The “definition of predictive policing” has been in use for years, but the growth of software and reliance upon it has given us insight into both the benefits and challenges of predictive policing. All technology in law enforcement has its pros and cons, and the predictive policing pros and cons are discussed here.
Much of modern law enforcement strategy and technology is based on the CompStat process, which enforces principles of tracking and rapidly responding to crime in an organized manner. Predictive policing pros and cons are found in this process fulfillment; it’s not simply faster reactive policing where patrol officers responding to a crime receive information in the field from many different sources very quickly. Although predictive policing owes its roots to the CompStat process, its goal is to prevent crimes from happening, not responding to them faster based on historic crimes.
Law enforcement agencies often assume that predictive policing technology is expensive, requires new hiring, and results in hardware costs. PredPol works with existing RMS (law enforcement crime records database) and using a secured data transfer, generates accurate predictions for every shift, beat, and crime in one tap or click. Predictions are printed or accessed securely through computers or mobile devices in patrol vehicles.
Predictive policing technology surpasses traditional hotspot mapping of past crimes to direct patrol. These “heatmaps” were once considered an innovative way to allocate limited police resources, but now that predictive forecasting technology can integrate criminological theory, law enforcement technology has new benefits. In fact, a 6 month randomized controlled trial found that crime analysts using PredPol technology in addition to their existing tools are twice as effective as experienced crime analysts using the industry’s latest hotspot mapping techniques.
Predictive policing predicts crimes that will happen in the 500′ by 500′ prediction “boxes” by providing locations that are highest risk of crimes during each patrol shift each day. Placing patrol officers in the these boxes creates a deterrence and suppression effect, preventing a crime from occurring, and reducing arrests. There have been cases in which criminals were stopped in the act of committing a crime, or leaving the scene of a recently committed crime, but those are rare. Fewer arrests result in reduced city costs in courts, jails, and departments – freeing up resources across the board to focus on community issues and dig deeper into solving problems rather than focusing on an increasing prisoner population.
PredPol uses only 3 points of reported crime data from police systems: what crime happened, when it happened, and where it happened. The data is not tied to any demographic or individual data of any kind. Since the crime is based off of civilian reports, it requires an actual citizen (or victim, in many unfortunate cases) to report a crime and call for service in their area. Departments then place officers in predicted areas — many times near the recently reported crime — to deter future crimes and prevent re-victimization due to repeat offense (a known criminal pattern). This results in repeated crime prevention through an intelligently placed officer presence; it does not mean that usage of PredPol results in police oppression or profiling.