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The Supreme Court Law Review: Osgoode’s Annual Constitutional Cases Conference

Authors

Lisa M. Austin

Abstract

Privacy law, to the extent that it regulates state information practices, wears two “public” hats. The first hat is constitutional law. For example, the Canadian Charter protects privacy through protecting individuals against unreasonable searches and seizures. The second hat is public sector data protection law modelled on what are known as Fair Information Practices (FIPs). For example, in Canada the federal Privacy Act regulates the collection, use and disclosure of personal information held by government institutions and provides individuals with a right of access to that information. The constitutional hat is concerned with state-individual relations in the context of law enforcement while the data protection hat is concerned with state-individual relations in the context of administering state programs. This article calls into question the ongoing relevance of this divide. The merging of these two frameworks is a large project to both undertake and defend. This article only purports to offer some initial reflections on a potential merger, focusing on recent Supreme Court cases, including R. v. Spencer; R. v. Wakeling; and R. v. Fearon. First, this article outlines some of the ways in which our Charter jurisprudence already adopts some of the insights that come out of the data protection law model and points to some of the ways in which this can be built upon. Next, the article outlines the potential problems of using data protection law framework in the context of law enforcement and anti-terrorism if the limitations of data protection are not well understood when balancing interests. Finally, it finishes with some proposals about how merging the two models might better address some new types of “Big Data” investigatory techniques, or, what we now all describe post-Snowden, as “collecting-the-haystack-to-find-the-needle”.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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