In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

Adler P, Falk C, Friedler SA, et al. (2016) Auditing black-box models by obscuring features. arXiv:1602.07043 [cs, stat]. Available at: http://arxiv.org/abs/1602.07043 (accessed 5 March 2016). Google Scholar
Agrawal, R, Srikant, R (2000) Privacy-preserving data mining. ACM Sigmod Record, ACM, pp. 439450. Available at: http://dl.acm.org/citation.cfm?id=335438 (accessed 20 August 2015). Google Scholar, Crossref
Allen, C, Wallach, W, Smit, I (2006) Why machine ethics?. Intelligent Systems, IEEE 21(4): Available at: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1667947 (accessed 1 January 2006). Google Scholar, Crossref
Ananny, M (2016) Toward an ethics of algorithms convening, observation, probability, and timeliness. Science, Technology & Human Values 41(1): 93117. Google Scholar, Link
Anderson, M, Anderson, SL (2007) Machine ethics: Creating an ethical intelligent agent. AI Magazine 28(4): 15. Google Scholar
Anderson M and Anderson SL (2014) Toward ethical intelligent autonomous healthcare agents: A case-supported principle-based behavior paradigm. Available at: http://doc.gold.ac.uk/aisb50/AISB50-S17/AISB50-S17-Anderson-Paper.pdf (accessed 24 August 2015). Google Scholar
Anderson, SL (2008) Asimov's ‘Three Laws of Robotics’ and machine metaethics. AI and Society 22(4): 477493. Google Scholar, Crossref
Applin, SA, Fischer, MD (2015) New technologies and mixed-use convergence: How humans and algorithms are adapting to each other. In: 2015 IEEE international symposium on technology and society (ISTAS), Dublin, Ireland: IEEE, pp. 16. . Google Scholar, Crossref
Arendt, H (1971) Eichmann in Jerusalem: A Report on the Banality of Evil, New York: Viking Press. Google Scholar
Barnet, BA (2009) Idiomedia: The rise of personalized, aggregated content. Continuum 23(1): 9399. Google Scholar, Crossref
Barocas S (2014) Data mining and the discourse on discrimination. Available at: https://dataethics.github.io/proceedings/DataMiningandtheDiscourseOnDiscrimination.pdf (accessed 20 December 2015). Google Scholar
Barocas, S, Selbst, AD (2015) Big data's disparate impact, SSRN Scholarly Paper, Rochester, NY: Social Science Research NetworkAvailable at: http://papers.ssrn.com/abstract=2477899 (accessed 16 October 2015). Google Scholar
Bello, P, Bringsjord, S (2012) On how to build a moral machine. Topoi 32(2): 251266. Google Scholar, Crossref
Birrer, FAJ (2005) Data mining to combat terrorism and the roots of privacy concerns. Ethics and Information Technology 7(4): 211220. Google Scholar, Crossref
Bozdag, E (2013) Bias in algorithmic filtering and personalization. Ethics and Information Technology 15(3): 209227. Google Scholar, Crossref
Brey, P, Soraker, JH (2009) Philosophy of Computing and Information Technology, Elsevier. Google Scholar, Crossref
Burrell, J (2016) How the machine ‘thinks:’ Understanding opacity in machine learning algorithms. Big Data & Society 3(1): 1–12. Google Scholar
Calders, T, Verwer, S (2010) Three naive Bayes approaches for discrimination-free classification. Data Mining and Knowledge Discovery 21(2): 277292. Google Scholar, Crossref
Calders T, Kamiran F and Pechenizkiy M (2009) Building classifiers with independency constraints. In: Data mining workshops, 2009. ICDMW'09. IEEE international conference on, Miami, USA, IEEE, pp. 13–18. Google Scholar
Cardona, B (2008) ‘Healthy ageing’ policies and anti-ageing ideologies and practices: On the exercise of responsibility. Medicine, Health Care and Philosophy 11(4): 475483. Google Scholar, Crossref, Medline
Coeckelbergh, M (2013) E-care as craftsmanship: Virtuous work, skilled engagement, and information technology in health care. Medicine, Health Care and Philosophy 16(4): 807816. Google Scholar, Crossref, Medline
Cohen, IG, Amarasingham, R, Shah, A (2014) The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Affairs 33(7): 11391147. Google Scholar, Crossref
Coll, S (2013) Consumption as biopower: Governing bodies with loyalty cards. Journal of Consumer Culture 13(3): 201220. Google Scholar, Link
Crawford, K (2016) Can an algorithm be agonistic? Ten scenes from life in calculated publics. Science, Technology & Human Values 41(1): 7792. Google Scholar, Link, ISI
Crnkovic, GD, Çürüklü, B (2011) Robots: ethical by design. Ethics and Information Technology 14(1): 6171. Google Scholar, Crossref
Danna, A, Gandy, OH (2002) All that glitters is not gold: Digging beneath the surface of data mining. Journal of Business Ethics 40(4): 373386. Google Scholar, Crossref
Datta A, Sen S and Zick Y (2016) Algorithmic transparency via quantitative input influence. In: Proceedings of 37th IEEE symposium on security and privacy, San Jose, USA. Available at: http://www.ieee-security.org/TC/SP2016/papers/0824a598.pdf (accessed 30 June 2016). Google Scholar
Davis, M, Kumiega, A, Van Vliet, B (2013) Ethics, finance, and automation: A preliminary survey of problems in high frequency trading. Science and Engineering Ethics 19(3): 851874. Google Scholar, Crossref, Medline
de Vries, K (2010) Identity, profiling algorithms and a world of ambient intelligence. Ethics and Information Technology 12(1): 7185. Google Scholar, Crossref
Diakopoulos, N (2015) Algorithmic accountability: Journalistic investigation of computational power structures. Digital Journalism 3(3): 398415. Google Scholar, Crossref
Diamond, GA, Pollock, BH, Work, JW (1987) Clinician decisions and computers. Journal of the American College of Cardiology 9(6): 13851396. Google Scholar, Crossref, Medline
Domingos, P (2012) A few useful things to know about machine learning. Communications of the ACM 55(10): 7887. Google Scholar, Crossref
Dwork C, Hardt M, Pitassi T, et al. (2011) Fairness through awareness. arXiv:1104.3913 [cs]. Available at: http://arxiv.org/abs/1104.3913 (accessed 15 February 2016). Google Scholar
Elish MC (2016) Moral crumple zones: Cautionary tales in human–robot interaction (WeRobot 2016). SSRN. Available at: http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2757236 (accessed 30 June 2016). Google Scholar
European Commission (2012) Regulation of the European Parliament and of the Council on the Protection of Individuals with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation), Brussels: European CommissionAvailable at: http://ec.europa.eu/justice/data-protection/document/review2012/com_2012_11_en.pdf (accessed 2 April 2013). Google Scholar
Feynman R (1974) ‘Cargo cult science’ – by Richard Feynman. Available at: http://neurotheory.columbia.edu/∼ken/cargo_cult.html (accessed 3 September 2015). Google Scholar
Floridi, L (2008) The method of levels of abstraction. Minds and Machines 18(3): 303329. Google Scholar, Crossref
Floridi, L (2011) The informational nature of personal identity. Minds and Machines 21(4): 549566. Google Scholar, Crossref
Floridi, L (2012) Big data and their epistemological challenge. Philosophy & Technology 25(4): 435437. Google Scholar, Crossref
Floridi, L (2014) The Fourth Revolution: How the Infosphere is Reshaping Human Reality, Oxford: OUP. Google Scholar
Floridi L and Sanders JW (2004a) On the morality of artificial agents. Minds and Machines 14(3). Available at: http://dl.acm.org/citation.cfm?id=1011949.1011964 (accessed 1 August 2004). Google Scholar
Floridi L and Sanders JW (2004b) On the morality of artificial agents. Minds and Machines 14(3). Available at: http://dl.acm.org/citation.cfm?id=1011949.1011964 (accessed 1 August 2004). Google Scholar
Floridi, L, Fresco, N, Primiero, G (2014) On malfunctioning software. Synthese 192(4): 11991220. Google Scholar, Crossref
Friedman, B, Nissenbaum, H (1996) Bias in computer systems. ACM Transactions on Information Systems (TOIS) 14(3): 330347. Google Scholar, Crossref
Fule P and Roddick JF (2004) Detecting privacy and ethical sensitivity in data mining results. In: Proceedings of the 27th Australasian conference on computer science – Volume 26, Dunedin, New Zealand, Australian Computer Society, Inc., pp. 159–166. Available at: http://dl.acm.org/citation.cfm?id=979942 (accessed 24 August 2015). Google Scholar
Gadamer, HG (2004) Truth and Method, London: Continuum International Publishing Group. Google Scholar
Glenn, T, Monteith, S (2014) New measures of mental state and behavior based on data collected from sensors, smartphones, and the internet. Current Psychiatry Reports 16(12): 110. Google Scholar, Crossref
Goldman, E (2006) Search engine bias and the demise of search engine utopianism. Yale Journal of Law & Technology 8: 188200. . Google Scholar
Granka, LA (2010) The politics of search: A decade retrospective. The Information Society 26(5): 364374. Google Scholar, Crossref
Grindrod, P (2014) Mathematical Underpinnings of Analytics: Theory and Applications, Oxford: OUP. Google Scholar, Crossref
Grodzinsky, FS, Miller, KW, Wolf, MJ (2010) Developing artificial agents worthy of trust: ‘Would you buy a used car from this artificial agent?’. Ethics and Information Technology 13(1): 1727. Google Scholar, Crossref
Hacking, I (2006) The Emergence of Probability: A Philosophical Study of Early Ideas about Probability, Induction and Statistical Inference, Cambridge: Cambridge University Press. Google Scholar, Crossref
Hajian, S, Domingo-Ferrer, J (2013) A methodology for direct and indirect discrimination prevention in data mining. IEEE Transactions on Knowledge and Data Engineering 25(7): 14451459. Google Scholar, Crossref
Hajian S, Monreale A, Pedreschi D, et al. (2012) Injecting discrimination and privacy awareness into pattern discovery. In: Data mining workshops (ICDMW), 2012 IEEE 12th international conference on, Brussels, Belgium, IEEE, pp. 360–369. Available at: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6406463 (accessed 3 November 2015). Google Scholar
Hildebrandt, M (2008) Defining profiling: A new type of knowledge? In: Hildebrandt, M, Gutwirth, S (eds) Profiling the European Citizen, the Netherlands: Springer, pp. 1745. Available at: http://link.springer.com/chapter/10.1007/978-1-4020-6914-7_2 (accessed 14 May 2015). Google Scholar, Crossref
Hildebrandt, M (2011) Who needs stories if you can get the data? ISPs in the era of big number crunching. Philosophy & Technology 24(4): 371390. Google Scholar, Crossref
Hildebrandt, M, Koops, B-J (2010) The challenges of ambient law and legal protection in the profiling era. The Modern Law Review 73(3): 428460. Google Scholar, Crossref
Hill, RK (2015) What an algorithm is. Philosophy & Technology 29(1): 3559. Google Scholar, Crossref
Illari, PM, Russo, F (2014) Causality: Philosophical Theory Meets Scientific Practice, Oxford: Oxford University Press. Google Scholar
Introna, LD, Nissenbaum, H (2000) Shaping the Web: Why the politics of search engines matters. The Information Society 16(3): 169185. Google Scholar, Crossref
Ioannidis, JPA (2005) Why most published research findings are false. PLoS Medicine 2(8): e124. Google Scholar, Crossref, Medline
James, G, Witten, D, Hastie, T (2013) An Introduction to Statistical Learning Vol. 6, New York: Springer. Google Scholar, Crossref
Johnson, JA (2006) Technology and pragmatism: From value neutrality to value criticality, SSRN Scholarly Paper, Rochester, NY: Social Science Research NetworkAvailable at: http://papers.ssrn.com/abstract=2154654 (accessed 24 August 2015). Google Scholar
Johnson, JA (2013) Ethics of data mining and predictive analytics in higher education, SSRN Scholarly Paper, Rochester, NY: Social Science Research NetworkAvailable at: http://papers.ssrn.com/abstract=2156058 (accessed 22 July 2015). Google Scholar
Kamiran F and Calders T (2010) Classification with no discrimination by preferential sampling. In: Proceedings of the 19th machine learning conf. Belgium and the Netherlands, Leuven, Belgium. Available at: http://wwwis.win.tue.nl/∼tcalders/pubs/benelearn2010 (accessed 24 August 2015). Google Scholar
Kamishima, T, Akaho, S, Asoh, H (2012) Considerations on fairness-aware data mining. In: IEEE 12th International Conference on Data Mining Workshops, Brussels, Belgium. 378385. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6406465 (accessed 3 November 2015). Google Scholar, Crossref
Kim, B, Patel, K, Rostamizadeh, A (2015) Scalable and interpretable data representation for high-dimensional, complex data. AAAI. 17631769. Google Scholar
Kim, H, Giacomin, J, Macredie, R (2014) A qualitative study of stakeholders' perspectives on the social network service environment. International Journal of Human–Computer Interaction 30(12): 965976. Google Scholar, Crossref
Kitchin, R (2016) Thinking critically about and researching algorithms. Information, Communication & Society. 20(1): 1429. Google Scholar
Kornblith, H (2001) Epistemology: Internalism and Externalism, Oxford: Blackwell. Google Scholar
Kraemer, F, van Overveld, K, Peterson, M (2011) Is there an ethics of algorithms?. Ethics and Information Technology 13(3): 251260. Google Scholar, Crossref
Lazer, D, Kennedy, R, King, G (2014) The parable of Google flu: Traps in big data analysis. Science 343(6176): 12031205. Google Scholar, Crossref, Medline
Leese, M (2014) The new profiling: Algorithms, black boxes, and the failure of anti-discriminatory safeguards in the European Union. Security Dialogue 45(5): 494511. Google Scholar, Link
Levenson, JL, Pettrey, L (1994) Controversial decisions regarding treatment and DNR: An algorithmic Guide for the Uncertain in Decision-Making Ethics (GUIDE). American Journal of Critical Care: An Official Publication, American Association of Critical-Care Nurses 3(2): 8791. Google Scholar, Medline
Lewis, SC, Westlund, O (2015) Big data and journalism. Digital Journalism 3(3): 447466. Google Scholar, Crossref
Lomborg, S, Bechmann, A (2014) Using APIs for data collection on social media. Information Society 30(4): 256265. Google Scholar, Crossref
Lou, Y, Caruana, R, Gehrke, J (2013) Accurate intelligible models with pairwise interactions. In: Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining, Chicago, USA, ACM, pp. 623631. Google Scholar, Crossref
Louch MO, Mainier MJ and Frketich DD (2010) An analysis of the ethics of data warehousing in the context of social networking applications and adolescents. In: 2010 ISECON Proceedings, Vol. 27 no. 1392, Nashville, USA. Google Scholar
Lupton, D (2014) The commodification of patient opinion: The digital patient experience economy in the age of big data. Sociology of Health & Illness 36(6): 856869. Google Scholar, Crossref, Medline
MacIntyre, A (2007) After Virtue: A Study in Moral Theory, 3rd ed. London: Gerald Duckworth & Co Ltd. Revised edition. Google Scholar
Macnish, K (2012) Unblinking eyes: The ethics of automating surveillance. Ethics and Information Technology 14(2): 151167. Google Scholar, Crossref
Mahajan, RL, Reed, J, Ramakrishnan, N (2012) Cultivating emerging and black swan technologies. ASME 2012 International Mechanical Engineering Congress and Exposition, Houston, USA. 549557. . Google Scholar
Markowetz, A, Błaszkiewicz, K, Montag, C (2014) Psycho-informatics: Big data shaping modern psychometrics. Medical Hypotheses 82(4): 405411. Google Scholar, Crossref, Medline
Matthias, A (2004) The responsibility gap: Ascribing responsibility for the actions of learning automata. Ethics and Information Technology 6(3): 175183. Google Scholar, Crossref
Mayer-Schönberger, V, Cukier, K (2013) Big Data: A Revolution that will Transform How We Live, Work and Think, London: John Murray. Google Scholar
Mazoué, JG (1990) Diagnosis without doctors. Journal of Medicine and Philosophy 15(6): 559579. Google Scholar, Crossref, Medline
Miller, B, Record, I (2013) Justified belief in a digital age: On the epistemic implications of secret Internet technologies. Episteme 10(2): 117134. Google Scholar, Crossref
Mittelstadt, BD, Floridi, L (2016) The ethics of big data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics 22(2): 303341. Google Scholar, Crossref, Medline
Mohler, GO, Short, MB, Brantingham, PJ (2011) Self-exciting point process modeling of crime. Journal of the American Statistical Association 106(493): 100108. Google Scholar, Crossref
Moor JH (2006) The nature, importance, and difficulty of machine ethics. Intelligent Systems, IEEE 21(4). Available at: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1667948 (accessed 1 January 2006). Google Scholar
Morek, R (2006) Regulatory framework for online dispute resolution: A critical view. The University of Toledo Law Review 38: 163. Google Scholar
Naik, G, Bhide, SS (2014) Will the future of knowledge work automation transform personalized medicine?. Applied & Translational Genomics, Inaugural Issue 3(3): 5053. Google Scholar, Crossref, Medline
Nakamura, L (2013) Cybertypes: Race, Ethnicity, and Identity on the Internet, New York: Routledge. Google Scholar
Newell, S, Marabelli, M (2015) Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of ‘datification’. The Journal of Strategic Information Systems 24(1): 314. Google Scholar, Crossref
Neyland, D (2016) Bearing accountable witness to the ethical algorithmic system. Science, Technology & Human Values 41(1): 5076. Google Scholar, Link
Orseau L and Armstrong S (2016) Safely interruptible agents. Available at: http://intelligence.org/files/Interruptibility.pdf (accessed 12 September 2016). Google Scholar
Pariser, E (2011) The Filter Bubble: What the Internet is Hiding from You, London: Viking. Google Scholar
Pasquale, F (2015) The Black Box Society: The Secret Algorithms that Control Money and Information, Cambridge: Harvard University Press. Google Scholar, Crossref
Patterson, ME, Williams, DR (2002) Collecting and Analyzing Qualitative Data: Hermeneutic Principles, Methods and Case Examples. Advances in tourism Application Series, Champaign, IL, Champaign, USA: Sagamore Publishing, IncAvailable at: http://www.treesearch.fs.fed.us/pubs/29421 (accessed 7 November 2012). Google Scholar
Portmess, L, Tower, S (2014) Data barns, ambient intelligence and cloud computing: The tacit epistemology and linguistic representation of Big Data. Ethics and Information Technology 17(1): 19. Google Scholar, Crossref
Raymond, A (2014) The dilemma of private justice systems: Big Data sources, the cloud and predictive analytics. Northwestern Journal of International Law & Business, Forthcoming. Available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2469291 (accessed 22 July 2015). Google Scholar
Romei, A, Ruggieri, S (2014) A multidisciplinary survey on discrimination analysis. The Knowledge Engineering Review 29(5): 582638. Google Scholar, Crossref
Rubel, A, Jones, KML (2014) Student privacy in learning analytics: An information ethics perspective. SSRN Scholarly Paper, Rochester, NY: Social Science Research NetworkAvailable at: http://papers.ssrn.com/abstract=2533704 (accessed 22 July 2015). Google Scholar
Sametinger, J (1997) Software Engineering with Reusable Components, Berlin: Springer Science & Business Media. Google Scholar, Crossref
Sandvig, C, Hamilton, K, Karahalios, K (2014) Auditing algorithms: Research methods for detecting discrimination on internet platforms. Data and Discrimination: Converting Critical Concerns into Productive Inquiry. Available at: http://social.cs.uiuc.edu/papers/pdfs/ICA2014-Sandvig.pdf (accessed 13 February 2016). Google Scholar
Schermer, BW (2011) The limits of privacy in automated profiling and data mining. Computer Law & Security Review 27(1): 4552. Google Scholar, Crossref
Shackelford, SJ, Raymond, AH (2014) Building the virtual courthouse: Ethical considerations for design, implementation, and regulation in the world of Odr. Wisconsin Law Review. 3, 615657. Google Scholar
Shannon, CE, Weaver, W (1998) The Mathematical Theory of Communication, Urbana: University of Illinois Press. Google Scholar
Simon, J (2010) The entanglement of trust and knowledge on the web. Ethics and Information Technology 12(4): 343355. Google Scholar, Crossref
Simon, J (2015) Distributed epistemic responsibility in a hyperconnected era. In: Floridi, L (ed.) The Onlife Manifesto, Springer International Publishing, pp. 145159. Available at: http://link.springer.com/chapter/10.1007/978-3-319-04093-6_17 (accessed 17 June 2016). Google Scholar, Crossref
Stark, M, Fins, JJ (2013) Engineering medical decisions. Cambridge Quarterly of Healthcare Ethics 22(4): 373381. Google Scholar, Crossref, Medline
Sullins JP (2006) When is a robot a moral agent? Available at: http://scholarworks.calstate.edu/xmlui/bitstream/handle/10211.1/427/Sullins%20Robots-Moral%20Agents.pdf?sequence=1 (accessed 20 August 2015). Google Scholar
Sweeney, L (2013) Discrimination in online ad delivery. Queue 11(3): 10:1010:29. Google Scholar, Crossref
Swiatek MS (2012) Intending to err: The ethical challenge of lethal, autonomous systems. Ethics and Information Technology14(4). Available at: https://www.scopus.com/inward/record.url?eid=2-s2.0-84870680328&partnerID=40&md5=018033cfd83c46292370e160d4938ffa (accessed 1 January 2012). Google Scholar
Taddeo, M (2010) Modelling trust in artificial agents, a first step toward the analysis of e-trust. Minds and Machines 20(2): 243257. Google Scholar, Crossref
Taddeo, M, Floridi, L (2015) The debate on the moral responsibilities of online service providers. Science and Engineering Ethics. 129. Google Scholar
Taylor, L, Floridi, L, van der Sloot, B (2017) Group Privacy: New Challenges of Data Technologies, 1st ed. New York, NY: Springer. Google Scholar, Crossref
Tene O and Polonetsky J (2013a) Big data for all: Privacy and user control in the age of analytics. Available at: http://heinonlinebackup.com/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/nwteintp11&section=20 (accessed 2 October 2014). Google Scholar
Tene O and Polonetsky J (2013b) Big Data for all: Privacy and user control in the age of analytics. Available at: http://heinonlinebackup.com/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/nwteintp11&section=20 (accessed 2 October 2014). Google Scholar
Tonkens, R (2012) Out of character: On the creation of virtuous machines. Ethics and Information Technology 14(2): 137149. Google Scholar, Crossref
Tufekci, Z (2015) Algorithmic harms beyond Facebook and Google: Emergent challenges of computational agency. Journal on Telecommunications and High Technology Law 13: 203. Google Scholar
Turilli, M (2007) Ethical protocols design. Ethics and Information Technology 9(1): 4962. Google Scholar, Crossref
Turilli, M, Floridi, L (2009) The ethics of information transparency. Ethics and Information Technology 11(2): 105112. Google Scholar, Crossref
Turner, R (2016) The philosophy of computer science. Spring 2016. In: Zalta, EN (ed.) The Stanford Encyclopedia of Philosophy. Available at: http://plato.stanford.edu/archives/spr2016/entries/computer-science/ (accessed 21 June 2016). Google Scholar
Tutt, A (2016) An FDA for algorithms. SSRN Scholarly Paper, Rochester, NY: Social Science Research NetworkAvailable at: http://papers.ssrn.com/abstract=2747994 (accessed 13 April 2016). Google Scholar
Valiant, LG (1984) A theory of the learnable. Communications of the Journal of the ACM 27: 11341142. Google Scholar, Crossref
van den Hoven, J, Rooksby, E (2008) Distributive justice and the value of information: A (broadly) Rawlsian approach. In: van den Hoven, J, Weckert, J (eds) Information Technology and Moral Philosophy, Cambridge: Cambridge University Press, pp. 376396. Google Scholar
Van Otterlo, M (2013) A machine learning view on profiling. In: Hildebrandt, M, de Vries, K (eds) Privacy, Due Process and the Computational Turn-Philosophers of Law Meet Philosophers of Technology, Abingdon: Routledge, pp. 4164. Google Scholar
Van Wel, L, Royakkers, L (2004) Ethical issues in web data mining. Ethics and Information Technology 6(2): 129140. Google Scholar, Crossref
Vasilevsky, NA, Brush, MH, Paddock, H (2013) On the reproducibility of science: Unique identification of research resources in the biomedical literature. PeerJ 1: e148. Google Scholar, Crossref
Vellido, A, Martín-Guerrero, JD, Lisboa, PJ (2012) Making machine learning models interpretable. In: ESANN 2012 proceedings, Bruges, Belgium, pp. 163172. Google Scholar
Wiegel, V, van den Berg, J (2009) Combining moral theory, modal logic and mas to create well-behaving artificial agents. International Journal of Social Robotics 1(3): 233242. Google Scholar, Crossref
Wiener, N (1988) The Human Use of Human Beings: Cybernetics and Society, Da Capo Press. Google Scholar
Wiltshire, TJ (2015) A prospective framework for the design of ideal artificial moral agents: Insights from the science of heroism in humans. Minds and Machines 25(1): 5771. Google Scholar, Crossref
Zarsky T (2013) Transparent predictions. University of Illinois Law Review 2013(4). Available at: http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2324240 (accessed 17 June 2016). Google Scholar
Zarsky, T (2016) The trouble with algorithmic decisions an analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology & Human Values 41(1): 118132. Google Scholar, Link