Police work in the 21st Century is getting a makeover thanks to data-driven crime-fighting models. As cities face tighter budgets, the use of so-called predictive policing may allow local authorities to maximize their limited resources and ensure the public is much safer. Take the city of Santa Cruz: its police force has lost several officers over the past decade to cuts, but the city has been experimenting with an algorithm system in order to predict when and where future crimes are most likely to occur. As technology has improved, the capabilities of such systems has enhanced also. Santa Cruz was chosen as an ideal testing ground because its crime rates are average and the entire police department and city is participating under the system. The software program basically guides police toward scoping out “hot spots,” i.e. locations where crime has been predicted most likely to occur. This means that officers are relying on specific maps that allow them to focus their attention on key areas as opposed to expending too many resources on vast patrol operations. Basic police work just got a little less basic. The publication Popular Science reports the following on the experiment’s creator, George Mohler, a 30-year-old mathematician:
“Mohler’s seismology-inspired algorithm is different. In his formula, the distance and time separating two crimes is a data point too, so it assesses the risk of main ‘shocks’ and the risk of aftershocks connected to that first event. ‘If you have 5,000 events, our model actually considers on the order of 5,000 events: 5,000 multiplied by 4,999 multiplied by 4,998, and so on,’ Mohler says. It’s this massive secondary data set that helps identify the high-probability zones, where ‘aftercrimes’ are most likely to occur. Before he moved to Santa Clara, Mohler proved that his algorithm could work in a simulation run on crime data from Los Angeles’s San Fernando Valley. Mohler and his colleagues at the University of California at Los Angeles found that their maps successfully predicted 20 to 95 percent more crimes than maps used in CompStat.”
While many officers may be skeptical of the system, predictive policing basically requires one officer to patrol a 500-by 500-foot hot spot during an hour-long window. There is no clear consensus yet as to whether the experiment is truly successful but it has been called “promising.” For instance, property crime was down 27 percent. Time will tell if other city police departments also adopt similar methods. Read more here.