British forces try out crime-predicting software | world | Hindustan Times
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British forces try out crime-predicting software

world Updated: Jul 25, 2010 23:50 IST

Two British police forces have begun trials of a sophisticated computer software package which aims to boost their efficiency by predicting where and when future crimes will take place.

The system, known as Crush (Criminal Reduction Utilising Statistical History) evaluates patterns of past and present incidents, then combines the information with a range of data including crime reports, intelligence briefings, offender behaviour profiles and even weather forecasts. This is used to identify hot spots, so police forces can allocate resources to areas where particular crimes are most likely to occur.

The technology, which belongs to a fast-growing field known as "predictive analytics", is being tested secretly in the UK following a successful long-term trial in Memphis, Tennessee, where the police department credits Crush as the key factor behind a 31% reduction in overall crime and a 15% fall in violent crime. The system has also been credited with improving morale among officers of the Memphis police by boosting arrest rates and helping them to feel as if they are "making a difference".

"This is more of a proactive tool than reacting after crimes have occurred. This pretty much puts officers in the area at the time that the crimes are being committed," said John Williams of Memphis Crime Analysis Unit.

The software behind the system has been developed by global computing giant IBM, which sees the increasing use of analytics as a massive growth area for the future and has invested more than $11bn in the field in the past four years.

The increasing use of predictive analytics by law enforcement agencies around the world has sparked inevitable comparisons with the Tom Cruise science fiction film Minority Report in which police "pre-crime" units use predictions made by psychics to apprehend potential offenders.

Earlier this year the Ministry of Justice began using predictive analytics to help predict which prisoners due for release were likely to reoffend.