Forecasting Crime? Algorithmic Prediction and the Doctrine of Police Entrapment

Abstract

To predict criminal activity, police departments around the world are using technology at an accelerating rate. These “predictive technologies” produce predictions that direct police resources toward particular people and places for investigation. Using the doctrine of police entrapment recently considered by the Supreme Court of Canada in R v Ahmad, this paper explores whether and to what extent developments in the area of artificial intelligence can legitimately inform the creation of reasonable suspicions and bona fide inquiries in the entrapment context. It argues that due to a number of factors, including their lack of transparency, predictive technologies present difficult challenges for many stakeholders and weaken the defendant’s ability to argue entrapment. Although predictive technologies can be useful, their place in entrapment law complicates things for the existing entrapment framework. The paper suggests that the developing popularity of predictive technologies requires that the doctrine of entrapment be revisited.