The tool helps identify the few ‘needles in the haystack’ who pose a major danger to the community, and whose release should be subject to additional layers of review.
- Lawrence Sherman
"It’s 3am on Saturday morning. The man in front of you has been caught in possession of drugs. He has no weapons, and no record of any violent or serious crimes. Do you let the man out on police bail the next morning, or keep him locked up for two days to ensure he comes to court on Monday?”
The kind of scenario Dr Geoffrey Barnes is describing – whether to detain a suspect in police custody or release them on bail – occurs hundreds of thousands of times a year across the UK. The outcome of this decision could be major for the suspect, for public safety and for the police.
“The police officers who make these custody decisions are highly experienced,” explains Barnes. “But all their knowledge and policing skills can’t tell them the one thing they need to now most about the suspect – how likely is it that he or she is going to cause major harm if they are released? This is a job that really scares people – they are at the front line of risk-based decision-making.”
Barnes and Professor Lawrence Sherman, who leads the Jerry Lee Centre for Experimental Criminology in the University of Cambridge’s Institute of Criminology, have been working with police forces around the world to ask whether AI can help.
“Imagine a situation where the officer has the benefit of a hundred thousand, and more, real previous experiences of custody decisions?” says Sherman. “No one person can have that number of experiences, but a machine can.”
Image credit: Rene Böhmer on Unsplash
Reproduced courtesy of the University of Cambridge