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- Intelligence is
the ability to understand.

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We passed on what we know to machines.

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- The rise of
artificial intelligence

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is happening fast, but some
fear the new technology

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might have more problems than anticipated.

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- We will not control it.

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- Artificially
intelligent algorithms are here,

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but this is only the beginning.

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- In the age of AI,
data is the new oil.

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- Today, Amazon,
Google and Facebook

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are richer and more
powerful than any companies

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that have ever existed
throughout human history.

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- A handful of people working at
a handful of technology companies

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steer what a billion
people are thinking today.

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- This technology is changing:
What does it mean to be human?

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- Artificial intelligence is simply
non-biological intelligence.

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And intelligence itself is simply
the ability to accomplish goals.

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I'm convinced that AI
will ultimately be either

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the best thing ever to happen to humanity,
or the worst thing ever to happen.

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We can use it to solve all
of today's and tomorrow's

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greatest problems; cure diseases,
deal with climate change,

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lift everybody out of poverty.

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But, we could use exactly
the same technology

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to create a brutal global
dictatorship with unprecedented

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surveillance and inequality and suffering.

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That's why this is the most important
conversation of our time.

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- Artificial intelligence is everywhere

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because we now have thinking machines.

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If you go on social media or online,

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there's an artificial intelligence engine
that decides what to recommend.

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If you go on Facebook and you're just
scrolling through your friends' posts,-

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there's an AI engine that's picking
which one to show you first

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- and which one to bury.

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If you try to get insurance,
there is an AI engine

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trying to figure out how risky you are.

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And if you apply for a job,
it's quite possible

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that an AI engine looks at the resume.

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- We are made of data.

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Every one of us is made of data
-in terms of how we behave,

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how we talk, how we love,
what we do every day.

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So, computer scientists are
developing deep learning

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algorithms that can learn
to identify, classify,

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and predict patterns within
massive amounts of data.

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We are facing a form of
precision surveillance,

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you could call it algorithmic surveillance,

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and it means that you
cannot go unrecognized.

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You are always under
the watch of algorithms.

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- Almost all the AI
development on the planet today

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is done by a handful of
big technology companies

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or by a few large governments.

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If we look at what AI is
mostly being developed for,

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I would say it's killing,
spying, and brainwashing.

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So, I mean, we have military AI,

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we have a whole surveillance
apparatus being built

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using AI by major governments,

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and we have an advertising
industry which is oriented

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toward recognizing what ads
to try to sell to someone.

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- We humans have come to
a fork in the road now.

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The AI we have today is very narrow.

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The holy grail of AI research
ever since the beginning

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is to make AI that can do
everything better than us,

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and we've basically built a God.

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It's going to revolutionize
life as we know it.

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It's incredibly important
to take a step back

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and think carefully about this.

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What sort of society do we want?

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- So, we're in this
historic transformation.

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Like we're raising this new creature.

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We have a new offspring of sorts.

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But just like actual offspring,

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you don't get to control
everything it's going to do.

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We are living at
this privileged moment where,

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for the first time, we
will see probably that AI

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is really going to outcompete
humans in many, many,

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if not all, important fields.

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- Everything is going to change.

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A new form of life is emerging.

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When I was a boy, I thought,
how can I maximize my impact?

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And then it was clear that
I have to build something

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that learns to become smarter than myself,

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such that I can retire,

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and the smarter thing
can further self-improve

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and solve all the problems
that I cannot solve.

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Multiplying that tiny
little bit of creativity

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that I have into infinity,

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and that's what has been
driving me since then.

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How am I trying to build

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a general purpose artificial intelligence?

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If you want to be intelligent,
you have to recognize speech,

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video and handwriting, and
faces, and all kinds of things,

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and there we have made a lot of progress.

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See, LSTM, neural networks,

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which we developed in our labs
in Munich and in Switzerland,

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and it's now used for speech
recognition and translation,

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and video recognition.

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They are now in everybody's
smartphone, almost one billion

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iPhones and in over
two billion Android phones.

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So, we are generating all
kinds of useful by-products

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on the way to the general goal.

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The main goal, some Artificial
General Intelligence,

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an AGI that can learn to improve
the learning algorithm itself.

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So, it basically can learn
to improve the way it learns

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and it can also recursively
improve the way it learns,

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the way it learns without
any limitations except for

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the basic fundamental
limitations of computability.

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One of my favorite
robots is this one here.

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We use this robot for our
studies of artificial curiosity.

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Where we are trying to teach
this robot to teach itself.

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What is a baby doing?

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A baby is curiously exploring its world.

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That's how he learns how gravity works

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and how certain things topple, and so on.

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And as it learns to ask
questions about the world,

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and as it learns to
answer these questions,

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it becomes a more and more
general problem solver.

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And so, our artificial
systems are also learning

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to ask all kinds of
questions, not just slavishly

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try to answer the questions
given to them by humans.

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You have to give AI the freedom
to invent its own tasks.

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If you don't do that, it's not
going to become very smart.

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On the other hand, it's really hard
to predict what they are going to do.

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- I feel that technology
is a force of nature.

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I feel like there is a lot of similarity between
technology and biological evolution.

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Playing God.

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Scientists have been accused
of playing God for a while,

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- but there is a real sense in
which we are creating something

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very different from anything
we've created so far.

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I was interested in the concept of
AI from a relatively early age.

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At some point, I got especially
interested in machine learning.

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What is experience?

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What is learning?

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What is thinking?

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How does the brain work?

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These questions are philosophical,

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but it looks like we can
come up with algorithms that

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both do useful things and help
us answer these questions.

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Like it's almost like applied philosophy.

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Artificial General Intelligence, AGI.

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A computer system that
can do any job or any task

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that a human does, but only better.

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Yeah, I mean, we definitely
will be able to create

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completely autonomous
beings with their own goals.

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And it will be very important,

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especially as these beings
become much smarter than humans,

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it's going to be important
to have these beings,

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that the goals of these beings
be aligned with our goals.

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That's what we're trying
to do at OpenAI.

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Be at the forefront of research
and steer the research,

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steer their initial conditions
so to maximize the chance

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that the future will be good for humans.

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Now, AI is a great thing
because AI will solve

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all the problems that we have today.

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It will solve employment,
it will solve disease,

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it will solve poverty,

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but it will also create new problems.

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I think that...

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The problem of fake news
is going to be a thousand,

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a million times worse.

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Cyberattacks will
become much more extreme.

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You will have totally
automated AI weapons.

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I think AI has the potential to create
infinitely stable dictatorships.

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You're gonna see dramatically
more intelligent systems

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in 10 or 15 years from now,
and I think it's highly likely

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that those systems will have
completely astronomical impact on society.

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Will humans actually benefit?

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And who will benefit, who will not?

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- In 2012, IBM estimated that

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an average person is
generating 500 megabytes

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of digital footprints every single day.

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Imagine that you wanted
to back-up one day worth

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of data that humanity is
leaving behind, on paper.

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How tall will be the stack
of paper that contains

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just one day worth of data
that humanity is producing?

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It's like from the earth
to the sun, four times over.

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In 2025, we'll be generating
62 gigabytes of data

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per person, per day.

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We're leaving a ton of digital footprints
while going through our lives.

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They provide computer algorithms
with a fairly good idea about who we are,

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what we want, what we are doing.

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In my work, I looked at different
types of digital footprints.

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I looked at Facebook likes,
I looked at language,

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credit card records, web browsing
histories, search records.

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and each time I found that if
you get enough of this data,

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you can accurately predict future behavior

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and reveal important intimate traits.

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This can be used in great ways,

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but it can also be used
to manipulate people.

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Facebook is delivering daily information

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to two billion people or more.

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If you slightly change the
functioning of the Facebook engine,

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you can move the opinions and hence,

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the votes of millions of people.

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- Brexit!
- When do we want it?

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- Now!

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- A politician
wouldn't be able to figure out

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which message each one of
his or her voters would like,

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but a computer can see
what political message

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would be particularly convincing for you.

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- Ladies and gentlemen,

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it's my privilege to speak
to you today about the power

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of big data and psychographics
in the electoral process.

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- Data from Cambridge Analytica

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secretly harvested the
personal information

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of 50 million unsuspecting Facebook users.

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USA!

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- The data firm hired by Donald Trump's
presidential election campaign

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used secretly obtained information
to directly target potential American voters.

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- With that, they say they can predict

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the personality of every single
adult in the United States.

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- Tonight we're hearing
from Cambridge Analytica

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whistleblower, Christopher Wiley.

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- What we worked on was
data harvesting programs

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where we would pull data and run that
data through algorithms that could profile

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their personality traits and
other psychological attributes

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to exploit mental vulnerabilities
that our algorithms showed that they had.

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- Cambridge Analytica mentioned once

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or said that their models
were based on my work,

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but Cambridge Analytica is
just one of the hundreds

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of companies that are using
such methods to target voters.

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You know, I would be asked
questions by journalists such as,

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"So how do you feel about

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"electing Trump and supporting Brexit?"

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How do you answer to such question?

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I guess that I have to deal
with being blamed for all of it.

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- How tech started was
as a democratizing force,

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as a force for good, as
an ability for humans

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to interact with each
other without gatekeepers.

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There's never been a bigger experiment
in communications for the human race.

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What happens when everybody
gets to have their say?

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You would assume that it
would be for the better,

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that there would be more democracy,
there would be more discussion,

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there would be more tolerance,
but what's happened is that

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these systems have been hijacked.

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- We stand for connecting every person.

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For a global community.

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- One company,
Facebook, is responsible

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for the communications of
a lot of the human race.

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Same thing with Google.

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Everything you want know about
the world comes from them.

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This is global information economy

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that is controlled by a
small group of people.

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- The world's richest companies
are all technology companies.

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Google, Apple, Microsoft,
Amazon, Facebook.

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It's staggering how,

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in probably just 10 years,

248
00:23:31,770 --> 00:23:34,810
that the entire corporate power structure

249
00:23:34,810 --> 00:23:39,460
are basically in the business
of trading electrons.

250
00:23:41,240 --> 00:23:47,060
These little bits and bytes
are really the new currency.

251
00:23:53,560 --> 00:23:55,800
- The way that data is monetized

252
00:23:55,800 --> 00:23:58,820
is happening all around us,
even if it's invisible to us.

253
00:24:00,960 --> 00:24:04,280
Google has every amount
of information available.

254
00:24:04,280 --> 00:24:07,110
They track people by their GPS location.

255
00:24:07,110 --> 00:24:10,080
They know exactly what your
search history has been.

256
00:24:10,080 --> 00:24:12,850
They know your political preferences.

257
00:24:12,850 --> 00:24:14,840
Your search history alone can tell you

258
00:24:14,840 --> 00:24:17,570
everything about an individual
from their health problems

259
00:24:17,570 --> 00:24:19,480
to their sexual preferences.

260
00:24:19,480 --> 00:24:21,880
So, Google's reach is unlimited.

261
00:24:28,750 --> 00:24:31,620
- So we've seen Google and Facebook

262
00:24:31,620 --> 00:24:34,150
rise into these large
surveillance machines

263
00:24:35,040 --> 00:24:38,200
and they're both actually ad brokers.

264
00:24:38,200 --> 00:24:42,040
It sounds really mundane,
but they're high tech ad brokers.

265
00:24:42,910 --> 00:24:46,080
And the reason they're so
profitable is that they're using

266
00:24:46,080 --> 00:24:49,750
artificial intelligence to
process all this data about you,

267
00:24:51,560 --> 00:24:54,660
and then to match you with the advertiser

268
00:24:54,660 --> 00:24:59,660
that wants to reach people
like you, - for whatever message.

269
00:25:03,000 --> 00:25:07,880
- One of the problems with technology is
that it's been developed to be addictive.

270
00:25:07,880 --> 00:25:09,910
The way these companies
design these things

271
00:25:09,910 --> 00:25:12,010
is in order to pull you in and engage you.

272
00:25:13,180 --> 00:25:16,820
They want to become essentially
a slot machine of attention.

273
00:25:18,600 --> 00:25:21,770
So you're always paying attention,
you're always jacked into the matrix,

274
00:25:21,770 --> 00:25:23,520
you're always checking.

275
00:25:26,580 --> 00:25:30,450
- When somebody controls what you read,
they also control what you think.

276
00:25:32,180 --> 00:25:34,610
You get more of what you've
seen before and liked before,

277
00:25:34,610 --> 00:25:37,890
because this gives more traffic
and that gives more ads,

278
00:25:39,410 --> 00:25:43,160
but it also locks you
into your echo chamber.

279
00:25:43,160 --> 00:25:46,350
And this is what leads
to this polarization that we see today.

280
00:25:46,460 --> 00:25:49,300
Jair Bolsonaro!

281
00:25:49,970 --> 00:25:52,590
- Jair Bolsonaro,
Brazil's right-wing

282
00:25:52,590 --> 00:25:56,000
populist candidate sometimes
likened to Donald Trump,

283
00:25:56,000 --> 00:25:58,640
winning the presidency Sunday
night in that country's

284
00:25:58,640 --> 00:26:01,840
most polarizing election in decades.

285
00:26:01,840 --> 00:26:02,840
- Bolsonaro!

286
00:26:04,160 --> 00:26:09,550
- What we are seeing around the world
is upheaval and polarization and conflict

287
00:26:10,770 --> 00:26:15,000
that is partially pushed by algorithms

288
00:26:15,000 --> 00:26:19,070
that's figured out that
political extremes,

289
00:26:19,070 --> 00:26:22,180
tribalism, and sort of
shouting for your team,

290
00:26:22,180 --> 00:26:25,290
and feeling good about it, is engaging.

291
00:26:30,420 --> 00:26:33,150
- Social media may
be adding to the attention

292
00:26:33,150 --> 00:26:35,490
to hate crimes around the globe.

293
00:26:35,490 --> 00:26:38,120
- It's about how
people can become radicalized

294
00:26:38,120 --> 00:26:41,740
by living in the fever
swamps of the Internet.

295
00:26:41,740 --> 00:26:45,960
- So is this a key moment for the tech giants?
Are they now prepared to take responsibility

296
00:26:45,960 --> 00:26:48,840
as publishers for what
they share with the world?

297
00:26:49,790 --> 00:26:52,750
- If you deploy a
powerful potent technology

298
00:26:52,750 --> 00:26:56,670
at scale, and if you're talking
about Google and Facebook,

299
00:26:56,670 --> 00:26:59,530
you're deploying things
at scale of billions.

300
00:26:59,530 --> 00:27:02,770
If your artificial intelligence
is pushing polarization,

301
00:27:02,770 --> 00:27:05,090
you have global upheaval potentially.

302
00:27:05,720 --> 00:27:09,240
White lives matter!

303
00:27:09,320 --> 00:27:13,620
Black lives matter!

304
00:28:00,620 --> 00:28:04,040
- Artificial General Intelligence, AGI.

305
00:28:06,350 --> 00:28:08,320
Imagine your smartest friend,

306
00:28:09,600 --> 00:28:11,950
with 1,000 friends, just as smart,

307
00:28:14,680 --> 00:28:17,580
and then run them at a 1,000
times faster than real time.

308
00:28:17,580 --> 00:28:19,940
So it means that in every day of our time,

309
00:28:19,940 --> 00:28:22,510
they will do three years of thinking.

310
00:28:22,510 --> 00:28:25,520
Can you imagine how much you could do

311
00:28:26,580 --> 00:28:31,480
if, for every day, you could
do three years' worth of work?

312
00:28:52,440 --> 00:28:55,720
It wouldn't be an unfair comparison to say

313
00:28:55,720 --> 00:28:59,780
that what we have right now
is even more exciting than

314
00:28:59,780 --> 00:29:02,510
the quantum physicists of
the early 20th century.

315
00:29:02,510 --> 00:29:04,240
They discovered nuclear power.

316
00:29:05,740 --> 00:29:08,380
I feel extremely lucky to
be taking part in this.

317
00:29:15,310 --> 00:29:18,820
Many machine learning experts,
who are very knowledgeable and experienced,

318
00:29:18,820 --> 00:29:20,820
have a lot of skepticism about AGI.

319
00:29:22,350 --> 00:29:25,900
About when it would happen,
and about whether it could happen at all.

320
00:29:31,460 --> 00:29:35,740
But right now, this is something that just
not that many people have realized yet.

321
00:29:36,500 --> 00:29:41,240
That the speed of computers,
for neural networks, for AI,

322
00:29:41,240 --> 00:29:45,240
are going to become maybe
100,000 times faster

323
00:29:45,240 --> 00:29:46,980
in a small number of years.

324
00:29:49,330 --> 00:29:52,100
The entire hardware
industry for a long time

325
00:29:52,100 --> 00:29:54,660
didn't really know what to do next,

326
00:29:55,660 --> 00:30:00,900
but with artificial neural networks,
now that they actually work,

327
00:30:00,900 --> 00:30:03,420
you have a reason to build huge computers.

328
00:30:04,530 --> 00:30:06,930
You can build a brain in
silicon, it's possible.

329
00:30:14,450 --> 00:30:18,710
The very first AGIs
will be basically very,

330
00:30:18,710 --> 00:30:22,850
very large data centers
packed with specialized

331
00:30:22,850 --> 00:30:25,660
neural network processors
working in parallel.

332
00:30:28,070 --> 00:30:30,920
Compact, hot, power hungry package,

333
00:30:32,140 --> 00:30:35,540
consuming like 10 million
homes' worth of energy.

334
00:30:54,140 --> 00:30:55,640
A roast beef sandwich.

335
00:30:55,640 --> 00:30:58,290
Yeah, something slightly different.

336
00:30:58,290 --> 00:30:59,200
Just this once.

337
00:31:04,060 --> 00:31:06,260
Even the very first AGIs

338
00:31:06,260 --> 00:31:09,060
will be dramatically
more capable than humans.

339
00:31:10,970 --> 00:31:14,730
Humans will no longer be
economically useful for nearly any task.

340
00:31:16,200 --> 00:31:17,880
Why would you want to hire a human,

341
00:31:17,880 --> 00:31:21,980
if you could just get a computer that's going to
do it much better and much more cheaply?

342
00:31:28,900 --> 00:31:31,020
AGI is going to be like, without question,

343
00:31:31,880 --> 00:31:34,660
the most important
technology in the history

344
00:31:34,660 --> 00:31:36,600
of the planet by a huge margin.

345
00:31:39,410 --> 00:31:42,550
It's going to be bigger
than electricity, nuclear,

346
00:31:42,550 --> 00:31:44,140
and the Internet combined.

347
00:31:45,740 --> 00:31:47,620
In fact, you could say
that the whole purpose

348
00:31:47,620 --> 00:31:49,660
of all human science, the
purpose of computer science,

349
00:31:49,660 --> 00:31:52,550
the End Game, this is the
End Game, to build this.

350
00:31:52,550 --> 00:31:54,130
And it's going to be built.

351
00:31:54,130 --> 00:31:56,000
It's going to be a new life form.

352
00:31:56,000 --> 00:31:57,090
It's going to be...

353
00:31:59,190 --> 00:32:00,740
It's going to make us obsolete.

354
00:32:22,070 --> 00:32:24,520
- European manufacturers
know the Americans

355
00:32:24,520 --> 00:32:27,460
have invested heavily in
the necessary hardware.

356
00:32:27,460 --> 00:32:29,780
- Step into a
brave new world of power,

357
00:32:29,780 --> 00:32:31,630
performance and productivity.

358
00:32:32,360 --> 00:32:35,480
- All of the images you are
about to see on the large screen

359
00:32:35,480 --> 00:32:39,030
will be generated by
what's in that Macintosh.

360
00:32:39,760 --> 00:32:42,210
- It's my honor and
privilege to introduce to you

361
00:32:42,210 --> 00:32:44,700
the Windows 95 Development Team.

362
00:32:45,640 --> 00:32:49,040
- Human physical labor has
been mostly obsolete for

363
00:32:49,040 --> 00:32:50,620
getting on for a century.

364
00:32:51,390 --> 00:32:55,300
Routine human mental labor
is rapidly becoming obsolete

365
00:32:55,300 --> 00:32:58,980
and that's why we're seeing a lot of
the middle class jobs disappearing.

366
00:33:01,010 --> 00:33:02,340
- Every once in a while,

367
00:33:02,340 --> 00:33:06,370
a revolutionary product comes
along that changes everything.

368
00:33:06,370 --> 00:33:09,190
Today, Apple is reinventing the phone.

369
00:33:20,730 --> 00:33:24,270
- Machine intelligence
is already all around us.

370
00:33:24,270 --> 00:33:27,620
The list of things that we humans
can do better than machines

371
00:33:27,620 --> 00:33:29,600
is actually
shrinking pretty fast.

372
00:33:35,730 --> 00:33:37,400
- Driverless cars are great.

373
00:33:37,400 --> 00:33:40,010
They probably will reduce accidents.

374
00:33:40,010 --> 00:33:43,670
Except, alongside with
that, in the United States,

375
00:33:43,670 --> 00:33:46,410
you're going to lose 10 million jobs.

376
00:33:46,480 --> 00:33:49,980
What are you going to do with
10 million unemployed people?

377
00:33:54,900 --> 00:33:58,660
- The risk for social
conflict and tensions,

378
00:33:58,660 --> 00:34:02,080
if you exacerbate inequalities,
is very, very high.

379
00:34:11,560 --> 00:34:13,870
- AGI can, by definition,

380
00:34:13,870 --> 00:34:16,700
do all jobs better than we can do.

381
00:34:16,700 --> 00:34:18,610
People who are saying,
"Oh, there will always be jobs

382
00:34:18,610 --> 00:34:21,120
"that humans can do better
than machines," are simply

383
00:34:21,120 --> 00:34:24,180
betting against science and
saying there will never be AGI.

384
00:34:30,860 --> 00:34:33,630
- What we are seeing
now is like a train hurtling

385
00:34:33,630 --> 00:34:37,880
down a dark tunnel at
breakneck speed and it looks like

386
00:34:37,880 --> 00:34:39,660
we're sleeping at the wheel.

387
00:35:29,170 --> 00:35:34,710
- A large fraction of the digital footprints
we're leaving behind are digital images.

388
00:35:35,690 --> 00:35:39,340
And specifically, what's really
interesting to me as a psychologist

389
00:35:39,340 --> 00:35:41,470
are digital images of our faces.

390
00:35:44,500 --> 00:35:47,260
Here you can see the difference
in the facial outline

391
00:35:47,260 --> 00:35:50,130
of an average gay and
an average straight face.

392
00:35:50,130 --> 00:35:52,660
And you can see that straight men

393
00:35:52,660 --> 00:35:55,380
have slightly broader jaws.

394
00:35:55,680 --> 00:36:00,580
Gay women have slightly larger jaws,
compared with straight women.

395
00:36:02,510 --> 00:36:05,670
Computer algorithms can
reveal our political views

396
00:36:05,670 --> 00:36:08,280
or sexual orientation, or intelligence,

397
00:36:08,280 --> 00:36:11,120
just based on the picture of our faces.

398
00:36:12,070 --> 00:36:16,760
Even a human brain can distinguish between
gay and straight men with some accuracy.

399
00:36:16,920 --> 00:36:21,700
Now it turns out that the computer
can do it with much higher accuracy.

400
00:36:21,700 --> 00:36:25,200
What you're seeing here is an accuracy of

401
00:36:25,200 --> 00:36:29,410
off-the-shelf facial recognition software.

402
00:36:29,410 --> 00:36:31,640
This is terrible news

403
00:36:31,640 --> 00:36:34,320
for gay men and women
all around the world.

404
00:36:34,320 --> 00:36:35,680
And not only gay men and women,

405
00:36:35,680 --> 00:36:38,300
because the same algorithms
can be used to detect other

406
00:36:38,300 --> 00:36:42,350
intimate traits, think being
a member of the opposition,

407
00:36:42,350 --> 00:36:45,090
or being a liberal, or being an atheist.

408
00:36:46,850 --> 00:36:50,070
Being an atheist is
also punishable by death

409
00:36:50,070 --> 00:36:52,610
in Saudi Arabia, for instance.

410
00:36:59,780 --> 00:37:04,440
My mission as an academic is to
warn people about the dangers of algorithms

411
00:37:04,440 --> 00:37:08,290
being able to reveal our intimate traits.

412
00:37:09,780 --> 00:37:14,060
The problem is that when
people receive bad news,

413
00:37:14,060 --> 00:37:16,260
they very often choose to dismiss them.

414
00:37:17,810 --> 00:37:22,250
Well, it's a bit scary when you start receiving
death threats from one day to another,

415
00:37:22,250 --> 00:37:24,830
and I've received quite a
few death threats, -

416
00:37:25,910 --> 00:37:30,870
-but as a scientist, I have to
basically show what is possible.

417
00:37:33,590 --> 00:37:36,900
So what I'm really interested
in now is to try to see

418
00:37:36,900 --> 00:37:41,080
whether we can predict other
traits from people's faces.

419
00:37:46,270 --> 00:37:48,580
Now, if you can detect
depression from a face,

420
00:37:48,580 --> 00:37:53,580
or suicidal thoughts, maybe a CCTV system

421
00:37:53,690 --> 00:37:56,970
on the train station can save some lives.

422
00:37:59,130 --> 00:38:03,830
What if we could predict that someone
is more prone to commit a crime?

423
00:38:04,960 --> 00:38:07,150
You probably had a school counselor,

424
00:38:07,150 --> 00:38:10,380
a psychologist hired
there to identify children

425
00:38:10,380 --> 00:38:14,830
that potentially may have
some behavioral problems.

426
00:38:17,330 --> 00:38:20,080
So now imagine if you could
predict with high accuracy

427
00:38:20,080 --> 00:38:22,590
that someone is likely to
commit a crime in the future

428
00:38:22,590 --> 00:38:24,780
from the language use, from the face,

429
00:38:24,780 --> 00:38:27,580
from the facial expressions,
from the likes on Facebook.

430
00:38:32,310 --> 00:38:35,210
I'm not developing new
methods, I'm just describing

431
00:38:35,210 --> 00:38:38,890
something or testing something
in an academic environment.

432
00:38:40,590 --> 00:38:42,790
But there obviously is a chance that,

433
00:38:42,790 --> 00:38:47,790
while warning people against
risks of new technologies,

434
00:38:47,960 --> 00:38:50,560
I may also give some people new ideas.

435
00:39:11,140 --> 00:39:13,830
- We haven't yet seen
the future in terms of

436
00:39:13,830 --> 00:39:18,780
the ways in which the
new data-driven society

437
00:39:18,780 --> 00:39:21,380
is going to really evolve.

438
00:39:23,540 --> 00:39:26,740
The tech companies want
to get every possible bit

439
00:39:26,740 --> 00:39:30,170
of information that they
can collect on everyone

440
00:39:30,170 --> 00:39:31,690
to facilitate business.

441
00:39:33,470 --> 00:39:37,090
The police and the military
want to do the same thing

442
00:39:37,090 --> 00:39:38,830
to facilitate security.

443
00:39:41,960 --> 00:39:46,440
The interests that the two
have in common are immense,

444
00:39:46,440 --> 00:39:51,220
and so the extent of collaboration
between what you might

445
00:39:51,220 --> 00:39:56,820
call the Military-Tech Complex
is growing dramatically.

446
00:40:00,400 --> 00:40:03,010
- The CIA, for a very long time,

447
00:40:03,010 --> 00:40:06,120
has maintained a close
connection with Silicon Valley.

448
00:40:07,110 --> 00:40:10,270
Their venture capital
firm known as In-Q-Tel,

449
00:40:10,270 --> 00:40:13,870
makes seed investments to
start-up companies developing

450
00:40:13,870 --> 00:40:17,490
breakthrough technology that
the CIA hopes to deploy.

451
00:40:18,660 --> 00:40:22,100
Palantir, the big data analytics firm,

452
00:40:22,100 --> 00:40:25,100
one of their first seed
investments was from In-Q-Tel.

453
00:40:28,950 --> 00:40:31,780
- In-Q-Tel has struck gold in Palantir

454
00:40:31,780 --> 00:40:35,990
in helping to create a private vendor

455
00:40:35,990 --> 00:40:40,850
that has intelligence and
artificial intelligence

456
00:40:40,850 --> 00:40:44,460
capabilities that the government
can't even compete with.

457
00:40:46,370 --> 00:40:48,720
- Good evening, I'm Peter Thiel.

458
00:40:49,740 --> 00:40:54,210
I'm not a politician, but
neither is Donald Trump.

459
00:40:54,210 --> 00:40:58,620
He is a builder and it's
time to rebuild America.

460
00:41:01,280 --> 00:41:03,940
- Peter Thiel,
the founder of Palantir,

461
00:41:03,940 --> 00:41:06,680
was a Donald Trump transition advisor

462
00:41:06,680 --> 00:41:09,180
and a close friend and donor.

463
00:41:11,080 --> 00:41:13,700
Trump was elected largely on the promise

464
00:41:13,700 --> 00:41:17,560
to deport millions of immigrants.

465
00:41:17,560 --> 00:41:22,240
The only way you can do that
is with a lot of intelligence

466
00:41:22,240 --> 00:41:25,010
and that's where Palantir comes in.

467
00:41:28,680 --> 00:41:33,340
They ingest huge troves
of data, which include,

468
00:41:33,340 --> 00:41:37,370
where you live, where
you work, who you know,

469
00:41:37,370 --> 00:41:40,930
who your neighbors are,
who your family is,

470
00:41:40,930 --> 00:41:44,480
where you have visited, where you stay,

471
00:41:44,480 --> 00:41:46,320
your social media profile.

472
00:41:49,250 --> 00:41:53,240
Palantir gets all of that
and is remarkably good

473
00:41:53,240 --> 00:41:58,240
at structuring it in a way
that helps law enforcement,

474
00:41:58,460 --> 00:42:02,450
immigration authorities
or intelligence agencies

475
00:42:02,450 --> 00:42:06,210
of any kind, track you, find you,

476
00:42:06,210 --> 00:42:09,550
and learn everything there
is to know about you.

477
00:42:48,430 --> 00:42:51,040
- We're putting AI in
charge now of evermore

478
00:42:51,040 --> 00:42:53,860
important decisions that
affect people's lives.

479
00:42:54,810 --> 00:42:58,050
Old-school AI used to have
its intelligence programmed in

480
00:42:58,050 --> 00:43:01,420
by humans who understood
how it worked, but today,

481
00:43:01,420 --> 00:43:04,080
powerful AI systems have
just learned for themselves,

482
00:43:04,080 --> 00:43:07,480
and we have no clue really how they work,

483
00:43:07,480 --> 00:43:09,680
which makes it really hard to trust them.

484
00:43:14,270 --> 00:43:17,820
- This isn't some futuristic
technology, this is now.

485
00:43:19,470 --> 00:43:23,220
AI might help determine
where a fire department

486
00:43:23,220 --> 00:43:25,900
is built in a community
or where a school is built.

487
00:43:25,900 --> 00:43:28,380
It might decide whether you get bail,

488
00:43:28,380 --> 00:43:30,680
or whether you stay in jail.

489
00:43:30,680 --> 00:43:32,930
It might decide where the
police are going to be.

490
00:43:32,930 --> 00:43:37,140
It might decide whether you're going to be
under additional police scrutiny.

491
00:43:43,340 --> 00:43:46,140
- It's popular now in the US
to do predictive policing.

492
00:43:46,980 --> 00:43:50,900
So what they do is they use an algorithm
to figure out where crime will be,

493
00:43:51,760 --> 00:43:55,240
- and they use that to tell where
we should send police officers.

494
00:43:56,430 --> 00:43:59,420
So that's based on a
measurement of crime rate.

495
00:44:00,640 --> 00:44:02,330
So we know that there is bias.

496
00:44:02,330 --> 00:44:05,090
Black people and Hispanic
people are pulled over,

497
00:44:05,090 --> 00:44:07,180
and stopped by the police
officers more frequently

498
00:44:07,180 --> 00:44:09,820
than white people are, so we
have this biased data going in,

499
00:44:09,820 --> 00:44:11,820
and then what happens
is you use that to say,

500
00:44:11,820 --> 00:44:13,640
"Oh, here's where the cops should go."

501
00:44:13,640 --> 00:44:17,320
Well, the cops go to those neighborhoods,
and guess what they do, they arrest people.

502
00:44:17,680 --> 00:44:21,160
And then it feeds back
biased data into the system,

503
00:44:21,160 --> 00:44:23,060
and that's called a feedback loop.

504
00:44:35,990 --> 00:44:40,650
- Predictive policing
leads at the extremes

505
00:44:41,590 --> 00:44:45,910
to experts saying, "Show me your baby,

506
00:44:45,910 --> 00:44:48,860
"and I will tell you whether
she's going to be a criminal."

507
00:44:51,300 --> 00:44:55,780
Now that we can predict it,
we're going to then surveil

508
00:44:55,780 --> 00:45:01,100
those kids much more closely
and we're going to jump on them

509
00:45:01,100 --> 00:45:03,700
at the first sign of a problem.

510
00:45:03,700 --> 00:45:06,700
And that's going to make
for more effective policing.

511
00:45:07,000 --> 00:45:11,250
It does, but it's going to
make for a really grim society

512
00:45:11,250 --> 00:45:16,250
and it's reinforcing
dramatically existing injustices.

513
00:45:22,960 --> 00:45:27,810
- Imagine a world in which
networks of CCTV cameras,

514
00:45:27,810 --> 00:45:30,930
drone surveillance
cameras, have sophisticated

515
00:45:30,930 --> 00:45:34,440
face recognition technologies
and are connected

516
00:45:34,440 --> 00:45:37,020
to other government
surveillance databases.

517
00:45:38,080 --> 00:45:41,190
We will have the
technology in place to have

518
00:45:41,190 --> 00:45:45,690
all of our movements comprehensively
tracked and recorded.

519
00:45:47,680 --> 00:45:50,330
What that also means is that we will have

520
00:45:50,330 --> 00:45:52,940
created a surveillance time machine

521
00:45:52,940 --> 00:45:56,620
that will allow governments
and powerful corporations

522
00:45:56,620 --> 00:45:58,710
to essentially hit rewind on our lives.

523
00:45:58,710 --> 00:46:01,780
We might not be under any suspicion now

524
00:46:01,780 --> 00:46:03,860
and five years from now,
they might want to know

525
00:46:03,860 --> 00:46:08,100
more about us, and can
then recreate granularly

526
00:46:08,100 --> 00:46:10,260
everything we've done,
everyone we've seen,

527
00:46:10,260 --> 00:46:13,050
everyone we've been around
over that entire period.

528
00:46:15,820 --> 00:46:19,320
That's an extraordinary amount of power

529
00:46:19,320 --> 00:46:21,660
for us to seed to anyone.

530
00:46:22,910 --> 00:46:25,370
And it's a world that I
think has been difficult

531
00:46:25,370 --> 00:46:29,180
for people to imagine,
but we've already built

532
00:46:29,180 --> 00:46:31,660
the architecture to enable that.

533
00:47:07,140 --> 00:47:10,290
- I'm a political reporter
and I'm very interested

534
00:47:10,290 --> 00:47:14,670
in the ways powerful industries
use their political power

535
00:47:14,670 --> 00:47:17,180
to influence the public policy process.

536
00:47:21,000 --> 00:47:24,420
The large tech companies and
their lobbyists get together

537
00:47:24,420 --> 00:47:27,530
behind closed doors and
are able to craft policies

538
00:47:27,530 --> 00:47:29,340
that we all have to live under.

539
00:47:30,790 --> 00:47:35,780
That's true for surveillance policies,
for policies in terms of data collection,

540
00:47:35,780 --> 00:47:40,540
but also increasingly important when it
comes to military and foreign policy.

541
00:47:43,930 --> 00:47:50,220
Starting in 2016, the Defense Department
formed the Defense Innovation Board.

542
00:47:50,220 --> 00:47:54,010
That's a special body created
to bring top tech executives

543
00:47:54,010 --> 00:47:56,420
into closer contact with the military.

544
00:47:59,140 --> 00:48:01,750
Eric Schmidt, former chairman of Alphabet,

545
00:48:01,750 --> 00:48:03,380
the parent company of Google,

546
00:48:03,380 --> 00:48:07,240
became the chairman of the
Defense Innovation Board,

547
00:48:07,240 --> 00:48:09,930
and one of their first
priorities was to say,

548
00:48:09,930 --> 00:48:13,850
"We need more artificial intelligence
integrated into the military."

549
00:48:15,930 --> 00:48:19,190
- I've worked with a group
of volunteers over the

550
00:48:19,190 --> 00:48:22,150
last couple of years to take
a look at innovation in the

551
00:48:22,150 --> 00:48:26,780
overall military, and my summary
conclusion is that we have

552
00:48:26,780 --> 00:48:30,460
fantastic people who are
trapped in a very bad system.

553
00:48:33,290 --> 00:48:35,700
- From the Department of
Defense's perspective,

554
00:48:35,700 --> 00:48:37,700
where I really started
to get interested in it

555
00:48:37,700 --> 00:48:40,980
was when we started thinking
about Unmanned Systems and

556
00:48:40,980 --> 00:48:45,980
how robotic and unmanned systems
would start to change war.

557
00:48:46,160 --> 00:48:50,320
The smarter you made the
Unmanned Systems and robots,

558
00:48:50,320 --> 00:48:53,570
the more powerful you might
be able to make your military.

559
00:48:55,540 --> 00:48:57,240
- Under Secretary of Defense,

560
00:48:57,240 --> 00:49:00,420
Robert Work put together
a major memo known as

561
00:49:00,420 --> 00:49:03,680
the Algorithmic Warfare
Cross-Functional Team,

562
00:49:03,680 --> 00:49:05,540
better known as Project Maven.

563
00:49:07,830 --> 00:49:10,760
Eric Schmidt gave a number of
speeches and media appearances

564
00:49:10,760 --> 00:49:14,310
where he said this effort
was designed to increase fuel

565
00:49:14,310 --> 00:49:18,240
efficiency in the Air Force,
to help with the logistics,

566
00:49:18,240 --> 00:49:21,300
but behind closed doors there
was another parallel effort.

567
00:49:26,710 --> 00:49:29,760
Late in 2017 as part of Project Maven,

568
00:49:29,760 --> 00:49:33,710
Google, Eric Schmidt's firm,
was tasked to secretly work

569
00:49:33,710 --> 00:49:36,100
on another part of Project Maven,

570
00:49:36,100 --> 00:49:41,480
and that was to take the vast
volumes of image data vacuumed up

571
00:49:41,480 --> 00:49:47,060
by drones operating in Iraq
and Afghanistan and to teach an AI

572
00:49:47,060 --> 00:49:49,690
to quickly identify
targets on the battlefield.

573
00:49:52,600 --> 00:49:58,470
- We have a sensor and the sensor
can do full motion video of an entire city.

574
00:49:58,470 --> 00:50:01,690
And we would have three
seven-person teams working

575
00:50:01,690 --> 00:50:06,360
constantly and they could
process 15% of the information.

576
00:50:06,360 --> 00:50:08,950
The other 85% of the
information was just left

577
00:50:08,950 --> 00:50:14,040
on the cutting room floor, so we said,
"Hey, AI and machine learning

578
00:50:14,040 --> 00:50:17,810
"would help us process
100% of the information."

579
00:50:25,380 --> 00:50:28,760
- Google has long had
the motto, "Don't be evil."

580
00:50:28,760 --> 00:50:30,630
They have created a public image

581
00:50:30,630 --> 00:50:35,080
that they are devoted
to public transparency.

582
00:50:35,080 --> 00:50:39,200
But for Google to slowly
transform into a defense contractor,

583
00:50:39,200 --> 00:50:41,720
they maintained
the utmost secrecy.

584
00:50:41,720 --> 00:50:45,280
And you had Google entering into
this contract with most of the employees,

585
00:50:45,280 --> 00:50:49,020
even employees who were working on
the program completely left in the dark.

586
00:51:01,840 --> 00:51:05,050
- Usually within Google,
anyone in the company

587
00:51:05,050 --> 00:51:08,100
is allowed to know about any
other project that's happening

588
00:51:08,100 --> 00:51:09,800
in some other part of the company.

589
00:51:11,180 --> 00:51:14,300
With Project Maven, the fact
that it was kept secret,

590
00:51:14,300 --> 00:51:18,740
I think was alarming to people
because that's not the norm at Google.

591
00:51:20,620 --> 00:51:22,940
- When this story was first revealed,

592
00:51:22,940 --> 00:51:25,540
it set off a firestorm within Google.

593
00:51:25,540 --> 00:51:28,420
You had a number of employees
quitting in protests,

594
00:51:28,420 --> 00:51:31,900
others signing a petition
objecting to this work.

595
00:51:34,130 --> 00:51:37,680
- You have to really say,
"I don't want to be part of this anymore."

596
00:51:38,820 --> 00:51:41,750
There are companies
called defense contractors

597
00:51:41,750 --> 00:51:45,830
and Google should just not
be one of those companies

598
00:51:45,830 --> 00:51:50,040
because people need to trust
Google for Google to work.

599
00:51:52,070 --> 00:51:55,710
- Good morning and welcome to Google I/O.

600
00:51:57,310 --> 00:52:00,160
- We've seen emails that
show that Google simply

601
00:52:00,160 --> 00:52:03,350
continued to mislead their
employees that the drone

602
00:52:03,350 --> 00:52:07,390
targeting program was only a
minor effort that could at most

603
00:52:07,390 --> 00:52:11,170
be worth $9 million to the firm,
which is drops in the bucket

604
00:52:11,170 --> 00:52:13,540
for a gigantic company like Google.

605
00:52:14,400 --> 00:52:17,300
But from internal emails that we obtained,

606
00:52:17,300 --> 00:52:21,530
Google was expecting Project
Maven would ramp up to as much

607
00:52:21,530 --> 00:52:26,530
as $250 million, and that this
entire effort would provide

608
00:52:26,630 --> 00:52:29,900
Google with Special Defense
Department certification to make

609
00:52:29,900 --> 00:52:32,660
them available for even
bigger defense contracts,

610
00:52:32,660 --> 00:52:34,980
some worth as much as $10 billion.

611
00:52:45,710 --> 00:52:49,750
The pressure for Google to
compete for military contracts

612
00:52:49,750 --> 00:52:53,780
has come at a time when its competitors
are also shifting their culture.

613
00:52:55,850 --> 00:53:00,070
Amazon, similarly pitching the
military and law enforcement.

614
00:53:00,070 --> 00:53:02,280
IBM and other leading firms,

615
00:53:02,280 --> 00:53:04,890
they're pitching law
enforcement and military.

616
00:53:05,840 --> 00:53:09,420
To stay competitive, Google
has slowly transformed.

617
00:53:15,150 --> 00:53:18,910
- The Defense Science
Board said of all of the

618
00:53:18,910 --> 00:53:22,170
technological advances that
are happening right now,

619
00:53:22,170 --> 00:53:26,780
the single most important thing
was artificial intelligence

620
00:53:26,780 --> 00:53:30,780
and the autonomous operations
that it would lead.

621
00:53:30,780 --> 00:53:32,330
Are we investing enough?

622
00:53:37,810 --> 00:53:41,220
- Once we develop what are known as

623
00:53:41,220 --> 00:53:45,820
autonomous lethal weapons, in other words,

624
00:53:45,820 --> 00:53:51,510
weapons that are not controlled at all,
they are genuinely autonomous,

625
00:53:51,510 --> 00:53:54,000
you've only got to get
a president who says,

626
00:53:54,000 --> 00:53:56,410
"The hell with international law,
we've got these weapons.

627
00:53:56,410 --> 00:53:58,560
"We're going to do what
we want with them."

628
00:54:02,540 --> 00:54:03,960
- We're very close.

629
00:54:03,960 --> 00:54:06,340
When you have the hardware
already set up

630
00:54:06,340 --> 00:54:10,360
and all you have to do is flip a switch
to make it fully autonomous,

631
00:54:10,360 --> 00:54:13,240
what is it there that's
stopping you from doing that?

632
00:54:14,670 --> 00:54:19,080
There's something really to be feared
in war at machine speed.

633
00:54:19,930 --> 00:54:24,370
What if you're a machine and you've run
millions and millions of different war scenarios

634
00:54:24,370 --> 00:54:28,060
and you have a team of drones and
you've delegated control to half of them,

635
00:54:28,060 --> 00:54:30,790
and you're collaborating in real time?

636
00:54:30,790 --> 00:54:35,600
What happens when that swarm of drones
is tasked with engaging a city?

637
00:54:37,490 --> 00:54:39,870
How will they take over that city?

638
00:54:39,870 --> 00:54:42,760
The answer is we won't
know until it happens.

639
00:54:50,020 --> 00:54:53,910
- We do not want an AI system to decide

640
00:54:53,910 --> 00:54:56,180
what human it would attack,

641
00:54:56,180 --> 00:54:59,500
but we're going up against
authoritarian competitors.

642
00:54:59,500 --> 00:55:02,450
So in my view, an authoritarian regime

643
00:55:02,450 --> 00:55:05,710
will have less problem
delegating authority

644
00:55:05,710 --> 00:55:08,460
to a machine to make lethal decisions.

645
00:55:09,410 --> 00:55:12,660
So how that plays out remains to be seen.

646
00:55:37,270 --> 00:55:41,020
- Almost the gift of AI
now is that it will force us

647
00:55:41,020 --> 00:55:44,410
collectively to think
through at a very basic level,

648
00:55:44,410 --> 00:55:46,310
what does it mean to be human?

649
00:55:48,620 --> 00:55:50,510
What do I do as a human better

650
00:55:50,510 --> 00:55:52,970
than a certain
super smart machine can do?

651
00:55:56,300 --> 00:56:01,000
First, we create our technology
and then it recreates us.

652
00:56:01,000 --> 00:56:05,630
We need to make sure that we
don't miss some of the things

653
00:56:05,630 --> 00:56:07,520
that make us so beautiful human.

654
00:56:11,840 --> 00:56:14,380
- Once we build intelligent machines,

655
00:56:14,380 --> 00:56:16,920
the philosophical vocabulary
we have available to think

656
00:56:16,920 --> 00:56:20,680
about ourselves as human
increasingly fails us.

657
00:56:23,160 --> 00:56:25,950
If I ask you to write up a
list of all the terms you have

658
00:56:25,950 --> 00:56:28,960
available to describe yourself as human,

659
00:56:28,960 --> 00:56:31,100
there are not so many terms.

660
00:56:31,100 --> 00:56:38,140
Culture, history, sociality,
maybe politics, civilization,

661
00:56:38,820 --> 00:56:45,090
subjectivity, all of these
terms ground in two positions

662
00:56:45,670 --> 00:56:48,020
that humans are more than mere animals

663
00:56:49,000 --> 00:56:52,200
and that humans are
more than mere machines.

664
00:56:55,140 --> 00:56:59,290
But if machines truly
think there is a large set

665
00:56:59,290 --> 00:57:03,520
of key philosophical questions
in which what is at stake is:

666
00:57:04,880 --> 00:57:09,080
Who are we? What is our place in the world?
What is the world? How is it structured?

667
00:57:09,080 --> 00:57:12,190
Do the categories that we have relied on

668
00:57:12,190 --> 00:57:14,510
- Do they still work? Were they wrong?

669
00:57:19,500 --> 00:57:22,220
- Many people think of intelligence
as something mysterious

670
00:57:22,220 --> 00:57:26,190
that can only exist inside of
biological organisms, like us,

671
00:57:26,190 --> 00:57:29,260
but intelligence is all
about information processing.

672
00:57:30,280 --> 00:57:32,230
It doesn't matter whether
the intelligence is processed

673
00:57:32,230 --> 00:57:35,940
by carbon atoms inside of
cells and brains, and people,

674
00:57:35,940 --> 00:57:38,020
or by silicon atoms in computers.

675
00:57:40,700 --> 00:57:43,320
Part of the success of
AI recently has come

676
00:57:43,320 --> 00:57:47,540
from stealing great ideas from evolution.

677
00:57:47,540 --> 00:57:49,320
We noticed that the brain, for example,

678
00:57:49,320 --> 00:57:52,920
has all these neurons inside
connected in complicated ways.

679
00:57:52,920 --> 00:57:55,660
So we stole that idea and abstracted it

680
00:57:55,660 --> 00:57:58,350
into artificial neural
networks in computers,

681
00:57:59,330 --> 00:58:02,800
and that's what has revolutionized
machine intelligence.

682
00:58:07,690 --> 00:58:10,300
If we one day get Artificial
General Intelligence,

683
00:58:10,300 --> 00:58:14,330
then by definition, AI can
also do better the job of AI

684
00:58:14,330 --> 00:58:18,930
programming and that means
that further progress in making

685
00:58:18,930 --> 00:58:22,950
AI will be dominated not by
human programmers, but by AI.

686
00:58:25,450 --> 00:58:29,090
Recursively self-improving AI
could leave human intelligence

687
00:58:29,090 --> 00:58:32,990
far behind,
creating super intelligence.

688
00:58:34,970 --> 00:58:37,970
It's gonna be the last
invention we ever need to make,

689
00:58:37,970 --> 00:58:40,520
because it can then invent everything else

690
00:58:40,520 --> 00:58:42,010
much faster than we could.

691
00:59:54,040 --> 00:59:59,040
- There is a future that
we all need to talk about.

692
00:59:59,110 --> 01:00:02,430
Some of the fundamental
questions about the future

693
01:00:02,430 --> 01:00:06,280
of artificial intelligence,
not just where it's going,

694
01:00:06,280 --> 01:00:09,630
but what it means for society to go there.

695
01:00:10,930 --> 01:00:14,620
It is not what computers can do,

696
01:00:14,620 --> 01:00:17,590
but what computers should do.

697
01:00:17,590 --> 01:00:22,210
As the generation of people
that is bringing AI to the future,

698
01:00:22,210 --> 01:00:27,690
we are the generation that will
answer this question first and foremost.

699
01:00:34,570 --> 01:00:37,380
- We haven't created the
human-level thinking machine yet,

700
01:00:37,380 --> 01:00:39,410
but we get closer and closer.

701
01:00:41,100 --> 01:00:44,780
Maybe we'll get to human-level
AI in five years from now

702
01:00:44,780 --> 01:00:47,410
or maybe it'll take 50
or 100 years from now.

703
01:00:47,660 --> 01:00:51,540
It almost doesn't matter.
Like these are all really, really soon,

704
01:00:51,540 --> 01:00:56,060
in terms of the overall
history of humanity.

705
01:01:01,200 --> 01:01:02,180
Very nice.

706
01:01:15,750 --> 01:01:19,350
So, the AI field is
extremely international.

707
01:01:19,350 --> 01:01:23,790
China is up and coming and it's
starting to rival the US,

708
01:01:23,790 --> 01:01:26,940
Europe and Japan in terms of putting a lot

709
01:01:26,940 --> 01:01:29,770
of processing power behind AI

710
01:01:29,770 --> 01:01:33,120
and gathering a lot of
data to help AI learn.

711
01:01:35,960 --> 01:01:40,540
We have a young generation
of Chinese researchers now.

712
01:01:40,540 --> 01:01:43,910
Nobody knows where the next
revolution is going to come from.

713
01:01:50,120 --> 01:01:54,290
- China always wanted to become
the superpower in the world.

714
01:01:56,120 --> 01:01:59,410
The Chinese government thinks AI
gave them the chance to become

715
01:01:59,410 --> 01:02:03,940
one of the most advanced
technology wise, business wise.

716
01:02:04,190 --> 01:02:07,780
So the Chinese government look at
this as a huge opportunity.

717
01:02:09,140 --> 01:02:13,670
Like they've raised a flag
and said, "That's a good field.

718
01:02:13,670 --> 01:02:16,300
"The companies should jump into it."

719
01:02:16,300 --> 01:02:18,300
Then China's commercial world
and companies say,

720
01:02:18,300 --> 01:02:20,800
"Okay, the government
raised a flag, that's good.

721
01:02:20,800 --> 01:02:22,500
"Let's put the money into it."

722
01:02:23,900 --> 01:02:28,090
Chinese tech giants, like Baidu,
like Tencent and like AliBaba,

723
01:02:28,090 --> 01:02:31,800
they put a lot of the
investment into the AI field.

724
01:02:33,410 --> 01:02:36,740
So we see that China's AI
development is booming.

725
01:02:43,430 --> 01:02:47,370
- In China, everybody
has Alipay and WeChat pay,

726
01:02:47,370 --> 01:02:49,500
so mobile payment is everywhere.

727
01:02:50,850 --> 01:02:54,850
And with that, they can
do a lot of AI analysis

728
01:02:54,850 --> 01:02:59,340
to know like your spending
habits, your credit rating.

729
01:03:01,150 --> 01:03:06,100
Face recognition technology
is widely adopted in China,

730
01:03:06,100 --> 01:03:08,200
in airports and train stations.

731
01:03:09,040 --> 01:03:11,570
So, in the future, maybe
in just a few months,

732
01:03:11,570 --> 01:03:15,140
you don't need a paper
ticket to board a train.

733
01:03:15,140 --> 01:03:15,970
Only your face.

734
01:03:24,620 --> 01:03:29,690
- We generate the world's biggest platform
of facial recognition.

735
01:03:31,260 --> 01:03:37,300
We have 300,000 developers
using our platform.

736
01:03:38,330 --> 01:03:41,550
A lot of it is selfie camera apps.

737
01:03:41,550 --> 01:03:43,930
It makes you look more beautiful.

738
01:03:46,550 --> 01:03:49,780
There are millions and millions
of cameras in the world,

739
01:03:50,760 --> 01:03:54,880
each camera from my point
is a data generator.

740
01:03:58,820 --> 01:04:02,810
In a machine's eye, your face
will change into the features

741
01:04:02,810 --> 01:04:06,660
and it will turn your face
into a paragraph of code.

742
01:04:07,720 --> 01:04:11,980
So we can detect how old you
are, if you're male or female,

743
01:04:11,980 --> 01:04:13,440
and your emotions.

744
01:04:16,640 --> 01:04:20,110
Shopping is about what kind
of thing you are looking at.

745
01:04:20,110 --> 01:04:25,650
We can track your eyeballs,
so if you are focusing on some product,

746
01:04:25,650 --> 01:04:28,690
we can track that so that we can know

747
01:04:28,690 --> 01:04:32,120
which kind of people like
which kind of product.

748
01:04:42,450 --> 01:04:45,820
Our mission is to create a platform

749
01:04:45,950 --> 01:04:50,300
that will enable millions of AI
developers in China.

750
01:04:51,280 --> 01:04:58,060
We study all the data we can get.

751
01:05:00,440 --> 01:05:04,350
Not just user profiles,

752
01:05:04,350 --> 01:05:08,380
but what you are doing at the moment,

753
01:05:09,460 --> 01:05:12,060
your geographical location.

754
01:05:15,380 --> 01:05:23,580
This platform will be so valuable that we don't
even worry about profit now,

755
01:05:23,580 --> 01:05:27,660
because it is definitely there.

756
01:05:29,660 --> 01:05:34,420
China's social credit system is
just one of the applications.

757
01:05:45,990 --> 01:05:48,040
- The Chinese government is using multiple

758
01:05:48,040 --> 01:05:50,810
different kinds of
technologies, whether it's AI,

759
01:05:50,810 --> 01:05:53,650
whether it's big data
platforms, facial recognition,

760
01:05:53,650 --> 01:05:57,030
voice recognition, essentially to monitor

761
01:05:57,030 --> 01:05:58,800
what the population is doing.

762
01:06:01,860 --> 01:06:04,240
I think the Chinese
government has made very clear

763
01:06:04,240 --> 01:06:09,240
its intent to gather massive
amounts of data about people

764
01:06:09,600 --> 01:06:13,300
to socially engineer a
dissent-free society.

765
01:06:16,040 --> 01:06:19,060
The logic behind the Chinese government's

766
01:06:19,060 --> 01:06:23,180
social credit system,
it's to take the idea that

767
01:06:23,180 --> 01:06:27,930
whether you are credit
worthy for a financial loan

768
01:06:27,930 --> 01:06:31,860
and adding to it a very
political dimension to say,

769
01:06:31,860 --> 01:06:34,270
"Are you a trustworthy human being?

770
01:06:36,530 --> 01:06:40,270
"What you've said online, have you ever been
critical of the authorities?

771
01:06:40,270 --> 01:06:42,190
"Do you have a criminal record?"

772
01:06:43,720 --> 01:06:47,340
And all that information is
packaged up together to rate

773
01:06:47,340 --> 01:06:51,820
you in ways that if you have
performed well in their view,

774
01:06:51,820 --> 01:06:56,490
you'll have easier access to certain kinds
of state services or benefits.

775
01:06:57,790 --> 01:06:59,710
But if you haven't done very well,

776
01:06:59,710 --> 01:07:02,130
you are going to be
penalized or restricted.

777
01:07:05,940 --> 01:07:09,020
There's no way for people to
challenge those designations

778
01:07:09,020 --> 01:07:12,100
or, in some cases, even know that
they've been put in that category,

779
01:07:12,100 --> 01:07:17,990
and it's not until they try to access some kind
of state service or buy a plane ticket,

780
01:07:17,990 --> 01:07:20,460
or get a passport, or
enroll their kid in school,

781
01:07:20,460 --> 01:07:23,590
that they come to learn that they've
been labeled in this way,

782
01:07:23,590 --> 01:07:27,550
and that there are negative
consequences for them as a result.

783
01:07:44,970 --> 01:07:48,660
We've spent the better part
of the last one or two years

784
01:07:48,660 --> 01:07:53,180
looking at abuses of surveillance
technology across China,

785
01:07:53,180 --> 01:07:56,030
and a lot of that work
has taken us to Xinjiang,

786
01:07:57,580 --> 01:08:01,220
the Northwestern region of
China that has a more than half

787
01:08:01,220 --> 01:08:05,870
population of Turkic Muslims,
Uyghurs, Kazakhs and Hui.

788
01:08:08,430 --> 01:08:10,980
This is a region and a
population the Chinese government

789
01:08:10,980 --> 01:08:14,900
has long considered to be
politically suspect or disloyal.

790
01:08:17,580 --> 01:08:20,160
We came to find information
about what's called

791
01:08:20,160 --> 01:08:23,130
the Integrated Joint Operations Platform,

792
01:08:23,130 --> 01:08:27,190
which is a predictive policing
program and that's one

793
01:08:27,190 --> 01:08:30,650
of the programs that has been
spitting out lists of names

794
01:08:30,650 --> 01:08:33,560
of people to be subjected
to political re-education.

795
01:08:39,090 --> 01:08:42,770
A number of our interviewees
for the report we just released

796
01:08:42,770 --> 01:08:46,110
about the political education
camps in Xinjiang just

797
01:08:46,110 --> 01:08:50,380
painted an extraordinary
portrait of a surveillance state.

798
01:08:53,460 --> 01:08:56,380
A region awash in surveillance cameras

799
01:08:56,380 --> 01:09:00,600
for facial recognition purposes,
checkpoints, body scanners,

800
01:09:00,600 --> 01:09:04,030
QR codes outside people's homes.

801
01:09:05,660 --> 01:09:10,690
Yeah, it really is the stuff of dystopian
movies that we've all gone to and thought,

802
01:09:10,690 --> 01:09:13,160
"Wow, that would be a
creepy world to live in."

803
01:09:13,160 --> 01:09:16,510
Yeah, well, 13 million
Turkic Muslims in China

804
01:09:16,510 --> 01:09:18,530
are living in that reality right now.

805
01:09:30,840 --> 01:09:33,060
- The Intercept reports
that Google is planning to

806
01:09:33,060 --> 01:09:36,490
launch a censored version of
its search engine in China.

807
01:09:36,490 --> 01:09:38,730
- Google's search
for new markets leads it

808
01:09:38,730 --> 01:09:42,170
to China, despite Beijing's
rules on censorship.

809
01:09:42,170 --> 01:09:44,080
- Tell us more
about why you felt it was

810
01:09:44,080 --> 01:09:46,650
your ethical responsibility to resign,

811
01:09:46,650 --> 01:09:51,060
because you talk about being complicit in
censorship and oppression, and surveillance.

812
01:09:51,060 --> 01:09:54,220
- There is a Chinese
venture company that has to be

813
01:09:54,220 --> 01:09:56,230
set up for Google to operate in China.

814
01:09:56,230 --> 01:09:58,920
And the question is, to what
degree did they get to control

815
01:09:58,920 --> 01:10:01,970
the blacklist and to what
degree would they have just

816
01:10:01,970 --> 01:10:05,220
unfettered access to
surveilling Chinese citizens?

817
01:10:05,220 --> 01:10:07,470
And the fact that Google
refuses to respond

818
01:10:07,470 --> 01:10:09,250
to human rights organizations on this,

819
01:10:09,250 --> 01:10:12,060
I think should be extremely
disturbing to everyone.

820
01:10:16,640 --> 01:10:21,120
Due to my conviction that dissent is
fundamental to functioning democracies

821
01:10:21,120 --> 01:10:25,560
and forced to resign in order to avoid
contributing to or profiting from the erosion

822
01:10:25,560 --> 01:10:27,510
of protections for dissidents.

823
01:10:28,560 --> 01:10:30,920
The UN is currently
reporting that between

824
01:10:30,920 --> 01:10:34,190
200,000 and one million
Uyghurs have been disappeared

825
01:10:34,190 --> 01:10:36,520
into re-education camps.

826
01:10:36,520 --> 01:10:39,290
And there is a serious argument
that Google would be complicit

827
01:10:39,290 --> 01:10:42,460
should it launch a surveilled
version of search in China.

828
01:10:45,180 --> 01:10:51,380
Dragonfly is a project meant
to launch search in China under

829
01:10:51,390 --> 01:10:55,810
Chinese government regulations,
which include censoring

830
01:10:55,810 --> 01:10:59,510
sensitive content, basic
queries on human rights,

831
01:10:59,510 --> 01:11:03,210
information about political
representatives is blocked,

832
01:11:03,210 --> 01:11:07,080
information about student
protests is blocked.

833
01:11:07,080 --> 01:11:09,180
And that's one small part of it.

834
01:11:09,180 --> 01:11:12,250
Perhaps a deeper concern is
the surveillance side of this.

835
01:11:16,070 --> 01:11:19,580
When I raised the issue with my managers,
with my colleagues,

836
01:11:19,580 --> 01:11:23,370
there was a lot of concern, but everyone
just said, "I don't know anything."

837
01:11:27,760 --> 01:11:30,200
And then when there was a meeting finally,

838
01:11:30,200 --> 01:11:35,080
there was essentially no addressing
the serious concerns associated with it.

839
01:11:37,010 --> 01:11:39,790
So then I filed my formal resignation,

840
01:11:39,790 --> 01:11:42,950
not just to my manager,
but I actually distributed it company-wide.

841
01:11:42,950 --> 01:11:45,440
And that's the letter
that I was reading from.

842
01:11:50,360 --> 01:11:55,960
Personally, I haven't slept well.
I've had pretty horrific headaches,

843
01:11:55,960 --> 01:11:58,520
wake up in the middle of
the night just sweating.

844
01:12:00,640 --> 01:12:03,340
With that said, what I
found since speaking out

845
01:12:03,340 --> 01:12:07,930
is just how positive the global
response to this has been.

846
01:12:10,350 --> 01:12:13,910
Engineers should demand
to know what the uses

847
01:12:13,910 --> 01:12:16,280
of their technical contributions are

848
01:12:16,280 --> 01:12:19,340
and to have a seat at the table
in those ethical decisions.

849
01:12:27,020 --> 01:12:29,590
Most citizens don't really
understand what it means to be

850
01:12:29,590 --> 01:12:32,250
in a very large scale
prescriptive technology.

851
01:12:33,720 --> 01:12:36,260
Where someone has already
pre-divided the work

852
01:12:36,260 --> 01:12:38,300
and all you know about
is your little piece,

853
01:12:38,300 --> 01:12:41,150
and almost certainly you don't
understand how it fits in.

854
01:12:44,630 --> 01:12:51,040
So, I think it's worth drawing the analogy
to physicists' work on the atomic bomb.

855
01:12:53,840 --> 01:12:56,610
In fact, that's actually
the community I came out of.

856
01:12:59,220 --> 01:13:03,460
I wasn't a nuclear scientist by any means,
but I was an applied mathematician

857
01:13:04,400 --> 01:13:09,400
and my PhD program was actually funded
to train people to work in weapons labs.

858
01:13:12,980 --> 01:13:17,100
One could certainly argue
that there is an existential threat

859
01:13:17,820 --> 01:13:22,060
and whoever is leading
in AI will lead militarily.

860
01:13:31,420 --> 01:13:34,250
- China fully expects to
pass the United States

861
01:13:34,250 --> 01:13:37,480
as the number one economy in
the world and it believes that

862
01:13:37,480 --> 01:13:42,450
AI will make that jump more
quickly and more dramatically.

863
01:13:43,900 --> 01:13:46,480
And they also see it as
being able to leapfrog

864
01:13:46,480 --> 01:13:49,820
the United States in
terms of military power.

865
01:13:57,580 --> 01:13:59,600
Their plan is very simple.

866
01:13:59,600 --> 01:14:03,620
We want to catch the United States
and these technologies by 2020,

867
01:14:03,620 --> 01:14:07,940
we want to surpass the United States
in these technologies by 2025,

868
01:14:07,940 --> 01:14:12,600
and we want to be the world leader in AI
and autonomous technologies by 2030.

869
01:14:15,110 --> 01:14:16,850
It is a national plan.

870
01:14:16,850 --> 01:14:21,790
It is backed up by at least
$150 billion in investments.

871
01:14:21,790 --> 01:14:25,060
So, this is definitely a race.

872
01:14:50,070 --> 01:14:52,070
- AI is a little bit like fire.

873
01:14:53,360 --> 01:14:56,270
Fire was invented 700,000 years ago,

874
01:14:57,480 --> 01:14:59,820
and it has its pros and cons.

875
01:15:01,960 --> 01:15:06,810
People realized you can use fire
to keep warm at night and to cook,

876
01:15:08,520 --> 01:15:14,420
but they also realized that you can
kill other people with that.

877
01:15:19,860 --> 01:15:24,300
Fire also has this
AI-like quality of growing

878
01:15:24,300 --> 01:15:27,400
in a wildfire without further human ado,

879
01:15:30,530 --> 01:15:35,970
but the advantages outweigh
the disadvantages by so much

880
01:15:35,970 --> 01:15:39,760
that we are not going
to stop its development.

881
01:15:49,540 --> 01:15:51,180
Europe is waking up.

882
01:15:52,160 --> 01:15:58,390
Lots of companies in Europe
are realizing that the next wave of AI

883
01:15:58,730 --> 01:16:01,540
will be much bigger than the current wave.

884
01:16:03,310 --> 01:16:08,000
The next wave of AI will be about robots.

885
01:16:09,810 --> 01:16:15,450
All these machines that make
things, that produce stuff,

886
01:16:15,450 --> 01:16:19,370
that build other machines,
they are going to become smart.

887
01:16:26,660 --> 01:16:29,950
In the not-so-distant future,
we will have robots

888
01:16:29,950 --> 01:16:33,290
that we can teach like we teach kids.

889
01:16:35,640 --> 01:16:38,660
For example, I will talk to a
little robot and I will say,

890
01:16:39,970 --> 01:16:42,550
"Look here, robot, look here.

891
01:16:42,550 --> 01:16:44,620
"Let's assemble a smartphone.

892
01:16:44,620 --> 01:16:48,720
"We take this slab of plastic like that
and we takes a screwdriver like that,

893
01:16:48,720 --> 01:16:52,310
"and now we screw in everything like this.

894
01:16:52,310 --> 01:16:54,310
"No, no, not like this.

895
01:16:54,310 --> 01:16:57,690
"Like this, look, robot, look, like this."

896
01:16:58,820 --> 01:17:01,890
And he will fail a couple
of times but rather quickly,

897
01:17:01,890 --> 01:17:05,860
he will learn to do the same thing
much better than I could do it.

898
01:17:06,710 --> 01:17:11,400
And then we stop the learning
and we make a million copies, and sell it.

899
01:17:32,410 --> 01:17:35,800
Regulation of AI sounds
like an attractive idea,

900
01:17:35,800 --> 01:17:38,210
but I don't think it's possible.

901
01:17:40,250 --> 01:17:42,720
One of the reasons why it won't work is

902
01:17:42,720 --> 01:17:46,360
the sheer curiosity of scientists.

903
01:17:47,260 --> 01:17:49,560
They don't give a damn for regulation.

904
01:17:52,640 --> 01:17:56,740
Military powers won't give a
damn for regulations, either.

905
01:17:56,740 --> 01:17:59,020
They will say,
"If we, the Americans don't do it,

906
01:17:59,020 --> 01:18:00,720
"then the Chinese will do it."

907
01:18:00,720 --> 01:18:03,150
And the Chinese will say,
"Oh, if we don't do it,

908
01:18:03,150 --> 01:18:04,810
"then the Russians will do it."

909
01:18:07,700 --> 01:18:10,930
No matter what kind of political
regulation is out there,

910
01:18:10,930 --> 01:18:14,660
all these military industrial complexes,

911
01:18:14,660 --> 01:18:17,570
they will almost by
definition have to ignore that

912
01:18:18,670 --> 01:18:21,250
because they want to avoid falling behind.

913
01:18:26,030 --> 01:18:27,690
Welcome to Xinhua.

914
01:18:27,690 --> 01:18:30,260
I'm the world's first female
AI news anchor developed

915
01:18:30,260 --> 01:18:32,690
jointly by Xinhua and
search engine company Sogou.

916
01:18:33,050 --> 01:18:36,310
- A program developed by
the company OpenAI can write

917
01:18:36,310 --> 01:18:39,500
coherent and credible stories
just like human beings.

918
01:18:39,500 --> 01:18:41,520
- It's one small step for machine,

919
01:18:41,520 --> 01:18:44,330
one giant leap for machine kind.

920
01:18:44,330 --> 01:18:47,170
IBM's newest artificial
intelligence system took on

921
01:18:47,170 --> 01:18:51,570
experienced human debaters
and won a live debate.

922
01:18:51,570 --> 01:18:54,160
- Computer-generated
videos known as deep fakes

923
01:18:54,160 --> 01:18:57,980
are being used to put women's
faces on pornographic videos.

924
01:19:02,510 --> 01:19:06,450
- Artificial intelligence
evolves at a very crazy pace.

925
01:19:07,970 --> 01:19:10,180
You know, it's like progressing so fast.

926
01:19:10,180 --> 01:19:12,940
In some ways, we're only
at the beginning right now.

927
01:19:14,490 --> 01:19:17,620
You have so many potential
applications, it's a gold mine.

928
01:19:19,590 --> 01:19:23,450
Since 2012, when deep learning
became a big game changer

929
01:19:23,450 --> 01:19:25,370
in the computer vision community,

930
01:19:25,370 --> 01:19:28,730
we were one of the first to
actually adopt deep learning

931
01:19:28,730 --> 01:19:31,080
and apply it in the field
of computer graphics.

932
01:19:34,640 --> 01:19:39,800
A lot of our research is funded by
government, military intelligence agencies.

933
01:19:43,950 --> 01:19:47,840
The way we create these photoreal mappings,

934
01:19:47,840 --> 01:19:50,300
usually the way it works is
that we need two subjects,

935
01:19:50,300 --> 01:19:53,740
a source and a target, and
I can do a face replacement.

936
01:19:58,880 --> 01:20:03,700
One of the applications is, for example,
I want to manipulate someone's face

937
01:20:03,700 --> 01:20:05,450
saying things that he did not.

938
01:20:08,920 --> 01:20:12,140
It can be used for creative
things, for funny contents,

939
01:20:12,140 --> 01:20:16,110
but obviously, it can also
be used for just simply

940
01:20:16,110 --> 01:20:18,660
manipulate videos and generate fake news.

941
01:20:21,050 --> 01:20:23,340
This can be very dangerous.

942
01:20:24,790 --> 01:20:29,300
If it gets into the wrong hands,
it can get out of control very quickly.

943
01:20:33,370 --> 01:20:35,750
- We're entering an era
in which our enemies can

944
01:20:35,750 --> 01:20:39,590
make it look like anyone is
saying anything at any point in time,

945
01:20:39,590 --> 01:20:41,830
even if they would
never say those things.

946
01:20:42,450 --> 01:20:46,970
Moving forward, we need to be more
vigilant with what we trust from the Internet.

947
01:20:46,970 --> 01:20:50,710
It may sound basic, but how
we move forward

948
01:20:50,710 --> 01:20:55,180
in the age of information
is going to be the difference

949
01:20:55,180 --> 01:20:58,160
between whether we survive
or whether we become

950
01:20:58,160 --> 01:21:00,270
some kind of fucked up dystopia.

951
01:22:31,070 --> 01:22:37,337
- One criticism that is frequently raised
against my work is saying that,

952
01:22:37,337 --> 01:22:43,610
"Hey, you know there were stupid ideas
in the past like phrenology or physiognomy.-

953
01:22:45,110 --> 01:22:49,210
- "There were people claiming
that you can read a character

954
01:22:49,210 --> 01:22:52,010
"of a person just based on their face."

955
01:22:53,820 --> 01:22:56,050
People would say, "This is rubbish.

956
01:22:56,050 --> 01:23:01,050
"We know it was just thinly
veiled racism and superstition."

957
01:23:05,300 --> 01:23:09,650
But the fact that someone
made a claim in the past

958
01:23:09,650 --> 01:23:14,650
and tried to support this
claim with invalid reasoning,

959
01:23:14,960 --> 01:23:18,970
doesn't automatically
invalidate the claim.

960
01:23:23,790 --> 01:23:25,710
Of course, people should have rights

961
01:23:25,710 --> 01:23:31,020
to their privacy when it comes to
sexual orientation or political views,

962
01:23:32,310 --> 01:23:35,600
but I'm also afraid that in
the current technological environment,

963
01:23:35,600 --> 01:23:38,220
this is essentially impossible.

964
01:23:42,640 --> 01:23:44,910
People should realize
there's no going back.

965
01:23:44,910 --> 01:23:48,330
There's no running away
from the algorithms.

966
01:23:51,120 --> 01:23:55,670
The sooner we accept the
inevitable and inconvenient truth

967
01:23:56,540 --> 01:23:59,430
that privacy is gone,

968
01:24:01,770 --> 01:24:05,380
the sooner we can actually
start thinking about

969
01:24:05,380 --> 01:24:07,440
how to make
sure that our societies

970
01:24:07,440 --> 01:24:11,660
are ready for the Post-Privacy Age.

971
01:24:35,080 --> 01:24:37,610
- While speaking about facial recognition,

972
01:24:37,610 --> 01:24:43,700
in my deep thoughts, I sometimes get to
the very dark era of our history.

973
01:24:45,490 --> 01:24:49,020
When the people had to live in the system,

974
01:24:49,020 --> 01:24:52,660
where some part of the society was accepted

975
01:24:53,680 --> 01:24:56,900
and some part of the society
was accused to death.

976
01:25:01,670 --> 01:25:06,180
What would Mengele do to have
such an instrument in his hands?

977
01:25:10,740 --> 01:25:14,390
It would be very quick and
efficient for selection

978
01:25:18,390 --> 01:25:22,100
and this is the apocalyptic vision.

979
01:26:15,880 --> 01:26:19,870
- So in the near future,
the entire story of you

980
01:26:19,870 --> 01:26:25,340
will exist in a vast array of
connected databases of faces,

981
01:26:25,750 --> 01:26:28,390
genomes, behaviors and emotion.

982
01:26:30,950 --> 01:26:35,320
So, you will have a digital
avatar of yourself online,

983
01:26:35,320 --> 01:26:39,510
which records how well you
are doing as a citizen,

984
01:26:39,510 --> 01:26:41,910
what kind of a relationship do you have,

985
01:26:41,910 --> 01:26:45,890
what kind of political orientation
and sexual orientation.

986
01:26:50,020 --> 01:26:54,120
Based on all of those data,
those algorithms will be able to

987
01:26:54,120 --> 01:26:58,390
manipulate your behavior
with an extreme precision,

988
01:26:58,390 --> 01:27:03,890
changing how we think and
probably in the future, how we feel.

989
01:27:25,660 --> 01:27:30,510
- The beliefs and desires of the
first AGIs will be extremely important.

990
01:27:32,730 --> 01:27:35,180
So, it's important to
program them correctly.

991
01:27:36,200 --> 01:27:37,850
I think that if this is not done,

992
01:27:38,810 --> 01:27:44,190
then the nature of evolution
of natural selection will favor

993
01:27:44,190 --> 01:27:48,340
those systems, prioritize their
own survival above all else.

994
01:27:51,860 --> 01:27:56,660
It's not that it's going to actively
hate humans and want to harm them,

995
01:27:58,780 --> 01:28:01,100
but it's just
going to be too powerful

996
01:28:01,400 --> 01:28:05,470
and I think a good analogy would be
the way humans treat animals.

997
01:28:06,970 --> 01:28:08,200
It's not that we hate animals.

998
01:28:08,260 --> 01:28:11,930
I think humans love animals
and have a lot of affection for them,

999
01:28:12,340 --> 01:28:17,610
but when the time comes to
build a highway between two cities,

1000
01:28:17,610 --> 01:28:20,130
we are not asking
the animals for permission.

1001
01:28:20,130 --> 01:28:23,340
We just do it because
it's important for us.

1002
01:28:24,250 --> 01:28:29,010
And I think by default, that's the kind of
relationship that's going to be between us

1003
01:28:29,010 --> 01:28:34,700
and AGIs which are truly autonomous
and operating on their own behalf.

1004
01:28:47,190 --> 01:28:51,400
If you have an arms-race
dynamics between multiple kings

1005
01:28:51,400 --> 01:28:54,140
trying to build the AGI first,

1006
01:28:54,140 --> 01:28:58,000
they will have less time to make sure
that the AGI that they build

1007
01:28:58,970 --> 01:29:00,520
will care deeply for humans.

1008
01:29:03,530 --> 01:29:06,540
Because the way I imagine it
is that there is an avalanche,

1009
01:29:06,540 --> 01:29:09,220
there is an avalanche
of AGI development.

1010
01:29:09,220 --> 01:29:12,300
Imagine it's a huge unstoppable force.

1011
01:29:15,780 --> 01:29:18,740
And I think it's pretty likely
the entire surface of the

1012
01:29:18,740 --> 01:29:22,070
earth would be covered with
solar panels and data centers.

1013
01:29:26,230 --> 01:29:28,700
Given these kinds of concerns,

1014
01:29:28,700 --> 01:29:32,830
it will be important that
the AGI is somehow built

1015
01:29:32,830 --> 01:29:35,570
as a cooperation
with multiple countries.

1016
01:29:38,060 --> 01:29:41,180
The future is going to be
good for the AIs, regardless.

1017
01:29:42,130 --> 01:29:45,020
It would be nice if it would
be good for humans as well.

1018
01:30:06,750 --> 01:30:10,580
- Is there a lot of responsibility
weighing on my shoulders?

1019
01:30:10,580 --> 01:30:11,800
Not really.

1020
01:30:13,420 --> 01:30:16,740
Was there a lot of
responsibility on the shoulders

1021
01:30:16,740 --> 01:30:19,100
of the parents of Einstein?

1022
01:30:20,190 --> 01:30:21,780
The parents somehow made him,

1023
01:30:21,780 --> 01:30:25,450
but they had no way of
predicting what he would do,

1024
01:30:25,450 --> 01:30:27,300
and how he would change the world.

1025
01:30:28,580 --> 01:30:32,540
And so, you can't really hold
them responsible for that.

1026
01:30:57,640 --> 01:31:00,240
So, I'm not a very human-centric person.

1027
01:31:01,840 --> 01:31:05,500
I think I'm a little stepping
stone in the evolution

1028
01:31:05,500 --> 01:31:08,060
of the Universe towards higher complexity.

1029
01:31:10,820 --> 01:31:14,860
But it's also clear to me that
I'm not the crown of creation

1030
01:31:14,860 --> 01:31:19,320
and that humankind as a whole
is not the crown of creation,

1031
01:31:21,140 --> 01:31:26,290
but we are setting the stage for something
that is bigger than us that transcends us.

1032
01:31:28,980 --> 01:31:32,780
And then will go out there in a way
where humans cannot follow

1033
01:31:32,780 --> 01:31:37,940
and transform the entire Universe,
or at least, the reachable Universe.

1034
01:31:41,520 --> 01:31:46,520
So, I find beauty and awe in seeing myself

1035
01:31:46,640 --> 01:31:50,260
as part of this much grander theme.

1036
01:32:14,070 --> 01:32:16,030
- AI is inevitable.

1037
01:32:17,560 --> 01:32:23,370
We need to make sure we have
the necessary human regulation

1038
01:32:23,370 --> 01:32:27,940
to prevent the weaponization
of artificial intelligence.

1039
01:32:28,690 --> 01:32:32,000
We don't need any more weaponization

1040
01:32:32,000 --> 01:32:33,960
of such a powerful tool.

1041
01:32:37,100 --> 01:32:41,960
- One of the most critical things, I think,
is the need for international governance.

1042
01:32:43,920 --> 01:32:46,310
We have an imbalance of
power here because now

1043
01:32:46,310 --> 01:32:49,140
we have corporations with
more power, might and ability,

1044
01:32:49,140 --> 01:32:51,100
than entire countries.

1045
01:32:51,100 --> 01:32:54,050
How do we make sure that people's
voices are getting heard?

1046
01:32:58,030 --> 01:32:59,930
- It can't be a law-free zone.

1047
01:32:59,930 --> 01:33:02,100
It can't be a rights-free zone.

1048
01:33:02,100 --> 01:33:05,870
We can't embrace all of these
wonderful new technologies

1049
01:33:05,870 --> 01:33:10,380
for the 21st century without
trying to bring with us

1050
01:33:10,380 --> 01:33:15,380
the package of human rights
that we fought so hard

1051
01:33:15,640 --> 01:33:19,190
to achieve, and that remains so fragile.

1052
01:33:28,680 --> 01:33:32,180
- AI isn't good and it isn't evil, either.

1053
01:33:32,180 --> 01:33:36,890
It's just going to amplify the desires
and goals of whoever controls it.

1054
01:33:36,890 --> 01:33:41,240
And AI today is under the control of
a very, very small group of people.

1055
01:33:44,430 --> 01:33:49,260
The most important question that we humans
have to ask ourselves at this point in history

1056
01:33:49,260 --> 01:33:51,380
requires no technical knowledge.

1057
01:33:51,590 --> 01:33:57,540
It's the question of what sort
of future society do we want to create

1058
01:33:57,540 --> 01:33:59,740
with all this
technology we're making?

1059
01:34:01,410 --> 01:34:05,110
What do we want the role of
humans to be in this world?