Big Data and Bad Data: On the Sensitivity of Security Policy to Imperfect Information

The University of Chicago Law Review, 117--137 (2016)

21 Pages Posted: 6 Jan 2019 Last revised: 14 Jan 2019

See all articles by James Graves

James Graves

Carnegie Mellon University

Alessandro Acquisti

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management

Nicolas Christin

Carnegie Mellon University

Date Written: 2016

Abstract

In this Essay, we examine some of the factors that make developing a “science of security” a significant research and policy challenge. We focus on how the empirical hurdles of missing data, inaccurate data, and invalid inferences can significantly impact—and sometimes impair—the security decisionmaking processes of individuals, firms, and policymakers. We offer practical examples of the sensitivity of policy modeling to those hurdles and highlight the relevance of these examples in the context of national security.

Keywords: Big Data, Security Policy, Information Sharing

Suggested Citation

Graves, James and Acquisti, Alessandro and Christin, Nicolas, Big Data and Bad Data: On the Sensitivity of Security Policy to Imperfect Information (2016). The University of Chicago Law Review, 117--137 (2016), Available at SSRN: https://ssrn.com/abstract=3305274

James Graves

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Alessandro Acquisti (Contact Author)

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management ( email )

Pittsburgh, PA 15213-3890
United States
412-268-9853 (Phone)
412-268-5339 (Fax)

Nicolas Christin

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

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