The police department in Santa Cruz, California, has begun an experiment that uses a mathematical algorithm to predict when and where certain crimes will be committed, and puts police on the scene before they happen.
So far police have arrested five people using this technique of “predictive policing” and the rates of certain categories of crimes in the city have dropped significantly, perhaps as a result. The program has correctly predicted 40 percent of the crimes it was designed to monitor.
Police departments have said that programs such as these, if proved to be reliable, could help them to deploy their resources more efficiently.
Unlike Philip K. Dick’s novel “The Minority Report” or the film inspired by the novel, the program relies on algorithms, and not mutants to predict the likelihood of something happening.
The program comes from the field of applied mathematics or operations research, and the algorithm was developed by a 29-year-old mathematician at Santa Clara University.
Other mathematical techniques have been developed to predict crimes, most famously Compstat, used in the mid-90s by the New York City Police Department to track serious crimes, like those depicted in the the Minority Report. The Santa Cruz program, which does not appear to have a name, concentrates on property crimes, such as car break-ins and burglaries.
The program was developed by George Mohler, an assistant professor of mathematics.
The algorithm he uses is based on computations used to predict aftershocks following a large earthquake.
The heart of the program is the belief that criminals often commit a second or third crime in the same location and the same time as a first successful crime. For example, if a burglar is successful breaking into a home at 2 p.m. in a certain neighborhood because no one is home, the criminal will use that experience to do it again to another house in the same neighborhood around the same time.
In the case of Santa Cruz, on California’s central coast and home to a University of California campus, that would be about four days later.
The algorithm knows this because Mohler has fed eight years of data on crimes in Santa Cruz into the algorithm.
He first tested the notion in Southern California’s San Fernando Valley with data from the Los Angeles Police Department. After a story about the project appeared in the Los Angeles Times, Zach Friend, a crime analyst at the Santa Cruz department, contacted Mohler and gave him data from 2002-2010. Uniquely, the data is updated daily, something other programs like Compstat don’t do.
As more data is slipped into the algorithm, the program is believed to get more accurate.
“The overall model is based on the belief that crime is not random,” Friend said.”So with enough data points you could predict where and when it will happen.”
A crime is broken down to the two most likely chunks of time it is likely to occur in a certain area. Police are sent out every day with a map of the ten “hot spots” they should watch.
The program does not give police probable cause to arrest anyone, but it does give them a good reason to ask questions when they see someone in the right area at the right time looking suspicious.
Since the program began in July, burglaries in Santa Cruz are down 27 percent. Whether the program was responsible is not clear, but police think their presence at locations where crimes are likely to be committed is having a deterrent affect.
Joel N. Shurkin is an author and freelance writer in Baltimore, MD. He is the author of nine books, which include: Invisible Fire, The Eradication of Smallpox; Engines Of The Mind, A History Of The Computer; Terman’s Kids, The Groundbreaking Study Of How The Gifted Grow Up; and Broken Genius, The Rise And Fall of William Shockley.
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