A critical exploration, analysis, and contextualization of discrete and continuous models of criminal behaviour for the prediction of future real-world crime occurrence

Abstract

This interdisciplinary project explores “predictive policing”, a blanket term given to a number of crime prediction algorithms and tools used by police departments across the globe in an effort to predict and pre-empt crime occurrence. This project attempts to cut through the profound amount of both positive and negative rhetoric surrounding predictive policing software to understand what theory they are based on, how they are actually implemented in software, and how they interface with police officers working on-the-beat. Through a literature review of empirical environmental criminology research, a theory of how crime self-concentrates in space and time is discussed, as well as the potential explanations for this behaviour. Using this literature, two predictive models of criminal behaviour are introduced, explained, tested, and analysed, to understand how empirical crime observations can be translated into software. Using numerical results obtained from these models in conjunction with existing meta-critiques of predictive policing tools, the argument is made that while current predictive policing tools may hold theoretical value in the field of crime prediction, they have enough significant drawbacks as to cast doubt on their use to predict real world crime.