Artificial
intelligence (AI) has been with us for over 40 years at least the philosophical
idea of it. AI in computers isn’t recent as we have been using the technology for
digital devices for a while now from having GPS maps to talking Phone apps.
During the 1980s to
1990s, a whole new, different approach to AI was made rather than to copy human
intelligence; it was to mimic our intelligence, and how our brain performed in
the real world. So thus researchers and scientists have said that this approach
to AI had the potential to be faster and better than us.
But in his recent
book Edward Tenner writes that "artificial intelligence, while it can be
highly effective, can hardly be called efficient."(Tenner, The Efficiency
Paradox: What Big Data Can't Do,2018 p. 260). And that "even some
enthusiasts of artificial intelligence recognize that while today’s information
technology can learn from data, it still cannot do so efficiently. As the
writer Alex Hern reported in The Guardian on a conference on machine learning,
artificial intelligence still does not have the equivalent of James Watt’s
condensation chamber, the late-eighteenth-century breakthrough that made the
coal-burning steam engine the motive power of the Industrial Revolution."
(Tenner, pp. 205-206).
The quantified self
and diagnostic AI share obstacles to true efficiency that are two of the most
troublesome issues in medical technology: false positives (with their consequences,
overdiagnoses) and toxic uncertainty. The simplest case of the former may be
alarm fatigue.
The Watson
supercomputer that won Jeopardy! needed 85,000 watts of power; the human brains
that it defeated, only 20 watts. It is yet another piece of expensive advanced
medical apparatus and one that has been subsidized by both IBM and its medical
partners. In other words, while highly effective in challenging cases, it is
not a miracle for public health. It has been mainly a public relations triumph
in search of profitable applications. It does promise at least one genuine
contribution to medical efficiency: earlier recognition of “rare” diseases,
defined by the National Institutes of Health as those affecting under 200,000
people in the United States; about 6,800 of such ailments are known. For the 10
percent of the population suffering from one or more, diagnosis takes an
average of over 7.5 years, visits to eight physicians, two or three
misdiagnoses, and often severe financial stress. AI assistance in spotting
these unusual cases can bring big gains to health care, even if most rare
diseases have no known treatment. And obstacles to extending Watson’s power to
the desktop suggest that medical supercomputers of its type are likely to
remain niche services. (M. Mitchell Waldrop, “More than Moore,” Nature 530
(February 11, 2016): 143–47; Larry Greenemeier, “Will
IBM’s Watson Usher in a New Era of Cognitive Computing?” Scientific American,
November 13, 2013; Judy Stone, “Have Pain? Are You Crazy? Rare Diseases Pt. 2,”
Scientific American, February 18, 2014.)
Two other themes
The debate over the
effects of artificial intelligence has also been dominated by two other themes.
One is the fear of a singularity,
an event in which an AI exceeds human intelligence and escapes human control,
with possibly disastrous consequences. The other is the worry that a new
industrial revolution will allow machines to disrupt and replace humans in
every-or almost every-area of society, from transport to the military to
healthcare.
There is also a third
way in which AI promises to reshape the world. By allowing governments to monitor,
understand, and control their citizens far more closely than ever before, AI
will offer authoritarian countries a plausible alternative to liberal
democracy, the first since the end of the Cold War. That will spark renewed
international competition between social systems.
For decades, most
political theorists have believed that liberal democracy offers the only path
to sustained economic success. Either governments could repress their people
and remain poor or liberate them and reap the economic benefits. Some
repressive countries managed to grow their economies for a time, but in the
long run authoritarianism always meant stagnation. AI promises to upend that
dichotomy. It offers a plausible way for big, economically advanced countries
to make their citizens rich while maintaining control over them.
Some countries are
already moving in this direction. China has begun to construct a digital
authoritarian state by using surveillance and machine learning tools to
control restive populations, and by creating what it calls a “social credit
system.” Several like-minded countries have begun to buy or emulate Chinese
systems. Just as competition between liberal democratic, fascist, and communist
social systems defined much of the twentieth century, so the struggle between
liberal democracy and digital authoritarianism is set to define the
twenty-first.
Digital Autoritarianism?
New technologies will
enable high
levels of social control at a reasonable cost. Governments will be able
selectively censor topics and behaviors to allow information for economically
productive activities to flow freely, while curbing political discussions that
might damage the regime. China’s so-called Great Firewall provides an early
demonstration of this kind of selective censorship.
As well as
retroactively censoring speech, AI and big data will allow predictive control
of potential dissenters. This will resemble Amazon or Google’s consumer
targeting but will be much more effective, as authoritarian governments will be
able to draw on data in ways that are not allowed in liberal democracies.
Amazon and Google have access only to data from some accounts and devices; an
AI designed for social control will draw data from the multiplicity of devices
someone interacts with during their daily life. And even more important,
authoritarian regimes will have no compunction about combining such data with
information from tax returns, medical records, criminal records, sexual-health
clinics, bank statements, genetic screenings, physical information (such as
location, biometrics, and CCTV monitoring using facial recognition software),
and information gleaned from family and friends. AI is as good as the data it
has access to. Unfortunately, the quantity and quality of data available to
governments on every citizen will prove excellent for training AI systems.
Even the mere
existence of this kind of predictive control will help authoritarians.
Self-censorship was perhaps the East
German Stasi’s most important disciplinary mechanism. AI will make the
tactic dramatically more effective. People will know that the omnipresent
monitoring of their physical and digital activities will be used to predict
undesired behavior, even actions they are merely contemplating. From a
technical perspective, such predictions are no different from using AI
health-care systems to predict diseases in seemingly healthy people before
their symptoms show.
In order to prevent
the system from making negative predictions, many people will begin to mimic
the behaviors of a “responsible” member of society. These may be as subtle as
how long one’s eyes look at different elements on a phone screen. This will
improve social control not only by forcing people to act in certain ways, but
also by changing the way they think. A central finding in the cognitive science
of influence is that making people perform behaviors can change
their attitudes and lead to self-reinforcing habits. Making people expound
a position makes them more likely to support it, a technique used by the
Chinese on U.S. prisoners of war during the Korean War. Salespeople know that
getting a potential customer to perform small behaviors can change attitudes to
later, bigger requests. More than 60 years of laboratory and fieldwork have
shown humans’ remarkable capacity to rationalize their behaviors.
As well as more effective
control, AI also promises better central economic planning. As Jack Ma, the
founder of the Chinese tech titan Alibaba, argues, with enough information,
central authorities can direct the economy by planning
and predicting market forces. Rather than slow, inflexible,
one-size-fits-all plans, AI promises rapid
and detailed responses to customers’ needs.
There’s no guarantee
that this kind of digital authoritarianism will work in the long run, but it
may not need to, as long as it is a plausible model for which some countries
can aim. That will be enough to spark a new ideological competition. If
governments start to see digital authoritarianism as a viable alternative to
liberal democracy, they will feel no pressure to liberalize. Even if the model
fails in the end, attempts to implement it could last for a long time.
Communist and fascist models collapsed only after thorough attempts to
implement them failed in the real world.
No matter how useful
a system of social control might prove to a regime, building one would not be
easy. Big IT projects are notoriously hard to pull off. They require high
levels of coordination, generous funding, and plenty of expertise. For a sense
of whether such a system is feasible, it’s worth looking to China, the most
important non-Western country that might build one.
China has proved that
it can deliver huge, society-spanning IT projects, such as the
Great Firewall. It also has the funding to build major new systems. Last
year, the country’s internal
security budget was at least $196 billion, a 12 percent increase from 2016.
Much of the jump was probably driven by the need for new big data platforms.
China also has expertise
in AI. Chinese companies are global
leaders in AI research and Chinese software engineers often beat their
American counterparts in international competitions. Finally, technologies,
such as smartphones, that are already
widespread can form the backbone of a personal monitoring system.
Smartphone ownership rates in China are nearing those in the West and in some
areas, such as mobile
payments, China is the world leader.
China is already
building the core components of a digital authoritarian system. The Great
Firewall is sophisticated and well established, and it has tightened
over the past year. Freedom House, a think tank, rates China
the world’s worst abuser of Internet freedom. China is implementing
extensive surveillance in the physical world, as well. In 2014, it
announced a social credit scheme, which will compute an integrated grade that
reflects the quality of every citizen’s conduct, as understood by the
government. The development of China’s surveillance state has gone furthest in
Xinjiang Province, where it is being used to monitor and control the Muslim
Uighur population. Those whom the system deems unsafe are shut out of everyday
life; many are even sent to reeducation centers. If Beijing wants, it could
roll out the system nationwide.
To be sure, ability
is not the same as intention. But China seems to be moving toward
authoritarianism and away from any suggestion of liberalization. The government
clearly believes that AI and big data will do much to enable this new
direction. China’s 2017 AI Development Plan describes how the ability to
predict and “grasp group cognition” means “AI brings new opportunities for
social construction.”
Digital
authoritarianism is not confined to China. Beijing is exporting its model. The
Great Firewall approach to the Internet has spread to Thailand and Vietnam.
According to news reports, Chinese experts have provided support for government
censors in Sri
Lanka and supplied surveillance or censorship equipment to Ethiopia, Iran,
Russia, Zambia,
and Zimbabwe.
Earlier this year, the Chinese AI firm Yitu sold
“wearable cameras with artificial intelligence-powered facial-recognition
technology” to Malaysian law enforcement.
More broadly, China
and Russia have pushed back against the U.S. conception of a free, borderless,
and global Internet. China uses its diplomatic and market power to influence
global technical standards and normalize the idea that domestic governments
should control the Internet in ways that sharply limit individual freedom.
After reportedly heated competition for influence over a new forum that will
set international standards for AI, the United States secured the secretariat,
which helps guide the group’s decisions, while Beijing hosted its first
meeting, this April, and Wael Diab, a senior director at Huawei, secured the
chairmanship of the committee. To the governments that employ them, these
measures may seem defensive—necessary to ensure domestic control-but other
governments may perceive them as tantamount to attacks on their way of life.
The response
The rise of an
authoritarian technological model of governance could, perhaps
counterintuitively, rejuvenate liberal democracies. How liberal democracies
respond to AI’s challenges and opportunities depends partly on how they deal
with them internally and partly on how they deal with the authoritarian alternative
externally. In both cases, grounds exist for guarded optimism.
Internally, although
established democracies will need to make concerted efforts to manage the rise
of new technologies, the challenges aren’t obviously greater than those
democracies have overcome before. One big reason for optimism is path
dependence. Countries with strong traditions of individual liberty will likely
go in one direction with new technology; those without them will likely go
another. Strong forces within U.S. society have long pushed back against
domestic government mass surveillance programs, albeit with variable success.
In the early years of this century, for example, the Defense Advanced Research
Projects Agency began to construct “Total Information Awareness” domestic
surveillance systems to bring together medical, financial, physical and other
data. Opposition from media and civil liberties groups led Congress to defund
the program, although it left some workarounds hidden from the public at the
time. Most citizens in liberal democracies acknowledge the need for espionage
abroad and domestic counterterrorism surveillance, but powerful checks and
balances constrain the state’s security apparatus. Those checks and balances
are under attack today and need fortification, but this will be more a repeat
of past efforts than a fundamentally new challenge.
In the West,
governments are not the only ones to pose a threat to individual freedoms.
Oligopolistic technology companies are concentrating power by gobbling up
competitors and lobbying governments to enact favorable regulations. Yet
societies have overcome this challenge before, after past technological
revolutions. Think of U.S. President Theodore Roosevelt’s trust-busting,
AT&T’s breakup in the 1980s, and the limits that regulators put on
Microsoft during the Internet’s rise in the 1990s.
Digital giants are
also hurting media diversity and support for public interest content as well as
creating a Wild West in political advertising. But previously radical new
technologies, such as radio and television posed similar problems and societies
rose to the challenge. In the end, regulation will likely catch up with the new
definitions of “media” and “publisher” created by the Internet. Facebook Chief
Executive Mark Zuckerberg resisted labeling political advertising in the same
way as is required on television, until political pressure forced his hand last
year.
Liberal democracies are
unlikely to be won over to digital authoritarianism. Recent polling suggests
that a declining proportion in Western societies view democracy as “essential,”
but this is a long way from a genuine weakening of Western democracy.
The external
challenge of a new authoritarian competitor may perhaps strengthen liberal
democracies. The human tendency to frame competition in us versus them terms
may lead Western countries to define their attitudes to censorship and
surveillance at least partly in opposition to the new competition. Most people
find the nitty-gritty of data policy boring and pay little attention to the
risks of surveillance. But when these issues underpin a dystopian regime in the
real world they will prove neither boring nor abstract. Governments and
technology firms in liberal democracies will have to explain how they are
different.
Lessons
The West can do very
little to change the trajectory of a country as capable and confident as China.
Digital authoritarian states will likely be around for a while. To compete with
them, liberal democracies will need clear strategies. First, governments and
societies should rigorously limit domestic surveillance and manipulation.
Technology giants should be broken up and regulated. Governments need to ensure
a diverse, healthy media environment, for instance by ensuring that overmighty
gatekeepers such as Facebook do not reduce media plurality; funding public
service broadcasting; and updating the regulations covering political
advertising to fit the online world. They should enact laws preventing
technology firms from exploiting other sources of personal data, such as
medical records, on their customers and should radically curtail data
collection from across the multiplicity of platforms with which people come
into contact. Even governments should be banned from using such data except in
a few circumstances, such as counterterrorism operations.
Second, Western
countries should work to influence how states that are neither solidly
democratic nor solidly authoritarian implement AI and big data systems. They
should provide aid to develop states’ physical and regulatory infrastructure
and use the access provided by that aid to prevent governments from using
joined-up data. They should promote international norms that respect individual
privacy as well as state sovereignty. And they should demarcate the use of AI
and metadata for legitimate national security purposes from its use in
suppressing human rights.
Finally, Western
countries must prepare to push back against the digital authoritarian
heartland. Vast AI systems will prove vulnerable to disruption, although as
regimes come to rely ever more on them for security, governments will have to
take care that tit-for-tat cycles of retribution don’t spiral out of control.
Systems that selectively censor communications will enable economic creativity
but will also inevitably reveal the outside world. Winning the contest with
digital authoritarian governments will not be impossible-as long as liberal
democracies can summon the necessary political will to join the struggle.
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