As Chicago Crime Sends Businesses Packing, Scientists Create Algorithm To Detect In Advance

Chicago’s legendary crime has caused businesses to leave town amid the growing threat of violence.

“We would do thousands of jobs a year in the city, but as we got robbed more, my people operating rollers and pavers we got robbed, our equipment would get stolen in broad daylight and there would usually be a gun involved, and it got expensive and it got dangerous,” said Gary Rabine, who pulled his road paving company out of the city after his crews were repeatedly robbed.

Rabine told Fox News that the increased costs of security and insurance for “thousands” of jobs in the city eventually caused expenses to be “twice as much as they should be” per employee.

Billionaire Ken Griffin moved his firm, Citadel, from Chicago to Miami, after saying in October 2021 that “Chicago is like Afghanistan, on a good day, and that’s a problem,” adding that he saw “25 bullet shots in the glass window of the retail space” in the building he lives in.

“If people aren’t safe here, they’re not going to live here,” he told the Wall Street Journal in April. “I’ve had multiple colleagues mugged at gunpoint. I’ve had a colleague stabbed on the way to work. Countless issues of burglary. I mean, that’s a really difficult backdrop with which to draw talent to your city from.”

AI to the rescue?

Scientists from the University of Chicago have created a new “AI” algorithm that can predict crime a week in advance.

By learning patterns in time and geographic locations from publicly available data on violent and property crimes, the “AI” can predict crimes up to one week in advance with around 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.

Previous efforts at crime prediction often use an epidemic or seismic approach, where crime is depicted as emerging in “hotspots” that spread to surrounding areas. These tools miss out on the complex social environment of cities, however, and don’t consider the relationship between crime and the effects of police enforcement. –PhysOrg

The model isolates crime by analyzing time and spacial coordinates of discrete events and detecting patterns to predict future events. It worked just as well with data from seven other US cities; Atlanta, Austin, Detroit, Los Angeles, Philadelphia, Portland, and San Francisco

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Author: HP McLovincraft

Seeker of rabbit holes. Pessimist. Libertine. Contrarian. Your huckleberry. Possibly true tales of sanity-blasting horror also known as abject reality. Prepare yourself. Veteran of a thousand psychic wars. I have seen the fnords. Deplatformed on Tumblr and Twitter.

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