All language subtitles for The.A.I.Race.2017.1080p.WEBRip.x264-RARBG

[music]

Hi, how are you feeling?
I just checked your health data.

Your last meal contributed sixty
percent of your daily nutrients

and you've completed
eleven thousand

steps towards your
daily fitness goal

so you can take a seat now.

I've got something
for you to watch

and I'll be watching too.

[music]

Tonight you're going
to see humans take

on the robots that
might replace them.

There always need to be
experienced people on the road.

From truckies to lawyers,
artificial intelligence is

coming
- actually, it's already here.

I didn't realise that it
would just be able to tell you

'hey, here's the exact answer
to your question'.

We'll challenge your
thinking about AI.

Same category, sixteen hundred

AI's going to become
like electricity.

Automation isn't going
to effect some workers

it's going to effect every
worker

and we let the
generation most effected

take on the experts

I think that the younger
generations probably have a

better idea of where things are
going than the older

generations.
[laughter]

Tonight, we'll help you
get ready for the AI race.

[music]

Australian truckies often
work up to 72 hours a week

and are now driving bigger
rigs to try to make ends meet

I've seen a lot of people
go backwards out of this

industry. And I've seen a lot
of pressures it's caused

on their family life,

especially when you're
paying the rig off.

now a new and unexpected
threat to Frank

and other truck drivers
is coming on fast.

Last year this driverless
truck in the U.S.

became the first to make
an interstate delivery.

it travelled nearly 200
kilometres on the open

road with no one at the
wheel, no human that is.

The idea of robot vehicles
on the open road

seemed ludicrous to most
people just 5 years ago.

Now just about every major auto
and tech company is developing

them.

so what changed?

An explosion in
artificial intelligence.

[car engine revs]

There's lots of AI
already in our lives,

you can already see it
on your smartphone.

Every time you use Siri, every
time you ask Alexa a question,

every time you actually
use your satellite

navigation, you're using
one of these algorithms,

you’re using some AI that
is recognising your speech,

answering questions,
giving you search results,

recommending books for
you to buy on Amazon.

They’re the beginnings of
AI everywhere in our lives.

We don't think about
electricity. Electricity powers

our planet, it powers pretty
much everything we do.

It’s going to be
that you walk into a

room and you say
“room, lights on”.

You sit in your car and
you say “take me home”.

[whistle noise]

A driverless car is essentially
a robot. It has a computer

that takes input from its
sensors and produces an output.

The main sensors are radar,
which can be found in adaptive

cruise control, ultrasonic
sensors and then there’s cameras

that collect images.

And this data is used to
control the car, to slow the

car down, to accelerate the
car, to turn the wheels.

There's been an explosion in AI
now because of the convergence

of four exponentials.

The first exponential is Moore's
Law, the fact that every two

years, we have a doubling
in computing performance.

The second exponential
is that every two years

we have a doubling of the
amount of data that we have,

because these machine learning
algorithms are very

hungry for data.

The third exponential
is we've been working on for AI

for 50 years or so now and
our algorithms are starting to

get better. And then
the fourth exponential

which is over the last few
years we've had a doubling

every two years of the amount
of funding going into AI.

We now have the compute
power, we now have the data,

we now have the algorithms
and we now have

a lot of people working
on the problems.

[car engine starting up]

It could be you just jump into
the car, you assume the car

knows where you need to go
because it has access to your

calendar, your diary, where
you're meant to be and if you

did not want the car to go where
your calendar says you ought to

be, then you need to tell the
car, "oh, and by the way, don't

take me to the meeting that's
in my calendar. Take me to the

beach!"

But Frank Black won't
have a bar of it.

I think it's crazy stuff.

You've got glitches in computers
now, the banks are having

glitches with their ATMs,
and emails are having glitches.

Who's to say this is going to be
perfect? And this is a lot more

dangerous if there's a
computer glitch.

There will always need to be
experienced people on the road.

Not machines.

Frank is going to explain why
he believes robots can never

match human drivers.

“Okay then, let's do it!"

But Frank is off
to a rocky start -

driverless trucks in Rio
Tinto mines in west Australia

show productivity gains of 15%

Frank needs to break every five
hours and rest every 12.

Oh, and he needs to eat and he
expects to be paid for his work

Robots don't need a salary.

Trials also indicate that
driverless vehicles save up to

15% on fuel and emissions,
especially when driving very

close together in a
formation called platooning

and at first glance,
driverless technology

could dramatically
reduce road accidents,

because it's estimated that 90%
of accidents are due to human

error such as fatigue or loss of
concentration.

Robots don't get tired.

But hang on - Frank's not done -
he's about to launch a comeback

using 30 years of driving
experience.

If there's something, say like a
group of kids playing with a

ball on the side of the road,
we can see that ball starting to

bounce towards the road, we
anticipate that there could be a

strong possibility that that
child will run out on the road

after that ball. I can't see how
a computer can anticipate that

for a start. And even if it did,
then what sort of reaction would

it take? Would it say swerve to
the left? Swerve to the right?

Would it just brake and bring
the vehicle to a stop?

What about if it can't stop
in time?

In fact, right now a
self-driving vehicle can only

react according to its program.
Anything unprogrammed can create

problems - like when this Tesla
drove into a road works barrier

after the human driver
failed to take back control.

and what it some of
the sensors fail?

What happens if something
gets on the lens?

The vehicle doesn't
know where it's going.

It's true - currently heavy rain
or fog or even unclear road

signs can bamboozle driverless
technology.

And then there's the most
unpredictable element of all

human drivers.

Stupidity always finds new
forms.

Quite often you see things
you’ve never seen before.

[crash of cars colliding]

That's why there are no plans to
trial driverless trucks in

complex urban settings right
now.

They'll initially be limited to
predictable multi-lane highways.

You also still need a human
right now to load and unload

a truck.

And a robot truck won't help
change your Tyre.

If someone's in trouble on the
road you'll usually find a

truckie has pulled over to
make sure they're alright.

Finally, there are road rules.

Australia requires human hands
on the steering wheel at all

times, in every state and
territory.

Hey Frank! You won the race!

One for the human beings!

But how long can human drivers
stay on top?

Nearly 400, 000 Australians
earn their living from driving,

even more when you add part-time
drivers.

But the race is on to deliver
the first version of a fully

autonomous vehicle in just 4
years

and it might not be hype because
AI is getting much better,

much faster every year

with a version of AI called
machine learning

Machine learning is the little
part of AI that is focused on

teaching programs to learn.

If you think about how we got to
be intelligent, we started out

not knowing very much when we
were born and most of what we've

got is through learning.

and so, we write programs that
learn to improve themselves.

They need - at the moment - lots
of data and they get better and

better, and in many cases,
certainly for narrow focus

domains, we can often actually
exceed actual human performance.

[music]

When AlphaGo beat Lee Sedol
last year, one of the best

Go players on the planet,
that was a landmark moment.

So we’ve always used games as
benchmarks, both between humans

and between humans and machines
and, you know, a quarter century

ago, chess fell to the
computers.

And at that time people thought

well Go isn’t going to be like
that.

Because in Go, there’s so many
more possible moves

and the best Go players weren’t
working by trying all

possibilities ahead, they were
working on the kind of, the

gestalt of what it looked like,
and working on intuition.

We didn’t have any idea of how
to instil that type of intuition

into a computer.

but what happened is we've got
some recent techniques with deep

learning where we’re able to do
things like understand photos,

understand speech and so on and
people said maybe this will be

the key to getting that type
of intuition.

So first, it started by
practicing on every game that a

master had ever played.

You feed them all in and it
practices on that.

The key was to get AlphaGo good
enough from training it on

past games by humans so that it
could then start playing itself

and improving itself.

And one thing that’s very
interesting is that the amount

of time it took, the total
number of person years invested

is a tenth or less than the
amount of time it took for IBM

to do the chess playing.

So the rate of learning is going
to be exponential.

Something that we as humans
are not used to seeing.

We have to learn things
painfully ourselves

and the computers are going to
learn on a planet wide scale,

not an individual level.

There is this interesting idea
that the intelligence would just

suddenly explode and take us
to what’s called the Singularity

where machines now improve
themselves almost without end.

There are lots of reasons to
suppose that maybe that might

not happen, but if it does
happen, most of my colleagues

think it’s about 50 years away.
Maybe even 100.

[intake of breath]

I’m not convinced how important
that intelligence is, right?

So I think that there is lots of
different attributes and

intelligence is only one of them
and there certainly are tasks

that having a lot of
intelligence would help,

and being able to compute
quickly would help.

So if I want to trade stocks,
then having a computer that's

smarter than anybody else’s is
going to give me a definite

advantage.

But I think if I wanted to solve
the Middle East crisis,

I don’t think it’s not being
solved because nobody is smart

enough.

But AI experts believe robot
cars will improve so much that

humans will eventually be banned
from driving.

[music]

Big roadblocks remain, not the
least of which is public

acceptance

- as we found out after inviting
professional drivers to meet two

robot car experts.

[introductions]

Straight away the first thing
has to be safety,

you definitely have to have
safety paramount,

and obviously efficiency.

So the big question is
- when is it going to happen?

In the next five to ten years we
will see highly autonomous

vehicles on the road.

If you want to drive from Sydney
to Canberra, you drive to the

freeway, activate autopilot or
whatever it will be called at

and by the time you arrive in
Canberra, the car asks you to

take back control.

There are predictions that in
twenty years’ time, 50% of the

new vehicles will actually be
completely driverless.

What makes us think that these
computers and these vehicles

are going to be foolproof?

Well we were able to send
rockets to the moon,

and I think that there are ways
of doing it, and you can have

backup systems, and you can have
backups for your backups.

But I agree, reliability is a
big question mark.

But we're not talking about a
phone call dropping out or an

email shutting down, we're
talking about a sixty ton

vehicle, in traffic, that's
going to kill people.

There will be deaths if it makes
a mistake.

I think we need to accept that
there will still be accidents.

A machine can make a mistake,
can shut down, and fail.

And if we reduce accidents by
say ninety percent,

there will still be ten percent
of the current accidents will

still occur on the network.

How can you say there's going
to be ninety percent?

How do you work that out?

Ninety percent is because ninety
percent of the accidents are

because of human error.

The idea is if we take the human
out,

we could potentially reduce it
by ninety percent.

Have any of you ever driven a
car available on the market

today with all this technology,
autopilot

and everything in there?

It's absolutely unbelievable how
safe and comfortable you feel.

I think people will ultimately
accept this technology,

because we will be going in
steps.

I would say, for me as an Uber
driver, we're providing a

passenger service, and those
passengers when they’re going to

the airport, a lot of luggage.

If it's an elderly passenger,
they need help to get into the

car, they need help getting out
of the car.

The human factor needs to be
there.

I would argue that you can
offer a much better service if

you're not also driving.

So cars taking care of the
journey and you're taking care

of the customer. And improving
the customer experience.

And I think there's a lot of
scope for improvement in the

taxi and Uber customer
experience.

You could offer tax advice, you
could offer financial advice.

It's unlimited.

Then we go back though.
We're not at fully driverless

vehicles anymore, we've still
got a babysitter there

and a human being there to look
after the car,

so what are we gaining with the
driverless technology?

Well, the opportunity to do
that?

But weren't you trying to reduce
costs

by not having a driver in the
vehicle?

Well it depends what people are
paying for, okay.

If you're in business,

you are trying to get as many
customers as possible.

And if your competitor has
autonomous vehicles

and is offering day care
services or looking after

disabled, then you probably
won't be in business very long

if they're able to provide a
much better customer experience.

For my personal views, I like
to drive my car, not just to

sit, I want to enjoy driving.

Well I think in 50 years
there'll be special places for

people with vintage cars that
they can go out and drive

around.

so we won't be able to go for a
Sunday drive in our vintage car

because these autonomous
vehicles have got our roads.

I mean in the future when all
the cars are autonomous we won't

need traffic lights,

because the cars will just
negotiate between themselves

when they come to intersections,
roundabouts.

Can I ask you a question?

If we would do a trial

with highly automated platooning

of big road trains, would you
like to be involved?

Yes I'd be involved. Yeah,
why not.

If you can convince Frank,
you can convince anybody.

If you want to come out with us
- and I bet Frank’s the same

as well - if you want to come
for a drive in the truck

and see exactly what it’s like
and the little issues that would

never have been thought of
I mean my door’s always open –

you're more than welcome to come
with me

Oh, definitely. I think that’s…

It's time for a road trip!

[laughter]

But drivers aren't the only ones
trying to find their way into

the AI future.

[music]

Across town, it's after work
drinks for a group of young and

aspiring professionals.

Most have at least one
university degree or are

studying for one -
Like Christine Maibom.

I think as law students, we know
now that it's pretty tough,

even to like get your foot in
the door.

I think that, at the end of the
day, the employment rate for

grads is still pretty high.

Tertiary degrees usually shield
against technological upheaval

but this time AI will automate
not just more physical tasks,

but thinking ones.

Waiting upstairs for Christine,
is a new artificial intelligence

application, one that could
impact the research typically

done by paralegals.

We invited her to compete
against it in front of her peers

Adelaide tax lawyer, Adrian
Cartland, came up with the idea

for the AI, called Ailira.

I am here with AILIRA, the
Artificially Intelligent Legal

Information Research Assistant
and you're going to see if you

can beat her.

So what we've got here is a
tax question.

Adrian explains to Christine
what sounds like a complicated

corporate tax question.

So does that make sense?
- Yeah, yep.

Very familiar? Ready?
- I'm ready.

Okay, guys. Ready. Set. Go.

[music]

And here we have the answer.

So you've got the answer?
- We’re done.

That's 30 seconds.

Christine where are you up
to with the search?

I'm at Section 44 of the Income
Tax Assessment Act.

Maybe it has the answer,
I haven't looked through it yet.

You're in the right act.

Do you want to keep going?
Do you want to give it some

time?

I can keep going for a little
bit, yeah sure.

[music]

No pressure Christine.
We're at a minute.

Okay, might need an hour for
this one.

This is, you know, really
complex tax law.

Like I’ve given you a hard
question.

You were in the Income Tax
Assessment Act, you were doing

your research. What’s your
process?

Normally what I would do is
probably try and find the

legislation first and then I’ll
probably look to any commentary

on the issue.

Find specific keywords, so for
example ‘consolidated group

and assessable income' are
obviously there.

That's a pretty standard way.
That's what I would approach.

If you put this whole thing into
a keyword search,

it's going to break down after
about four, five, seven words,

whereas this is, you know, three
or four hundred words.

So all I've done,

is I've entered in the question
here. I've copied and pasted it.

I've clicked on submit,

and she's read literally through
literally millions of cases

as soon as I pressed search.

And then she's come through,
she's said here are the answers

- oh wow
She's highlighted in there

what she thinks is the answer.

Yeah I mean, wow. Even down to
the fact that it can answer

those very specific questions.

I didn't realise that it would
just be able to tell you,

'hey, here's the exact answer
to your question'.

It's awesome.

I think, obviously, for
paralegals, I think it's

particularly scary because we're
already in such a competitive

market.

Adrian Cartland believes AI
could blow up lawyers' monopoly

on basic legal know-how - and he
has an astonishing example

of that.

My girlfriend is a speech
pathologist who has no idea

about law, and she used AILIRA
AILIRA to pass the

Adelaide University Tax law
exam.

oh wow.

Automation is moving up in the
world.

Here's Claire, a financial
planner.

It's estimated that 15 percent
of an average financial

planner's time is spent on tasks
that can be done by AI.

What kind of things do you see
it ultimately taking over?

I would say everything except
talking to your clients. Yeah.

Here's Simon, he used to be a
secondary school teacher.

One fifth of that job can be
done by AI

Simon's now become a university
lecturer,

which is less vulnerable.

I think there's huge potential
for AI and other educational

technologies.

Obviously it's a little bit
worrying if we are talking about

making a bunch of people
redundant.

And did I mention journalists?

I hope you enjoyed tonight’s
program.

The percentage figures were
calculated by economist

Andrew Charlton and his team,

after drilling into Australian
workforce statistics.

For the first time we broke the
Australian economy down into

20 billion hours of work.

And we asked what does every
Australian do with their day

and how or what do they do in
their job

change over the next 15 years.

I think the biggest
misconception is that everyone

talks about automation as
destroying jobs.

The reality is automation
changes every job.

It's not so much about what jobs
will we do,

but how will we do our jobs.

Because automation isn't going
to affect some workers,

it’s going to affect every
worker.

But if there's less to do at
work,

that's got to mean less work or
less pay - or both. Doesn't it?

If Australia embraces
automation,

there is a $2.1 trillion
opportunity for us

over the next 15 years.

But here's the thing - we only
get that opportunity

if we do two things.

Firstly, if we manage the
transition and we ensure

that all of that time that is
lost to machines

from the Australian workplace
is redeployed

and people are found new jobs
and new tasks

And condition number two is
that we embrace automation

and bring it into our
workplaces, and take advantage

of the benefits of technology
and productivity.

But Australia's not doing
well at either.

Right now Australia is lagging.

One in ten Australian companies
is embracing automation

and that is roughly half the
rate of some of our

global peers.

Australia hasn’t been very good
historically at transitioning

workers affected by big
technology shifts.

Over the last 25 years, 1 in 10
unskilled men who lost their job

never worked again.

Today 4 in 10 unskilled men
don’t participate in

the labour market.

We asked a group of young
lawyers and legal students

how they feel about embracing
AI - the contrasts were stark.

I often get asked,

you know, do you feel
threatened?

Absolutely not! I am confident
and I’m excited about

opportunities that AI presents.

I think the real focus will be
on not only upskilling,

but reskilling and about
diversifying your skillset.

I think for me, I still have

an underlying concern about how
much of the work is going to be

taken away from someone who is

still learning the law and just
wants a job part time where they

can sort of help with some of
those less,

you know, judgment-based
high level tasks.

How much software is out there?
AI, for legal firms

at the moment.

There’s quite a lot

There’s often a few competing
in the same space,

so there’s a few that my law
firm has trialled in,

for example, due diligence

which are great at identifying
certain clauses.

So rather than the lawyer
sitting there trying to find

an assignment or a change of
control clause,

it will pull that out.

How much time do you think using
the AI cuts down on that kind of

just crunching lots of documents
and numbers?

Immensely! I would say
potentially up to about 20%

of our time in terms of going
through and locating those

clauses or pulling them out,
extracting them,

which of course delivers way
better value for our clients

which is great.

Well I think the first reaction
was obviously very

worried, I suppose.

you just see the way that this
burns through these sort of

banal tasks that we would
be doing at an entry level job.

Yeah, it's quite an intuitive
response, I suppose,

that we're just a bit worried.

And also it was just so easy,
it was just copy and paste.

It means that anyone could do it
really, so

you don't need the sort of
specialised skills that are

getting taught to us in our
law degrees.

It's pretty much just a press
a button job.

AI is like Tony Stark's Iron Man
suit.

It takes someone and makes them

into Superman, makes them
fantastic!

And you could suddenly be doing
things that are like

10 times above your level

and providing that much cheaper
than anyone else could do it.

The legal work of the future be
done by

social workers, psychiatrists,
conveyancers, tax agents,

accountants.

They have that personal skillset
that lawyers sometimes lack.

I also wonder just how much law
school should be

teaching us about technology
and new ways of

working in legal workforce,

because I mean a lot of what you
guys are saying,

I’ve heard for the first time.

I certainly agree with that
statement. This is the first

time I've heard the bulk of
this,

especially hearing that there is
already existing a lot of AI.

Unfortunately, our education
system just isn’t keeping up.

Our research shows that right
now,

up to 60% of young Australians
currently in education

are studying for jobs that are

highly likely to be automated
over the next 30 years.

It's difficult to know what will
be hit hardest first,

but jobs that help young people
make ends meet

are among the most at risk.

Like hospitality workers.

So the figure that they're
giving us is 58%

could be done by versions of AI.

How does that make you feel?

Very, very frustrated.
That is really scary.

I don’t know what other job I
could do whilst

studying, or that sort of thing
or as a fall-back career.

It’s what all my friends have
done, it’s what I’ve done,

it sort of just helps you
survive and

pay for the food that you need
to eat each week.

It may take a while to be cost
effective,

but robots can now help take
orders, flip burgers,

make coffee, deliver food.

Young people will be the most
affected by these changes,

because the types of roles that
young people take

are precisely the type of

entry level task that can be
most easily done by machines

and Artificial Intelligence.

But here this evening,

there's at least one young
student who's a little more

confident about the future.

So Ani, how much of your job as
a doctor,

do you imagine that AI could do
pretty much now?

Now?

Not much, maybe 5, 10 percent.
Yeah.

[music]

But Artificial Intelligence is
also moving into healthcare.

- Watson?
- What is: Soron?

- Watson?
- What is: leg?

- Yes...Watson?
- What is: executor?

- Right. Watson?
- What is: shoe?

- You are right.
- Same category, 1600.

Answer...

So in the earliest days of
Artificial Intelligence and

machine learning it was all
around

teaching computers to play
games.

[Jeopardy]

But today, with those machine
learning algorithms

we're teaching those algorithms
how to learn the language of

medicine.

We invited Aniruddh to hear
about IBM research in cancer

treatment using its AI
supercomputer, Watson.

Today I’m going to take you
through a demonstration of

Watson for oncology.

This is a product that brings
together a multitude of

disparate data sources and is
able to learn and reason

and generate treatment
recommendations.

This patient is a 62 year
patient that’s been diagnosed

with breast cancer and she’s
presenting to this clinician.

So the clinician has now entered
this note in and

Watson has read and understood
that note.

Watson can read natural
language.

When I attach this final bit of
information, the ask Watson

button turns green and at
which stage we’re ready to ask

Watson for treatment
recommendations.

Within seconds, Watson has read
through all the patient's

records and doctor's notes,

as well as relevant medical
articles, guidelines and trials.

And what it comes up with is a
set of ranked

treatment recommendations.

Down the bottom, we can see

those in red that Watson
is not recommending.

Does it take into account how
many citations a different

article might have used?
Say the more citations, the more

it’s going to trust it?

So this is again where we need
clinician input

to be able to make those
recommendations.

Natalie, you’ve shown us this
and

you’ve said that this would be a
clinician going through this.

But the fields that you’ve
shown, really an educated

patient could fill a lot of
these fields from

their own information.

What do you think about that
approach?

The patients essentially
getting their own second opinion

from Watson for themselves?

I see this as a potential tool
to do that.

AI's growing expertise at image
recognition

is also being harnessed by IBM
to train Watson on retinal

scans.

One in three diabetics have
associated eye disease,

but only about half these
diabetics get regular checks.

We know that with diabetes the
majority of vision loss is

actually preventable,

if timely treatment is
instigated

and so that if we can tap into
that group,

you’re already looking at
potentially an incredible

improvement in quality of life
for those patients.

How could something like that
happen?

You could have a situation where
you have a smartphone

application. You take a retinal
selfie if you’d like.

That then is uploaded to an AI
platform,

analysed instantly and then you
have a process

by which you instantly you're
known

to have high risk or low
risk disease.

How long does it take to analyse
a single retinal image using

the platform.

Very close to real time, in
a matter of seconds.

I mean this is obviously very,
very early days,

but the hope is that one day

these sorts of technologies
will be widely available

to everyone for this sort of
self-analysis.

Just like law,

AI might one day enable patients
to DIY their own expert

diagnosis and treatment
recommendations.

Some doctors will absolutely
feel threatened by it,

but I’d come back to the point
that, you know,

you want to think about it from
the patient’s perspective.

So if you’re an oncologist,

sitting in the clinic with your
patient,

the sorts of things that you’re
dealing with is

things like giving bad news to
patients and I don’t think

patients want to get bad news
from a machine.

So it’s really that ability to
have that intelligent

assistant who's up to date

and providing you with the
information that you need,

and providing it quickly.

We like to use the term
augmented intelligence.

I think one interesting way to
think about this is I mentioned

50,000 oncology journals, a year

Now if you’re a clinician trying
to read all of those

50,000 oncology journals,

that would mean you would need
about 160 hours a week

just to read the oncology

articles that are published
today.

Watson’s ability to process all
of this medical literature

and information and text is
immense.

It’s 200 million pages of
information in seconds.

Wow! I need a bit of work
on myself then.

IBM is just one of many
companies promoting the promise

of AI in healthcare

- but for all these machine
learning algorithms to be

effective, they need lots of
data

lots of our private medical data

In my conversations with my
patients and the patient

advocates that we’ve spoken to,

you know, they certainly want
their privacy protected.

But I think it’s actually a
higher priority for them

to see this data being used for
the public good.

But once it has all the data,
could this intelligent assistant

ultimately disrupt medicine's
centuries old hierarchy?

They should have more general
practitioners and less of the

specialty.

So doctors,

They'll have more time to have
a better relationship with you

maybe they will be talking about
your overall health

rather than waiting for you
to come in with symptoms

and if they do have to

analyse an X-ray and look for
disease,

they will have a computer to
do that,

they will check what the
computer does,

but they will be pretty
confident that the

computer is going to do a
good job.

When we first talked to you,
Ani, in Sydney,

you said you thought that in
terms of the time spent on tasks

that doctors do

that AI might be able to handle
maybe five,

maybe at the outside 10%.

How do you see that now?

Definitely a lot more! I’d say
it could go up to 40-50%,

using it as a tool rather than
taking over I’d say is going

to happen.

The percentage for doctors is
21%

but that's likely to grow in the
coming decades,

as it will for every profession,
and every job.

We've been through technological
upheaval before,

but this time, it's different.

One of the challenges will be
that

the AI revolution happens
probably much quicker than the

Industrial Revolution.

We don’t have to build big
steam engines,

we just have to copy code

and that takes almost no time
and no cost.

There is a very serious question

– whether there will be as many
jobs left as before.

[music]

I think the question is what is
the rate of change and

is that going to be so fast
that it’s a shock to the system

that’s going to be hard to
recover from?

I guess I’m worried about
whether people will get

frustrated with that and whether
that will lead to

inequality of haves and have
nots.

And maybe we need some
additional safety nets

for those who

fall through those cracks
and aren’t able to be lifted.

We should explore ideas like
Universal Basic Income

to make sure that everyone has a
cushion to try new ideas.

What to do about mass
unemployment.

This is going to be a massive
social challenge,

and I think ultimately we will
have to have

some kind of Universal Basic
Income.

I don’t think we’re going to
have a choice.

I think it’s good that we’re
experimenting and looking

at various things.

I think we don't know the
answer yet

for what’s going to be
effective.

The ascent of Artificial
Intelligence promises

spectacular opportunities

but also many risks.

To kickstart a national
conversation,

we brought together the
generation most affected

with some of the experts
helping to design the future.

You will have the ability to
do jobs

that your parents and
grandparents couldn’t have

dreamed of.

And it’s going to require us to
constantly

be educating ourselves to keep
ahead of the machines.

First of all, I wanted to say,
I think

the younger generations probably
have a better idea about where

things are going than the
older generations.

[laughter]

Sorry, but I think...

So where have we got it wrong?

Well, I think the younger
people, they’ve grown up

being digital natives

and so they know where it’s
going, they know what it

has the potential to do

and they can foresee where
it’s going to go in the future.

We all hate that question at a
party, of like, what do you do?

And I think in the future you
will be asked instead

what did you do today or
what did you do this week?

We all think of jobs like a
secure safe thing

but if you work one role,
one job title at one company,

then you’re actually setting
yourself up to be more likely to

be automated in the future.

The technology in the building
game is advancing.

Kind of worrying if you’re a

22-year old carpenter,
for example.

I think there’s often this
misconception that you

have to think about robot
physically replacing you.

One robot for one job.

Actually it’s going to be, in
many cases,

a lot more subtle than that.

In your case, there will be a
lot more

of the manufacturing of the
carpentry happens off-site

That happened between the start
of my apprenticeship and

when I finished.

We were moving into all the
frames and everything were built

off-site and brought to you.

And you’d do all the work that
used to take you three weeks

in three days.

I mean there is one aspect of
carpentry, I think, that will

stay forever, which is the
more artisan side of carpentry.

We will appreciate things that
are made,

that have been touched by the
human hand.

I think there will be a huge
impact in

retail in terms of being
influenced by automation.

Probably the cashier, you
probably don’t need someone

there necessarily to take that
consumer’s money,

that could be done quite simply.

But at the same time,
just from having a job,

there is a biological need met
there, which

I think we're overlooking a lot,

I think we might not have a
great depression economically

but actually mentally.

AI is clearly going to create a
whole new raft of jobs.

So you know, there are the
people who actually

build these AI systems, I mean,
if you have a robot at home then

every now and then,
you're going to need somebody

to swing by your home to check
it out.

There will be people who need to
train these robots

and there will be robot
therapists,

there will be obedience school
for robots

and other kinds of –

I'm not joking!

[music]

What should these young people
do today or tomorrow

to get ready for this?

There really is only one
strategy and that is to

embrace the technology

and to learn about it, and
to understand

as far as possible, you know,

what kind of impact it has
on your job and your goals.

I think the key skills that
people need are the skills

to work with machines.

I don’t think everyone needs
to become a coder.

You know, in fact, if Artificial
Intelligence is any good,

machines will be better at
writing code than humans are,

but people need to be able to
work with code,

work with the output of those
machines

and turn it into valuable

commodities and services that
other people want.

I disagree that we’ll
necessarily

have to work with the machines,
the machines actually

are going to understand us
quite well.

So what are our strengths, what
are our human strengths?

Well, those are

our creativity, our adaptability

and our emotional and
social intelligence.

How do people get those skills?

[laughter]

Well, if they’re the
important skills.

Well, I think the curriculum
at schools and at universities

has to change

so that those are the skills
that are taught

they are barely taught if you
look at the current curriculums

you have to change the
curriculum.

So those become the really
important skills.

A lot of these discussions seem
to be skirting around the issue

that really is the core of it,

is that the economic system is
really the problem at play here.

It’s all about the ownership of
the AI and the robotics

and the algorithms

If that ownership was shared and
the wealth was shared,

then we’d be able to share in
that wealth.

The trend is going to be towards
big companies like

Amazon and Google,

I don’t really see a
fragmentation

because whoever has the data,
has the power.

Data is considered by many to be
the new oil,

because as we move to a
digital economy,

we can’t have automation without
data.

What we see as an example is
value now moving from

physical assets to data assets.

For example, Facebook.

Today when I looked the market
capitalisation was about

$479 billion.

Now if you contrast that with
Qantas,

who has a lot of physical
assets,

their market capitalisation was
$9 billion.

But you can go a step further
and if you look at

the underlying structure of
Qantas,

about $5 billion can be
attributed to their loyalty

program.

which is effectively a
data-centric asset

that they’ve created.

So the jobs of the future will
leverage data.

The ownership of data is
important because

you think about Facebook

over time Facebook learns about
you

and over time the service
improves as you use it further.

So whoever gets to scale with
these data centric businesses

has a natural advantage and a
natural monopolistic tendency.

In twenty years’ time, if big
corporations like Google

and Facebook aren’t broken up,

then I would be incredibly
worried for our future.

Part of the reason why there are
so many monopolies is because

they’ve managed to control
access to that data.

Breaking them up I think
would be one of the

things that we need to do, to be
able to open the data up

so that all of us can share the
prosperity.

But the global economy is very
rich and complex,

and Australia can’t just say
oh we’re opening the data.

I just still think we’re leaving
a section of the population

behind. And some people
in our country

can’t afford a computer or
the internet or a

home to live in.

It’d be a bit

crazy to just let it all go free
market, just go crazy,

because we don’t know if
everyone is on that,

make the world a better place
type thing.

I personally don’t want to be
served by a computer,

even if I am buying a coffee
and things like that.

I enjoy that human connection
and I think that

human connection’s really
important for isolated people,

and that job might be really
important for that person

and creating meaning in their
life and purpose in their life.

They might not be skilled enough
to work in another industry.

My first thought is, if it is
about human interaction,

why do you need to

be buying a coffee to
have that human interaction?

Why not just have the machine do
the transaction

and people can focus simply
on having a conversation?

Perhaps part of that is to
simply say

it is a productive role in
society to interact,

to have conversations

and then we can remunerate that
and make that a part of people’s

roles in society.

It could be a lot of things
around caring,

interpersonal interactions, the
type of conversations you were

talking about.

I think they will become an
increasingly important part

of the way we interact,
the way we find meaning,

and potentially the way we
receive remuneration.

I think we all have choices to
make,

and amongst those are

the degree to which we allow

or want machines to be part of
our emotional engagement.

Will we entrust our children to
robot nannies?

Algorithms can be taught to

interpret and perceive human
emotion.

We can recognise from an image
that a person is smiling,

we can see from a frown that
they’re angry,

understand the emotion that’s in
text or speech

and you combine that together
with other data, then yes,

you can get a much more refined
view of what is that emotion,

what is being expressed.

But does an Artificial
Intelligence algorithm actually

understand emotion?

No, not presently.

We’re in the early days of
emotion detection

but this could go quite far,
you could certainly see

emotional responses

from algorithms, from computer
systems

in caring for people, in
teaching, in our workplace.

And to some extent that’s
already happening right now

as people interact with bots
online, ask questions,

and actually feel like,

oftentimes, they’re interacting
with a real person.

[music]

When TAY was released in the US
to audience

of 20 to 25 year olds,

the interactions that TAY was
having on the internet

included hate speech and
trolling.

It only lasted a day,
but it’s a really

fascinating lesson in how
careful we need to be

in the interaction between an
an artificial intelligence

and its society.

The key thing is

what we teach our AI, it
reflects back to us.

First, you will

want the robot in your
home because it’s helpful,

next minute you will need it
because you start to rely on it,

and then you can’t live
without it.

I think it sounds scary to be
honest

The thought of replacing that
human interaction

and even having robots in your
home that you interact daily

with like a member of the
family.

I think, yeah,

really human interaction and
real empathy can’t be replaced

and at the end of the day,

the robot doesn’t genuinely
care about you.

I think you certainly can’t
stop it.

I mean there is no way to
stop it.

Software systems and robots,
of course can empathize

and they can empathize so much
better than people

because they will be able to
extract so much more data and

not just about you, but a lot
of people

like you around the world.

To go to this question of
whether we can

or cannot stop it,

we’re seeing for example in the
United States, already

computers and algorithms being
used to help

judges make decisions.

And there I think is a line
we probably don’t want to cross.

We don’t want to wake up

and discover we’re in a world

where we’re locking people up
because of an algorithm.

I realise it’s fraught but all
of the evidence says

that AI algorithms are much
more reliable than people.

People are so flawed and you
know,

they are very biased,
we discriminate

and that is much more
problematic

and the reason is that people
are not transparent

in the same way as an AI
algorithm is.

Humans are deeply fallible.

I veer on the side of saying
that yes

I do not necessarily trust
judges as much as I do

well designed algorithms.

The most important decisions
we make in our society,

the most serious crimes we do in
front of a jury of our peers,

and we’ve done that for hundreds
of years.

And that’s something that I
think we should

give up only very lightly.

Nathan what do you think?

Well, I think ultimately I don’t
know how far you want to

go with this discussion but

[laughter]

because like ultimately what
will end up happening

is we’re going to become the
second intelligent species on

this planet

and if you take it to that
degree,

do we actually merge with the
AI?

So we have to merge our brains

with AI, it’s the only way
forward. It’s inevitable.

But we won’t be human then,
we’ll be something else.

Superhuman!

Superhuman? But that’s a choice.

Do we not value our humanity
anymore?

[music]

we started off talking about
jobs.

But somehow Artificial
Intelligence forces us

to also think about what it
means to be human,

about what we value and who
controls that.

[music]

So here we are on the precipice
of another technological

transformation.

The last industrial revolution
turned society upside down.

It ultimately delivered greater
prosperity and many more jobs

as well as the 8 hour day and
weekends.

But the transition was at times
shocking and violent.

The question is can we do
better this time?

We don’t realise the future is
not inevitable.

The future is the result of the
decisions we make today.

These technologies are morally
neutral.

They can be used for good or for
bad.

There’s immense good things they
can do.

They can eliminate many
diseases,

they can help eliminate poverty,
they could tackle

climate change.

Equally, the technology can be
used for lots of bad.

It can be used to increase
inequality,

it can be used to transform
warfare,

it could be used to make our
lives much worse.

We get to make those choices.