Why Technology Favors Tyranny
Artificial
intelligence could erase many practical advantages of democracy, and erode the
ideals of liberty and equality. It will further concentrate power among a small
elite if we don’t take steps to stop it.
Yoshi Sodeoka
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Editor’s Note: This article is part
of a series that attempts to answer the
question: Is democracy dying?
I. The Growing Fear of Irrelevance
There is nothing inevitable about
democracy. For all the success that democracies have had over the past century
or more, they are blips in history. Monarchies, oligarchies, and other forms of
authoritarian rule have been far more common modes of human governance.
The emergence of liberal
democracies is associated with ideals of liberty and equality that may seem
self-evident and irreversible. But these ideals are far more fragile than we
believe. Their success in the 20th century depended on unique technological
conditions that may prove ephemeral.
In the second decade of
the 21st century, liberalism has begun to lose credibility. Questions about the
ability of liberal democracy to provide for the middle class have grown louder;
politics have grown more tribal; and in more and more countries, leaders are
showing a penchant for demagoguery and autocracy. The causes of this political
shift are complex, but they appear to be intertwined with current technological
developments. The technology that favored democracy is changing, and as
artificial intelligence develops, it might change further.
Information technology
is continuing to leap forward; biotechnology is beginning to provide a window
into our inner lives—our emotions, thoughts, and choices. Together, infotech
and biotech will create unprecedented upheavals in human society, eroding human
agency and, possibly, subverting human desires. Under such conditions, liberal
democracy and free-market economics might become obsolete.
FROM OUR OCTOBER 2018 ISSUE
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Ordinary people may not
understand artificial intelligence and biotechnology in any detail, but they
can sense that the future is passing them by. In 1938 the common man’s
condition in the Soviet Union, Germany, or the United States may have been
grim, but he was constantly told that he was the most important thing in the
world, and that he was the future (provided, of course, that he was an
“ordinary man,” rather than, say, a Jew or a woman). He looked at the
propaganda posters—which typically depicted coal miners and steelworkers in
heroic poses—and saw himself there: “I am in that poster! I am the hero of the
future!”
In 2018 the common
person feels increasingly irrelevant. Lots of mysterious terms are bandied
about excitedly in ted Talks,
at government think tanks, and at high-tech conferences—globalization, blockchain, genetic
engineering, AI, machine learning—and common
people, both men and women, may well suspect that none of these terms is about
them.
In the 20th century, the
masses revolted against exploitation and sought to translate their vital role
in the economy into political power. Now the masses fear irrelevance, and they
are frantic to use their remaining political power before it is too late.
Brexit and the rise of Donald Trump may therefore demonstrate a trajectory
opposite to that of traditional socialist revolutions. The Russian, Chinese,
and Cuban revolutions were made by people who were vital to the economy but
lacked political power; in 2016, Trump and Brexit were supported by many people
who still enjoyed political power but feared they were losing their economic
worth. Perhaps in the 21st century, populist revolts will be staged not against
an economic elite that exploits people but against an economic elite that does
not need them anymore. This may well be a losing battle. It is much harder to
struggle against irrelevance than against exploitation.
The revolutions in
information technology and biotechnology are still in their infancy, and the
extent to which they are responsible for the current crisis of liberalism is
debatable. Most people in Birmingham, Istanbul, St. Petersburg, and Mumbai are
only dimly aware, if they are aware at all, of the rise of AI and its potential
impact on their lives. It is undoubtable, however, that the technological
revolutions now gathering momentum will in the next few decades confront
humankind with the hardest trials it has yet encountered.
II. A New Useless Class?
Let’s start with jobs and incomes, because whatever
liberal democracy’s philosophical appeal, it has gained strength in no small
part thanks to a practical advantage: The decentralized approach to decision
making that is characteristic of liberalism—in both politics and economics—has
allowed liberal democracies to outcompete other states, and to deliver rising
affluence to their people.
Liberalism reconciled
the proletariat with the bourgeoisie, the faithful with atheists, natives with
immigrants, and Europeans with Asians by promising everybody a larger slice of
the pie. With a constantly growing pie, that was possible. And the pie may well
keep growing. However, economic growth may not solve social problems that are
now being created by technological disruption, because such growth is
increasingly predicated on the invention of more and more disruptive
technologies.
Fears of machines
pushing people out of the job market are, of course, nothing new, and in the
past such fears proved to be unfounded. But artificial intelligence is different
from the old machines. In the past, machines competed with humans mainly in
manual skills. Now they are beginning to compete with us in cognitive skills.
And we don’t know of any third kind of skill—beyond the manual and the
cognitive—in which humans will always have an edge.
At least for a few more
decades, human intelligence is likely to far exceed computer intelligence in
numerous fields. Hence as computers take over more routine cognitive jobs, new
creative jobs for humans will continue to appear. Many of these new jobs will
probably depend on cooperation rather than competition between humans and AI.
Human-AI teams will likely prove superior not just to humans, but also to
computers working on their own.
However, most of the new
jobs will presumably demand high levels of expertise and ingenuity, and
therefore may not provide an answer to the problem of unemployed unskilled
laborers, or workers employable only at extremely low wages. Moreover, as AI
continues to improve, even jobs that demand high intelligence and creativity
might gradually disappear. The world of chess serves as an example of where
things might be heading. For several years after IBM’s computer Deep Blue
defeated Garry Kasparov in 1997, human chess players still flourished; AI was
used to train human prodigies, and teams composed of humans plus computers
proved superior to computers playing alone.
Yet in recent years,
computers have become so good at playing chess that their human collaborators
have lost their value and might soon become entirely irrelevant. On December 6,
2017, another crucial milestone was reached when Google’s AlphaZero program
defeated the Stockfish 8 program. Stockfish 8 had won a world computer chess
championship in 2016. It had access to centuries of accumulated human
experience in chess, as well as decades of computer experience. By contrast,
AlphaZero had not been taught any chess strategies by its human creators—not
even standard openings. Rather, it used the latest machine-learning principles
to teach itself chess by playing against itself. Nevertheless, out of 100 games
that the novice AlphaZero played against Stockfish 8, AlphaZero won 28 and tied
72—it didn’t lose once. Since AlphaZero had learned nothing from any human,
many of its winning moves and strategies seemed unconventional to the human
eye. They could be described as creative, if not downright genius.
Can you guess how long AlphaZero
spent learning chess from scratch, preparing for the match against Stockfish 8,
and developing its genius instincts? Four hours. For centuries, chess was
considered one of the crowning glories of human intelligence. AlphaZero went
from utter ignorance to creative mastery in four hours, without the help of any
human guide.
AlphaZero is not the
only imaginative software out there. One of the ways to catch cheaters in chess
tournaments today is to monitor the level of originality that players exhibit.
If they play an exceptionally creative move, the judges will often suspect that
it could not possibly be a human move—it must be a computer move. At least in
chess, creativity is already considered to be the trademark of computers rather
than humans! So if chess is our canary in the coal mine, we have been duly
warned that the canary is dying. What is happening today to human-AI teams in
chess might happen down the road to human-AI teams in policing, medicine,
banking, and many other fields.
What’s more, AI enjoys
uniquely nonhuman abilities, which makes the difference between AI and a human
worker one of kind rather than merely of degree. Two particularly important
nonhuman abilities that AI possesses are connectivity and updatability.
For example, many
drivers are unfamiliar with all the changing traffic regulations on the roads
they drive, and they often violate them. In addition, since every driver is a
singular entity, when two vehicles approach the same intersection, the drivers
sometimes miscommunicate their intentions and collide. Self-driving cars, by
contrast, will know all the traffic regulations and never disobey them on
purpose, and they could all be connected to one another. When two such vehicles
approach the same junction, they won’t really be two separate entities, but
part of a single algorithm. The chances that they might miscommunicate and
collide will therefore be far smaller.
Similarly, if the World
Health Organization identifies a new disease, or if a laboratory produces a new
medicine, it can’t immediately update all the human doctors in the world. Yet
even if you had billions of AI doctors in the world—each monitoring the health
of a single human being—you could still update all of them within a split
second, and they could all communicate to one another their assessments of the
new disease or medicine. These potential advantages of connectivity and
updatability are so huge that at least in some lines of work, it might make
sense to replace all humans with computers, even if
individually some humans still do a better job than the machines.
The same technologies that might make
billions of people economically irrelevant might also make them easier to
monitor and control.
All of this leads to one
very important conclusion: The automation revolution will not consist of a
single watershed event, after which the job market will settle into some new
equilibrium. Rather, it will be a cascade of ever bigger disruptions. Old jobs
will disappear and new jobs will emerge, but the new jobs will also rapidly
change and vanish. People will need to retrain and reinvent themselves not just
once, but many times.
Just as in the 20th
century governments established massive education systems for young people, in
the 21st century they will need to establish massive reeducation systems for
adults. But will that be enough? Change is always stressful, and the hectic
world of the early 21st century has produced a global epidemic of stress. As
job volatility increases, will people be able to cope? By 2050, a useless class
might emerge, the result not only of a shortage of jobs or a lack of relevant
education but also of insufficient mental stamina to continue learning new
skills.
III. The Rise of Digital Dictatorships
As many people lose their economic value, they might
also come to lose their political power. The same technologies that might make
billions of people economically irrelevant might also make them easier to
monitor and control.
AI frightens many people
because they don’t trust it to remain obedient. Science fiction makes much of
the possibility that computers or robots will develop consciousness—and shortly
thereafter will try to kill all humans. But there is no particular reason to
believe that AI will develop consciousness as it becomes more intelligent. We
should instead fear AI because it will probably always obey its human masters,
and never rebel. AI is a tool and a weapon unlike any other that human beings
have developed; it will almost certainly allow the already powerful to
consolidate their power further.
from the atlantic archives
Jihad vs. McWorld
by Benjamin R. Barber
March 1992
by Benjamin R. Barber
March 1992
“IN ALL THIS high-tech
commercial world there is nothing that looks particularly democratic. It lends
itself to surveillance as well as liberty, to new forms of manipulation and
covert control as well as new kinds of participation, to skewed, unjust market
outcomes as well as greater productivity. The consumer society and the open
society are not quite synonymous. Capitalism and democracy have a relationship,
but it is something less than a marriage.” Read more
Matt Huynh
Consider surveillance.
Numerous countries around the world, including several democracies, are busy
building unprecedented systems of surveillance. For example, Israel is a leader
in the field of surveillance technology, and has created in the occupied West
Bank a working prototype for a total-surveillance regime. Already today
whenever Palestinians make a phone call, post something on Facebook, or travel
from one city to another, they are likely to be monitored by Israeli
microphones, cameras, drones, or spy software. Algorithms analyze the gathered
data, helping the Israeli security forces pinpoint and neutralize what they
consider to be potential threats. The Palestinians may administer some towns
and villages in the West Bank, but the Israelis command the sky, the airwaves,
and cyberspace. It therefore takes surprisingly few Israeli soldiers to
effectively control the roughly 2.5 million Palestinians who live in the West
Bank.
In one incident in
October 2017, a Palestinian laborer posted to his private Facebook account a
picture of himself in his workplace, alongside a bulldozer. Adjacent to the
image he wrote, “Good morning!” A Facebook translation algorithm made a small
error when transliterating the Arabic letters. Instead of Ysabechhum (which
means “Good morning”), the algorithm identified the letters as Ydbachhum (which
means “Hurt them”). Suspecting that the man might be a terrorist intending to
use a bulldozer to run people over, Israeli security forces swiftly arrested him.
They released him after they realized that the algorithm had made a mistake.
Even so, the offending Facebook post was taken down—you can never be too
careful. What Palestinians are experiencing today in the West Bank may be just
a primitive preview of what billions of people will eventually experience all
over the planet.
Imagine, for instance,
that the current regime in North Korea gained a more advanced version of this
sort of technology in the future. North Koreans might be required to wear a
biometric bracelet that monitors everything they do and say, as well as their
blood pressure and brain activity. Using the growing understanding of the human
brain and drawing on the immense powers of machine learning, the North Korean
government might eventually be able to gauge what each and every citizen is
thinking at each and every moment. If a North Korean looked at a picture of Kim
Jong Un and the biometric sensors picked up telltale signs of anger (higher
blood pressure, increased activity in the amygdala), that person could be in
the gulag the next day.
The conflict between democracy and
dictatorship is actually a conflict between two different data-processing
systems. AI may swing the advantage toward the latter.
And yet such hard-edged
tactics may not prove necessary, at least much of the time. A facade of free
choice and free voting may remain in place in some countries, even as the
public exerts less and less actual control. To be sure, attempts to manipulate
voters’ feelings are not new. But once somebody (whether in San Francisco or
Beijing or Moscow) gains the technological ability to manipulate the human
heart—reliably, cheaply, and at scale—democratic politics will mutate into an
emotional puppet show.
We are unlikely to face
a rebellion of sentient machines in the coming decades, but we might have to
deal with hordes of bots that know how to press our emotional buttons better
than our mother does and that use this uncanny ability, at the behest of a
human elite, to try to sell us something—be it a car, a politician, or an
entire ideology. The bots might identify our deepest fears, hatreds, and
cravings and use them against us. We have already been given a foretaste of
this in recent elections and referendums across the world, when hackers learned
how to manipulate individual voters by analyzing data about them and exploiting
their prejudices. While science-fiction thrillers are drawn to dramatic
apocalypses of fire and smoke, in reality we may be facing a banal apocalypse
by clicking.
The biggest and most frightening impact of the AI
revolution might be on the relative efficiency of democracies and
dictatorships. Historically, autocracies have faced crippling handicaps in
regard to innovation and economic growth. In the late 20th century, democracies
usually outperformed dictatorships, because they were far better at processing
information. We tend to think about the conflict between democracy and
dictatorship as a conflict between two different ethical systems, but it is
actually a conflict between two different data-processing systems. Democracy
distributes the power to process information and make decisions among many
people and institutions, whereas dictatorship concentrates information and
power in one place. Given 20th-century technology, it was inefficient to
concentrate too much information and power in one place. Nobody had the ability
to process all available information fast enough and make the right decisions.
This is one reason the Soviet Union made far worse decisions than the United
States, and why the Soviet economy lagged far behind the American economy.
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However, artificial
intelligence may soon swing the pendulum in the opposite direction. AI makes it
possible to process enormous amounts of information centrally. In fact, it
might make centralized systems far more efficient than diffuse systems, because
machine learning works better when the machine has more information to analyze.
If you disregard all privacy concerns and concentrate all the information
relating to a billion people in one database, you’ll wind up with much better
algorithms than if you respect individual privacy and have in your database
only partial information on a million people. An authoritarian government that
orders all its citizens to have their DNA sequenced and to share their medical
data with some central authority would gain an immense advantage in genetics
and medical research over societies in which medical data are strictly private.
The main handicap of authoritarian regimes in the 20th century—the desire to
concentrate all information and power in one place—may become their decisive
advantage in the 21st century.
Yoshi Sodeoka
New technologies will
continue to emerge, of course, and some of them may encourage the distribution
rather than the concentration of information and power. Blockchain technology,
and the use of cryptocurrencies enabled by it, is currently touted as a
possible counterweight to centralized power. But blockchain technology is still
in the embryonic stage, and we don’t yet know whether it will indeed
counterbalance the centralizing tendencies of AI. Remember that the Internet,
too, was hyped in its early days as a libertarian panacea that would free
people from all centralized systems—but is now poised to make centralized
authority more powerful than ever.
IV. The Transfer of Authority to Machines
Even if some societies remain ostensibly democratic, the
increasing efficiency of algorithms will still shift more and more authority
from individual humans to networked machines. We might willingly give up more
and more authority over our lives because we will learn from experience to
trust the algorithms more than our own feelings, eventually losing our ability
to make many decisions for ourselves. Just think of the way that, within a mere
two decades, billions of people have come to entrust Google’s search algorithm
with one of the most important tasks of all: finding relevant and trustworthy
information. As we rely more on Google for answers, our ability
to locate information independently diminishes. Already today, “truth” is
defined by the top results of a Google search. This process has likewise
affected our physical abilities, such as navigating space. People ask Google
not just to find information but also to guide them around. Self-driving cars
and AI physicians would represent further erosion: While these innovations
would put truckers and human doctors out of work, their larger import lies in
the continuing transfer of authority and responsibility to machines.
Humans are used to
thinking about life as a drama of decision making. Liberal democracy and
free-market capitalism see the individual as an autonomous agent constantly
making choices about the world. Works of art—be they Shakespeare plays, Jane
Austen novels, or cheesy Hollywood comedies—usually revolve around the hero
having to make some crucial decision. To be or not to be? To listen to my wife
and kill King Duncan, or listen to my conscience and spare him? To marry Mr.
Collins or Mr. Darcy? Christian and Muslim theology similarly focus on the
drama of decision making, arguing that everlasting salvation depends on making
the right choice.
What will happen to this
view of life as we rely on AI to make ever more decisions for us? Even now we
trust Netflix to recommend movies and Spotify to pick music we’ll like. But why
should AI’s helpfulness stop there?
Every year millions of
college students need to decide what to study. This is a very important and
difficult decision, made under pressure from parents, friends, and professors
who have varying interests and opinions. It is also influenced by students’ own
individual fears and fantasies, which are themselves shaped by movies, novels,
and advertising campaigns. Complicating matters, a given student does not
really know what it takes to succeed in a given profession, and doesn’t
necessarily have a realistic sense of his or her own strengths and weaknesses.
It’s not so hard to see
how AI could one day make better decisions than we do about careers, and
perhaps even about relationships. But once we begin to count on AI to decide
what to study, where to work, and whom to date or even marry, human life will
cease to be a drama of decision making, and our conception of life will need to
change. Democratic elections and free markets might cease to make sense. So
might most religions and works of art. Imagine Anna Karenina taking out her
smartphone and asking Siri whether she should stay married to Karenin or elope
with the dashing Count Vronsky. Or imagine your favorite Shakespeare play with
all the crucial decisions made by a Google algorithm. Hamlet and Macbeth would
have much more comfortable lives, but what kind of lives would those be? Do we
have models for making sense of such lives?
Can parliaments and political parties overcome these
challenges and forestall the darker scenarios? At the current moment this does
not seem likely. Technological disruption is not even a leading item on the
political agenda. During the 2016 U.S. presidential race, the main reference to
disruptive technology concerned Hillary Clinton’s email debacle, and despite
all the talk about job loss, neither candidate directly addressed the potential
impact of automation. Donald Trump warned voters that Mexicans would take their
jobs, and that the U.S. should therefore build a wall on its southern border.
He never warned voters that algorithms would take their jobs, nor did he
suggest building a firewall around California.
So what should we do?
For starters, we need to
place a much higher priority on understanding how the human mind
works—particularly how our own wisdom and compassion can be cultivated. If we
invest too much in AI and too little in developing the human mind, the very
sophisticated artificial intelligence of computers might serve only to empower
the natural stupidity of humans, and to nurture our worst (but also, perhaps,
most powerful) impulses, among them greed and hatred. To avoid such an outcome,
for every dollar and every minute we invest in improving AI, we would be wise
to invest a dollar and a minute in exploring and developing human
consciousness.
More practically, and
more immediately, if we want to prevent the concentration of all wealth and
power in the hands of a small elite, we must regulate the ownership of data. In
ancient times, land was the most important asset, so politics was a struggle to
control land. In the modern era, machines and factories became more important
than land, so political struggles focused on controlling these vital means of
production. In the 21st century, data will eclipse both land and machinery as
the most important asset, so politics will be a struggle to control data’s
flow.
Unfortunately, we don’t
have much experience in regulating the ownership of data, which is inherently a
far more difficult task than regulating land or machines. Data are everywhere
and nowhere at the same time, they can move at the speed of light, and you can
create as many copies of them as you want. Do the data collected about my DNA,
my brain, and my life belong to me, or to the government, or to a corporation,
or to the human collective?
The race to accumulate
data is already on, and is currently headed by giants such as Google and
Facebook and, in China, Baidu and Tencent. So far, many of these companies have
acted as “attention merchants”—they capture our attention by providing us with
free information, services, and entertainment, and then they resell our
attention to advertisers. Yet their true business isn’t merely selling ads.
Rather, by capturing our attention they manage to accumulate immense amounts of
data about us, which are worth more than any advertising revenue. We aren’t
their customers—we are their product.
Ordinary people will
find it very difficult to resist this process. At present, many of us are happy
to give away our most valuable asset—our personal data—in exchange for free
email services and funny cat videos. But if, later on, ordinary people decide
to try to block the flow of data, they are likely to have trouble doing so,
especially as they may have come to rely on the network to help them make
decisions, and even for their health and physical survival.
Nationalization of data
by governments could offer one solution; it would certainly curb the power of
big corporations. But history suggests that we are not necessarily better off
in the hands of overmighty governments. So we had better call upon our
scientists, our philosophers, our lawyers, and even our poets to turn their
attention to this big question: How do you regulate the ownership of data?
Currently, humans risk
becoming similar to domesticated animals. We have bred docile cows that produce
enormous amounts of milk but are otherwise far inferior to their wild
ancestors. They are less agile, less curious, and less resourceful. We are now
creating tame humans who produce enormous amounts of data and function as
efficient chips in a huge data-processing mechanism, but they hardly maximize
their human potential. If we are not careful, we will end up with downgraded
humans misusing upgraded computers to wreak havoc on themselves and on the
world.
If you find these
prospects alarming—if you dislike the idea of living in a digital dictatorship
or some similarly degraded form of society—then the most important contribution
you can make is to find ways to prevent too much data from being concentrated
in too few hands, and also find ways to keep distributed data processing more
efficient than centralized data processing. These will not be easy tasks. But
achieving them may be the best safeguard of democracy.
This article has been adapted from Yuval Noah Harari’s
book, 21 Lessons for
the 21st Century.
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