Original subtitles

[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.

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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

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j people j

J what's the deal

J' you have been hurt j