The submitted divulgative article did not quite clarify what the AI is doing - it seems like weather forecasting on crime related events, but I expected more content about "how" and "how well"; for example, you do not need AI to determine "how much", and it takes some cleverness to instead predict "when", which is one of the interesting points you want explicit.

So I found another divulgative article at Phys.org : https://phys.org/news/2022-06-algorithm-crime-week-advance-r...

and a news piece / press release at UChicago.edu : https://biologicalsciences.uchicago.edu/news/algorithm-predi...

and finally, the original research article, at: https://www.nature.com/articles/s41562-022-01372-0

I am unfortunately lacking the time now to examine the material (hopefully I will later). For now, it seems clear that the effort is not really about crime prediction but to show that some methodology can produce unbalanced police planning:

> We introduce a stochastic inference algorithm that forecasts crime by learning spatio-temporal dependencies from event reports, with a mean area under the receiver operating characteristic curve of ~90% in Chicago for crimes predicted per week within ~1,000 ft. Such predictions enable us to study perturbations of crime patterns that suggest that the response to increased crime is biased by neighbourhood socio-economic status, draining policy resources from socio-economically disadvantaged areas, as demonstrated in eight major US cities