A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology

A Theoretical Examination of the Objections to Body-Worn Cameras
With the Addition of Real-Time Facial Recognition
CR 6006 – Dissertation on Criminology
Author: Robert Lucas Ross
University College Cork

A Theoretical Examination of the Objections to Body-Worn Cameras
With the Addition of Real-Time Facial Recognition
Author: Robert Lucas Ross
Submitted in partial fulfilment, as required, for the award of
MA Criminology
National University of Ireland, Cork
Department of Sociology and Criminology
December 2020
Head of Department: Professor Maggie O’Neill
Supervisor: Dr. James Cuffe
Word Count: 16,070

Contents
Declaration
Acknowledgements
Abstract
Chapter 1: Introduction
1.1 Introduction 1
1.2 History and Trajectory 2
1.3 The USA Patriot Act 3
1.4 Law Enforcement and Body-Worn Cameras 6
1.5 Rationale for Research 8
1.6 Aims and Objectives 9
1.7 Research Questions 10
Chapter 2: Legal Context 12
Chapter 3: Literature Review
3.1 Introduction 17
3.2 Theories of Surveillance 17
3.2.1 The Evolution of the Panopticon 17
3.2.2 Rational Choice Theory 23
3.2.3 Environmental Criminology 25
ii

3.2.4 Opportunity Theory and Routine Activity Theory 27
3.2.5 Biological Positivism 31
3.3 Research on Body-Worn Cameras without Facial Recognition 33
3.4 Ethical Implications 34
3.5 Conclusion 35
Chapter 4: Methodology
4.1 Quantitative Research 36
4.2 Ethical Considerations 37
4.3 Challenges to Research 37
Chapter 5: Accuracy and Monitoring 39
Chapter 6: Case Study Project Green Light 42
Chapter 7 Analysis and Theoretical Connections
7.1 Introduction 48
7.2 Displacement of Power 49
7.3 The Rational Actor 52
7.4 Routine Activity Theory in Action 53
7.5 Environmental Connections 54
iii

7.6 Profiling and Biological Positivism 55
7.7 Habituation 57
Chapter 8: Conclusion 61
Bibliography 62
Images:
Figure 1 – map of racial demographics (Cable, 2013) 56
Figure 2 – map of Project Green Light partner businesses 56
(City of Detroit, 2020)
Figure 3 – photograph of Detroit reproductive health clinic 59
(Garvie & Moy, 2019)
Figure 4 – close-up of cameras at Detroit reproductive health clinic 59
(Garvie & Moy 2019)
Acronyms:
AI – Artificial Intelligence
BWC – Body-worn Camera
CCTV – Closed-Circuit Television
CNN – Convolutional Neural Network
DPD - Detroit Police Department
FBI – Federal Bureau of Investigation
FIVE – Face in Video Evaluation
FRT – Facial Recognition Technology
iv

NIST – National Institute of Standards and Technology
RCT – Rational Choice Theory
UPI – User Profile Information
YTD – Year to Date
v

Declaration: This is to certify that the work I am submitting is my own and has
not been submitted for another degree, either at University College Cork or
elsewhere. All external references and sources are clearly acknowledged and
identified within the contents. I have read and understood the regulations of
University College Cork concerning plagiarism.
Robert L. Ross
vi

Acknowledgements: My thanks go to my supervisor, Dr. James Cuffe, for
extending his help across the world to the United States. I would also like to thank
Dr. Katharina Swirak for her support. Despite these challenging times of the
pandemic, the Criminology Department has given me the experience of a lifetime.
I would also like to thank Dr. Catherine O’Sullivan, Dr. James Windle, Dr. Lydia
Sapouna, Dr. Maggie O’Neill, and Dr. Claire Edwards.
vii

ABSTRACT
This paper aims to provide the reasoning behind the objection from the public and civil
rights groups to the deployment of body cameras with facial recognition technology that is
monitored in real-time by law enforcement. To provide context, I will first elaborate on the
connection between the terrorist attacks of September 11, 2001, in New York and the resulting
body of government policies that enabled a groundswell of surveillance in the United States.
Further relevant context is provided in the historical legal objections to infringement on privacy
and civil liberties by increased surveillance and in a review of the technological unreliability of
current facial recognition software. Following contextual background, I will examine the existing
criminological theories of surveillance and connect their application to a case study of Project
Green Light, a public/private initiative that uses advanced methods of surveillance that include
real-time facial recognition technology. Though not mobile as in a body camera, the comparison
with Project Green Light allows a platform to estimate the potential effect of adding facial
recognition to real-time surveillance. This case study, when analyzed through the lens of
surveillance theory, reveals that the actual intent of this form of enhanced surveillance veers
away from establishing trust and accountability and enables pro-active policing that creates
objection by the public.
viii

CHAPTER 1: INTRODUCTION
1.1 Introduction
It is a unique time in the history of post-9/11 United States with the advances and
proliferation of CCTV involving the controversial usage of facial recognition technology. Real-
time facial recognition enables a new form of ‘stop and frisk.’ Public and government support for
accountability has led to a deployment of body-worn cameras as an essential addition to law
enforcement officer uniforms that have the potential capability of real-time, mobile surveillance.
This addition, in turn, enables pro-active policing. Close to seventy-five percent of research
concerning body camera deployment, with no facial recognition software, has been conducted in
the United States and offers encouraging evidence on the effectiveness and acceptance of this
technology (Lum, et al., 2019). Documentation of accuracy and implementation of facial
recognition revealed in government reports and legal precedents shows varying levels of
reliability. Currently, critical decisions are being made on whether the rewards of facial
recognition are worth the risks to privacy. Therefore, cities and states are enacting their own laws
because there is no federally coordinated response. In 2019, the state of California banned the
use of facial recognition technology in body cameras by state and local law enforcement until
2023 (The People of the State of California, 2019). Because of the delay between rapid
development of new technology and the slow enactment of reasonable regulations, values like
privacy and civic freedom are being threatened whilst accuracy and reliability are imperfect.
Real-time, mobile facial recognition as a ‘digital dragnet,’ that includes innocent citizens as well
as dangerous individuals, has greater potential for negative consequences than stationary closed-
circuit television. A factor to consider in the coming years will be complacency and a tolerance
1

for incremental additions to existing technology with the normalization of constant surveillance.
1.2 History and Trajectory
Following the terrorist attack on the World Trade Center in New York City on September
11, 2001, and the coordinated attack on the Pentagon in Washington, D.C., the necessity for
sophisticated threat detection by law enforcement prompted a surge in biometric identification
technology. The development of Facial Recognition Technology (FRT) as a tool for enhanced
security has escalated dramatically since these events. A goal of security and thorough
identification placed a priority on developing biometric technology. Kelly Gates (2006, p. 418)
comments, “One specific type of biometric that drew the attention of policy makers and the press
was automated facial recognition.” Only two weeks after the attacks, Transportation Secretary,
Norman Mineta, was consulting with Viisage Technology to deploy facial recognition
technology in airports and shortly thereafter, federal security legislation established the
Department of Homeland Security (Gates, 2006). With the attention from the press and public,
Congress additionally funded more research and development for integration of facial
recognition technology into border and immigration control systems (Gates, 2006). From this
effort to find solutions to terror threats, legislation of the USA Patriot Act, the Homeland
Security Act, the Enhanced Border Security and Visa Entry Reform Act, and the Aviation and
Transportation Security Act all contain provisions for biometric implementation (Gates, 2006).
Assuming hindsight on the lack of facial recognition technology implementation at the
time of the attack, manufacturers of the software and influential political leaders declared that the
2 acts of terror on September 11, 2001, were a direct result of the inability to identify terrorists.
2

In an interview with the Wall Street Journal, Tom Colasti, chief executive of Viisage
Technology, claimed, “If our technology had been deployed, the likelihood is [the terrorists]
would have been recognized” (Gates, 2006, p. 424). In congressional hearings, Senator Dianne
Feinstein remarked:
How could a large group of coordinated terrorists operate for more than a year in the
United States without being detected, then get on four different airliners in a single
morning without being stopped? The answer is that we could not identify them (Gates,
2006, p.424).
Government participation in the deployment of facial recognition technology proved
instrumental in the progression of this mode of surveillance in the private sector and in law
enforcement.
1.3 The USA Patriot Act
The USA Patriot Act was the Bush administration’s response to one of the most
horrendous mass casualties ever seen on American soil. The terrorist attacks on September 11th
resulted in 2,997 deaths (Katersky, 2018). President George W. Bush signed the USA Patriot Act
on October 26, 2001, just fifteen days after the terrorist attacks on the Twin Towers and the
Pentagon. This Act provided implementation protocols standardized through the acronym USA
PATRIOT, “… drawn from Uniting and Strengthening America by Providing Appropriate Tools
Required to Intercept and Obstruct Terrorism” (Mason & Stephenson, 2015, p. 653). The USA
Patriot Act established textbook utilization of the means to which the United States
governmental coordination operates with fluidity amongst the system of checks and balances and
3

separation of powers, whilst simultaneously magnifying the ‘crime-fighting powers’ associated
in law enforcement’s jurisdictional effectiveness. Mason & Stephenson (2015, p. 653) declare
that, “… no single piece of legislation in recent decades has done more to enhance the
government’s crime-fighting powers.” Expressing the cost to which such sacrifices affect civil
liberties, Mason and Stephenson (2015, p. 653) further state, “That expansion, however, has
come with a price: a curtailment of some freedoms.”
The articles that comprise the structure of the USA Patriot Act direct the police power of
law enforcement from every aspect of the United States governmental structure to aid in the
eradication and containment of acts of terror. The influence on surveillance and the constitutional
liberties of the United States civilians, who are directly affected by the infringement of their
rights to privacy, is primarily caused by specific components mentioned in the Patriot Act. These
components include, but are not limited to the authorization of “… Sneak and Peek search
warrants that allow agents to conduct a search without notifying the owner and to delay
notification for up to 30 days (with the possibility of extensions) that a search has taken place”
(Mason & Stephenson, 2015, p. 654). This power is outlined in Section 213 of the Act and the
ACLU warns that eliminating the requirement of presenting cause to a neutral magistrate
threatens Fourth Amendment constitutional protections (American Civil Liberties Union, 2020).
Law enforcement’s presence in deterring terrorism has since directed its gaze with more
clarity, focusing on specific crimes that before the attacks on 9/11 were of little concern. This
addition included “… terrorist and computer crimes to the list of predicate offenses subject to
warrant authorized and justice department approved electronic surveillance under Title III of the
1968 Omnibus Crime Control and Safe Streets Act” (Mason & Stephenson, 2015, p. 654).
4

Removal of legal barriers has become instrumental to uncover and shed light on the weak areas
of national security to ensure the prevention, detection, and application of the use of force to
combat and suppress the flow of terror. The focus of law enforcement has now shifted toward
‘techno-policing’ due to the increase in cyber-crimes, providing improvement of the means to
which such infractions can be prevented, detected, tracked and traced (Marx, 2008). Such
methods have drastically increased in proficiency and remain at the forefront of importance as
artificial intelligence (AI) has become a tool that law enforcement can now utilize. Sections 215,
216, and 217 enable law enforcement to access business records, phone records and computer
records where internet and associated counterparts of artificial intelligence remain fungible tools
that exist as public domain (The United States Department of Justice, 2018). The USA Patriot
Act includes the following provision implementing just that, stating, “[The USA Patriot Act]
Adds electronic communications (such as email) to those communications already subject to
‘track and trace’ devices and pen registers” (Mason & Stephenson, 2015, p. 654).
The USA Patriot Act was a significant motivating factor for the push toward proliferation
of the common use of closed-circuit television surveillance systems and cameras as a ‘techno-
policing’ tool (Gates, 2006). The presence of this technology can be measured from the stance of
its potential energy in terms of the impact it has on society. In this case, the impact of closed-
circuit television integrated with facial recognition technology can be viewed from a sociological
perspective, regarding its correlation amongst criminological theories. The trade-off between
funding, use and demand for development of facial recognition technology and constitutional
rights to privacy reflects the relative concerns for safety and security. Due to the evolving
uncertainty regarding the expanded surveillance that is supported and enacted by the USA Patriot
5

Act, certain powers are designated as ‘sunset provisions’ (Mueller, 2005). This distinction means
that at intervals, Congress must re-evaluate their merits and authorize the extension of these
surveillance powers. Amid the Covid-19 pandemic turmoil, Section 215 expired on March 15,
2020, without re-approval, but was given a short-term reprieve to be reconsidered in the near
future (McKinney & Crocker, 2020). The impact of this development may determine the
legalities and future of governmental surveillance.
1.4 Law Enforcement and Body-Worn Cameras
The rapid expansion of public surveillance has transformed observational policing tactics
that have moved beyond stationary closed-circuit television (CCTV) to mobile video monitoring
such as body-worn cameras (Lum, et al., 2019). In fact, the Bureau of Justice Statistics reported
in 2016, that 60% of U.S. police departments and 49% of sheriff’s departments had deployed
body-worn cameras (Lum, et al., 2019). Body-worn cameras (BWC) are audio-video-
photographic recording systems that have been in use since the early 2000s. In 2014, a catalyst
for widespread use of CCTV body-worn cameras in the United States occurred in Ferguson,
Missouri, with the police officer involved shooting of Michael Brown, an unarmed black man
(Lum, et al., 2019). Racial tension and rioting erupted as the police account conflicted with
bystander accounts, with no video evidence to corroborate the differing versions (Lum, et al.,
2019). This escalating controversy prompted President Barack Obama to create a task force that
recommended changes to increase public trust of the police (Lum, et al., 2019). High on the list
of recommendations was a government commitment to provide 50,000 body-worn cameras to
police departments across the United States of America (Lum, et al., 2019). This deployment
initiated the steady build-up of mobile surveillance that can be augmented with facial recognition
6

software in a ‘low-research environment’ (Lum, et al., 2019, p. 95).
The capabilities of closed-circuit television have potential for an increase in investigative
proficiency through the implementation of facial recognition because identification can occur
remotely and without consent (Garvie, et al., 2016). However, advancement of the functions of
closed-circuit television depends upon states’ acceptance of facial recognition technology as an
added, legal component to real-time, mobile surveillance. That empowerment is viewed
differently across the United States. The legality of enabling body-worn cameras with facial
recognition technology varies from location to location. In the article, California Becomes the
Third State to Ban Facial Recognition Software in Police Body Cameras, Haley Samsel (2019,
para. 2) reports:
AB1215, which will go into effect on Jan. 1, bans biometric surveillance technology in
body cameras as well as taking body camera footage and running it through facial
recognition software later. However, police are not banned from using the technology on
other cameras, and federal law enforcement could potentially use the software while
operating in California.
This governmental ban illustrates the growing public distrust of potential misuse. Aside from
recognizing the indicators that facial recognition offers a controversial measure of crime
detection, it is banned in the states of Oregon and New Hampshire. The loophole circumstances
of its use in California are exposed by Samsel (2019) identifying the alternative presence it plays
through other methods of surveillance.
Facial recognition technology does not provide a perfect solution. The opportunities for
false positives and algorithmic biases present themselves under recognizable circumstances. The
7

notion that such discrepancies take place in perceptible contexts is promising in that mistakes are
identifiable, yet they present difficulties in the application of its use as a reliable policing tactic.
Not only do accuracy issues present complications for the implementation of such policing
methods, the protection of civil liberties is also under scrutiny. The justification for surveillance,
despite the risks to privacy in a post-9/11 world, is a mentality of “better safe than sorry” (Galic,
et al., 2017, p. 27). This particular point in time is pivotal as police departments in the United
States currently have not officially deployed body cameras with facial recognition technology
software. However, one police force in New Mexico is in the process of a beta test of the
Wolfcom Halo body camera with integrated facial recognition capability (Gershgorn, 2020).
Focusing on the current environment and capacity in the United States, the available literature
affirms the theoretical and practical applications of surveillance augmented with facial
recognition technology while revealing the additional, consequential threat to privacy and civil
liberties when the camera is monitored in real-time. The Literature Review will introduce a
compilation of this research and connection.
1.5 Rationale for Research
In the United States, police departments are dealing with reduced budgets and public
pressure to be ‘defunded’ and ‘demilitarized.’ Using a technology that would amplify manpower
and provide accountability sounds like a logical decision. However, a key difference lies in the
manner of data collection. Traditionally, law enforcement has used the fingerprints, DNA and
pictures of criminals (i.e., mugshots) to make identifications (Garvie, et al., 2016). With facial
8

recognition technology, the collection of subjects includes primarily innocent civilians by
incorporating driver’s license photographs and passports into the database (Garvie, et al., 2016).
Identification through the use of biometrics has been utilized for decades. The most familiar
biometric is the fingerprint and now, even law-abiding citizens can reasonably expect that they
have a ‘faceprint.’ Currently, the Federal Bureau of Investigation (FBI) has over 641 million
photos in its database (United States Government Accountability Office, 2019). Deploying body-
worn cameras with real-time facial recognition technology enables a form of mobile, proactive
policing that occurs before a criminal event instead of being used as an identification tool in a
post-crime investigation. A ‘digital dragnet’ is possible as individuals in public encounter a
search without probable cause or legal warrant. Even so, facial recognition does add a layer of
security if the end users of the output are screening people in an unbiased and ethical way.
Artificial intelligence, in the form of facial recognition, would seem to be an unbiased tool,
however, the systems are run by people and inherent biases are possible. In one study done by
Georgetown Law, it was found that black people were misidentified at a rate of 5-10% more than
white people (Garvie, et al., 2016). Researching the effectiveness of surveillance with artificial
intelligence and its impact on deterring crime, including the power to identify criminals, will
reveal whether the allure of increased proactive security is worth the cost to personal privacy.
1.6 Aims and Objectives
The research aim of this dissertation is to explore the benefits of real-time, mobile
surveillance for law enforcement compared with real-time, stationary surveillance and the
9

differing results of each method. Video surveillance has increasingly been compared to ‘Big
Brother’ in George Orwell’s novel, 1984. I will seek confirmation that the current theories of
surveillance are still relevant in light of the mobility and immediate access of video feeds, not
only of those who are under surveillance, but those who enforce the law. The next generation of
facial recognition being developed is designed to determine moods through facial expressions
and to predict behavior and actions (Hashemi & Hall, 2020). This aspect of identification could
provide opportunities for intervention prior to criminal acts but would also subject a person to
accusations due to physical appearance. As law enforcement agencies are coping with reduced
budgets and manpower, artificial intelligence can make up for deficits. The original goal for
gaining public trust in law enforcement motivated the initial deployment of body cameras in
2014, yet adding facial recognition changes the end result. While people go about their daily
lives, unconscious of being watched ‘in the wild,’ anonymity becomes a luxury instead of a
given liberty. The aim of this dissertation is to connect the goals of deploying mobile, real-time
surveillance equipped with facial recognition software with both the anticipated results and
divergence from the theoretical understanding of surveillance in order to determine the reasoning
of public distrust.
1.7 Research Questions
To document the issues surrounding the possibility of deploying facial recognition in
body-worn cameras, there are several questions that will shed light on this controversial tool of
law enforcement.
1. Do the historical theories of surveillance remain valid in the concept of deterrence of
crime through the use of facial recognition capability in a mobile, real-time setting?
10

2. What are the different goals of real-time, mobile surveillance compared with post-
crime surveillance?
3. What is the accuracy rate of facial recognition identification and how is it measured
and monitored?
4. Is this technology neutral or can it be influenced by racial bias?
5. Does the use of facial recognition mold the behavior of the public and law
enforcement?
6. Does the introduction of facial recognition technology have public support? And if
not universal support, in what instances is it acceptable?
11

CHAPTER 2: LEGAL CONTEXT
The threat to privacy is the most common objection to facial recognition technology
deployment (American Civil Liberties Union, 2020). Tracing the legal boundaries of facial
recognition technology is found in government policy and court decisions. From the focal point
of evidence collection, the Fourth Amendment to the United States Constitution provides the
most significant reference for guidance on this enforcement tool. However, a study of the
interpretations and limitations of this standard reveals a variety of judicial decisions. The Fourth
Amendment to the United States Constitution states:
The right of the people to be secure in their persons, houses, papers and effects, against
unreasonable searches and seizures, shall not be violated, and no warrants shall issue, but
upon probable cause, supported by oath or affirmation, and particularly describing the
place to be searched, and the person or things to be seized (Find Law for Legal
Professionals, 2020, para. 6).
As stated, there must be a documented reason, known as ‘probable cause,’ in order to search a
place or to seize a particular person. Then, a ‘warrant’ must be obtained, which is an official
authorization for search or arrest that is issued by a judge. Mason and Stephenson (2015, p. 383)
comment, “Before the executive branch, acting through a police officer, may invade a person’s
physical privacy, the judicial branch must be convinced of the need for this search of this place
before giving its approval.” Gary Marx (2016) provides comprehension toward circumstantiality
and the difficulties that occur interpreting the association amongst perspectives on accumulation
of observational data. Marx (2016, p. 310) questions, “At what point does momentary
surveillance in a public place evolve into the kind of search prohibited by the Fourth Amendment
without a warrant?” Originally, the understanding was stated in the Bill of Rights, which strictly
12

involves only the accountability of human cognition.
In observation of the evolving and seemingly omniscient presence of closed-circuit
television, interpretations of the law through the scope of privacy question the role that artificial
intelligence plays in the capture of instances that were unfathomable at the time of the Fourth
Amendment’s addition to the Constitution. The lack of a sentient entity’s direct function in
prosecuting citizens, without what was originally founded by the act of administering a ‘writ of
assistance,’ tests the strength of United States constitutional law and rights to privacy. On the
ambiguity of a search, Marx (2016, p. 310) asks:
Searches based on the unaided senses that physically cross protective barriers such as
walls, desk drawers, briefcases, or bodies are already well understood. But what of
technologies that read what persons or places radiate with no need to enter and remove
what is within?
In consideration of the replacement of methods to which unlawful searches are conducted, and
the tools to which searches (neglecting ‘probable cause’) are performed; the government’s
judicial system loses the ability to prosecute against a machine and function in favor of civilians
who are exposed to unlawful infringement upon their rights. Marx once more introduces new
questions about the function of artificial intelligence within the spectrum of human conduct
regulation and its invasive presence within the ever diminishing, private sphere of existence. He
reasons:
How does search by an “impersonal” machine or animal differ in its consequences and
desirability from that by a human? Is due process honored when an individual is singled
out not because of wrongful behavior, but because of how close he or she fits an
aggregate statistical model believed to be associated with wrongful behavior (Marx,
2016, p. 310)?
13

This reliance on technology allows a lack of human oversight and produces impediments to
judicial fairness.
Surveillance can be viewed as an unreasonable search, but as the word ‘unreasonable’ is
subjective in nature, there is argument that prompts judicial review. Commenting on the concept
of a search, Marc Blitz (2013, p. 22) states:
Police engage in a search when they (1) not only observe, but also record, images, sounds
of people or events outside police presence; or (2) magnify details on a person or
documents or other items the person is carrying and thereby reveal information that
would not otherwise be apparent without a pat-down, or a stop-and-search of a person’s
papers or effects.
The Supreme Court of the United States has limited that definition with decisions that confirm
that when an individual is in a public space (i.e., a business), privacy is not always a reasonable
expectation (Legal Information Institute, 2020). The more public the space, the less privacy can
be demanded. Further complaints are that the use of facial recognition technology will inhibit
democracy and free speech when crowds are monitored as in a real-time sweep. The Bill of
Rights of the United States Constitution contains protections for civil liberties. Reference to
constitutional law is essential in addressing the complex matters involving civil liberties. The
precedents to which courtroom procedures, dissents, and exemplifications of the arbitrary nature
involved in interpretations of civil rights, federal, state, and local jurisdictional laws are
accurately depicted in American Constitutional Law: Introductory Essays and Selected Cases
(Mason & Stephenson, 2018).
Few limitations demand accountability for law enforcement’s use of data. Governmental
policy reports show the intent of transparency and the extent of compliance. A lack of uniformity
14

between federal and state government regulation does exist, but there are two laws that constrain
the collection and use of face images. The Privacy Act of 1974 requires public notice when
personal data in a system of records is maintained and the purpose of that collected data (United
States Government Accountability Office, 2019). Additionally, the E-Government Act of 2002
requires that when personal data through information technology is collected by a government
agency, a Privacy Impact Assessment must be conducted (United States Government
Accountability Office, 2019). This report is intended to examine the privacy risks when
government databases are merged, centralized, or manipulated. Oversight structures in the
Department of Justice and Federal Bureau of Investigation are tasked with monitoring
compliance to policy requirements, but adherence is inadequate at best. Following an
accountability report from 2016, only one of six accountability measures had been implemented
by the FBI by 2019 (United States Government Accountability Office, 2019).
Currently, U.S. federal laws do not specifically address facial recognition and rely on
state governments to police themselves, leaving only a few states with legislation regarding
biometric information. These state laws restrict the use of data concerning students, businesses,
and government actors (Global Justice Information Sharing Initiative, 2017). Additionally, many
state laws include biometric information in their definitions of covered personal information
when regulating data security and breach response. A potentially influential legal case, Hiibel v.
Sixth Judicial Court of Nevada, allows that while no federal law requires a person to identify
themselves in a police stop, state law may require an individual to disclose his or her name if a
reasonable suspicion of criminal activity exists (Global Justice Information Sharing Initiative,
2017). This loophole lays a foundation for the use of facial recognition by law enforcement with
15

the potential to encroach on civil liberties.
16

CHAPTER 3: LITERATURE REVIEW
3.1 Introduction
This literature review will open by looking at the relevant theories of surveillance that
have influenced the inclusion of technological tools that are used in deterrence of crime. This
background will provide the logic behind the growing reliance on hard technology and the
potential of surveillance to mold behavior in a maximum-security society. This section will be
followed by an examination of a specific piece of equipment, the body-worn camera, that merges
technology with theoretical deterrence. The final theme of this review will be to acknowledge
relevant ethical concerns for the underlying consequences of using artificial intelligence before
enacting reasonable regulations.
3.2 Theories of Surveillance
3.2.1 The Evolution of the Panopticon
The use and effect of surveillance on human behavior has been studied by many theorists
and is enlightening when evaluating the recent development in real-time video capture, its
accuracy and effectiveness. Theories that have inspired the increase in demand for various forms
of CCTV and have boosted public perceptions of its implementation, can be traced back to
essential thinkers of criminological research. Jeremy Bentham’s contribution to the perception of
surveillance includes the highly innovative, ideological prison architecture known as ‘the
Panopticon.’ Galic, Timan and Koops (2017) trace the origins of the prison-Panopticon as an
octagonal structure with a central guard tower where incarcerated convicts below are unsure
when they are under observation. This illusion of constant surveillance induces internalized good
17

behavior and reduces the necessity of an inspector to surveil the convicts (Galic, et al., 2017).
The objective of Bentham’s modern panoptic prison leads to the transition of a non-panoptic
phase where crime is minimized through self-discipline. Galic, Timan and Koops (2017) view
panopticism as a template that can be adapted to modify behavior in many societal roles.
Diversity in Bentham’s paradigm reaches other non-disciplinary sections of society in the
pauper-Panopticon and the chrestomatic-Panopticon in a classroom setting (Galic, et al., 2017).
The strategy of ‘the few watch the many’ is visible in many institutions and is useful in
demonstrating the potential of closed-circuit television to prevent crime.
Though the origins of panopticism consisted of Jeremy Bentham’s alternative design for
optimal surveillance of prison inmates, the current use of the term ‘panoptic’ formulates the
resemblance of a structural societal concept. This concept invokes the utilization of observation
in modern preventative measures that deter antisocial behavior and enable the potential capture
of real-time events used in prosecution of unlawful behavior. The resulting self-discipline,
derived from power configurations modeled on the architectural panoptic structure of
surveillance, exhibits predictive reasoning that is identical to conclusions anticipated through the
hypotheses of Bentham. The rapid increase of adaptation and cybernetic assimilation of
technological advancements and the panoptic architecture of the structurally evolving modernity
of public and private surveillance is consistent. Current features of artificial intelligence allow
for mass presence and further extend the threshold and reach of panoptic structures. As panoptic
structures grow, the influence on behalf of not only the deterrence of anti-social behavior, but the
encouragement of consumer behavior increases at a steady rate (Galic, et al, 2017). This brings
about the notion of ‘surveillance capitalism’ expressed by Shoshana Zuboff (2019). The new age
18

of big data and the constantly evolving replication of behavioral molding sets the foundational
configuration of theoretical points established in Michel Foucault’s interpretation of Jeremy
Bentham’s ideologies for surveillance in the modern age.
From such ideations, theorists have analyzed the advancement of methodological
surveillance tactics, providing other dimensions to the Panopticon. Foucault’s disciplinary power
approach expands Bentham’s observations and offers insight on the control of criminogenic
behavior through constant supervision as a societal containment mechanism (Mathiesen, 2006).
Foucault (1995) addresses technocratic Western societies and finds the panoptic penitentiary
system of governing hidden or unnoticed in many processes of daily life. With the goal of
‘normation,’ the possibility of surveillance molds the souls of individuals into “…subjected, and
practiced, ‘docile bodies’ that are continuously measured against the norm” (Galic, et al., 2017,
p. 17). Social control is influenced heavily in what Foucault (1995) refers to as the ‘mode of
governance,’ provoking the behavioral tendencies which are put under even stricter scrutiny
whilst manipulating the individual’s actions on behalf of the state’s best interest.
Foucault’s (1995) analysis of the amplifying societal impact provided by the effects of
the Panopticon are contained in his book, Discipline and Punish: The Birth of the Prison.
Concerning panopticism, he states, “In appearance, it is merely the solution of a technical
problem; but, through it, a whole type of society emerges” (Foucault, 1995, p. 216). Foucault
(1995) proceeds to uncover the development of what can be referred to as a ‘carceral society.’ In
greater detail, once more stating within his writings, is the description that panopticism has been
transported “…from the penal institution to the entire social body” (Foucault, 1995, p. 298).
19

Thus, the principle of panopticism gradually and imperceptibly invades ever-larger segments of
society. Foucault (1995) finds panopticism spreading in the form of carceral methods in
charitable societies, moral improvement associations, and discreet surveillance. Discipline then
works to achieve long-term goals for a stable and prosperous society. This disciplinary power
approach recognizes that criminals do not abstain from committing crime because it is wrong,
but because of the presence of observational policing tactics such as closed-circuit television
surveillance in public spaces. The side effects of the introduction of technological control of
individuals adds a dehumanizing dimension that allows control from a distance.
Exemplification of power displacement is presented through the functions of closed-
circuit television as a means of social control through public surveillance. Aspects of control, the
influence on which the operations of closed-circuit television surveillance are conducted, and the
effects on the surveilled are examined by Norris & Armstrong (2016). They offer an explanatory
account that includes the observations of interconnectivity presented through the structural
components of panopticism in, Surveillance, Closed-Circuit Television and Social Control.
Concerning video surveillance, the authors state, “… the possibility of directly questioning and
challenging the watcher is lost. The differences between the unmediated gaze of the eyes, and the
camera mediated gaze of the CCTV operative illustrates the profound asymmetry of power
inherent in CCTV monitoring” (Norris & Armstrong, 2016, p. 5). The harsh reality of an unfair
fight due to the lack of attributes and abilities, to which the power displacement pointed out by
Foucault is identified, acknowledges the mismatch and fixation on those under inspection
through the ‘one-way mirror’ disposition of closed-circuit television. Norris and Armstrong
(2016, p. 5) explain:
20

Whether a person is the object of attention while the watcher can see the watched, the
reverse is not true. The watcher, at least in the more sophisticated systems, can zoom in
to reveal the smallest details and monitor every nuance of their facial expressions and
gestures for clues to their intentions. The watched have no such ability; whereas
ordinarily the intentions and motivations of the watcher may be ‘read off’ from a person’s
face by contextualizing a ‘look’ as quizzical, threatening, lecherous etc., the veil of the
camera denies the possibility of the reciprocal exchange of visual data.
The power displacement is seen as a representational “crystallization of the power of vision
embodied in an architectural form” (Norris & Armstrong, 2016, p. 5). Clarifying on behalf of
this notion, Foucault (1995, p. 202-203) identifies introspection and self-discipline through
involvement with the functions of the panoptic architectural structures stating:
He who is subject to a field of visibility, and knows it, assumes responsibility for the
constraints of power, he makes them play spontaneously upon himself; he inscribes in
himself the power relations in which he simultaneously plays both roles, he becomes the
principle of his own subjection.
Alternative understanding of the Panopticon is presented through innovative usage of the
term exhibited through re-examination of a reversible context that is labeled the ‘Synopticon.’
Following the logic, Thomas Mathiesen (2006) explains the evolving nature of technology’s
influence on surveillance. Mathiesen (2006, p. 217) proposes a ‘viewer society’ that restructures
the system of inverse perspectives, shifting from “the few watch the many” to “the many watch
the few,” referred to as the Synopticon. Mathiesen (2006) still finds panoptic evidence in the
growth of the Europol Information System and the Shengen Information System with
computerized policing. He states, “…organized computerized surveillance of whole categories
of people rather than individuals, with a view towards possible future crimes rather than past acts
has grown enormous” (Mathiesen, 2006, p. 218). However, Mathiesen (2006) finds Foucault’s
21

interpretation ignores the influence of mass media in desensitizing the public to surveillance
while giving great power to media personalities. Mathiesen (2006) acknowledges that
Panopticons co-exist with many decentralized Synopticons that can be combined and
coordinated through technology to direct consumerism in Western capitalist societies.
The “hidden apparatus” of surveillance is then a method of political control that is
difficult to concretely identify as it molds and adjusts consciousness (Mathiesen, 2006). An
example of the Synopticon is the body-worn police camera if the objective of deployment is to
promote public trust and make the police accountable to the people. However, this synoptic
effect is not the only product of body-worn cameras when facial recognition capability is added
into the capture. Current features of artificial intelligence allow for mass presence of surveillance
that extends the threshold and reach of panoptic and synoptic structures, tightening the grasp of
its control unto those within the scope of closed-circuit television’s field of vision. As these
structures grow, the influence on behalf of not only the deterrence of antisocial behavior, but the
encouragement of consumer behavior increases at a steady rate. Mathiesen (2006, p. 221)
explains, “The decentralized, narrowly oriented panopticons may quickly be combined into large
broad-ranging systems by simple technological devices, covering large categories of people in
full detail.” Mathiesen’s (2006) criticism of the comprehensiveness of Foucault’s theories
relates strongly to the changing nature of surveillance due to increased technological capabilities.
Further discernment toward the modernity of surveillance reveals the possibilities of a
multiplicity of tools acting together in a “…rhizomatic leveling of the hierarchy of surveillance,
such that groups which were previously exempt from routine surveillance are now increasingly
being monitored” (Haggerty & Ericson, 2003, p. 606). Kevin Haggerty and Richard Ericson
22

(2003) reveal in The Surveillant Assemblage that technology has changed the paradigm to one
where surveillance is decentralized and has numerous purposes beyond molding good behavior.
As an assemblage, surveillance combines systems, practices and technologies and integrates
them to achieve exponentially increased levels of capacity (Haggerty & Ericson, 2003). The flow
and unstable boundaries that are caused by multiple components of the assemblage prevent the
banning of ‘unpalatable technology’ such as video surveillance (Haggerty & Ericson, 2003). An
example of an assemblage is the ‘multi-agency’ approach in law enforcement. Additionally, non-
criminal justice entities are encouraged to cooperate with law enforcement by sharing data. The
notion as to whether closed-circuit television is an extension of the Prison Industrial Complex is
a multifaceted and complicated claim to decipher. Such claims are sound in that closed-circuit
television usage often relies on collaboration and coordination of government and private
resources. This conglomeration of mechanisms contributing to the proliferation of the prison
system and its external workings identifies the Prison Industrial Complex’s “…overlapping
interests of government and industry that use surveillance, policing and imprisonment as
solutions to economic, social and political problems” (Empty Cages Collective, 2019, para. 1).
Haggerty and Ericson (2003) believe that surveillance has moved beyond Foucault’s discipline
focus and is increasingly used to manipulate economic strategy.
3.2.2 Rational Choice Theory
Understanding the motivations of the criminal is key to finding deterrents that are
effective. Rational Choice Theory proposes that risk/benefit economics determine the potential
for crime as individuals make logical decisions about their own self-interest. Keith Hayward
(2007) takes a methodical approach to test the limitations of Rational Choice Theory (RCT).
23

Referring to Beccaria, Bentham, Locke and Hume, he explains:
Central to these writers’ accounts of criminality was the belief that human nature was
predicated upon the search for pleasure and the avoidance of pain, and that human action
was consequently organized around calculative strategies aimed at utility maximization:
Nature has placed mankind under the governance of two sovereign masters, pain and
pleasure (Hayward, 2007, p. 233).
While this theory lacks attention to social causes of deviant behavior, it provides a route for more
immediate deterrent action. Instead of focusing on understanding the cause of deviance, the
focus engages in the means to control it. Rising crime rates in the 1970s and 1980s encouraged a
more solution oriented, conservative movement to deter crime by limiting opportunity for
deviant behavior (Hayward, 2007). Ken Pease (2006, cited in Hayward, 2007, p. 234) explains,
“The starting point of RCT is that offenders seek advantage to themselves by their criminal
behavior. This entails making decisions among alternatives. These decisions are rational within
the constraints of time, ability and the availability of relevant information.” Also commenting on
the mentality of the criminal, Charles Murray (1973, p. 117) observes:
Their calculations seemed to be based on a hard-headed appreciation of the facts. Real
risks of being observed, real risk of someone calling the police or intervening, and real
risk of being cut off without an escape route loomed largest in their thinking.
This theory has inspired new methods of surveillance that are designed to prevent the
opportunity for crime on ‘soft targets.’
Building on the Rational Choice Theory, situational crime prevention methods are target
specific. Keith Hayward (2007, p. 235) explains:
In other words, the emphasis is squarely on micro-preventative crime strategies, and as
such local authorities, businesses, and the public at large are encouraged to employ
24

practical deterrents to ensure that buildings, public spaces, and people do not provide
‘soft targets’ for the criminal.
High profile surveillance and physical security are key components to eliminating ‘soft targets.’
Hayward (2007) does point out that there is not universal support for relying solely on situational
crime strategies because it diverts efforts away from social remedies. He states,
… for many commentators such a pragmatic approach to the crime problem was a major
step back. Indeed, some even suggested that it heralded the advent of a new ‘criminology
of normality’ or ‘culture of control’ and management of social problems (Hayward, 2007,
p. 236).
These criticisms are reminders of the discipline approach of Foucault. Hayward’s (2007)
reasoning then centers on the fallacy of relying exclusively on Rational Choice Theory. He
points to the possibility of an irrational actor committing acquisitive/property crimes due to the
influence of drugs or a high emotional or thrill element (Hayward, 2007). Despite Hayward’s
(2007) critique, the Rational Choice Theory and its convergence with situational crime
prevention tactics have support from the public and law enforcement and empower private
citizens.
3.2.3 Environmental Criminology
Video surveillance serves as a means of situational crime prevention and is readily
observed through the scope of Environmental Criminology. Three main strands present
themselves in the deliberation of the location to which closed-circuit television should be
effective, the design of the environment, and the necessity for conscious effort toward
management of the current environment of a geographical location in relation to crime hot spots.
25

The idea that the neighborhood environment contributed to ecological causations of crime was
not new as The Chicago School studied location specificity of high-delinquency areas in the
early 1900s (Lutters & Ackerman, 1996). Their geographically based studies examined the
relationship of urbanization and urban decay on tendencies toward crime (Lutters & Ackerman,
1996).
In 1973, Oscar Newman presented a novel idea for preventing crime by manipulating the
environment surrounding a crime target using urban design. Newman (1973) based his
conclusions on a study of the architecture of two housing projects that had the same demographic
of people in the same neighborhood but had different crime rates. Key to Newman’s theory is the
establishment of ‘defensible space’ by “…creating the physical expression of a social fabric that
defends itself” (Newman, 1973, p. 325). He further states:
All the different elements which combine to make a defensible space have a common
goal – an environment in which latent territoriality and sense of community in the
inhabitants can be translated into responsibility for ensuring a safe, productive, and well-
maintained living space (Newman, 1973, p. 325).
The potential criminal perceives that he or she is recognizable and improved surveillance
controls access. Essential to maintaining a ‘defensible space,’ is “…the capacity of physical
design to provide surveillance opportunities for residents and their agents: mechanisms for
improving the capacity of residents casually and continually to survey the nonprivate areas of
their living environment, indoor and out” (Newman, 1973, p. 332). These calculations divide
surveillance in the maximum-security society into strategic and nonstrategic components for
maintaining defensible space (Marx, 2016). This focus on structural innovation is a reminder of
26

Bentham’s Panopticon that motivates architectural changes resulting in concrete reductions of
crime in criminogenic environments. Supporting those changes, closed-circuit television plays an
important role in the visual surveillance component of defensible space.
3.2.4 Opportunity Theory & Routine Activity Theory
In consideration of the environmental criminological aspects of surveillance, facial
recognition technology adds to the impact of closed-circuit television’s perception as a method
of deterrence to antisocial behavior due to the implied sense that technological advancements
increase efficiency. This, in turn, encourages belief in an increased chance for the incarceration
rate as a by-product of the development of artificial intelligence. The risk of exposure to
geographical locations, predestined to developing into potential crime hotspots, is greatly
influenced by the presence of the opportunity to commit a crime. This is known as the
Opportunity Theory. Reduction of the contributing factors that form the construct of opportunity
involves the presence of a deterrent such as closed-circuit television or foot patrol officers. To
break it down in terms of logic in eliminating the potential for crime, it is best looked at in
consideration of Routine Activity Theory.
Though the opportunity to commit a crime could always remain present, the notion that
all activity is expected to be recorded on real-time video camera footage provides incentive
leading to the displacement of criminal activity to other regions. Identifying ‘hot spots of crime’
reinforces the importance of place in what social ecologist from the Chicago School, Robert
Burgess, labeled as Concentric Zones (Weisburd, 2018). This concept properly exemplifies the
first strand of environmental criminology, location of the crime. Closed-circuit television was not
27

considered at the time of the Chicago School arguments, though the notion that there are
‘concentric zones’ within cities still holds ground even today. David Weisburd (2018) found that
in the cities he researched (Cincinnati, Ohio; New York, New York; Sacramento, California;
Seattle, Washington; and Tel Aviv, Israel), 50% of crime occurred in 4.2-6% of distinct city
segments. Closed-circuit television has the potential to drastically affect what such areas reflect
of today’s application of the schematic model and structural aspects of urban and suburban
infrastructure to crime, in terms of what offences occur and where they occur.
The causation of crime, in terms of environmental influence as opposed to the behavioral,
psychological and internal motivations of the offender, places emphasis in causal reasoning on
behalf of external stimuli such as the environment from an ecological standpoint. This viewpoint
avoids factors such as that of Robert Merton’s Strain Theory, Robert Agnew’s General Strain
Theory, or a Marxist interpretation of capitalism’s effect on individuals of low socio-economic
status with limited opportunities to achieve financial gain. The inability to attain economic
prosperity then leads to a desire to perpetrate unconventional and illicit methods directed at
obtaining fiscal success. These theories typically address factors involving the motivations
toward criminal behavior from a sociological positivist perspective of criminology. Though these
influences are not predominantly considered to be direct sources for motivations of individuals to
commit crime through an environmental criminological perspective, such sociological positivist
impacts are indirectly connected. Therefore, there is a need to acknowledge each chain of events
as an aspect of influences to the patterns in which criminal behavior is formed.
In spite of the increase in economic prosperity since the 1960s, the violent crime rates in
the United States were trending up at alarming rates (Cohen & Felson, 1979). Whilst trying to
28

locate the triggers for this paradox, The Routine Activity Theory was identified by Cohen
and Felson in the 1970s. Cohen and Felson (1979) argued that changes in routine activities have
a clear effect on the incidence of crime. For a violation to occur, three elements converge that
are “(1) motivated offenders, (2) suitable targets, and (3) the absence of capable guardians
against a violation” (Cohen & Felson, 1979, p. 589). Cohen and Felson (1979) assume the
continual existence of motivated offenders and therefore, the changeable elements are the
suitable targets and the absence of a guardian. First, using closed-circuit television will make the
target less suitable due to rational decision. Like the Rational Choice Theory, the Routine
Activity Theory is not providing societal answers to understand the causation of deviance.
Second, in a risk/benefit thought process, closed-circuit television acts as a substitute for a
guardian. If one of these three spatio-temporal elements is unavailable, crime can be deterred.
Using the compatible Environmental Theory, intervention on the physical space with the
placement of cameras has power in crime prevention and in collecting evidence following a
crime. Cohen and Felson (1979, p. 592) state, “In addition, many studies report that architectural
and environmental design as well as community crime programs serve to decrease target
suitability and increase capable guardianship.” In their study, using statistics and crime rate
trends, household activity played a major role when a criminal determined the suitability of a
target (Cohen & Felson, 1979). The household activity is essentially the guardian. At the time of
Cohen and Felson’s work, closed-circuit television was not a readily available option as a
guardian, but now it is a viable alternative. Therefore, video observation acts as a reasonable
example of a guardian.
In the article, Guardianship for Crime Prevention, researchers provide in-depth
29

evaluation offering conclusions of the association of closed-circuit television as an
essential, capable guardian element involved within the spectrum of the Routine Activity Theory.
The authors found that closed-circuit television is most effective when it is actively monitored
with an operator who watches the video capture in real-time with the ability to intervene (Hollis-
Peale, et. al., 2011). This theory does hinge on the perpetrator acting in a rational manner in a
defensible space. At this point, Rational Choice Theory proposes that risk/benefit economics
determine potential for crime. These practical considerations account for the validity in the
capacity for deterrence and identification, which are achieved through facial recognition.
Body-worn cameras (BWC) are capable in the role of guardian for molding behavior
during police/civilian encounters. Studying the bilateral effect on both police and civilians,
Wood and Groff (2019, p. 65) report, “…the evidence to date indicates that BWCs play a
promising role in diminishing bad outcomes from police–citizen encounters, especially
encounters where use of force options come in to play for officers.” Following deployment of
body-worn cameras by the Philadelphia Police Department, a ‘pre-post’ survey concludes:
Officers reported that citizens are not necessarily aware of the presence of BWCs,
especially since officers wear many other pieces of equipment. However, in cases where
citizens do notice, or where officers announce that they are being recorded, officers
remarked that people’s attitudes and behavior can change in a positive direction (calming
people down once they realize they are on camera) (Wood & Groff, 2019, p. 67).
Additionally, body-worn cameras have the potential to expand the role of guardianship through
proactive policing. Wood & Groff (2019, p. 71) comment:
BWCs are more portable; the camera goes where the officer goes. Officers have more
control over BWCs; the camera can be “aimed” by the officer and adjusted dynamically.
Indeed, officers can use BWCs in a coordinated fashion; they can work together to
30

provide different angles to document a place or particular situations at places as they
unfold.
While Cohen and Felson’s original study, Social Change and Crime Rate Trends, presents
research that pertains to a window in time, the concept of video guardianship with the addition of
facial recognition capability as a crime deterrent is valid.
3.2.5 Biological Positivism
Early proposals of biological positivism provide a link to the current dimensions of
biometrics such as facial recognition. Cesare Lombroso is credited with attaching phenotypical
identifiers as easily recognizable ‘red flags,’ modeling the criminal look that is understood in
Criminal Man (Carrabine, et al., 2020). This Darwinian approach explains the longstanding
fascination with visual identification, but at the same time, it explains the racial bias and
assumptions that can exist in the seemingly neutral witness of closed-circuit television.
Lombroso singled out features like “enormous jaws, high cheek bones, prominent superciliary
arches, solitary lines in the palms, extreme size of orbits, handle-shaped or sessile ears” as
indicators of a born criminal (Carrabine, et al., 2020, p. 61). While this theory is understood to be
dated and potentially dangerous in its assumptions, it still has underlying implications for biases
in facial recognition technology.
The neutrality of the technology is not supported by researchers or journal articles.
Following 9/11, the metaphor, ‘the face of terror,’ was frequently used in newspaper articles and
white papers by facial recognition technology suppliers to committees in government (Gates,
2006). Kelly Gates (2006, p. 434) explains, “With images of the faces of the hijackers and of
31

Osama Bin Laden circulating in the press, the ‘face of terror’ metaphor invoked specific objects:
mug-shots and grainy images of Arab men.” The development of facial recognition technology
within the studies of emotional detection has increased rapidly and shown serious advances
through the machine learning of Convolutional Neural Networks (CNN). Details of emotional
detection via facial recognition technology is broken down and represented in the article,
Criminal Tendency Detection from Facial Images and the Gender Bias Effect (Hashemi & Hall,
2020). This study summarizes the correlational studies of criminogenic behavior and facial
features exhibiting six recognizable emotional features (Hashemi & Hall, 2020). This article has
since been retracted due to failure to receive approval from an ethics committee prior to research.
Research conducted by Hashemi and Hall (2020) follow up on the research of Wu and Zhang
(2016) that tested whether criminality could be predicted through photographs. The researchers
specifically based their topic on the theories of Lombroso’s Criminal Man (Hashemi & Hall,
2020). Using a comparison of 10,000 photos of criminal and non-criminal individuals, Hashemi
and Hall (2020, p. 8) report, “The test accuracy of 97%, achieved by CNN, exceeds our
expectations and is a clear indicator of the possibility to differentiate between criminals and non-
criminals using their facial images.” While accuracy will be addressed in a later section, it is
important to note that biological positivism is still considered a plausible theory in some current
technical research, despite the danger of labeling and stigma based on physiognomy.
Nuance to which values and priorities of concerns such as security and protection of civil
liberties, is considerable due to the implications to which stigma is generated. Such
categorizations of specific cohorts within the social strata of modern urban culture are associated
with social control and acknowledgment of these associations is necessary to weigh the arbitrary
32

nature presented in the unpredictability of the surveilled subject resembling that of the dependent
variable (Hashemi & Hall, 2020). Racial bias cooperates as a detriment to the attainability of
acceptance of proper implementation of such forms of surveillance, including the usage of facial
recognition technology. Contrary to consideration of facial recognition as the dominant paradigm
for law enforcement’s presence within the sphere of ‘techno-crime’ as a ‘techno-policing’
mechanism, Biological Positivism and the studies associated with Convolutional Neural
Networks, Logistic Regression, and Support Vector Machines cannot be the only desired aspect
of facial recognition. The multiplicity of other aspects affecting the outcome of video
surveillance footage resolution requires more research.
3.3 Research on Body-Worn Cameras Without Facial Recognition
Although the widespread use of body cameras by law enforcement is relatively recent,
thorough research is available. Lum, Stoltz, Koper and Sherer (2019) compile the results of
seventy published studies through 2018. From this evaluation, conclusions can be drawn for the
impact of this technology on the public and the police. The officers accept and value the
technology as a protection for themselves against false accusations and the use of cameras
reduces the number of complaints against officers from the public (Lum, et al., 2019). It can be
inferred that the camera as a witness molds better behavior on the part of both the officers and
civilians. There is a concern that the cameras will cause ‘camera induced passivity’ due to
recorded scrutiny (Lum, et al., 2019). The results on this topic were conflicting but overall, the
number of subject stops declines after the addition of body-worn cameras (Lum, et al., 2019).
Finally, although the goal of deploying body cameras was initially intended to create public trust
and better relations between the public and police, an unintended consequence is that camera
33

evidence may lead to more criminal convictions. These recordings are highly valued by
prosecutors with 80% supporting its use and 63% believing camera evidence helps prosecutors
and not defense attorneys (Lum, et al., 2019).
3.4 Ethical Implications
Resources from ideological viewpoints contain insight on motivations and behavior of
individuals participating in the ‘maximum security society.’ Gary Marx (2016, p. 4) comments,
“Such a society increasingly relies on categorical suspicion, dossiers, actuarial decision making,
self-monitoring and the engineering of control.” For Marx (2016), there is a distinction between
non-strategic information gathering and adversarial, strategic surveillance where information is
not freely given. In his book, Windows into the Soul, Gary Marx (2016, p.20) defines
surveillance as “scrutiny of individuals, groups, and contexts through the use of technical means
to extract or create information.” He further questions the concepts of privacy and borders and
their implications for violations when compliance is the goal of surveillance (Marx, 2016). The
usage of closed-circuit television within the private sector of business as well as the public sector
has caused a dramatic pressure towards disintegration and removal of boundaries. Either side of
the public and private sectors maintains highly advanced capabilities of surveillance. The
partition between the two runs the risk of eventually evolving structurally to that of a
metaphysical floodgate to which only one side has access to its open and close capability.
In order to determine resistance to the capture of personal information through
surveillance, Marx explains measurable concepts. He defines ‘surveillance slack’ as “…the size
of the gap between what technology is capable of doing and the extent of its application” (Marx,
34

2016, p. 304). On the other hand, ‘achieved privacy ratio’ is the “content of information
individuals seek to and/or are able to protect” (Marx, 2016, p. 305). Marx (2016) concludes that
conservatism in the use of surveillance provides the room to consider both the short and long-
term consequences. The paradoxical priorities of security versus privacy when considering
surveillance depend on the values held by society. He states, “Surveillance is neither good nor
bad, but context and comportment make it so” (Marx, 2016, p. 284). Applying this statement to
law enforcement, Marx (2016, p. 288) states, “Under appropriate conditions, agents have a right
and even an obligation to surveil, but they also have a duty to do it responsibly and accountably.”
3.5 Conclusion
This literature review has shown that the theoretical basis for using video surveillance has
practical applications that support its value as a deterrent to crime. Including empirical research
regarding body cameras explains the acceptance and use of a technological tool that incorporates
mobile video surveillance into law enforcement. As legislation is considered regarding the extent
that facial recognition can be enabled on an accepted piece of police equipment, ethical concerns
emerge relating to the goal and purpose of deployment.
35

CHAPTER 4: METHODOLOGY
Due to limitations created by the pandemic, my research methods will include no direct
personal interactions.
4.1 Quantitative Research
I will use a meta-analysis approach to gather relevant, published studies and empirical
data that connect facial recognition technology to issues of unreliability. A recurring objection to
facial recognition technology is the accuracy of the algorithms and potential for
misidentification. Reporting from government agencies and research studies provides evidence
of reliability and conditions for errors. I will analyze independent research on skin tones that
increases the likelihood of misidentification. Next, I will find examples of government ‘self-
reporting’ to find trends of improvement in facial recognition technology. In the same meta-
analysis, I will look for studies that illustrate the behavioral effects due to body-worn cameras on
law enforcement officers and the public. This research will confirm the capability of video in a
guardianship role.
Next, I will do background research to produce a case study on Project Green Light in
Detroit, Michigan. Demographic information, distribution of surveillance sites and crime rate
comparisons will complete an understanding of the experience of real-time facial recognition
surveillance in a defined area. Following a thorough understanding of the theories of surveillance
and mechanics of facial recognition technology, the case study on Project Green Light in Detroit
will demonstrate the successes, acceptance, and public opposition to a concentrated system of
surveillance. The Detroit Police Department has the technology to enable body cameras that have
36

facial recognition but has stated that they will not use this capability. Instead, Detroit
aggressively uses real-time facial recognition in a city-wide deployment of stationary closed-
circuit television. Reports from police representatives and community research provide a
historical perspective on the acceleration of the initiative throughout the city and will illustrate
the power of real-time surveillance in contrast to after-the-event surveillance for investigation.
Another source for research will be news articles and interviews. These sources will reveal
current tensions and challenges caused by the deployment of the technology.
Finally, an examination of ethical issues by authors such as Gary Marx and Shoshana
Zuboff will complete the understanding of ordinary citizens’ objections to increased surveillance
and calls for reasonable regulation.
4.2 Ethical Considerations
As I will be using historical and secondary, published accounts and empirical research, I
do not have any ethical considerations to limit analysis.
4.3 Challenges to the Research
Several police departments across the United States use facial recognition technology as
an evidentiary tool after-the-event of a crime for investigative purposes. Businesses that produce
the software that enables real-time surveillance have offered their products to law enforcement
agencies to conduct free trials. However, these agencies are, to a large degree, unwilling to
provide results of these trials. By using widespread surveillance that is monitored by a Real-
Time Crime Center with facial recognition software, Detroit’s Project Green Light provides a
meaningful approximation of the impact that body cameras enabled with facial recognition that
37

are monitored in real-time will have on a distinct population.
38

CHAPTER 5: ACCURACY AND MONITORING
Following the theoretical background that connects surveillance to behavior, it is
important to understand the technology that creates facial recognition capability. Facial
recognition technology is a form of biometric data. Biometric data is the measurable physical
characteristic that can be used to identify a person digitally. The most familiar example is a
fingerprint. Due to the mathematical nature of the software, the precision of the algorithms, and
the scope of dissemination, empirical data is needed. Many authors give a concise,
understandable lesson in biometrics through extensive research and reports. The Georgetown
Law Center on Privacy and Technology produced a thorough report, The Perpetual Line-Up,
evaluating the use of facial recognition technology by police in the United States that offers key
points on the mechanics (Garvie, et al., 2016). Facial recognition is the automated comparison of
two or more faces to identify a person using an algorithm. An algorithm extracts and numerically
quantifies features like eye position or width of the nose, then creates a numerical score based on
the similarity of their nodal points or ‘biometric template’ (Global Justice Information Sharing
Initiative, 2017). In this way, a face becomes a data set. These templates are stored in an archive
for future comparison to unknown persons.
To achieve potential matches, it is necessary to have a database of photographs for
comparison. State and local law enforcement have access to their own databases but can request
to use the FBI database. Governmental agencies in the United States are required to produce
reports about their facial recognition systems and these provide valuable insight into the extent of
usage. For instance, at this time, the FBI database includes over 641 million photos derived from
driver’s licenses, passports, and mugshots (United States Government Accountability Office,
39

2019). As the technology progresses, live video streaming can be deployed on 4G and 5G
networks through mobile devices (Gershgorn, 2020). With the speed that this technology
changes, it is useful to find trustworthy news reporting to stay current on new developments.
A key factor in the legitimacy of facial recognition technology is the accuracy of its
results. Governmental audits and reports provide detailed information on facial recognition
technology data. Industry standards of algorithm accuracy are measured and recorded in
governmental reports produced by the National Institute of Standards and Technology (NIST)
through the United States Department of Commerce. Assessments, nationally recognized as Face
Recognition Vendor Tests, determine the standard for the most current algorithmic exactitude to
be expected (Grother, et al., 2019). In 2016, The United States Government Accountability
Office made six recommendations to the FBI regarding privacy and accuracy. However, a 2019
follow-up report revealed that the FBI had only taken action on three of those recommendations
(United States Government Accountability Office, 2019). Further clarification regarding
unfulfilled initiatives for improvement of face recognition databases and technology reveals that
as of May 2019, the FBI had only fully implemented one of the recommendations (United States
Government Accountability Office, 2019). Algorithmic biases and false positives present
continual obstacles associated with current facial recognition software. Additionally, the report,
Face in Video Evaluation (FIVE), reveals, “Non-cooperative imaging of subjects is generally
adverse to recognition accuracy, because face recognition algorithms are sensitive to head
orientation relative to the optical axis of the camera, accompanying shadows, and to variations in
facial expression” (Grother, et al., 2017, p. 5). The ‘non-cooperative’ description in this case
does not infer resistance of the subject, but instead, the less than ideal option where the image is
40

not a face-front, still image. These ‘non-cooperative’ images are the source that body-worn
cameras enabled with facial recognition software would be transmitting. FIVE concludes, “This
leads to the possibility that a member of the public can be falsely matched to someone on a
watchlist; the occurrence of such hazards is mitigated by elevating a recognition threshold”
(Grother, et al., 2017, p.2).
In practice, facial recognition algorithms have been shown to have less accuracy in
identifying dark-skinned people. The National Institute of Standards and Technology that
evaluates facial recognition software by vendors reports, “With domestic law enforcement
images, the highest false positives are in American Indians, with elevated rates in African
American and Asian populations; the relative ordering depends on sex and varies with
algorithm” (Grother, et al., 2019, p. 2). A study from MIT confirmed these findings through
complex research concerning gender and exact skin tones (Buolamwini & Timnit, 2018).
Specificity in such evidence of algorithmic bias, and the complications brought forth through
face recognition vendor surveys expose the need for caution in the implementation of facial
recognition technology. Acknowledging the barriers to accuracy provides insight on the aspects
of its functions that require refinement. Awareness of weaknesses in its deployment as a
surveillance tool is a necessary component to its current usage. The National Institute of
Standards and Technology acknowledges, “In identification applications such as visa or passport
fraud detection, or surveillance, a false positive match to another individual could lead to a false
accusation, detention or deportation” (Grother, et al., 2019, p. 5). The ongoing availability of
public reports illustrates levels of accountability and the progression of accuracy in facial
recognition algorithms.
41

CHAPTER 6: CASE STUDY – PROJECT GREEN LIGHT
Prior to the 1960s, Detroit, Michigan, had a thriving economy based in the automotive
industry. “The Motor City” was home to General Motors, Ford, and Chrysler, known as the Big
Three Automakers (Counts, et al., 1999). Following the civil rights movement, the oil crisis of
1979, the shift of auto manufacturing to Mexico and the rise in popularity of foreign cars,
Detroit’s economy went into a downward tailspin (Counts, et al., 1999). As racial unrest rose,
unemployment accelerated and wealthy, white citizens moved to the suburbs. The city of Detroit
lost its property tax base and headed toward financial insolvency. By 2013, Detroit filed for
Chapter 9 bankruptcy, which was the largest municipal bankruptcy to date, and in 2018, was
reported to be the “poorest city” in the United States with 34.5% of its citizens living below the
poverty line (MacDonald & Chambers, 2018). Correspondingly, Detroit has fluctuated between
first and second city with the highest crime rate in the United States with 2,056.7 violent crimes
per 100,000 people in 2018 (The World Atlas, 2019). According to Captain Sloan of the Detroit
Police Department, during 2015, it was observed that 25% of violent crime in the city was
occurring within 500 feet of gas stations (Detroit Community Technology Project, 2019). This
information led to an innovative program, Project Green Light, that was implemented on January
1, 2016, to prevent and combat the city’s crime crisis (Detroit Community Technology Project,
2019).
Project Green Light is a targeted police program that partners with business owners in an
effort to curb crime in Detroit using risk modeling. Business owners pay between $4,000 -
$6,000 to acquire signs, install high definition cameras and enhanced security lighting that
includes flashing green lights to make a statement that the property is being monitored (The City
42

of Detroit, 2020). Then, a monthly fee of approximately $150 is charged for data storage (The
City of Detroit, 2020). Closed-circuit television transmits the feed directly to the department in
real-time and has facial recognition capability. These feeds are monitored at a 24-hour
surveillance center called a Real-Time Crime Center (Detroit Community Technology Project,
2019). A Real-Time Crime Center with the presence of 24-hour monitoring offers business
employees and customers a sense of security that would not persist if Project Green Light were
not in place. Further, project participants are given Priority 1 status on any incidents at their
business (Detroit Community Technology Project, 2019). Security claims are exemplified by Jon
Campbell, an owner of McDonald’s fast food restaurants participating in Project Green Light,
who affirms, “My customers and employees feel secure knowing law enforcement is monitoring
in real-time should they be needed” (Hunter, 2017, para. 29). As of June 2019, Project Green
Light had 564 partners (cameras) and is now adding a public intersection component of 440
cameras to monitor neighborhoods (Gross, 2019). These partners now include not only gas
stations, but also churches and reproductive health centers (Detroit Community Technology
Project, 2019).
In its Real-Time Crime Center, Project Green Light employs police officers and ‘non-
sworn’ individuals to monitor video footage (Hunter, 2017). In other words, a ‘non-sworn’
individual is a civilian. Further, video obtained at the Real-Time Crime Center is shared with
government partners including the FBI, the Department of Homeland Security, and private
partners such as DTE, Rock Financial, Downtown Detroit Partnership, and the Ilitch Holdings
(Department Board of Police Commissioners, 2018). Concerns about staffing with a growing
base of participants is reasonable when considering whether the Real-Time Crime Center can
43

adequately monitor over 500 locations and whether there will be misuse if more civilians are
employed to monitor feeds. Additionally, video feed shared with corporate alliances like Ilitch
Holdings and Rock Financial have the potential to be misused for purposes other than crime
prevention and investigation.
In the process of using facial recognition software, a monitor must visually confirm the
match made by the technology. The Center on Privacy and Technology at Georgetown Law
reports that human examiners make the wrong decision on matches about half of the time
(Garvie, et al., 2016). In fact, the U. S. Federal Bureau of Investigation does not set or enforce
accuracy standards and only recommends that police departments perform their own accuracy
checks (Federal Bureau of Investigation, 2019). Aside from human error, facial recognition has
been shown to have less accuracy in identifying dark-skinned people. The National Institute of
Standards and Technology in the United States that evaluates facial recognition software by
vendors found higher rates of false positives for Asian and African American faces relative to
images of Caucasians, with the least accuracy in dark-skinned women (Grother, et al., 2019). A
false positive occurs when two different individuals are matched as the same person. The risk of
misidentifying innocent citizens with dark complexion limits the accuracy of searches and poses
a tremendous risk to these individuals. Unfortunately, with such a hiccup in the system, in a city
like Detroit where 78.6% of the population is black, according to The United State Census
Bureau (2019), the incentive to increase efforts at perfecting the accuracy of facial recognition of
all ethnicities is a valid concern.
The Detroit Police Department offers impressive statistics citing, “Incidents of violent
crime have been reduced by 23% YTD at all sites and 48% YTD at the original eight sites
44

compared to YTD 2015” (The City of Detroit, 2020). The most noted business associations that
have shown dramatic improvement in decreasing rates of crime are gas stations, which were the
mentioned original sites (The City of Detroit, 2020). Crime rates have decreased exponentially
over the past few years and part of the explanation for such success in the Detroit Police
Department’s Public Safety Plan is due to the intervention of Project Green Light. Garvie and
Moy (2019, para. 17) report:
DPD’s face surveillance system may expand beyond Project Green Light as well. The
Department’s face recognition policy, which went into effect on July 1, 2018, states that
DPD “may connect the face recognition system to any interface that performs live video,
including cameras, drone footage, and body-worn cameras.
The additional layer of mobility to the current real-time surveillance would convey more power
to the Detroit Police Department.
Despite the apparent rapid decline in crime rates, the most controversial aspect of Project
Green Light is the argument of whether it is legal to require businesses to participate in this
system at their own expense. The City of Detroit proposes to mandate participation in Project
Green Light if a business is open after 10:00 p.m. (Hunter, 2017). This requirement would
include sports stadiums and theaters in addition to gas stations and liquor stores. Concern is
raised in consideration that Project Green Light is a method of paying for policing or extortion
for protection beyond legal taxation. Proceeding to point out the legal implications, George
Hunter (2017, para. 3) states, “Others insist it would be government overreach to force
businesses to join the program, raising privacy concerns and questioning whether such a broad
ordinance would be legal.” Further, The City of Detroit provides an approved vendor list that
must be used for the $4,000-$6,000 installation of signs, lighting and high definition cameras and
45

monthly data storage but explains that all payments go to the vendors, not the city (The City of
Detroit, 2020). Contradicting the legitimacy of a Detroit mandate, U. S. Department of the
Treasury (2020, para. 3) states, “Our American economy is based on the free enterprise system.
Consumers are free to decide how to spend or invest their time and money.” In support of the
public good, cities and counties provide police protection. The U. S. Department of the Treasury
(2020 para. 4) specifies, “Two good examples are national defense and state or local police
protection. Everyone benefits from these services, and the most practical way to pay for them is
through taxes, instead of a system of service fees.” As Project members get Priority 1 for their
911 emergency calls, The ACLU explains, “In Detroit, 911 calls aren’t treated equally – and if
business owners want quality service, they’ll have to subsidize the construction of the police’s
surveillance apparatus to get it” (Williams, 2018, para. 5). In this case, regulation potentially
promotes technology usage through mandates, for better or for worse.
City officials assert that Project Green Light supports both economic development and
safety and are continuing to expand the program to locations such as restaurants, multi-family
dwellings, and mixed-use developments (Detroit Community Technology Project, 2019). Even
with research contradicting the effectiveness of camera presence in schools and potentially
psychologically detrimental consequences, the City of Detroit has moved forward with an
expansion into public schools with monitoring at the Real-Time Crime Center (Detroit
Community Technology Project, 2019). In a different capacity of integrating facial recognition
technology into video surveillance, the city policies directly state that although the Detroit Police
Department cannot use the cameras for immigration enforcement purposes, they do not forbid
giving access to Department of Homeland Security and facial recognition may be used to
46

monitor First Amendment protected events (Detroit Community Technology Report, 2019).
Further areas of concern stem from data storage. A suspect of a crime may have their image
stored in the system until such time as they are “identified, no longer a suspect, or the statute of
limitation has expired” and “the public may or may not be notified of data breaches” (Detroit
Community Technology Report, 2019, p.8).
Even as the police department claims success, critics focus on the monetary and
manpower resources that are diverted away from addressing the sociological causes of crime like
poverty and inequality (Detroit Community Technology Project, 2019). These critics believe that
instead of a more militarized society and police force, marginalized citizens would see a greater
benefit from improved housing, education, and affordable utilities (Detroit Community
Technology Project, 2019). A study by John Hipp and Kevin Kane (2017), confirms that rising
levels of inequality elevate the crime rates in United States cities. Additionally, critics protest the
erosion of privacy and questionable access and use of data. Despite these points, Detroit was
faced with a crisis of criminal activity and has taken dramatic, proactive steps to regain control
of the situation. The community of citizens and law enforcement will need to evaluate results and
decide if “…the risk acceptable when measured against the perceived benefits” (Leman-
Langlois, 2008, p. 28). In the coming years, continued scrutiny of Project Green Light and its
successes and costs will influence the use and regulation of comprehensive video surveillance in
police departments across the United States.
47

CHAPTER 7: ANALYSIS AND THEORETICAL CONNECTIONS
7.1 Introduction
While facial recognition technology has many benefits, the public is leery of widespread
use. Due to the past emphasis on national security, the public has accepted facial recognition
technology in certain locations such as airports (Reservations.Com, 2019). Now, however, there
is push-back. The question is, what creates the conflict where the public and police both support
body camera use, but the public does not universally support body camera use with the addition
of facial recognition technology that is monitored in real-time. Through Project Green Light,
Detroit has the capability to deploy body cameras that could be monitored by their Real-Time
Crime Center (Garvie & Moy, 2019). At this point in time, the city has not sanctioned adding
this tool to their surveillant assemblage of private businesses and law enforcement.
Several theories of surveillance have been considered to shed light on the controversies
surrounding possible deployment of body-worn cameras enabled with facial recognition
technology that is monitored in real-time. Bentham’s Panopticon Prison, Environmental
Criminological Theories such as Routine Activity Theory, Rational Choice Theory, Opportunity
Theory, Situational Crime Prevention and Burgess’ Concentric Zones involving location
specificity of crime, and positivist leanings including Biological Positivism have relevance in
this research. Due in part by the reciprocal nature of these fields in criminology,
acknowledgement of the functional interdependence amongst one another allows those in search
of preventative measures directed at criminal behavior, an effective social control strategy in the
containment of crime. Viewing real-time facial recognition in Project Green Light from these
theoretical standpoints enables a comparison of closed-circuit television that is used strategically
48

addressing crime ‘after-the-fact’ with potential to provide incriminating evidence and
accountability versus taking the technology mobile.
7.2 Displacement of Power
There is no debate that Detroit’s violent crime impacted all of its citizens, but the strong
application of surveillance has created questions about social control and societal interventions
when facial recognition is added to real-time, video surveillance. With a purpose of crime
deterrence and self-regulation, the anti-panoptic notion of Project Green Light is that wherever a
closed-circuit television camera with a flashing green light is seen, it alerts citizens that they are
being watched and recorded. Because the viewed knows that the viewer is constantly watching in
real-time, within the context of Project Green Light, the questionability that arises within the
surveilled amidst a true panoptic architectural structure would not apply. Bentham’s train of
thought regarding the Panopticon involved a degree of uncertainty on behalf of the detainee’s
notion of whether they knew assuredly that they were being surveilled whilst the potential for
being surveilled was always there (Galic, et al., 2017). The Panopticon relied more heavily on
deterrence as opposed to 24-hour scrutiny such as that of Project Green Light’s monitoring
within Real-Time Crime Centers. However, in a body camera deployment, the entire public is
potentially being scanned and uncertainty remains intact.
One of the public objections to the deployment of facial recognition in Detroit stems from
the Foucauldian disciplinary advantage of law enforcement. The act of expression in disclosure
of personal information through self-surveillance is more intimate and voluntary than the
increasingly prevalent methodologies of the invasive presence of closed-circuit television and
49

facial recognition technology in modern reconnaissance of the global population. Involuntary
submission of physical characteristics, as well as personal information identified through data
searches with the intent to distinguish citizens through unwanted behavior, is considered
‘nonreciprocal’ (Marx, 2016). The intent to utilize such data is a fulfillment of social control.
Self-surveillance offers readily available personal information from willing participants in
submission of approved characteristics and traits about themselves. This occurs primarily when
individuals see the act of doing so beneficial in aiding their desires and tending to their needs for
social acceptance. Because the individual controls the flow of information, there is less concern
about conventional privacy invasion (Marx, 2016). Involuntary submission of physical
characteristics through external sources of surveillance, such as video-recorded evidence by
closed-circuit television, is extracted without the direct disclosure of from willing participants.
The consent of release to such documented footage has not been given and provides less
specified and over-generalized subject matter that tends to be induced rather than deduced.
According to Jean-Paul Brodeur (2008), this surveillance illustrates a results-oriented approach
where ‘the ends justify the means.’ Such reasoning relies on context clues, speculation, and
inference. Reasoning, to which these depictions are formulated, occurs in the form of such
methodology because sources that are only capable of being categorized from video observation
lack the certainty involved in first-hand knowledge. Without full and consent ridden disclosure,
involuntary compliance leaves this data as less reliable information.
From a similar standpoint, the weight of inference and format of reasoning creates a ‘one-
way mirror’ that is “…based on asymmetries of knowledge and power” and is referred to in The
Age of Surveillance Capitalism, as User Profile Information (UPI) (Zuboff, 2019, p. 81). Zuboff
50

(2019) points out the foundational formulation of routes to create User Profile Information as
personal data that may be based on generalized presumptions. Increased dimensions of
cooperation amongst User Profile Information, the individuals who contribute to ‘machine-
intelligence’ and the means of behavioral modification connect any and all information about the
user. Zuboff (2019, p. 79) states:
Such information may be provided by the user, provided by a third-party authorized to
release user information, and/or derived from user actions. Certain user information can
be deduced or presumed using other users’ information of the same user and/or user
information of other users. UPI may be associated with various entities.
The unreliability associated with inferences relying on deduction from second-hand sources of
information runs similar risks to those related to the inaccuracies affiliated with algorithmic
biases in identification of minority classes in the usage of facial recognition technology
(Buolamwini & Gebru, 2018). Such risks leave room for a lower degree of validation and are not
reliable as reinforceable evidence that is “…formatted according to legal standards of proof”
(Brodeur, 2008, p. 182). Thus, the ability to reinforce behavioral modification widens the
standard deviation to greater lengths leaving a wider margin of error. Attention that is more
narrowly focused and directed toward entirely relevant and factual User Profile Information
provides grounded knowledge (Brodeur, 2018).
Similar standards should apply to parallelism involved in the duality of Convolutional
Neural Network’s exactitude in recognizing the criminogenic, phenotypic facial characteristics
of offenders and historically supported biological positivist theories within the context of closed-
circuit television surveillance and social control (Hashemi & Hall, 2020). Scientists at Google
admit that User Profile Information is riddled with inconsistencies and inaccurate, toxic rhetoric
51

that shares a similar relationship as facial recognition technology does to algorithmic bias and
inaccuracy (Zuboff, 2019). Problematic occurrences tend to reach resolution when attacked from
all angles. The ability to gain insight through the implementation of problem-solving methods on
issues that coincide with one another, yet are separate in nature, allows for innovation and
perspective. The power structure creates an adversarial relationship instead of public trust. The
power of surveillance causes conformity to the value system benefitting the watcher (Zuboff,
2019). In the case of Project Green Light, the values and agenda of the business community play
a strong role in the deployment of video surveillance.
7.3 The Rational Actor
Another compelling reason for objection to facial recognition technology deployed on body
cameras with real-time monitoring is also found in the power structure that is inherent in a
targeted scan or sweep of individuals. Rational Choice Theory loses relevance when the goal of
surveillance is identification of a missing person or a wanted person from a ‘hot list’ instead of
inducement from an informed choice to avoid committing a crime. In the step by step process of
a sweep, The Perpetual Line-Up outlines:
A face recognition program extracts faces from live video feeds of one or more security
cameras and continuously compares them, in real-time, to the faces of the people on the hot
list. Every person that walks by those security cameras is subjected to this process. When it
finds a match, the system may send an alert to a nearby police officer (Garvie, et al., 2016,
sec. C, para. 5).
There is no choice to opt out of the scan, even if you are innocent of any charge. The power of
consent is out of the hands of the individual and there is no choice to pursue their best interests.
52

A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology

A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology

Recommended

Recommended

More Related Content

Similar to A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology

Similar to A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology (20)

More from Arlene Smith

More from Arlene Smith (20)

Recently uploaded

Recently uploaded (20)

A Theoretical Examination Of The Objections To Body-Worn Cameras With The Addition Of Real-Time Facial Recognition CR 6006 -Dissertation On Criminology