SoylentNews is people
SoylentNews
A new computer model uses publicly available data to predict crime accurately in eight U.S. cities:
Advances in machine learning and artificial intelligence have sparked interest from governments that would like to use these tools for predictive policing to deter crime. Early efforts at crime prediction have been controversial, however, because they do not account for systemic biases in police enforcement and its complex relationship with crime and society.
Data and social scientists from the University of Chicago have developed a new algorithm that forecasts crime by learning patterns in time and geographic locations from public data on violent and property crimes. The model can predict future crimes one week in advance with about 90% accuracy.
In a separate model, the research team also studied the police response to crime by analyzing the number of arrests following incidents and comparing those rates among neighborhoods with different socioeconomic status. They saw that crime in wealthier areas resulted in more arrests, while arrests in disadvantaged neighborhoods dropped. Crime in poor neighborhoods didn't lead to more arrests, however, suggesting bias in police response and enforcement.
[...] The new model isolates crime by looking at the time and spatial coordinates of discrete events and detecting patterns to predict future events. It divides the city into spatial tiles roughly 1,000 feet across and predicts crime within these areas instead of relying on traditional neighborhood or political boundaries, which are also subject to bias. The model performed just as well with data from seven other U.S. cities: Atlanta, Austin, Detroit, Los Angeles, Philadelphia, Portland, and San Francisco.
This strikes me as something more useful for determining where to improve crime prevention strategies (better lighting, etc.) than it is for catching perps in action.
Journal Reference:
Rotaru, V., Huang, Y., Li, T. et al. Event-level prediction of urban crime reveals a signature of enforcement bias in US cities. Nat Hum Behav (2022). DOI: 10.1038/s41562-022-01372-0
This AI Algorithm Supposedly Predicts Big City Crime Before it Happens. Is That a Good Idea?
Claims to predict future crimes a week in advance with 90% accuracy. So much for free will and all that ...
(Score: 5, Insightful) by looorg on Sunday July 10 2022, @12:14AM (2 children)
Yes, more or less. I have not read the paper yet but I put it on the to read list when I get back to the office (cause I'm not paying for something I can read for free at work) but I wouldn't hold my breath bases on the abstract and some other sources. If this actually works like Minority Report it would basically revolutionize Criminology, Law and Law Enforcement. But it won't.
That said it's not Minority Report levels since it can't really mind read people. As in we won't know who will do the crime. It's more like it's very likely that this will happen now or in a week based on previous factors. In a lot of cases you don't even need this model for that level of prediction. But if they think it will happen then in some best case scenario they will increase patrols in the area. It's not detailed or on the level of sending out Tom Cruise to tranq (or eliminate) people.
There is also a very real possibility that all this model shows is where police go to make easy busts or pointing out areas with an already high crime rate. So it's not that they are really telling police something they don't already know as they already know which are the high crime areas of the city and well then it's not really a surprise that crime happens there. So they already tend to patrol there. Which means they bust people there which creates more data for the model to show how correct it is and round and round it goes. So while the headline sounds like awesome it's not really as fantastic as one is somewhat led to believe.
(Score: 1, Interesting) by Anonymous Coward on Sunday July 10 2022, @03:18AM
I think the "predict crime" part will probably be even less impressive than the headline makes it sound once you dig into it. It sounds like they added a temporal variable to the spatial "crime hot spots" maps (and it seems they may have used used higher spatial fidelity than previously). So instead of showing the streets with all the pubs in red on a map for public intoxication and fighting arrests, they can now show that Monday through Thursday there isn't much of that on the street, but it peaks on Friday and Saturday nights, so they've predicted when those infractions are most likely to occur. The researcher is correct in that this might be a useful tool to help police departments optimize their available resources.
(Score: 2) by krishnoid on Sunday July 10 2022, @03:51AM
And while you're at work, you're getting paid to read it! Win-win.