Authors: Marco Pollanen & Bruce Cater, Trent University, Canada
Email: marcopollanen@trentu.ca
Published: May 31, 2017
https://doi.org/10.22492/ijpel.4.1.01
Citation: Pollanen, A., & Cater, B. (2017). The Evidentiary Value of Big Data Analysis. IAFOR Journal of Politics, Economics & Law, 4(1). https://doi.org/10.22492/ijpel.4.1.01
Abstract
Big data is transforming the way governments provide security to, and justice for, their citizens. But it also has the potential to increase surveillance and government power. Indeed, information gathered from license plate recognition, mobile phone usage, biometric matches of DNA, facial recognition, financial transactions, and internet search history is increasingly allowing government agencies to search and cross-reference. The opportunity for big data searches then raises the question: what is the probative value of the information that results?
The scientific method begins with the development of a hypothesis that is then tested against data that will either support or refute the hypothesis. That method is essentially followed in a conventional criminal investigation in which, after a suspect is first identified, evidence is gathered to either build a case against, or rule out, that suspect.
The analysis of big data, by contrast, may at times be more akin to trawling for data first, only to subsequently define a hypothesis. In this paper, we investigate the conditions in which this approach may lead to problematic outcomes, including higher rates of false positives. We then sketch a big data analysis legal/policy framework that may address these problems.
Keywords
database searches, forensic science, big data analysis, criminal databases