---
title: 'Demis Hassabis On The Future of Work in the Age of AI'
source: 'https://youtube.com/watch?v=CRraHg4Ks_g'
video_id: 'CRraHg4Ks_g'
date: 2026-06-19
duration_sec: 0
---

# Demis Hassabis On The Future of Work in the Age of AI

> Source: [Demis Hassabis On The Future of Work in the Age of AI](https://youtube.com/watch?v=CRraHg4Ks_g)

## Summary

In this interview, Demis Hassabis, CEO of Google DeepMind, discusses the definition, progress, and timeline for achieving Artificial General Intelligence (AGI). He outlines both the immense potential for solving global problems and the significant risks of misuse and technical control, emphasizing the need for smart regulation and international cooperation.

### Key Points

- **AGI Definition** [01:30] — Hassabis defines AGI as a system that can exhibit all cognitive capabilities of a human.
- **AGI Timeline** [01:12] — He estimates a 50% chance of AGI within 5-10 years.
- **Challenges with Current AI** [02:43] — Current AI lacks consistency; fails at basic tasks despite excelling in others.
- **Incremental Transition** [03:41] — He thinks AGI arrival will be incremental, not a sudden step function.
- **Key Risks** [06:14] — Two main risks: bad actors using AI for harm, and technical risks of powerful AI.
- **International Regulation** [07:29] — Calls for smart, nimble, international regulation.
- **Advice for Students** [12:36] — Advises students to master prompting, fine-tuning, and STEM to stay productive.
- **Promise of AGI** [13:43] — Envisions AGI solving root problems like disease, energy, and water access.
- **Mindset Shift** [16:44] — Hopes radical abundance will shift societal mindset to non-zero-sum.

## Transcript

- It's a very intense time in the field.
We obviously want all
of the brilliant things
these AI systems can do,
come up with new cures for
diseases, new energy sources,
incredible things for humanity.
That's the promise of AI.
But also, there are worries
if the first AI systems are built
with the wrong value systems
or they're built unsafely,
that could be also very bad.
- Wired sat down with Demis Hassabis,
who's the CEO of Google
DeepMind, which is the engine
of the company's artificial intelligence.
He's a Nobel Prize
winner and also a knight.
We discussed AGI, the future of work,
and how Google plans to
compete in the age of AI.
This is "The Big Interview."
[upbeat music]
Well, welcome to "The
Big Interview," Demis.
- Thank you, thanks for having me.
- So let's start talking
about AGI a little here.
Now, you founded DeepMind with the idea
that you would solve intelligence
and then use intelligence
to solve everything else.
And I think it was like a 20-year mission.
We're like 15 years into
it, and you're on track?
- I feel like, yeah,
we're pretty much dead on track, actually,
is what would be our estimate.
- That means five years away
from what I guess people will call AGI.
- Yeah, I think in the
next five to 10 years,
that would be maybe 50% chance
that we'll have what we
are defined as AGI, yes.
- Well, some of your peers are saying,
"Two years, three years,"
and others say a little more,
but that's really close,
that's really soon.
How do we know that we're that close?
- There's a bit of a debate
going on in the moment
in the field about definitions of AGI,
and then obviously, of
course, dependent on that.
There's different predictions
for when it will happen.
We've been pretty consistent
from the very beginning.
And actually, Shane Legg,
one of my co-founders
and our chief scientist,
you know, he helped define
the term AGI back in, I think,
early 2001 type of timeframe.
And we've always thought
about it as system
that has the ability to exhibit,
sort of all the cognitive
capabilities we have as humans.
And the reason that's important,
the reference to the human mind,
is the human mind is the
only existence proof we have.
Maybe in the universe, the
general intelligence is possible.
So if you want to claim sort
of general intelligence, AGI,
then you need to show that it generalizes
to all these domains.
- Is when everything's filled in,
all the check marks are
filled in, then we have it-
- Yes, so I think there are
missing capabilities right now.
You know, that all of us
who have used the latest
sort of LLMs and chatbots,
will know very well, like on reasoning,
on planning, on memory.
I don't think today's
systems can invent, you know,
do true invention,
you know, true creativity,
hypothesize new scientific theories.
They're extremely useful,
they're impressive,
but they have holes.
And actually, one of the
main reasons I don't think
we are at AGI yet is
because of the consistency of responses.
You know, in some domains,
we have systems that can do
International Math Olympiad,
math problems to gold medal standard-
- Sure.
- With our AlphaFold system.
But on the other hand,
these systems sometimes still
trip up on high school maths
or even counting the number
of letters in a word.
- Yeah.
- So that to me is not
what you would expect.
That level of sort of difference
in performance across the
board is not consistent enough,
and therefore shows
that these systems are not
fully generalizing yet.
- But when we get it,
is it then like a phase
shift that, you know,
then all of a sudden things are different,
all the check marks are checked?
- Yeah.
- You know,
and we have a thing
that can do everything.
- Mm-hmm.
- Are we then power in a new world?
- I think, you know, that again,
that is debated, and it's not clear to me
whether it's gonna be more
of a kind of incremental
transition versus a step function.
My guess is, it looks
like it's gonna be more
of an incremental shift.
Even if you had a system like
that, the physical world,
still operates with the physical laws,
you know, factories,
robots, these other things.
So it'll take a while for the
effects of that, you know,
this sort of digital
intelligence, if you like,
to really impact, I think, a
lot of the real world things.
Maybe another decade plus,
but there's other theories on that too,
where it could come faster.
- Yeah, Eric Schmidt, who I
think used to work at Google,
has said that, "It's almost
like a binary thing."
He says, "If China,
for instance, gets AGI,
then we're cooked."
Because if someone gets
it like 10 minutes,
before the next guy, then
you can never catch up.
You know, because then
it'll maintain bigger,
bigger leads there.
You don't buy that, I guess.
- I think it's an unknown.
It's one of the many unknowns,
which is that, you know,
that's sometimes called
the hard takeoff scenario,
where the idea there is
that these AGI systems,
they're able to self-improve,
maybe code themselves
future versus themselves,
that maybe they're extremely
fast at doing that.
So what would be a slight lead,
let's say, you know, a few days,
could suddenly become a
chasm if that was true.
But there are many other
ways it could go too,
where it's more incremental.
Some of these self-improvement
things are not able
to kind of accelerate in that way,
then being around the same time,
would not make much difference.
But it's important, I mean,
these issues are the geopolitical issues.
I think the systems that are being built,
they'll have some imprint of the values
and the kind of norms of the
designers and the culture
that they were embedded in.
- [Steven] Mm-hmm.
- So, you know, I think it is important,
these kinds of international questions.
- So when you build AI at Google,
you know, you have that in mind.
Do you feel competitive imperative
to, in case that's true,
"Oh my God, we better be first?"
- It's a very intense time
at the moment in the field
as everyone knows.
There's so many resources going
into it, lots of pressures,
lots of things that need to be researched.
And there's sort of
lots of different types
of pressures going on.
We obviously want all
of the brilliant things
that these AI systems can do.
You know, I think eventually,
we'll be able to advance
medicine and science with it,
like we've done with AlphaFold,
come up with new cures for
diseases, new energy sources,
incredible things for humanity,
that's the promise of AI.
But also there are worries
both in terms of, you know,
if the first AI systems are built
with the wrong value systems
or they're built unsafely,
that could be also very bad.
And, you know, there
are at least two risks
that I worry a lot about.
One is, bad actors in
whether it's individuals
or rogue nations repurposing
general purpose AI technology
for harmful lens.
And then the second one is, obviously,
the technical risk of AI itself.
As it gets more and more powerful,
more and more agentic,
can we make sure the
guardrails are safe around it?
They can't be circumvented.
And that interacts with
this idea of, you know,
what are the first systems that are built
by humanity gonna be like?
There's commercial imperative-
- [Steven] Right.
- There's national imperative,
and there's a safety aspect to worry
about who's in the lead and
where those projects are.
- A few years ago, the
companies were saying,
"Please, regulate us.
We need regulation."
- Mm-hmm, mm-hmm.
- And now, in the US at least,
the current administration
seems less interested
in putting regulations on
AI than accelerating it
so we can beat the Chinese.
Are you still asking for regulation?
Do you think that that's
a miss on our part?
- I think, you know,
and I've been consistent in this,
I think there are these other
geopolitical sort of overlays
that have to be taken into account,
and the world's a very different place
to how it was five years
ago in many dimensions.
But there's also, you know,
I think the idea of smart regulation
that makes sense around these
increasingly powerful systems,
I think is gonna be important.
I continue to believe that.
I think though, and I've
been certain on this as well,
it sort of needs to be international,
which looks hard at the moment
in the way the world is working,
because these systems, you know,
they're gonna affect everyone,
and they're digital systems.
- Yeah.
- So, you know, if you sort
of restrict it in one area,
that doesn't really help
in terms of the overall safety
of these systems getting
built for the world
and as a society.
- [Steven] Yeah.
- So that's the bigger problem, I think,
is some kind of international
cooperation or collaboration,
I think, is what's required.
And then smart regulation,
nimble regulation
that moves as the knowledge
about the research
becomes better and better.
- Would it ever reach a point
for you where you would feel,
"Man, we're not putting the guardrails in.
You know, we're competing,
that we really have to stop,
or you can't get involved in that?"
- I think a lot of the
leaders of the main labs,
at least the western labs,
you know, there's a small number of them
and we do all know each other
and talk to each other regularly.
And a lot of the lead researchers do.
The problem is, is that it's not clear
we have the right definitions
to agree when that point is.
Like, today's systems,
although they're impressive
as we discussed earlier,
they're also very flawed.
And I don't think today's systems,
are posing any sort of existential risk.
- Mm-hmm.
- So it's still theoretical,
but the problem is that a lot of unknowns,
we don't know how fast those will come,
and we don't know how risky they will be.
But in my view, when there
are so many unknowns,
then I'm optimistic we'll overcome them.
At least technically,
I think the geopolitical
questions could be actually,
end up being trickier, given
enough time and enough care
and thoughtfulness, you know,
sort of using the scientific method
as we approach this AGI point.
- That makes perfect sense.
But on the other hand, if
that timeframe is there,
we just don't have much time, you know?
- No, we don't.
We don't have much time.
I mean, we're increasingly
putting resources into security
and things like cyber,
and also research into controllability
and understanding of these systems,
sometimes called mechanistic
interpretability.
You know, there's a lot of
different sub-branches of AI.
- Yeah, that's right.
I wanna get to interpretability.
- Yeah, that are being invested in,
and I think even more needs to happen.
And then at the same time,
we need to also have societal debates more
about institutional building.
How do we want governance to work?
How are we gonna get
international agreement,
at least on some basic principles,
around how these systems
are used and deployed
and also built?
- What about the effect on
work on the marketplace?
- Yeah.
- You know,
how much do you feel that AI is going
to change people's jobs,
you know, the way jobs are
distributed in the workforce?
- I don't think we've seen,
my view is if you talk to economists,
they feel like there's
not much has changed yet.
You know, people are
finding these tools useful,
certainly in certain domains-
- [Steven] Yeah.
- Like, things like AlphaFold,
many, many scientists are using
it to accelerate their work.
So it seems to be additive at the moment.
We'll see what happens over
the next five, 10 years.
I think there's gonna be a lot of change
with the jobs world, but
I think as in the past,
what generally tends to
happen is new jobs are created
that are actually better,
that utilize these tools
or new technologies,
what happened with the internet,
what happened with mobile?
We'll see if it's different this time.
- Yeah.
- Obviously everyone
always thinks this new one,
will be different.
And it may be, it will be,
but I think for the next few years,
it's most likely to be, you know,
we'll have these incredible tools
that supercharge our productivity,
make us really useful for creative tools,
and actually almost make
us a little bit superhuman
in some ways in what we're
able to produce individually.
So I think there's gonna
be a kind of golden era,
over the next period of
what we're able to do.
- Well, if AGI can do
everything humans can do,
then it would seem that they
could do the new jobs too.
- That's the next question
about like, what AGI brings.
But, you know, even if you
have those capabilities,
there's a lot of things I
think we won't want to do
with a machine.
You know, I sometimes give this example
of doctors and nurses.
You know, maybe a doctor
and what the doctor
does and the diagnosis,
you know, one could imagine
that being helped by AI tool
or even having an AI kind of doctor.
On the other hand, like nursing,
you know, I don't think you'd
want a robot to do that.
I think there's something
about the human empathy
aspect of that and the care,
and so on, that's particularly humanistic.
I think there's lots of examples like that
but it's gonna be a
different world for sure.
- If you would talk to a graduate now,
what advice would you give
to keep working-
- Yeah.
- Through the course
of a lifetime-
- Yeah.
- You know, in the age of AGI?
- My view is, currently,
and of course, this is
changing all the time
with the technology developing.
But right now, you know,
if you think of the next
five, 10 years as being,
the most productive people
might be 10X more productive
if they are native with these tools.
So I think kids today, students today,
my encouragement would be immerse yourself
in these new systems, understand them.
So I think it's still important
to study STEM and
programming and other things,
so that you understand how they're built,
maybe you can modify them yourself
on top of the models that are available.
There's lots of great open
source models and so on.
And then become, you know,
incredible at things like
fine-tuning, system prompting,
you know, system instructions,
all of these additional
things that anyone can do.
And really know how to get
the most out of those tools,
and do it for your
research work, programming,
and things that you are
doing on your course.
And then come out of that being incredible
at utilizing those new tools
for whatever it is you're going to do.
- Let's look a little beyond
the five and 10-year range.
Tell me what you envision
when you look at our future
in 20 years, in 30 years,
if this comes about,
what's the world like
when AGI is everywhere?
- Well, if everything goes well,
then we should be in an era of what I like
to call sort of radical abundance.
So, you know, AGI solves
some of these key,
what I sometimes call root node problems
in the world facing society.
So a good one, examples
would be curing diseases,
much healthier, longer lifespans,
finding new energy sources,
you know, whether that's optimal batteries
and better room temperature,
superconductors, fusion.
And then if that all happens,
then we know it should be a kind of era
of maximum human flourishing
where we travel to the stars
and colonize the galaxy.
You know, I think the
beginning of that will happen
in the next 20, 30 years if
the next period goes well.
- I'm a little skeptical of that.
I think we have an
unbelievable abundance now,
but we don't distribute it,
you know, fairly.
- Yeah.
- I think that we kind of know
how to fix climate change, right?
We don't need a AGI to
tell us how to do it,
yet we're not doing it.
- I agree with that.
I think we being as a species,
a society not good at collaborating,
and I think climate is a good example.
But I think we are still operating,
humans are still operating
in a zero-sum game mentality.
Because actually, the
earth is quite finite,
relative to the amount
of people there are now
in our cities.
And I mean, this is why
our natural habitats,
are being destroyed,
and it's affecting
wildlife and the climate
and everything.
- [Steven] Yeah.
- And it's also partly
'cause people are not willing
to accept, we do now
to figure out climate.
But it would require
people to make sacrifices.
- Yeah.
- And people don't want to.
But this radical abundance
would be different.
We would be in a finally, like,
it would feel like a non-zero-sum game.
- How will we get [indistinct] to that?
Like, you talk about diseases-
- Well, I gave you an example.
- We have vaccines,
and now some people think
we shouldn't use it.
- Let me give you a very simple example.
- Sure.
- Water access.
This is gonna be a huge issue
in the next 10, 20 years.
It's already an issue.
Countries in different, you know,
poorer parts of the world,
dryer parts of the world,
also obviously compounded
by climate change.
- [Steven] Yeah.
- We have a solution to water access.
It's desalination, it's easy.
There's plenty of sea water.
- Yeah.
- Almost all countries have a coastline.
But the problem is, it's salty water,
but desalination only very rich countries.
Some countries do do
that, use desalination
as a solution to their
fresh water problem,
but it costs a lot of energy.
- Mm-hmm.
- But if energy was essentially zero,
there was renewable free
clean energy, right?
Like fusion, suddenly, you
solve the water access problem.
Water is, who controls a river
or what you do with that does not,
it becomes much less
important than it is today.
I think things like water access,
you know, if you run forward 20 years,
and there isn't a solution
like that, could lead
to all sorts of conflicts,
probably that's the way it's trending-
- Mm-hmm, right.
- Especially if you include
further climate change.
- So-
- And there's many,
many examples like that.
You could create rocket fuel easily-
- Mm-hmm.
- Because you just separate
that from seawater, hydrogen and oxygen.
It's just energy again.
- So you feel that these problems
get solved by AGI, by AI,
then we're going to,
our outlook will change,
and we will be-
- That's what I hope.
Yes, that's what I hope.
But that's still a secondary part.
So the AGI will give us the
radical abundance capability,
technically, like the water access.
- Yeah.
- I then hope,
and this is where I think we
need some great philosophers
or social scientists to be involved.
That should hopefully shift our mindset
as a society to non-zero-sum.
You know, there's still the issue
of do you divide even the
radical abundance fairly, right?
Of course, that's what should happen.
But I think there's much more likely,
once people start
feeling and understanding
that there is this almost
limitless supply of raw materials
and energy and things like that.
- Do you think that
driving this innovation
by profit-making companies
is the right way to go?
We're most likely to reach
that optimistic high point through that?
- I think it's the current capitalism
or, you know, is the current
or the western sort of
democratic kind of systems,
have so far been proven
to be sort of the best
drivers of progress.
- Mm-hmm.
- So I think that's true.
My view is that once you get
to that sort of stage of
radical abundance and post-AGI,
I think economics starts changing,
even the notion of value and money.
And so again, I think we need,
I'm not sure why economists
are not working harder on this
if maybe they don't believe
it's that close, right?
But if they really did that,
like the AGI scientists do,
then I think there's a lot
of economic new economic
theory that's required.
- You know, one final thing,
I actually agree with you
that this is so significant
and is gonna have a huge impact.
But when I write about it,
I always get a lot of response from people
who are really angry already
about artificial intelligence
and what's happening.
Have you tasted that?
Have you gotten that pushback
and anger by a lot of people?
It's almost like the
industrial revolution people-
- Yeah.
- Fighting back.
- I mean, I think that anytime there's,
I haven't personally seen a lot of that,
but obviously, I've read
and heard a lot about,
and it's very understandable.
That's all that's happened many times.
As you say, industrial revolution,
when there's big change,
a big revolution.
- [Steven] Yeah.
- And I think this will be at least
as big as the industrial
revolution, probably a lot bigger.
That's surprising, there's unknowns,
it's scary, things will change.
But on the other hand,
when I talk to people about the passion,
the why I'm building AI-
- Mm-hmm.
- Which is to advance science
and medicine-
- Right.
- And understanding of
the world around us.
And then I explain to people, you know,
and I've demonstrated, it's not just talk.
Here's AlphaFold, you know,
Nobel Prize winning breakthrough,
can help with medicine and drug discovery.
Obviously, we're doing
this with isomorphic now
to extend it into drug discovery,
and we can cure terrible diseases
that might be afflicting your family.
Suddenly, people are like,
"Well, of course, we need that."
- Right.
- It'll be immoral not
to have that if that's within our grasp.
And the same with climate and energy.
- Yeah.
- You know,
many of the big societal problems,
it's not like you know,
we know, we've talked about,
there's many big challenges
facing society today.
And I often say I would be
very worried about our future
if I didn't know something
as revolutionary as AI
was coming down the line
to help with those other challenges.
Of course, it's also a
challenge itself, right?
But at least, it's one of these challenges
that can actually help with
the others if we get it right.
- Well, I hope your optimism
holds out and is justified.
Thank you so much.
- And I'll do my best.
Thank you.
[upbeat music]