An Algorithm Can Predict All Types Crimes Weeks In Advance | Intelligent and Tireless Police Force

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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.

The tool was tested and validated using historical data from the City of Chicago around two broad categories of reported events: violent crimes (homicides, assaults, and batteries) and property crimes (burglaries, thefts, and motor vehicle thefts). These data were used because they were most likely to be reported to police in urban areas where there is historical distrust and lack of cooperation with law enforcement. Such crimes are also less prone to enforcement bias, as is the case with drug crimes, traffic stops, and other misdemeanor infractions.

Source: https://Phys.org/