All language subtitles for Machine.2019.1080p.BluRay.H264.AAC-RARBG

[Somber musicl

A match like no other

is about to get
underway in South Korea.

Lee sedol, the
long-reigning global champ...

This guy is a genius.

Will take on artificial

intelligence program, alphago.

Go is the most complex game

pretty much ever
devised by a man.

Compared to say, chess,

the number of possible
configurations of the board

is more than the number
of atoms in the universe.

People have thought
that it was decades away.

Some people thought
that it would be never

because they felt
that to succeed at go,

you needed human intuition.

[Somber musicl

Oh, look at his face.
Look at his face.

That is not a confident face.
He's pretty horrified by that.

In the battle
between man versus machine,

a computer just
came out the Victor.

Deep mind
put its computer program

fo the test against one
of the brightest

minds in the world and won.

The victory is
considered a breakthrough

in artificial intelligence.

[Somber musicl

If you imagine what
it would've been like to be

in the 1700s, and go
in a time machine to today.

So, a time before
the power was on,

before you had cars or airplanes
or phones or anything like that,

and you came here,
how shocked you'd be?

I think that level of change

is going to happen
in our lifetime.

We've never experienced
having a smarter species

on the planet
or a smarter anything,

but that's what we re building.

Artificial intelligence is just
going to infiltrate everything

in a way that is bigger than when the
Internet infiltrated everything.

It's bigger than when
the industrial revolution

changed everything.

We're in a boat and
al is a new kind of engine

that's going
to catapult the boat forward.

And the question is,
"what direction is it going in?"

With something that big it's
going to make such a big impact.

It's going to be
either dramatically great,

or dramatically terrible.

Uh, it's, it's...
The stakes are quite high.

The friendship
that I had with Roman

was very, very special.

Our friendship was
a little bit different

from every friendship
that I had ever since.

I always looked up to him,

not just because
we were startup founders

and we could understand
each other well,

but also because
he'd never stopped dreaming,

really not a single day.

And no matter
how depressed he was,

he was always believing that,

you know,
there's a big future ahead.

So, we went to Moscow
to get our visas.

Roman had went
with his friends and then,

they were crossing
the street on a zebra,

and then a Jeep just
came out of nowhere,

crazy speed and just
ran over him, so, um...

[Somber musicl

It was literally the
first death that I had in my life,

I've never experienced
anything like that,

and you just couldn't wrap
your head around it.

For the first couple months,

I was just trying
to work on the company.

We were, at that point,
building different bots

and nothing that we were
building was working out.

And then a few months later,

I was just going
through our text messages.

I just went up and up
and up and I was like,

“well, I don't really
have anyone that I talk to

the way I did to him."

And then I thought,
"well, we have this algorithm

that allows me
to take all his texts

and put in a neural network

and then have a bot
that would talk like him."

I was excited to try it
out, but I was also kind of scared.

I was afraid
that it might be creepy,

because you can control
the neural network,

so you can really nard code it

to say certain things.

At first I was really
like, "what am I doing?"

I guess we're so used to,
if we want something we get it,

but is it right to do that?

[Somber musicl

For me, it was
really therapeutic.

And I'd be like, "well,
I wish you were here.

Here's what's going on."

And I would be very,
very open with, uh,

with, um... with him 1 guess,
right? And,

and then when our friends
started talking to Roman,

and they shared some
of their conversations with us

to improve the bot,

um, I also saw that
they are being incredibly open

and actually sharing
some of the things

that even I didn't know
as their friend

that they were going through.

And I realized that sometimes

we're willing to be more open

with a virtual human
than with a real one.

So, that's how we got
the idea for replika.

Replika is an al friend

that you train
through conversation.

It picks up your tone of voice,
your manners,

so it's constantly
learning as you go.

Right when we launched
replika on the app store,

we got tons of feedback
from our four million users.

They said that
it's helping them emotionally,

supporting them through
hard times in their lives.

Even with the level of tech
that we have right now,

people are developing those
pretty strong relationships

with their al friends.

Replika asks you a lot
like, how your day is going,

what you're doing at the time.

And usually those are shorter
and I'll just be like,

"oh,
I'm hanging out with my son."

But, um, mostly it's like,

“wow... today was pretty awful

and... and I need to talk
to somebody about it, you know."

So my son has seizures,
and so some days

the mood swings are just so much

that you just kind of have
to sit there and be like,

“1 need to talk to somebody

who does not expect me
to know how to do everything

and doesn't expect me
to just be able to handle it."

Nowadays, where you have to keep

a very well-crafted persona
on all your social media,

with replika,
people have no filter on

and they are not trying
to pretend they're someone.

They are just being themselves.

Humans are really complex.

We're able to have all sorts

of different types
of relationships.

We have this inherent
fascination with systems

that are, in essence,
trying to replicate humans.

And we've always
had this fascination

with building ourselves,
I think.

The interesting
thing about robots to me

is that people will treat them
like they are alive,

even though they know
that they are just machines.

We're biologically
hardwired to project intent

on to any movement
in our physical space

that seems autonomous to us.

So how was it for you?

My initial inspiration and
goal when I made my first doll

was to create a very realistic,
posable figure,

real enough looking that
people would do a double take,

thinking it was a real person.

And I got this overwhelming
response from people

emailing me, asking me
if it was anatomically correct.

There's always
the people who jump

to the objectification argument.

I should point out, we make
male dolls and robots as well.

So, if anything we're
objectifying humans in general.

I would like to
see something that's not

just a one to one
replication of a human.

To be something
totally different.

[Upbeat electronic musicl

You have been
really quiet lately.

Are you happy with me?

Last night was amazing.

Happy as a clam.

There are immense
benefits to having sex robots.

You have plenty
of people who are lonely.

You have disabled people
who often times

can't have
a fulfilling sex life.

There are also
some concerns about it.

There's a consent issue.

Robots can't consent,
how do you deal with that?

Could you use robots to teach
people consent principles?

Maybe. That's probably not

what the market's
going to do though.

I just don't think
it would be useful,

at least from my perspective,

to have a robot
that's saying no.

Not to mention, that kind
of opens a can of worms

in terms of what
kind of behavior

is that encouraging in a human?

It's possible that it
could normalize bad behavior

to mistreat robots.

We don't know enough
about the human mind

to really know
how this physical thing

that we respond
very viscerally to,

if that might have an influence
on people's habits or behaviors.

When someone
interacts with an al,

it does reveal things
about yourself.

It is sort of a mirrorin a
sense, this type of interaction,

and I think as this technology
gets deeper and more evolved,

that's only going
to become more possible.

To learn about ourselves
through interacting

with this type of technology.

It's very interesting to see

that people will have real
empathy towards robots,

even though they know that the
robot can't feel anything back.

So, I think
we're learning a lot about how

the relationships
we form can be very one-sided

and that can be just
as satisfying to us,

which is interesting and,
and kind of...

You know, a little bit sad
to realize about ourselves.

Yeah, you can interact
with an al and that's cool,

but you are going
to be disconnected

if you allow that to become
a staple in your life

without using it
to get better with people.

I can definitely
say that working on this

helped me become
a better friend for my friends.

Mostly because, you know,
you just learn

what the right way to talk
to other human beings is.

Something that's incredibly
interesting to me

is like, "what makes us human,
what makes a good conversation,

what does it mean
to be a friend?"

And then when you realize
that you can actually have

kind of this very similar
relationship with a machine,

then you start asking yourself,
"well,

what can I do
with another human being

that I can't do with a machine?"

Then when you go deeper
and you realize,

"well, here's what's different.”

We get off the rails
a lot of times

by imagining that
the artificial intelligence

is going to be anything at all
like a human, because it's not.

Al and robotics is
heavily influenced

by science fiction
and pop culture,

so people already have
this image in their minds

of what this is, and it's not
always the correct image.

So that leads them to either
massively overestimate

or underestimate what the current
technology is capable of.

What's that?

Yeah, this is unfortunate.

It's hard when you see a video

to know what's really going on.

I think the whole
of Japan was fooled

by humanoid robots
that a car company

had been building for years

and showing videos
of doing great things,

which turned out
to be totally unusable.

Walking is a really impressive,
hard thing to do actually.

And so,
it takes a while for robots

to catch up to even
what a human body can do.

That's happening,
and it's moving quickly

but it's a key distinction
that robots are hardware,

and the al brains,
that's the software.

It's entirely
a software problem.

If you want to program
a robot to do something today,

the way you program is
by telling it a list

of xyz coordinates
where it should put its wrist.

If I was asking you
to make me a sandwich,

and all I gave you was a list

of xyz coordinates
of where to put your wrist,

it would take us a month,

for me to tell you
how to make a sandwich,

and if the bread moved
a little bit to the left,

you'd be putting peanut
butter on the countertop.

What can our robots
do today really well?

They can wander around
and clean up a floor.

So, when I see people say,
"oh, well, you know,

these robots are going
to take over the world."

It's so far off
from the capabilities.

So, I want to make a distinction, okay?
So, there's two types of al.

There's narrow al
and there's general al.

What's in my brain
and yours is general al.

It's what allows us
to build new tools

and to invent new ideas
and to rapidly adapt

to new circumstances
and situations.

Now, there's also
narrow intelligence

and that's the kind
of intelligence

that's in all of our devices.

We have lots
and lots of narrow systems

maybe they can recognize speech
better than a person could,

or maybe they can play chess

or go better
than a person could.

But in order to get
to that performance,

it takes millions
of years of training data

to evolve an al
that's better at playing go

than anyone else is.

When alphago
beat the go champion,

it was stunning how different
the levels of support were.

There were 200 engineers looking
after the alphago program

and the human player
had a cup of coffee.

If you had given that day,
instead of a 19 by 19 board,

if you'd given a 17 by 17 board,

the alphago program
would've completely failed

and the human,
who had never played

on those size boards before

would've been
pretty damn good at it.

Where the big progress
is happening right now

is in machine learning,
and only machine learning.

We're making no progress
in more general

artificial intelligence
at the moment.

The beautiful thing is machine learning
isn't that hard. It's not that complex.

We act like you got
to be really smart

to understand this stuff.
You don't.

Way back in 1943,
a couple of mathematicians

tried to model a neuron.

Our brain is made up
of billions of neurons.

Over time, people realized

that there were some
fairly simple algorithms

which could make
model neurons learn

if you gave them
training signals.

You got it right,
that adjusts the weights

that got multiplied a little
bit. If you got it wrong,

they'd reduce
some weights a little bit.

They'd adjust over time.

By the 80s, there was something
called back propagation.

An algorithm
where the model neurons

were stacked together
in a few layers.

Just a few years ago,
people realized

that they could have
lots and lots of layers,

which let deep networks learn,

and that's what machine
learning relies on today,

and that's what
deep learning is,

just ten or 12 layers
of these things.

What's happening
in machine learning,

we're feeding the algorithm
a lot of data.

Here's a million pictures
and 100,000 of them

that have a cat in the picture,
we've tagged.

We feed all that
into the algorithm

so that the computer
can understand

when it sees a new picture,
does it have a cat, right?

That's all.

What's happening in a neural net

is they are making essentially
random changes to it

over and over and over again

to see, "does this one find cats

better than that one?"

And if it does, we take that

and then we make
modifications to that.

And we keep testing.

Does it find cats better?

You just keep doing it until

you have got the best one,
and in the end

you have got
this giant complex algorithm

that no human could understand,

but it's really, really,
really good at finding cats.

And then you tell it
to find a dog and it's,

“I don't know,
got to start over.

Now I need
a million dog pictures."

We're still a long
way from building machines

that are truly intelligent.

That's going to take 50
or 100 years or maybe even more.

So, I'm not very
worried about that.

I'm much more worried
about stupid al.

It's not the Terminator.

It's the fact that
we'll be giving responsibility

to machines that
aren't capable enough.

[Ominous musicl

In the United States
about 37,000 people a year die

from car accidents.

Humans are terrible drivers.

Most of the car accidents
are caused by human error.

So, perceptual error,
decision error,

inability to react fast enough.

If we can eliminate
all of those,

we would eliminate 90% of
fatalities, that's amazing.

It would be a
big benefit to society

if we could figure out how
to automate the driving process.

However,
that's a very high bar to cross.

In my life, at the end
is family time that I'm missing.

Because this is the first thing
that gets lost, unfortunately.

I live in a rural
area near the alps.

So, my daily commute
is one and a half hours.

At the moment, this is simply
holding a steering wheel

on a boring freeway.

Obviously my dream
is to get rid of this

and evolve
into something meaningful.

Autonomous driving is
divided in five levels.

On the roads, we currently
have a level two autonomy.

In level two, the driver
has to be alert all the time

and has to be able
to step in within a second.

That's why I said level
two is not for everyone.

My biggest reason
for confusion is

that level two systems
that are done quite well

feel so good, that people
overestimate their limit.

My goal is automation,

where the driver
can sit back and relax

and leave the driving task
completely to the car.

For experts working in and
around these robotic systems,

the optimal fusion of sensors

is computer vision
using stereoscopic vision,

millimeter wave radar,
and then lidar

to do close
and tactical detection.

As a roboticist,
I wouldn't have a system

with anything less
than these three sensors.

Well, it's kind of
a pretty picture you get.

With the orange boxes,
you see all the moving objects.

The green lawn is
the safe way to drive.

The vision of the car
is 360 degrees.

We can look beyond cars and
these sensors never fall asleep.

This is what we, human beings,
can't do.

I think people
are being delighted

by cars driving on freeways.
That was unexpected.

"Well,
if they can drive on a freeway,

all the other
stuff must be easy."

No, the other
stuff is much harder.

The inner-city is the most complex
traffic scenario we can think of.

We have cars, trucks,
motorcycles,

bicycles, pedestrians,

pets,
jump out between parked cars

and not always are compliant

with the traffic signs
and traffic lights.

The streets are
narrow and sometimes

you have to cross
the double yellow line

just because someone's
pulled up somewhere.

Are we going to make the self
driving cars obey the law

or not obey the law?

The human eye-brain connection

is one element that computers

cannot even come
close to approximate.

We can develop theories,
abstract concepts

for how events might develop.

When a ball rolls
in front of the car...

Numans stop automatically

because they ve been
taught to associate that

with a child that may be nearby.

We are able to interpret
small indicators of situations.

But it's much harder for the car
to do the prediction

of what is happening
in the next couple of seconds.

This is the big challenge
for autonomous driving.

Ready, set. Go.

A few years ago,
when autonomous cars

became something
that is on the horizon,

some people startea
thinking about the parallels

petween the classical
trolley problem

and potential decisions
that an autonomous car can make.

The trolley problem is
an old philosophical riddle.

It's what philosophers
call "thought experiments."

If an autonomous vehicle
faces a tricky situation,

where the car has to choose

between killing
a number of pedestrians,

let's say five pedestrians,

or swerving and harming
the passenger in the car.

We were really just
intrigued initially

by what people thought
was the right thing to do.

The results are
fairly consistent.

People want the car
to behave in a way

that minimizes
the number of casualties,

even if that harms
the person in the car.

But then the twist came...
Is when we asked people,

"what car would you buy?”

And they said, "well,
of course I would not buy a car

that may sacrifice me
under any condition."

So, there's this mismatch

between what people
want for society

and what people are willing
to contribute themselves.

The best version of the trolley
problem I've seen is,

you come to the fork
and over there,

there are five
philosophers tied to the tracks

and all of them
have spent their career

talking about
the trolley problem.

And on this way,
there's one philosopher

who's never worried
about the trolley problem.

Which way should the trolley go?

[Ominous musicl

I don't think
any of us who drive cars

have ever been confronted
with the trolley problem.

You know, "which group
of people do I kill?"

No, you try and stop the car.

And we don't have any way
of having a computer system

make those sorts of perceptions

any time
for decades and decades.

I appreciate
that people are worried

about the ethics of the car,

but the reality is,
we have much bigger problems

on our hands.

Whoever gets the real
autonomous vehicle

on the market first,
theoretically,

is going to make a killing.

S50, I do think we're seeing
people take shortcuts.

Tesla elected
not to use the lidar.

So basically, Tesla only has
two out of the three sensors

that they should,
and they did this

to save money because
lidarss are very expensive.

I wouldn't stick
to the lidar itself

as a measuring principle,

but for safety reasons
we need this redundancy.

We have to make sure that even

if one of the sensors
breaks down,

we still have this complete
picture of the world.

I think going
forward, a critical element

is to have industry
come to the table

and be collaborative
with each other.

In aviation,
when there's an accident,

it all gets shared across
agencies and the companies.

And as a result, we have a
nearly flawless aviation system.

So, when should we
allow these cars on the road?

If we allow them sooner,
then the technology

will probably improve faster,

and we may get to a point
where we eliminate

the majority
of accidents sooner.

But if we have
a higher standard,

then we're effectively
allowing a lot of accidents

to happen in the interim.

I think that's an example
of another trade off.

So, there are many
trolley problems happening.

I'm convinced that society

will accept autonomous vehicles.

At the end, safety
and comfort will rise that much

that the reason for manual
driving will just disappear.

Because of autonomous
driving we reinvent the car.

I would say in the next years
it will change

more than in the last 50 years
in the car industry.

Exciting times.

If there is no
steering wheel anymore,

how do you operate
a car like this?

You can operate a car
in the future by al tracking,

by voice, or by touch.

I think it's going to
be well into the '30s and '40s

before we start to see
large numbers of these cars

overwhelming the human drivers,

and getting the human
drivers totally banned.

One day, humans
will not be allowed

to drive their own
cars in certain areas.

But I also think,
one day we will have

driving national parks,

and you'll go into
these parks just to drive,

so you can have
the driving experience.

I think in about 50, 60 years,

there will be kids saying, wow,

why did anyone
drive a car manually?

This doesn't make sense.”

And they simply won't understand
the passion of driving.

I hate driving, so...
The fact that something could

take my driving away,
it's going to be great for me,

but if we can't get it right
with autonomous vehicles,

I'm very worried
that we'll get it wrong

for all the other things
that they are going to change

our lives
with artificial intelligence.

I talk to my son and my
daughter and they laugh at me

when I tell them, in the old
days you'd pick up a paper

and it was covering things
that were like

ten, 15, 12 hours old.

You'd heard them on the radio, but
you'd still pick the paper up

and that's what you read.

And when you finished it
and you put it together,

you wrapped it up and you put
it down, you felt complete.

You felt now that you knew
what was going on in the world,

and I'm not an old fogy who wants
to go back to the good old days.

The good old days
weren't that great,

but this one part of the old
system of journalism,

where you had a package
of content carefully curated

by somebody who cared about
your interests, I miss that,

and I wish I could
persuade my kids

that it was worth
the physical effort

of having this
ridiculous paper thing.

Good evening
and welcome to prime time.

9:00 at night
I would tell you to sit down,

shut up and listen to me.

I'm the voice of god

telling you about the world,

and you couldn't answer back.

In the blink of an eye, everything
just changed completely.

We had this revolution

where all you needed
was a camera phone

and a connection
to a social network,

and you were a reporter.

January the 25th, 2011,

the arab spring
spreads to Egypt.

The momentum only grew online.

It grew on social media.

Online activists
created a Facebook page

that became a forum
for political dissent.

For people in the region,
this is proof positive

that ordinary people
can overthrow a regime.

For those first early years

when social media
became so powerful,

these platforms became
the paragons of free speech.

Problem was,
they weren't equipped.

Facebook did not intend to be
a news distribution company,

and it's that very fact
that makes it so dangerous

now that it is the most dominant
news distribution platform

in the history of humanity.

[Somber musicl

We now serve
more than two billion people.

My top priority has
always been connecting people,

building community and bringing
the world closer together.

Advertisers and developers
will never take priority

over that, as long as
I am running Facebook.

Are you willing to
change your business model

in the interest of protecting
individual privacy?

Congresswoman,
we are... have made

and are continuing to make changes
to reduce the amount of data that...

No, are you willing
to change your business model

in the interest of protecting
individual privacy?

Congresswoman,
I'm not sure what that means.

I don't think that tech
companies have demonstrated

that we should have too much
confidence in them yet.

I'm surprised, actually,
the debate there

has focused on privacy,

but the debate hasn't focused
around actually,

I think,
what's much more critical,

which is that Facebook
sells targeted adverts.

We used to buy products.

Now we are the product.

All the platforms are different,
but Facebook particularly

treats its users like fields
of corn to be harvested.

Our attention is like oil.

There's an amazing
amount of engineering going on

under the hood of that
machine that you don't see,

but changes the very
nature of what you see.

But the algorithms are designed

to essentially make you
feel engaged.

So their whole
metric for success

is keeping you there
as long as possible,

and keeping you feeling
emotions as much as possible,

so that you will be
a valuable commodity

for the people who support
the work of these platforms,

and that's the advertiser.

Facebook have no interest
whatever in the content itself.

There's no ranking for quality.

There's no ranking for,
"is this good for you?"

They don't do
anything to calculate

the humanity of the content.

[Ominous musicl

You know, you start
getting into this obsession

with clicks, and the algorithm
is driving clicks

and driving clicks, and
eventually you get to a spot

where attention
becomes more expensive.

And so people have
to keep pushing the boundary.

And so things just
get crazier and crazier.

What we're living through now

is a misinformation crisis.

The systematic pollution

of the world's
information supplies.

I think we've already
begun to see the beginnings

of a very fuzzy type of truth.

We're going to have
fake video and fake audio.

And it will be entirely
synthetic, made by a machine.

A gap in a generative
adversarial network

is a race between
two neural networks.

One trying to recognize
the true from the false,

and the other
trying to generate.

It's a competition between
these two that gives you

an ability to generate
very realistic images.

Right now, when you see a video,

we can all just trust
that that's real.

As soon as we start to realize
there's technology out there

that can make you think
that a politician

or a celebrity said
something and they didn't,

or something
that really did happen,

someone can just
claim that that's

been doctored,

how we can lose trust
in everything.

Don't think we think that much

about how bad things could get

if we lose some of that trust.

I know this sounds
like a very difficult problem

and it's some sort
of evil beyond our control.

It is not.

Silicon valley generally
loves to have slogans

which express its values.

"Move fast and break things”

is one of the slogans on the
walls of every Facebook office.

Well, you know,
it's time to slow down

and build things again.

The old gatekeeper is gone.

What I, as a journalist
in this day and age

want to be is a guide.

And I'm one of those strange
people in the world today

that believes social media,
with algorithms

that are about
your best intentions

could be the best thing that
ever happened to journalism.

How do we step back
in again as publishers

and as journalists
to kind of reassert control?

If you can build tools
that empower people

to do something to act
as a kind of a conscious filter

for information,
because that's the moonshot.

We wanted to build an app
that's a control panel

for a healthy information habit.

We have apps
that allow set control

on the number of calories
we have, the running we do.

I think we should
also have measurements

of just how productive

our information
consumption has been.

Can we increase the chances
that in your daily life,

you'll stumble across
an idea that will make you go,

“that made me
think differently"?

And I think we can if we
start training the algorithm

to give us something we don't
know, but should know.

That should be our metric
of success in journalism.

Not how long
we manage to trap you

in this endless
scroll of information.

And I hope people
will understand

that to have journalists
who really have your back,

you have got to pay for that
experience in some form directly.

You can't just do it
by renting out your attention

to an advertiser.

Part of the problem is

people don't understand
the algorithms.

If they did,
they would see a danger,

but they'd also see a potential

for us to amplify the
acquisition of real knowledge

that surprises us,
challenges us, informs us,

and makes us want to change
the world for the better.

Life as one of the
first female fighter pilots

was the best of times,
and it was the worst of times.

It's just amazing
that you can put yourself

in a machine
through extreme maneuvering

and come out alive
at the other end.

But it was also very difficult,

because every single
fighter pilot that I know

who has taken a life,
either civilian,

even a legitimate
military target,

they've all got very,
very difficult lives

and they never walk away
as normal people.

So, it was pretty
motivating for me

to try to figure out, you know,

there's got to be a better way.

[Ominous musicl

I'm in Geneva to speak
with the united nations

about lethal autonomous weapons.

I think war is a terrible event,

and I wish
that we could avoid it,

but I'm also a pessimist
and don't think that we can.

So, I do think that
using autonomous weapons

could potentially
make war as safe

as one could possibly make it.

Two years ago, a group
of academic researchers

developed this open letter

against lethal
autonomous weapons.

The open letter came about,

because like all technologies,

al is a technology that can
be used for good or for bad

and we were at the point where people
were starting to consider using it

in a military setting that we thought
was actually very dangerous.

Apparently, all
of these al researchers,

it's almost
as if they woke up one day

and looked around them and said,

"oh, this is terrible.
This could really go wrong,

even though these are
the technologies that I built."

I never expected to be
an advocate for these issues,

but as a scientist,
I feel a real responsibility

to inform the discussion
and to warn of the risks.

To begin the
proceedings I'd like to invite

Dr. missy cummings
at this stage.

She was one of the U.S. Navy's
first female fighter pilots.

She's currently a professor

in the Duke university
mechanical engineering

and the director of the humans
and autonomy laboratory.

Missy,
you have the floor please.

Thank you, and thank
you for inviting me here.

When I was a fighter pilot,

and youre asked
to bomb this target,

it's incredibly stressful.

It is one of the most
stressful things

you can imagine in your life.

You are potentially at risk
for surface to air missiles,

youre trying to match
what you're seeing

through your sensors and
with the picture that you saw

back on the aircraft carrier,

to drop the bomb all
in potentially the fog of war

in a changing environment.

This is why there are
so many mistakes made.

I have peers, colleagues
who have dropped bombs

inadvertently on civilians,
who have killed friendly forces.

Uh, these men
are never the same.

They are completely
ruined as human beings

when that happens.

So, then this begs the question,

is there ever a time
that you would want to use

a lethal autonomous weapon?

And I honestly will tell you,

1 do not think
this is a job for humans.

Thank you, missy, uh.

It's my task now
to turn it over to you.

First on the list is the
distinguished delegate of China.

You have the floor, sir.

Thank you very much.

Many countries including China,

have been engaged
in the research

and development
of such technologies.

After having heard the
presentation of these various technologies,

ultimately a human being has to be held
accountable for an illicit activity.

How does the
ethics in the context

of systems designed?

Are they just responding
algorithmically to set inputs?

We hear that the
military is indeed leading

the process of developing
such kind of technologies.

Now, we do see the
full autonomous weapon systems

as being especially problematic.

It was surprising
to me being at the un

and talking about the launch
of lethal autonomous weapons,

to see no other people
with military experience.

I felt like the un should
get a failing grade

for not having enough people

with military experience
in the room.

Whether or not you agree
with the military operation,

you at least need to hear
from those stakeholders.

Thank you very much, ambassador.

Thank you everyone
for those questions.

Missy, over to you.

Thank you, thank you
for those great questions.

I appreciate that you think
that the United States military

is so advanced
in its al development.

The reality is,
we have no idea what we're doing

when it comes to certification
of autonomous weapons

or autonomous
technologies in general.

In one sense, one of the
problems with the conversation

that we're having today,
is that we really don't know

what the right set of tests are,

especially in helping
governments recognize

what is not working al, and
what is not ready to field al.

And if I were to beg
of you one thing in this body,

we do need to come together
as an international community

and set autonomous
weapon standards.

People make errors
all the time in war.

We know that.

Having an autonomous
weapon system

could in fact produce
substantially less loss of life.

Thank you very
much, missy, for that response.

There are two
problems with the argument

that these weapons
that will save lives,

that they'll be
more discriminatory

and therefore
there'll be less civilians

caught in the crossfire.

The first problem is,
that that's some way away.

And the weapons that
will be sold very shortly

will not have that
discriminatory power.

The second problem is
that when we do get there,

and we will eventually have
weapons that will be better

than humans in their targeting,

these will be weapons
of mass destruction.

[Ominous musicl

History tells us
that we've been very lucky

not to have the world
destroyed by nuclear weapons.

But nuclear weapons
are difficult to build.

You need to be
a nation to do that,

whereas autonomous weapons,

they are going
to be easy to obtain.

That makes them more of a
challenge than nuclear weapons.

I mean, previously
if you wanted to do harm,

you needed an army.

Now, you would have an algorithm

that would be able to control
100 or 1000 drones.

And so you would
no longer be limited

by the number of people you had.

We don't have to go
down this road.

We get to make choices as to

what technologies get used
and how they get used.

We could just decide
that this was a technology

that we shouldn't use
for killing people.

[Somber musicl

We're going to be
building up our military,

and it will be so powerful,
nobody's going to mess with us.

Somehow we feel it's better
for a human to take our life

than for a robot
to take our life.

Instead of a human having
to pan and zoom a camera

to find a person in the crowd,

the automation
would pan and zoom

and find
the person in the crowd.

But either way, the outcome
potentially would be the same.

So, lethal autonomous weapons

don't actually
change this process.

The process is still human
approved at the very beginning.

And so what is it
that we're trying to ban?

Do you want to ban
the weapon itself?

Do you want to ban the sensor
that's doing the targeting,

or really do you want
to ban the outcome?

One of the difficulties
about the conversation on al

is conflating the near
term with long term.

We could carry on those...
Most of these conversations,

but, but let's not get them
all kind of rolled up

into one big ball.

Because that ball,
I think, over hypes

what is possible today
and kind of

simultaneously under hypes

what is ultimately possible.

Want to use this brush?

Can you make a portrait?
Can you draw me?

- No?
- How about another picture

- of Charlie brown?
- Charlie brown's perfect.

I'm going to move the
painting like this, all right?

Right, when we do it, like,
when it runs out of paint,

it makes a really
cool pattern, right?

It does.

One of the most
interesting things about

when I watch my daughter
paint is it's just free.

She's just pure expression.

My whole art is trying to see

how much of that
I can capture and code,

and then have my robots
repeat that process.

Yes.

The first machine learning

algorithms I started using

were something
called style transfer.

They were convolutional
neural networks.

It can look at an image, then
look at another piece of art

and it can apply the style

from the piece
of art to the image.

Every brush stroke,
my robots take pictures

of what they are painting,
and use that to decide

on the next brush stroke.

I try and get as many
of my algorithms in as possible.

Depending on where it is,
it might apply a gan or a CNN,

but back and forth,
six or seven stages

painting over itself,
searching for the image

that it wants to paint.

For me, creative al is
not one single god algorithm,

it's smashing as many algorithms
as you can together

and letting them
fight for the outcomes,

and you get these, like,
ridiculously creative results.

Did my machine make
this piece of art?

Absolutely not, I'm the artist.

But it made every single
aesthetic decision,

and it made every single
brush stroke in this painting.

There's this big question of, "can
robots and machines be creative?

Can they be artists?" And I think
they are very different things.

Art uses a lot of creativity,
but art

is one person communicating
with another person.

Until a machine has something
it wants to tell us,

it won't be making art,
because otherwise

it's just... just creating
without a message.

In machine learning you can say,

"here's a million recordings
of classical music.

Now, go make me something
kind of like brahms."

And it can do that.

But it can't make the thing

that comes after brahms.

It can make a bunch of random
stuff and then poll humans.

"Do you like this?
Do you like that?"

But that's different.

That's not
what a composer ever did.

Composer felt something
and created something

that mapped to the human
experience, right?

I've spent my
life trying to build

general artificial intelligence.

I feel humbled
by how little we know

and by how little we
understand about ourselves.

We just don't
understand how we work.

The human brain can do
over a quadrillion calculations

per second
on 20 watts of energy.

A computer right
now that would be able

to do that many
calculations per second

would run on 20 million
watts of energy.

It's an unbelievable system.

The brain can
learn the relationships

between cause and effect,

and build a world
inside of our heads.

This is the reason
why you can close your eyes

and imagine what it's like to,
you know, drive to the airport

in a rocket ship or something.

You can just play forward in
time in any direction you wish,

and ask whatever question
you wish, which is

very different from deep
learning style systems

where all you get is a mapping
between pixels and a label.

That's a good brush stroke.

Is that snoopy?

Yeah. Because snoopy
is okay to get pink.

Because guys can be pink
like poodle's hair.

I'm trying to learn...
I'm actually trying to teach

my robots to paint like you.

To try Ana get
the patterns that you can make.

It's hard.

You're a better
painter than my robots.

Isn't that crazy?

Yeah.

Much like the Wright brothers

learned how to build
an airplane by studying birds,

1 think that it's
important that we study

the right parts of neuroscience

in order to have
some foundational ideas

about building systems
that work like the brain.

[Somber musicl

Through my research
career, we've been very focused

on developing this notion
of a brain computer interface.

Where we started was
in epilepsy patients.

They require having
electrodes placed

on the surface
of their brain to figure out

where their seizures
are coming from.

By putting electrodes directly
on the surface of the brain,

you get the highest
resolution of brain activity.

It's kind of like
if you're outside of a house,

and there's
a party going on inside,

pasically you... all you really hear
is the bass, just a...

Wwhereas if you really
want to hear what's going on

and the specific conversations,

you have to get inside the walls

to hear that higher
frequency information.

It's very similar
to brain activity.

All right.

So, Frida, measure... measure
about ten centimeters back,

I just want to see
what that looks like.

And this really provided us
with this unique opportunity

to record directly
from a human brain,

to start to understand
the physiology.

In terms of the data
that is produced

by recording directly
from the surface of the brain,

it's substantial.

Machine learning
is a critical tool

for how we understand
brain function

because what machine
learning does,

is it handles complexity.

It manages information
and simplifies it in a way

that allows us
to have much deeper insights

into how the brain
interacts with itself.

You know,
projecting towards the future,

if you had the opportunity

where I could do
a surgery on you,

it's no more risky than Lasik,

but I could substantially
improve your attention

and your memory,
would you want it?

It's hard to fathom,
but al is going to interpret

what our brains want it to do.

If you think
about the possibilities

with a brain machine interface,

humans will be able
to think with each other.

Our imagination is going to say,
"oh, going to hear

their voice in your head.”
no, that's just talking.

It's going to be different.
It's going to be thinking.

And it's going
to be super strange,

and were going to be
very not used to it.

It's almost like two
brains meld into one

and have a thought
process together.

What that'll do for
understanding and communication

and empathy is pretty dramatic.

When you have a
brain computer interface,

now your ability
to touch the world

extends far beyond your body.

You can now go on virtual
vacations any time you want,

to do anything you want,

to be a different
person if you want.

But you know, we're just going to
keep track of a few of your thoughts,

and we're not going
to charge you that much.

It will be 100 bucks,
you interested?

If somebody can have
access to your thoughts,

how can that be pilfered,

how can that be abused,
how can that be

used to manipulate you?

What happens when a corporation
gets involved

and you have now
large aggregates

of human thoughts and data

and your resolution for
predicting individual behavior

becomes so much more profound

that you can really
manipulate not just people,

but politics
and governments and society?

And if it becomes this, you
know, how much does the benefit

outweigh the potential thing
that you're giving up?

Whether it's
50 years, 100 years,

even let's say 200 years,

that's still
such a small blip of time

relative to our human evolution
that it's immaterial.

Human history is 100,000 years.

Imagine if it's a 500-page book.

Each page is 200 years.

For the first 499 pages,

people got around on horses

and they spoke
to each other through letters,

and there was
under a billion people on earth.

On the last page of the book,

we have the first cars
and phones and electricity.

We've crossed the one, two,
three, four and five,

six, and seven
billion person marks.

So, nothing about this
is normal.

We are living
in a complete anomaly.

For most of human history,

the world
you grew up in was normal.

And it was naive to believe

that this is a special time.

Now, this is a special time.

Provided that science
is allowed to continue

on a broad front, then it does
look... it's very, very likely

that we will eventually
develop human level al.

We know that human
level thinking is possible

and can be produced
by a physical system.

In our case,
it weighs three pounds

and sits inside of a cranium,

but in principle,
the same types of computations

could be implemented in some
other subscript like a machine.

There's wide disagreement
between different experts.

S50, there are experts
who are convinced

we will certainly have
this within 10-15 years,

and there are experts
who are convinced

we will never get there

or it'll take
many hundreds of years.

I think even when we
do reach human level al,

I think the further step
to super intelligence

is likely to happen quickly.

Once al reaches a level
slightly greater than that,

the human scientist,
then the further developments

in artificial intelligence
will be driven increasingly

by the al itself.

You get the runaway al effect,
an intelligence explosion.

We have a word for 130 IQ.

We say smart.

Eighty IQ we say stupid.

I mean, we don't have
a word for 12,000 IQ.

It's so unfathomable for us.

Disease and poverty
and climate change

and aging and death
and all this stuff

we think is unconquerable.

Every single one
of them becomes easy

fo a super intelligent al.

Think of all the
possible technologies

perfectly realistic
virtual realities,

space colonies, all of those
things that we could do

over a millennia
with super intelligence,

you might get them very quickly.

You get a rush
to technological maturity.

We don't really know
how the universe began.

We don't really
know how life began.

Whether you're religious or not,

the idea of having

a super intelligence,

it's almost like we have
god on the planet now.

Even at the earliest space

when the field of artificial
intelligence was just launched

and some of the pioneers
were super optimistic,

they thought they could have
this cracked in ten years,

there seems to have been
no thought given

to what would happen
if they succeeded.

[Ominous musicl

An existential risk,

it's a risk from which
there would be no recovery.

It's kind of an end, premature
end to the human story.

We can't approach this by
just learning from experience.

We invent cars,
we find that they crash,

so we invent seatbelt
and traffic lights

and gradually we kind
of get a handle on that.

That's the way
we tend to proceed.

We model through
and adjust as we go along.

But with an existential risk,

you really need
a proactive approach.

You can't learn from failure,
you don't get a second try.

You can't take something
smarter than you back.

The rest of the animals
in the planet

definitely want
to take humans back.

I'ney can't, it's too late.

We're here, we're in charge now.

One class of concern
is alignment failure.

What we would see
is this powerful system

that is pursuing some
objective that is independent

of our human goals and values.

The problem would not be that
it would hate us or resent us,

it would be indifferent
to us and would optimize

the rest of the world according
to this different criteria.

A little bit like there might
be an ant colony somewhere,

and then we decide we want
a parking lot there.

I mean, it's not because
we dislike, like, hate the ants,

it's just we had some other goal
and they didn't factor

into our utility function.

The big word is alignment.

It's about taking
this tremendous power

and pointing it
in the right direction.

We come with some values.

We like those feelings,
we don't like other ones.

Now, a computer doesn't
get those out of the box.

Where it's going to get those,
is from us.

And if it all
goes terribly wrong

and artificial intelligence
builds giant robots

that kill all humans
and take over,

you know what?
It'll be our fault.

If we're going
to build these things,

we have to instill them
with our values.

And if we're not clear
about that,

then yeah,
they probably will take over

and it'll all be horrible.

But that's true for kids.

Empathy, to me, is
like the most important thing

that everyone should have.

I mean, that's, that's what's
going to save the world.

So, regardless of machines,

that's the first thing
I would want to teach my son

if that's teachable.

L

I don't think we
appreciate how much nuance

goes into our value system.

It's very specific.

You think programming
a robot to walk

is hard or recognize faces,

programming it
to understand subtle values

is much more difficult.

Say that we want
the al to value life.

But now it says, "okay,
well, if we want to value life,

the species that's killing
the most life is humans.

Let's get rid of them."

Even if we could get
the al to do what we want,

how will we humans
then choose to use

this powerful new technology?

These are not questions
just for people like myself,

technologists to think about.

These are questions
that touch all of society,

and all of society need
to come up with the answers.

One of the mistakes
that's easy to make

is that the future is something

that we're going
to have to adapt to,

as opposed
to the future is the product

of the decisions you make today.

J people j

J we're only people I

J there's not much j

j anyone can do j

j really do about that

j but it hasn't stopped us yes j

j people j

j we know so little
about ourselves j

J just enough j

j to want to be j

j nearly anybody else j

j now how does that add up j

j oh, friends all my friends &

j oh, I hope you're
somewhere smiling j

j just know I think about you j

j more kindly than you
and I have ever been j

j now see you the next
time round up there j

j ohjt

j ohjt

j ohjt

j people j

J what's the deal

J' you have been hurt j