IEEE Technology and Society Magazine - June 2018 - 83
instance, developers could be influenced by imperatives
from (e.g., an abusive) government, when developing
technology. If there is a problem with the current government, algorithmic technology could be intentionally
misused, hiding behind the "veil of sophistication." In
particular, if algorithms are left to their own devices to
govern Smart Cities, the more complex conundrum is
what algorithmic government models for Smart Cities
should look like to prevent or mitigate voluntary or unintended abuses. Who will be in charge of deciding which
algorithms to run? If politics are in charge of deciding
the rules governing a city, who will be in charge of developing algorithms and to check that they are adhering to
the rules? Who will tune the parameters for the algorithms and how? What about the possibility of instantiating multiple algorithms, and that such algorithms
become antagonistic [14], i.e., conflicting with each
other? What does an objective function for governance
models look like? What does a termination condition for
algorithmic governance models look like? Who will be
responsible for bugs? For algorithms governing safety
critical situations [31], such questions are already pressing, and this problem will be dramatically exacerbated
in the future. Just think at the use of artificial intelligence (AI) and autonomous decisions in weaponry [15].
Hinton, in [13], also argued that there is not only a need
to tame AI research, but also to improve political systems so that AI is not misused.
Strictly related, algorithms governing our cities may
also be involved in decisions involving ethical or moral
dilemmas. For instance, a human driver who managed
to swerve her car in time to avoid killing several pedestrians while sacrificing herself might be lauded, but a
self-driving car that killed its driver even while saving
pedestrians might worry passengers [16]. Self-driving
cars could reduce the need to learn driving, and so
fewer people might end up knowing how to drive. This
could be a problem in situations where such a skill is
indeed needed. But moral algorithms that make humanaccepted judgments are problematic. For example, an
algorithm that behaves in a utilitarian manner could
benefit society as a whole, but could hurt individuals,
and therefore might not be accepted.
With regard to the third issue, the risk that politicians
and governments lose control over algorithms, can lead
to an "algocracy." The term "algocracy," contrasts with
"democracy," and literally means that the power ("kratos" in greece) lies with the algorithms rather than with
the people ("demos" in Greece). To some extent, it may
appear we are already living in a partial algocracy, given
that algorithmic decisions already affect some of our
civil life. For instance, when applying for a visa for some
countries, based on some business rules, applicants
with a certain type of passport will receive immediate
JUNE 2018
∕
clearance, whereas others will be pushed to the next
level of scrutiny. These procedures treat people differently based on the settings and semantics of algorithms. Yet until the settings and the semantic of such
algorithms are perfectly compliant with legislation and
rules, the power still resides with the government and,
ultimately, in a democratic system, with the people who
voted for them.
However, given that algorithms can be difficult to
implement, configure, and fully understand, the risk
exists that governments end up relying on algorithms
they do not fully understand without being capable of
effectively verifying the adherence of the algorithms to
the existing laws. Thus, we may end up implicitly delegating decisional power to the algorithms, or to the group of
people devoted to designing and developing them.
Algorithms in future societies and cities will serve
the same role that civil law and urban regulations,
respectively, serve in today's democratic systems.
Accordingly, new political procedures need to be put in
place to regulate which code is installed. The responsibility for (technical) code verification and (juridical)
semantic verification needs to be clearly defined. Most
importantly, to avoid having algorithmic governance
degenerate into algocracy, it is necessary for citizens,
politicians, and decision makers to become capable of
understanding and harnessing the complexity of algorithms and their configuration.
How to Deal with the Problems
Let us now analyze what solutions, possibly enabled
by the same pervasive computing technologies that
cause them, can be envisioned to attack the identified problems.
Data Access Control
Algorithmic governance in Smart Cities is enabled by
the availability of large amounts of data, making it possible for algorithms to understand what is happening
and act accordingly. In this context, the dense and pervasive collection, processing, and dissemination of data
in the midst of people's private lives, while useful for
offering a range of sophisticated and personalized services that provide utility to users, necessarily gives rise
to certain privacy and algorithmic concerns.
From the privacy viewpoint, the pervasive collection
of information exacerbates existing issues associated
with privacy in data handling. In fact, such details can
be used to algorithmically construct a virtual biography
of our activities, revealing private behavior and lifestyle
patterns. Disclosure of this type of analysis or information gives rise to the notion of behavioral privacy [17]
which is distinctly different from traditional identity
privacy. The possession of such detailed personal
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