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.
Graves, James T.; Acquisti, Alessandro; and Christin, Nicolas
"Big Data and Bad Data: On the Sensitivity of Security Policy to Imperfect Information,"
University of Chicago Law Review: Vol. 83
, Article 6.
Available at: https://chicagounbound.uchicago.edu/uclrev/vol83/iss1/6