New Algorithm Can Predict Future Crime a Week In Advance, With 90% Accuracy
Published on July 01, 2022 at 03:32AM
An anonymous reader quotes a report from PsychNewsDaily: Scientists from the University of Chicago have developed a new algorithm that can predict future crime a week in advance with about 90% accuracy, and within a range of about 1000 feet. It does so by learning patterns from public data on violent and property crimes. 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, unlike drug crimes, traffic stops, and other misdemeanor infractions. 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. Previous models relied more on traditional neighborhood or political boundaries, which are 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. Lead author Ishanu Chattopadhyay is careful to note that the tool's accuracy does not mean it should be used to direct law enforcement policy; police departments, for example, should not use it to swarm neighborhoods proactively to prevent crime, Chattopadhyay said. Instead, it should be added to a toolbox of urban policies and policing strategies to address crime. "We created a digital twin of urban environments. If you feed it data from what happened in the past, it will tell you what's going to happen in the future," he said. "It's not magical; there are limitations, but we validated it and it works really well," Chattopadhyay added. "Now you can use this as a simulation tool to see what happens if crime goes up in one area of the city, or there is increased enforcement in another area. If you apply all these different variables, you can see how the systems evolve in response." The findings have been published in the journal Nature Human Behavior.
Published on July 01, 2022 at 03:32AM
An anonymous reader quotes a report from PsychNewsDaily: Scientists from the University of Chicago have developed a new algorithm that can predict future crime a week in advance with about 90% accuracy, and within a range of about 1000 feet. It does so by learning patterns from public data on violent and property crimes. 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, unlike drug crimes, traffic stops, and other misdemeanor infractions. 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. Previous models relied more on traditional neighborhood or political boundaries, which are 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. Lead author Ishanu Chattopadhyay is careful to note that the tool's accuracy does not mean it should be used to direct law enforcement policy; police departments, for example, should not use it to swarm neighborhoods proactively to prevent crime, Chattopadhyay said. Instead, it should be added to a toolbox of urban policies and policing strategies to address crime. "We created a digital twin of urban environments. If you feed it data from what happened in the past, it will tell you what's going to happen in the future," he said. "It's not magical; there are limitations, but we validated it and it works really well," Chattopadhyay added. "Now you can use this as a simulation tool to see what happens if crime goes up in one area of the city, or there is increased enforcement in another area. If you apply all these different variables, you can see how the systems evolve in response." The findings have been published in the journal Nature Human Behavior.
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