Beyond Informed Consent—Investigating Ethical Justifications for Disclosing, Donating or Sharing Personal Data in Research

  • Markus ChristenEmail author
  • Josep Domingo-Ferrer
  • Dominik Herrmann
  • Jeroen van den Hoven
Part of the Philosophical Studies Series book series (PSSP, volume 128)


In the last two decades, we have experienced a tremendous growth of the digital infrastructure, leading to an emerging web ecosystem that involves a variety of new types of services. A characteristic element of this web ecosystem is the massive increase of the amount, availability and interpretability of digitalized information—a development for which the buzzword “big data” has been coined. For research, this offers opportunities that just 20 years ago were believed to be impossible. Researchers now can access large participant pools directly using services like Amazon Mechanical Turk, they can collaborate with companies like Facebook to analyze their massive data sets, they can create own research infrastructures by, e.g., providing data-collecting Apps for smartphones, or they can enter new types of collaborations with citizens that donate personal data. Traditional research ethics with its focus of informed consent is challenged by such developments: How can informed consent be given when big data research seeks for unknown patterns? How can people control their data? How can unintended effects (e.g., discrimination) be prevented when a person donates personal data? In this contribution, we will discuss the ethical justification for big data research and we will argue that a focus on informed consent is insufficient for providing its moral basis. We propose that the ethical issues cluster along three core values—autonomy, fairness and responsibility—that need to be addressed. Finally, we outline how a possible research infrastructure could look like that would allow for ethical big data research.


Research ethics Informed consent Data analytics Contextual integrity Discrimination Autonomy Fairness Responsibility 


  1. Allan, R. (2009). Virtual research environments: From portals to science gateways. Oxford: Chandos Publishing.CrossRefGoogle Scholar
  2. Anthes, G. (2015). Data brokers are watching you. Communications of the ACM, 58(1), 28–30.CrossRefGoogle Scholar
  3. Berendt, B., & Preibusch, S. (2014). Better decision support through exploratory discrimination-aware data mining: Foundations and empirical evidence. Artificial Intelligence and Law, 22(2), 175–209.CrossRefGoogle Scholar
  4. Carusi, A., & Reimer, T. (2010). Virtual research environment—collaborative landscape sudy. A JISC funded project. Available at: (Last Access: December 9 2016).
  5. Christen, M., Domingo-Ferrer, J., Draganski, B., Spranger, T., & Walter, H. (2016). On the compatibility of big data driven research and informed consent based on traditional disease categories—the example of the Human Brain Project. In L. Floridi & B. Mittelstadt (Eds.) Ethics of biomedical big data (pp. 199–218). Cham: Springer.Google Scholar
  6. Custers, B., Calders, T., Schermer, B., & Zarsky, T. (Eds.). (2013). Discrimination and privacy in the information society (Vol. 3) of studies in applied philosophy, epistemology and rational ethics. Berlin/London: Springer.Google Scholar
  7. Domingo-Ferrer, J. (2011). Coprivacy: An introduction to the theory and applications of co-operative privacy. SORT-Statistics and Operations Research Transactions, 35, 25–40.Google Scholar
  8. Domingo-Ferrer, J., & Muralidhar, K. (2016). New directions in anonymization: Permutation paradigm, verifiability by subjects and intruders, transparency to users. Information Sciences, 337–338, 11–24.CrossRefGoogle Scholar
  9. Domingo-Ferrer, J., Sánchez, D., & Soria-Comas, J. (2016). Co-utility: Self-enforcing collaborative protocols with mutual help. Progress in Artificial Intelligence, 5(2), 105–110.CrossRefGoogle Scholar
  10. Druschel, P., Backes, M., & Tirtea, R. (2012). The right to be forgotten—Between expectations and practice. ENI SA. Available at: Last Access: December 9 2016.
  11. Duşa, A., Oellers, C., & Wolff, S. (2014). A Common agenda for the European research infrastructures in the social sciences and humanities. In A. Duşa, D. Nelle, G. Stock, & G. G. Wagner (Eds.), Facing the future: European research infrastructures for the humanities and social sciences (pp. 225–234). Berlin: SCIVERO Verlag.Google Scholar
  12. EDPS. (2013). European sata protection supervisor, see: Last Access: December 9 2016.
  13. European Data Protection Regulation. (2012). The approved version is available at the following website: Last Access: December 9 2016.
  14. Farago, P. (2014). Understanding how research infrastructures shape the social sciences: impact, challenges, and outlook. In A. Duşa, D. Nelle, G. Stock, & G. G. Wagner (Eds.), Facing the Future: European Research Infrastructures for the Humanities and Social Sciences (pp. 21–34). Berlin: SCIVERO Verlag.Google Scholar
  15. 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), 1445–1459.CrossRefGoogle Scholar
  16. Hajian, S., Domingo-Ferrer, J., & Farràs, O. (2014). Generalization-based privacy preservation and discrimination prevention in data publishing and mining. Data Mining and Knowledge Discovery, 28, 1158–1188.CrossRefGoogle Scholar
  17. Hoofnagle, C. J., Soltani, A., Good, N., Wambach, D. J., & Ayenson, M. D. (2012). Behavioral advertising: The offer you cannot refuse. Harvard Law & Policy Review, 6, 273–296.Google Scholar
  18. Jain, P., Kumaraguru, P., & Joshi, A. (2013). @i seek ‘’: identifying users across multiple online social networks. WWW (Companion Volume): 1259–1268. Available at: Last Access: December 9 2016.
  19. Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802–5805.CrossRefGoogle Scholar
  20. Liu, K., & Terzi, E. (2010). A framework for computing the privacy score of users in online social networks. ACM Transactions on Knowledge Discovery from Data, 5(1), Article 6.Google Scholar
  21. Malhotra, A., Totti, L., Meira, W. Jr., Kumaraguru, P., & Almeida, V. (2012). Studying user footprints in different online social networks. In Proceedings of ASONAM 2012 (pp. 1065–1070). arXiv:1301.6870.Google Scholar
  22. Nissenbaum, H. (2004). Privacy as contextual integrity. Washington Law Review, 79, 119–157.Google Scholar
  23. Nunes, A., Calado, P., & Martins, B.. (2012). Resolving user identities over social networks through supervised learning and rich similarity features. In Proceedings of the 27th Annual ACM symposium on applied computing. (pp. 728–729).Google Scholar
  24. Review Group. (2013). See Last Access: December 9 2016.
  25. Romei, A., & Ruggieri, S. (2013). A multidisciplinary survey on discrimination analysis. The Knowledge Engineering Review, 29(5), 1–57.Google Scholar
  26. Ruggieri, S., Pedreschi, D., & Turini, F. (2010). Data mining for discrimination discovery. ACM Transactions on Knowledge Discovery from Data, 4(2), Article 9.CrossRefGoogle Scholar
  27. Soria-Comas, J., & Domingo-Ferrer, J. (2015). Big data privacy: Challenges to privacy principles and models. Data Science and Engineering, 1(1), 21–28.CrossRefGoogle Scholar
  28. Tene, O., & Polonetsky, J. (2012). Privacy in the age of big data: A time for big decisions. Stanford Law Review Online, 64(63), 63–69.Google Scholar
  29. Turow, J. (2011). The daily you: How the new advertising industry is defining your identity and your world. New Haven: Yale University Press.Google Scholar
  30. Van den Hoven, J. (1997). Computer ethics and moral methodology. Metaphilosophy, 28(3), 234–248.CrossRefGoogle Scholar
  31. Van den Hoven, J. (2008). Information technology, privacy, and the protection of personal data. In J. Van den Hoven & J. Weckert (Eds.), Information technology and moral philosophy (pp. 301–321). Cambridge: Cambridge University Press.Google Scholar
  32. Van den Hoven, J., Helbing, D., Pedreschi, D., Domingo-Ferrer, J., Gianotti, F., & Christen, M. (2012). FuturICT—The Road towards Ethical ICT. European Physical Journal—Special Topics, 214, 153–181.CrossRefGoogle Scholar
  33. Vosecky, J., Hong, D., & Shen, V. (2009). User identification across multiple social networks. In Proceedings of the first international conference on Networked Digital Technologies, NDT ’09, IEEE, pp. 360–365.Google Scholar
  34. Walzer, M. (1983). Spheres of justice: A defense of pluralism and equality. New York City: Basic Books.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Markus Christen
    • 1
    Email author
  • Josep Domingo-Ferrer
    • 2
  • Dominik Herrmann
    • 3
  • Jeroen van den Hoven
    • 4
  1. 1.Centre for EthicsUniversity of ZurichZurichSwitzerland
  2. 2.Universitat Rovira i VirgiliCataloniaSpain
  3. 3.University of HamburgHamburgGermany
  4. 4.Philosophy SectionDelft University of TechnologyDelftThe Netherlands

Personalised recommendations