Law Commons^™

Smart Devices In Criminal Investigations: How Section 8 Of The Canadian Charter Of Rights And Freedoms Can Better Protect Privacy In The Search Of Technology And Seizure Of Information, Lee-Ann Conrod

LLM Theses

This thesis examines the jurisprudence from the Supreme Court of Canada (SCC) on informational privacy under section 8 of the Canadian Charter of Rights and Freedoms as it relates to searches of technology in the context of criminal investigations. The development and use of technology in criminal investigations will be detailed along with an overview of the current state of the law in this area. Challenges with the interpretation of section 8 demonstrate a prevalent uncertainty. This thesis proposes a new approach for the SCC to apply to cases where technology intersects with section 8 of the Charter. The proposal …

User-Generated Evidence, Rebecca Hamilton

Articles in Law Reviews & Other Academic Journals

Around the world, people are using their smartphones to document atrocities. This Article is the first to address the implications of this important development for international criminal law. While acknowledging the potential benefits such user-generated evidence could have for international criminal investigations, the Article identifies three categories of concern related to its use: (i) user security; (ii) evidentiary bias; and (iii) fair trial rights. In the absence of safeguards, user-generated evidence may address current problems in international criminal justice at the cost of creating new ones and shifting existing problems from traditional actors, who have institutional backing, to individual users …

Bias In, Bias Out, Sandra G. Mayson

All Faculty Scholarship

Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic risk assessment to estimate the likelihood that a person will commit future crime. As many scholars have noted, these algorithms tend to have disparate racial impacts. In response, critics advocate three strategies of resistance: (1) the exclusion of input factors that correlate closely with race; (2) adjustments to algorithmic design to equalize predictions across racial lines; and (3) rejection of algorithmic methods altogether.

This Article’s central claim is that these strategies are at best superficial and at worst counterproductive because the source of racial inequality in risk assessment lies …