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AI and Ethics (2022) 2:377–387
https://doi.org/10.1007/s43681-021-00077-w
ORIGINAL RESEARCH
The ethics offacial recognition technologies, surveillance,
andaccountability inanage ofartificial intelligence: acomparative
analysis ofUS, EU, andUK regulatory frameworks
DeniseAlmeida1 · KonstantinShmarko2 · ElizabethLomas1
Received: 9 May 2021 / Accepted: 26 June 2021 / Published online: 29 July 2021
© The Author(s) 2021
Abstract
The rapid development of facial recognition technologies (FRT) has led to complex ethical choices in terms of balancing
individual privacy rights versus delivering societal safety. Within this space, increasingly commonplace use of these technolo-
gies by law enforcement agencies has presented a particular lens for probing this complex landscape, its application, and the
acceptable extent of citizen surveillance. This analysis focuses on the regulatory contexts and recent case law in the United
States (USA), United Kingdom (UK), and European Union (EU) in terms of the use and misuse of FRT by law enforcement
agencies. In the case of the USA, it is one of the main global regions in which the technology is being rapidly evolved, and
yet, it has a patchwork of legislation with less emphasis on data protection and privacy. Within the context of the EU and the
UK, there has been a critical focus on the development of accountability requirements particularly when considered in the
context of the EU’s General Data Protection Regulation (GDPR) and the legal focus on Privacy by Design (PbD). However,
globally, there is no standardised human rights framework and regulatory requirements that can be easily applied to FRT
rollout. This article contains a discursive discussion considering the complexity of the ethical and regulatory dimensions at
play in these spaces including considering data protection and human rights frameworks. It concludes that data protection
impact assessments (DPIA) and human rights impact assessments together with greater transparency, regulation, audit and
explanation of FRT use, and application in individual contexts would improve FRT deployments. In addition, it sets out ten
critical questions which it suggests need to be answered for the successful development and deployment of FRT and AI more
broadly. It is suggested that these should be answered by lawmakers, policy makers, AI developers, and adopters.
Keywords Facial recognition technology· Accountability· AI ethics· AI regulation· Data protection· GDPR· Human
rights· Impact assessment· Law enforcement· Privacy· Surveillance
1 Introduction
Law enforcement agencies globally are constantly seeking
new technologies to better ensure successful detection and
prosecution of crimes to keep citizens and society safe. In
addition, there is a public expectation to deliver value for
money and where possible to provide economic efficiencies
and reduced labor costs, which potentially new technolo-
gies can help deliver. Over the last decade, many new tech-
nologies have been harnessed by law enforcement agencies
including, but not limited to surveillance cameras, auto-
mated license plate readers, body cameras, drones, and now
facial recognition technologies (FRT). Law enforcement
agencies have been at the forefront of FRT adoption due
to the benefits that can be seen to be derived and justified
in this space. However, each of these technologies changes
the relationships between law enforcement operatives and
citizens and requires the negotiation of new boundaries
and revised accountability requirements. It is important to
recognise that each technology has encroached on citizens’
privacy and relationship with the state. As such, what is
being deemed as acceptable in terms of reshaping bounda-
ries is under scrutiny and debate. However, the decisions
All authors contributed equally to the writing, research, and ideas
within this article. The initial concept was conceived by Denise
Almeida with Konstantin Shmarko initiating the research work.
* Denise Almeida
denise.almeida.18@ucl.ac.uk
1 Department ofInformation Studies, UCL, London, UK
2 Department ofEconomics, UCL, London, UK
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378 AI and Ethics (2022) 2:377–387
1 3
being made in regard to technology adoption are not cur-
rently uniform. There are distinct differences in technology
adoption and roll out nation to nation and in some national
contexts state to state. These largely depend on the legal
landscape in terms of privacy/data protection legislation and
citizen acceptance and expectations of surveillance. Within
this context, COVID-19 has further pushed the boundaries
of privacy, with nations introducing new measures to track
citizens’ movements and connections to contain the spread
of the virus. However, the shift in enhanced monitoring,
surveillance and privacy disclosures, and accountability
in this regard is being questioned globally, drawing atten-
tion to changes and challenges [1, 2]. This latter question
of accountability and acceptable privacy limits is critical in
terms of balancing rights and responsibilities for FRT.
Accountability provides for the obligation to explain,
justify, and take responsibility for actions. In the context
of the state and law enforcement, the state is obligated to
be responsible for and answer for the choices it makes in
terms of the technologies it rolls out and how these impact
in particular case contexts. Many questions about the use
of FRT and Artificial Intelligence (AI) have yet to be fully
resolved. FRT usage by law enforcement agencies provides
a strong case study for considering aspects of FRT and AI
ethics more generally. It provides for a very understandable
use of personal data with clear impacts on individuals rights.
This article considers the complexity of the ethical and
regulatory dimensions at play in the space of FRT and law
enforcement. The paper starts by providing a brief explana-
tion of FRT, followed by an analysis of the use of FRT by
law enforcement and legal approaches to the regulation of
FRT in the US, EU, and UK. We conclude by recommending
that there must be better checks and balances for individuals
and societal needs. There needs to be accountability through
greater transparency, regulation, audit and explanation of
FRT use and application in individual contexts. One critical
tool for this is the impact assessment, which can be used
to undertake data protection impact assessments (DPIA)
and human rights impact assessments. Ten critical ethical
questions are framed that need to be considered for the ethi-
cal development, procurement, rollout, and use of FRT for
law enforcement purposes. It is worth stating these from
the outset:
1. Who should control the development, purchase, and
testing of FRT systems ensuring the proper manage-
ment and processes to challenge bias?
2. For what purposes and in what contexts is it acceptable
to use FRT to capture individuals’ images?
3. What specific consents, notices and checks and bal-
ances should be in place for fairness and transparency
for these purposes?
4. On what basis should facial data banks be built and
used in relation to which purposes?
5. What specific consents, notices and checks and bal-
ances should be in place for fairness and transparency
for data bank accrual and use and what should not be
allowable in terms of data scraping, etc.?
6. What are the limitations of FRT performance capabili-
ties for different purposes taking into consideration the
design context?
7. What accountability should be in place for different
usages?
8. How can this accountability be explicitly exercised,
explained and audited for a range of stakeholder needs?
9. How are complaint and challenge processes enabled
and afforded to all?
10. Can counter-AI initiatives be conducted to challenge
and test law enforcement and audit systems?
Finally, it should be established that while law enforce-
ment agencies are at the forefront of FRT adoption, others
can learn valuable ethical lessons from the frameworks put
in place to safeguard citizens’ rights and ensure account-
ability through time. Many of these same questions are
applicable to AI development more broadly and should be
considered by law makers to legislate and mandate for robust
AI frameworks.
2 Facial recognition technologies (FRT)
Facial recognition in essence works by capturing an indi-
vidual’s image and then identifying that person through
analysing and mapping of those captured features compar-
ing them to identified likenesses. Facial images, and their
careful analysis, have been a critical toolkit of law enforce-
ment agencies since the nineteenth century. However, in the
twenty-first century, the application of facial recognition,
moving from manual techniques to facial recognition tech-
nologies (FRT), to automatically extract and compare fea-
tures and every nuance of their measurement through the
application of artificial intelligence (AI) and algorithms has
significantly enhanced this basic tool [3]. As such, the face
can be mapped and compared to other data which offers a
more formal match and identification to an individual. This
can sometimes involve the introduction of other biometric
data such as eye recognition data. One-to-one matching pro-
vides for certain identification of an individual in a specific
context. However, using an identified image in connection
with other data banks or data lakes enables one-to-many pos-
sibilities and connotations of usage. Matching that can pro-
cess data at scale presents new possibilities and complexities
when considering machine learning, algorithms, and AI.
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379AI and Ethics (2022) 2:377–387
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The context of the situation of FRT rollout and data gath-
ering is potentially all important in terms of how it aligns
with citizens’ security versus privacy concerns in differing
situations. In 2008, Lenovo launched a new series of laptops
that instead of requiring a password, could recognise the face
of their authorised user [4]. This functionality was seen as
a marketing benefit for Lenovo and clearly users consented
and engaged with the capture and use for their own per-
sonal computing needs and one-to-one matching. However,
there will be distinctions between expectations in one-to-one
matching in a more private controlled space for transparent
individual benefits versus taking and using a verification
process in broader and potentially big data contexts. As the
proposed EU regulation on AI suggests, the use of FRT in
public spaces is ethically (and legally) significantly different
than its use for device unlocking. Citizens will have different
expectations about spaces in which surveillance and FRT
should be in place. For example, when crossing national
border jurisdictions, there has always been an exchange of
data and careful identification of individuals and as such
FRT may be deemed to be more acceptable in this space as
opposed to when moving around public spaces more gen-
erally, functioning in working spaces and finally residing
within private home dwellings. In each of these spaces, the
expectations for active law enforcement and surveillance
clearly differ and there are a number of ethical questions to
be answered for a successful rollout in different contexts and
for different law enforcement purposes. In addition, there
are differences between expectations for localised enforce-
ment agencies such as police services and national intel-
ligence agencies undertaking more covert security opera-
tions. In each citizen space, and dependent upon the form
of law enforcement, there will be different perspectives and
concerns from individuals and groups of stakeholders. As
such, reaching a consensus in technological rollouts will be
a journey. Even in the example of border controls, where ID
data have always been exchanged, studies have shown that
the views of travellers on acceptable technologies differ from
the views of board control guards [5].
In regard to law enforcement, some scholars have
advanced the theory that monitoring of social media by law
enforcement could be perceived as a ‘digital stop and frisk’,
potentially delivering, “everyday racism in social media
policing as an emerging framework for conceptualizing
how various forms of racism affect social media policing
strategies” [6]. This statement evidences concerns about the
bias and credibility of law enforcement agencies. Applying
this same conceptual framework to, sometimes flawed, facial
recognition algorithms without taking accountability for the
consequences of this usage could not only lead to further
discrimination and victimisation of specific communities,
but also to an even greater loss of trust between the general
population and law enforcement agencies. In recent years,
we have seen an exponential increase in research focused on
issues of algorithmic accountability,1 with the overarching
message being that algorithms tend to reflect the biases of
those who build them, and the data used to train them. The
extent to which they can be relied on without human checks
is one of constant concern, particularly as the use of these
technologies as well as identifying individuals is extending
their reach to make further judgements about individuals
including in regard to their behaviours, motivations, emo-
tions, and protected characteristics such as gender or sexual-
ity [7].
In the specific case of FRT, it is important to understand
some aspects at play in the design and roll out that have led
to concerns over biases and unbalanced power structures.
The majority of technology workers in the West are claimed
to be white men, which as such unintentionally influences
the development of technologies such as FRT [8]. Input bias
has been known about for decades, but has not been fully
surfaced in an FRT context. If FRT are trained on white
male faces, then there will be implications when it is used to
process data related to non-white and female faces. As such,
studies have indicated that identification and bias failings do
occur [9]. Even where inputs are adjusted, systems can be
biased by attempting to meet the anticipated needs of pur-
chasers and users which may skew the system particularly as
algorithms are applied and developed through time. In each
of these instances, a high proportion of the stakeholders with
power and influence are likely to be male and white [10].
These biases can lead to severe consequences, particularly
when carried into uses by law enforcement. This brings to
the surface issues of power dynamics and citizen trust of its
law enforcement.
However, it is equally to be noted that AI has the potential
to challenge biases and to be used in innovative ways that
can alter existing power dynamics. A significant example of
this, is the recent use of FRT by human rights activists and
protesters as a way to identify, and hold accountable, law
enforcement officers who might be abusing their power [11].
This ‘turn of the tables’ adds a further layer of complexity
to discussions of accountability and power. However, while
a group of people who typically do not hold power may
in limited circumstances use FRT to hold law enforcement
1 For example, see McGregor, L. (2018) ‘Accountability for Govern-
ance Choices in Artificial Intelligence: Afterword to Eyal Benven-
isti’s Foreword’, European Journal of International Law, 29(4), pp.
1079–1085.; Shah, H. (2018) ‘Algorithmic accountability’, Philo-
sophical Transactions of the Royal Society A: Mathematical, Physi-
cal and Engineering Sciences, 376(2128), p. 20,170,362. https:// doi.
org/ 10. 1098/ rsta. 2017. 0362; Buhmann, A., Paßmann, J. and Fieseler,
C. (2020) ‘Managing Algorithmic Accountability: Balancing Reputa-
tional Concerns, Engagement Strategies, and the Potential of Rational
Discourse’, Journal of Business Ethics, 163(2), pp. 265–280. https://
doi. org/ 10. 1007/ s10551- 019- 04226-4.0.
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380 AI and Ethics (2022) 2:377–387
1 3
accountable, that does not make the technology ethically via-
ble. However, this power shift, if more formally supported,
might provide a part of the solution to FRT deployment and
its impacts. For example, as images are captured and signifi-
cant in legal case contexts, AI has the power to potentially
assist with identifying deep fakes and calling out adaptions
to footage and photographs. As such, it is important to drill
down into the use of FRT and the frameworks which sit
around FRT.
3 The EU andUK legislative landscape
forFRT inalaw enforcement context
There are currently no FRT specific pieces of legislation in
the EU and UK domains, but there are other pieces of leg-
islation that dictate the management and rollout of FRT. In
terms of personal data management, the EU’s GDPR, which
came into force in 2018 covering all the Member States of
the EU, has been seen as setting the bar at the highest level
for the management of personal data. As such, for many tech
companies operating at a global level, it has been seen as the
de facto standard to roll out across all global operations. It
is to be noted that as the GDPR came into force, while the
UK was part of the EU, it was enshrined into UK domestic
legislation and still continues to apply within a UK context.
The UK’s ongoing adequacy in terms of alignment to EU
GDPR will continue to be judged by the EU.
The GDPR has required systems to be implemented
where ‘privacy by design’ (PbD) and ‘privacy by default’ are
inbuilt for any personal data processing. Processing covers
any activity with personal data including creating, receiving,
sharing, and even destroying/deleting personal data. There
must be a clear lawful basis for personal data processing,
and in addition, the data must be processed fairly and trans-
parently. Within this context, it is important to understand
that this does not prevent personal data collection, but does
require carefully documented processes and active personal
data management through time. In addition, it must be noted
that what is considered fair and lawful is potentially open
to interpretation and legal debate and contest. In certain
instances, consent for processing is required. In addition,
there are specific data subject rights such as the right to
know what is held on/about you, subject to certain exemp-
tions and to ask for data to be rectified or deleted (the right
to be forgotten) in certain circumstances.
Where special category personal data are processed,
stricter controls are required. Of note in this regard is bio-
metric data which is categorised as physical or behavioural
characteristics that uniquely identify an individual, includ-
ing but not limited to DNA, fingerprints, faces, and voice
patterns as examples. As such FRT are caught under this
definition and within Article 9 of the GDPR, it is clarified
that biometric data should not be used to identify a person
unless an individual has provided explicit consent or alter-
natively other exemptions exist. One such example of an
exempted area across the EU and UK is law enforcement. In
the GDPR, personal data management for law enforcement
purposes was derogated in Article 23, for determination at
Member State level. There is therefore some divergence in
terms of how the checks and balances exist between personal
data rights and law enforcement rights. Within most EU
Member States there is an expectation that for the purposes
of pursuing law enforcement to identify and track offenders
certain exemptions would exist, and consent would not be
required. Within this space, the new technological landscape
is further continuing to evolve and as such its rollout and use
by law enforcement agencies is not consistent across the EU.
Regardless of certain consent exemptions, other GDPR
requirements do still apply, such as PbD, which does pro-
vide a framework of accountability for law enforcement.
For FRT purposes, a DPIA must be undertaken as a way of
demonstrating and achieving PbD. The DPIA is a process of
identifying risks that arise from data processing and is man-
datory for high-risk applications, such as facial recognition
in law enforcement use.2 This requires that all aspects of a
process are reviewed and considered to ensure that there are
justifications for the process; this ensures it is ‘fair and law-
ful’, it is appropriately targeted, implemented and managed
through time. This procedure is not only useful for the FRT
operators, as it forces them to scrutinise their algorithms,
focus and security, but can also benefit the general public,
as, if published, a DPIA can explain data processing in terms
that are accessible to any individual, not just an IT specialist.
Mandatory publication of the DPIA does not exist, but there
is a requirement to be transparent about DP processing and
to have in place privacy notices for this reason.
Another important GDPR requirement is the need to have
a Data Protection Officer (DPO) within any public author-
ity or private entities where the core activities require large
scale, regular, and systematic monitoring of individuals or
large-scale processing of special category data or data relat-
ing to criminal convictions or offences. As such, this does
mean that law enforcement agencies and businesses pro-
viding processing services will be required to have a DPO.
The DPO is required to advise an organisation on its data
protection compliance. In addition, were an organisation to
fail to fully comply with the GDPR, the DPO would act as
a whistle-blower reporting to the relevant national ombuds-
man on data protection.
Each EU Member State and the UK has a regulatory
requirement which establishes an oversight, complaint,
and investigatory regime to be in place, a data protection
2 For the formal definition of the DPIA, see GDPR Article 35.
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381AI and Ethics (2022) 2:377–387
1 3
ombudsman/regulator. There are currently 27 data protec-
tion authorities in the EU, one for each country, plus the
European Data Protection Supervisor, which oversees EU
institutions and bodies. The UK also has a data protection
supervisor. The exact responsibilities of the organisations
differ, but all of them are tasked with monitoring and ensur-
ing data protection and privacy compliance regionally on
behalf of their citizens. In accordance with this mandate, it
is not uncommon to see these authorities actively interven-
ing in relevant disputes, sometimes even before any citizen
complaints are filed. The benefit to accountability of these
organisations is obvious—the data protection regulators have
bigger budgets and better legal teams than most individuals,
meaning that they are more effective in holding FRT opera-
tors accountable. The authorities with enforcement powers
can bypass litigation entirely, issuing fines and orders faster
than a court would be able to. These factors ensure that the
FRT providers and operators should never get complacent.
Separately, citizens may bring forward lawsuits for data
protection failings, but the ability to complain to a regulator
provides the citizen with a cheaper alternative and one which
should actively investigate and oversee any organisational
data protection failings. The regulators are publicly funded
and the resources for each across the EU and UK vary sig-
nificantly. The extent of investigations and the timeliness of
dealing with complaints have both been areas of criticism.
For example, in 2020, a group of cross-party Members of the
UK Parliament wrote complaining about the performance
of the UK’s Information Commissioner.3 Such complaints
are not limited to the UK. In July 2020, the Irish High Court
gave permission for a judicial review of the Data Protection
Commissioner in respect of the delay dealing with com-
plaints. It is to be noted that Ireland is the home to many
tech companies’ European headquarters, and thus, these
delays can impact more broadly upon EU citizens. However,
equally, there are many examples of active engagement and
investigation.
In terms of moving to cover new developments, the
GDPR is not a prescriptive piece of legislation and, as such,
its ‘vagueness by default’ is intended to ensure that the regu-
lation maintains its relevance, allowing for application to
new technologies, including FRT. Even more importantly,
the GDPR holds some sway outside of the EU as well, since
any business dealing with the bloc has to adhere to the rules
when managing European’s data, even if those same rules
do not apply in their own domestic jurisdiction. This is gen-
erally known as ‘The Brussels Effect’ [12, 13]. In practice,
where FRT are rolled out in the EU, this means that it is
much easier to hold FRT operators accountable, as there is
no need to navigate a complex web of regional laws, and the
operators themselves are more consistent in their behaviour,
unable to use the splintering of regulation to their advan-
tage.In addition, companies will often roll out the same
systems globally, meaning that those outside the EU may
benefit from some read over of standards. However, this is
not to say that the systems will then be operated and man-
aged in the same ways globally.
In terms of AI more specifically, this has become a focus
for the EU and UK regulators and governments. The UK
Information Commissioner’s Office (ICO) has recently pub-
lished [14] guidance on AI auditing, supported by impact
assessments. Although this guidance marks an important
start towards specific guidance tailored towards the compli-
ance of AI systems, we are still lacking case studies and
dedicated frameworks to address this problem in a standard-
ised way [15]. Recently, the EU has engaged with the need
to actively manage the ethics and legislation that sit around
AI innovation. A 2019 press release by the European Data
Protection Supervisor Wiewiórowsk, called out the account-
ability and transparency concerns of facial recognition, par-
ticularly around the input data for facial recognition systems
stating, “the deployment of this technology so far has been
marked by obscurity. We basically do not know how data are
used by those who collect it, who has access and to whom
it is sent, how long do they keep it, how a profile is formed
and who is responsible at the end for the automated decision-
making.” [16]. As such, the European Commission began
publishing a roadmap for dealing with AI. In April 2021,
the European Commission released documentation on its
approach to AI, which includes an aspiration to harmonise
all legislation and bring in a specific Artificial Intelligence
Act. FRT more specifically have yet to be dealt with in detail
but, within the proposals for harmonisation, law enforcement
systems are categorised as high risk. It is stated that AI sys-
tems used by law enforcement must ensure, “accuracy, reli-
ability and transparency… to avoid adverse impacts, retain
public trust and ensure accountability and effective redress”
[17]. The documentation draws out areas of greater concern
focusing on vulnerable people and those contexts where AI
systems failures will have greater consequences. Examples
include managing asylum seekers and ensuring individuals
have a right to a fair trial. The importance of data quality and
documentation is highlighted [17]. The Commission states
that there must be oversight regarding:
“the quality of data sets used, technical documentation
and record-keeping, transparency and the provision of
information to users, human oversight, and robustness,
accuracy and cybersecurity. Those requirements are
necessary to effectively mitigate the risks for health,
safety and fundamental rights…”
3 See https:// www. openr ights group. org/ app/ uploa ds/ 2020/ 08/ Letter-
for- MPs- Final- sigs-1. pdf.
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382 AI and Ethics (2022) 2:377–387
1 3
The place of the human in the system review is an impor-
tant part of the process. In addition, the need for transpar-
ency is highlighted. However, what is not yet in place is a
prescribed system for transparency and accountability. As
the publications are currently at a high level, a need to drill
down and consider case examples is necessary for delivery.
There are some limitations to these publications and the
recent publications by the EU have been criticized for not
bringing in a moratorium on biometric technologies such
as FRT [18]
In an EU context, in addition to the GDPR which dic-
tates rules around managing personal data, privacy is further
legislated for through the European Convention on Human
Rights. As with the GDPR, this is enshrined in UK law as
well as across all 27 EU Member States. The Human Rights
legislation is potentially more holistic in terms of offering
frameworks for consideration of law enforcement versus
individual rights in the rollout considerations for FRT. It
enshrines principles of equality and inclusion as well as
privacy and rights to fair legal processes. The checks and
balances of different and sometimes competing human rights
are well established and tested through the courts. Under
the terms of the law, individuals can bring legal cases, and,
in the EU Member States (although not the UK), cases can
progress to the European Court of Human Rights. How-
ever, there is not the same active regulatory framework
sitting around the legislation which provides for quicker
and cheaper routes to justice, and which can actively take
action without the requirement for an individual to bring a
case. Justice through the European Courts most normally
is expensive, uncertain, and takes years. In addition, the
requirements for accountability and design documentation
for human rights compliance are not explicitly enshrined in
the law. In terms of transparency, aspects of accountabil-
ity for policy more generally fall under freedom of infor-
mation legislation which is enacted at Member State level
and differs very widely nation to nation in terms of public
accountability requirements for administration more gener-
ally. There are also certain law enforcement and national
security exemptions from freedom of information require-
ments. Finally, it is important to note that it does not bind
on private entities who do not have the same accountability
requirements.
In terms of actual FRT legal accountabilities, cases have
been brought under both the GDPR and the Human Rights
Act in respect of FRT. One such instance is the 2019 UK
case of Bridges v. South Wales Police. Bridges, a civil rights
campaigner, argued that the active FRT deployed by the
police at public gatherings infringed on the right to respect
for human life under the Human Rights Act 1998 and his
privacy rights under the Data Protection Act 2018 (DPA
2018), the UK implementation of the GDPR. Relevant to
this discussion, Bridges also claimed that, since the police
failed to account for this infringement, its DPIA was not
performed correctly [19]. After a lengthy litigation process,
the court ruled in favour of Bridges, agreeing with the points
above and additionally finding that the police had too broad
a discretion regarding the use of FRT.
This example highlights the value of the GDPR (or simi-
lar legislative frameworks) and, in particular, the importance
of the DPIA. Here, the impact assessment not only provided
the basis for a large portion of the claimant’s argument, but
it was also released to the public, making it easy for anyone
with internet access to learn the details of the FRT data pro-
cessing employed by the South Wales Police.4 In addition,
the case shows that the DPIA is not a checkbox exercise but,
instead, requires that the FRT operator possesses substantial
knowledge about the inner workings of the algorithm and its
wider repercussions.
The lawsuit also draws attention to the holistic under-
standing of privacy under the GDPR. In a country with
less-developed data protection laws, it may be sufficient for
an FRT operator to encrypt and anonymise faceprints, and,
regardless of how they are collected, this will constitute suf-
ficient protection; the GDPR goes to great lengths to ensure
that this is never the case. Of particular importance are the
concepts of PbD and privacy by default, as mentioned above
and defined in Article 25 of the regulation. In this example,
the South Wales Police ensured privacy by design, meaning
that its facial recognition algorithms were built around data
protection. That, however, was not enough, since the FRT
were then deployed indiscriminately, which violated privacy
by default—the amount of personal data collected was dis-
proportionate with respect to the intended goal of identifying
individuals on watchlists. As such, the police use of FRT
for these processes had to be stopped. This “one strike and
you’re out” approach to personal data collection goes a long
way towards ensuring accountability in facial recognition,
since it makes it much harder for the FRT operator to get
away with negligent data processing for which there can be
significant consequences. However, while the Human Rights
legislation was deployed as part of the case, the lack of a
published Human Rights Impact Assessment does diminish
accountability in this regard. It is to be noted that a similar
requirement to the provision of a DPIA, in regards to Human
Rights Impact Assessments and human rights’ by design and
default, could better improve citizen rights more generally.
In spite of the data protection legislation, it is important
to highlight that authorities and corporate entities may fall
short in their duties, which is why a proactive regulator is a
significant attribute in the GDPR regime. In August 2018,
upon the request of the London Mayor, the UK ICO started
4 This particular assessment is available here: https:// afr. south- wales.
police. uk/ wp- conte nt/ uploa ds/ 2019/ 10/ DPIA- V5.4- Live. pdf.
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383AI and Ethics (2022) 2:377–387
1 3
to investigate whether a private property company (Kings
Cross Estate Services), which managed the area around
Kings Cross, a critical London transport hub was using FRT
in its CCTV. It emerged that for a number of years, this com-
pany had been using FRT for ‘public safety’ reasons, but had
not properly disclosed or made people aware that the scheme
was in operation. In addition, as part of this investigation it
transpired that not only had it been using FRT to capture
the images of all those people passing through the transport
hub, but it had been working with the Metropolitan Police in
London to check and match for certain people entering the
area. A data sharing agreement was in place with the inten-
tion of providing for the potential identification of wanted
individuals, known offenders, and missing persons. Over a
2-year period from 2016 to 2018, the Police passed images
of seven people to the property entity. These people had
been either arrested and charged, reprimanded, cautioned, or
given a formal warning for offences. However, it was clear
that the Police had failed to disclose that the scheme existed.
[20]. That said, more generally the ICO has found that it
is acceptable for the Police to use FRT and that there is a
great deal of public support for its use, but that nevertheless
it must be done so in a carefully targeted way taking into
account individual’s Article 8 human rights to privacy [21].
Reflecting on the position of the Regulators and their
investigatory powers, one of the most active national data
protection bodies in the EU is the Swedish Authority for Pri-
vacy Protection (IMY), formerly known as the Swedish Data
Protection Authority. In recent years, it has been involved
in two FRT cases of note: a school using FRT to monitor
class attendance [22], and the police using facial recognition
software [23].
The first case, while not related to law enforcement,
showcases how a data protection authority’s independence
and legal expertise can ensure accountability where an indi-
vidual or a civil organisation would not have been able to do
so for various reasons. In this instance, the IMY “became
aware through information in the media” that the school was
trialing FRT on its students and decided to intervene. In the
ensuing process, the authority found that the school’s use of
facial recognition did not satisfy proportionality and neces-
sity, which also led to the DPIA being conducted incorrectly.
Most importantly, the IMY ruled that the consent that was
given by the children’s parents to the school was invalid, as
the students were in a position of dependence (school attend-
ance is compulsory). The school’s board was subsequently
fined approximately €20,000.
There are several important aspects to this example. First,
note that the IMY intervened in the case on its own voli-
tion, without receiving any complaints or being asked to take
action. This autonomy is important, as individuals may not
always be able/willing to alert the authorities when their data
are being collected and/or processed unlawfully. The reason
why none of the parents came forward could be that they did
not possess enough legal expertise to notice the problems
in the FRT deployment or did not feel able to challenge the
school given their own and their children’s relationship with
it. The IMY had independence, sufficient knowledge, and a
position of power to hold the school accountable. Finally,
note the “one strike and you’re out” approach mentioned
above. While the school made reasonable efforts to comply
with the legal requirements—the faceprints were recorded
on a hard drive connected to an offline computer locked
away in a cupboard, and a DPIA was conducted—it failed
to ensure complete compliance, and so was prosecuted.
The second example concerns the use of FRT by the
Swedish police. The IMY found that the police failed to con-
duct a DPIA and were negligent enough to let unauthorised
employees access the software, after which it imposed a fine
of €250,000. Here, the law enforcement was ignorant to any
negative consequences of FRT use and did not take appro-
priate active PbD steps; as a result, it was held accountable
for its failings.
Exact data on how widespread FRT are across the EU
is difficult to find, but the technologies are not ubiquitous
yet. In 2019, 12 national police forces had already deployed
facial recognition with 7 more planning or testing deploy-
ment at that date. Deployment has been deemed to be much
slower than in USA [24]. This may in part be due to the fact
that it is also surrounded by much more suitable, uniform
legislation, greater transparency, and active data protection
authorities—all of these components will play a large role in
making Europe a better model for facial recognition account-
ability. However, in the context of FRT, it is important to
note that a lot of the development has happened outside the
boundaries of the EU and UK. As such, while the EU may
have set a high bar in terms of requiring PbD, much FRT
application happens within a USA context.
4 The USA ethical andlegislative landscape
forFRT inalaw enforcement context
Having considered the European regulatory framework,
strongly positioned to ensure some forms of ethical con-
siderations before the deployment of FRT, we now turn to
a much more fragmented legislative territory: the United
States of America (USA). Within USA, FRT are heavily
used by law enforcement, affecting over 117million adults
[25], which is over a third of the country’s total popula-
tion. FRT rollouts are widespread, yet an average citizen
has very limited means of holding its operators account-
able should it be misused. The USA was an early adopter of
freedom of information laws, passing the federal Publication
Information Act in 1966, with individual state laws being
passed after this date. This set of legislation provides for
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
384 AI and Ethics (2022) 2:377–387
1 3
state authorities to answer for their policies and actions on
receipt of a freedom of information request. This does not
impact on private companies who are not held accountable
in the same way. In addition, there are certain exemptions
under the legislation for law enforcement and national secu-
rity purposes. There are some sector-specific privacy laws,
covering, for instance children online, but no overarching
data protection law akin to the GDPR. These federal laws
are then enforced by the Federal Trade Commission, which
has an extremely broad mandate of protecting consumers
against deceptive practices; it is not comparable, however,
to the data protection authorities in European countries [26].
Such a massive rollout of FRT without a regulator/ombuds-
man to investigate is a cause for concern as it then relies on
individual legal action to call out wrongdoings. In addition,
there are very considerable state-by-state differences, and
a notable lack of requirements for transparency or calls for
that transparency.
This reliance on individual action originates from USA
lacking any federal (or state) data protection authority. This
means that there is no body which would actively represent
and protect citizens’ interests, while possessing the legal
and regulatory powers of the state. Moreover, as we have
seen, data protection authorities can intervene on behalf of
the citizen and enforce decisions without initiating court
proceedings; in the USA, this is not an option—any conflict
regarding FRT and related personal data has to be heard in
court, necessitating lengthy and costly court battles (which
is why citizen representation is so important). As a result,
individuals often have to seek legal support from non-profit
organisations; those who fail to secure it may not be able to
hold FRT operators or providers accountable at all.
The second issue is centered around state-by-state dif-
ferences; it occurs thanks to an absence of a general federal
privacy legislation, with state law often providing only very
basic rights for holding FRT operators accountable. The
extent of privacy laws in most states is limited to notifying
an individual if their data have been stolen in a security
breach [27]—hardly a consolation for someone who has
been affected by unintentionally biased or malicious use
of FRT. Relevant to our discussion, at the time of writing,
there is only one state (Illinois) that has legislation allowing
private individuals to sue and recover damages for improper
usage and/or access to their biometric data, including face-
prints [26]. However, even if you are lucky to live in Illinois,
holding a malicious FRT provider or operator, private or
public, accountable is likely to be difficult. Accountability
relies on transparency—if, for instance, an individual would
like to sue an FRT provider on the basis of a privacy viola-
tion, they will need some knowledge of how their data are
processed. This is where the USA falls short; not only are the
law enforcement and federal agencies notoriously secretive,
but they often do not understand how their own FRT works
in the first place. Without PbD and the requirements for a
DPIA, there is less transparency on FRT processes, and it is
harder to know exactly how processing is occurring and to
hold operators to account. In addition, operators may often
not have duly considered and weighted the implications of
the FRT usage.
In a USA context, the law on privacy and use of FRT for
localised law enforcement operates very much at a state-
by-state level. Within this context, California is often held
to be the state with the strongest privacy laws; in 2020, it
strengthened its existing privacy laws with the California
Privacy Rights Act (CCPA), which established the Califor-
nia Privacy Protection Agency and extended residents’ rights
in terms of how business could collect and use their data.
However, notably, it did not touch on any privacy powers in
respect of law enforcement, and, in tandem with the CCPA,
the state started to try to introduce a Facial Recognition Bill
to enhance the use of FRT for law enforcement purposes. It
is to be noted that some cities in California (e.g., Berkeley
and San Francisco) have banned FRT usage. Interestingly,
the Bill received lobbying support from Microsoft, but was
fiercely campaigned against by Civil Rights groups, and as
such, it was not passed in June 2020. This period marked
a growing sense of unease with the ethics around FRT. In
the same month, IBM stated that it would cease all export
sales of FRT. In its statement, it described FRT as akin to
other innovations such as nuclear arms on which the USA
has had to seize a lead for the protection of its citizens [28].
In addition, it highlighted the flaws in the technology, for
example its failure to deal with Black and Asian faces with
sufficient accuracy. At the same time, another big tech entity,
Amazon stated that it would cease to sell FRT to the Police
for 1 year to give Congress time to put in place new regula-
tions to govern its ethical usage. Microsoft followed suit stat-
ing, “we will not sell facial recognition technology to police
departments in the United States until we have a national
law in place, grounded in human rights, that will govern
this technology" [29]. Each of these entities clearly became
concerned about the potential misuse of the technology by
law enforcement agencies which IBM said had caused con-
cerns since the revelations by Edward Snowden in 2014 [29].
Clearly, there were valid ethical concerns about the devel-
opment of FRT. However, when beneficial influences leave
the marketplace, this may open up the field to less ethical
developers. Each of these entities has a process for review-
ing the ethics of technology roll outs, for example, IBM
has an Ethics AI Board led by a Chief Privacy Officer. It is
difficult to know how ethical or effective these private enti-
ties are where there is such limited transparency, although
clearly these large global corporations worry about their
images. This was evidenced in the case of Google which
received international press attention and criticism when it
fired Timnit Gebru, co-lead of its Ethical AI Research Team,
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385AI and Ethics (2022) 2:377–387
1 3
for refusing to edit out certain statements from a research
article on AI [30], and as a result of the controversy, it has
since had to change its publication approach.
The concerns of private enterprise and the relationship
with law enforcement and national security have been rec-
ognised at a national level. For example in the context of the
Federal Bureau of Investigation (FBI), there have been hear-
ings in Washington on the acceptable use of FRT.5 At this
hearing, it was stated that the “FBI has limited information
on the accuracy of its face recognition technology capabili-
ties.” These hearings called for greater accountability and
transparency in the use of the technologies, although defini-
tive outcomes from the hearings are still awaited.
A recent illustration of the current opacity of the USA
system is demonstrated in the case of Willie Allen Lynch,
a black man convicted in 2016 by a Florida court of sell-
ing cocaine; the Police Department made the decision to
arrest him based on a facial recognition match, among other
factors. In an attempt to appeal the decision, Lynch argued
that the facial recognition system made an erroneous match
(a reasonable statement, given FRT’s known inaccuracy
with black faceprints [9]), proving this, however, required
the police to turn over the photo in question and the list of
possible faceprint matches offered by the system, which it
refused to do. Strikingly, the detectives involved in the case
admitted that, while the FRT rated Lynch’s faceprint as the
closest match, they did not actually know how the rating sys-
tem worked or even which scale the rating was assigned on.
Ultimately, the court ruled in favour of the Police Depart-
ment, and Lynch was never given access to the photo and
potential matches [31].
On a federal level, the issues of a lack of transparency
and accountability persist; an attempt by the American Civil
Liberties Union (ACLU) to gather information about the use
of FRT by the Department of Justice, the FBI and the Drug
Enforcement Administration failed, since none of the agen-
cies responded to a Freedom of Information Act request.
Undeterred, the ACLU pursued legal action, with results yet
to be seen—there has been no information about the case
since October 2019, when the initial complaint was filed
[32]. In addition, the ACLU has called out the Government’s
and private enterprises’ surveillance operations at airports
and customs boundaries across the USA [33].
In regard to private companies, as previously noted, these
are not caught by freedom of information laws and can often
afford legal firepower beyond the reach of even the wealthi-
est individuals. Clearview AI, one of the leading providers
of FRT to the USA law enforcement agencies, supplies the
technologies to more than 600 police departments across
USA [34]; the ACLU filed a lawsuit against the company in
the state of Illinois, arguing that it collected faceprints with-
out consent, as required by the state’s Biometric Information
Privacy Act [35]. Filed in May 2020, the case remains active
at the time of writing, accumulating a seemingly endless
stream of motions, memoranda, and briefs from both sides.
The amount and complexity of the legal paperwork on a case
that has not even been heard yet is illustrative of how fiercely
opposed the company is to any efforts to hold it account-
able, and it is problematic for ordinary citizens to follow
the lawsuit through on their own; although crowdsourcing
and group action has become a reality for legal cases, as
seen in the actions brought by the Austrian Max Schrems
in the EU. In addition, there has been a class action brought
against the Department Store Macy’s in Illinois for its use of
FRT [36], so such legal action may become more common.
Nevertheless, a mature democratic nation should have other
solutions in place.
This absence of the threat of litigation removes the pro-
verbial sword hanging above the FRT providers’ heads,
allowing them to have a free-for-all feast on user informa-
tion. For instance, Clearview AI openly discloses informa-
tion about scraping Facebook user profiles for images to
build up its reference database [34], even though this action
is explicitly prohibited by the website’s terms of service.
IBM, in a similar fashion, collected individuals’ Flickr pho-
tos without consent; the affected users were not given a fea-
sible way of deleting their information from the database
[37]. A complete absence of data protection and privacy
rights is hugely problematic.
5 Conclusion andrecommendations
FRT is no longer a topic of science fiction or a concern
for the future. It is here now, impacting people’s lives on a
daily basis, from wrongful arrests to privacy invasions and
human rights infringements. The widespread adoption of
this technology without appropriate considerations could
have catastrophic outcomes, and ultimately may jeopardise
its development if some jurisdictions decide to ban the use of
the technology for an indefinite amount of time [38]. How-
ever, critical in the success of FRT is the transparency and
accountability in each stage of its development and usage
and the ability to audit and challenge as required. The idea
of power is particularly linked to the intended, and actual,
outcomes of FRT, which should not be dissociated from dis-
cussions around accountability.
This discussions in this article makes the case that at all
stages of the FRT process in all aspects of design and use
including specific contexts, there is a requirement to docu-
ment and account for the usage ensuring mechanisms for
5 See for example the 2019 report at https:// overs ight. house. gov/ legis
lation/ heari ngs/ facial- recog nition- techn ology- part- ii- ensur ing- trans
paren cy- in- gover nment- use.
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386 AI and Ethics (2022) 2:377–387
1 3
transparency and challenge. The GDPR provides a good
regulatory starting point to address some of its concerns.
However, the ethical considerations of this technology go
far beyond issues of privacy and transparency alone. It
requires broader considerations of equality, diversity, and
inclusion as well as human rights issues more generally.
As such other forms of assessments, such as Human Rights
Impact Assessments, in addition to DPIA, should be part
of the development and rollout of FRT—a DPIA alone is
insufficient. These Assessments should be automatically
required to be put into the public domain. In addition, the
requirements must equally be enacted upon both public
and private enterprises with transparency and accountabil-
ity requirements. In conjunction with these steps, global
regulators are needed with powers to actively investigate
each aspect of the development and deployment processes
of FRT in case contexts, and with powers to step in, stop
and fine inappropriate FRT development and deployment.
In addition, there should be more normal audit processes
required for FRT deployment just as there are for financial
oversights. The societal impacts for FRT misconduct are
not to be underestimated.
We conclude this paper with the recommendation of
ten critical ethical questions that need to be considered,
researched, and answered in granular detail for law enforce-
ment purposes and which in addition have read over to other
AI development. It is suggested that these need to be dealt
with and regulated for. The questions are:
1. Who should control the development, purchase, and
testing of FRT systems ensuring the proper manage-
ment and processes to challenge bias?
2. For what purposes and in what contexts is it acceptable
to use FRT to capture individuals’ images?
3. What specific consents, notices and checks and bal-
ances should be in place for fairness and transparency
for these purposes?
4. On what basis should facial data banks be built and
used in relation to which purposes?
5. What specific consents, notices and checks and bal-
ances should be in place for fairness and transparency
for data bank accrual and use and what should not be
allowable in terms of data scraping, etc.?
6. What are the limitations of FRT performance capabili-
ties for different purposes taking into consideration the
design context?
7. What accountability should be in place for different
usages?
8. How can this accountability be explicitly exercised,
explained and audited for, for a range of stakeholder
needs?
9. How are complaint and challenge processes enabled
and afforded to all?
10. Can counter-AI initiatives be conducted to challenge
and test law enforcement and audit systems?
We are at a tipping point in the relationships and power
structures in place between citizens and law enforcers. We
cannot wait to step in and act, and in fact, there are many
potential solutions to better ensure ethical FRT deployment.
However, this is currently an ethical emergency requiring
urgent global attention.
Funding This work received partial funding from the UCL AI Centre.
Declarations
Conflict of interest The authors confirm there are no conflicts of inter-
est.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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