Real-life Minority Report as crooks will be caught before crime takes place using AI

UK forces are already testing around 100 AI projects, with tech designed to keep the ‘eyes of the state’ on offenders ‘at all times’. It echoes Tom Cruise movie Minority Report

Police could bust crooks before a crime happens in futuristic plans ripped straight out of the sci-fi film Minority Report.

UK forces are already testing around 100 AI projects, with tech designed to keep the “eyes of the state” on offenders “at all times”. One aims to identify Britain’s top 1,000 most dangerous predators who pose the highest risk to women and girls.

Home Secretary Shabana Mahmood is set to unveil the high-tech crackdown next week. A government source said: “This doesn’t mean watching people who are non-criminals, but she feels like if you commit a crime, you sacrifice the right to the kind of liberty the rest of us enjoy.”

Tom Cruise flick Minority Report, released in 2002, imagines a chilling future where police nab people for crimes they haven’t even done yet.

Sir Andy Marsh, head of the College of Policing, said “predictive analytics” has already helped catch perverts. He said: “It’s far from uncommon for these individuals to move from one female victim to another.

“We understand all of the difficulties of bringing successful cases to bear in court. So what we want to do is use these predictive tools to take the battle to those individuals, so that they are the ones who are frightened because the police are coming after them, and we’re going to lock them up.”

The Government is ploughing £4m into building an interactive AI-driven map of England and Wales within the next four years. It will use data to track recent crime and identify areas likely to see incidents, such as knife attacks, escalate.

But critics have warned the tech must be tested properly and have human oversight.

Ms Mahmood told MPs that AI was an “incredibly powerful tool that can and should be used by our police forces”. She insisted it would be regulated in a way that was “always accurate”.

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