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[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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