Crime fighters have long used brains and brawn but now a new kind of technology known as “predictive policing” promises to make them more efficient.
People are creatures of habit... the criminal wants to go where he will be successful ...
A growing number of law enforcement agencies, in the US and elsewhere, have been adopting software tools with predictive analytics, based on algorithms that aim to predict crimes before they happen.
The concept sounds like something out of science fiction and the thriller Minority Report based on a Philip K. Dick story.
Without some of the sci-fi gimmickry, police departments from Santa Cruz, California, to Memphis, Tennessee, and law enforcement agencies from Poland to Britain have adopted these new techniques.
The premise is simple: criminals follow patterns, and with software – the same kind that retailers like Wal-Mart and Amazon use to determine consumer purchasing trends – police can determine where the next crime will occur and sometimes prevent it.
Colleen McCue, a behavioural scientist at GeoEye, a firm that works with US Homeland Security and local law enforcement on predictive analytics, said studying criminal behaviour was not that different from examining other types of behaviour like shopping.
“People are creatures of habit,” she said. “When you go shopping you go to a place where they have the things you’re looking for... the criminal wants to go where he will be successful also.”
She said the technology could help in cities where tight budgets were forcing patrol reductions.
The key to success in predictive policing is getting as much data as possible to determine patterns. IBM has worked with dozens of agencies such as London’s Metropolitan Police, the Polish National Police and a number of US and Canadian cities.
In Memphis, officials said serious crimes fell 30 per cent and violent crimes declined 15 per cent since implementing predictive analytics in a programme with IBM and the University of Memphis in 2006.
The programme known as Crush – Criminal Reduction Utilising Statistical History – targeted certain “hot spots” to allow police to deploy more efficiently.