“Los Angeles Predictive Policing Experiment” Lecture by Dr. P. Jeffrey Brantingham February 5, 2013

Departments of Criminology & Criminal Justice, Anthropology and Public Safety Lecture
February 5, 2013, 12:00-2:00pm, Juan Ramon Jimenez (Room 2208), Stamp Student Union


Dr. P. Jeffrey Brantingham is Professor of Anthropology at UCLA.  Dr. Brantingham directs the UC Mathematical and Simulation Modeling of Crime project (UC MaSC), which is focused on bridging the gap between the mathematical and social sciences in the study of crime (see http://paleo.sscnet.ucla.edu).  He co-founded PredPol – The Predictive Policing Company which is delivering real-time predictive policing to law enforcement agencies nationally and internationally (see http://www.predpol.com).


The term predictive policing refers broadly to the use of data analysis to inform the allocation of police resources.  Not surprisingly, the vagueness of this definition allows many different data analysis programs to be called predictive policing.  Dr. Brantingham defines predictive policing as a formal process that (1) uses data to assign explicit probabilities to future crime events in space and time, (2) presents crime event probabilities in a useable framework to law enforcement decision makers, and (3) leads to resource deployment patterns conditioned on crime probabilities.  For predictive policing to be effective it also must hold that (4) the accuracy of predictions be evaluated and (5) law enforcement be willing to act on probabilistic information.  Dr. Brantingham outlines the behavioral and mathematical and architecture underlying his approach to predictive policing.  He then reviews the results of the Los Angeles Predictive Policing Experiment, a real-time single-blind field deployment of predictive policing in multiple divisions of the LAPD.  The experiment establishes a predictive accuracy six-times random and more than two-times that achievable by a dedicated crime analyst.  The experiment also underscores the critical importance of officer ‘buy-in’ for successful real-world deployments.


Event is free and open to public.