Digital Surveillance and Preventive Policing

Abstract

Police departments are increasingly relying on sophisticated machine learning algorithms to process data about past crimes and “predict” the timing and location of future crimes. This turn towards “digital policing” raises numerous privacy and criminal procedure concerns. While commentators and policymakers have given a large amount of attention to these issues, they have largely ignored digital policing’s non-procedural, criminal law implications. This article examines the effects of digital policing on deterrence policy and substantive criminal law. It shows that digital policing helps reduce the complexity of law enforcement and creates economies of scale. The article’s main contribution is showing that digital and preventive policing will lead to inefficient over-deterrence, unless lawmakers reduce the gross sanctions for criminal misconduct. This is true for first-time offenders and for repeat offenders. But in the latter case, the problem is magnified by the fact that the digital footprint left behind by an offender who is caught and convicted will make it much easier for the authorities to identify, arrest, and convict repeat offenders. The article also examines digital policing’s implications for inchoate crimes, such as criminal attempt, conspiracy, and solicitation, and for plea bargains, the entrapment defense, and police corruption.

Keywords: criminal law, policing, privacy, surveillance, optimal deterrence, criminal procedure, preventive policing

JEL Classification: K14