iHuman (2019)
Genre: Documentary, Technology, Artificial Intelligence
Director: Tonje Hessen Schei
Stars: Max Tegmark, Zeynep Tüfekçi, Elenore Pauwels
Synopsis: This documentary explores the rapidly advancing field of artificial intelligence, delving into its revolutionary opportunities and challenges. It examines AI’s potential impact on humanity, society, and global systems through interviews with leading researchers, thinkers, and activists in the field. A thought-provoking look at the promises and perils of AI technology.
The film premiered at the 2019 International Documentary Film Festival Amsterdam on 23 November.
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The Digital Conundrum: How iHuman Forces Us to Confront the AI Revolution
Artificial intelligence, once a concept confined to the realm of speculative science fiction, has now emerged as an omnipresent force that permeates almost every aspect of modern life. In iHuman, a thought-provoking and deeply unsettling documentary directed by Tonje Hessen Schei, the viewer is compelled to confront the staggering implications of this technological metamorphosis. Through an intricate tapestry of insights, interviews, and vivid imagery, the film lays bare the profound transformations wrought by artificial intelligence, underscoring both its boundless potential and its terrifying risks.
This documentary is an incisive examination of the societal, ethical, and existential dilemmas posed by AI. Schei deftly constructs a narrative that oscillates between cautious optimism and outright alarm, drawing on the perspectives of renowned scientists, technologists, and activists to present an unvarnished portrait of humanity’s uncertain future in the age of algorithms. Through interviews with a veritable who’s who of the AI world—figures like Max Tegmark, Stuart Russell, and Kara Swisher—iHuman provides an invaluable glimpse into the intellectual and philosophical underpinnings of this burgeoning field. These architects of intelligence are the shapers of a new epoch, individuals whose work will determine the trajectory of human existence for generations to come.
Yet, while their technical achievements are lauded, the film refuses to shy away from their limitations and the unintended consequences of their creations. Visionaries like Ilya Sutskever and Jürgen Schmidhuber extol the virtues of Artificial General Intelligence (AGI), envisioning a future where machines can surpass human cognitive abilities in every conceivable domain. However, this ambition is tempered by sobering reflections on the risks of misaligned incentives, uncontrolled development, and the inherent unpredictability of autonomous systems. The film paints AGI as a double-edged sword: it could either usher in an unprecedented golden age or render humanity obsolete, a relic of its own evolutionary misstep.
One of the most chilling aspects of iHuman is its exploration of the pervasive role AI already plays in surveillance. Schei meticulously dissects how governments and corporations alike are leveraging this technology to monitor, manipulate, and, in many cases, subjugate individuals. The documentary devotes significant attention to China’s social credit system, a dystopian program that quantifies the trustworthiness of citizens through a labyrinthine network of data points, facial recognition software, and behavioral tracking. The film starkly juxtaposes the promises of AI-enhanced security with its potential to erode fundamental freedoms. From predictive policing systems that disproportionately target marginalized communities to corporate surveillance programs that mine personal data for profit, the message is clear: the tools intended to safeguard society are increasingly being used to undermine its most vulnerable members. Schei masterfully critiques the opacity of these systems, emphasizing the profound ethical questions they raise. When algorithms make decisions about who receives bail, who gets a loan, or who is deemed a threat, who ensures their fairness? And when these decisions are cloaked in the inscrutable logic of machine learning, how do we hold anyone accountable?
The documentary explores the extraordinary concentration of power within a handful of tech giants—Google, Amazon, Facebook, and their ilk—whose influence over AI development has profound implications for society at large. These companies, iHuman argues, are not merely purveyors of technological progress; they are oligarchic entities wielding unprecedented control over the flow of information, the shaping of public opinion, and the commodification of human behavior. Through incisive commentary and alarming case studies, the film reveals how these corporations manipulate algorithms to influence elections, drive consumer behavior, and exploit psychological vulnerabilities. The infamous Cambridge Analytica scandal serves as a case in point, illustrating how AI-driven psychographic profiling can subvert democratic processes by tailoring propaganda to exploit individual fears and biases. Schei suggests that such practices are not anomalies but rather emblematic of a broader trend in which profit motives eclipse ethical considerations.
At its core, iHuman poses a series of profound questions that strike at the heart of what it means to be human in the age of intelligent machines. If AI is capable of surpassing human intelligence and creativity, what remains of our unique identity? And if the primary drivers of AI development are profit and power, how can we ensure that its benefits are equitably distributed? The film’s philosophical inquiry is both expansive and unsettling. It challenges the viewer to consider whether concepts such as free will, autonomy, and privacy can survive in a world dominated by algorithmic decision-making. Schei juxtaposes the utopian visions of AI advocates—who see the technology as a panacea for humanity’s most intractable problems—with the dystopian realities of its current applications, from autonomous weapons systems to deepfake technologies that blur the line between truth and deception.
iHuman does not merely present a litany of concerns; it issues a clarion call for global dialogue and action. Schei argues that the development and deployment of AI cannot be left to technocrats and corporate elites. Instead, it demands a robust framework of international governance, one that prioritizes transparency, accountability, and the preservation of human rights. The documentary makes a compelling case for the urgency of such measures, warning that the window for meaningful intervention is rapidly closing. As AI systems become more autonomous and pervasive, the risks of misuse, inequality, and unintended consequences multiply exponentially. Yet, as Schei acknowledges, regulating an inherently borderless and rapidly evolving technology presents challenges that defy easy solutions.
iHuman is not an easy film to watch, but it is an essential one. It forces us to confront the uncomfortable truths about the world we are building and the forces shaping it. Through its intricate and meticulously researched narrative, the documentary transforms artificial intelligence from an abstract concept into an immediate and pressing reality—one that demands our attention, our scrutiny, and our collective action.
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Transcript
Intelligence is the ability to understand.
We passed on what we know to machines.
The rise of artificial intelligence is happening fast, but some fear the new technology might have more problems than anticipated.
We will not control it.
Artificially intelligent algorithms are here, but this is only the beginning.
In the age of AI, data is the new oil.
Today, Amazon, Google and Facebook are richer and more powerful than any companies that have ever existed throughout human history.
A handful of people working at a handful of technology companies steer what a billion people are thinking today.
This technology is changing: What does it mean to be human?
Artificial intelligence is simply non-biological intelligence.
And intelligence itself is simply the ability to accomplish goals.
I’m convinced that AI will ultimately be either
the best thing ever to happen to humanity, or the worst thing ever to happen.
We can use it to solve all of today’s and tomorrow’s greatest problems; cure diseases, deal with climate change, lift everybody out of poverty.
But, we could use exactly the same technology to create a brutal global dictatorship with unprecedented surveillance and inequality and suffering.
That’s why this is the most important conversation of our time.
Artificial intelligence is everywhere because we now have thinking machines.
If you go on social media or online, there’s an artificial intelligence engine that decides what to recommend.
If you go on Facebook and you’re just scrolling through your friends’ posts,- there’s an AI engine that’s picking which one to show you first and which one to bury.
If you try to get insurance, there is an AI engine trying to figure out how risky you are.
And if you apply for a job, it’s quite possible that an AI engine looks at the resume.
We are made of data.
Every one of us is made of data -in terms of how we behave, how we talk, how we love, what we do every day.
So, computer scientists are developing deep learning algorithms that can learn to identify, classify, and predict patterns within massive amounts of data.
We are facing a form of precision surveillance, you could call it algorithmic surveillance, and it means that you cannot go unrecognized.
You are always under the watch of algorithms.
Almost all the AI development on the planet today is done by a handful of big technology companies or by a few large governments.
If we look at what AI is mostly being developed for, I would say it’s killing, spying, and brainwashing.
So, I mean, we have military AI, we have a whole surveillance apparatus being built using AI by major governments, and we have an advertising industry which is oriented toward recognizing what ads to try to sell to someone.
We humans have come to a fork in the road now.
The AI we have today is very narrow.
The holy grail of AI research ever since the beginning is to make AI that can do everything better than us, and we’ve basically built a God.
It’s going to revolutionize life as we know it.
It’s incredibly important to take a step back and think carefully about this.
What sort of society do we want?
So, we’re in this historic transformation.
Like we’re raising this new creature.
We have a new offspring of sorts.
But just like actual offspring, you don’t get to control everything it’s going to do.
We are living at this privileged moment where, for the first time, we will see probably that AI is really going to outcompete humans in many, many, if not all, important fields.
Everything is going to change.
A new form of life is emerging.
When I was a boy, I thought, how can I maximize my impact?
And then it was clear that I have to build something that learns to become smarter than myself, such that I can retire, and the smarter thing can further self-improve and solve all the problems that I cannot solve.
Multiplying that tiny little bit of creativity that I have into infinity, and that’s what has been driving me since then.
How am I trying to build a general purpose artificial intelligence?
If you want to be intelligent, you have to recognize speech, video and handwriting, and faces, and all kinds of things, and there we have made a lot of progress.
See, LSTM, neural networks, which we developed in our labs in Munich and in Switzerland, and it’s now used for speech recognition and translation, and video recognition.
They are now in everybody’s smartphone, almost one billion iPhones and in over two billion Android phones.
So, we are generating all kinds of useful by-products on the way to the general goal.
The main goal, some Artificial General Intelligence, an AGI that can learn to improve the learning algorithm itself.
So, it basically can learn to improve the way it learns
and it can also recursively improve the way it learns,
the way it learns without any limitations except for
the basic fundamental limitations of computability.
One of my favorite robots is this one here.
We use this robot for our studies of artificial curiosity.
Where we are trying to teach this robot to teach itself.
What is a baby doing?
A baby is curiously exploring its world.
That’s how he learns how gravity works
and how certain things topple, and so on.
And as it learns to ask questions about the world,
and as it learns to answer these questions,
it becomes a more and more general problem solver.
And so, our artificial systems are also learning
to ask all kinds of questions, not just slavishly
try to answer the questions given to them by humans.
You have to give AI the freedom to invent its own tasks.
If you don’t do that, it’s not going to become very smart.
On the other hand, it’s really hard to predict what they are going to do.
I feel that technology is a force of nature.
I feel like there is a lot of similarity between technology and biological evolution.
Playing God.
Scientists have been accused of playing God for a while,
but there is a real sense in which we are creating something
very different from anything we’ve created so far.
I was interested in the concept of AI from a relatively early age.
At some point, I got especially interested in machine learning.
What is experience?
What is learning?
What is thinking?
How does the brain work?
These questions are philosophical,
but it looks like we can come up with algorithms that
both do useful things and help us answer these questions.
Like it’s almost like applied philosophy.
Artificial General Intelligence, AGI.
A computer system that can do any job or any task
that a human does, but only better.
Yeah, I mean, we definitely will be able to create
completely autonomous beings with their own goals.
And it will be very important,
especially as these beings become much smarter than humans,
it’s going to be important to have these beings,
that the goals of these beings be aligned with our goals.
That’s what we’re trying to do at OpenAI.
Be at the forefront of research and steer the research,
steer their initial conditions so to maximize the chance
that the future will be good for humans.
Now, AI is a great thing because AI will solve
all the problems that we have today.
It will solve employment, it will solve disease,
it will solve poverty,
but it will also create new problems.
I think that…
The problem of fake news is going to be a thousand,
a million times worse.
Cyberattacks will become much more extreme.
You will have totally automated AI weapons.
I think AI has the potential to create infinitely stable dictatorships.
You’re gonna see dramatically more intelligent systems
in 10 or 15 years from now, and I think it’s highly likely
that those systems will have completely astronomical impact on society.
Will humans actually benefit?
And who will benefit, who will not?
In 2012, IBM estimated that
an average person is generating 500 megabytes
of digital footprints every single day.
Imagine that you wanted to back-up one day worth
of data that humanity is leaving behind, on paper.
How tall will be the stack of paper that contains
just one day worth of data that humanity is producing?
It’s like from the earth to the sun, four times over.
In 2025, we’ll be generating 62 gigabytes of data
per person, per day.
We’re leaving a ton of digital footprints while going through our lives.
They provide computer algorithms with a fairly good idea about who we are,
what we want, what we are doing.
In my work, I looked at different types of digital footprints.
I looked at Facebook likes, I looked at language,
credit card records, web browsing histories, search records.
and each time I found that if you get enough of this data,
you can accurately predict future behavior
and reveal important intimate traits.
This can be used in great ways,
but it can also be used to manipulate people.
Facebook is delivering daily information
to two billion people or more.
If you slightly change the functioning of the Facebook engine,
you can move the opinions and hence,
the votes of millions of people.
Brexit! When do we want it?
Now!
A politician wouldn’t be able to figure out
which message each one of his or her voters would like,
but a computer can see what political message
would be particularly convincing for you.
Ladies and gentlemen,
it’s my privilege to speak to you today about the power
of big data and psychographics in the electoral process.
Data from Cambridge Analytica
secretly harvested the personal information
of 50 million unsuspecting Facebook users.
USA!
The data firm hired by Donald Trump’s presidential election campaign
used secretly obtained information to directly target potential American voters.
With that, they say they can predict
the personality of every single adult in the United States.
Tonight we’re hearing from Cambridge Analytica
whistleblower, Christopher Wiley.
What we worked on was data harvesting programs
where we would pull data and run that data through algorithms that could profile
their personality traits and other psychological attributes
to exploit mental vulnerabilities that our algorithms showed that they had.
Cambridge Analytica mentioned once
or said that their models were based on my work,
but Cambridge Analytica is just one of the hundreds
of companies that are using such methods to target voters.
You know, I would be asked questions by journalists such as,
“So how do you feel about
“electing Trump and supporting Brexit?”
How do you answer to such question?
I guess that I have to deal with being blamed for all of it.
How tech started was as a democratizing force,
as a force for good, as an ability for humans
to interact with each other without gatekeepers.
There’s never been a bigger experiment in communications for the human race.
What happens when everybody gets to have their say?
You would assume that it would be for the better,
that there would be more democracy, there would be more discussion,
there would be more tolerance, but what’s happened is that
these systems have been hijacked.
We stand for connecting every person.
For a global community.
One company, Facebook, is responsible
for the communications of a lot of the human race.
Same thing with Google.
Everything you want know about the world comes from them.
This is global information economy
that is controlled by a small group of people.
The world’s richest companies are all technology companies.
Google, Apple, Microsoft, Amazon, Facebook.
It’s staggering how,
in probably just 10 years,
that the entire corporate power structure
are basically in the business of trading electrons.
These little bits and bytes are really the new currency.
The way that data is monetized
is happening all around us, even if it’s invisible to us.
Google has every amount of information available.
They track people by their GPS location.
They know exactly what your search history has been.
They know your political preferences.
Your search history alone can tell you
everything about an individual from their health problems
to their sexual preferences.
So, Google’s reach is unlimited.
So we’ve seen Google and Facebook
rise into these large surveillance machines
and they’re both actually ad brokers.
It sounds really mundane, but they’re high tech ad brokers.
And the reason they’re so profitable is that they’re using
artificial intelligence to process all this data about you,
and then to match you with the advertiser
that wants to reach people like you, for whatever message.
One of the problems with technology is that it’s been developed to be addictive.
The way these companies design these things
is in order to pull you in and engage you.
They want to become essentially a slot machine of attention.
So you’re always paying attention, you’re always jacked into the matrix,
you’re always checking.
When somebody controls what you read, they also control what you think.
You get more of what you’ve seen before and liked before,
because this gives more traffic and that gives more ads,
but it also locks you into your echo chamber.
And this is what leads to this polarization that we see today.
Jair Bolsonaro!
Jair Bolsonaro, Brazil’s right-wing
populist candidate sometimes likened to Donald Trump,
winning the presidency Sunday night in that country’s
most polarizing election in decades.
Bolsonaro!
What we are seeing around the world is upheaval and polarization and conflict
that is partially pushed by algorithms
that’s figured out that political extremes,
tribalism, and sort of shouting for your team,
and feeling good about it, is engaging.
Social media may be adding to the attention
to hate crimes around the globe.
It’s about how people can become radicalized
by living in the fever swamps of the Internet.
So is this a key moment for the tech giants? Are they now prepared to take responsibility
as publishers for what they share with the world?
If you deploy a powerful potent technology
at scale, and if you’re talking about Google and Facebook,
you’re deploying things at scale of billions.
If your artificial intelligence is pushing polarization,
you have global upheaval potentially.
White lives matter!
Black lives matter!
Artificial General Intelligence, AGI.
Imagine your smartest friend,
with 1,000 friends, just as smart,
and then run them at a 1,000 times faster than real time.
So it means that in every day of our time,
they will do three years of thinking.
Can you imagine how much you could do
if, for every day, you could do three years’ worth of work?
It wouldn’t be an unfair comparison to say
that what we have right now is even more exciting than
the quantum physicists of the early 20th century.
They discovered nuclear power.
I feel extremely lucky to be taking part in this.
Many machine learning experts, who are very knowledgeable and experienced,
have a lot of skepticism about AGI.
About when it would happen, and about whether it could happen at all.
But right now, this is something that just not that many people have realized yet.
That the speed of computers, for neural networks, for AI,
are going to become maybe 100,000 times faster
in a small number of years.
The entire hardware industry for a long time
didn’t really know what to do next,
but with artificial neural networks, now that they actually work,
you have a reason to build huge computers.
You can build a brain in silicon, it’s possible.
The very first AGIs will be basically very,
very large data centers packed with specialized
neural network processors working in parallel.
Compact, hot, power hungry package,
consuming like 10 million homes’ worth of energy.
A roast beef sandwich.
Yeah, something slightly different.
Just this once.
Even the very first AGIs
will be dramatically more capable than humans.
Humans will no longer be economically useful for nearly any task.
Why would you want to hire a human,
if you could just get a computer that’s going to do it much better and much more cheaply?
AGI is going to be like, without question,
the most important technology in the history
of the planet by a huge margin.
It’s going to be bigger than electricity, nuclear,
and the Internet combined.
In fact, you could say that the whole purpose
of all human science, the purpose of computer science,
the End Game, this is the End Game, to build this.
And it’s going to be built.
It’s going to be a new life form.
It’s going to be…
It’s going to make us obsolete.
European manufacturers know the Americans
have invested heavily in the necessary hardware.
Step into a brave new world of power,
performance and productivity.
All of the images you are about to see on the large screen
will be generated by what’s in that Macintosh.
It’s my honor and privilege to introduce to you
the Windows 95 Development Team.
Human physical labor has been mostly obsolete for
getting on for a century.
Routine human mental labor is rapidly becoming obsolete
and that’s why we’re seeing a lot of the middle class jobs disappearing.
Every once in a while,
a revolutionary product comes along that changes everything.
Today, Apple is reinventing the phone.
Machine intelligence is already all around us.
The list of things that we humans can do better than machines
is actually shrinking pretty fast.
Driverless cars are great.
They probably will reduce accidents.
Except, alongside with that, in the United States,
you’re going to lose 10 million jobs.
What are you going to do with 10 million unemployed people?
The risk for social conflict and tensions,
if you exacerbate inequalities, is very, very high.
AGI can, by definition,
do all jobs better than we can do.
People who are saying, “There will always be jobs
“that humans can do better than machines,” are simply
betting against science and saying there will never be AGI.
What we are seeing now is like a train hurtling
down a dark tunnel at breakneck speed and it looks like
we’re sleeping at the wheel.
A large fraction of the digital footprints we’re leaving behind are digital images.
And specifically, what’s really interesting to me as a psychologist
are digital images of our faces.
Here you can see the difference in the facial outline
of an average gay and an average straight face.
And you can see that straight men
have slightly broader jaws.
Gay women have slightly larger jaws, compared with straight women.
Computer algorithms can reveal our political views
or sexual orientation, or intelligence,
just based on the picture of our faces.
Even a human brain can distinguish between gay and straight men with some accuracy.
Now it turns out that the computer can do it with much higher accuracy.
What you’re seeing here is an accuracy of
off-the-shelf facial recognition software.
This is terrible news
for gay men and women all around the world.
And not only gay men and women,
because the same algorithms can be used to detect other
intimate traits, think being a member of the opposition,
or being a liberal, or being an atheist.
Being an atheist is also punishable by death
in Saudi Arabia, for instance.
My mission as an academic is to warn people about the dangers of algorithms
being able to reveal our intimate traits.
The problem is that when people receive bad news,
they very often choose to dismiss them.
Well, it’s a bit scary when you start receiving death threats from one day to another,
and I’ve received quite a few death threats, –
-but as a scientist, I have to basically show what is possible.
So what I’m really interested in now is to try to see
whether we can predict other traits from people’s faces.
Now, if you can detect depression from a face,
or suicidal thoughts, maybe a CCTV system
on the train station can save some lives.
What if we could predict that someone is more prone to commit a crime?
You probably had a school counselor,
a psychologist hired there to identify children
that potentially may have some behavioral problems.
So now imagine if you could predict with high accuracy
that someone is likely to commit a crime in the future
from the language use, from the face,
from the facial expressions, from the likes on Facebook.
I’m not developing new methods, I’m just describing
something or testing something in an academic environment.
But there obviously is a chance that,
while warning people against risks of new technologies,
I may also give some people new ideas.
We haven’t yet seen the future in terms of
the ways in which the new data-driven society
is going to really evolve.
The tech companies want to get every possible bit
of information that they can collect on everyone
to facilitate business.
The police and the military want to do the same thing
to facilitate security.
The interests that the two have in common are immense,
and so the extent of collaboration between what you might
call the Military-Tech Complex is growing dramatically.
The CIA, for a very long time,
has maintained a close connection with Silicon Valley.
Their venture capital firm known as In-Q-Tel,
makes seed investments to start-up companies developing
breakthrough technology that the CIA hopes to deploy.
Palantir, the big data analytics firm,
one of their first seed investments was from In-Q-Tel.
In-Q-Tel has struck gold in Palantir
in helping to create a private vendor
that has intelligence and artificial intelligence
capabilities that the government can’t even compete with.
Good evening, I’m Peter Thiel.
I’m not a politician, but neither is Donald Trump.
He is a builder and it’s time to rebuild America.
Peter Thiel, the founder of Palantir,
was a Donald Trump transition advisor
and a close friend and donor.
Trump was elected largely on the promise
to deport millions of immigrants.
The only way you can do that is with a lot of intelligence
and that’s where Palantir comes in.
They ingest huge troves of data, which include,
where you live, where you work, who you know,
who your neighbors are, who your family is,
where you have visited, where you stay,
your social media profile.
Palantir gets all of that and is remarkably good
at structuring it in a way that helps law enforcement,
immigration authorities or intelligence agencies
of any kind, track you, find you,
and learn everything there is to know about you.
We’re putting AI in charge now of evermore
important decisions that affect people’s lives.
Old-school AI used to have its intelligence programmed in
by humans who understood how it worked, but today,
powerful AI systems have just learned for themselves,
and we have no clue really how they work,
which makes it really hard to trust them.
This isn’t some futuristic technology, this is now.
AI might help determine where a fire department
is built in a community or where a school is built.
It might decide whether you get bail,
or whether you stay in jail.
It might decide where the police are going to be.
It might decide whether you’re going to be under additional police scrutiny.
It’s popular now in the US to do predictive policing.
So what they do is they use an algorithm to figure out where crime will be,
and they use that to tell where we should send police officers.
So that’s based on a measurement of crime rate.
So we know that there is bias.
Black people and Hispanic people are pulled over,
and stopped by the police officers more frequently
than white people are, so we have this biased data going in,
and then what happens is you use that to say,
“Here’s where the cops should go.”
Well, the cops go to those neighborhoods, and guess what they do, they arrest people.
And then it feeds back biased data into the system,
and that’s called a feedback loop.
Predictive policing leads at the extremes
to experts saying, “Show me your baby,
“and I will tell you whether she’s going to be a criminal.”
Now that we can predict it, we’re going to then surveil
those kids much more closely and we’re going to jump on them
at the first sign of a problem.
And that’s going to make for more effective policing.
It does, but it’s going to make for a really grim society
and it’s reinforcing dramatically existing injustices.
Imagine a world in which networks of CCTV cameras,
drone surveillance cameras, have sophisticated
face recognition technologies and are connected
to other government surveillance databases.
We will have the technology in place to have
all of our movements comprehensively tracked and recorded.
What that also means is that we will have
created a surveillance time machine
that will allow governments and powerful corporations
to essentially hit rewind on our lives.
We might not be under any suspicion now
and five years from now, they might want to know
more about us, and can then recreate granularly
everything we’ve done, everyone we’ve seen,
everyone we’ve been around over that entire period.
That’s an extraordinary amount of power
for us to seed to anyone.
And it’s a world that I think has been difficult
for people to imagine, but we’ve already built
the architecture to enable that.
I’m a political reporter and I’m very interested
in the ways powerful industries use their political power
to influence the public policy process.
The large tech companies and their lobbyists get together
behind closed doors and are able to craft policies
that we all have to live under.
That’s true for surveillance policies, for policies in terms of data collection,
but also increasingly important when it comes to military and foreign policy.
Starting in 2016, the Defense Department formed the Defense Innovation Board.
That’s a special body created to bring top tech executives
into closer contact with the military.
Eric Schmidt, former chairman of Alphabet,
the parent company of Google,
became the chairman of the Defense Innovation Board,
and one of their first priorities was to say,
“We need more artificial intelligence integrated into the military.”
I’ve worked with a group of volunteers over the
last couple of years to take a look at innovation in the
overall military, and my summary conclusion is that we have
fantastic people who are trapped in a very bad system.
From the Department of Defense’s perspective,
where I really started to get interested in it
was when we started thinking about Unmanned Systems and
how robotic and unmanned systems would start to change war.
The smarter you made the Unmanned Systems and robots,
the more powerful you might be able to make your military.
Under Secretary of Defense,
Robert Work put together a major memo known as
the Algorithmic Warfare Cross-Functional Team,
better known as Project Maven.
Eric Schmidt gave a number of speeches and media appearances
where he said this effort was designed to increase fuel
efficiency in the Air Force, to help with the logistics,
but behind closed doors there was another parallel effort.
Late in 2017 as part of Project Maven,
Google, Eric Schmidt’s firm, was tasked to secretly work
on another part of Project Maven,
and that was to take the vast volumes of image data vacuumed up
by drones operating in Iraq and Afghanistan and to teach an AI
to quickly identify targets on the battlefield.
We have a sensor and the sensor can do full motion video of an entire city.
And we would have three seven-person teams working
constantly and they could process 15% of the information.
The other 85% of the information was just left
on the cutting room floor, so we said, “Hey, AI and machine learning
“would help us process 100% of the information.”
Google has long had the motto, “Don’t be evil.”
They have created a public image
that they are devoted to public transparency.
But for Google to slowly transform into a defense contractor,
they maintained the utmost secrecy.
And you had Google entering into this contract with most of the employees,
even employees who were working on the program completely left in the dark.
Usually within Google, anyone in the company
is allowed to know about any other project that’s happening
in some other part of the company.
With Project Maven, the fact that it was kept secret,
I think was alarming to people because that’s not the norm at Google.
When this story was first revealed,
it set off a firestorm within Google.
You had a number of employees quitting in protests,
others signing a petition objecting to this work.
You have to really say, “I don’t want to be part of this anymore.”
There are companies called defense contractors
and Google should just not be one of those companies
because people need to trust Google for Google to work.
Good morning and welcome to Google I/O.
We’ve seen emails that show that Google simply
continued to mislead their employees that the drone
targeting program was only a minor effort that could at most
be worth $9 million to the firm, which is drops in the bucket
for a gigantic company like Google.
But from internal emails that we obtained,
Google was expecting Project Maven would ramp up to as much
as $250 million, and that this entire effort would provide
Google with Special Defense Department certification to make
them available for even bigger defense contracts,
some worth as much as $10 billion.
The pressure for Google to compete for military contracts
has come at a time when its competitors are also shifting their culture.
Amazon, similarly pitching the military and law enforcement.
IBM and other leading firms,
they’re pitching law enforcement and military.
To stay competitive, Google has slowly transformed.
The Defense Science Board said of all of the
technological advances that are happening right now,
the single most important thing was artificial intelligence
and the autonomous operations that it would lead.
Are we investing enough?
Once we develop what are known as
autonomous lethal weapons, in other words,
weapons that are not controlled at all, they are genuinely autonomous,
you’ve only got to get a president who says,
“The hell with international law, we’ve got these weapons.
“We’re going to do what we want with them.”
We’re very close.
When you have the hardware already set up
and all you have to do is flip a switch to make it fully autonomous,
what is it there that’s stopping you from doing that?
There’s something really to be feared in war at machine speed.
What if you’re a machine and you’ve run millions and millions of different war scenarios
and you have a team of drones and you’ve delegated control to half of them,
and you’re collaborating in real time?
What happens when that swarm of drones is tasked with engaging a city?
How will they take over that city?
The answer is we won’t know until it happens.
We do not want an AI system to decide
what human it would attack,
but we’re going up against authoritarian competitors.
So in my view, an authoritarian regime
will have less problem delegating authority
to a machine to make lethal decisions.
So how that plays out remains to be seen.
Almost the gift of AI now is that it will force us
collectively to think through at a very basic level,
what does it mean to be human?
What do I do as a human better
than a certain super smart machine can do?
First, we create our technology and then it recreates us.
We need to make sure that we don’t miss some of the things
that make us so beautiful human.
Once we build intelligent machines,
the philosophical vocabulary we have available to think
about ourselves as human increasingly fails us.
If I ask you to write up a list of all the terms you have
available to describe yourself as human,
there are not so many terms.
Culture, history, sociality, maybe politics, civilization,
subjectivity, all of these terms ground in two positions
that humans are more than mere animals
and that humans are more than mere machines.
But if machines truly think there is a large set
of key philosophical questions in which what is at stake is:
Who are we? What is our place in the world? What is the world? How is it structured?
Do the categories that we have relied on
Do they still work? Were they wrong?
Many people think of intelligence as something mysterious
that can only exist inside of biological organisms, like us,
but intelligence is all about information processing.
It doesn’t matter whether the intelligence is processed
by carbon atoms inside of cells and brains, and people,
or by silicon atoms in computers.
Part of the success of AI recently has come
from stealing great ideas from evolution.
We noticed that the brain, for example,
has all these neurons inside connected in complicated ways.
So we stole that idea and abstracted it
into artificial neural networks in computers,
and that’s what has revolutionized machine intelligence.
If we one day get Artificial General Intelligence,
then by definition, AI can also do better the job of AI
programming and that means that further progress in making
AI will be dominated not by human programmers, but by AI.
Recursively self-improving AI could leave human intelligence
far behind, creating super intelligence.
It’s gonna be the last invention we ever need to make,
because it can then invent everything else
much faster than we could.
There is a future that we all need to talk about.
Some of the fundamental questions about the future
of artificial intelligence, not just where it’s going,
but what it means for society to go there.
It is not what computers can do,
but what computers should do.
As the generation of people that is bringing AI to the future,
we are the generation that will answer this question first and foremost.
We haven’t created the human-level thinking machine yet,
but we get closer and closer.
Maybe we’ll get to human-level AI in five years from now
or maybe it’ll take 50 or 100 years from now.
It almost doesn’t matter. Like these are all really, really soon,
in terms of the overall history of humanity.
Very nice.
So, the AI field is extremely international.
China is up and coming and it’s starting to rival the US,
Europe and Japan in terms of putting a lot
of processing power behind AI
and gathering a lot of data to help AI learn.
We have a young generation of Chinese researchers now.
Nobody knows where the next revolution is going to come from.
China always wanted to become the superpower in the world.
The Chinese government thinks AI gave them the chance to become
one of the most advanced technology wise, business wise.
So the Chinese government look at this as a huge opportunity.
Like they’ve raised a flag and said, “That’s a good field.
“The companies should jump into it.”
Then China’s commercial world and companies say,
“Okay, the government raised a flag, that’s good.
“Let’s put the money into it.”
Chinese tech giants, like Baidu, like Tencent and like AliBaba,
they put a lot of the investment into the AI field.
So we see that China’s AI development is booming.
In China, everybody has Alipay and WeChat pay,
so mobile payment is everywhere.
And with that, they can do a lot of AI analysis
to know like your spending habits, your credit rating.
Face recognition technology is widely adopted in China,
in airports and train stations.
So, in the future, maybe in just a few months,
you don’t need a paper ticket to board a train.
Only your face.
We generate the world’s biggest platform of facial recognition.
We have 300,000 developers using our platform.
A lot of it is selfie camera apps.
It makes you look more beautiful.
There are millions and millions of cameras in the world,
each camera from my point is a data generator.
In a machine’s eye, your face will change into the features
and it will turn your face into a paragraph of code.
So we can detect how old you are, if you’re male or female,
and your emotions.
Shopping is about what kind of thing you are looking at.
We can track your eyeballs, so if you are focusing on some product,
we can track that so that we can know
which kind of people like which kind of product.
Our mission is to create a platform
that will enable millions of AI developers in China.
We study all the data we can get.
Not just user profiles,
but what you are doing at the moment,
your geographical location.
This platform will be so valuable that we don’t even worry about profit now,
because it is definitely there.
China’s social credit system is just one of the applications.
The Chinese government is using multiple
different kinds of technologies, whether it’s AI,
whether it’s big data platforms, facial recognition,
voice recognition, essentially to monitor
what the population is doing.
I think the Chinese government has made very clear
its intent to gather massive amounts of data about people
to socially engineer a dissent-free society.
The logic behind the Chinese government’s
social credit system, it’s to take the idea that
whether you are credit worthy for a financial loan
and adding to it a very political dimension to say,
“Are you a trustworthy human being?
“What you’ve said online, have you ever been critical of the authorities?
“Do you have a criminal record?”
And all that information is packaged up together to rate
you in ways that if you have performed well in their view,
you’ll have easier access to certain kinds of state services or benefits.
But if you haven’t done very well,
you are going to be penalized or restricted.
There’s no way for people to challenge those designations
or, in some cases, even know that they’ve been put in that category,
and it’s not until they try to access some kind of state service or buy a plane ticket,
or get a passport, or enroll their kid in school,
that they come to learn that they’ve been labeled in this way,
and that there are negative consequences for them as a result.
We’ve spent the better part of the last one or two years
looking at abuses of surveillance technology across China,
and a lot of that work has taken us to Xinjiang,
the Northwestern region of China that has a more than half
population of Turkic Muslims, Uyghurs, Kazakhs and Hui.
This is a region and a population the Chinese government
has long considered to be politically suspect or disloyal.
We came to find information about what’s called
the Integrated Joint Operations Platform,
which is a predictive policing program and that’s one
of the programs that has been spitting out lists of names
of people to be subjected to political re-education.
A number of our interviewees for the report we just released
about the political education camps in Xinjiang just
painted an extraordinary portrait of a surveillance state.
A region awash in surveillance cameras
for facial recognition purposes, checkpoints, body scanners,
QR codes outside people’s homes.
Yeah, it really is the stuff of dystopian movies that we’ve all gone to and thought,
“Wow, that would be a creepy world to live in.”
Yeah, well, 13 million Turkic Muslims in China
are living in that reality right now.
The Intercept reports that Google is planning to
launch a censored version of its search engine in China.
Google’s search for new markets leads it
to China, despite Beijing’s rules on censorship.
Tell us more about why you felt it was
your ethical responsibility to resign,
because you talk about being complicit in censorship and oppression, and surveillance.
There is a Chinese venture company that has to be
set up for Google to operate in China.
And the question is, to what degree did they get to control
the blacklist and to what degree would they have just
unfettered access to surveilling Chinese citizens?
And the fact that Google refuses to respond
to human rights organizations on this,
I think should be extremely disturbing to everyone.
Due to my conviction that dissent is fundamental to functioning democracies
and forced to resign in order to avoid contributing to or profiting from the erosion
of protections for dissidents.
The UN is currently reporting that between
200,000 and one million Uyghurs have been disappeared
into re-education camps.
And there is a serious argument that Google would be complicit
should it launch a surveilled version of search in China.
Dragonfly is a project meant to launch search in China under
Chinese government regulations, which include censoring
sensitive content, basic queries on human rights,
information about political representatives is blocked,
information about student protests is blocked.
And that’s one small part of it.
Perhaps a deeper concern is the surveillance side of this.
When I raised the issue with my managers, with my colleagues,
there was a lot of concern, but everyone just said, “I don’t know anything.”
And then when there was a meeting finally,
there was essentially no addressing the serious concerns associated with it.
So then I filed my formal resignation,
not just to my manager, but I actually distributed it company-wide.
And that’s the letter that I was reading from.
Personally, I haven’t slept well. I’ve had pretty horrific headaches,
wake up in the middle of the night just sweating.
With that said, what I found since speaking out
is just how positive the global response to this has been.
Engineers should demand to know what the uses
of their technical contributions are
and to have a seat at the table in those ethical decisions.
Most citizens don’t really understand what it means to be
in a very large scale prescriptive technology.
Where someone has already pre-divided the work
and all you know about is your little piece,
and almost certainly you don’t understand how it fits in.
So, I think it’s worth drawing the analogy to physicists’ work on the atomic bomb.
In fact, that’s actually the community I came out of.
I wasn’t a nuclear scientist by any means, but I was an applied mathematician
and my PhD program was actually funded to train people to work in weapons labs.
One could certainly argue that there is an existential threat and whoever is leading in AI will lead militarily.
China fully expects to pass the United States as the number one economy in the world and it believes that AI will make that jump more quickly and more dramatically.
And they also see it as being able to leapfrog the United States in terms of military power.
Their plan is very simple.
We want to catch the United States and these technologies by 2020, we want to surpass the United States in these technologies by 2025, and we want to be the world leader in AI and autonomous technologies by 2030.
It is a national plan.
It is backed up by at least $150 billion in investments.
So, this is definitely a race.
AI is a little bit like fire.
Fire was invented 700,000 years ago, and it has its pros and cons.
People realized you can use fire to keep warm at night and to cook, but they also realized that you can kill other people with that.
Fire also has this AI-like quality of growing
in a wildfire without further human ado,
but the advantages outweigh the disadvantages by so much
that we are not going to stop its development.
Europe is waking up.
Lots of companies in Europe are realizing that the next wave of AI
will be much bigger than the current wave.
The next wave of AI will be about robots.
All these machines that make things, that produce stuff,
that build other machines, they are going to become smart.
In the not-so-distant future, we will have robots
that we can teach like we teach kids.
For example, I will talk to a little robot and I will say,
“Look here, robot, look here.
“Let’s assemble a smartphone.
“We take this slab of plastic like that and we takes a screwdriver like that,
“and now we screw in everything like this.
“No, no, not like this.
“Like this, look, robot, look, like this.”
And he will fail a couple of times but rather quickly,
he will learn to do the same thing much better than I could do it.
And then we stop the learning and we make a million copies, and sell it.
Regulation of AI sounds like an attractive idea,
but I don’t think it’s possible.
One of the reasons why it won’t work is
the sheer curiosity of scientists.
They don’t give a damn for regulation.
Military powers won’t give a damn for regulations, either.
They will say, “If we, the Americans don’t do it,
“then the Chinese will do it.”
And the Chinese will say, “If we don’t do it,
“then the Russians will do it.”
No matter what kind of political regulation is out there,
all these military industrial complexes,
they will almost by definition have to ignore that
because they want to avoid falling behind.
Welcome to Xinhua.
I’m the world’s first female AI news anchor developed
jointly by Xinhua and search engine company Sogou.
A program developed by the company OpenAI can write
coherent and credible stories just like human beings.
It’s one small step for machine,
one giant leap for machine kind.
IBM’s newest artificial intelligence system took on
experienced human debaters and won a live debate.
Computer-generated videos known as deep fakes
are being used to put women’s faces on pornographic videos.
Artificial intelligence evolves at a very crazy pace.
You know, it’s like progressing so fast.
In some ways, we’re only at the beginning right now.
You have so many potential applications, it’s a gold mine.
Since 2012, when deep learning became a big game changer
in the computer vision community,
we were one of the first to actually adopt deep learning
and apply it in the field of computer graphics.
A lot of our research is funded by government, military intelligence agencies.
The way we create these photoreal mappings,
usually the way it works is that we need two subjects,
a source and a target, and I can do a face replacement.
One of the applications is, for example, I want to manipulate someone’s face
saying things that he did not.
It can be used for creative things, for funny contents,
but obviously, it can also be used for just simply
manipulate videos and generate fake news.
This can be very dangerous.
If it gets into the wrong hands, it can get out of control very quickly.
We’re entering an era in which our enemies can
make it look like anyone is saying anything at any point in time,
even if they would never say those things.
Moving forward, we need to be more vigilant with what we trust from the Internet.
It may sound basic, but how we move forward
in the age of information is going to be the difference
between whether we survive or whether we become
some kind of fucked up dystopia.
One criticism that is frequently raised against my work is saying that,
“Hey, you know there were stupid ideas in the past like phrenology or physiognomy.-
“There were people claiming that you can read a character
“of a person just based on their face.”
People would say, “This is rubbish.
“We know it was just thinly veiled racism and superstition.”
But the fact that someone made a claim in the past
and tried to support this claim with invalid reasoning,
doesn’t automatically invalidate the claim.
Of course, people should have rights
to their privacy when it comes to sexual orientation or political views,
but I’m also afraid that in the current technological environment,
this is essentially impossible.
People should realize there’s no going back.
There’s no running away from the algorithms.
The sooner we accept the inevitable and inconvenient truth
that privacy is gone,
the sooner we can actually start thinking about
how to make sure that our societies
are ready for the Post-Privacy Age.
While speaking about facial recognition,
in my deep thoughts, I sometimes get to the very dark era of our history.
When the people had to live in the system,
where some part of the society was accepted
and some part of the society was accused to death.
What would Mengele do to have such an instrument in his hands?
It would be very quick and efficient for selection and this is the apocalyptic vision.
So in the near future, the entire story of you will exist in a vast array of connected databases of faces, genomes, behaviors and emotion.
So, you will have a digital avatar of yourself online, which records how well you are doing as a citizen, what kind of a relationship do you have, what kind of political orientation and sexual orientation.
Based on all of those data, those algorithms will be able to manipulate your behavior with an extreme precision, changing how we think and probably in the future, how we feel.
The beliefs and desires of the first AGIs will be extremely important.
So, it’s important to program them correctly.
I think that if this is not done, then the nature of evolution of natural selection will favor those systems, prioritize their own survival above all else.
It’s not that it’s going to actively hate humans and want to harm them,
but it’s just going to be too powerful
and I think a good analogy would be the way humans treat animals.
It’s not that we hate animals.
I think humans love animals and have a lot of affection for them,
but when the time comes to build a highway between two cities,
we are not asking the animals for permission.
We just do it because it’s important for us.
And I think by default, that’s the kind of relationship that’s going to be between us
and AGIs which are truly autonomous and operating on their own behalf.
If you have an arms-race dynamics between multiple kings
trying to build the AGI first,
they will have less time to make sure that the AGI that they build
will care deeply for humans.
Because the way I imagine it is that there is an avalanche,
there is an avalanche of AGI development.
Imagine it’s a huge unstoppable force.
And I think it’s pretty likely the entire surface of the
earth would be covered with solar panels and data centers.
Given these kinds of concerns,
it will be important that the AGI is somehow built
as a cooperation with multiple countries.
The future is going to be good for the AIs, regardless.
It would be nice if it would be good for humans as well.
Is there a lot of responsibility weighing on my shoulders?
Not really.
Was there a lot of responsibility on the shoulders
of the parents of Einstein?
The parents somehow made him,
but they had no way of predicting what he would do,
and how he would change the world.
And so, you can’t really hold them responsible for that.
So, I’m not a very human-centric person.
I think I’m a little stepping stone in the evolution
of the Universe towards higher complexity.
But it’s also clear to me that I’m not the crown of creation
and that humankind as a whole is not the crown of creation,
but we are setting the stage for something that is bigger than us that transcends us.
And then will go out there in a way where humans cannot follow
and transform the entire Universe, or at least, the reachable Universe.
So, I find beauty and awe in seeing myself
as part of this much grander theme.
AI is inevitable.
We need to make sure we have the necessary human regulation
to prevent the weaponization of artificial intelligence.
We don’t need any more weaponization
of such a powerful tool.
One of the most critical things, I think, is the need for international governance.
We have an imbalance of power here because now
we have corporations with more power, might and ability,
than entire countries.
How do we make sure that people’s voices are getting heard?
It can’t be a law-free zone.
It can’t be a rights-free zone.
We can’t embrace all of these wonderful new technologies
for the 21st century without trying to bring with us
the package of human rights that we fought so hard
to achieve, and that remains so fragile.
AI isn’t good and it isn’t evil, either.
It’s just going to amplify the desires and goals of whoever controls it.
And AI today is under the control of a very, very small group of people.
The most important question that we humans have to ask ourselves at this point in history
requires no technical knowledge.
It’s the question of what sort of future society do we want to create
with all this technology we’re making?
What do we want the role of humans to be in this world?
