Why Big Data Needs the Virtues
In this paper I offer a critical reflection on Big Data through the lens of “the virtues” in an attempt to separate much of the “hype” from reality. Part 1 defines what is meant by Big Data and describes why it is valuable. I examine its ethical issues in the context of the characteristics of Big Data as exemplified by the 4V’s: volume, velocity, variety (traditional 3V’s) and a 4th, veracity. Part 2 considers whether Big Data Science is really a “theory free” science based only on statistical correlations. In Part 3, I explore the role of the “Big Data Scientist” and her responsibilities as virtuous epistemic agent. Part 4 applies both virtue ethics and virtue epistemology to Big Data, focusing on how it can be used in an ethically responsible way to benefit society. Finally, I will explain why thinking in terms of the virtues is helpful in the analysis of Big Data because when a Data Scientist habitually acts in accordance with the virtues, she will be better able to cope with the “messiness” and dynamic flux of Big Data with open-mindedness and intellectual courage.
KeywordsBig data Big data scientist Ethical responsibility Virtue ethics Virtue epistemology Statistical correlations Virtuous epistemic agent
This keynote talk was presented at CEPE-IACAP 2015. I would like to thank everyone for their comments. I especially want to thank Deborah Johnson, Herman Tavani, Richard Volkman, Alexis Elder, Terry Bynum, Steve Lilley, and the other philosophers of the Research Group at SCSU who offered insightful criticism of earlier versions of this paper.
- Buchta, H. (2014, November 25). How did data get to be so big? Inside counsel. Breaking News. http://www.insidecounsel.com/2014/11/25/how-did-data-get-to-be-so-big. Accessed 1 June 2015.
- CBS News. (2010). Facebook: One social graph to rule them All. http://www.cbsnews.com/news/facebook-one-social-graph-to-rule-them-all/. Accessed 7 June 2015.
- Economic Predictions Research Project. (2012). http://www.economicpredictions.org/who-predicted-the-financial-crisis.htm, Accessed 10 June 2015.
- Elgin, C. Z. (2013). Epistemic Agency. In Theory and research in education 11(2). (pp. 135–152). Sage Publishing Company. doi: 10.1177/1477878513485173.
- EMC2. (2015). Data science and big data analytics: Discovering, analyzing, visualizing and presenting data. New York: Wiley.Google Scholar
- Floridi, L. (1999). Philosophy and computing: An introduction. New York: Routledge.Google Scholar
- Gumbus A, & Grodzinsky, F. (2014). Big bad data? An analysis of the positive applications of the uses of Big Data. Ethicomp Proceedings, ETHCOMP 2014. Paris, France.Google Scholar
- Kitchin, R. (2014, April–June). Big data, new epistemologies and paradigm shifts. Big Data and Society, Sage Publishing Co. pp. 1–12. doi: 10.1177/2053951714528481.
- Lohr, S. (2015). Dataism. New York: Harper Collins.Google Scholar
- Longino, H. E. (1990). Science as social knowledge: Values and objectivity in scientific inquiry. Princeton: Princeton University Press.Google Scholar
- Longino, H. (2002). The fate of knowledge. Princeton: Princeton University Press.Google Scholar
- Louden, R. B. (1984). On some vices of virtue ethics. In The Virtues: Contemporary essays on moral character (pp. 66–79). California: Wadsworth Publishing, 1987.Google Scholar
- Manyika, J. et al. (2011). Big data: the next frontier for innovation, competition and productivity. McKinsey Global Institute Report. http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
- Mayer-Schonberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work and think. Boston: Houghton Mifflin Harcourt.Google Scholar
- McGuire, T., Manyika, J., & Chui, M. (2012). Why big data is the new competitive advantage. Ivey Business Journal, 76(4), 1–4.Google Scholar
- MIT Technology Review. (2013). http://www.technologyreview.com/view/519851/the-big-data-conundrum-how-to-define-it/, Accessed 3 October 2013.
- Moor, J. H. (2004). Just Consequentialism and Just Computing. In R. A. Spinello & H. T. Tavani (Eds.), Readings in cyberethics (2nd ed., pp. 407–417). Jones and Bartlett: Sudbury.Google Scholar
- Moscaritolo, A. (2012). Internet traffic to reach 1.3 zettabytes by 2016. PCMag.com, http://www.pcmag.com/article2/0,2817,2405038,00.asp. Accessed 15 June 2015.
- Murphy, M., & Barton, J. (2014). From a sea of data to actionable insights: Big data and what it means for lawyers. Intellectual property & Technology Law Journal, 26(3), 8–17.Google Scholar
- Shirky, C. (2009). Algorithmic authority. http://p2pfoundation.net/Algorithmic_Authority. Accessed 15 June 2015.
- Vance, A. (2012, October 10). The making of 1 Billion. Bloomberg Business Week.Google Scholar
- Williams, B. (1985). Ethics and the limits of philosophy. Cambridge: Harvard University Press.Google Scholar
- Zagzebski, L. (2001). Recovering Understanding. In M. Steup (Ed.), Knowledge, truth, and duty: Essays on epistemic justification, responsibility, and virtue. Oxford: Oxford University Press.Google Scholar
- Zwitter, A. (2014, July–December). Big data ethics. Big Data & Society, pp. 1–6.Google Scholar