Artificial intelligence, or AI, constitutes a common motif in science fiction literature – the aspect of a “robot uprising”, where AI becomes sufficiently advanced such that it surpasses human intelligence and escapes human control. Common perceptions of AI focus on the ethical and human impacts of a malevolent, artificially intelligent agent itself. In this document, I wish to instead focus on an equally important, and, I will argue, more plausible case of sufficiently advanced AI which poses immense risk to human activity: the use of AI in conjunction with big data for authoritarian rule and population control. In these scenarios, AI has no agency, and instead serves as a sufficiently advanced and intelligent tool for human agents. Throughout this document, I summarize current and potential applications of this type of AI, explore the ethical ramifications, and last, propose and evaluate solutions and safeguards.

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Digital Authoritarianism: Possible Implementation, Associated Ethics,
and Safeguards
Andrew Aukerman
December 2018

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Artificial intelligence, or AI, constitutes a common motif in science fiction literature – the
aspect of a “robot uprising”, where AI becomes sufficiently advanced such that it surpasses human
intelligence and escapes human control. Common perceptions of AI focus on the ethical and
human impacts of a malevolent, artificially intelligent agent itself. In this document, I wish to
instead focus on an equally important, and, I will argue, more plausible case of sufficiently
advanced AI which poses immense risk to human activity: the use of AI in conjunction with big
data for authoritarian rule and population control. In these scenarios, AI has no agency, and instead
serves as a sufficiently advanced and intelligent tool for human agents. Throughout this document,
I summarize current and potential applications of this type of AI, explore the ethical ramifications,
and last, propose and evaluate solutions and safeguards.
KEY CONCEPTS OF DIGITAL AUTHORITARIANISM
Authoritarian regimes exhibit certain key identifying features, two of which have great
importance in the context of AI. The first being strength of a centralized and consolidated
government [1] and the second being the destruction of dissenting or auxiliary institutions.
Dictatorships and rising authoritarian governments today display these traits. Military parades are
a prominent common example of power; it is important for an authoritarian regime to maintain a
façade (whether true or false) of power and control over possible threats to the regime [2].
Destruction of institutions is also key, however also problematic for the long term success of such
regimes. Liberal-democratic systems, (e.g. political, judiciary, cultural, and civil institutions) are
regarded as essential to a country’s growth.
Failure to grow will lead to economic regression, which in turn leads to instability of the
ruling regime [1]. History reveals this, as democracies produce lasting economic success [3]. The
same article found that in more modern years, dictatorships did provide increasingly lasting

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“economic miracles” keeping them on par with democratic and free economies. One such example
is China; where a one party system has successfully lead China to become the most prominent and
emerging economy in the world [3]. This jeopardizes the comfortable idea that economic success
and liberal democracy go “hand in hand” [1], and begs the question of, “what changed?”
I focus on the element of careful control in these successful non-liberal economies. China
in particular has a vast bureaucracy [4], keeping political and economic actives entrenched in a
large system which employs 50 million people. Deployed alongside this is careful information
control. The so-called “Great Firewall” censors the internet in China, limiting information access
[5]. As markets that require open internet emerge, China has faced tension in maintaining control
and promoting economic activity. “Digital authoritarianism” lies at this intersection of software
and this type of one-party rule [1].
AI USE IN DIGITAL AUTHORITARIANISM
The proposed use of AI come into play here, as countries (such as China) are facing the
very real dichotomy between economic success and political control. AI in conjunction with “big
data”, i.e., data that is massively collected, diverse, and (usually) unstructured, promise a new
means of control while guaranteeing economic success on two fronts: AI implementation for
economic systems and large-scale, predictive AI for population control.
Economic Planning: These systems already exist – businesses today have already
turned to AI to manage everything from their supply chains to employee schedules. Machine
learning demonstrates great success in targeted adverting [6], prediction of demand [7], and
currently serves as a quickly growing tool in the financial sector [8]. Companies have realized that
they have incidentally amassed a valuable but unused resource: big data. Transaction history,

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invoices, browser history, user activity, and stock prices all underpin the essential data for these
AI analytics. It has proven essential to exploit this data for financial gain.
Jack Ma, a giant in Chinese tech and proponent of the Communist Party of China, sees no
limit to using AI in predicting and optimizing to market forces. The localized technology used by
companies, he argues, can be scaled up to the economic activities of China as a whole. The
beginnings of such have already come to pass [9]; the technology is there, and increasing
bureaucracy and state-interplay provides more than enough political infrastructure to implement
enhanced surveillance programs.
Predicting Human Behavior with Varied Input: The technology to predict human
strategic behavior exists today in limited forms; a popular example being AlphaGo [10], which
went on to beat the world champion in the board game Go. Some underlying, albeit symbolic,
understanding of its opponent’s strategic stance must be necessary for such success. Further,
during the match, surprising and novel moves were played, which “overturned hundreds of
years of received wisdom” [10]. However, it is not evident that this understanding can be
expanded to the more complex world of human behavior in social environments. Go is a zero-sum,
sequential game with a fixed action and input space, while our usual interactions in the real world
are general-sum and varied.
Advancements in AI show promise in handling these types of inputs and outputs. In
machine learning models, structured data input is important; one needs to know what kind of data
is used, and what the desired outcomes are so that training can take place. Such data are difficult
to produce when extrapolating to general human behavior, whereof anything collected – social
media activity, text conversations, transactions, criminal history, education, health – can serve as
input vectors, and the output space is ill-defined. Hartford et al. detail a software architecture that

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accepts varied input by pooling arbitrary length-input vectors into “feature layers” (much like a
convolutional neural net) and propagating these aggregated features into action response layers
[11]. This removes the need to “tune by hand” the neural network, allowing for greater generality
in how the network is used. It is still similar to feed-forward neural networks, however would
allow learning of certain patterned behavior from inputs. The conclusions reached by the article
show that input vectors, such as aggregated data about some person, can be utilized in AI systems.
Classification Algorithms: Recurrent neural networks may also provide the ability to
follow the evolution of person over large time scales and classify activity. A key feature of
recurrent neural nets is context awareness – a simple example being that ‘bat’ appearing near-by
the word ‘flew’ provides a different context than if appearing in a sentence with the word ‘ball’.
Latest advancements go above and beyond simple recurrent neural networks in aggregating time-
sequence data, responding to inputs in the context of previous inputs in a temporarily deep sense
that also compounds overtime, as shown in Long-term Recurrent Convolutional Networks for
Visual Recognition and Description [12]. This work shows the ability to perform “activity
detection”. While this example is on the time-frame of seconds, there is no real limit to the
‘deepness’ in the time domain. Activity detection is quite fruitful in security and crime prevention
[7]; however, if crime is defined as political dissent, protesting, or even talking about political
reform, such systems can be deployed to squash this type of activity. Ultimately, an authoritarian
regime would be interested in classification using largely amassed data. This exists today; as
shown by Rasoul Kiani, AI implementations already provide geographic profiles, social network
analysis, crime patterns and suspect detection [13].
Summary: These algorithms are incredibly complex – and might provide insights that go
above and beyond that which a human reviewer could, practically or even ultimately, manifest.

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But – these algorithms are also dumb in the sense that they are not aware, not sentient, not
conscious, and have no agency. As stated by Scott Bauguess in his keynote speech about the role
of AI: “The algorithm doesn’t care why the association exists. It doesn’t matter if the predictions
don’t make intuitive sense. The algorithm just cares about the accuracy of the prediction”. The
trend throughout history follows a similar note: people in power like to stay in power, and will use
whatever tools necessary to do so. The AI algorithms need not be perfect; they just need to be
effective. It is this growing efficacy that poses legitimate risk, and motivates exploration of ethics
in the face of this risk.
ETHICS OF DIGITAIL AUTHORITARIANISM
Trusting Algorithms and Accountability: This occurs already in the social media
spheres, and I surmise this effect as a type of accountability vagueness. Such vagueness is the
first ethical challenge posed by digital authoritarianism. While there has been a pleasant shift in,
e.g. Facebook’s attitude in the face of unsavory outcomes from the very algorithms deployed on
their platform1
, most responses still come down to “it’s the algorithm”. The complexity of these
algorithms requires a degree of trust, both in algorithm itself, and from those who are affected by
it. The vagueness in accountability can help dismiss legitimate abuses of such technology, as
expanded upon by Amitai Etzioni in Are New Technologies the Enemy of Privacy? [14].
For example, what happens when AI messes up? Is the engineer to blame? Is the fault in
those trusting the AI, or perhaps society is at fault, in the case that an AI algorithm takes on a racist
or sexist prejudice? AI can amplify existing prejudices and perpetuate modes of oppression [7].
On the other hand, it may simply reveal these prejudices and help eliminate them. Crime detection
is one such example. By pooling information about a person’s character, including their race,
1
There is still a long way to go, see [19] for a opinions (in pop-culture) on this.

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prejudices can be induced into an AI model of criminal activity. Some argue that such prejudices
are simply true, as it is the most faithful reflection of the data. However, examples exist already in
which biased data, through human error, consequently produced biased algorithms. See Gender
Shades: Intersectional Accuracy Disparities in Commercial Gender Classification [15] for a more
detailed look at biases in facial recognition.
Privacy and Freedom: Working on the Privacy and Security axis, two dichotomies
emerge: Privacy and innocence in the face of surveillance, and freedom in the face of control. The
primary stakeholders being those in countries with advanced digital surveillance programs, and
secondary stakeholders are those in still liberal-democratic countries, who will likely feel the
effects of such countries [1]. AI technology can actually provide greater control over a population
in two ways, one being direct, where human intervention directly removes, imprisons, or
subjugates dissenters, while the other is indirect, where those who know they are being watched
and fear repercussions alter their behaviors.
In the direct sense, a population would face even greater violation of privacy, and near-
complete removal of freedom of speech, protest, and press. AI exacerbates these violations through
classification and pattern recognition. In a sense, these algorithms generate a new type of (private)
information2
that is immediately abused and violated. In trying to model behavior, one reduces
someone (even if partially) down to whatever an algorithm spits-out. As varied as that output may
be, it is prone to error, but the lack of transparency in the would make understanding possible
errors (i.e. proving one’s innocence) near impossible. This lack of transparency against relates
2
Even though this information is purely symbolic, there does exists interesting arguments that something new is
happening – See Clocksin, William F. "Artificial Intelligence and the Future." Philosophical Transactions:
Mathematical, Physical and Engineering Sciences 361, no. 1809 (2003): 1721-748.
http://www.jstor.org.pitt.idm.oclc.org/stable/3559219.

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back to trust and accountability – that is, if the computer says no3
, or if the computer says you’re
a criminal, who is to say otherwise, or what counts as sufficient counter evidence? In authoritarian
regimes, such a question may be unimportant – perfection is not needed, only intimidation. This
indirect sense of control is much more powerful, as research shows that the fear of being watched
may impact behavior, which in turn, may impact one’s own beliefs and thoughts [1].
Global Impacts: In the social view of human rights, all aspects of AI driven, digital
authoritarianism are unstatutable. Assuming universal human right to autonomy, enjoyment of
liberty, justice, and access to free and open culture, it is clear these rights are all harshly infringed.
However, a proponent of successful types of authoritarianism may offer a different perspective.
China already stands as a complex example, especially ethically. If not for their economic success,
one may easily point to them as a regressive state. Rather, many Chinese citizens enjoy aspects of
liberal-democracy, with social programs, education, increasing health access, and vibrant culture
[16]. Beijing itself is quite cosmopolitan, and a great number of Chinese citzens, while unhappy
with certain aspects of their country, have healthy levels of appreciation and patriotism for China.
Hence, we find the waters muddied, as it may become increasingly difficult to untangle the notion
of freedom from political or social determinism. As we enter an age where AI-driven analysis
provides a greater access to and control of human activity, our sense of freedom and autonomy
may be altered.
POTENTIAL SOLUTIONS
The solutions and safeguards against digital authoritarianism fall into three spheres, policy
about data use, promoting privacy as a human right, and AI-driven encryption and digital warfare.
3
Making reference to the Little Britain skits, see [20].

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Defining Ethical Data Use: It is not illegal to buy uranium, one can go online and buy
a radioactive source4
. However, anyone familiar with the Iran nuclear deal will understand that
possession of certain types of uranium is a point of immense contention, and the focus of precarious
global policy [17]. This dichotomy reveals an important insight: the type and use of some resource
is what makes it dangerous. In the same sense that uranium itself has no ethically charged value,
data does not either; it is human interaction with these entities that begets ethical questions.
Working within the framework of consequentialism, one can safely argue that data
collection, by itself, has no ethical dilemmas; instead, it is the use of data that does. It is this
distinction that must be explored and worked out as data collection becomes more apparent and
powerful. Companies have tried skirting this distinction, inferring that data being an inert entity
means any use of that data is equally ethically inert. Instead, it must be made clear, in the context
of global policy, that there is ethical and unethical use of data and implementation of technology.
Unfortunately, it would be impossible, and possibly regressive itself, to ban certain types
of AI, or to try and regulate a country’s “right” to collect data about its citizenry. No country could
really suggest such without being hypocritical, as justification of data collection are always made.
Data collection is somewhat accepted in the US, perhaps because either Google is considered
trustworthy and just wants to ‘curate our experience’, or the NSA is only concerned chiefly with
our security. Likewise, in defense of a regime that has implemented AI for successful economic
and political control, one can provide the justification that such a regime is chiefly interested in
the health, success, and stability of the country. Giving up privacy or liberty is a necessary
component of that success. It seems that trying to regulate data on a global scale has challenges, it
may be more fruitful to appeal to aspects of human rights instead.
4
I presume for calibrating a scintillator or testing a Giger counter.

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Promoting Privacy as a Right: This requires a redefinition of success in the global
system. It is a privileged comfort that we perceive economically successful countries as such
because they are free democracies (with exceptions). If the landscape shifts, such that authoritarian
governments enjoy equal or greater success, alongside near absolute control of its citizenry, one
must rely on a different definition of success in the modern world. This is a nuanced point, and
ties into economic systems on the global scale. Naturally, types of political systems that enhance
economic growth are the ones pursued. It had been expected that China would eventually fail a
few years after establishing communist rule [4], while today its GDP is on pace to out rank the US
in about 10 years.
This solution relies, perhaps heavily, on the idea that freedom of speech, protest, press, is
not a privileged right, bestowed selectively, but rather, a universal human right. Thus, recognition
of this right would help in the fight against digital authoritarianism, and good policy in this regard
is key [7]. However, this is again difficult to implement – if no natural market forces promote
privacy, little realistic expectation could be made that authoritarian regimes would care for it.
Though, some promising changes have taken place in recent years, as companies such as Apple
[7] pursue differential privacy and promote user privacy as an important aspect of their business.
Encryption and Digital Warfare: Smart Encryption is the first line of defense against
privacy violation. As much as our activities exist on a platform where information is easily
duplicated, copied, and stored, equally those platforms provide encryption and security that make
certain content only accessible by you as the user [14]. As AI progresses, it will also become better
at protecting privacy. Biometric information can enhance this, as AI-driven systems guarantee both
security and privacy.5
5
See, for example, Apple’s Face ID technology https://support.apple.com/en-us/HT208108

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If the desire for privacy outpaces the capabilities of privacy violation, economic forces may
easily overtake authoritarian attempts to trespass on private data. This requires a multi-faceted
approach: privacy must be viewed as a desirable and necessary right, and, I would hope, those
interested in selling that idea can develop technology to promote that right. In the same way that
anti-fraud or “anti-dissent” technology may flag “undesirable” activity, smart privacy software
could detect equally “undesirable” activity, protecting users against unauthorized use of their data.
Regimes that exhibit economic success will also pose a significant perceived threat to
liberal-democratic countries [1]. As real or empty as this threat may be, another technical solution
does exist: the undermining of digital authoritarian states with AI itself. This is perhaps the most
far-fetched solution. It may be that a digital type of war is upon us, but instead of robots with guns,
it’s software with algorithms.
Drawing on the words of Scott Bauguess, “It doesn’t matter if the predictions don’t make
intuitive sense.” [8], it also doesn’t matter, in a sense, if the way AI works doesn’t make sense. We
may design systems that have so much complexity that they exceed human understanding entirely
– this doesn’t mean they suddenly rise up, but rather, we develop digital weapons that we don’t
understand. As data becomes increasingly valuable, its loss becomes equally destructive. We
already see the possible beginnings of such a war, the launch of Stuxnet [18] (a “smart virus”),
exploitation of Facebook’s AI algorithms, and ransomware, which locks data with outside
encryption. The smarter these programs become, the more damage they can do to authoritarian
uses of data. As the stakes in data and software rise, the tensions between countries that wield this
software them can be expected to increase [1].
Promoting privacy, and encouraging the development of AI driven encryption and privacy,
I argue, is the best bet moving into the future. The political forces to maintain control may be too

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strong to regulate or combat, perhaps the only force on par is that of economic gain: to sell
advanced privacy options to individuals. Regardless, focus on ethical use of data in global politics
will prove important, else we may face the erosion of privacy all together.
CONCLUSION
Throughout the course of this document, I have covered the key components of
authoritarianism, and how AI can curb the pitfalls or exacerbate the dangerous aspects of such a
political system. AI can promise greater optimization of economic systems, and in countries like
China, implementing the insights from this system can only further accelerate their economic
progress. At the same time, with increased data collection and the implementation of increasingly
advanced algorithms, such as temporally deep recurrent neural nets, behaviors and actions of a
citizenry falls under greater scrutiny and, ultimately, greater control. The “all seeing eye” of AI
can, and already does, affect behavior, whether directly or indirectly. As these capabilities expand,
infringement of privacy will too, and upset of the global system, which today favors liberal
democracies, will become more probable. Defining and enforcing ethical use of data is important,
however difficult. A more economical solution may be advocating of privacy, and cultural change
to appreciate privacy as a right. This will motivate natural markets to develop advanced privacy
software and technology. In all cases, conflicts between countries will take on an increasingly
digital flavor as the stakes of big data increases. Perhaps AI will never escape human control, but
only human understanding. Wielding tools that we don’t understand may have severe
consequences, and moving carefully into this future is of the utmost importance.

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