Urban life can be unpredictable and inefficient, with traffic
jams, coin-operated public machines, and wasted water and
electricity. The smart city promises a future in which
city living will mean being managed through the networked
communications of sensors, artificial intelligence and
robots that are part of a city's infrastructure. The
real-time collection and assessment of data promise to
improve the management of pedestrian and vehicle traffic,
weather preparedness and energy use. And, while
purpose-built smart cities like Songdo, South Korea
and Dongtan, China (Brenhouse, 2010) have failed, many existing
cities are eager to retrofit themselves to gain the
benefits of connectivity and data collection.
There are many examples. In Copenhagen, an array of sensors
brighten streetlights only as vehicles approach (Cardwell,
city of Jun, Spain, relies on Twitter to do everything
from receiving crime reports to booking appointments
Public housing units in Singapore provide data about
household energy use, waste production and water use
(Souppouris, 2016). In 2017, Sidewalk Labs – owned by Google's
parent company, Alphabet – announced that it will develop
800 acres in Toronto of federally owned waterfront into a
smart, sensor-laden neighbourhood (Austen, 2017).
And, if the smart city improves the delivery of services of
uncontroversial value, like traffic management,
parking-space allotment and package delivery, it may also
enhance the power of a more contested service: policing.
Every data point useful for the efficient distribution of
resources in the city can also be of potential value in a
criminal investigation or to prevent crime from occurring
in the first place.
What will be the consequences for policing as cities become
increasingly ‘smarter’? The emerging questions about
policing and the smart city thus far have focused
primarily on the increased surveillance
capacity that a highly networked urban setting provides
for law enforcement. More cameras and sensors will mean
more watching and less freedom from being watched. The
perception of ubiquitous government surveillance might
quell dissent and inhibit free expression (Brundage
et al., 2018, p. 28). As a result,
concerns about policing and the smart city echo other
responses to surveillance technologies. Regulatory
proposals include minimising unnecessary data collection,
anonymising data when possible and deleting data as soon
as practicable (e.g. ACLU, 2017; Hardy, 2016).
To be sure, the smart city will enhance further the
‘surveillance capacity’ of the police (Ericson and
p. 95). Gaining access to sensors collecting real-time
information throughout a smart city increases the ability
of the police to watch and to act. While few urban police
departments have the human capacity to watch every source
of data collection, ‘smart’ cameras and similar
technologies can automate the process of flagging
suspicious persons and activities (Joh, 2016). But
enhanced surveillance is not the only effect of increased
connectivity that will alter policing.
This essay proposes a different analysis: as cities become
‘smarter’, they increasingly embed policing itself into
the urban infrastructure. Policing is inherent to the
smart city. In exchange for receiving the benefits of more
efficiently delivered services like public transportation
and garbage collection, city dwellers agree to the
monitoring of and response to their own behaviours.
From that premise, we can make a few broad observations.
First, policing the smart city will be a hybrid model:
relying upon both private and public forms of data
collection and response. Second, policing in this
environment will increasingly resemble the methods of
private security rather than traditional public policing.
Third, any attempts to regulate policing in the smart city
will highlight the growing clash between
intellectual-property rights and public accountability.
New methods of policing will increasingly rely on
privately created technologies whose details are guarded
by the companies that created them.
These consequences arise not from wholly new technological
developments, but rather developing trends that we can
observe already in policing. The essay first reviews these
developments before turning to what they mean in the
context of smart cities.
2 Artificial intelligence and policing
Relying on the collection and analysis of data is not new in
policing. The use of rogues’ galleries and DNA databases
reflects the importance of information gathering in
policing (e.g. Cole, 2002). But what is new and different today
is the sheer quantity of data and the technological
capability to analyse it. So, while it is true that
policing has long relied on data, today there are many
technologies that permit the police to draw inferences
from information in ways ordinary human beings cannot.
Whether referred to as a change in software, big data or
algorithms, police today increasingly rely upon automated
technologies in the same way as providers of dating
services, retail shopping, health care and financial
services do. Automated license-plate readers can collect
and identify thousands of plates per second (Angwin and
Valentino-DeVries, 2012). Place-based predictive policing software
forecasts where crime might occur in the future (Sengupta,
Social-network analysis predicts which persons might be
future victims or perpetrators of gun violence (Eligon and
Facial-recognition technology can identify individuals out
of a crowd of thousands (BBC, 2018). None of these feats was
possible, or not easily so, with human beings alone (but
see Keefe, 2016).
Thus far in the US, these new technologies have taken the
form of products adopted by local police departments.
Sometimes, as in the case of police body cameras, the
federal government has provided initial funding to local
departments to purchase new technologies (Phippen, 2016). For the
most part, though, these are local decisions by police
departments to procure new technologies on a case-by-case
basis (Joh, 2017). While there are increasing calls by
civil-liberties organisations and others to impose new
rules on departments to purchase new technologies (e.g.
Crump, 2016), for
the most part, American police departments enjoy
considerable freedom in deciding which investigative
technologies to purchase and deploy.
And, once purchased, these technologies can be used by police
agencies with few legal restraints. Data collected about
persons and activities in public spaces are not protected
by the Fourth Amendment of the US Constitution. And, if
the police retrieve data from third parties – usually
private companies collecting data for their own purposes –
there are few restrictions under current American law.
3 Consequences for policing in smart cities
Smart cities will integrate technologies that collect and
analyse information into the urban architecture. Streets,
sidewalks, buildings and vehicles will all contain
sensors. No source of data will be too insignificant to
analyse or to yield some insight. While the increased
collection of data certainly means that there will be
greater surveillance within a smart city, the ability of
the smart city to respond to the data that are collected
also includes automated responses to unwanted behaviours
Consider how urban police officers respond to service calls
today. A call to respond to a problem – a public argument,
a suspicious person, a burglarised car – might yield a
quick police response, a slower one or none at all. And,
even if a police officer arrives, that officer's response
will likely depend on several discretionary, and
ultimately human, considerations. These might be as varied
as the race of the perpetrator and complainant or how
close the call is to the end of the officer's shift (e.g.
In a smart city, controls might arise from the urban
infrastructure itself. Those identified as probable
shoplifters or credit-card thieves might be banned from
entering certain places. An all-purpose public autonomous
robot might identify you as a threat and automatically
deploy an electric stun gun (cf. Lin and Singer, 2016). Your own
autonomous car – in conjunction with road sensors –might
make it impossible to speed, change lanes illegally or run
red lights. Some forms of law breaking might be rendered
impossible and others discouraged through denials of entry
and provision of incentives.
3.1 Public and private data sources
The American smart city will embed policing into the
city's own infrastructure: one that is both public
and private. Public roads will collect and analyse
data. But so too will private companies assemble
facial-recognition databases for their own use and
for sharing with the police. Automated
license-plate-reader data will be collected both by
public smart cameras looking for criminal activity
and financial services firms looking for delinquent
account holders. None of these activities is wholly
novel; some exist right now. But the smart city
accelerates these trends and assumes that policing
is central to what the city's technologies
And even traditionally public agencies will not escape
private entanglements. Smart-city technologies –
whether in the form of hardware, software or both –
are privately developed products sold to public and
private customers. Surveillance technologies already
used by American police agencies today – such as
social-media threat-analysis software and
location-based predictive policing programs – are
developed by private corporations that consider the
police customers like any other. These companies
might rely upon strategies that are familiar in the
business world but novel in policing. For instance,
a technology company might provide free or nearly
free services to a police agency with the hope of
ensuring customer loyalty and dependence on its
products (Joh, 2017). The dominant provider of police
body cameras, for instance, has offered American
police agencies a year of free cameras that require
use of its subscription-based technology platform
3.2 The model of private policing
Moreover, the type of policing made possible through
the smart city more closely resembles approaches we
typically associate with private security. First,
private security organisations focus on a much wider
scope of activity: not just crime, but accidents and
errors of all kinds (Shearing and Stenning, 1983).
Second, private police organisations stress
prevention and compliance over apprehension and
coercion (Shearing and Stenning, 1983).
Private policing organisations are far more
interested in avoiding the disruption of routine
activity than they are on the punishment of
More than thirty years ago, Shearing and Stenning
discussed how Disney World represented an unlikely
paradigm of private policing (Shearing and Stenning,
1985). Accompanying its promise to provide a
fun and safe experience to visitors is a set of
nearly invisible but powerful policing tools. The
company anticipates and prevents possibilities for
disorder through constant instructions to visitors,
physical barriers that both guide and limit
visitors’ movements and through ‘omnipresent’
employees who detect and correct the smallest errors
(Shearing and Stenning, 1985, p. 301). Neither the
costumed characters nor the many signs, barriers,
lanes and gardens feel coercive to visitors. Yet,
through constant monitoring, prevention and
correction, embedded policing is part of the
Visitors also willingly co-operate in the structures of
control designed into Disney World. The kind of
order sought by the company is presented as an
interest shared with the visitors. So, for example,
having been convinced that these measures exist for
their safety, visitors are willing to wait in long
lines grouped by families (Shearing and Stenning,
p. 302). There are no police uniforms, guns, batons
or handcuffs. Instead, Disney policing is ‘embedded,
preventative, subtle, cooperative, and apparently
non-coercive and consensual’ (Shearing and Stenning,
As cities become ‘smarter’, urban policing might look
more like Disney's private policing: embedded in the
environment itself. Traffic stops are the most
common form of police–citizen interactions in the US
(Eith and Durose, 2011). An artificially intelligent car
could eliminate most of the traffic-law-related
reasons for these sometimes hostile encounters (Joh,
2007). Autonomous vehicles programmed to
follow rules (and that can be halted by police if
necessary) might render certain kinds of regulatory
offences impossible (Rich, 2013).
In other cases, policing could become instantaneous
when artificial intelligence shrinks the gap between
identification and adjudication. In the Chinese city
of Shenzhen, facial-recognition technology will
identify jaywalkers and immediately send fines to
their cellphone by text message (Tao, 2018). Too
many instances of traffic-rule violations will
affect a person's social credit score: the Chinese
national ranking system to be rolled out nationwide
by 2020. This government-sanctioned measurement of
‘trustworthiness’ considers good behaviours
(financial solvency) and bad ones (traffic fines).
Those with high credit scores enjoy perks like bank
loans with favourable terms while those with low
scores may be denied access to airline travel or
high-speed trains (Mistreanu, 2018).
Countries like the US are unlikely to develop
centralised public ranking systems, but even local
governments can embed systems of policing as they
retrofit their urban environments. For as little as
six dollars a month, the American technology company
Amazon has offered a subscription facial-recognition
service to police agencies and marketers alike
(Dwoskin, 2018). Customers add known images of persons
into a database and artificial intelligence scans
new images – fed by public-facing cameras, for
instance – to look for matches. While marketers
might use the Amazon Rekognition program to identify
celebrities in crowds, police might rely on the
service to identify suspected criminals (Wingfield,
2018). Persons deemed suspicious or
dangerous could be deliberately stopped by their own
cars, by robotics or by other features of the
existing smart city.
3.3 The regulatory gap
Smart-city capabilities are dual-use technologies. Any
technology designed to create and manipulate data to
increase the efficiency of city management will also
serve as a convenient tool for law enforcement. A
self-monitoring garbage can might also flag
suspicious contraband. Automated sewer-system
monitoring might also identify opioids and other
substances flushed from individual residences. In
order to function at all, autonomous public buses
and shuttles must continuously monitor and collect
data on the environment around them, including
potential criminal activity.
A key challenge for cities in the US will be how to
maintain oversight over these new forms of policing.
With traditional policing, practical considerations
like ‘limited police resources and community
hostility’ can check the police from intruding too
much on civil liberties.
When a city embeds powerful but inexpensive
systems of prevention, deterrence, surveillance and
enforcement into its structure, however, meaningful
oversight becomes much more difficult.
Regulating the policing aspects of the smart city will
post an even greater challenge because of the source
of these new technologies. One consequence of
greater automation in policing is the increasing
influence of privatisation (Wexler, 2018, p.
1349). Police agencies do not create licence-plate
readers, facial-recognition programs and other uses
of artificial intelligence. New technologies are
developed and sold instead by private companies.
These companies use private law mechanisms to
protect their own interests in ways that
disadvantage public agencies and communities.
In practice, this claim of private power has meant that
companies have succeeded in hiding information about
their products by citing intellectual-property
concerns. There are a small but growing number of
legal cases that provide examples. The dominant
manufacturer of cell site simulators, used by police
to trick suspects’ phones into providing location
information, has relied upon non-disclosure
agreements to prevent police agencies from
disclosing information about their products in open
records requests (Joh, 2017). Similarly, criminal
defendants have been unable to learn about the
source codes in forensic DNA software and in audio
surveillance software used to help prosecute them
because of developers’ trade secrets claims (Wexler,
2018). As police agencies and smart cities
increase their reliance on privately developed
technologies, we can expect to see more
confrontations between public claims to transparency
and private assertions about intellectual
As cities become ‘smart’, connected and watchful, policing
will become a less visible and a more embedded aspect of
the urban environment. These developments represent but
one more step in the rapid changes brought to policing by
the increasing use of digitised data and artificial
intelligence. In a smart city, however, we might see some
qualitative changes to policing, too.
Sensors, artificial intelligence and robotics will lead not
just to increased surveillance within a smart city, but
the embedding of policing into the built environment.
Private and public sources of data will provide the fuel
both for the smart city to become more efficient, but also
for the increased capacity for the police to detect and
react to crime and disorder. These measures will look less
like twentieth-century coercive policing and more like the
models of prevention and apparently consensual control
found in private policing. And, because many of the tools
of smart-city policing will have been developed by private
hands, there will be increased difficulties in maintaining
oversight over urban policing. Public officials and judges
will be asked to weigh competing values of
intellectual-property protection, public-agency
transparency and the rights of criminal defendants. These
challenges will arise because policing will be a part of
the smart city itself.
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