Philosophy & Technology

, Volume 32, Issue 1, pp 111–134 | Cite as

Trust and Justice in Big Data Analytics: Bringing the Philosophical Literature on Trust to Bear on the Ethics of Consent

  • J. Patrick WoolleyEmail author
Research Article


Much bioethical literature and policy guidances for big data analytics in biomedical research emphasize the importance of trust. It is essential that potential participants trust so they will allow their data to be used to further research. However, comparatively, little guidance is offered as to what trustworthy oversight mechanisms are, or how policy should support them, as data are collected, shared, and used. Generally, “trust” is not characterized well enough, or meaningfully enough, for the term to be systematically applied in policy development. Yet points made in the philosophical literature on trust can help. They allow us, not only to better distinguish the different ways the term “trust” may be interpreted, but also to better determine how different approaches to trust can align with policy and governance—in what ways they may relate to key bioethical concepts and related laws, and in what ways they can help to balance individual and group interests in data sharing. This article draws from the philosophical literature on trust to identify a relationship among consent, trust, and justice. Specifically, parallels are drawn between “character-trustworthiness” and “natural justice,” a set of widely held legal safeguards intended to ensure decision-makers follow a pattern of procedural fairness which protects the rights of the individual and thereby maintains public confidence in the decision-making process. Relevance to traditional bioethical principles, established laws, and consent procedures are addressed throughout. In conclusion, policy actions are suggested.


Big data Biomedicine Consent ELSI Ethics Human rights Information technologies Law Policy Regulation Trust UNESCO 



This work was made possible by a Fellowship at Harris Manchester College, University of Oxford and the Center for Health, Law, and Emerging Technologies (HeLEX), Nuffield Department of Population Health, University of Oxford. My thanks go to Tom Simpson for sharing his unpublished essay discussed in this article, and to the reviewers of this article whose feedback helped to improve it substantially.

Compliance with Ethical Standards

Conflict of Interest

The author is a member of the Global Alliance for Genomics and Health and has helped produce some of the policy documents and ICT tools highlighted in the article.


  1. Aicardi, C., Del Savio, l., Dove, E., Lucivero, Niccolò Tempini, F., & Prainsack, B. (2016). Emerging ethical issues regarding digital health data. On the World Medical Association Draft Declaration on Ethical Considerations Regarding Health Databases and Biobanks. Croatian Medical Journal, 57(2), 207.CrossRefGoogle Scholar
  2. Ananny, M. (2016). Toward an ethics of algorithms: convening, observation, probability, and timeliness. Science, Technology, and Human Values, 41(1), 93–117.CrossRefGoogle Scholar
  3. Angrist, M. (2009). Eyes wide open: the personal genome project, citizen science and veracity in informed consent. Personalized Medicine, 6, 691.CrossRefGoogle Scholar
  4. Baier, A. (1995). Moral prejudices: essays on ethics. Cambridge: Harvard University Press.Google Scholar
  5. Beauchamp, T. L., & Childress, J. F. (2001). Principles of biomedical ethics. Oxford University Press.Google Scholar
  6. Carter, P., Laurie, G. T., Dixon-Woods, M. (2015). The social licence for research: why ran into trouble. Journal of Medical Ethics.
  7. Coakley, M., Leerkes, M., Barnett, J., et al. (2013). Unlocking the power of big data at the national institutes of health. Big Data, 1(3), 183–186.CrossRefGoogle Scholar
  8. Coleman, J. S. (1990). Foundations of social theory. Cambridge: Belknap Press.Google Scholar
  9. Crawford, K. (2016). Can an algorithm be agonistic? Ten scenes from life in calculated publics. Science, Technology, and Human Values, 41(1), 77–92.CrossRefGoogle Scholar
  10. de Vries, J., Williams, T., Bojang, K., Kwiatkowski, D., Fitzpatrick, R., & Parker, M. (2014). Knowing who to trust: exploring the role of ‘ethical metadata’ in mediating risk of harm in collaborative genomics research in Africa. BMC Medical Ethics, 15(1), 62.CrossRefGoogle Scholar
  11. Dove, E. S., Knoppers, B. M., & Ma'n, H. Z. (2014). Towards an ethics safe harbor for global biomedical research. Journal of Law and the Biosciences, 1(1), 3–51.CrossRefGoogle Scholar
  12. Dyke, S., Philippakis, A., Rambla De Argila, J., Paltoo, D., Luetkemeier, et al. (2016). Consent codes: upholding standard data use conditions. PLoS Genetics, 12(1), e1005772.CrossRefGoogle Scholar
  13. Erlich, Y., Williams, J. B., Glazer, D., Yocum, K., Farahany, N., Olson, M., Narayanan, A., Stein, L. D., Witkowski, J. A., & Kain, R. C. (2014). Redefining genomic privacy: trust and empowerment. PLoS Biology, 12(11), e1001983.CrossRefGoogle Scholar
  14. Faulkner, P. (2014). The practical rationality of trust. Synthese, 191(9), 1975–1989.CrossRefGoogle Scholar
  15. Federal Register (2017). Revisions to US Federal Policy for the Protection of Human Subjects, originally promulgated as a Common Rule in 1991.
  16. Global Alliance for Genomics & Health (GA4GH) and International Rare Disease Research Consortium (IRDiRC) (2016). Automatable Discovery and Access Matrix (“ADA-M”) v1.0. Guidance document.
  17. Global Alliance for Genomics and Health (2017). Global Ethics Review Recognition Policy. Policy Document.
  18. Green, E. D., Guyer, M. S., & National Human Genome Research Institute. (2011). Charting a course for genomic medicine from base pairs to bedside. Nature, 470, 204–213.CrossRefGoogle Scholar
  19. Hardin, R. (2002). Trust and trustworthiness. Russell Sage Foundation.Google Scholar
  20. Holton, R. (1994). Deciding to trust, coming to believe. Australasian Journal of Philosophy, 72(1), 63–76.CrossRefGoogle Scholar
  21. Ioannidis, J. P. A. (2013). Informed consent, big data, and the oxymoron of research that is not research. The American Journal of Bioethics, 13(4), 40–42.CrossRefGoogle Scholar
  22. Juengst, E., McGowan, M., Fishman, J., & Settersten, R. (2016). From “personalized” to “precision” medicine: the ethical and social implications of rhetorical reform in genomic medicine. Hastings Center Report, 46(5), 21–33.CrossRefGoogle Scholar
  23. Karlsen, J. R., Solbakk, J. H., & Holm, S. (2011). Ethical endgames: broad consent for narrow interests; open consent for closed minds. Cambridge Quarterly of Healthcare Ethics, 20(4), 572–583.CrossRefGoogle Scholar
  24. Kaye, J., Whitley, E. A., Lund, D., Morrison, M., Teare, H., & Melham, K. (2015). Dynamic consent: a patient interface for twenty-first century research networks. European Journal of Human Genetics, 23(2), 141–146.CrossRefGoogle Scholar
  25. Knoppers, B., Harris, J., Budin-Ljøsne, I., & Dove, E. (2014). A human rights approach to an international code of conduct for genomic and clinical data sharing. Human Genetics, 133(7), 895–903.CrossRefGoogle Scholar
  26. Lunshof, J. E., Chadwick, R., Vorhaus, D. B., & Church, G. M. (2008). From genetic privacy to open consent. Nature Reviews Genetics, 9(5), 406–411.CrossRefGoogle Scholar
  27. Manyika J, Chui M, Farrell D, et al. (2013). Open data: unlocking innovation and performance with liquid information. McKinsey Global Institute. 21.Google Scholar
  28. Metcalf, J. (2017). Letter on Proposed Changes to the Common Rule. Council for Big Data, Ethics, and Society. Accessed July 17, 2017. Al-Rodhan, Nayef. The Social Contract 2.0: Big Data and the Need to Guarantee Privacy and Civil Liberties. Harvard International Review (2014).
  29. Mills, P. (2015). Comments on WMA Declaration on Ethical Considerations regarding Health Databases and Biobanks (Draft 2015–03-18). Nuffield Council on Bioethics.
  30. Mittelstadt, B., and Floridi, L. (2016). The ethics of big data: current and foreseeable issues in biomedical contexts. In B. Mittelstadt and L. Floridi (Eds.), The ethics of biomedical big data. Volume 29 of the series Law, Governance and Technology Series (pp. 455–480). Springer International Publishing.Google Scholar
  31. National Institute of Health, ‘About the All of Us Research Program’ (2017).
  32. Nature Editorial. (2014). Power to the people: NHS medical records policy. Nature, 50(5), 261.Google Scholar
  33. Neyland, D. (2016). Bearing account-able witness to the ethical algorithmic system. Science, Technology, and Human Values, 41(1), 50–76.CrossRefGoogle Scholar
  34. Nickel, P. J. (2007). Trust and obligation-ascription. Ethical Theory and Moral Practice, 10(3), 309–319.CrossRefGoogle Scholar
  35. O'Neill, O. (2002). Autonomy and trust in bioethics. Cambridge: Cambridge University Press.Google Scholar
  36. O'Neill, O. (2003). Some limits of informed consent. Journal of Medical Ethics, 29(1), 4–7.CrossRefGoogle Scholar
  37. Prainsack, B., & Buyx, A. (2011). Solidarity: reflections on an emerging concept in bioethics. London: Nuffield Council on Bioethics.Google Scholar
  38. Prainsack, B., & Buyx, A. (2012). Understanding solidarity (with a little help from your friends) response to Dawson and Verweij. Public Health Ethics., 5(2), 206–210.CrossRefGoogle Scholar
  39. Prainsack, B., & Buyx, A. (2013). A solidarity-based approach to the governance of research biobanks. Medical Law Review, 1(1), 71–91.CrossRefGoogle Scholar
  40. Prainsack, B., & Buyx, A. (2016). Solidarity in Biomedicine and Beyond (Vol. 33). Cambridge University Press.Google Scholar
  41. Richards, M. R., Anderson, S., Hinde, J., Kaye, J., Lucassen, A., Matthews, P., Parker, M., et al. (2015). The collection, linking and use of data in biomedical research and health care: ethical issues. London: Nuffield Council on Bioethics Scholar
  42. Sankar, P.L., and Parker, L.S. (2016). The precision medicine initiative’s all of us research program: an agenda for research on its ethical, legal, and social issues. Genetics in Medicine 19, 743–750.
  43. Shabani, M., & Borry, P. (2016). “You want the right amount of oversight”: interviews with data access committee members and experts on genomic data access. Genetics in Medicine, 18(9), 892–897.CrossRefGoogle Scholar
  44. Sheehan, M. (2011a). Broad consent is informed consent. BMJ, 343, d6900.CrossRefGoogle Scholar
  45. Sheehan, M. (2011b). Can broad consent be informed consent? Public Health Ethics, 4, 226–235 phr020.CrossRefGoogle Scholar
  46. Shrack, T. D., Ruff, A. M. and Johnson, M. T. (2015). Proposed revisions to the common rule receive harsh criticism from industry stakeholders.
  47. Simpson, T. (2012). What Is Trust?. Pacific Philosophical Quarterly, 93(4), 550–569.Google Scholar
  48. Simpson, T. (2013). Trustworthiness and moral character. Ethical Theory and Moral Practice, 16(3), 543–557.CrossRefGoogle Scholar
  49. Sterckx, S., Cockbain, J., Howard, H., Huys, I., & Borry, P. (2013). “Trust is not something you can reclaim easily”: patenting in the field of direct-to-consumer genetic testing. Genetics in Medicine, 15(5), 382–387.CrossRefGoogle Scholar
  50. Sterckx, S., Rakic, V., Cockbain, J., & Borry, P. (2016). “You hoped we would sleep walk into accepting the collection of our data”: controversies surrounding the UK scheme and their wider relevance for biomedical research. Medicine, Health Care and Philosophy., 19(2), 177–190. Scholar
  51. UK’s Department for Business Innovation and Skills (2011). The Strategy for UK Life Sciences.
  52. UNESCO (2003). International Declaration on and Human Genetic Data.
  53. UNESCO (2005). Universal Declaration on Bioethics and Human Rights.
  54. United Nations (1948). International Declaration of Human Rights.
  55. Vayena, E., Brownsword, R., Edwards, S. J., Greshake, B., Kahn, J. P., Ladher, N, Montgomery, J. et al. (2015). Research led by participants: a new social contract for a new kind of research. Journal of Medical Ethics. medethics-2015.Google Scholar
  56. Wolff, J. (2010). Five types of risky situation. Law, Innovation and Technology, 2(2), 151–163.CrossRefGoogle Scholar
  57. Woolley, J. P. (2016). How data are transforming the landscape of biomedical ethics: the need for ELSI metadata on consent. In B. Mittelstadt and L. Floridi (Eds.), The ethics of biomedical big data. Volume 29 of the series Law, Governance and Technology Series (pp. 171–197). Springer International Publishing.Google Scholar
  58. Woolley, J. P., McGowan, M., Teare, H., Coathup, V., Fishman, J., Settersten, R., et al. (2016). Citizen science or scientific citizenship? Disentangling the uses of public engagement rhetoric in national research initiatives. BMC Medical Ethics, 17(1), 1.CrossRefGoogle Scholar
  59. World Medical Association (2016). Declaration of Taipei on Ethical Considerations regarding Health Databases and Biobanks.
  60. 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, and Human Values, 41(1), 118–132.CrossRefGoogle Scholar
  61. Ziewitz, M. (2016). Governing algorithms: myth, mess, and methods. Science, Technology, and Human Values, 41(1), 3–16.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Center for Health, Law, and Emerging Technologies (HeLEX), Nuffield Department of Population HealthUniversity of OxfordOxfordUK

Personalised recommendations