Abstract
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.
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Notes
- 1.
According to Elgin: “Virtue epistemologists hold that knowledge results from the display of epistemic virtues—open- mindedness, rigor, sensitivity to evidence, and the like” (Elgin 2013: 135).
- 2.
“Epistemic agents should think of themselves as, and act as, legislating members of a realm of epistemic ends: they make the rules, devise the methods, and set the standards that bind them. The epistemic virtues are the traits of intellectual character that equip them to do so” (Elgin 2013:135).
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Acknowledgment
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.
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Grodzinsky, F.S. (2017). Why Big Data Needs the Virtues. In: Powers, T. (eds) Philosophy and Computing. Philosophical Studies Series, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-319-61043-6_12
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