Algorithms and artificial intelligence reading list

The following is a selection of key books, journal articles and papers on Algorithms and Artificial Intelligence issues, with an emphasis on equality and human rights issues.  Please email our Library if you have any suggestions for a book or journal article to add to this list.

Allen, R. (2020) ‘Artificial Intelligence, Machine Learning, algorithms and discrimination law: the new frontier’. Paper prepared for Discrimination Law in 2020 conference, Congress House, 31 January.

Allen, R. and Masters, D. (2020) ‘Artificial Intelligence: the right to protection from discrimination caused by algorithms, machine learning and automated decision-making’, ERA Forum, 20 (4), pp. 585-98.

Allen, R, and Masters, D. (2018) Algorithms, apps & Artificial Intelligence: the next frontier in discrimination law’. Paper prepared for Public Law Project session, 16 October. London: Cloisters.

Blackham, A. (2018) ‘”We are all entrepreneurs now”: options and new approaches for adapting equality law for the “gig economy”’, International Journal of Comparative Labour Law and Industrial Relations, 34 (4), pp. 413-34.

Bogen, M. (2018) ‘Help wanted: an examination of hiring algorithms, equity, and bias’, Upturn (December).

Bogen, M. (2019) ‘All the ways hiring algorithms can introduce bias’, Harvard Business Review, 6 May.

Brione, P. (2020) My Boss the Algorithm: an Ethical Look at Algorithms in the Workplace. (Acas Research Paper).

Brione, P. and Wakeling, A. (2019) New Technology and the World of Work: the Winners and the Losers (Acas Policy Paper).

Centre for Data Ethics and Innovation (2019) Review into Bias in Algorithmic Decision-Making. Interim report. London: The Centre for Data Ethics.

Chamorro-Premuzic, T. (2019) ‘Will AI reduce gender bias in hiring?Harvard Business Review, 10 June.

Committee on Standards in Public Life (2020) Artificial Intelligence and Public Standards: A Review by the Committee on Standards in Public Life. London: Committee on Standards in Public Life.

Council of Europe (2018) Algorithms and Human Rights: Study on the Human Rights Dimensions of Automated Data Processing Techniques and Possible Regulatory Implications, Strasbourg: Council of Europe.

Council of Europe (2018) Discrimination, Artificial Intelligence, and Algorithmic Decision-Making, Strasbourg: Council of Europe.

Dalenberg, D.J. (2018) ‘Preventing discrimination in the automated targeting of job advertisements’, Computer Law & Security Review, 34(3), pp.615-27.

D’Ignazio, C. and Klein, L.F. (2020) Data Feminism, Cambridge, Massachusetts: The MIT Press.

Edwards, L. and Veale, M. (2018) ‘Enslaving the algorithm: from a “right to an explanation” to a “right to better decisions?IEEE Security and Privacy, 16(3), pp. 46-54.

Eubanks, V. (2018) Automating Inequality. New York: St Martin’s Press.

European Commission (2020) White Paper: On Artificial Intelligence: A European Approach to Excellence and Trust. (Brussels, 19.2.2020 COM(2020) 65 final).

Fjeld, J., Achten, N., Hilligoss, H., Nagy, A.C. and Srikumar, M. (2020), Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI. Berkman Klein Center for Internet & Society Research Publication Series. Harvard University.

Gerards, J. (2019) ‘The fundamental rights challenges of algorithms’, Netherlands Quarterly of Human Rights, 37 (3), pp.205-09.

Griffin, P. (2019) ‘Artificial intelligence and the future of work’, Employment Law Journal, 190, pp. 22-24.

High-Level Expert Group on Artificial Intelligence (2019) A Definition of AI: Main Capabilities and Disciplines, Brussels: European Commission.

House of Commons Science and Technology Committee (2018) Algorithms in Decision-making. London: House of Commons. Fourth Report of Session 2017-19.

Irving, A. (2019) ‘Rise of the algorithms’, UK Human Rights Blog, 4 November.:

O’Neill, C. (2016) Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. London: Penguin.

Neufeind, M., O’Reilly, J. and Ranft, F. (ed.) (2018) Work in the Digital Age: Challenges of the Fourth Industrial Revolution, London: Rowman and Littlefield.

Noble, S.U. (2018) Algorithms of Oppression. New York: New York University Press.

Piasna, A. and Drahokoupil, J. (2017) Gender inequalities in the new world of work, Transfer: European Review of Labour and Research, 23(3). pp. 249-52.

Rennie, J. (2019) ‘Can an algorithm eradicate bias in our decision making?Personnel Today, 29 August.

Tzanou, M. (forthcoming) ‘Addressing big data challenges: a taxonomy and why the GDPR cannot provide a one-size-fits-all solution’. In M. Tzanou (ed.), Big Health Data and the GDPR: Data Protection, Privacy and the Law, Abingdon: Routledge.

Wachter, S. (forthcoming, 2020) ‘Affinity profiling and discrimination by association in online behavioural advertising’, Berkeley Technology Law Journal, 35 (2).

Wachter, S., Mittelstadt, B. and Russell, C. (forthcoming) ‘Why fairness cannot be automated: Bridging the gap between EU non-discrimination law and AI’.

West, S.M., Whittaker, M. and Crawford, K. (2019) Discriminating Systems: Gender, Race and Power in AI. New York: AI Now Institute.

Williams, B.A, Brooks, C.F and Shmargad, Y. (2018) How algorithms discriminate based on data they lack: challenges, solutions, and policy implications, Journal of Information Policy; 8: pp. 78-115.

Last updated: 17 May 2019