FAINT GARBLED VOICES
Intelligence is the ability to understand.
We passed on what we know to machines.
The rise of artificial intelligence is happening fast,
but some fear the new technology
might have more problems than anticipated.
We will not control it.
Artificial intelligence is simply non-biological intelligence,
and intelligence itself is simply the ability to accomplish goals.
I'm convinced that AI will ultimately be
either the best thing ever to happen to humanity,
or the worst thing ever to happen.
We can use it to solve
all of today's and tomorrow's greatest problems -
cure diseases, deal with climate change,
lift everybody out of poverty.
But we could use exactly the same technology
to create a brutal global dictatorship,
with unprecedented surveillance and inequality and suffering.
That's why this is the most important conversation of our time.
Artificial intelligence is everywhere
because we now have thinking machines.
If you go on social media or online,
there's an artificial intelligence engine
that decides what to recommend.
If you go on Facebook
and you're just scrolling through your friends' posts,
there's an artificial intelligence engine
that's picking which one to show you first and which one to bury.
If you try to get insurance,
there's an AI engine trying to figure out how risky you are.
And if you apply for a job,
it's quite possible that an AI engine looks at the resume.
We are made of data.
Every one of us is made of data.
In terms of how we behave, how we talk, how we love,
what we do every day.
So computer scientists are developing deep learning algorithms
that can learn to identify, classify and predict patterns
within massive amounts of data.
We are facing a form of precision surveillance.
You could call it algorithmic surveillance,
and it means that you cannot go unrecognised.
You are always under the watch of algorithms.
Almost all the AI development on the planet today
is done by a handful of big technology companies
or by a few large governments.
If we look at what AI is mostly being developed for,
I would say it's, er...
..killing, spying and brainwashing.
So, I mean, we have military AI,
we have a whole surveillance apparatus
being built using AI by major governments.
And we have an advertising industry
which is oriented toward recognising what ads to try to sell to someone.
We humans have come to a fork in the road now.
The AI we have today is very narrow.
The Holy Grail of AI research ever since the beginning
is to make AI that can do everything better than us.
We basically built a god.
It's going to revolutionise life as we know it.
It's incredibly important
to take a step back and think carefully about this.
What sort of society do we want?
So we're in this historic transformation.
Like, we're raising this new creature.
You have a new offspring of sorts.
But, just like actual offspring,
you don't get to control everything it's going to do.
We are living at this privileged moment
where, for the first time, we will see, probably,
that AI is really going to outcompete humans
in many, many, if not all important fields.
Everything is going to change.
A new form of life is emerging.
When I was a boy, I thought, "How can I maximise my impact?"
And then it was clear that I have to build something
that learns to become smarter than myself,
such that I can retire
and the smarter thing can further self-improve
and solve all the problems that I cannot solve.
Multiplying that tiny little bit of creativity that I have
into infinity.
And that's what has been driving me since then.
How am I trying to build
a general-purpose artificial intelligence?
If you want to be intelligent,
you have to recognise speech and video and handwriting and faces
and all kinds of things.
And there we have made a lot of progress.
The LSTM neural networks,
which we developed in our labs in Munich and in Switzerland,
that's now used for speech recognition
and translation and video recognition.
They are now in everybody's smartphone.
Almost 1 billion iPhones
and in over 2 billion Android phones.
So we are generating all kinds of useful by-products
on the way to the general goal.
The main goal...
..is an artificial general intelligence, an AGI,
that can learn to improve the learning algorithm itself.
So it basically can learn to improve the way it learns
and it can also recursively improve the way it learns the way it learns
without any limitations,
except for the basic fundamental limitations of computability.
One of my favourite robots is this one here.
We use this robot for our studies of artificial curiosity,
where we are trying to teach this robot to teach itself.
What is a baby doing?
A baby is curiously exploring its world.
That's how it learns how gravity works
and how certain things topple and so on.
And as it learns to ask questions about the world,
and as it learns to answer these questions,
it becomes a more and more general problem-solver.
And so our artificial systems
are also learning to ask all kinds of questions,
not just slavishly try to answer
the questions given to them by humans.
You have to give AI the freedom to invent its own tasks.
If you don't do that, it's not going to become very smart.
On the other hand,
it's really hard to predict what they are going to do.
I feel that technology is a force of nature.
I feel like there is a lot of similarity
between technology and biological evolution.
Playing God.
Scientists have been accused of playing God for a while.
But there is a real sense
in which we are creating something...very different
from anything we've created so far.
SCANNER BEEPS
I was interested in the concept of AI from a relatively early age.
At some point, I got especially interested in machine learning.
What is experience?
What is learning? What is thinking?
How does the brain work?
These questions are philosophical,
but it looks like we can come up with algorithms
that both do useful things and help us answer these questions.
Like, it's almost like applied philosophy.
Artificial general intelligence, AGI.
A computer system that can do any job or any task
that a human does, but only better.
Yeah, I mean, we definitely will be able to create...
..completely autonomous beings with their own goals.
And it will be very important...
Especially as these beings become much smarter than humans,
it's going to be important to...to have these beings...
That the goals of these beings be aligned with our goals.
That's what we're trying to do at OpenAI -
be at the forefront of research
and steer the research, steer the initial conditions,
so to maximise the chance that the future will be good for humans.
Now, AI is a great thing,
because AI will solve all the problems that we have today.
It will solve employment.
It will solve disease.
It will solve poverty.
But it will also create new problems.
I think that...
Hm.
..the problem of fake news is going to be 1,000 million times worse.
Cyber attacks will become much more extreme.
You will have totally automated AI weapons.
I think AI has the potential to create
infinitely stable dictatorships.
You're going to see dramatically more intelligent systems
in 10 or 15 years from now.
And I think it's highly likely that those systems
will have completely astronomical impact on society.
Will humans actually benefit?
And who will benefit, who will not?
In 2012, IBM estimated that an average person
is generating 500 megabytes of digital footprints every single day.
Imagine that you wanted to back up one day worth of data
that humanity is leaving behind on paper.
How tall would be the stack of paper
that contains just one day worth of data that humanity's producing?
It's like from the Earth to the sun four times over.
In 2025, we'll be generating 62 gigabytes of data
per person per day.
We are leaving a ton of digital footprints
while going through our lives.
They provide computer algorithms with a fairly good idea
about who we are, what we want, what we're doing.
In my work, I looked at different types of digital footprints.
I looked at Facebook likes, I looked at language, credit card records,
web-browsing histories, search records.
Then each time, I found that if you get enough of this data,
you can accurately predict future behaviour
and reveal important intimate traits.
This can be used in great ways,
but it can also be used to manipulate people.
Facebook is delivering daily information
to 2 billion people or more.
If you slightly change the functioning of Facebook engine,
you can move the opinions, and hence the votes, of millions of people.
What do we want? Brexit!
When do we want it? Now!
A politician wouldn't be able to figure out
which message each one of his or her voters would like,
but a computer can see what political message
would be particularly convincing for you.
Ladies and gentlemen, it's my privilege to speak to you today
about the power of big data and psychographics
in the electoral process.
Data firm Cambridge Analytica secretly harvested
the personal information
of 50 million unsuspecting Facebook users.
CHANTING: USA! USA! USA!
The data firm,
hired by Donald Trump's presidential election campaign,
used secretly-obtained information
to directly target potential American voters.
With that, they say they can predict the personality
of every single adult in the United States.
Tonight, we're hearing from
Cambridge Analytica whistle-blower Christopher Wylie.
What we worked on was data-harvesting programmes
where we would pull data
and run that data through algorithms
that could profile their personality traits
and other psychological attributes
to exploit mental vulnerabilities
that our algorithms show that they had.
Cambridge Analytica mentioned once,
or said that their models were based on my work.
But Cambridge Analytica is just one of the hundreds of companies
that are using such methods to target voters.
You know, I would be asked questions by journalists such as, you know,
"So how do you feel about electing Trump and supporting Brexit?"
And, you know, how do you answer to such a question?
But I guess that I have to deal with being blamed for all of it.
How tech started was as a democratising force.
As a force for good,
as an ability for humans to interact with each other without gatekeepers.
There's never been a bigger experiment
in communications for the human race.
What happens when everybody gets to have their say?
You would assume that it would be for the better,
that there'd be more democracy. there'd be more discussion,
there'd be more tolerance.
But what's happened is that these systems have been hijacked.
We stand for connecting every person.
For a global community.
One company, Facebook, is responsible for the communications
of a lot of the human race.
Same thing with Google.
Everything you want to know about the world comes from them.
This is a global information economy
that is controlled by a small group of people.
BELL RINGS
CHEERING
The world's richest companies are all technology companies.
Google, Apple, Microsoft, Amazon, Facebook.
It's staggering how, in probably just ten years,
that the entire corporate power structure
are basically in the business of trading electrons.
These little bits and bytes are really the new currency.
The way that data is monetised is happening all around us,
even if it's invisible to us.
Google has every amount of information available.
They track people
by their GPS location.
They know exactly what your search history has been.
They know your political preferences.
Your search history alone can tell you everything about an individual,
from their health problems to their sexual preferences.
So Google's reach is unlimited.
So we've seen Google and Facebook
rise into these large surveillance machines,
and they're both actually ad brokers.
It sounds really mundane, but they're high-tech ad brokers.
And the reason they're so profitable
is that they're using artificial intelligence
to process all this data about you...
..and then to match you with the advertiser
that wants to reach people like you, for whatever message.
One of the problems with technology
is that it's been developed to be addictive.
The way these companies design these things
is in order to pull you in and engage you.
They want to become essentially a slot machine of attention.
So you're always paying attention.
You're always jacked into The Matrix.
You're always checking.
When somebody controls what you read,
they also control what you think.
You get more of what you've seen before and liked before,
because this gives more traffic and that gives more ads.
But it also locks you into your echo chamber.
And this is what leads to this polarisation that we see today.
CHANTING
Jair Bolsonaro, Brazil's right-wing populist candidate,
sometimes likened to Donald Trump, winning the presidency Sunday night,
in that country's most polarising election in decades.
Bolsonaro!
What we're seeing around the world
is upheaval and polarisation and conflict...
..that is partially pushed by algorithms
that's figured out that political extremes,
tribalism and sort of shouting for your team
and feeling good about it, is engaging.
SINGING
Social media may be adding to the attention
to hate crimes around the globe.
It's about how people can become radicalised
by living in the fever swamps of the Internet.
So is this a key moment for the tech giants?
Are they now prepared to take responsibility as publishers
for what they share with the world?
If you deploy a powerful, potent technology at scale -
and if you're talking about Google and Facebook,
you're deploying things at a scale of billions -
if your artificial intelligence is pushing polarisation,
you have global upheaval, potentially.
CHANTING: White lives matter! White lives matter! White lives matter!
CHANTING: Black lives matter! Black lives matter! Black lives matter!
SCREAMING
QUIET CLASSICAL PIANO
Artificial general intelligence, AGI.
Imagine your smartest friend.
With 1,000 friends, just as smart.
And then run them at 1,000-times faster than real-time.
So it means that, in every day of our time,
they will do three years of thinking.
Can you imagine how much...
..you could do...
..if for every day...
..you could do three years' worth of work?
It wouldn't be an unfair comparison to say that what we have right now
is even more exciting than, you know, the quantum physicists
of the early 20th century when they discovered nuclear power.
I feel extremely lucky to be taking part in.
Many machine learning experts, people who are very knowledgeable,
very experienced, have a lot of scepticism about AGI.
About when it could happen and about whether it could happen at all.
But right now, this is something
that just not that many people have realised yet,
that the speed of computers for neural networks, for AI,
are going to become maybe 20,000 times faster
in a small number of years.
The entire hardware industry,
for a long time, didn't really know what to do next.
But with artificial neural networks, now that they actually work,
you have a reason to build huge computers.
You can build a brain in silicon. It's possible.
But the very first AGIs will be
basically very, very large data centres,
packed with specialised neural network processors,
working in parallel.
A compact, hot, power-hungry package.
Consuming, like, 10 million homes' worth of energy.
Do you have a... a roast beef sandwich?
Roast beef sandwich. Yeah. Something slightly different.
Yes. Just this once.
But even the very first AGIs
will be dramatically more capable than humans.
Humans will no longer be economically useful
for nearly any task.
Why would you want to hire a human if you could just get a computer
that's going to do it much better and much more cheaply?
AGI is going to be, like, without question,
the most important technology in the history of the planet
by a huge margin.
It's going to be bigger than electricity,
nuclear and Internet combined.
In fact, you could say that the whole purpose of all human science,
the purpose of computer science, the endgame,
this is the endgame, to build this. And it's going to be built.
It's going to be a new life form. It's going to be...
It's going to make us obsolete.
TELEGRAPH BEEPS IN MORSE CODE
RADIO: We got programmes to go down here,
where we got that AK-47 fire, over.
INDISTINCT RADIO CHATTER
European manufacturers know the Americans have invested heavily
in the necessary hardware...
..to step into a brave new world of power,
performance and productivity.
All of the images you are about to see on the large screen
will be generated by what's in that Macintosh.
It's my honour and privilege to introduce to you
the Windows 95 development team.
Human physical labour has been mostly obsolete
for getting on for a century.
Routine human mental labour is rapidly becoming obsolete.
And that's why we're seeing a lot of middle class jobs disappearing.
STEVE JOBS: Every once in a while,
a revolutionary product comes along that changes everything.
Today, Apple is reinventing the phone.
EXCITED SCREAMS
Machine intelligence is already all around us.
The list of things that we humans can do better than machines
is actually shrinking pretty fast.
Driverless cars are great, they probably will reduce accidents,
except alongside with that in the United States,
you're going to lose 10 million jobs.
What are you going to do with 10 million unemployed people?
The risk for social conflict and tensions
if you exacerbate inequalities, is very, very high.
AGI can, by definition, do all jobs better than we can do.
People who are saying,
"Ah, there'll always be jobs that humans can do better than machines,"
are simply betting against science in saying there'll never be AGI.
What we're seeing now
is like a train hurtling down a dark tunnel at breakneck speed.
And it looks like we're sleeping at the wheel.
BUTTONS BEEP
A large fraction of the digital footprints we are leaving behind
are digital images.
And specifically what's really interesting to me as a psychologist
are digital images of our faces.
Here you can see the difference in the facial outline
of an average gay and average straight face.
And you can see that straight men have slightly broader jaws.
Gay women have slightly larger jaws,
compared with straight women.
Computer algorithms can reveal
our political views or sexual orientation
or intelligence, just based on the picture of our faces.
Even a human brain can distinguish between gay and straight men
with some accuracy.
Again, now, it turns out
that the computer can do it with much higher accuracy.
What you're seeing here is an accuracy
of off-the-shelf facial recognition software.
This is terrible news for gay men and women all around the world.
And not only gay men and women,
because the same algorithms can be used to detect
other intimate traits.
Think being a member of the opposition,
or being a liberal, or being an atheist.
Being an atheist is also punishable by death
in Saudi Arabia, for instance.
My mission as an academic is to warn people about the dangers
of algorithms being able to reveal our intimate traits.
The problem is that when people receive bad news,
they very often choose to dismiss them.
Well, it's a bit scary when you start receiving
death threats from one day to another.
And I received quite a few death threats.
But as a scientist,
I have to basically show what is possible.
So what I'm really interested in now is to try to see
whether we can predict other traits from people's faces.
Now, if you can detect depression from face or suicidal thoughts,
maybe a CCTV system on the train station can save some lives.
What if we could predict that someone is more prone
to commit a crime?
You probably had a school counsellor, a psychologist
hired there to identify children that potentially
may have some behavioural problems.
So now imagine if you could predict with high accuracy that someone
is likely to commit a crime in the future from the language used,
from their face, from their facial expressions,
from the likes on Facebook.
I'm not developing new methods,
I'm just describing something or testing something
in an academic environment.
But there obviously is a chance that while warning people against
risks of new technologies,
I may also give some people new ideas.
We haven't yet seen the future in terms of the ways
in which the new data-driven society is going to really evolve.
The tech companies want to get every possible bit of information
that they can collect on everyone to facilitate business.
The police and the military want to do the same thing
to facilitate security.
The interests that the two have in common are immense,
and so the extent of collaboration between what you might call
a military tech complex is growing dramatically.
The CIA, for a very long time, has maintained a close connection
with Silicon Valley.
Their venture capital firm, known as In-Q-Tel,
makes seed investments to start-up companies
developing breakthrough technology that the CIA hopes to deploy.
Palantir, the big data analytics firm,
one of their first seed investments was from In-Q-Tel.
In-Q-Tel struck gold in Palantir
in helping to create a private vendor
that has intelligence and artificial intelligence capabilities
that the government can't even compete with.
Good evening.
I'm Peter Thiel.
I'm not a politician, but neither is Donald Trump.
He is a builder.
And it's time to rebuild America.
CHEERING AND APPLAUSE
Peter Thiel, the founder of Palantir,
was a Donald Trump transition adviser
and a close friend and donor.
Trump was elected largely on the promise to deport
millions of immigrants.
The only way you can do that is with a lot of intelligence -
and that's where Palantir comes in.
They ingest huge troves of data which include where you live,
where you work, who you know, who your neighbours are,
who your family is, where you have visited, where you stay,
your social media profile.
Palantir gets all of that and is remarkably good at structuring it
in a way that helps law enforcement, immigration authorities
or intelligence agencies of any kind track you, find you
and learn everything there is to know about you.
We're putting AI in charge now of ever more important decisions
that affect people's lives.
Old-school AI used to have its intelligence programmed in
by humans who understood how it worked.
But today, powerful AI systems have just learned for themselves,
and we have no clue, really, how they work,
which makes it really hard to trust them.
This isn't some futuristic technology.
This is now.
AI might help determine where a fire department is built in a community
or where a school is built.
It might decide whether you get bail or whether you stay in jail.
It might decide where the police are going to be.
It might decide whether you're going to be
under additional police scrutiny.
It's popular now in the US to do predictive policing.
So what they do is they use an algorithm to figure out
where crime will be...
..and then they use that to tell
where we should send police officers.
So, that's based on a measurement of crime rate,
so we know that there is bias.
Black people and Hispanic people are pulled over or stopped
by the police officers more frequently than white people are,
so we have this biased data going in.
And then what happens is you use that to say,
"Oh, here's where the cops should go."
Well, the cops go to those neighbourhoods - and guess what they do? They arrest people.
And then it feeds back biased data into the system.
And that's called a feedback loop.
Predictive policing leads, at the extremes,
to experts saying, "Show me your baby and I will tell you
"whether she's going to be a criminal."
Now that we can predict it,
we're going to then surveil those kids much more closely
and we're going to jump on them at the first sign of a problem.
And that's going to make for more effective policing.
It does, but it's going to make for a really grim society,
and it's reinforcing - dramatically - existing injustices.
Imagine a world in which networks of CCTV cameras,
drone surveillance cameras,
have sophisticated face recognition technologies
and are connected to other government surveillance databases.
We will have the technology in place to have all of our movements
comprehensively tracked and recorded.
What that also means is that we will have created
a surveillance time machine that will allow governments
and powerful corporations to essentially hit rewind on our lives.
We might not be under any suspicion now.
And five years from now, they might want to know more about us
and can then recreate - granularly - everything we've done,
everyone we've seen, everyone we've been around
over that entire period.
That's an extraordinary amount of power
for us to cede to anyone.
And it's a world that I think has been difficult
for people to imagine.
But we've already built the architecture to enable that.
I'm a political reporter, and I'm very interested in the ways
powerful industries use their political power to influence
the public policy process.
The large tech companies and their lobbyists get together
behind closed doors and are able to craft policies
that we all have to live under.
That's true for surveillance policies,
for policies in terms of data collection,
but also increasingly important when it comes to
military and foreign policy.
Starting in 2016,
the Defense Department formed the Defense Innovation Board.
That's a special body created to bring top tech executives
into closer contact with the military.
Eric Schmidt, former chairman of Alphabet,
the parent company of Google,
became the chairman of the Defense Innovation Board.
And one of their first priorities was to say,
"We need more artificial intelligence
"integrated into the military."
I've worked with a group of volunteers
over the last couple of years to take a look at innovation
in the overall military.
And my summary conclusion is that we have fantastic people
who are trapped in a very bad system.
From the Department of Defense's perspective,
where I really started to get interested in it,
when we started to think about unmanned systems
and how robotic and unmanned systems would start to change war.
The smarter you made the unmanned systems and robots,
the more powerful you might be able to make your military.
Under Secretary of Defense Robert Work
put together a major memo known as
the Algorithmic Warfare Cross-Functional Team,
better known as Project Maven.
Eric Schmidt gave a number of speeches
and media appearances where he said this effort was designed to increase
fuel efficiency in the Air Force to help with the logistics.
But behind closed doors, there was another parallel effort.
Late in 2017, as part of Project Maven,
Google, Eric Schmidt's firm,
was tapped to secretly work on another part of Project Maven,
and that was to take the vast volumes of image data
vacuumed up by drones operating in Iraq and Afghanistan
and to teach an AI to quickly identify targets on the battlefield.
We have a sensor and the sensor can do full motion video
of an entire city.
And we would have three seven-person teams working constantly
and they could process 15% of the information.
The other 85% of the information was just left
on the cutting room floor.
So we said, "Hey, AI and machine learning would help us process
"100% of the information."
Google has long had the motto, "Don't be evil."
They have created a public image that they are devoted
to public transparency.
But for Google to slowly transform into a defence contractor,
they maintained the utmost secrecy.
You had Google entering into this contract with most of the employees,
even employees who were working on the programme,
completely left in the dark.
Usually within Google,
anyone in the company is allowed to know
about any other project that's happening in some other part
of the company.
With Project Maven, the fact that it was kept secret
I think was kind of alarming to people,
cos that's not the norm at Google.
When the story was first revealed,
it started off a firestorm within Google.
You had a number of employees quitting in protest,
others signing a petition objecting to this work.
You have to really say, like,
"I don't want to be part of this any more."
There are companies called defence contractors
and Google should just not be one of those companies,
because people need to trust Google for Google to work.
Good morning.
Welcome to Google I/O.
CHEERING
We've seen emails that show that Google
simply continued to mislead their employees,
that the drone targeting programme was only a minor effort
that could at most be worth $9 million to the firm, which is,
you know, drops in the bucket for a gigantic company like Google.
But from internal emails that we obtained,
Google was expecting Project Maven would ramp up to
as much as $250 million and that this entire effort
would provide Google with special Defence Department certification
to make them available for even bigger defence contracts,
some worth as much as $10 billion.
The pressure for Google to compete for military contracts has come
at a time when its competitors are also shifting their culture.
Amazon similarly pitching the military and law enforcement.
IBM and other leading firms,
they're pitching law enforcement and military.
To stay competitive, Google has slowly transformed.
The Defense Science Board said of all of the technological advances
that are happening right now,
the single most important thing was artificial intelligence
and the autonomous operations that it would lead.
Are we investing enough?
Once we develop what are known as autonomous lethal weapons -
in other words, weapons that are not controlled at all,
they are genuinely autonomous -
you've only got to get a president who says,
"The hell with international law. We've got these weapons.
"We're going to do what we want with them."
We're very close.
When you have the hardware already set up
and all you have to do is flip a switch
to make it fully autonomous,
what is it there that's stopping you from doing that?
There's something really to be feared in war machine speed.
What if you're a machine and you've run millions and millions
of different war scenarios and you have a team of drones
and you've delegated control to half of them,
and you're collaborating in real time?
What happens when that swarm of drones is tasked
with engaging a city?
How will they take over that city?
The answer is, we won't know until it happens.
We do not want an AI system to decide what human it would attack,
but we're going up against authoritarian competitors.
So in my view, an authoritarian regime will have less problem
delegating authority to a machine to make lethal decisions.
So how that plays out remains to be seen.
Almost the gift of AI now is that it will force us collectively
to think through, at a very basic level,
what does it mean to be human?
What do I do as a human better
than a certain super smart machine can do?
First, we create our technology, and then it recreates us.
We need to make sure that we don't miss some of the things
that make us so beautifully human.
Once we build intelligent machines,
the philosophical vocabulary we have available
to think about ourselves as human increasingly fails us.
If I ask you to write up a list of all the terms you have available
to describe yourself as human, there are not so many terms -
culture, history, sociality, maybe politics,
civilisation, subjectivity.
All of these terms ground in two positions -
that humans are more than mere animals
and that humans are more than mere machines.
But if machines truly think,
there is a large set of key philosophical questions
in which what is at stake is...
..who are we? What's our place in the world?
What is the world? How is it structured?
Do the categories that we have relied on,
do they still work? Are they wrong?
Many people think of intelligence as something mysterious
that can only exist inside of biological organisms like us.
But intelligence is all about information processing.
It doesn't matter whether the intelligence is processed
by carbon atoms inside of cells in brains in people
or by silicon atoms in computers.
Part of the success of AI recently has come from stealing
great ideas from evolution.
We noticed that the brain, for example,
has all these neurons inside connected in complicated ways.
So we stole that idea and abstracted it
into artificial neural networks in computers.
And that's what's revolutionised machine intelligence.
If we one day get artificial general intelligence,
then by definition, AI can also do better
the job of AI programming.
And that means that further progress in making AI will be dominated
not by human programmers, but by AI.
Recursively self-improving AI could leave human intelligence far behind,
creating superintelligence.
It's going to be the last invention we ever need to make,
because it can then invent everything else
much faster than we could.
MACHINE MURMURS AND STUTTERS
MACHINE SPEAKS INDISTINCTLY
MACHINE SPEEDS UP
There is a future that we all need to talk about.
Some of the fundamental questions about the future
of artificial intelligence, not just where it's going,
but what it means for society to go there.
It is not what computers can do,
but what computers should do.
As the generation of people that is bringing AI to the future,
we are the generation that will answer this question
first and foremost.
We haven't created the human-level thinking machine yet,
but we get closer and closer.
Maybe we'll get to human-level AI in five years from now,
or maybe it'll take 50 or 100 years from now.
It almost doesn't matter.
Like, these are all really, really soon
in terms of the overall history of humanity.
AI SINGS OPERATICALLY
Very nice.
So, the AI field is extremely international.
China is up-and-coming
and it's starting to rival the US, Europe and Japan
in terms of putting a lot of processing power behind AI
and gathering a lot of data to help AI learn.
We have a young generation of Chinese researchers now.
Nobody knows where the next revolution is going to come from.
China always wants to become a superpower in the world.
The Chinese government thinks AI gave them the chance
to become one of the most advanced technology-wise, business-wise.
So the Chinese government look at this as a huge opportunity.
Like, they raise a flag and said, "That's good field.
"The companies should jump into it."
Then China's commercial world, as a company,
just, "OK, come and raise the flag. That's good.
"Let's put the money into it."
Chinese tech giants like Baidu, like Tencent, like Alibaba,
they put a lot of their investment into the AI field.
So we see China's AI development is booming.
In China, everybody has Alipay and WeChat Pay,
so the mobile payment is everywhere.
And with that, they can do, like, a lot of AI analysis
to know, like, your spending habits,
like, your credit rating.
Face recognition technology is widely adopted in China,
in the airport, in the train station.
So in the future, maybe in just a few months,
you don't need a paper ticket to board a train.
Only your face.
We generate the world's biggest platform of facial recognition.
We have 300,000 developers using our platform.
A lot of it is the selfies camera apps.
It makes you look more beautiful.
There is millions and millions of camera in the world.
Each camera, from my point, is a data generator.
In the machine's eye, your face would change into the features
and it would turn your face into a paragraph of the code...
..so we can detect,
"How old are you?", "Are you male or female?", and your emotions.
This whole thing is about what kind of thing you are looking at.
So then we can track your eyeballs,
so if you are focusing on some product,
we can track that so that we can know which kind of people
like which kind of product.
The Chinese government is using multiple
different kinds of technologies,
whether it's AI, whether it's big data platforms,
facial recognition, voice recognition,
essentially to monitor what the population is doing.
I think the Chinese government has made very clear its intent
to gather massive amounts of data about people to socially engineer
a dissent-free society.
The logic behind the Chinese government's social credit system,
it's to take the idea that whether you are credit worthy
for a financial loan and adding to it a very political dimension
to say, are you a trustworthy human being?
What you've said online,
have you ever been critical of the authorities?
Do you have a criminal record?
And all of that information is packaged up together
to rate you in ways that if you have performed well, in their view,
you'll have easier access to certain kinds of state services or benefits,
but that if you haven't done very well, you're going
to be penalised or restricted.
There's no way for people to challenge those designations,
or in some cases even know that they've been put in that category.
And it's not until they try to access some kind of state service
or buy a plane ticket or get a passport or enrol their kids
in school that they come to learn that they've been labelled
in this way and that there are negative consequences for them
as a result.
We've spent the better part of the last one or two years
looking at abuses of surveillance technology across China.
And a lot of that work has taken us to Xinjiang...
..the northwestern region of China that has a more than half population
of Turkic Muslims, Uyghurs, Kazakhs, Hui.
This is a region and a population the Chinese government has
long considered to be politically suspect or disloyal.
We came to find information about what's called
the Integrated Joint Operations Platform,
which is a predictive policing programme.
And that's one of the programmes that has been spitting out lists
of names of people to be subjected to political re-education.
A number of our interviewees for the report we just released
about the political education camps in Xinjiang
just painted an extraordinary portrait of a surveillance state.
A region awash in surveillance cameras
for facial recognition purposes,
checkpoints, body scanners, QR codes outside people's homes.
It really is the stuff of dystopian movies that we've all gone to
and thought, "Wow, that would be a creepy world to live in."
Yeah, well, 13 million Turkic Muslims in China are living
in that reality right now.
The Intercept reports that Google is planning to launch
a censored version of its search engine in China.
Google's search for new markets leads it to China
despite Beijing's rules on censorship.
Tell us more about why you felt it was your ethical responsibility
to resign, because you talk about
being complicit in censorship and oppression and surveillance.
There is a Chinese venture company that has to be set up
for Google to operate in China.
And the question is, to what degree did they get to control
the blacklist and to what degree would they have just unfettered
access to surveilling Chinese citizens?
And the fact that Google refuses to respond
to human rights organisations on this,
I think, should be extremely disturbing to everyone.
Due to my conviction that dissent is fundamental
to functioning democracies,
I am forced to resign in order to avoid contributing to
or profiting from the erosion of protections for dissidents.
The United Nations is currently reporting
that between 200,000 and one million Uyghurs
have been disappeared into re-education camps.
And there is a serious argument that Google would be complicit,
should it want to surveil the version of Search in China.
Dragonfly is a project meant to launch Search in China
under Chinese government regulations,
which include censoring sensitive content,
basic queries on human rights.
Information about political representatives is blocked.
Information about student protests is blocked,
and that's one small part of it.
Perhaps a deeper concern is the surveillance side of this.
When I raised the issue with my managers, with my colleagues,
there was a lot of concern.
But everyone just said, "I don't know anything."
And then when there was a meeting, finally, there was essentially
no addressing the serious concerns associated with it.
So then I filed my formal resignation, not just to my manager,
but I actually distributed it company-wide.
And that's the letter that I was reading from.
Personally, I haven't slept well.
I've had pretty horrific headaches.
Wake up in the middle of the night just sweating.
With that said, what I've found since speaking out
is just how positive the global response to this has been.
Engineers should demand to know
what the uses of their technical contributions are
and to have a seat at the table in those ethical decisions.
Most citizens don't really understand what it means
to be in a very large scale prescriptive technology,
where someone has already pre-divided the work
and all you know about is your little piece,
and almost certainly you don't understand how it fits in.
So I think it's worth drawing the analogy to physicists' work
on the atomic bomb.
In fact, that's actually the community I came out of.
I wasn't a nuclear scientist by any means,
but I was an applied mathematician.
And my PhD programme was largely funded to train people
to work in weapons labs.
One could certainly argue that there is an existential threat.
And whoever is leading in AI will lead militarily.
China fully expects to pass the United States
as the number one economy in the world
and it believes that AI will make that jump more quickly
and more dramatically.
And they also see it as being able to leapfrog the United States
in terms of military power.
CHANTING
Their plan is very simple.
We want to catch the United States in these technologies by 2020.
We want to surpass the United States in these technologies by 2025.
And we want to be the world leader in AI
and autonomous technologies by 2030.
It is a national plan.
It is backed up by at least $150 billion in investments.
So this is definitely a race.
AI is a little bit like fire.
Fire was invented 700,000 years ago.
And it has its pros and cons.
People realised you can use fire to keep warm at night and to cook.
But they also realise that you can...
..kill other people with it.
Fire also has this AI-like quality of growing in a wildfire
without further human ado.
But the advantages outweigh the disadvantages by so much
that we are not going to stop its development.
Europe is waking up.
Lots of companies in Europe are realising that the next wave
of AI will be much bigger than the current wave.
The next wave of AI will be about robots.
All these machines that make things, that produce stuff,
that build other machines, they are going to become smart.
In the not so distant future,
we will have robots that we can teach like we teach kids.
For example, I will talk to a little robot and I will say,
"Look here, robot, look here.
"Let's assemble a smartphone.
"We take a slab of plastic like that and we take
"the screwdriver like that.
"And now we screw in everything like this.
"No, no, not like this. Like this.
"Look, robot, look. Like this."
And he will fail a couple of times, but rather quickly,
he will learn to do the same thing much better than I could do it.
And then we stop the learning
and we make a million copies and sell it.
Regulation of AI sounds like an attractive idea,
but I don't think it's possible.
One of the reasons why it won't work
is the sheer curiosity of scientists.
They don't give a damn for regulation.
Military powers won't give a damn for regulations either.
They will say, "If we, the Americans, don't do it,
"the Chinese will do it," and the Chinese will say,
"Oh, if we don't do it, then the Russians will do it."
No matter what kind of political regulation is out there,
all these military industrial complexes,
they will almost by definition have to ignore that,
because they want to avoid falling behind.
A programme developed by the company Open AI
can write coherent and credible stories just like human beings.
It's one small step for machine, one giant leap for machinekind.
IBM's newest artificial intelligence system took on experienced
human debaters and won a live debate.
Computer generated videos known as deepfakes are being used
to put women's faces on pornographic videos.
Artificial intelligence evolves at a very crazy pace.
You know, it's, like, progressing so fast.
In some ways, we're only at the beginning right now.
You have so many potential applications.
It's a gold mine.
Well, since 2012, when deep learning became, like, a big game changer
in the computer vision community,
we were one of the first to actually adopt deep learning
and apply it in the field of computer graphics.
A lot of our research is funded by government,
military, intelligence agencies.
The way we create these photo-real mappings, usually the way it works
is that we need two subjects, a source and a target,
and I can do a face replacement.
One of the applications is, for example, I want to manipulate
someone's face saying things that he did not.
It can be used for creative things, for funny content, but obviously,
it can also be used for just simply manipulate videos
and generate fake news.
This can be very dangerous.
If it gets into the wrong hands,
it can get out of control very quickly.
We're entering an era in which our enemies can make it look like
anyone is saying anything at any point in time.
Even if they would never say those things.
Moving forward, we need to be more vigilant
with what we trust from the internet.
It may sound basic, but how we move forward
in the age of information is going to be the difference
between whether we survive or whether we become some kind
of fucked-up dystopia.
OVERLAPPING VOICES BABBLE
One criticism that is frequently raised against my work
is saying that, hey, you know, there were stupid ideas in the past,
like phrenology or physiognomy.
There were people claiming that you can read a character
of a person just based on their face.
People would say, this is rubbish -
we know it was just thinly veiled racism and superstition.
But the fact that someone made a claim in the past
and tried to support this claim with invalid reasoning
doesn't automatically invalidate the claim.
Of course, people should have rights to their privacy when it comes
to sexual orientation or political views.
But I'm also afraid that in the current
technological environment, this is essentially impossible.
People should realise there's no going back.
There's no running away from the algorithms.
The sooner we accept the inevitable and inconvenient truth
that privacy is gone...
..the sooner we can actually start thinking about how to make sure
that our societies are ready for the post-privacy age.
While speaking about facial recognition,
in my deep thoughts, I sometimes get
to the very dark era of our history...
..when the people had to live in the system
where some part of the society was accepted
and some part of the society was abused to death.
What would Mengele do to have such an instrument in his hands?
It would be very quick and efficient for selection.
And this is the apocalyptic vision.
TRAIN WHOOSHES
So in the near future, the entire story of you will exist
in a vast array of connected databases
of faces, genomes, behaviours and emotion.
So you will have a digital avatar of yourself online, which records
how well you are doing as a citizen,
what kind of relationship do you have,
what kind of political orientation and sexual orientation.
Based on all of those data, those algorithms will be able
to manipulate your behaviour with an extreme precision.
Changing how we think,
and probably in the future, how we feel.
The beliefs and desires of the first AGIs will be extremely important.
So it's important to programme them correctly.
I think that if this is not done, then the nature of evolution,
of natural selection, would favour those systems,
prioritise their own survival above all else.
It's not that it's going to actively hate humans and want to harm them.
But it is going to be too powerful.
And I think a good analogy would be the way
humans treat animals.
It's not that we hate animals. I think humans love animals
and have a lot of affection for them.
But when the time comes to build a highway between two cities,
we're not asking the animals for permission.
We just do it because it's important for us.
And I think by default, that's the kind of relationship
that's going to be between us and AGIs which are truly autonomous
and operating on their own behalf.
If you have an arms race dynamics
between multiple teams trying to do the AGI first,
they will have less time to make sure
that the AGI they will build do care deeply for humans.
Because the way I imagine it is that there is an avalanche.
There is an avalanche of AGI development.
Imagine you have this huge unstoppable force.
And I think it's pretty likely that the surface of the Earth
will be covered with solar panels and data centres.
Given these kinds of concerns,
it will be important that AGI is somehow built
as a cooperation between multiple countries.
The future is going to be good for the AIs regardless.
It would be nice if it were good for humans as well.
Is there a lot of responsibility weighing on my shoulders?
Not really.
Was there a lot of responsibility on the shoulders
of the parents of Einstein?
The parents somehow made him, but they had no way of predicting
what he would do and how he would change the world.
And so you can't really hold them responsible for that.
So I'm not a very human-centric person.
I think I'm a little stepping stone in the evolution of the universe
towards higher complexity.
But it's also clear to me that I'm not the crown of creation
and that humankind as a whole is not the crown of creation.
But we are setting the stage for something that is bigger than us,
that transcends us.
And that will go out there in a way where humans cannot follow
and transform the entire universe, or at least the reachable universe.
So I find beauty and awe
and see myself as part of this much grander theme.
AI is inevitable.
We need to make sure we have the necessary human regulation
to prevent the weaponization of artificial intelligence.
We don't need any more weaponization of such a powerful tool.
One of the most critical things, I think, is the need
for international governance.
We have an imbalance of power here.
So now we have corporations with more power, might and ability
than entire countries.
How do we make sure that people's voices are getting heard?
It can't be a law-free zone. It can't be a rights-free zone.
We can't embrace all of these wonderful new technologies
for the 21st century
without trying to bring with us the package
of human rights that we fought so hard to achieve,
and that remains so fragile.
AI isn't good and it isn't evil either.
It's just going to amplify the desires and goals
of whoever controls it.
And the AI today is under the control
of a very, very small group of people.
The most important question that we humans have to ask ourselves
at this point in history requires no technical knowledge.
It's the question of,
what sort of future society do we want to create
with all this technology we're making?
What do we want the role of humans to be in this world?