Original subtitles

- [Gemma] Artificial intelligence,

for years, a dream of scientists and Hollywood producers,

but also the violent

and destructive stuff of our nightmares.

My name is Gemma Chan.

I play a robot in the futuristic sci-fi drama, "Humans."

As the development of artificial intelligence accelerates

and starts to pervade every aspect of our lives,

I'm hoping to find out whether the world depicted

in science fiction is 10 years away,

100 years away, or closer than we think.

I'm going to meet some of the greatest minds in science.

They're divided.

Some think AI holds the key to a safe and prosperous future.

- I see AI as an opportunity actually,

to unlock humanity's full potential.

- [Gemma] Others think the nightmare

may just be about to begin.

- We're worried that this will come out too soon,

people will die.

- Once you have a kind of super intelligent genie

that's out of the bottle,

it might not be possible to put it back in again.

- [Gemma] To see just how far we can take the power of AI,

we're conducting a unique experiment,

building a robot version of me.

- This is really the first time we've tried this,

so it's very, very new.

(intense music)

- It's really quite uncanny.

A robot that looks like me is one thing.

That is my nose.

But can it harness the power of artificial intelligence

to actually think like me?

- [Robot Gemma] I like the taste of cheese.

(laughing)

Can we build a human?

It's so strange.

(intense music)

(eerie music)

Hi!

Hello.

Nice to meet you.

Day one of the robot build

and we need a body to house its brain.

- Welcome to Millennium FX.

- [Gemma] Thank you, thanks for having us.

Millennium FX is one of Europe's leading suppliers

of prosthetics, animatronics and specialist makeup.

(eerie music)

Oh my goodness.

- This is something that we do a lot at Millennium.

Babies come up in TV shows a lot

but you can't film on babies for very long

so we produce these lifelike babies

so that people can hold them.

- It's just so weird.

The closer something is to looking human,

the weirder it feels.

- It's what we call the Uncanny Valley,

where your mind kind of knows, it kinda knows,

that no matter how perfect something is,

no matter how good the movement is

or how realistic it looks,

your mind knows that there's something not quite right.

- I think I'm just gonna put her down.

Making a silicone duplicate will enable the robot builders

to create a lifelike skin.

A-E-I-O-U.

My double will need to have hundreds of facial expressions

just like me and they'll need to be in sync

with what the artificial brain is thinking.

Hi, pleasure to meet you.

Time for me to get my face copied.

- [Kate] We're going to have you 3D scanned.

- Kate Walsh is the producer in charge.

- Today we're gonna try and watch you as closely as possible

and see if we can pick up on all the subtle expressions

and movements of your face.

- I'm intrigued to see how far we can go

and how lifelike we can make it.

I really have no idea what to expect.

- [Man] Three, two, one, scanning.

(eerie music)

- [Gemma] It's so cool.

- This is the room where we'll be doing your headcast

and on the wall behind you are some of the people

who have had the pleasure of light casting before.

- Is that Gordon Ramsay there?

- [Kate] It is, yes.

- That's it, perfect.

And if you wanna just open your mouth, just a fraction,

and just blow out gently.

That's it.

Keep your eyes nice and relaxed.

You're doing fantastically.

- [Gemma] The cast consists

of two different types of silicone

and is finished off with a traditional plaster shell.

- [Man] One, two, three. (camera snapping)

Great shot. Well done.

- [Gemma] The whole process needs to be quick,

as after 20 minutes, the heat becomes intolerable.

- [Man] We're gonna wipe that off.

That's great.

That's a great cast and you did really, really, really well.

- Great, thank you!

While the team will need to turn silicone

into something that resembles me,

a bigger challenge will be to create its mind.

For that, the robot needs artificial intelligence,

defined by computer scientists as a machine

having the capability to make a human-like decision.

Thank you so much for agreeing to talk to us today.

Oxford professor of philosophy, Nick Bostrom,

is one of the world's leading experts in AI.

- So the goal of AI, artificial intelligence,

has all along, since it's beginnings in the 50s,

been to make machines that have the same general purpose,

smartness, that we humans have,

that can do all the things that the human brain can do.

(intense music)

- [Gemma] From smartphones to share prices,

from online customer support, to CCTV,

we're now surrounded by so much of it,

we started to take it for granted.

- AI is a general purpose technology.

You can go through any sector in the economy.

You can go through healthcare, entertainment,

medicine, defense, you name it,

it could think of ways in which processes

could be improved by being smarter.

- [Gemma] Machines are being developed as soldiers,

mastering real time translations

using the latest in word recognition software.

- Can you hear me in french?

(speaking foreign language)

- Oh weird! (laughing)

- [Gemma] And AI could soon have a significant role

in the legal system.

An AI judge that was shadowing cases

from the European Court of Human Rights,

recently came up with the same decision

as the human judge in four out of five cases.

(eerie music)

The medical profession is also making use of it.

These Canadian scientists have recently been

to the U.K. to sell a AI diagnostic tool

that they say can identify a tumor instantly

and accurately without the need for a biopsy

and with immediate results.

- Just like a human, the machine got trained

on multiple thousands of images to get an accuracy level.

- [Gemma] Not only is it less invasive and quicker,

but it could say the NHS millions of pounds if introduced.

(relaxing music)

Some of us are already entrusting our lives to AI.

(relaxing music)

This is the Tesla Model S,

on the market for a cool 100,000 pounds.

(relaxing music)

Pick a lane.

Noel Sharkey is an academic specializing in AI

and is interested in how autonomous decision making

will effect us all.

- You're gonna take your hands off.

- I've arranged to meet him on a test track

to try out one of the car's most impressive features,

the ability to drive itself using artificial intelligence.

(intense music)

All right, the hands are coming off.

The hands are off.

- Whoa. - We're approaching a bend.

- Oh!

(dramatic music)

(beeping)

- Oh my goodness. See that?

It nearly took us off the road there.

- [Noel] Yes.

- I know this is meant to be

a less stressful driving experience but I don't know.

I'm sweating. - Yeah, of course.

- I'm sweating.

Oh my goodness, right.

- You try being the passenger.

(laughing)

- The semi-autonomous cars like this

are really quite controversial,

especially in the field of robotics

and we really need much broader societal debate.

The U.K. government's rolling out autonomous cars

and they haven't really debated

as to whether people want it or not.

- [Gemma] This controversy has been fueled

by drivers in America,

ignoring the company's safety guidelines

and uploading outrageous clips to the internet.

- But I think what puts it all in perspective

is the recent fatal crash in the U.S.A.

- Yes, I remember hearing something about that in the news.

Earlier this year, a driver crashed and died,

allegedly whilst watching a Harry Potter film.

His car hit the underside of a trailer at 74 miles per hour.

- It pulled out right in front of it, bright white trailer,

bright white sky, very sunny,

and the camera couldn't detect the trailer

and that's why it ran into it.

- And I suppose the more autonomous vehicles

you have on the road,

the likelihood of incidents like that, or accidents,

they're bound to happen.

- It's measuring the space now with its sensors, I think.

(beeping)

- [Gemma] But while Tesla say AI cars will have fewer accidents-

Wow!

Ultimately, we won't be in control.

Look at, look!

It's correcting itself as well!

- So you imagine what's going to happen

when there really are fully autonomous

because you're gonna have to delegate

all your driving decisions to them.

- [Gemma] Life and death decisions.

- It could well be life and death decisions.

Well look, do you see this van coming down here.

Well we're just driving along here

on that side in this direction.

The van comes hammering at us for some reason

and you got that woman there in the push chair

and she's gonna be hit if we avoid it.

The car has to make a decision to take the hit

or to kill the mother and baby.

What would you do?

- I don't know.

I don't know what I would do in that split second.

I- - Yeah, that's what I'm-

thinking. - I think it's a really,

that's a really difficult decision for anyone to make,

for a human to make.

How can a car decide which life is more valuable?

- I don't think it should, myself.

(ominous music)

- The robot we're building

won't need to make life and death decisions

but it will have to harness AI's decision making powers

to think like me.

It's being built on a modest industrial estate

on the outskirts of Penryn, Cornwall.

I wasn't expecting the hub of the robot build

to be next to a B & Q.

I wonder if it's going to be a mop head.

Will Jackson is at the forefront

of constructing human like robots.

- [Robot] Well hello!

- Hello.

To be convincing, robots need to reason,

learn and understand so they can react

almost instinctively like us.

- Hello.

How are you?

- I'm very well, thank you.

How are you?

- [Will] He's thinking about it.

- I'm very well, thank you.

- He's great!

- He's very much a robot.

You definitely know that this is a machine, not a person.

He's pretty limited.

- [Gemma] Will plans to apply the knowledge acquired

building RoboThespian RT4 as a basis

for constructing the AI version of me.

In order to be convincing,

the robot will need to master the complexity of language.

- So the first thing that's gonna happen

is somebody's gonna speak to the robot

and we've got microphones in the ears,

pick up the sound and at that point, it's just sound.

It doesn't mean anything

so we have to turn the sound into words, into texts.

Once we've got the sound as text,

we've gotta try and find the meaning.

What is this person actually saying to me?

What's the key word?

What did they ask about?

And once we've got that meaning,

we have to try and think of a sensible reply.

We have to then turn that back into speech.

So we're gonna have to take

the computer generated version of your voice,

that sounds like you.

While we're doing all of this,

the robot can't just sit still so it has to have

all of the little actions that you would have

the way you can listen,

the way you think about what somebody's going to say,

the way you think about what you're going to say.

You've gotta get all these little subtle things right

all at the same time.

The brain in this robot has got to come up

with an answer that makes sense,

even when it's never heard the question before.

It's a huge challenge

and we have so many things to get right.

(intense music)

- [Gemma] Will's going to use his existing robot hardware

to test out the speech recognition software

that he plans to use on the robot me.

- There's an old saying in computer programming,

it's garbage in, garbage out.

If the robot cannot recognize what you're saying,

if it just gets one or two words in a sentence wrong

when you speak, what you get back is complete gibberish.

- [Gemma] Using speech recognition software,

can it recognize words it hears, turn them into text,

and then accurately repeat them?

- Echo on.

- [Robot] Okay, Echo on.

- Peter Piper picked a piece of pickled pepper,

put it on a panda car, drove it around the moon,

and ate a sausage on the way home.

- Peter Piper picked a piece of pickled pepper,

put in on a pan, pick our dragon's random name generator,

sausage on the way home.

(laughing)

- Random name generator sausage.

- [Gemma] Part of the challenge is to get

our robot to respond as quickly as a human would.

That's within a 10th of a second.

- [Will] Hello.

- [Robot] Hello.

- Too slow.

Hello.

- [Robot] Hello.

- It's too slow.

- [Gemma] To respond as fast as a human,

the robot needs to work out what's being said

and what it means before the end of a sentence

and reply with a lightening fast response,

which involves instinct, like us.

- We've got to be so quick with understanding

what's being said that we can be replying

before even really the last words come out.

So it's gotta be super fast.

- [Gemma] Building a machine that can understand a human

and answer back convincingly

is one of the toughest challenges in AI.

- If I speak quicker, does it work better?

- [Robot] If I speak quicker, does it work better?

- It's almost fast enough.

It's almost there but it's not quite.

If we can't get the recognition that quick,

blown it on the robot.

(intense music)

- [Gemma] We're testing the boundaries of science,

with a unique artificial intelligence test,

building a robot that looks, sounds and thinks like me.

(intense music)

The robot team is progressing well

but it's my facial expressions that are proving hard

for the robot to sync with its brain.

- [Man] It's quite a scary looking thing at the moment

but once it's got the rest of the core

that goes on which has got the top teeth in it,

and then the skin will go over the top,

it will start to look a lot more like Gemma.

(intense music)

- [Gemma] The physical part of the build is tricky

but it's the robot's ability to converse like a human

that's really going to test their engineers.

With Moore's Law stating that computer processing power

doubles every two years,

artificially intelligent achievements in the real world

have been accelerating fast.

In the 1950s, computers beat us at knots and crosses,

then in the 1990s, they beat us at chess.

Those computers were programmed to work out

all the possible outcomes of each move

and then weighed up how each move would contribute

to a winning strategy but we're now entering an age

when computers aren't just programmed

but can learn for themselves, computers like IBM's Watson.

- [Announcer] This is "Jeopardy," the IBM Challenge.

(audience applauding)

Here are-

- [Gemma] In 2011, Watson was put up to one of

the toughest challenges ever,

a general knowledge quiz

that requires logic and quick thinking.

- This is "Jeopardy."

It's a bit of an American institution.

It's a general knowledge quiz program

and they ask questions in a really strange way.

They give you the answer

and you have to work out what the question is.

- [Gemma] Duncan Anderson is IBM's European

Chief Technology Officer for Watson.

- So we've got the two best players here.

We've got the person who won

the most amount of money on the show

and the person who has the longest winning streak.

- [Gemma] Two of the most brilliant reigns

had won $5 million between them.

This game was worth another million.

- Watson itself, is not connected to the internet.

So it's not out there searching.

It's there, standalone, playing against

these champion players.

It was a big risk.

- The category is 19th Century Novelists

and here is the clue.

(beeping)

William Wilkinson's "An Account of the Principalities

"of Wallachia and Moldavia,"

inspired this author's most famous novel.

- [Alex] Who is Bram Stoker?

Hello!

- And this is the point where Watson's won!

We've beat the best human players at "Jeopardy."

- So how exactly do you program a machine

to do something that it's never done before?

- Well, the first thing is you don't program it.

Trying to guess every single question that might come up

and then program the computer

with the right answer for that question,

we would be here forever,

so we use this thing called machine learning

which is an approach to solving problems

where by the machine can learn from experiences,

so we took Watson and we taught it,

we fed it lots of information.

For example, back issues of "Time" magazine,

Wikipedia, encyclopedias-

- So Watson was learning, in a way.

- Mm, and then we go through a teaching process,

just like you would teach a child.

We're teaching Watson, we're testing it,

and we're giving it feedback when it gets it right

and feedback when it gets it wrong

and then it adjusts it's approach to making decisions.

You could think of it a bit like trying to find

a pathway through a field.

So you have a very faint distinct path

that maybe only one person has trodden through

and what you're trying to do is to feed information

so that that pathway becomes more defined.

As more people go down that path,

the path gets more trodden through

and becomes more obvious.

- So the more data that you feed into Watson,

it's almost like the more or the wider the path becomes,

or the more distinct the path becomes.

- Precisely.

So Watson becomes more confident

that that pathway is the right pathway to take.

- [Gemma] We now need my robot to undergo

a basic version of this process.

It needs its own pathway

and be fed hundreds of bespoke new rules

on how to respond to a question

and then learn how to use them.

- Ready to go now if you wanna try,

try the latest transcript from Bruce.

- Okay. Key moment.

- [Gemma] Will has commissioned one of the world's

leading computer programmers to build a chatbot,

a piece of software which simulates human conversation

and responds with the answer it thinks I would give.

- Do you like repetition?

- [Chatbot] Yes.

- Do you like repetition?

- [Chatbot] You said that already.

- Aha! Now that's the kind of reply I'm looking for.

That's what I wanna get to.

That was good.

You're improving.

- [Chatbot] Right.

How about we talk about work?

- [Will] You've played a lot of supernatural characters.

Are you a fan of the genre or is it just a coincidence?

- [Chatbot] I do love science fiction

and things that explore

the boundaries of the possible,

but actually having a bunch of moves in that genre

is just a coincidence.

- [Gemma] The team have certainly done their homework.

Just as Watson was fed information

from previous "Jeopardy" games,

our chatbot has been fed interviews

and background information on me.

- Once we can get the expressions

and all those other little subtle cues,

movement, things in there,

I think it will start to come together.

- [Chatbot] Fantastic!

- Yeah, it will be fantastic.

- [Chatbot] Are you sure?

- I am positive.

- What's your next question?

- [Gemma] The next question

is how to make it sound like me.

Hello. - Hello.

- I'm Gemma. - My name's Burdill.

- [Gemma] The human voice has a huge variation

of inflection, pitch and intonation.

Our robot will need to replicate the essence of my voice,

with all the specific quirks that make it unique to me.

- So just keep in mind that when you get commas,

you make a small pause.

- Burdill Madison is a computational linguist

and works for a company that specializes

in synthesized voices.

It's not the words that you're recording here. You're more

interested in the different sounds that I'm making.

- Yeah, I'm not interested in words at all.

I'm interested in the combinations

of phoniums that we are getting.

- Oh the phoniums, oh I see.

- So the combinations of sounds.

- [Gemma] How many sentences do I need to record?

- [Burdill] Well, in the end it's about 1400 sentences.

- [Gemma] 1400?

- [Burdill] Yeah.

- Today? This is gonna be quite a long afternoon.

(intense music)

I certainly have appreciated

that outlook for my creativity.

(intense music)

Imagine George Bush singing in the shower.

(intense music)

- You will have to do the previous one again.

- We're teaching our robot how to speak like me.

You are an athlete if you play golf.

But in the future, we may get to a stage

where it can teach itself, learning from experience,

and coming up with its own solutions,

which is what AIs are starting to do.

- Hi. - Hi, Denis!

- Nice to meet you. - Good to meet you.

Thanks. - So welcome to the offices.

- Thanks for having me. - No problem at all.

So-

- [Gemma] Demis Hassabis was a child chess prodigy

from North London.

- It's actually quite strange meeting you

because I've watched you on,

being, pretending to be an AI.

- Pretending to be a robot. - Yeah.

(laughing)

- [Gemma] In 2011, he launched

a British artificial intelligence company called DeepMind.

Just three years later, Google bought his company

for 400 million pounds.

- One of the first things we got our program to do

was to play classic Atari games

and we wanted the AI to actually learn

to play these games by just from the pixels on the screen

and no other information so it had to learn for itself

what the rules of the game were, how to get points,

and how to sort of master the game.

The idea behind "Breakout" is that you control

a bat and a ball and you've got to breakout through

a rainbow colored wall brick by brick.

- I think I remember this from when I was younger.

- Atari.

So you can see it's starting

to get the hang of what it should do.

It's not very good.

It misses the ball quite a lot

but it's starting to understand

that it's got to move the bat towards the ball

if it wants to get points.

(beeping)

This is after 300 games.

It's still not that many.

So we thought this is pretty good

but what would happen if we just let the program

continue to play the game

so we left it playing for another 200 games

and then we came back and it did this amazing strategy

of digging a tunnel around the side of the wall

and actually sending the ball round the back.

So it's really amazing. - That's amazing!

- It's discovered it for itself

and obviously it can do it with super human precision.

(beeping)

- [Gemma] Then last year, Demis and his team

built a computer program to play

the most complex game ever devised,

an ancient Chinese game called "Go."

- The aim of the game in "Go" is to either capture

your opponent's pieces or to surround areas of the board

and make it your territory.

- [Gemma] In chess, the board is made up

of an eight by eight grid.

This means the number of possible moves in a game

can be number crunched by a computer.

(robotic noises)

With a 19 by 19 board, Go is a much more complex game.

- Even the best players, they use their intuition

and their instincts more than calculation.

- [Gemma] Astonishingly, the number of possible moves

is greater than the number of atoms in the universe.

- So even if you took all the world's computing power

and ran it for a million years,

that would still not be enough

to brute force a solution to how to win "Go."

- [Gemma] So Demis gave a more powerful computer

the same challenge it gave

the Atari computer five years before.

Could it teach itself how to play

the world's most complex board game

and beat the world's best player?

(intense music)

Earlier this year, Demis took the computer program

he'd named AlphaGo to Korea to play the world champion.

- It was actually a genuine sort of excitement

and sort of fear about what was actually gonna happen.

- [Gemma] The man on the right is making the moves

on behalf of AlphaGo.

- That's a very surprising move.

- I thought it was, I thought it was a mistake.

- AlphaGo played a move that was just completely unthinkable

for a human to play.

(intense music)

So there's two important lines in "Go."

If you play on the third line,

you are trying to take territory on the side of the board.

If you play on the fourth line,

you are trying to take influence

into the center of the board

and what AlphaGo did is it played on the fifth line

and you never do that in the position that it played in.

And we were actually quite worried because obviously at that point,

we didn't know if this was a crazy move

or a brilliant, original move, and then 50 moves later,

that move ended up joining up

with another part of the board-

- [Gemma] So it worked.

- And sort of magically just, yeah,

resulting in helping it win the game.

- [Gemma] Demis' AI made headlines around the world

when it won the match.

- We're not there yet, but in the next few years

we would like to get to the point where

you could give it any data,

scientific, medical or commercial,

and it would find these structures or these patterns,

that perhaps human experts have missed

and highlight those so that improvements can be made, yeah.

(intense music)

- I think what's really interesting about it

is the fact that this program can teach itself.

It can learn from its mistakes.

It can come up with a genuinely creative solution

to a problem and really you can apply that to anything.

So if we can give my robot the ability to learn for itself,

who knows where it might take us.

It's so strange.

(intense music)

We're testing the boundaries of science

with a unique artificial intelligence test,

building a robot that looks, sounds and thinks like me.

The team is working on getting the robot's facial expressions

to work in tandem with the AI.

- If you look at other robots of this type,

this kind of flexible silicone face robot,

this is bloody good.

Look at me.

Look at me.

Oh, spooky.

(chuckling)

- [Gemma] The heart of the robot is conversation

that seems real and the software to do this,

the chatbot, has just arrived.

- [Chatbot] Hello, my name is Gemma Chan.

I am not a robot.

- That sounds like Gemma, doesn't it?

I think it sounds like Gemma.

Do you think? I think that sounds like Gemma.

- [Gemma] But it's proving a real challenge

to synchronize the body with the mind.

- When we can get all of the actions going at the same time,

it will look really good.

- [Gemma] Hopefully, the robot will be able

to pick the right expression for the right thought.

- [Will] This is the first stored pose

and it's a little smile.

- That's awesome.

I like the look of that.

- [Gemma] Will is teaching the robot 180

of the most common movements.

- I think she's happy.

- [Gemma] Hoping she'll chose the right ones

to react and be convincing as a human.

- Gemma now knows how to smile forever

and she will be able to seamlessly blend

from one smile to a frown to anger

to despair and the whole range of human emotions

but we have to teach her them.

- If we can teach AI almost anything

that involves reasoning and decision making,

once it has those skills, what might be the consequences?

(intense music)

Oh we're high.

This is the London Gateway Dockyard.

(intense music)

Every day, over 20,000 containers are moved

by a highly complex AI which controls

the logistics and timing of what happens when and where.

I can only see about five people.

Just 10 years ago, a port of this size

would've employed thousands of workers

to shift these containers.

Today, many of the 500 employees spend their time

supervising the AI machines.

The AI is incredibly efficient,

moving the containers in the fewest number of moves,

like a very basic AlphaGo.

It comes up with solutions faster

than any human would be able to.

- Wow, that's a lot of containers.

- [Gemma] AI expert and writer, Martin Ford,

thinks what we're seeing here reflects

the shape of things to come.

- Look out at all these containers here

and think of those as representing the job market

in the United Kingdom and imagine 35%,

roughly a third of those disappearing

and what would happen to our society and our economy

if that were to happen?

(eerie music)

There's an incredible impact on all of us

and on the economy.

It's something that is gonna be uniquely disruptive,

something that we've never seen before in history

and one of the things that is really driving it

is that machines in a limited way

are at least, they're beginning to think.

- [Gemma] And it's not just blue collar jobs.

You may not realize this but a lot of online journalism

based on statistics like sports and business articles

are increasingly being written by AIs.

- This is a corporate earning report for Star Bulk carriers,

which is actually one of the companies

that utilizes this port.

One of these items is written by a machine

and one is written by a human journalist

and just take a look and see

if you can determine which is which.

- Yeah, so the first one, Athens, Greece.

Star Bulk Carriers Corporation on Wednesday

reported a loss of $48.8 million in its first quarter.

Sounds pretty... Sounds pretty human to me.

- And the other one starts,

this Star Bulk Carriers Corporation reported

a net revenue decrease of 14.9 percent

in the first quarter of 2016.

- Which one do you think is human

and which one do you think is a machine?

- It's really hard to tell.

Which one is written by, do you know?

- I believe the one on the right is written by a person

and the one on the left is written by the machine.

- They both sound like something

that a person could've written,

doesn't it. - That's right.

We are really heading toward a kind of a tipping point,

or a point at which things are gonna accelerate

beyond anything we've seen before.

This is just really historic.

It's not just about muscle power anymore.

It's about brain power.

Machines are moving in to cognitive capability

and that of course is the thing

that really sets people apart.

That's the reason that most people today

still have jobs whereas horses have been put out of work.

It's because we have this ability to think,

to learn, to figure out how to do new things

and to solve problems but increasingly,

the machines are pushing into that area

and that's gonna have huge implications for the future.

- Are any jobs safe?

- Right now, it's really hard to build robots

that can approach human ability and dexterity

and mobility so a lot of skilled trade type jobs,

electricians and plumbers and that type of things

are probably gonna be relatively safe.

But that's thinking out over the next 10, 20 maybe 30 years.

Once you go beyond that, really nothing is off the table.

- [Gemma] But the biggest danger may not be losing our jobs.

Professor Stephen Hawking recently warned

that the creation of powerful AI will be either the best

or the worst thing ever to happen to humanity.

Hawking was recently joined by Tesla founder Elon Musk

and other leading figures in an open letter

highlighting the potential dangers of unchecked AI.

One of the most vocal was professor Nick Bostrom.

- Development in the last few years in machine learning

have just more rapid than people expected

with these deep learning algorithms and so forth.

- How far away are we from achieving

human level artificial intelligence?

- The median opinion by which year do you think

there's a 50% chance was 2040 or 2050.

- That's within our lifetime.

- Yeah.

Within the lifetime of a lot of people alive today.

The concern is you're building

this very, very powerful intelligence,

and you wanna be really sure then that this goal that it has

is the same as your goal,

that it incorporates human values in it

because if it's not a goal that you're happy with

then you might see the world transform

into something that maximizes the AI's goal

but leaves no room for you and your values.

- [Gemma] This idea of autonomous and dangerous AIs

is a recurring theme in the world of science fiction.

Nick thinks that super-intelligent machines

could one day inhabit the real world

and use their power to negative effect

if we don't put the right safeguards in place.

AIs could take their instructions to logical

but unanticipated extremes.

- The concern is not that these AIs would resent us

or resent being exploited by us

or that they would hate us or something

but that they would be indifferent to us.

So if you think maybe you have some big department store

and it wants to build a new parking place,

maybe there was an ant colony there before, right?

So it got paved over.

It's not because we hate the ants.

It's just because they didn't factor into our goal.

- I see. - We didn't care.

Similarly, if you had a machine that wants

to optimize the universe,

to maximize the realization of some goal,

in realizing this goal we wouldn't be kind of stomped out.

- Collateral damage. - In the same way that,

yeah, collateral damage.

(intense music)

(ringing)

- [Gemma] The way in which AIs can be diverted

from what their architects intended

played out earlier this year

when Microsoft introduced Tay to Twitter.

The AI persona was designed to act like an American teenager

to attract a younger audience.

The chatbot worked by absorbing and mimicking

the language of other Twitter users

but Tay was hijacked by internet trolls,

who gave it a very different set of values.

The original intention was corrupted

and Tay was unable to work out

which views were acceptable and which weren't.

Within a day, Tay became a Hitler loving, racist, sex pest.

This shows what can happen to AI

if it falls into the wrong hands

but could a future Tay be far worse?

- Once you have a kind of super-intelligent genie

that's out of the bottle like,

it might not be possible to put it back in again.

Like, you don't have a super-intelligent adversary

that is working at cross-purposes with you

that might then resist your attempts to shut it down.

It's much better to get it right on the first attempt,

not to build a super-intelligent

evil genie in the first place, right?

If you're gonna have a super-intelligent genie,

you want it to be- - You want it to be-

on your side. - On your side, yeah. Exactly.

(intense music)

- [Gemma] In Cornwall, our genie

is about to be let out of its bottle

and I want to know who's side it's on.

- Robot's upstairs here.

Bear in mind this is not your final skin so,

let's have a look inside and just let her peak right out.

- [Gemma] Oh my goodness.

(gasping)

That's so weird.

(eerie music)

- See?

It's quite warm.

Now, just feel it though, it's weird.

(eerie music)

What do you think of the eyes.

(eerie music)

- Ah! Oh my God!

(laughing)

(eerie music)

It's so strange 'cause she's not quite right

but she, I can recognize, like the nose is,

well, I mean it's, yeah, it's my nose.

- [Will] Try asking her something.

- Okay.

What have you been up to today?

- We've been busy filming season two of "Humans" since April

and it's been very exciting.

- Not bad.

- [Will] So we can have a kind of guess

of the sort of things people might say.

Say-

- [Robot Gemma] I can't resist cheese on toast.

(laughing)

- What did you have for breakfast?

- [Robot Gemma] I had a toasted cheese sandwich.

- Is that because you can't resist cheese on toast?

- [Robot Gemma] I like the taste of cheese.

(laughing)

- Is that true? Do you really like cheese on toast?

- I love cheese, yeah.

- Oh, so there's a little personality trait

we might've got got right.

- Maybe not as much as she likes cheese.

It's the facial expressions.

They're not quite in sync with what she's saying.

- Basically, it's a slight software bug.

- [Will] Don't worry too much.

- [Gemma] She's confused.

- [Will] Very strange.

- [Gemma] A few facial ticks going on.

- Yeah, she has but this is really

the first time we've tried this

so it's very, very new and what you'll find

is that things will progress very, very quickly.

- [Gemma] Facial ticks aside, the build it going well.

Every day, the robot is making progress

in terms of how it looks, sounds and thinks.

So we've come up with an idea to put it to the test.

- Hi Gemma.

- [Robot Gemma] Hi.

- Robot Gemma, do not fail.

(eerie music)

- We're building an artificially intelligent robot

that looks like me, talks like me and thinks like me

and today I'm going to meet her in her finished form.

Last time I saw her, she needed quite a bit of work

so I'm hoping that today we will have

more of a finished product.

Yeah, I don't know. I'm quite nervous.

(eerie music)

- [Will] Here it is. - Ah!

Oh no.

Really strange.

- [Will] It is spooky, isn't it?

(gasping)

- Wow.

It's really quite uncanny.

(eerie music)

In the 1950s, the visionary godfather of British computing,

Alan Turing, saw forward to the days

when a computer would be able to think like us

and he came up with a test.

Could a bystander tell if he was talking

to a machine or a person?

It's known as a Turing Test and we've adapted it

to try out on our own robot.

- This is an enormous challenge.

Basically, what we're doing is taking

a fictional vision of the future

and trying to bring it here now.

- She's ready for her closeup.

I've invited some journalists to come and interview her

to see if they can tell it's not actually me

and we've rigged the place with hidden cameras.

(people talking)

- Hi there.

- Hello.

- [Gemma] And I've called in a favor

from "Humans" castmates Emily Barrington and Will Tudor

to give proceedings an air of reality

and the journalists will meet them first.

- I'll come back and tell you when we've got two minutes.

- Okay. - All right.

(intense music)

- [Gemma] Before being taken into a second room,

where to give us a fighting chance,

they'll interview Robot Gemma over a video call.

- Hey Gemma.

- [Robot Gemma] Hi, I'm so sorry I can't be there in person.

- [Gemma] I'll be in a room down the hall,

watching with the robot's creators, Will and Kate.

Come in.

- [Will] I'm so excited.

- [Gemma] But first, there's just time

to introduce Robot Gemma to my castmates.

(gasping)

- Oh my goodness, that's terrifying.

What's extraordinary is the tiny movements in the face.

- Are you real?

- Maybe.

- [Both] Oh!

- So with everything in place, the experiment begins.

I'm so nervous.

Oh my God.

- So should I just get started and ask you questions.

- I live in Notting Hill. (laughing)

- That's very interesting.

- Could you say- - Sorry?

- [Robot Gemma] Apology accepted.

- [Gemma] It's not the smoothest of starts.

- My name's Lareb.

- [Robot Gemma] Got it.

- How are you today? - Your name is,

is your name?

- No, Lareb L-A-R-E-B.

- [Robot Gemma] Could you say that one more time?

- Lareb.

- [Robot Gemma] Great, yeah, what's the name?

(smacking)

- Thank you for coming on and Skyping.

That's really nice of you. - [Robot Gemma] Oh, thank you

for taking the time to talk to me.

(laughing)

- How was season one for you?

- [Robot Gemma] I wish I could explain it to you

but I think it is just an instinct.

(groaning)

- [Kate] No!

- I think he knows.

So far, Robot Gemma's responses

haven't gone as well as I'd hoped

but gradually, she starts to find her train of thought.

- So tell me about series two.

- It's a key word for Gemma Robot.

Series two.

If this journalist just keeps saying series two,

everything will go fine.

- It seems that the scope has got bigger for series two.

- [Robot Gemma] The main difference is that the world

of the show has become bigger.

- And what does Mia want in series two?

- [Robot Gemma] Mia's trying to find her place in the world.

- The voice is a little bit glitchy, isn't it.

- She's going though.

She's getting into it.

- Do you think a synth can enjoy art?

- That's a good question.

- [Robot Gemma] Yes, especially like sculpture.

- Yes, good answer!

- Can you hear me now?

- [Robot Gemma] Yup, I can see and hear you okay.

- Lovely, perfect.

Okay, so-

- [Robot Gemma] We're short on time.

- Okay, that's absolutely fine.

- I don't think she's clocked

that she's not talking to me yet.

- [Robot Gemma] What would you like to see a robot do?

- Oh, I'd love a robot to tidy my room.

(laughing)

- Oh my God.

- What can we expect from season two?

- [Robot Gemma] The synth characters

have fragmented, in a way.

- Yes, yes!

- [Robot Gemma] I can't tell you anymore more specific

about the plot, I'm afraid.

- Can you tell us where we find your character?

- [Robot Gemma] Mia's not with the Hawkins family.

Mia's trying to find her place in the world.

- We've got her.

She totally believes it.

- And there's a new character that you spend quite a lot of time with.

- She's perfect.

- What can you tell us about their relationship if anything?

- I can't answer that.

- Oh. - She's not sure.

- That's okay.

It's okay to be evasive on that.

- [Robot Gemma] Who's your favorite character?

- You, obviously.

- [Gemma] Time to meet the journalists and reveal the ruse.

(intense music)

- Hello?

- [Gemma] Hello.

Hi.

- This is so confusing.

- [Gemma] Just how convincing was it?

- She looks so real!

What did you have for breakfast this morning?

- The usual, got dressed and sat at my computer.

(laughing)

- [Gemma] What do you think?

- Well, I wasn't sure to be honest.

- Yeah. - Yeah.

- [Gemma] What were the giveaways?

- [Woman] The voice maybe.

- Fooled me when I first sat down and looked at it,

yeah, completely fooled me.

- [Gemma] Oh wow.

- It just looks like it kind of not the best Skype connection.

(laughing)

How are you today?

- I am very good, thank you.

(laughing)

- Did you believe you were talking to me?

- I did, yeah.

I honestly thought it was you.

- Could you say that one more time?

(intense music)

- [Gemma] What's really surprised me

is that we've got as far as we have.

- There was obviously something slightly uncanny about her.

- I'm really impressed that she held her own.

I didn't know if anyone would be convinced by our robot

and quite a few people were for at least a bit so in that sense, that's a success.

Having set out to find out how far we are

from the unsettling fictional world of "Humans,"

the answer is perhaps a bit more complicated than I thought.

Whilst human-like robots may well be some way away,

what's clear is that AI is developing at speed

and we need to debate the potential pitfalls

before it's too late.

(intense music)

- It's very clear that these technologies

are getting better and better

and I do think we have to understand

that we're approaching this tipping point,

this point where it's gonna have a greatly amplified effect

and we need to find a way to adapt to that.

- The same technology can be used for good or for bad

and I think it's down to society

and the inventors of that technology and the public at large

to make sure that it gets used for the right things.

- [Gemma] This is just the beginning.

(upbeat music)