Fighting Crime with Math
Sometimes predicting human behavior doesn’t depend on understanding our psychology.
Researchers at the annual meeting of the American Association for the Advancement of Science in San Diego today presented a mathematical model that predicts the likelihood that a police force can conquer either a new drug market or end a rash of burglaries.
Treating criminal behavior as a deterministic system they created equations, based on Los Angeles Police Department data, that describe the movement of neighborhood crime and how cops might better control the crime rate.
The model produced two types of so-called criminal “hot spots,” which are mathematically referred to as supercritical (which is an unstable system) and subcritical (which is a stable system.)
A subcritical hot spot, like a large neighborhood drug market, can be effectively suppressed according to the model. Because this sort of hot spot requires complex organization and is not easily re-established even after police pressure is relaxed.
But a strong police presence in a supercritical hot spot doesn’t provide a lasting solution. Here, the crime hot spot simply pops up in a nearby area. Think of thieves moving through densely packed homes and quickly able to establish new targets outside the heavily policed area.
But the model’s predictions about hot spot displacement have not been observed in real life. So while the scientists are talking with the LAPD there are no plans, yet, to alter police strategy.