Big data is transforming the way that governments provide security to, and justice for, their citizens. It also, however, has the potential to increase surveillance and government power. Geospecific information – from licence plate recognition and mobile phone data, biometric matches of DNA, facial recognition, financial transactions, and internet search history – is increasingly allowing government agencies to search and cross-reference. This increased reliance on big data searches raises the question: what is the probative value of the information that results?A distinguishing feature of the scientific method is the development of a hypothesis that is then tested against data that either support or refute the hypothesis. A conventional criminal investigation can be seen to parallel that method – after a suspect is identified, evidence is gathered to either build a case against, or rule out, that suspect. The analysis of big data, by contrast, can deviate from a path that parallels the scientific method, at times being more akin to trawling through data to then generate a hypothesis. In this paper we investigate conditions in which this leads to problematic outcomes, such as more data leading to high rates of false positives. We then sketch a big data analysis legal/policy framework that can circumvent these problems.
Marco Pollanen, Trent University, Canada
Bruce Cater, Trent University, Canada
Stream: Law 12. Criminal Justice Policy and Law
This paper is part of the ACPEL2016 Conference Proceedings (View)
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