Researchers are using AI to predict criminal activity

Back in 2016, for instance, the Chicago Police Department became embroiled in controversy for creating a database of people deemed most at risk of being involved in a shooting – either as a victim or assailant. They referred to this as the city’s ‘heat list.’

The contents fed through the AI algorithm were initially kept secret, until the machine egregiously suggested that 56% of Black men within the city (aged 20 to 29) would feature on it.

Oh please, we have been through all this before. It doesn’t work. There is no magic AI “one weird trick” to solve crime. https://t.co/8Jl8fcfOeI

— Timandra Harkness (@TimandraHarknes) July 5, 2022

There’s a solid argument to be made, that because of the way in which crimes are recorded, the whole system was susceptible to bias before even beginning.

Crimes within Chicago’s wealthier areas have been proven to lead to more arrests, for one, and we know that minority groups, certainly within lower socioeconomic levels, are disproportionately stopped and searched.

Chattopadhyay concedes that the newest data will inevitably be slightly biased, but says that efforts have been taken to reduce this. He clarified that his AI doesn’t identify suspects, only potential sites of crime. ‘It’s not Minority Report,’ he reassured.

Speaking with some trepidation on the subject, Cambridge expert Lawrence Sherman warned: ‘It could be reflecting international discrimination by police in certain areas.’ It’s hard to alleviate those worries too.

As long as policing efforts rely on criminal infraction reports state to state, which brings to head the complex relationship between enforcement, misconduct, and wider society, using AI for direct crime prevention appears too murky to fully get on board with.

If, on the other hand, researchers are keen to utilise AI technology to unearth where these biases exist, that would be a far more agreeable prospect.