How well earn money in a future without jobs Martin Ford
I’m going to begin with a scary question:
Are we headed toward
a future without jobs?
The remarkable progress that we’re seeing
in technologies like self-driving cars
has led to an explosion
of interest in this question,
but because it’s something
that’s been asked
so many times in the past,
maybe what we should really be asking
is whether this time is really different.
The fear that automation
might displace workers
and potentially lead
to lots of unemployment
goes back at a minimum 200 years
to the Luddite revolts in England.
And since then, this concern
has come up again and again.
I’m going to guess
that most of you have probably never
heard of the Triple Revolution report,
but this was a very prominent report.
It was put together
by a brilliant group of people –
it actually included
two Nobel laureates –
and this report was presented
to the President of the United States,
and it argued that the US was on the brink
of economic and social upheaval
because industrial automation
was going to put millions of people
out of work.
Now, that report was delivered
to President Lyndon Johnson
in March of 1964.
So that’s now over 50 years,
and, of course, that
hasn’t really happened.
And that’s been the story again and again.
This alarm has been raised repeatedly,
but it’s always been a false alarm.
And because it’s been a false alarm,
it’s led to a very conventional way
of thinking about this.
And that says essentially that yes,
technology may devastate
entire industries.
It may wipe out whole occupations
and types of work.
But at the same time, of course,
progress is going to lead
to entirely new things.
So there will be new industries
that will arise in the future,
and those industries, of course,
will have to hire people.
There’ll be new kinds of work
that will appear,
and those might be things that today
we can’t really even imagine.
And that has been the story so far,
and it’s been a positive story.
It turns out that the new jobs
that have been created
have generally been
a lot better than the old ones.
They have, for example,
been more engaging.
They’ve been in safer,
more comfortable work environments,
and, of course, they’ve paid more.
So it has been a positive story.
That’s the way things
have played out so far.
But there is one particular
class of worker
for whom the story
has been quite different.
For these workers,
technology has completely
decimated their work,
and it really hasn’t created
any new opportunities at all.
And these workers, of course,
are horses.
(Laughter)
So I can ask a very provocative question:
Is it possible that at some
point in the future,
a significant fraction of the human
workforce is going to be made redundant
in the way that horses were?
Now, you might have a very visceral,
reflexive reaction to that.
You might say, “That’s absurd.
How can you possibly compare
human beings to horses?”
Horses, of course, are very limited,
and when cars and trucks
and tractors came along,
horses really had nowhere else to turn.
People, on the other hand,
are intelligent;
we can learn, we can adapt.
And in theory,
that ought to mean that we can
always find something new to do,
and that we can always remain
relevant to the future economy.
But here’s the really
critical thing to understand.
The machines that will threaten
workers in the future
are really nothing like those cars
and trucks and tractors
that displaced horses.
The future is going to be full
of thinking, learning, adapting machines.
And what that really means
is that technology is finally
beginning to encroach
on that fundamental human capability –
the thing that makes us
so different from horses,
and the very thing that, so far,
has allowed us to stay ahead
of the march of progress
and remain relevant,
and, in fact, indispensable
to the economy.
So what is it that is really so different
about today’s information technology
relative to what we’ve seen in the past?
I would point to three fundamental things.
The first thing is that we have seen
this ongoing process
of exponential acceleration.
I know you all know about Moore’s law,
but in fact, it’s more
broad-based than that;
it extends in many cases,
for example, to software,
it extends to communications,
bandwidth and so forth.
But the really key thing to understand
is that this acceleration has now
been going on for a really long time.
In fact, it’s been going on for decades.
If you measure from the late 1950s,
when the first integrated
circuits were fabricated,
we’ve seen something on the order
of 30 doublings in computational power
since then.
That’s just an extraordinary number
of times to double any quantity,
and what it really means
is that we’re now at a point
where we’re going to see
just an extraordinary amount
of absolute progress,
and, of course, things are going
to continue to also accelerate
from this point.
So as we look forward
to the coming years and decades,
I think that means
that we’re going to see things
that we’re really not prepared for.
We’re going to see things
that astonish us.
The second key thing
is that the machines are,
in a limited sense, beginning to think.
And by this, I don’t mean human-level AI,
or science fiction
artificial intelligence;
I simply mean that machines and algorithms
are making decisions.
They’re solving problems,
and most importantly, they’re learning.
In fact, if there’s one technology
that is truly central to this
and has really become
the driving force behind this,
it’s machine learning,
which is just becoming
this incredibly powerful,
disruptive, scalable technology.
One of the best examples
I’ve seen of that recently
was what Google’s DeepMind
division was able to do
with its AlphaGo system.
Now, this is the system that was able
to beat the best player in the world
at the ancient game of Go.
Now, at least to me,
there are two things that really
stand out about the game of Go.
One is that as you’re playing the game,
the number of configurations
that the board can be in
is essentially infinite.
There are actually more possibilities
than there are atoms in the universe.
So what that means is,
you’re never going to be able to build
a computer to win at the game of Go
the way chess was approached, for example,
which is basically to throw
brute-force computational power at it.
So clearly, a much more sophisticated,
thinking-like approach is needed.
The second thing
that really stands out is that,
if you talk to one
of the championship Go players,
this person cannot necessarily
even really articulate what exactly it is
they’re thinking about
as they play the game.
It’s often something
that’s very intuitive,
it’s almost just like a feeling
about which move they should make.
So given those two qualities,
I would say that playing Go
at a world champion level
really ought to be something
that’s safe from automation,
and the fact that it isn’t should really
raise a cautionary flag for us.
And the reason is that we tend
to draw a very distinct line,
and on one side of that line
are all the jobs and tasks
that we perceive as being on some level
fundamentally routine and repetitive
and predictable.
And we know that these jobs
might be in different industries,
they might be in different occupations
and at different skill levels,
but because they are innately predictable,
we know they’re probably at some point
going to be susceptible
to machine learning,
and therefore, to automation.
And make no mistake –
that’s a lot of jobs.
That’s probably something
on the order of roughly half
the jobs in the economy.
But then on the other side of that line,
we have all the jobs
that require some capability
that we perceive as being uniquely human,
and these are the jobs
that we think are safe.
Now, based on what I know
about the game of Go,
I would’ve guessed that it really ought
to be on the safe side of that line.
But the fact that it isn’t,
and that Google solved this problem,
suggests that that line is going
to be very dynamic.
It’s going to shift,
and it’s going to shift in a way
that consumes more and more jobs and tasks
that we currently perceive
as being safe from automation.
The other key thing to understand
is that this is by no means just about
low-wage jobs or blue-collar jobs,
or jobs and tasks done by people
that have relatively
low levels of education.
There’s lots of evidence to show
that these technologies are rapidly
climbing the skills ladder.
So we already see an impact
on professional jobs –
tasks done by people like accountants,
financial analysts,
journalists,
lawyers, radiologists and so forth.
So a lot of the assumptions that we make
about the kind of occupations
and tasks and jobs
that are going to be threatened
by automation in the future
are very likely to be
challenged going forward.
So as we put these trends together,
I think what it shows is that we could
very well end up in a future
with significant unemployment.
Or at a minimum,
we could face lots of underemployment
or stagnant wages,
maybe even declining wages.
And, of course, soaring levels
of inequality.
All of that, of course, is going to put
a terrific amount of stress
on the fabric of society.
But beyond that, there’s also
a fundamental economic problem,
and that arises because jobs
are currently the primary mechanism
that distributes income,
and therefore purchasing power,
to all the consumers that buy the products
and services we’re producing.
In order to have a vibrant market economy,
you’ve got to have
lots and lots of consumers
that are really capable of buying
the products and services
that are being produced.
If you don’t have that,
then you run the risk
of economic stagnation,
or maybe even a declining economic spiral,
as there simply aren’t enough
customers out there
to buy the products
and services being produced.
It’s really important to realize
that all of us as individuals rely
on access to that market economy
in order to be successful.
You can visualize that by thinking
in terms of one really exceptional person.
Imagine for a moment you take,
say, Steve Jobs,
and you drop him
on an island all by himself.
On that island, he’s going
to be running around,
gathering coconuts just like anyone else.
He’s really not going to be
anything special,
and the reason, of course,
is that there is no market
for him to scale
his incredible talents across.
So access to this market
is really critical to us as individuals,
and also to the entire system
in terms of it being sustainable.
So the question then becomes:
What exactly could we do about this?
And I think you can view this
through a very utopian framework.
You can imagine a future
where we all have to work less,
we have more time for leisure,
more time to spend with our families,
more time to do things that we find
genuinely rewarding
and so forth.
And I think that’s a terrific vision.
That’s something that we should
absolutely strive to move toward.
But at the same time, I think
we have to be realistic,
and we have to realize
that we’re very likely to face
a significant income distribution problem.
A lot of people are likely
to be left behind.
And I think that in order
to solve that problem,
we’re ultimately going
to have to find a way
to decouple incomes from traditional work.
And the best, more straightforward
way I know to do that
is some kind of a guaranteed income
or universal basic income.
Now, basic income is becoming
a very important idea.
It’s getting a lot
of traction and attention,
there are a lot of important
pilot projects
and experiments going on
throughout the world.
My own view is that a basic income
is not a panacea;
it’s not necessarily
a plug-and-play solution,
but rather, it’s a place to start.
It’s an idea that we can
build on and refine.
For example, one thing that I have
written quite a lot about
is the possibility of incorporating
explicit incentives into a basic income.
To illustrate that,
imagine that you are a struggling
high school student.
Imagine that you are at risk
of dropping out of school.
And yet, suppose you know
that at some point in the future,
no matter what,
you’re going to get the same
basic income as everyone else.
Now, to my mind, that creates
a very perverse incentive
for you to simply give up
and drop out of school.
So I would say, let’s not
structure things that way.
Instead, let’s pay people who graduate
from high school somewhat more
than those who simply drop out.
And we can take that idea of building
incentives into a basic income,
and maybe extend it to other areas.
For example, we might create
an incentive to work in the community
to help others,
or perhaps to do positive
things for the environment,
and so forth.
So by incorporating incentives
into a basic income,
we might actually improve it,
and also, perhaps, take at least
a couple of steps
towards solving another problem
that I think we’re quite possibly
going to face in the future,
and that is, how do we all find
meaning and fulfillment,
and how do we occupy our time
in a world where perhaps
there’s less demand for traditional work?
So by extending and refining
a basic income,
I think we can make it look better,
and we can also, perhaps, make it
more politically and socially acceptable
and feasible –
and, of course, by doing that,
we increase the odds
that it will actually come to be.
I think one of the most fundamental,
almost instinctive objections
that many of us have
to the idea of a basic income,
or really to any significant
expansion of the safety net,
is this fear that we’re going to end up
with too many people
riding in the economic cart,
and not enough people pulling that cart.
And yet, really, the whole point
I’m making here, of course,
is that in the future,
machines are increasingly going
to be capable of pulling that cart for us.
That should give us more options
for the way we structure
our society and our economy,
And I think eventually, it’s going to go
beyond simply being an option,
and it’s going to become an imperative.
The reason, of course,
is that all of this is going to put
such a degree of stress on our society,
and also because jobs are that mechanism
that gets purchasing power to consumers
so they can then drive the economy.
If, in fact, that mechanism
begins to erode in the future,
then we’re going to need to replace
it with something else
or we’re going to face the risk
that our whole system simply
may not be sustainable.
But the bottom line here
is that I really think
that solving these problems,
and especially finding a way
to build a future economy
that works for everyone,
at every level of our society,
is going to be one of the most important
challenges that we all face
in the coming years and decades.
Thank you very much.
(Applause)