Original subtitles

[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.