There is a camera at the airport’s gate. Often, it is left unnoticed, but if one
is asked she would probably know to say it is there. Many of us are by now
familiar with such cameras and various security apparatuses that are installed
in public spaces airports, streets, pubs, train stations, shopping malls, or
elevators. Most of the readers of this book are probably also familiar with the
many critiques of the growing expansion of such mechanisms, their uses and
abuses. But what does the camera monitor? Some cameras today can identify
faces (to match the profile of a runaway), body heat (to trigger an alert when
detecting an anxious and thus presumably a suspicious person) or logos
of cars (to identify the economic status of a person, in order to prompt the
appropriate advertising on a billboard). But the vast majority of security appa-
ratuses today monitor movement.1
These security apparatuses are based on algorithms that analyze the data
accumulated via a variety of sensors. The algorithms are used, first, to identify
regular patterns of movement and then to flag movements that deviate from
this identified norm. The norm thus becomes a pattern of movement deduced
from sets of natural and social phenomena.2 Once established, every deviation
from this norm is defined as a problem or a potential threat. We therefore
have “normal” and “abnormal” movements: the movements of airport travelers
(and the airplanes themselves), of the business people or shoppers in their
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