Ética y tecnologías emergentes: reconocimiento facial
| Autor | Archil Chochia, Teele Nässi |
| Cargo | Departamento de Derecho Universidad Técnica de Tallin Ehitajate tee 5, Tallin 19086, Estonia/Universidad Tecnológica de Tallinn (TalTech) |
| Páginas | 1-12 |
https://idp.uoc.edu
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
1
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
Dossier “Europe facing the digital challenge: obstacles and solutions”
Ethics and emerging technologies
– facial recognition
Archil Chochia
Tallinn University of Technology (TalTech)
Teele Nässi
Tallinn University of Technology (TalTech)
Date of submission: May 2021
Accepted in: October 2021
Published in: December 2021
Abstract
Emerging technologies and digitalization have an increasing impact on our everyday lives. New technol-
ogy solutions offer a variety of opportunities to our society, yet the ethical implications of this process
have long been discussed by scholars in order to fully understand what the potential ethical risks are.
One of such technologies is facial recognition. This article intends to contribute to the above indicated
scholarly discussion by analyzing recent developments in the field, focusing on facial recognition.
Keywords
artificial intelligence; AI; digitalization; ethics; ethics of technology; facial recognition
Ética y tecnologías emergentes: reconocimiento facial
Resumen
Las tecnologías emergentes y la digitalización tienen un impacto cada vez mayor en nuestra vida coti-
diana. Las nuevas soluciones tecnológicas ofrecen una variedad de oportunidades a nuestra sociedad;
sin embargo, las implicaciones éticas de este proceso han sido discutidas durante mucho tiempo por los
académicos para comprender completamente cuáles son los potenciales riesgos éticos. Una de estas
tecnologías es el reconocimiento facial. Este artículo trata de contribuir a dicha discusión académica
analizando los avances recientes en este campo, centrándose en el reconocimiento facial.
Palabras clave
inteligencia artificial; IA; digitalización; ética; ética de la tecnología; reconocimiento facial
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
2
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
Introduction
Ever since technologies have become part of our lives, the
discussion on the positive and negative effects of these
technologies and the technologization process has been a
topic for debate on different levels. This research intends
to contribute to such discussion on an academic level, fo-
cusing on facial recognition, and is partially based on earli-
er findings of the authors (please see Joamets & Chochia,
2021). When explaining the complexity of determining an
attitude toward technologies, Winston and Edelbach (2011)
talk about two distinctive viewpoints — techno-pessimism
and techno-optimism. While techno-pessimists focus on
the negative aspects of technology and remain sceptical
of technological solutions, techno-optimists place empha-
sis on the benefits that technologies offer to society and
remain confident that technological solutions will solve
the potential problems of technology.
From the philosophical standpoint, this can be linked to two
historical phases of technological analyses: the first being
mid-twentieth-century classical hermeneutic critiques that
focus on the negative effects on humans caused by mod-
ern technologies; and the second being an empirical ap-
proach looking at technology rather as socially determined
elements through local use. A notable example of the first
historical phase is philosopher Jacque Ellul, who believed
that technology had developed at such a rapid pace that
it could not be controlled by humans and therefore saw
it as rather destructive (Ellul, 1964). On the other hand,
the second phase approach shifts from general technology
to a more nuanced approach, looking at local narratives,
examining each technology individually and empirically,
viewing it within the values and culture of those societies
that use the technology in question (see, e.g., Brey, 2010;
Verbeek, 2011). Similarly, to the rest of the branches of phi-
losophy, ethics derives from supposedly simple questions;
nevertheless, as John Deigh (2010, p.1) puts it, these ques-
tions often “seem simple, yet are ultimately perplexing”.
Digitalization has been posing such new questions and,
therefore, the ethical implications of digitalization pro-
cess have long been discussed by scholars. Philosopher
Deborah Johnson (2004, p.69) speaks of the information
society as a society in which digital technologies shape
“human activity and social institutions”. Digitalization and
emerging technologies affect our lives and are increasing-
ly present in a growing number of fields (see, e.g., Kerik-
mäe et al., 2020). Legal scholars are trying to find the best
way to regulate the emerging technologies; also, substan-
tial research is devoted to understanding the implications
of emerging technologies on legal systems (Brownsword
& Goodwin, 2012, 2018). However, while both of the above
approaches can be found in current scholarly discussions
on the ethical aspects of technology, the emphasis is on
the “continuity of people and technology with the rest of
nature” (Parsons, pp.6-9), while not enough attention is
being paid to the widespread use of modern technologies,
such as social media, Twitter, augmented reality, smart-
phones, internet and others, often resulting in moral and
ethical issues (Deloitte, n.d.; Jobin et al., 2019).
The lack of literacy in digital ethics within our societies is
alarming, as Beever et al. (2019, pp.9-25) argue in their
book Understanding Digital Ethics. They draw attention
to the issues of technology control, moral agency, and
responsibility, drawing parallels with the famous ethical
thought experiment in moral philosophy, the “trolley prob-
lem”, for example when it comes to autonomous vehicles.
The authors believe that digital ethics is a combination of
two literacies: one being a digital literacy-understanding
of modern technologies and information, and a second
ethical literacy-understanding which is being motivated
to act on the emerging ethical issues. And, consequently,
in order to achieve a necessary understanding of digital
ethics, it is absolutely crucial to possess a sufficient level
of both digital literacy and ethical literacy.
Artificial intelligence (AI) is a field that is developing at a
rapid pace and such rapid development has taken the le-
gal and ethical discussion to another level. AI has already
replaced humans in many actions performed and this
process of “preplacement” is going fast forward (see, e.g.,
Joamets & Chochia, 2020; Troitiño et al., 2020, pp.303-
317). One of the particular areas in this development is
Facial Recognition Technology (FRT) and the increasing
use of this technology in different areas has provoked dis-
cussion due to its close link to human rights, specifically
the right to privacy, one of the fundamental human rights.
As Naker and Greenbaum (2017, p. 101) explain, “privacy
is a precondition for democracy development and free-
dom. Without privacy, there is no freedom of expression,
freedom of religion, or freedom of movement.” This re-
search tries to analyze FRT and explain what the human
rights-related issue with its usage are.
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
3
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
1. History of facial recognition
technology (FRT)
As Welinder (2012, p. 167) explains, facial parameters
are extremely useful for identification due to distinction,
availability, difficulty to alter, etc. The first scientific facial
recognition indications date back to 1884 when an anato-
mist Welcker compared what was thought to be Raphael’s
skull with a self-portrait and compared the supposed skull
of Kant with his death mask and found that the respective
correlations were too good for chance. He used two-dimen-
sional techniques; he provided accurate orthogonal per-
spective drawings as an outline of the skull and the death
mask, and then attempted to superimpose the outlines,
while making allowance for the outer tissues (Wilkinson,
2004). After that, there were several anthropologists and
anatomists, who tried to perform the facial recognition of
early hominids such as Neanderthal and Pithecanthropus,
and others of the Stone Age (Verze, 2009, p. 8).
A computer technique for forensic purposes was first
developed in the 1980s by Moss and his colleagues at
London’s University College in the UK. It was based on
a system used for cranial reconstructive surgery. The
system was developed for 3D surface data acquisition
of the human face, involved limited manual intervention,
and was subject to minimal human error (Arridge et al.,
1985, p. 13; Moss, 1987, p. 9). As Gates (2011, p. 3) explains:
“The search for automated face perception technologies
and new forms of human-machine integration promises
to make surveillance systems function more effectively
and extend their reach over time and space. But whether
these experimental technologies can or should be made
to accomplish these goals remains open to debate, one
that often plays out in press and policy discussions as a
trade-off between ‘security’ and ‘privacy’.”
The facial recognition process, as we know it today, begins
with the capturing of the face image, also known as the
probe image (usually taken from a still or video camera,
for example); then the face is being detected and extract-
ed from the larger image (background or other faces); the
system will then “normalize” the image in the database
and pass it through the recognition software where the
possible match will be made between the new image and
database images (Introna & Nissenbaum, 2010, p. 11). As
Spiesel (2020) explains, Facial recognition is a task-spe-
cific technology, which relies on the data obtained by its
sensors and an algorithm, and it requires to be trained to
perform the matching of the obtained images. By now,
FRT is used around the world by different law enforce-
ment agencies to monitor the public space via biometric
data collection.
2. Protection of privacy
Protection of privacy is embodied in most human rights
instruments, including the Charter of Fundamental Rights
of the European Union, the Universal Declaration of Hu-
man Rights (UDHR), and the European Convention on
Human Rights (ECHR). The General Data Protection Reg-
ulation (GDPR), which came into force on 25 May 2018,
regulates the main issues about data protection law in the
European Union (EU) with modern rules that fit better in
a time where technology is evolving at a massive speed.
GDPR’s core principle is that personal data should not
be collected, or processed, more than what is necessary
for a certain purpose. As formulated in articles 1 and 2,
the regulation protects fundamental rights and freedoms
of a natural person and their right to the protection of
their personal data. GDPR (art. 9) protects and requires
consent for the collection of personal data, particularly
sensitive data, including biometrics.
According to GDPR Article 4(14), biometric data is con-
sidered personal data resulting from specific technical
processing. Biometric data allows confirming the unique
identification of natural persons, such as facial images.
The GDPR principles also include making clear to indi-
viduals when and how facial recognition data are being
collected, stored, and used; developing data management
practices that consider how individuals are enrolled and
what the risks, harms, and benefits of such (in)voluntary
enrolment and maintaining the accuracy and integrity of
any stored data may be (National Telecommunications
and Information Administration, 2016).
Although the GDPR protects individual personal and
sensitive data, including biometrics, it remains unclear
if facial images always fall under the scope of the GDPR,
depending, for example, on the legal justification for
processing, because a substantial public interest such as
national security or public safety may provide a path for
circumventing consent (Buckley & Hunter, 2011, p. 639). As
underlined by Jennifer Lynch (2012, p. 14), staff attorney
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
4
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
with the Electronic Frontier Foundation and a researcher
on biometrics and facial recognition, “advanced biom-
etrics like face recognition creates additional concerns
because the data may be collected in public without a
person’s knowledge.”
The GDPR has somewhat regulated the use of biometric
data, including FRT, but it is still not certain that the use
of such technology always considers people’s privacy.
According to Omar Tene (2011, p. 21), “the use of biomet-
rics raises privacy risks, including identity theft, function
creep, and government surveillance.” Buckley and Hunter
(2011, p. 639) claim that “the application of facial recogni-
tion technology to an individual’s facial image constitutes
processing of personal data and, therefore, can only take
place if a legal justification exists.” This indicates that the
processing of such data has to fall within the processing
conditions set in GDPR article 7, and individuals must be
informed of the process according to articles 10 and 11.
The EU Agency for Fundamental Rights (FRA) conducted
a study on the human rights issues related to FRT, how-
ever without guidance on possible legal regulation of
the technology (FRA, 2019). The European Commission’s
White Paper on AI (2020) addresses remote biometric
identification and indicates certain high-risk applications,
with additional specific requirements.
3. Privacy gaps in facial recognition
The survey, done by German and Switzerland researchers
in China, Germany, UK, and USA showed that almost half
of all German (48%) and US responders (44%) believe
that FRT increases privacy violations, and a majority of
Germans (66%) and roughly half of UK and US responders
believe that FRT increases surveillance (Steinacker et al.,
2020, p. 5). More than half of all country responders agree
that FRT increases security. Arguably, that is to be expect-
ed, because most of the people feel secure, and do not
consider their privacy invaded if they see a camera in pub-
lic areas or for example in shops. Seeing a camera might
make individuals feel that if anything should happen to
them or their property, someone will immediately notice
and send help, if necessary. The analysis also showed that
the interpretation of privacy threat is a strong and signifi-
cant negative predictor of acceptance. In other words, the
more a participant perceives the technology as a risk to
their privacy, the less likely they are to accept FRT use in
public (Steinacker et al., 2020, p. 5).
Researchers have raised the issues over privacy violations
before. For example, Christopher S. Milligan (1999, p. 299)
stated in his research that “in addition to the constitution-
al issues, there are also social and ethical issues that merit
public debate. These questions deal with whether people
are willing to live their lives under the watchful lens of a
camera and monitor — whether they are able to sacrifice
personal autonomy and risk governmental abuse of their
data for the sense of safety and order which video sur-
veillance provides”. He further explains that “the use of
video surveillance and facial recognition technology elim-
inates some amount of personal privacy and anonymity”
(Milligan, 1999, p. 326). Jennifer Lynch (2012, p. 2) says
that “face recognition technology, like other biometrics
programs that collect, store, share and combine sensitive
and unique data poses critical threats to privacy and civil
liberties.” Brenda Leong (2019, p. 113), director of strategy
at the Future of Privacy Forum, continues: “the ethical
considerations of where and how to use facial recognition
systems even exceed the boundaries of traditional privacy
considerations”.
Even without security concerns, the presence of FRT se-
verely damages the ability of regular people to maintain
their anonymity in the public space. Akin to the evolving
right to be forgotten, people ought to have the right to
remain anonymous (Naker & Greenbaum, 2017, p. 109). Al-
ready in 1999, it was acknowledged that facial recognition
and video surveillance technology can be successful in
catching criminals and preventing criminal activity (Milli-
gan, 1999, p. 323). However, with all its potential benefits,
FRT can pose serious challenges to the right to privacy
and data security. It creates problems of unwanted iden-
tification, discrimination, and the likely hacking of large
datasets of not only faces, but also all the data associated
with those faces (Naker & Greenbaum, 2017, p. 122). Bias
FRT and discrimination issues against minorities are ex-
tensively discussed by Timnit Gebru (2020).
An example of a database using FRT comes from a com-
pany called Clearview AI. They have created a research
tool, that is used by law enforcement agencies to identify
perpetrators and victims of crimes. They provide their
service worldwide and their facial recognition database
has billions of images, which they have allegedly collected
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
5
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
from open sources. The database can be used by analysts,
who can compare the uploaded crime scene images with
publicly available images in the database. In their 31st ple-
nary session, the European Data Protection Board (EDPB)
raised concerns regarding certain developments in facial
recognition technologies and expressed doubts as to
whether any Union or Member State law provides a legal
basis for using a service such as the one offered by Clear-
view AI (EDPB, 2020, p. 10). The EDPB was therefore of the
opinion that the use of a service such as Clearview AI by
law enforcement authorities in the European Union would,
as it stands, likely not be consistent with the EU data pro-
tection regime. Steinacker et al. (2020, p. 1) discovered in
their research, that while some of US Governments have
banned the use of FRT by city and state agencies, there
is currently no federal legislative consensus despite ex-
tensive activism for regulation. Neither has the European
Commission nor any of the EU Member states explicitly
ruled on FRT.
Amnesty International (2020), an organisation whose pri-
ority is to help people claim their rights, is also calling for a
ban on the use, development, production, sale, and export of
facial recognition technology for mass surveillance purpos-
es by the police and other state agencies. The tension be-
tween the technology and the right to privacy highlight the
dialectic between national security and law enforcement,
economic efficiency or public health promoted through the
application of facial recognition systems, on the one side,
and concerns relating to the potential for disproportionately
violating fundamental principles on our society such as the
right to personal autonomy, anonymity, to being forgotten,
to control one’s own personal identifying information, and
the person’s right to protect the own human body, on the
other (Naker & Greenbaum, 2017, p. 100).
During the COVID-19 pandemic, facial recognition was also
considered by many as a tool to help fight the virus. Since
the outbreak of the pandemic, the adoption or develop-
ment of digital systems in order to control the spread
of the infection, such as contact management software
(e.g., the WHO-provided Go.Data2) and to track persons
that may have been in contact with the virus (e.g., mobile
contact-tracing applications), has attracted the attention
of the public administration, private enterprises, and
research institutions around the world (Ramos, 2020, p.
176). Professor Silvia Barona Vilar (2020) talks about how
the employment of AI technologies, including facial rec-
ognition, in an attempt to eradicate the pandemic, shifts
the balance between freedom and security towards the
latter. Despite the enormous benefits of the technology,
privacy-related consequences due to additional security
and control measures put up a huge challenge in front of
our societies. The Human Rights Watch (2020), along with
numerous other organizations, published a joint state-
ment, indicating some conditions that technology-assist-
ed measures to fight the COVID-19 pandemic should meet
in order to respect human rights.
Many of these novel systems developed to control the
spread of infectious diseases have incorporated biometric
technologies, such as facial recognition access control
systems that can check people’s temperature and iden-
tification systems that recognize people even if they are
wearing protective masks (Ring, 2020, p. 4). The research
carried out in China, France, Israel, Poland, Singapore,
South Korea, and Russia about the FRT systems used dur-
ing the COVID-19 pandemic and the information available
on the analyzed systems, did not clarify which measures
were being considered to guarantee that the personal
data collected was used only to address the spread of
COVID-19 and not for additional law enforcement and
national security purposes, and it provided no assurance
that risk assessments were adopted (Ramos, 2020, p. 178).
There are also growing concerns that, once COVID-19 has
passed, the data derived from these digital systems could
be misused.
The lack of adequate regulations does not provide the
certainty that governments will restrict their measures,
particularly where there is no specific legislation estab-
lishing the rules on the processing, storing, or discarding
of the collected data (Ramos, 2020, p. 178). In order to
mitigate these risks, the European Commission went
ahead and edited guidelines for apps supporting the fight
against COVID-19 pandemic in relation to data protection
(eHealth Network, 2020). Furthermore, the EDPB (2020)
published some guidelines on the use of location data,
contact tracing tools, and the processing of personal data.
These documents provide valuable insights for facial rec-
ognition systems as well, since they enumerate applicable
data protection principles and recommendations for this
emergency period (Ramos, 2020, p. 179).
FRT is widely considered in different fields to try and use it
as a tool to find better solutions. However, research often
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
6
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
points to the existing gaps of such technology and, conse-
quently, to unsatisfactory results. An interesting research
is being conducted in the field of experimental psychology,
where facial cue is used in emotion recognition and decep-
tion detection attempt, but so far it has been concluded
that facial cue detection does not aid deception recogni-
tion (please see e.g., Zloteanu et al., 2021, pp. 910-927).
Sandford and Bindemann (2020, pp. 294-297) talk about
the usage of facial recognition in psychology and prob-
lems with the results delivered by working with subtle
metric differences in facial configuration, concluding that
“configuration theory provides limited explanatory power
for recognition of familiar faces”. Prof. Kosinski’s (2021)
research focuses on how FRT can determine several char-
acteristics of individuals and argues that even though FRT
is often a useful tool to improve human-technology inter-
actions, it could also identify more sensitive data, such as
political or sexual orientation, personality.
Using CCTV as a tool to identify individuals with the help
of FRT, therefore having a “super recognizer ability” could
be a great support to police in its work to fight crime,
however, this technology also has its limitations (Davis
et al., 2018, pp. 350-351). Brandy Dieterle (2021) explains
how FRT makes it hard to truly stay anonymous due to
the nature of social media engagement and argues that
there is a need for more comprehensive research ethics
when working with the intimate data of individuals. Such
“improved” ethical standards are especially important in
social media research, when working on minorities, such
as sexual minorities.
There are also interesting legal precedents; for example,
in early 2020, a Dutch court ruled that automated surveil-
lance system violated human rights and ordered its imme-
diate halt. A technology tool was used by the authorities to
help them fight benefit and tax fraud, by identifying those
individuals who might be committing the wrongdoing.
Later in August 2020, The Royal Courts of Justice in Lon-
don (EWCA Civ 1058, Case No: C1/2019/2670) issued the
ruling stating that facial recognition technology violates
personal freedoms, invades privacy, and is discriminato-
ry. The court stated that South Wales Police use of Live
Automated Facial Recognition technology, which engaged
Article 8(1) of the European Convention on Human Rights,
was not in accordance with the law for the purposes of
Article 8(2) (EWCA Civ 1058, Case No: C1/2019/2670, p.
210). As for the ongoing use of Live Automated Facial Rec-
ognition technology, its Data Protection Impact Assess-
ment did not comply with section 64(3)(b) and (c) of the
UK Data Protection Act 2018 (A data protection impact
assessment must include the following: an assessment of
the risks to the rights and freedoms of data subjects and
the measures envisaged to address those risks).
The case shows that the use of FRT violated right to pri-
vacy, because the appropriate safeguards, which apply
to the processing of personal data, including biometric
data, where not used. The judges also mentioned that the
FRT was supposed to be used to identify and locate peo-
ple who were suspected of criminality, or wanted by the
courts and police, who might pose a risk, or who may be
vulnerable, but in this case, the police scanned and identi-
fied everyone, and by doing this, violated privacy and data
protection rights.
Conclusion
Emerging technologies and the digitalization process in
general have an increasing impact on our everyday lives.
These technologies bring various opportunities and offer
solutions to us in a variety of fields. Professionals in all
those fields try to measure the new opportunities and
solutions that the use of these technologies would offer,
trying to benefit from the technological progress and
achieve new levels within these sectors. The opportunities
are truly unique, while the process is extremely fast. How-
ever, ever since technology has taken an important part
of our lives and the lives of our societies, the ethical impli-
cations of this process have been discussed by scholars,
in order to fully understand what potential ethical risks
are there from such “cooperation” between humans and
technology.
The discussion on the positive and negative effects of these
technologies and the technologization process has been
topic for debate on different levels. This research intended
to contribute to that debate at the academic level, focusing
on facial recognition. A brief analysis of the situation with
FRT usage in different fields and the feedback received
from the scholars focusing their research on these ques-
tions, demonstrates evident gaps in the results delivered
by FRT. Provided examples clearly indicate that very fre-
quently there is an actual violation of human rights when
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
7
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
using a facial recognition technology, while often there
is a genuine risk. As evidenced by the analysis, there is a
lack of clear regulation regarding how, when and for what
purposes this technology can be used in specific fields,
and until there is one, the technology should not be used,
as it is often in violation of human rights or entails clear
risks of doing so. There is no argument whether FRT or AI
technologies in general, can support our work in different
fields and in various ways, extending our abilities and pos-
sibilities. However, as Spiesel (2020) puts it, assuming that
conscious AI will care for humankind would be a mistake.
The EU has been a pioneer in the world trying to address
the complicated issues related to the widespread and rap-
idly growing usage of modern technologies, including FTR.
It has been providing extensive documentation on this
topic. The European Commission’s Ethics Guidelines for
Trustworthy Artificial Intelligence is a huge step forward
in this direction, in addition to all above-indicated doc-
uments, with some of them specifically addressing FRT.
However, European efforts remain slow in comparison
with how rapidly the technology is developing and used
daily. When assessing challenges of regulatory frame-
work on AI ethics, the European Parliamentary Research
Service (2020) identified six main risks factors, which
included a challenge of “a growing mismatch between
the exponential growth of the AI market and a ‘delayed’
regulatory response.”
Questions raised by the researchers from the specific
fields where facial recognition has been used as a tool,
demonstrate the need to further develop field-specific
guidelines to ensure an ethical and human rights friendly
employment of such technology. Parfet et al. (2020) in-
terestingly compare AI technology to a child, as it needs
to be educated and trained before we could rely on the
results delivered by it. Just like children learn from their
parents and from what their parents teach them, these
technologies need to learn from what the data and pro-
grammes tell them.
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
8
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
References
AMNESTY INTERNATIONAL (2020). “Amnesty International Calls for Ban on the Use of Facial Recogni-
tion Technology for Mass Surveillance”. In: Amnesty International [online]. Available at: https://www.
amnesty.org/en/latest/research/2020/06/amnesty-international-calls-for-ban-on-the-use-of-fa-
cial-recognition-technology-for-mass-surveillance/ [Accessed: 17 May 2021].
ARRIDGE, S.; MOSS, J. P.; LINNEY, A. D.; JAMES, D. R. (1985). “Three dimensional digitization of the face
and skull”. In: Journal of Maxillofacial Surgery, vol. 13, no. 3, pp. 136-143 [online]. DOI: https://doi.
org/10.1016/S0301-0503(85)80034-5
BEEVER, J.; MCDANIEL, R.; STANLICK, N. A. (2019). Understanding Digital Ethics: Cases and Contexts
[online]. Abingdon: Routledge. DOI: https://doi.org/10.4324/9781315282138
BREY, P. (2010). “Philosophy of technology after the empirical turn”. In: Techné: Research in Philosophy
and Technology, vol. 14, no. 1, pp. 36-48 [online]. DOI: https://doi.org/10.5840/techne20101416
BROWNSWORD, R.; GOODWIN, M. (2012). Law and the Technologies of the Twenty-First Century [on-
line]. New York: Cambridge University Press. DOI: https://doi.org/10.1017/CBO9781139047609
BUCKLEY, B.; HUNTER, M. (2011). “Say Cheese! Privacy and facial recognition”. In: Computer Law and
Security Review, vol. 27, vol. 6, pp. 637-640 [online]. DOI: https://doi.org/10.1016/j.clsr.2011.09.011
CLEARVIEW.AI (n.d.). Clearview AI official website [online]. Available at: https://clearview.ai [Accessed:
17 May 2021].
COUNCIL OF EUROPE (1950). European Convention for the Protection of Human Rights and Fundamen-
tal Freedoms [online]. Available at: https://www.refworld.org/docid/3ae6b3b04.html [Accessed: 17
May 2021].
DAVIS, J. P.; FORREST, C.; TREML, F.; JANSARI, A. (2018). “Identification from CCTV: Assessing police
super-recogniser ability to spot faces in a crowd and susceptibility to change blindness”. In: Appl
Cognit Psychol, no. 32, pp. 337-353 [online]. DOI: https://doi.org/10.1002/acp.3405
DEIGH, J. (2010). An Introduction to Ethics [online]. New York: Cambridge University Press. DOI: https://
doi.org/10.1017/CBO9780511750519
DELOITTE (n.d.). Europe’s “Trustworthy AI” meets AI Ethics. The ethics of AI [online]. Available at:
https://www2.deloitte.com/nl/nl/pages/risk/articles/europes-trustworthy-ai-meets-ai-ethics.html
[Accessed: 27 April 2021].
DIETERLE, B. (2021). “People As Data?: Developing an Ethical Framework for Feminist Digital Research”.
In: Computers and Composition, vol. 59 [online]. DOI: https://doi.org/10.1016/j.compcom.2021.102630
EHEALTH NETWORK (2020). “Mobile Applications to Support Contact Tracing in the EU’s Fight against
COVID-19” [online]. Available at: https://ec.europa.eu/health/sites/default/files/ehealth/docs/cov-
id-19_apps_en.pdf [Accessed: 17 May 2021].
ELLUL, J. (1964). The Technological Society. New York: Vintage Books.
EUROPEAN COMMISSION (2020). “White Paper on Ar tificial Intelligence-A European approach to
excellence and trust” [online]. Available at: https://ec.europa.eu/info/sites/default/files/commis-
sion-white-paper-artificial-intelligence-feb2020_en.pdf [Accessed: 20 September 2021].
EUROPEAN DATA PROTECTION BOARD (EDPB) (2020). “Guidelines 04/2020 on the Use of Location
Data and Contact Tracing Tools in the Context of the COVID-19 Outbreak” [online]. Available at:
https://edpb.europa.eu/sites/default/files/files/file1/edpb_guidelines_20200420_contact_trac-
ing_covid_with_annex_en.pdf [Accessed: 17 May 2021].
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
9
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
EUROPEAN PARLIAMENTARY RESEARCH SERVICE (2020). “European framework on ethical aspects
of artificial intelligence, robotics and related technologies. European Added Value Assessment”
[online]. Available at: https://www.europarl.europa.eu/thinktank/en/document.html?refer-
ence=EPRS_STU(2020)654179 [Accessed: 23 September 2021].
EUROPEAN UNION (2012). Charter of Fundamental Rights of the European Union, 2012/C 326/02
[online]. Available at: https://eur-lex.europa.eu/legal-content/HR/TXT/?uri=celex:12012P/TXT [Ac-
cessed: 17 May 2021].
EUROPEAN UNION (2016). EU General Data Protection Regulation (GDPR). Regulation (EU) 2016/679
of the European Parliament and of the Council of 27 April 2016 [online]. Available at: https://eur-
lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN [Accessed: 17 May
2021].
EUROPEAN UNION AGENCY FOR FUNDAMENTAL RIGHTS (FRA) (2019). Facial recognition technology:
fundamental rights considerations in the context of law enforcement [online]. Available at: https://
fra.europa.eu/en/publication/2019/facial-recognition-technology-fundamental-rights-considera-
tions-context-law [Accessed: 20 September 2021].
GATES, K. A. (2011). Our Biometric Future: Facial Recognition Technology and the Culture of Surveil-
lance [online]. 2nd. ed. NYU Press. DOI: https://doi.org/10.18574/nyu/9780814732090.001.0001
GEBRU, T. (2020). “Race and gender”. In: The Oxford handbook of ethics of AI, pp. 251-269 [online]. DOI:
https://doi.org/10.1093/oxfordhb/9780190067397.013.16
HUMAN RIGHTS WATCH (2020). “Joint Civil Society Statement: States Use of Digital Surveillance
Technologies to Fight Pandemic Must Respect Human Rights” [online]. Available at: https://www.
hrw.org/news/2020/04/02/joint-civil-society-statement-states-use-digital-surveillance-technolo-
gies-fight [Accessed: 17 May 2021].
INTRONA, L.; NISSENBAUM, H. (2010). “Facial Recognition Technology A Survey of Policy and Imple-
mentation Issues”. In: Organisation, Work and Technology Working Paper Series. Lancaster: The
Department of Organisation, Work and Technology of Lancaster University Management School.
JOAMETS, K.; CHOCHIA, A. (2020). “Artificial intelligence and its impact on labour relations in Esto-
nia”. In: Slovak Journal of Political Sciences, vol. 20, no. 2, pp. 255-277 [online]. DOI: http://doi.
org/10.34135/sjps.200204 https://doi.org/10.34135/sjps.200204
JOAMETS, K.; CHOCHIA, A. (2021). “Access to Artificial Intelligence for Persons with Disabilities:
Legal and Ethical Questions Concerning the Application of Trustworthy AI”. In: Acta Baltica His-
toriae et Philosophiae Scientiarum, vol. 9, no. 1, pp. 51-66 [online]. DOI: https://doi.org/10.11590/
abhps.2021.1.04
JOBIN, A.; IENCA, M.; VAYENA, E. (2019). “The global landscape of AI ethics guidelines”. In: Nature
Machine Intelligence, vol. 1, pp. 389-399 [online]. DOI: https://doi.org/10.1038/s42256-019-0088-2
JOHNSON, D. (2004). “Computer ethics”. In: FLORIDI, L. (ed.). The Blackwell Guide to the Philoso-
phy of Computing and Information, pp. 65-75 [online]. New York: Blackwell. DOI: https://doi.
org/10.1002/9780470757017.ch5
KERIKMÄE, T.; HOFFMANN, T.; CHOCHIA, A. (2018). “Legal technology for law firms: determining road-
maps for innovation”. In: Croatian International Relations Review, vol. 24, no. 81, pp. 91-112 [online].
Available at: https://hrcak.srce.hr/199994 [Accessed: 28 November 2021].
KERIKMÄE, T.; SOLARTE-VASQUEZ, M. C.; RUDANKO, M.; TROITIÑO, D. R. (eds.) (2020). Inteligencia
artificial: de la discrepancia regional a las reglas universales. Integración de percepciones políticas,
económicas y legales. Pamplona: Thomson Reuters.
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
10
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
KOSINSKI, M. (2021). “Facial recognition technology can expose political orientation from naturalistic
facial images”. In: Sci Rep, no. 11, 100 [online]. DOI: https://doi.org/10.1038/s41598-020-79310-1
LEONG, B. (2019). “Facial recognition and the future of privacy: I always feel like…somebody’s watching
me”. In: Bulletin of the Atomic Scientists, vol. 75, no. 3, pp. 109-115 [online]. DOI: https://doi.org/10.1
080/00963402.2019.1604886
LYNCH, J. (2012). “What Facial Recognition Technology Means for Privacy and Civil Liberties”. In: Sen-
ate Committee on the Judiciary [online]. DOI: https://doi.org/10.2139/ssrn.2134497
MILLIGAN, C. S. (1999). “Facial recognition technology, video surveillance, and privacy”. In: Southern
California Interdisciplinary Law Journal, vol. 9, no. 1, pp. 295-334.
MOSS, J. P.; LINNEY, A. D.; GRINDROD, S. R.; ARRIDGE, S. R.; CLIFTON, J. S. (1987). “Three-dimensional
visualization of the face and skull using computerized tomography and laser scanning techniques”.
In: European Journal of Orthodontics, vol. 9, no. 4, pp. 247-253 [online]. DOI: https://doi.org/10.1093/
ejo/9.4.247
NAKER, S.; GREENBAUM, D. (2017). “Now you see me: Now you still do: Facial recognition technology
and the growing lack of privacy”. In: Boston University Journal of Science and Technology Law, vol.
23, no. 1, pp. 88-122.
NATIONAL TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION (2016). “Privacy Best
Practices Recommendations for Commercial Facial Recognition Use” [online]. Available at: https://
www.ntia.doc.gov/files/ntia/publications/privacy_best_practices_recommendations_for_commer-
cial_use_of_facial_recogntion.pdf [Accessed: 17 May 2021].
PARFETT, A.; TOWNLEY, S.; ALLERFELDT, K. (2020). “AI-based healthcare: a new dawn or apartheid
revisited?”. In: AI & Society [online]. DOI: https://doi.org/10.1007/s00146-020-01120-w
PARSONS, T. D. (2019). Ethical Challenges in Digital Psychology and Cyberpsychology [online]. Cam-
bridge: Cambridge University Press. DOI: https://doi.org/10.1017/9781108553384
RAMOS, L. F. (2020). “Evaluating privacy during the COVID-19 public health emergency: the case of
facial recognition technologies”. In: Proceedings of the 13th International Conference on Theory
and Practice of Electronic Governance, pp. 176-179 [online]. New York: Association for Computing
Machinery. DOI: https://doi.org/10.1145/3428502.3428526
RING, T. (2020). “Face ID Firms Battle Covid-19 as Users Shun Fingerprinting”. In: Biometric Technology
Today, vol. 4, pp. 1-2 [online]. DOI: https://doi.org/10.1016/S0969-4765(20)30042-4
ROYAL COURT OF JUSTICE (2019). R (Bridges) vs. CC South Wales & ors. EWCA Civ 1058, Case No:
C1/2019/2670 [online]. Available at: https://www.judiciary.uk/wp-content/uploads/2020/08/R-
Bridges-v-CC-South-Wales-ors-Judgment.pdf [Accessed: 14 May 2021].
SANDFORD, A.; BINDEMANN, M., (2020). “Discrimination and recognition of faces with changed con-
figuration”. In: Mem Cogn, no. 48, pp. 287-298 [online]. DOI: https://doi.org/10.3758/s13421-019-
01010-7
SPIESEL, C. (2020). “Technology’s Black Mirror: Seeing, Machines, and Culture”. In: Int J Semiot Law
[online]. DOI: https://doi.org/10.1007/s11196-019-09679-4
STEINACKER, L.; MECKEL, M.; KOSTKA, G.; BORTH, D. (2020). “Facial Recognition: A cross-national
Survey on Public Acceptance, Privacy, and Discrimination”. In: Law and ML Workshop.
TENE, O. (2011). “Privacy: The new generations”. In: International Data Privacy Law, vol. 1, no. 1, pp.
15-27 [online]. DOI: https://doi.org/10.1093/idpl/ipq003
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
11
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
THE GUARDIAN (2020). “Welfare surveillance system violates human rights, Dutch court rules” [on-
line]. Available at: https://www.theguardian.com/technology/2020/feb/05/welfare-surveillance-
system-violates-human-rights-dutch-court-rules [Accessed: 14 May 2021].
TROITIÑO, D. R.; KERIKMÄE, T.; SHUMILO, O.; RAMÍREZ BARBOSA, P. A. (2020). “El libro blanco sobre
inteligencia artificial: análisis y comentarios sobre mercado, valores y cooperación europea”. In:
KERIKMÄE, T.; SOLARTE-VASQUEZ, M. C.; RUDANKO, M.; TROITIÑO, D. R. (eds.). El Parlamento Eu-
ropeo y la necesidad de una legislación común en un marco europeo de la inteligencia artificial. In-
teligencia artificial: de la discrepancia regional a las reglas universales. Integración de percepciones
políticas, económicas y legales, pp. 303-317. Pamplona: Thomson Reuters.
UNITED KINGDOM (2018). “UK Data Protection Act” [online]. Available at: https://www.legislation.gov.
uk/ukpga/2018/12/contents/enacted [Accessed: 17 May 2021].
UNITED NATIONS (1948). “Universal Declaration of Human Rights” [online]. Available at: https://www.
un.org/en/about-us/universal-declaration-of-human-rights [Accessed: 17 May 2021].
VERBEEK, P.-P. (2011). Moralizing Technology, Understanding and Designing the Morality of Things [online].
Chicago: University of Chicago Press. DOI: https://doi.org/10.7208/chicago/9780226852904.001.0001
VERZE, L. (2009). “History of facial recognition”. In: Acta Biomed, vol. 80, pp. 5-12.
VILAR, S. B. (2020). “La sociedad postcoronavirus con big data, algoritmos y vigilancia digital, ¿excusa
por motivos sanitarios?, ¿y los derechos dónde quedan?”. Revista Boliviana de Derecho, no. 30, pp.
14-39.
WELINDER, Y. (2012). “A Face Tells More than a Thousand Posts: Developing Face Recognition Privacy
in Social Networks”. In: Harvard Journal of Law and Technology, vol. 26, no. 1, pp. 166-237.
WILKINSON, C. (2004). “Forensic facial reconstruction”. Cambridge University Press.
WINSTON, M.; EDELBACH, R. (2011). Society, Ethics and Technology [online]. Belmont, CA: Wadsworth
Publishing. DOI: https://doi.org/10.1017/CBO9781107340961
ZLOTEANU, M.; BULL, P.; KRUMHUBER, E. G.; RICHARDSON, D. C. (2021). “Veracity judgement, not
accuracy: Reconsidering the role of facial expressions, empathy, and emotion recognition training
on deception detection”. In: Quarterly Journal of Experimental Psychology, vol. 74, no. 5, pp. 910-
927 [online]. DOI: https://doi.org/10.1177/1747021820978851
https://idp.uoc.edu
Universitat Oberta de Catalunya
Ethics and emerging technologies – facial recognition
IDP No. 34 (December, 2021) I ISSN 1699-8154 Journal promoted by the Law and Political Science Department
12
2021, Archil Chochia and Teele Nässi
of this edition: 2021, Universitat Oberta de Catalunya
Recommended citation
CHOCHIA, Archil; NÄSSI, Teele (2021). “Ethics and emerging technologies – facial recognition”. IDP.
Internet, Law and Politics E-Journal. No. 34. UOC [Accessed: dd/mm/aa]
http://dx.doi.org/10.7238/idp.v0i34.387466
The texts published in this journal, unless otherwise indicated, are subject to a Creative
Commons Attribution No Derivative Works 3.0 Spain licence. They may be copied, distribut-
ed and broadcast provided the the author, the journal and the institution that publishes
them (IDP. Revista de Internet, Derecho y Política; UOC) are cited. Derivative works are not
permitted. The full licence can be consulted on http://creativecommons.org/licenses/by-
nd/3.0/es/deed.es.
About the authors
Archil Chochia
Tallinn University of Technology (TalTech)
archil.chochia@taltech.ee
Department of Law
Tallinn University of Technology
Ehitajate tee 5, Tallinn 19086, Estonia
Senior Researcher at TalTech Law School of Tallinn University of Technology. Dr. Chochia obtained
his doctoral degree from Tallinn University of Technology in 2013. He has more than 90 academic
publications and is a co-editor of the books Political and Legal Perspectives of the EU Eastern Partner-
ship Policy (Springer, 2016), Brexit: History, Reasoning and Perspectives (Springer, 2018) and Russian
Federation in the Global Knowledge Warfare — Influence Operations in Europe and Its Neighbourhood
(Springer, 2021). Archil is a managing editor of TalTech Journal of European Studies. His research fields
of interest are law and technology, ethical aspects of digitalization, alternative dispute resolution, EU
integration, EU Neighbourhood Policy. Archil is a Senior Fellow of Weinstein International Foundation.
ORCID: https://orcid.org/0000-0003-4821-297X
Teele Nässi
Tallinn University of Technology (TalTech)
teenas@taltech.ee
Master level student at TalTech Law School of Tallinn University of Technology, Estonia. Ms. Nässi has
obtained her diploma, BA in Law, from TalTech Law School of Tallinn University of Technology in 2012.
Currently, Ms. Nässi works for local government as a lawyer, while she previously worked as a clerk at
the Harju County court for five years.
