IEEE Technology and Society Magazine - June 2021 - 80

Feature
[16] S. Verma and J. Rubin, " Fairness definitions explained, "
in Proc. IEEE/ACM FairWare, May 2018, pp. 1-7.
[17] C. Dwork et al., " Fairness through awareness, " in Proc.
ITCS. New York, NY, USA: ACM, 2012, pp. 214-226.
[18] M. Feldman et al., " Certifying and removing disparate
impact, " in Proc. ACM-SIGKDD. New York, NY, USA:
ACM, 2015, pp. 259-268.
[19] T. Bolukbasi et al., " Man is to computer programmer
as woman is to homemaker? Debiasing word
embeddings, " in Proc. Adv. Neural Inf. Process. Syst.,
2016, pp. 4349-4357.
[20] A. Romei and S. Ruggieri, " A multidisciplinary survey
on discrimination analysis, " Knowl. Eng. Rev., vol. 29,
no. 5, 2014, Art. no. 582638.
[21] S. Barocas and A. Selbst, " Big data's disparate
impact, " California Law Rev., vol. 104, no. 3, pp.
671-729, Jun. 2016. [Online]. Available: https://ssrn.
com/abstract=2477899
[22] M. Hildebrandt and B.-J. Koops, " The challenges of
ambient law and legal protection in the profiling era,''
Mod. Law Rev., vol. 73, no. 3, pp. 428-460, 2010.
[23] M. Leese, " The new profiling: Algorithms, black boxes,
and the failure of anti-discriminatory safeguards in
the European union, " Secur. Dialogue, vol. 45, no. 5,
pp. 494-511, Oct. 2014.
[24] S. Walby, J. Armstrong, and S. Strid, " Intersectionality:
Multiple inequalities in social theory, " Sociology,
vol. 46, no. 2, pp. 224-240, Apr. 2012.
[25] M. Ananny and K. Crawford, " Seeing without
knowing: Limitations of the transparency ideal and
its application to algorithmic accountability, " New
Media Soc., vol. 20, no. 3, pp. 973-989, Mar. 2018.
[26] T. van Nuenen et al., " Transparency for whom?
Assessing discriminatory artificial intelligence, "
Computer, vol. 53, no. 11, pp. 36-44, Nov. 2020.
[27] R. Binns et al., " 'It's reducing a human being to a
percentage': Perceptions of justice in algorithmic
decisions, " in Proc. CHI. New York, NY, USA: ACM,
2018, p. 377.
[28] O. S. Curry, D. A. Mullins, and H. Whitehouse, " Is it
good to cooperate? Testing the theory of moralityas-cooperation
in 60 societies, " Current Anthropol.,
vol. 60, no. 1, pp. 47-69, Feb. 2019.
[29] J. Tasioulas, " First steps towards an ethics of robots
and artificial intelligence, " J. Practical Ethics, vol. 7,
no. 1, 2019.
Xavier Ferrer received the Ph.D. degree in
informatics from the Artificial Intelligence Institute,
Spanish National Research Council (IIIA-CSIC),
80
Barcelona, Spain, and the Universitat Autonoma de
Barcelona (UAB), Barcelona, in 2017.
He is currently a Research Associate in digital
discrimination with the Department of Informatics,
King's College London, London, U.K. His research
interests are related to natural language processing,
machine learning, and fairness.
Tom van Nuenen received the Ph.D. degree
in cultural studies from Tilburg University, Tilburg,
Netherlands, in 2016.
He is currently a Research Associate with the
Department of Informatics, King's College London,
London, U.K., and a Visiting
Scholar
in
digital
humanities with the University of California at
Berkeley, Berkeley, CA, USA. He focuses on the use
of mixed methods to identify and solve social, ethical,
and development questions related to big data,
artificial intelligence (AI), and machine learning.
Jose M. Such is currently a Reader (Associate
Professor) with the Department of Informatics and
the Director of the KCL Cybersecurity Centre, King's
College London, London, U.K. He has been a Principal
Investigator for a number of large projects funded
by EPSRC, including the Discovering and Attesting
Digital Discrimination (DADD) Project and the Secure
AI Assistants (SAIS) Project. His research interests are
at the intersection of artificial intelligence (AI), human-
computer interaction, and cybersecurity, with a strong
focus on human-centered AI security, ethics, and privacy.
Mark Coté is currently a Senior Lecturer in data
culture and society with the Department of Digital
Humanities, King's College London, London, U.K.
He is a Principal Investigator (PI) and a Co-Principal
Investigator (CI) on a range of H2020 and UKRI grants,
namely, through the Engineering and Physical Science
Research Council and the Arts and Humanities
Research Council. He is involved in
research on
critical interdisciplinary methods focusing on the
social, cultural, and political-economic dimensions of
big data, algorithms, and machine learning.
Natalia Criado is currently a Senior Lecturer in
computer science with the Department of Informatics
and the Co-Director of the UKRI Centre for Doctoral
Training
in Safe and Trusted AI, King's College
London, London, U.K. Her research interests are
computational norms and normative multiagent
systems, and the application of multiagent systems,
data science, and artificial intelligence to enhance
cybersecurity and privacy.
 Direct questions and comments about this article to
Xavier Ferrer, King's College London, London WC2R
2LS, U.K.; xavier.ferrer_aran@kcl.ac.uk.
IEEE Technology and Society Magazine
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IEEE Technology and Society Magazine - June 2021

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