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“Strictly Biomedical? Sketching the Ethics of the Big Data Ecosystem in Biomedicine”

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The Ethics of Biomedical Big Data

Part of the book series: Law, Governance and Technology Series ((LGTS,volume 29))

Abstract

In today’s ever evolving data ecosystem it is evident that data generated for a wide range of purposes unrelated to biomedicine possess tremendous potential value for biomedical research. Analyses of our Google searches, social media content, loyalty card points and the like are used to draw a fairly accurate picture of our health, our future health, our attitudes towards vaccination, disease outbreaks within a county and epidemic trajectories in other continents. These data sets are different from traditional biomedical data, if a biomedical purpose is the categorical variable. Yet the results their analyses yield are of serious biomedical relevance. This paper discusses important but unresolved challenges within typical biomedical data, and it explores examples of non-biomedical Big Data with high biomedical value, including the specific conundrums these engender, especially when we apply biomedical data concepts to them. It also highlights the “digital phenotype” project, illustrating the Big Data ecosystem in action and an approach believed as likely to yield biomedical and health knowledge. We argue that to address the challenges and make full use of the opportunities that Big Data offers to biomedicine, a new ethical framework taking a data ecosystem approach is urgently needed. We conclude by discussing key components, design requirements and substantive normative elements of such a framework.

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Notes

  1. 1.

    IBM. The Four V’s of Big Data. http://www.ibmbigdatahub.com/infographic/four-vs-big-data

  2. 2.

    Data Science at NIH. 2015. What is Big Data? https://datascience.nih.gov

  3. 3.

    National Institutes of Health. NIH Genomic Data Sharing Policy. August 27 2014. (http://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html).

  4. 4.

    U.S. v. Jones, 132 S.Ct. 945, 957 (2012) (Sotomayor, J., concurring).

  5. 5.

    DataTags. 2015. The President and Fellows of Harvard College. http://datatags.org/

  6. 6.

    PIA: A formal process which assists organizations in identifying and minimizing the privacy risks of new projects or policies that make use of Data. The assessment involves working with people within the organization, with partner organizations, and with the people affected to identify and reduce privacy risks.

  7. 7.

    Article 18: Council of the European Union. 2015. Draft Data Protection Regulation. http://data.consilium.europa.eu/doc/document/ST-9565-2015-INIT/en/pdf

  8. 8.

    Harvard School of Engineering and Applied Sciences. 2014. Privacy Tools for Sharing Research Data. http://privacytools.seas.harvard.edu/

References

  • Almishari, Mishari, Mohamed Ali Kaafar, Gene Tsudik, and Ekin Oguz. 2014. Are 140 characters enough? A large-scale linkability study of tweets. http://arxiv.org/pdf/1406.2746.pdf. Accessed 19 Sept 2015.

  • Anema, A., S. Kluberg, K. Wilson, etal. 2014. Digital surveillance for enhanced detection and response to outbreaks. The Lancet Infectious Diseases 14(11): 1035–1037. doi:10.1016/S1473-3099(14)70953-3.

    Google Scholar 

  • Angrist, Misha. 2007. Here is a human being: At the dawn of personal genomics. New York: Harper.

    Google Scholar 

  • Auffray, Charles, and Leroy Hood. 2012. Systems biology and personalized medicine–the future is now. Biotechnology Journal 7(8): 938–939.

    Article  Google Scholar 

  • Ayres, J.W., B.M. Althouse, and M. Dredze. 2014. Could behavioral medicine lead the web data revolution? The Journal of the American Medical Association 311(14): 1399–1400. doi:10.1001/jama.2014.1505.

    Article  Google Scholar 

  • Cate, F.H., and V. Mayer-Schönberger. 2013. Notice and consent in a world of Big Data. International Data Privacy Law 3(2): 67–73. doi:10.1093/idpl/ipt005.

    Article  Google Scholar 

  • Christie, G.P., K. Patrick, and D. Schmuland. 2015. Consultation for collective action on personalized health technology: Eliminating ethical, legal, and social barriers for individual and societal benefit. Journal of Health Communication: International Perspectives 20(8): 867–868. doi:10.1080/10810730.2015.1063404.

    Article  Google Scholar 

  • Dawkins, Richard. 1982. The extended phenotype: The gene as the unit of selection. Oxford/San Francisco: W.H. Freeman and Company.

    Google Scholar 

  • Dove, E.S., B.M. Knoppers, and M.H. Zawati. 2014. Towards an ethics safe harbor for global biomedical research. Journal of Law and the Biosciences 1(1): 3–51. doi:10.1093/jlb/lst002.

    Article  Google Scholar 

  • Duhigg, Charles. 2012. How companies know your secrets. New York Times, February 16.

    Google Scholar 

  • Feiler, Bruce. 2014. The United States of metrics. New York Times, May 16.

    Google Scholar 

  • Felch, Jason. 2008. DNA Databases blocked from the public. Los Angeles Times, August 29.

    Google Scholar 

  • Fox, Susanne. 2011. The social life of health information. Pew Research Center. http://www.pewinternet.org/2011/05/12/the-social-life-of-health-information-2011/. Accessed 19 Sept 2015.

  • Freifeld, C.C., J.S. Brownstein, C.M. Menone, etal. 2014. Digital drug safety surveillance: Monitoring pharmaceutical products in twitter. Drug Safety 37(5): 343–350. doi:10.1007/s40264-014-0155-x.

    Google Scholar 

  • Gasser, Urs. 2015. Perspectives on the future of digital privacy. ZSR II 134: 426–427.

    Google Scholar 

  • Gasser, Urs, Ryan Budish, and Sarah Myers West. 2015. Multistakeholder as Governance Groups: Observations from case studies. Berkman Center Research Publication No. 2015–1. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2549270. Accessed 19 Sept 2015.

  • Gächter, T., and G. Werder. 2015. Gedanken zur allfälligen Verankerung eines «Rechts auf Kopie» in der schweizerischen Bundesverfassung. See also entry in the Swiss Parliament https://www.parlament.ch/de/ratsbetrieb/suche-curia-vista/geschaeft?AffairId=20154045.

  • Ginsburg, G. 2014. Medical genomics: Gather and use genetic data in health care. Nature 508: 451–453. doi:10.1038/508451a.

    Article  Google Scholar 

  • Gleibs, I.H. 2014. Turning virtual public spaces into laboratories: Thoughts on conducting online field studies using social network sites. Analyses of Social Issues and Public Policy 14: 352–370. doi:10.1111/asap.12036.

    Article  Google Scholar 

  • Global Alliance for Genomics and Health. 2015. Privacy and security policy. https://genomicsandhealth.org. Accessed 19 Sept 2015.

  • Hafen, E., D. Kossmann, and A. Brand. 2014. Health data cooperatives – Citizen empowerment. Methods of Information in Medicine 53(2): 82–86. doi:10.3414/ME13-02-0051.

    Article  Google Scholar 

  • Hayden, E.C. 2015. Genome researchers raise alarm over Big Data. Nature. 312–314. doi:10.1038/nature.2015.17912.

  • Heger, Monica. 2015. Regulators move toward adverse event reporting via mobile apps. Nat Med 21: 104. doi:10.1038/nm0215-104.

    Google Scholar 

  • Homer, Nils, etal. 2008. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet 4(8): e1000167. doi:10.1371/journal.pgen.1000167.

    Google Scholar 

  • Hood, L., and M. Flores. 2012. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. N Biotechnol 29(6): 613–624.

    Article  Google Scholar 

  • Hood, L., and C. Auffray. 2013. Participatory medicine: a driving force for revolutionizing healthcare. Genome Med 5(12): 110.

    Article  Google Scholar 

  • Jain, S.H., B.W. Powers, J.B. Hawkins, and J.S. Brownstein. 2015. The digital phenotype. Nature Biotechnology 33(5): 462–463. doi:10.1038/nbt.3223.

    Article  Google Scholar 

  • Juengst, E.T., R.A. Settersten Jr., J.R. Fishman, and M.L. McGowan. 2012. After the revolution? Ethical and social challenges in ‘personalized genomic medicine’. Per Med 9(4): 429–439. doi:10.2217/pme.12.37.

    Article  Google Scholar 

  • Kahn, J.P., E. Vayena, and A.C. Mastroianni. 2014. Opinion: Learning as we go: Lessons from the publication of Facebook’s social-computing research. Proceedings of the National Academy of Sciences 111(38): 13677–13679. doi:10.1073/pnas.1416405111.

    Article  Google Scholar 

  • Koenig, B.A. 2014. Have we asked too much of consent? Hastings Center 44(4): 33–34.

    Article  Google Scholar 

  • Kosinski, M., D. Stillwell, and T. Graepe. 2013. Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences of the United States of America 110(15): 5802–5805. doi:10.1073/pnas.1218772110.

    Article  Google Scholar 

  • Levinson, Daniel R. 2012. Hospital incident reporting systems do not capture most patient harm. Department of health and human services. http://oig.hhs.gov/oei/reports/oei-06-09-00091.pdf. Accessed 17 Oct 2013.

  • Mandeville, K.L., M. Harris, L.H. Thomas, Y. Chow, and C. Seng. 2014. Using social networking sites for communicable disease control: Innovative contact tracing or breach of confidentiality? Public Health Ethics. 7(1): 47–50. doi:10.1093/phe/pht023.

    Article  Google Scholar 

  • Manson, Neil C., and Onora O’Neill. 2007. Rethinking informed consent in bioethics. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Markham, Annette, and Elizabeth Buchanan. 2012. Ethical decision-making and Internet research, Recommendations from the AoIR Ethics Working Committee. http://aoir.org/reports/ethics2.pdf. Accessed 19 Sept 2015.

  • Mayer-Schönberger, Viktor, and Kenneth Cukier. 2013. Big Data: A revolution that will transform how we live, work, and think. London: John Murray.

    Google Scholar 

  • Mitchell, C., L.B. Moraia, and J. Kaye. 2014. Health database: Restore public trust in care data project. Nature 508: 458. doi:10.1038/508458e.

    Article  Google Scholar 

  • Mittelstadt, B.D., and L. Floridi. 2016. The ethics of big data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics 22(2): 303–341. doi:10.1007/s11948-015-9652-2.

    Google Scholar 

  • de Montjoye, Y.-A., L. Radaelli, V.K. Singh, and A. Pentland. 2015. Unique in the shopping mall: On the reidentifiability of credit card data. Science 347(6221): 536–539. doi:10.1126/science.1256297.

    Article  Google Scholar 

  • Murdoch, T.B., and A.S. Detsky. 2013. The inevitable application of Big Data in health care. The Journal of the American Medical Association. 309(13): 1351–1352. doi:10.1001/jama.2013.393.

    Article  Google Scholar 

  • Narayanan, Arvind, and Vitaly Shmatikov. 2008. Robust de-anonymization of large sparse datasets. http://www.cs.utexas.edu/~shmat/shmat_oak08netflix.pdf. Accessed 19 Sept 2015.

  • National Institutes of Health. 2014. NIH Genomic Data Sharing Policy. http://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html. Accessed 19 Sept 2015.

  • Narayanan, Arvid, and Edward Felten. 2014. No silver bullet: De-identification still doesn’t work. http://randomwalker.info/publications/no-silver-bullet-de-identification.pdf. Accessed 19 Sept 2015.

  • Nuffield Council of Bioethics. 2010. Medical profiling and online medicine: The ethics of ‘personalised healthcare’ in a consumer age. London: Nuffield Council on Bioethics.

    Google Scholar 

  • Nuffield Council on Bioethics. 2015. The collection, linking and use of data in biomedical research and health care: Ethical issues, 4–18. London: Nuffield Council on Bioethics.

    Google Scholar 

  • O’Brien, David, Jonathan Ullman, Micah Altman, Urs Gasser, Michael Bar-Sinai, Kobbi Nissim, Salil Vadhan, Michael John Wojcik, and Alexandra Wood. 2015. Integrating approaches to privacy across the research lifecycle: When is information purely public? Berkman Center Research Publication No. 2015–7. http://dx.doi.org/10.2139/ssrn.2586158. Accessed 19 Sept 2015.

  • Ohm, Paul. 2010. Broken promises of privacy: Responding to the surprising failure of anonymization. UCLA Law Review 57: 1701–1777.

    Google Scholar 

  • Oliver, J.M., M.J. Slashinski, T. Wang, P.A. Kelly, S.G. Hilsenbeck, and A.L. McGuire. 2012. Balancing the risks and benefits of genomic data sharing: genome research participants’ perspectives. Public Health Genomics 15(2): 106–114. doi:10.1159/000334718.

    Article  Google Scholar 

  • O’Neill, Onora. 2002. Autonomy and trust in bioethics. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • O’Neill, Onora. 2013. Can data protection secure personal privacy? In Genetic privacy: An evaluation of the ethical and legal landscape, ed. Terry Sheung-Hung Kaan and Calvin Wai-Loon Ho, 25–40. London: Imperial College Press.

    Chapter  Google Scholar 

  • Palfrey, John, and Urs Gasser. 2012. Interop: The promise and perils of highly interconnected systems. New York: Basic Books.

    Google Scholar 

  • Paul, Maria. 2015. Your phone knows if you are depressed. Northwestern News, July 15.

    Google Scholar 

  • Pentland, Alex, Todd G. Reid, and Tracy Heibeck. 2013. Big Data and health. Revolutionalizing medicine and public health. Report of the Big Data and Health Working Group. http://kit.mit.edu/sites/default/files/documents/WISH_BigData_Report.pdf. Accessed 19 Sept 2015.

  • Polonetsky, Jules, Omer Tene, and Joseph Jerome. 2014. Benefit-risk analysis for Big Data Projects. Future of Privacy Forum. http://www.futureofprivacy.org/wp-content/uploads/FPF_DataBenefitAnalysis_FINAL.pdf. Accessed 19 Sept 2015.

  • Rivers, Caitlin M. and Bryan L. Lewis. 2014. Ethical research standards in a world of Big Data. 3F1000Research.

    Google Scholar 

  • Rudder, Christian. 2014. Dataclysm: Who we are (when we think no one’s looking.). UK: Harper Collins. New York.

    Google Scholar 

  • Saeb, S., M. Zhang, C.J. Karr, etal. 2015. Mobile Phone Sensor correlates of depressive symptom severity in daily-life behavior: An exploratory study. J Med Internet 17(7): e175. doi:10.2196/jmir.4273.

    Google Scholar 

  • Samaritans. 2014. Samaritans launches Twitter app to help identify vulnerable people. http://www.samaritans.org/. Accessed 19 Sept 2015.

  • Schneier, Bruce. 2014. Data and goliath: The hidden battles to collect your data and control your world. New York: W.W. Norton & Company.

    Google Scholar 

  • Schwartz, Paul M., and Daniel J. Solove. 2011. The PII problem: Privacy and a New concept of personally identifiable information. New York University Law Review 86(2011): 1814.

    Google Scholar 

  • Secretary’s Advisory Committee on Human Research Protections. 2015. Human subjects research implications of “Big Data”. http://www.hhs.gov/ohrp/sachrp/commsec/hsrimplicationsofbig_datastudies.html. Accessed 19 Sept 2015.

  • Sengupta, Somini. 2012. Should personal data be personal? New York Times, February 4.

    Google Scholar 

  • Shaw, Jonathan. 2014. Why “Big Data” is a big deal. Harvard Magazine, March-April. http://harvardmagazine.com/2014/03/why-big-data-is-a-big-deal. Accessed 19 Sept 2015.

  • Stephens, Zachary D., S.Y. Lee, F. Faghri, R.H. Campbell, C. Zhai, etal. 2015. Big Data: Astronomical or genomical? PLoS Biology 13(8): e1002195. doi:10.1371/journal.pbio.1002195.

    Google Scholar 

  • Sweeney, Latanya. 2000. Simple demographics often identify people uniquely. http://dataprivacylab.org/projects/identifiability/paper1.pdf. Accessed 19 Sept 2015.

  • The Economist. 2014. Ebola and Big Data: Waiting on hold. The Economist, October 25.

    Google Scholar 

  • Van Noorden, R. 2014. US agency updates rules on sharing genomic data. Nature. doi:10.1038/nature.2014.15800. http://www.nature.com/news/us-agency-updates-rules-on-sharing-genomic-data-1.15800.

  • Vayena, E., A. Ganguli-Mitra, and N. Biller-Andorno. 2008. Guidelines on biobanks: emerging consensus and unresolved controversies. In Ethical issues in governing biobanks : global perspectives, ed. B. Elger, N. Biller-Andorno, A. Mauron, and A.M. Capron, 23–35. Farnham: Ashgate.

    Google Scholar 

  • Vayena, Effy, and John Tasioulas. 2013. Adapted standards: Ethical oversight of participant–led health research. PLoS Medicine 10(3): e1001402. doi:10.1371/journal.pmed.1001402.

    Google Scholar 

  • Vayena, E., A. Mastroianni, and J. Kahn. 2013. Caught in the web: Informed consent for online health research. Science Translational Medicine 5(173): 173fs6. doi:10.1126/scitranslmed.3004798.

    Article  Google Scholar 

  • Vayena, E., M. Salathé, L.C. Madoff, and J.S. Brownstein. 2015. Ethical challenges of Big Data in public health. PLoS Computational Biology 11(2): e1003904. doi:10.1371/journal.pcbi.1003904.

    Article  Google Scholar 

  • Vayena, Effy, and Urs, Gasser. 2016. Between opness and privacy in genomics. PLoS Medicine 13(1): e1001937. doi: 10.1371/journal.pmed.1001937

    Google Scholar 

  • Watson, Sarah M. 2014. Data is the new “____” on the industrial metaphors of Big Data. http://dismagazine.com/discussion/73298/sara-m-watson-metaphors-of-big-data/. Accessed 19 Sept 2015.

  • Weber, G.M., K.D. Mandl, and I.S. Kohane. 2014. Finding the missing link for Big biomedical data. The Journal of the American Medical Association 311(24): 2479–2480. doi:10.1001/jama.2014.4228.

    Google Scholar 

  • Wesolowski, Amy, C.O. Buckee, L. Bengtsson, E. Wetter, X. Lu, and A.J. Tatem. 2014. Commentary: containing the ebola outbreak – The potential and challenge of mobile network data. PLoS Currents Outbreaks. 2014 Sept 29. doi:10.1371/currents.outbreaks.0177e7fcf52217b8b634376e2f3efc5e.

  • Widdows, Heather. 2013. The connected self. The ethics and governance of the genetic individual. Cambridge: Cambridge University Press.

    Google Scholar 

  • World Health Organization. 2002. Safety of medicines – A guide to detecting and reporting adverse drug reactions – Why health professionals need to take action. http://apps.who.int/medicinedocs/en/d/Jh2992e/12.html. Accessed 19 Sept 2015.

  • Zimmer, Michael. 2010. “But the data is already public”: On the ethics of research in Facebook. Ethics Information Technology 12: 313–325. doi:10.1007/s10676-010-9227-5.

    Article  Google Scholar 

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Authors and Affiliations

  1. Health Ethics and Policy Lab, Institute of Epidemiology, Biostatistics and Prevention, University of Zurich, Hirschengraben 84, Zurich, 8001, Switzerland

    Effy Vayena

  2. Berkman Center for Internet & Society, Harvard Law School, Harvard University, 23 Everett Street, 2nd Floor, Cambridge, MA, 02138, USA

    Urs Gasser

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  1. Effy Vayena
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  2. Urs Gasser
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Correspondence to Effy Vayena .

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Editors and Affiliations

  1. Oxford Internet Institute, University of Oxford, Oxford, United Kingdom

    Brent Daniel Mittelstadt

  2. Oxford Internet Institute, University of Oxford, Oxford, United Kingdom

    Luciano Floridi

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Vayena, E., Gasser, U. (2016). “Strictly Biomedical? Sketching the Ethics of the Big Data Ecosystem in Biomedicine”. In: Mittelstadt, B., Floridi, L. (eds) The Ethics of Biomedical Big Data. Law, Governance and Technology Series, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-33525-4_2

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