All language subtitles for MV5BYm7878UxMWF

- [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)