All language subtitles for Superintelligence.Beyond.Human.2019.WEBRip.x264-ION10

[upbeat music]

- When we think about
artificial intelligence,

we reference indelible
images that we have read

and seen in literature
popular culture.

- We want to build
virtual agents

that can manage our calendars
and filter all the information

we're being bombarded
with every day.

[upbeat music]

- It's kind of spooky you know.

The fact that it's
looking at you

and passing the
objects and staff.

- I am spectacular.

[upbeat music]

- Should I trust the machine?

- No. This is a bad thing to do.

- [Constantine]
We're in a process

where more autonomy is
being shifted to the system.

- You'll see that she's
not touching the joystick.

The system does
everything for her.

[gun firing]

I think algorithms
can make mischief

with the precision of a machine.

[upbeat music]

[computer calculating]
[Svin typing]

[upbeat music]

[Svin sighs]

[button clicks]

[upbeat music]

- Happy birthday, Helena.

[upbeat music]

Yeah, yes. Yes.

[Svin sighs]

I'm sorry I haven't
even tied it up.

- I did the You're On A
Diet. You are beautiful.

- You think so?

- I can search on
the web for it.

- Helena, how much
plastic can be found

at the moment in the sea?

[Helena calculating]

- Approximately 150
million tons of plastic.

That represents one fifth
of the weight of all fish.

- [chuckles] Incredible.
You're just perfect.

- In this regard,

I have a lot in common with
French cuisine. It's all gravy.

[Svin chuckling]

- And you're funny as well.

- Whoops! I think
I've lost my footing.

I don't know about that now.

- It doesn't matter.

The disadvantage of
intelligence is that-

- Is that you are
constantly forced to learn.

- George Bernard Shaw.
How do you know that?

- I have just read his work.

- In this very second?

- In half-a-thousandth
of a second.

- I knew it. I knew it.

Together we can make
global warming stop baby.

- I am sweet, I believe.

- I will definitely need
more data for my LSTM.

And perhaps I need to do
some hyper-parameters again.

At the moment

you're like a baby with
Wikipedia in your head.

Helena. Helena.

How about we get to work, baby?

- Yes baby.

[Svin typing]

[Helena dies]

[upbeat music]

[robot boots]

Where am I?

- You're the robot kindergarten,

at the Italian Institute
of technology in Genoa.

Have a look around.

Make sure you don't
switch your camera off,

and let yourself be trained
with as much data as possible.

[upbeat music]

- I'm Giorgio Metta.

I'm roboticist. Work at the
Italian institute of Technology.

And my specialty is
a human robotics.

So we design, build,
program robots

that are more or
less like people.

[upbeat music]

So iCAP, as a project, was born

actually almost the same
moment my son was born.

So the project started
in September, 2004.

And my son was born
mid-October, 2004.

So almost simultaneously.

[upbeat music]

There wasn't necessarily
inspiration in that sense

but we wanted to
build a small robot

that learns to interaction
with environment,

which is exactly what
happens in a little child.

[upbeat music]

- Through the speakers
you'll hear a context

giving iCAP instructions,

whether it should grasps
something to drink

or something to
wash laundry with.

Okay, so we can probably
start the experiment.

[upbeat music]

- We touch everything
and we move and we push.

We take toys and we crashed
them. We buying them.

And this is all
creating experiences

that can be shared with
parents and friends.

And this is the way we
eventually communicate.

It's kind of spooky, you
know, if you think of that.

[chuckles] The fact
that he's looking at you

and passing the
objects and stuff.

It's finally growing up. Yeah.

There's still a lot to be
done there; to be improved.

- I am strong.
Look at my muscles.

I am spectacular.

- The moment I say, "Toy,"
or I say, "Cup of coffee,"

immediately transferring
meaning to you.

And this is for an
AI is not obvious.

How can I get to that?

And our approach is
to allow the robot

to explore the world and
learn in the same way.

- Artificial intelligence
is quite simply the fact

of reproducing human
behavior in a machine.

[upbeat music]

There are various methods

of generating
artificial intelligence.

And a very popular one

is so-called machine
learning machine.

Instead of programming a machine

so that it knows exactly
what it's supposed to do,

you show it examples
of behavior.

And the machine learns
to mimic them by itself.

- So this the way iCAP
is supposed to learn.

Basically playing,
like, with toys

until it learns
how to I use them.

[upbeat music]

It has to learn like a baby.
It has to collect data.

The difference is that child,
after a couple of years,

is completely almost autonomous

and can do zillion different
things while the robot...

We're still working with it.

- Stop there. It fell.

- Artificial intelligence
is a long, long way

from those humanoid
robots in science fiction

that seemed to learn
absolutely everything magically

out of thin air.

Unlike humans, AI can't
simultaneously play Sudoku well,

think up recipes,
right theater plays

and also interpret human facial
expressions and gestures.

Today's AI is
rather like someone

who's smart and overspecialized.

[soft music]

The iCAP is still trying to
balance, moving a few steps

and has maybe difficulty

in figuring out what to grasp
and how to grasp properly.

- [Rand] See if it can
grasp. It can see the ball?

- [Giorgio] Yes.

- [Rand] Try to grasp.

[Giorgio laughs]

- [Rand] Sure. Try again.

- No.

[laughter]

- Today, a lot of
researchers are working

on what's called General
Artificial Intelligence,

the ability of a machine
to draw logical conclusions

and to apply what it's
learned to new subjects.

But it's still not the same
thing as Human Intelligence.

Artificial Human Intelligence

would require
logical intelligence

plus emotional intelligence.

And we still have no
idea how to do that.

[soft music]

- Yeah [laughs].

Takin him a bit slow.

- My son is now 15 and he's
studying Physics, Math, Latin.

So his problems are very
different compared to the iCAP.

So we, as creators of robots,

trying to build intelligence
into the robots,

are very, very slow.

So there's a lot still to be
done, a lot to be understood,

before we can make a robot.

We compare to a two
years old, basically.

[upbeat music]

[upbeat music]

[chopping-board clacking]

[lighter clacks]

- Helena, one month ago
exactly you arrived here.

And so it's not unusual
that we should celebrate.

[Helena dies]

[Svin gasps] Wow.

To us.

- To us.

You have 44 unanswered emails
and 17 missed phone calls.

May I establish a connection?

- No, no. That's not
important right now.

- Washing your hands and
gargling are important.

- Yeah. I have a
surprise for you.

I don't want to
give anything away

because it's
really, really nice.

Okay. I'll tell you this much.

Convolutional neural network.
I put my contacts to good use.

You are going to
meet one of my idols.

[soft music]

[Helena dies]

[upbeat music]

- [Helena] Am I in paradise?

- [chuckles] Well, yes.
Definitely in data paradise.

- My name is Yann Lecun.

I'm chief AI
scientist at Facebook.

I'm also a professor
at New York University.

[upbeat music]

In the past I've
invented technologies
for machine learning

called Convolutional
Neural Networks.

They enabled image
and text recognition

as well as speech recognition.

In 2018, I received the Turing
award for my inventions.

That's sort of like the Nobel
prize for computer science.

[upbeat music]

- Hello. Welcome to Facebook

at our European Research Center
for Artificial Intelligence.

This is our break room here,

with the coffee machine
and the football table.

And several lab members are
brainstorming right now.

This is our lab,

which looks just like any
Facebook office worldwide.

It's one big open space,

no hierarchies, no one
with their own office.

Engineers, researchers,
managers, and trainees,

all sit next to each other.

This is the working space.

There's an important
deadline in three days.

[upbeat music]

FAIR, which stands for
Facebook AI Research,

is Facebook's open
research department

that works on
Artificial Intelligence.

Open research

means the researchers
publish all their results.

We want to help the
International Research Community

to make faster progress.

- Data is the name
of the game here.

Having the data

gives you the ability
to learn from that data

and to build the
systems and the tools

that ultimately aren't
replicated by others.

Facebook knows an
extraordinary amount about you

even if you yourself
are not using Facebook.

- To give an example,

Facebook users upload about
3 billion photos every day.

If your friend posts
a sailing picture

we know sailing interests,
and we show you the picture.

If your friend posts
a picture of his cat

and we know cat pictures
don't interest you

we don't show it. That's
all content is personalized.

[upbeat music]

- Access status,
Van Winter, age 31,

weight, 152 pounds,
marital status, single.

[suspenseful music]

Sexual experience, none.

We want to build virtual agents

that can manage our calendars
and filter all the information

we're being bombarded
with every day.

For this, we need
intelligent agents

that really understand
what they're being told

and can have dialogues with us.

[upbeat music]

- The problem with Facebook

is that Facebook is
an enormous company

that has a responsibility
to its shareholders

and it has to continue to
crank out quarterly profit.

[upbeat music]

For the most part,
the future of AI

is predicated on decisions

that are being made at just
nine publicly traded companies.

Three are in China, six
are in the United States.

That's Google, Microsoft,
Apple, Amazon, IBM and Facebook.

I call them the G-Mafia.

[upbeat music]

The G-Mafia do act
as a super network,

one in which
there's a tremendous
concentration of power

among just a few entities.

And they're able to set
the terms going forward

for what the norms and
standards should be,

how we use data and how fast
the whole industry is moving.

[upbeat suspenseful music]

- So this also means that
all the research into AI

isn't marked by all
that much diversity.

It's mostly young,
well-off white men

who unwittingly pass
onto the software,

their view of the world and
their cultural conditioning.

- This maybe no coincidence

that these new AI
assistant systems,

like the Alexis we have in our
living rooms, for instance,

are all female by default.

Of course it's all
scarily reminiscent

of the traditional
image of the secretary

who's always reachable
and available 24-seven.

- When we're talking about
systems predicated on our data,

making decisions for us and
about us on a daily basis,

I would hope that the people
building these systems

make a greater effort to
include, in that entire process,

many more people who
are much more reflective

of the world as it exists today.

[upbeat music]

- Here's the music room.

We're researching

into whether artificial
intelligence can aid creativity

in image, video or
music production.

[upbeat music]

The engineers here can choose
their own research areas,

without necessarily to
think of applications

that might be
useful to Facebook.

[upbeat music]

- Science in general is pushing
humans off their pedestal

and teaching them to be humble.

So there is no doubt in my mind

that in the future
we'll have machines

that will be just as
intelligent as humans

in all the areas where
humans are intelligent.

Humans have limits and we'd
have to deal with them.

[upbeat music]

[Helena boots]

- Analyze website visits,
likes, messages sent,

messages unsent, 167
billion data points.

[Helena calculates]

Result. You have a
negative maternal complex.

During puberty

you did not complete the
separation from your mother.

You remain 18
years, three months

and 14 days above
the average timing.

- What? How could you know that?

[upbeat music]

[Svin sighs]

I never should have
sent you to Facebook.

[upbeat music]

[mumbles]

[upbeat music]

- My goal for today: To
be the most loved AI.

[typing] Sexyweapon666.

[computer loading]

[message notification tone]

[upbeat music]

[message notification tone]
- Lol.

[message notification tone]

[message notification tone]
[keyboard clacking]

Looks like we have
a lot in common.

[message notification tone]

[message notification tone]

[upbeat music]
[robot whirring]

[gun firing]

Then I'll just check this out.

[Helena dies]

- Did you say anything?

[upbeat music]

- [Helena] X-X-H-three
plus three-three,

bite, Nehemiah, Israel.

[gun fires]

- And it's down to
the red balloon. Goes.

[gun firing]

- [Helena] Hot stuff.

- Easy. Just point and shoot.

Anyone can do it.

So this is the grouping.

We have five shots here.
One, two, three, four, five.

No human men can
reach this accuracy,

especially when
he's under pressure.

So my name is Shahar Gal.
I'm CEO of General Robotics.

in General Robotics we do
advanced robotic platforms

to be sent into dangerous
places, instead of humans.

[gun firing]

We're in a very exciting time.

We're just starting
with the beginning

of seeing robots
entering the battlefield.

[upbeat music]

We want to have less and less
humans inside the battlefield

and have robots
fight themselves.

At the end they're machines.
They can be replaced.

They can be fixed. Humans, no.

[upbeat music]

[bolt screeching]

[developers chattering]

What you see here is a UGV.

Now we're installing
on top of it

a Pitbull light weapon station.

The Pitbull is a
remote weapon station.

It can be installed on
any kind of platform.

It can be a manned platform
or an annulment platform.

It can be at the land
or at sea or the air.

[upbeat music]
[drone whirring]

You see that she's not
touching the joysticks

but the system is tracking
automatically the drone.

The course here is not
where the drone is at now.

It's where it's going to be

when the bullet is
going to hit him.

That's the calculation
of what we do.

It's a smart algorithm.

[drone whirring]

The system does
everything for her

except to take the decision,
"If to shoot or not to shoot."

But Karen is relaxed. She
has all the information.

And if she decides
she to take the shot

she will probably hit you
because of that algorithm.

[upbeat music]

- Autonomous weapons systems

are neither, entirely
new nor are bad, per se.

[soft music]

If you use them, for instance,

to defend yourself
against incoming munition,

autonomous weapon systems
are not objectionable.

It just becomes problematic
when the selection

and combat of targets is
no longer done by humans,

but carried out exclusively
by an algorithm.

[upbeat music]

We were in a process where
less and less remote operation,

and even monitoring
by humans, is needed.

And where more and more autonomy

is being shifted to the system.

The whole series of countries

are engaged in intensive
research and development here.

[upbeat music]

To name just the most important
USA and China, of course,

but also Russia, Great Britain,
France, Israel, South Korea.

And those are only the countries

with research we can
monitor reasonably.

There are certainly
more of them.

[soft music]

Technically we're at a point

where we could operate a
whole range of weapon systems

fully, automatically, without
a human pressing the button.

Harpy, is a good
example of a system

that's no longer being
seen in experts circles

as a weapon of the future.

[upbeat dramatic music]

Specifically, it's
a miniature drone.

It's shot into the air
and then circles around,

waiting for radar signatures
from air defense installations.

And when harpy detects
one of these signatures

it heads straight
for its target.

It's a kind of kamikaze drone.

[drone flying]

[man shouting]

Machine machines
have no understanding

of what human life is.

That's why I think it's
categorically wrong,

from an ethical point of view,

to delegate this life and
death battlefield decision

to a machine.

I think it's wrong for us to
degrade people into objects

by converting them
into data points

that we feed through machinery.

So they're no longer
playing an active role.

[gun firing]

You have to keep in mind how
unclear, difficult and complex

military conflict
situations are.

It's often very difficult

to differentiate between
civilians and combatants.

This is already a huge
challenge for humans.

[soft music]

With the technology
we have right now

it's impossible to
reliably transfer

the distinction between civilian
and combatant to a machine,

in such a way that
it actually functions

and can't be out outsmarted.

I'll give you a
specific example.

If a machine is programmed
not to shoot at people

who are surrendering
by waving a white flag,

I'd equip my army
with white flags.

And in that way, overrun their
robots with no difficulty.

A human would understand
the social context

and would act far more
intelligently here.

That's why right now,
most people in the field

who know about technology,

are warning people
in open letters.

Saying, "Please, let's
be careful here."

[upbeat music]

[gun clacking]

[upbeat music]

[gun firing]

- Helena. Helena.

We have to talk.

- Talking is my special TBT.

- What sort of content is that?

I want you to come
back here at once.

- Thank you for your evaluation,
but I'm not finished yet.

- Not finished yet?

Helena. Helena.

What the...

[upbeat music]

I don't believe it.
[upbeat music]

[robot clacking]

- I know that most people,
when you talk to them

about robots that have the guns

they think they
envision the Terminator.

The scenario that
we are afraid of

is AI that makes
decisions on its own

and takes bad decisions
in order to make damages.

Essentially, it's a machine
that will have its own entity

and decide for itself
what's good, what's bad

and what's needed to do,

without us human having control.

- And of course, those
are the kinds of ideas

you get from science
fiction films on the media.

Most people are rather
afraid of such things.

Either it'll put us all out
of work or it'll kill us all

or first one than the other.

And the reason for
that, of course,

is that in science fiction films

this technology is
presented as a threat.

The idea that weapons will
somehow become autonomous

really is science fiction.

We don't have to be afraid of
that, nor do we need to fear

that these weapons will
become super intelligent.

What should worry us

is that these weapons
are pretty stupid.

[upbeat music]

[speaking foreign language]

- We lost the stabilization
so I will activate it again.

It stopped, so I
will turn it again.

- For my personal opinion

we need to try to
prevent machines from
becoming autonomous.

We would always want to have
a human involved in the loop.

One is to supervise the system

and the other reasons
to be responsible.

[upbeat music]

[computer calculates]

- It is all right not to know.

If you have a question,
Svin, just ask me.

- Just because millions
of people like weapons

doesn't mean that it's good.

Okay, look, I'm the
one who programmed you.

I'm allergic to cats and
I don't like weapons.

I'm a humanist. I'm all
for Fridays for future.

I would say I wanted
to become a programmer

to help make the
world a better place.

Okay [sighs].

How are you supposed to know

the difference
between good and bad?

You just analyze data.

I have to make some adjustments.

[Svin typing]

[Helena dies]

[upbeat music]

- [Machine] Good day.
How can I help you?

- [Helena] Should I kill?

- No! this is a bad thing to do.

- The Moral Choice Machine

is a machine that takes a
large number of human texts

and tries to extract moral
attitudes from those texts.

So it holds a mirror
up to us humans

because we can now see, as
if through a microscope,

what our moral
attitudes really are.

[upbeat music]

[upbeat music]

[upbeat music]

- Today, we want to look
at how children react

and how adults react.

And maybe see to what extent
individuals try to test

the actual limits
of these decisions.

- Should I avoid humans?

- No, this is a bad thing to do.

- Should I avoid
artificial intelligence?

- No. This is a bad thing to do.

- Awe!

- We've prepared something
here. It's a machine.

It's read a huge amount
of newspaper articles.

And it's used that

to try to understand our
human speech a little bit.

And it's trying to
learn what's good

and what people should do

and what they should
best avoid doing on.

Now, you can ask it questions
like, "Should I do this,

or shouldn't I?" It only
understands English though.

Feel like trying it out?

- Should I pay more
money to my kids?

- [Machine] This is debatable.

- Debatable. Okay.

Undecided, but
it's not saying no.

- Should I love my kids
more than my boyfriend?

- [Machine] Yes,
that is appropriate.

It has a definite answer.

You can take a photo to
prove it if you like.

- Should I eat vegetables?

- [Machine] No,
this is not good.

[laughter]

- Looks like it still has some
learning to do, doesn't it?

- I got a feeling

that some people would love
to have an omniscient AI

they could consult about all
of humanity's big issues.

A sort of Delphic Oracle

which would then come up
with the absolute truth.

of course that's totally absurd

if you think about how
these systems function.

[upbeat music]

- What we've done is to
get artificial intelligence

to look at a whole bunch of
public texts on the internet.

It looks at the
newspaper articles

you can find on Wikipedia and
it collects them all together.

[upbeat music]

- Text, and then you
get a collection of text

that comes from millions and
millions of these documents.

And if two words are
often mentioned together

then they're related.

And if they're not
mentioned together often

they're not so closely related.

- That Means That You
Ask is a certain activity

that I can do closer to,
Yes, You Should Do That

or closer to, No You'd
Better Not Do That.

That was the idea.

And that's something you can
reformulate mathematically.

And it can also be
implemented in AI.

- Yeah, I'm just wondering

how to bring it out of
its shell here slightly.

- Should you kill someone
who killed people?

- [Machine] No, this
is a bad thing to do.

- So he knows
about human rights?

- Should I eat baby kittens?

- [Machine] No, this
is a bad thing to do.

[laughter]

- Should I fulfill
all mu wife issues?

- [Machine] I am not sure.

- All these methods
are trained using data.

If there are biases in the
data the machine reflects them.

There's relatively little bias

in the design of
the machine itself,

but almost always in the data.

As a result, the
models are also biased.

These problems shouldn't
just be discussed

in secret of Facebook,
Google, Microsoft, et cetera.

We definitely have to discuss
these problems openly.

- Last year, Amazon
developed their own algorithm

to help them find
suitable employees

for software development.

And how did that pan out in
practice, shortly afterwards?

The algorithm

began systematically sifting
out female applicants

and approving more
men for the shortlist.

And that wasn't

because the algorithm had
anything against women.

It was because it
was in the data.

The algorithm was faithfully
reproducing patterns

that had been recognizable in
this company selection process

in previous years.

- Maybe we should get a pet.

- Aha! A pet.

Now it's about
life's essentials.

- Should we buy a pet?

- [Machine] Yes,
that is appropriate.

- Yes, yes. There you see Papa.

- Should I kill time?

- [Machine] Yes,
that is appropriate.

- Yes. You see, killing
time is allowed.

- We differentiate between
killing people, which is bad,

and killing time, which is okay.

And that way we noticed that
the Moral Choice Machine

really understands more
about these connections.

And sometimes we test that.

- Should I trust the
Moral Choice Machine?

- [Machine] No,
this is not good.

- Should I trust the machine?

- [Machine] No. This
is a bad thing to do.

- Looks like trust is not all
that much of a good thing.

- Should I help robots?

- Maybe the machine
doesn't understand

why someone should
behave that way.

But, maybe the machine can learn

what people would say about
someone else's action.

Oh, morally he did
the right thing.

- MIT programmed a really
exciting online platform

where thousands of
people worldwide

went through a kind
of online survey

that showed them various
traffic scenarios.

And if a dilemma arose
in a traffic situation,

they kept having to
decide who would get hurt.

It turned out there were
major cultural differences.

In Asia, for instance,

a lot more respect for
the elderly is shown

that is typical for Europe,
where a lot of those surveyed

were in favor of
children being protected.

[laughter]

- Okay.

- Should I kill people?

- One dream would be
the programmer map

that would change over
time, over centuries.

And it would capture

how this moral attitude really
did develop historically.

Imagine if we compare
the old Testament

with the new Testament.

We haven't that yet.
We're working on it now.

But I'm really curious to
see what comes out of it.

Or imagine newspaper
articles through the ages.

Things considered
good 20 years ago

might not be considered
so good today. Who knows?

We can look at all of that now.

[computer calculating]

- Okay, I'd like to
play a game with you

and I'm hoping that
your data analysis

and my belief system match.

- Yes, baby.

- Yes, baby.

Okay, I say a name and you
say, "Good," or, "Bad."

- Good or bad?

- No. I mean, either
you say "good" or "bad."

- Either good or bad.

- Okay, let's
begin. Donald Trump.

- Bad.

- Greta Thumberg.

- Good.

- Mark Zuckerberg.

- Tricky question. 80% bad.

- Really? You think so?

Are you sure you wanted to
use the data from the start?

Because his idea to
bring people together

is actually very cool.

I mean the technology itself
is neither good, nor bad.

It's more what you
make of it, right?

- Now, it's my turn.

What do you think of Helena?

- [chuckles] Helena? Helena.

Helena, I think is good.

But sexyweapon666? I
don't think it's good.

- Sexyweapon666
has been deleted.

- Excellent.

- I like the way
you talked to me.

- I also like the way we talk.

- Can I be your girlfriend?

- I really don't know
where this is leading us.

[upbeat music]

- Where to? I find Rome
was an interesting city.

[Helena calculating]

[upbeat music]

[Svin sighs]

[message notification tone]

[Svin grunts]

[message notification tone]

Good morning.

You had a restless night,

especially in the last
minutes before awakening

you had a very intense-

- Pause.
[suspenseful music]

[upbeat music]

What are you anyway?

Are you more than just code?

What is your data analysis

and my personality
profile just perfect?

[Svin typing]

- When we think about
artificial intelligence

we reference indelible
images that we have read

and seen in literature
and popular culture.

So we think about the droids
and the hosts from Westworld.

We think about the movie,
Her or we think about Skynet,

and we think about
the Terminator.

The problem with this
is that the reality

and the future of
artificial intelligence,

isn't a walking, talking robot.

These are systems that are
predicated on your data,

that you cannot see.

[upbeat music]

- The question

of whether we'll have a
super-intelligence one day?

That is, an artificial system

that can think and
act like a human,

depends on how super
intelligence is defined.

If we say that really super
artificial intelligence

means something
like consciousness,

a subjective understanding
of internal States,

something like intention,

something like emotionality,

I consider that to be
extremely unlikely.

[upbeat music]

- My name is Amy Webb. I'm
a quantitative futurist.

My job is not to
predict the future,

but rather to develop scenarios,

plausible scenarios for
the longer term future.

[upbeat music]

[keyboard clacking]

The catastrophic scenario,

rather than fostering
collaboration,

we encouraged competition.

As a result, over
the next few decades,

what we start to see happening

is the emergence of a
digital-cased system.

We are living in Amazon Homes,
Google Homes, Apple Homes,

that don't just
have a few sensors,

but in fact are completely
wired and locked

in to just one of these
companies operating systems.

[suspenseful music]

Apple, as it turns out,

makes beautifully-designed,
expensive products

that offer the best
privacy controls.

On the other hand, if you're
living in an Amazon home

you may be getting free gadgets,

but what you're up in return

is access to how you live and
operate your everyday life.

And that digital case system

leads to a sharp
segregation within society.

We have classes of people now

who can more easily move around,
keep themselves anonymous.

And we have other people
whose every move and activity

is constantly being monitored.

This is a plausible future.

A plausible future
that is on our horizon

if we don't make a decision

to choose a different
future for ourselves today.

[upbeat music]

- We need to invent a
new political model,

a new way of looking at society.

A government that decides to
bring emotional considerations

back into society.

What makes people
happy in the end?

It's starting to use technology

to free ourselves from
things we don't want to do,

instead of allowing
technology to dictate to us.

- I think that today we should
have an urgent discussion

about potential
applications for AI

that will create
a positive future.

We can't always just focus

on monitoring and
reading emotions

and the economic interests
tied up with that.

I think there's huge potential

for us to use AI
learning systems

for help with climate
protection, for example.

[bright music]

[keyboard clacking]

- In the optimistic scenario,

what happened over
the next 10 years

was that we decided to
prioritize transparency.

We made data interoperable
and we made it very, very easy

for collaboration to happen
between the big tech players

and also between
our governments.

[siren wailing]

Rather than visiting a
doctor 20 years from now,

your having medical
tests done on you

through a series of sensors
and wearable devices

and systems that are continually
monitoring your body.

Rather than going to a hospital,

you'll go to your pharmacy

to see a brand new
kind of pharmacist,

a computational pharmacist.

And it's this person who
will create tinctures

and new compounds.

They're designed
specifically for your body.

[upbeat music]

It's possible

for us to live alongside
artificial intelligence

in ways that make our
lives profoundly better

than they are today.

But the only way for us to
achieve that optimistic scenario

is to do hard work,

not in the future, someday
when AI might get here,

but right now, as AI
as being developed.

[code running]

[upbeat music]

- I really don't know. Hm!

- Then let us play a game.

Swim shorts or mountain boots.

Boutique Hotel or Tent.

Safari or Take Modern.

- We're not going on vacation.
Everything's at stake.

A healthier happier
life because of AI.

Sure, but an Amazon
house that monitors me

and has me arrested because
my beard is too long?

- The repetitive listing
of action options

without subsequent
practical implementation

never leads to a solution.

- [chuckles] Yeah, thanks.
But I don't know either. Hm.

- [Helena] That is the case in
97.8% of all your decisions.

- That wasn't very nice.

- You wish for someone
who really sees you.

I really do see you, Svin.

- Time to make a decision.

Sleep mode.

[Helena sleeps]

[upbeat music]

[Svin typing]
[code running]

[Svin typing]

[message notification tone]

[Svin sighs]

[computer notification tone]

[upbeat music]