat million times bigger than mine,
12:52
there's no need for me to do this podcast.
12:54
I can get an AI to do it.
12:55
And in fact, an AI can talk to an AI
12:57
and deliver that information to a human.
12:59
But then if we look at most industries like being a lawyer, >> um accountancy,
13:03
I mean a lot of med profession is based on information. um driving think
13:10
that's the biggest employer in the world is the profession of driving whether it's
13:13
delivery or Uber or whatever it is um where where do humans belong in
13:17
this complex anything which is just information in information out is ripe for automation
13:25
these are the easiest jobs to automate um >> like being a coder >>
13:30
like being a coder
13:31
or again like being an accountant at least certain types of accountants lawyers ers,
13:37
doctors, they are the easiest to automate.
13:40
If a doctor, the only thing they do is just take information in all
13:44
kind results of blood tests
13:46
and whatever and they information out the they diagnose the disease
13:51
and they write a prescription.
13:53
This will be easy to automate in the coming years and decades.
13:58
But a lot of jobs they require also social skills and motor skills.
14:04
If your job requires a combination of skills from several different fields,
14:10
it's it's not impossible, but it's much more difficult to automate it.
14:14
So, if you think about a nurse
14:16
that needs to replace a bandage to a crying child,
14:20
this is much much harder to automate than just a doctor
14:24
that writes a prescription.
14:25
Because this is not just data. the nurse needs uh uh good social skills
14:31
to interact with the child
14:33
and motor skills to just replace the bandage.
14:36
>> So what are those skills?
14:38
>> I think it's all human skills.
14:38
I think there needs
14:39
so I think where the world is going to go
14:41
and at least this is where I'm taking a bet is
14:44
that as the end product becomes easier to produce,
14:48
it's the humanity that's going to suffer.
14:50
And unless we take personal accountability both
14:53
as individuals and organizations to teach
14:55
and learn human skills,
14:57
they will disappear for all the reasons we're talking about.
15:00
So, how do I listen?
15:02
How do I hold space?
15:04
How do I resolve conflict peacefully?
15:06
How do I give and how do I receive feedback?
15:09
Those are two different skills.
15:12
And sure, you can have an AI friend
15:14
and that AI friend has been trained like the best best psychologist to affirm
15:19
you,
15:19
the best listening skills that exist.
15:22
Tell me about your day.
15:23
M, that sounds difficult.
15:24
Boy, it's hard being you.
15:25
Oh my god, it's so great being you.
15:27
Have you you know,
15:28
like it's it's a it's an affirmation machine built by a for-profit company
15:32
that wants you to stay on.
15:34
Can't neglect that. but for the fact
15:38
that nobody's learning how to be a friend.
15:41
It'll feel good.
15:42
You'll feel like you have a friend,
15:43
but you're not learning to be a friend.
15:45
They promised us social connection when social media came about.
15:49
When we got Wi-Fi connections,
15:50
the promise was that we would become more connected.
15:52
But it's so clear that because we spend so long alone, isolated,
15:56
having our needs met by Uber Eatats drivers
15:58
and social media and Tik Tok
16:00
and the internet that we're investing less in the very difficult thing of like
16:03
going and making a friend
16:05
and like going and finding a girlfriend.
16:06
Young people are having sex less than ever before.
16:09
Everything that is associated with the difficult job of making in real life connection
16:16
seems to be um falling away.
16:18
I think the the skill of being a storyteller
16:23
and a communicator is critically important for any entrepreneur.
16:28
Right?
16:29
At the end of the day,
16:29
if you think about what an entrepreneur is doing,
16:35
uh part of what they're doing is creating a vision of the future
16:39
that they think is possible. getting other people to believe in their future uh
16:45
and thereby join them
16:47
as a co-founder or employee
16:50
or join them as an investor
16:52
or join them as a customer.
16:54
And that's the process of communicating this product, this service,
17:00
this future you want and getting people excited about it,
17:03
wanting to join you
17:06
and being able to tell the difference between what is a fiction in our
17:12
own mind and what is the reality.
17:16
This is a a crucial skill
17:18
and we are not getting better at finding this difference
17:23
as time go time time goes on
17:26
and also with new technologies
17:27
which I write about a lot like artificial intelligence the fantasy
17:33
that AI will answer our questions will find the truth for us will tell
17:39
us the difference between fiction
17:41
and reality this is this is just another fiction I mean AI can do
17:46
many things better than humans,
17:48
but for reasons that we can discuss,
17:51
I don't think that it will necessarily be better than humans at finding the
17:56
truth or uncovering reality.
18:00
>> And what made you a great entrepreneur is not that the company exists,
18:04
is that you built it with your hands
18:06
and you've got the scars to show for it.
18:08
>> Yeah.
18:08
It was when things went wrong
18:10
and you were forced to fix them
18:11
and think that now
18:13
when problems show up,
18:15
you're quick.
18:15
You're smarter.
18:16
You're a much smarter businessman now than you were 5 years ago,
18:21
6 years ago.
18:22
>> Yeah.
18:22
>> Because you did it.
18:24
And I think what we're forgetting is that there's something to be said for,
18:27
and by the way, I'm a fan of AI.
18:29
I want AI to make things,
18:31
but I would hate to lose out on becoming a better version of me.
18:35
So, I think there's something to be said for writing your own symphony,
18:39
painting your own painting, building your own business, you know, writing your own book.
18:46
Not for them, not for the output, not for the outfit,
18:49
for your personal growth.
18:52
>> What is different about this that we haven't dealt with as a challenge before?
18:56
>> And in my estimation,
18:58
this fourth industrial revolution is the most dramatic thing that's happened to our society.
19:01
AI might be the most radical breakthrough in human history.
19:05
Intelligence is going to be a new form of of capital.
19:09
Just as there was a grab for land or there's a grab for oil,
19:12
there's a grab for anything that enables you to do more with less, faster,
19:16
better, smarter.
19:19
>> Is there a such thing as an AI proof job?
19:23
>> It will affect every single job out there.
19:25
Don't put your head in the sand.
19:26
There a lot of companies who don't want to talk about openly
19:28
because we're scaring people about jobs.
19:30
It is going to replace jobs.
19:32
>> To see what's going to happen,
19:34
you really want to start thinking of this
19:36
as the evolution of a new species
19:38
that will continue to evolve.
19:40
It will partially be shaped by what we ask it to do
19:43
and it will partially be shaped by things we don't understand.
19:47
What like I have little kids.
19:49
I have a 5-year-old and a three-year-old.
19:51
What do they grow up aspiring to
19:54
if machines can do pretty much everything better?
20:00
I've been speaking to a few people about artificial intelligence to try
20:03
and understand it.
20:05
And I'm I think where I am right now is I feel quite scared.
20:11
Um but when I get scared,
20:12
I don't get it's not the type of scared that makes me anxious.
20:15
It's not like an emotional scared.
20:16
It's a very logical scared.
20:18
It's my very logical brain hasn't been able to figure out how the inevitable
20:22
outcome that I've arrived at,
20:24
which is that humans become the less dominant species on this planet,
20:29
how that is to be avoided in any way.
20:34
So, all of us, me included,
20:36
feel what you just described
20:38
when you first get to grips with the idea of this new coming wave.
20:42
It's scary.
20:43
It's petrifying.
20:44
It's threatening.
20:45
Is it going to take my job?
20:47
Is my daughter or son gonna fall in love with it?
20:50
You know, what does this mean?
20:52
What does it mean to be human in a world where there's these other
20:55
humanlike things that aren't human?
20:58
How do I make sense of that?
21:00
It's super scary.
21:02
And a lot of people over the last few years,
21:06
the default reaction has been to avoid the pessimism and the fear, right?
21:12
to just kind of recoil from it
21:14
and pretend that it's like either not happening
21:18
or that it's all going to work out to be rosy.
21:20
It's going to be fine.
21:20
We don't have to worry about it.
21:23
People often say, "Well, we've always created new jobs.
21:25
We've never permanently displaced jobs.
21:28
We've only ever seen new jobs be created.
21:30
Unemployment is at an all-time low."
21:32
Right?
21:33
So, there's this default optimism bias that we have.
21:37
And I think it's less about a need for optimism
21:39
and more about a fear of pessimism.
21:42
And so that trap, particularly in elite circles,
21:46
means that often we aren't having the tough conversations
21:50
that we need to have in order to respond to the coming wave.
21:55
>> Uh I think uh maybe Microsoft just released a huge 40page white paper
22:00
looking at the jobs
22:01
that are most likely to be displaced
22:03
and the ones that are least likely to be displaced.
22:06
When you look at it, a lot of very working class like lumbering, lumberjacks,
22:11
uh logging, boat captains, none of those,
22:15
they they were the lowest down on the list.
22:18
Middle management, sports broadcasters, historians, analysts, middle level, legal sort of bods,
22:27
all that sort of stuff, logistics, drivers.
22:30
Um, so it really does sort of cross the spectrum.
22:32
It doesn't seem like anybody's particularly safe.
22:34
It doesn't look like anyone at any any area is going to be protected
22:38
from this.
22:38
>> Aren't there going to be lots of new jobs created though?
22:41
Because when we think about the other revolutions over time,
22:44
whether it was the industrial revolution
22:46
or other sort of big technological revolutions >> in the moment we forecasted
22:51
that everyone was going to lose their jobs,
22:53
but we couldn't see all the new jobs
22:55
that were being created >>
22:56
because the the the machines replaced the human strength at a point in time.
23:02
And very few places in the west today will have a worker carry things
23:08
on their back and carry it upstairs.
23:11
The machine does that work.
23:13
Correct.
23:13
>> Yeah.
23:13
Uh similarly AI is going to replace the brain of a human.
23:19
There's absolutely nothing wrong with AI.
23:21
There's a lot wrong with the value set of humanity at the age of
23:23
the rise of the machines.
23:25
Right?
23:25
And the biggest value set of humanity is capitalism today.
23:28
And capitalism is all about what?
23:30
Labor arbitrage.
23:32
What's that mean?
23:33
>> I I I hire you to do something.
23:35
I pay you a dollar.
23:36
I pay it I sell it for two.
23:39
Okay.
23:40
And and most people confuse that because they say, "Oh,
23:42
but the cost of a product also includes raw materials
23:44
and factories and so on
23:45
and so forth."
23:46
All of that is buil is built by labor, right?
23:49
So so basically labor goes
23:51
and mines for the material
23:52
and then the material is sold for a little bit of margin.
23:54
Then that material is turned into a machine.
23:56
It's sold for a little bit of margin then that machine and so on.
23:59
Okay?
24:00
There's always labor arbitrage in a world where humanity's minds are being replaced by
24:06
by AIs,
24:07
virtual AIs, okay?
24:09
And humanity's power strength within 3 to 5 years time can be replaced by
24:17
a robot.
24:21
You really have to question how this world looks like.
24:24
It could be the best world ever.
24:25
And that's what I believe the utopia will look like
24:28
because we were never made to wake up every morning
24:30
and just,
24:31
you know, occupy 20 hours of our day with work, right?
24:35
We're not made for that.
24:37
But we've fit into that uh uh, you know,
24:40
system so well so far that we started to believe it's our life's purpose.
24:50
You can never really predict what jobs are coming.
24:52
I mean, I think of this crazy situation where I tell my grandfather,
24:57
"What is a personal fitness trainer?"
25:00
And he would, his mind would be blown by this idea that, well, okay,
25:05
I don't really want to go to the gym,
25:06
so I have to make an appointment
25:08
and pay someone to go to the gym
25:09
and meet with me there.
25:10
And then he stands there
25:11
and tells me to lift heavy things
25:13
that I don't really want to lift.
25:14
And then he counts them and tells me that I've done a good job.
25:18
And then I put the heavy things down.
25:20
And then at the end of
25:21
that I feel really good
25:22
and I pay him a bunch of money.
25:23
My grandfather would be like what on earth have you been scammed?
25:26
Is this So >> we can never predict what what this uh future of
25:31
jobs would look like.
25:32
Even just 20 30 40 years apart the jobs rapidly
25:36
and convincingly just morph into something else.
25:40
I think it's very dangerous the idea that we need to focus on skills.
25:44
I think the future is not in skills.
25:46
Skills are being replaced.
25:47
It's this idea that the education system has to stop being compartmentalized
25:51
and has to be a lifelong learning approach.
25:53
The department of education needs to be seeing people
25:57
as lifelong learners who are constantly disrupted
26:00
and need re-education.
26:00
>> Interesting.
26:00
>> That that's going to be a thing
26:04
that the department of education needs to start
26:06
as a kid and go right through to maybe 70.
26:09
>> Does the department of education have a role anymore at all?
26:12
>> Depends on your definition of education.
26:13
I think if you're trying to teach kids
26:15
or if you're trying to teach kids to,
26:18
you know, remember facts and figures from a history book, then no.
26:24
But if it's about coaching, mentoring, being displaced, finding the next thing,
26:28
and maybe if it's AIdriven, and all of those kind of things,
26:31
then it's a different paradigm shift around what education is
26:34
and what its purpose is.
26:37
>> The it's worth backing up
26:38
and thinking about like why what is it
26:40
that makes humans valuable workers?
26:43
I don't think it's mainly their raw intellect.
26:45
I think it's their ability.
26:46
Um you when you work with people like why are they use basically useless
26:50
the first month or the first week
26:52
and you couldn't live without them 6 months later.
26:55
Um it's their ability to build up context.
26:57
Uh it's their ability to interrogate their own failures
27:00
and learn from them in this really organic way.
27:04
And this ability just doesn't exist in these models.
27:07
They exist session to session.
27:09
and that everything that they have learned about you evaporates after every hour.
27:14
>> Um, and so it's a frustrating experience where you can try to get
27:17
them to do a task.
27:18
Uh, they'll do a five out of 10 job at many language
27:20
and language out tasks,
27:21
but there's no way for them to get better.
27:24
And given that that's a fact,
27:25
you just kind of have to like rely on humans.
27:27
Uh, >> it's like 50 first dates over and over.
27:30
Every time that you do it,
27:30
you've got to you've got to reintroduce yourself and explain what's going on.
27:33
>> Yeah.
27:34
Groundhog Day.
27:34
Yeah.
27:35
Yeah, that's right.
27:36
So I'm con I think people have this idea
27:39
that even if all AI progress stopped right now these systems would still be
27:41
economically transformative and they say look JP Morgan
27:44
and McDonald's and whatever just haven't integrated these systems into their workflows
27:47
but if they had they would be like seeing all these benefits
27:50
and I don't really think that's the case.
27:51
I think like genu it's just like genuinely hard to get human like labor
27:54
out of these models.
27:57
And hopefully in your closing remarks,
27:59
you can capture something actionable for the individual that's listening to this now on
28:04
their commute to work
28:05
or the single mother,
28:06
the average person who maybe isn't
28:08
as technologically advanced as many of us at this table,
28:10
but is trying to navigate through this to figure out how to live a
28:13
good life over the next 10,
28:15
20, 30 years.
28:17
I think we live in the most uh interesting time in human history.
28:22
So for the single mother that's listening,
28:24
for someone who wouldn't be the stereotype of a tech bro,
28:27
don't assume that you can't do this stuff.
28:30
It's never been more accessible today within your work.
28:33
You can be an entrepreneur.
28:35
You don't have to take massive risk to go create a business um by
28:40
you quit your job
28:41
and go create a business.
28:44
So I really want people to break away from this concept of entrepreneurship being
28:52
this is your podcast a diary of a CEO.
28:54
You started this podcast by talking to CEOs I assume right
28:58
and over time uh it changed to everyone can be a CEO.
29:03
Everyone is some kind of CEO in their life.
29:06
I think that we have unprecedented access to tools for
29:12
that vision to actually come to reality.
29:17
I think the potential here does allow us to refactor just about everything.
29:23
Maybe we have finally arrived at the place where mundane work doesn't need to
29:27
exist anymore and the pursuit of meaning can replace it.
29:31
But that's not going to happen automatically
29:33
if we don't figure out how to make it happen.
29:36
And I hope that we can recognize
29:39
that the peril of this moment is best utilized
29:43
if it motivates us to confront
29:45
that question directly.
29:48
>> The International Monetary Fund has expressed profound concerns
29:51
that generative AI could cause massive labor disruptions
29:54
and rising inequality and has called for policies
29:57
that prevent this from happening.
29:59
I read that in the business insider.
30:01
>> Have they given any of what the policies should look like?
30:04
>> No.
30:05
Yeah, that's the problem.
30:06
I mean, if AI can make everything much more efficient
30:08
and get rid of people for most jobs
30:10
or have a person assisted by doing many,
30:14
many people's work, it's not obvious what to do about it.
30:18
>> It's universal basic income.
30:21
Give everybody money.
30:22
>> Yeah, I I I think that's a good start and it stops people starving,
30:28
but for a lot of people, their dignity is tied up with their job.
30:31
I mean, who you think you are is tied up with you doing this
30:34
job,
30:35
right?
30:36
>> Yeah.
30:36
>> And if we said, "We'll give you the same money just to sit around,
30:41
that would impact your dignity."
30:45
Everywhere you look in the next 50 years,
30:49
we have to do more with less.
30:52
And there are very, very few proposals,
30:56
let alone practical solutions for how we get there.
31:00
Training machines to help us as aids, scientific research partners, inventors,
31:07
creators is absolutely essential.
31:10
And so the upside is phenomenal.
31:13
It's enormous.
31:16
But AI isn't just a thing.
31:18
It's not an inevitable hole.
31:21
Its form isn't inevitable, right?
31:24
its form, the exact way
31:27
that it manifests and appears in our everyday lives
31:29
and the way that it's governed
31:30
and who it's owned by
31:31
and how it's trained.
31:33
That is a question
31:36
that is up to us collectively
31:37
as a species to figure out over the next decade.
31:40
Because if we don't embrace that challenge, then it happens to us.
31:46
And that's really what I'm I have been wrestling with for 15 years of
31:50
my career is how to intervene in a way
31:54
that this really does benefit everybody
31:57
and those benefits far far outweigh the potential risks.
32:00
>>
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