Big data to help curb gun violence in Chicago

Big data is now being used by law enforcement authorities to curb gun violence related crimes in the city of Chicago. The Chicago Police Department (CPD) has developed an algorithm that can help predict which people are most at risk of committing crime or being targeted by gun violence.

Past year, over 3,000 people were shot dead in gun related crimes and another 240 are dead already this year in the state of Chicago. In a city of 2.7 million, most crimes are being attributed by ‘Gangs’ as per a CPD survey. This algorithm assigns scores to people based on their criminal records as well as known gang affiliations and other variables.

A professor from Illinois Institute of Technology, DR. Miles Wernick, created the algorithm. He disclosed that the algorithm does takes a person’s past criminal activities into record, but excluded variables like race, gender, ethnicity and location.

With it, the CPD curated a 1,400-member “Strategic Subject List” that has already proven to be uncannily accurate. In 2016, over 70 percent of the people shot in the Second City have been on the list, as have 80 percent of the shooters.

According to the CPD, 117 of the 140 people arrested during a city-wide gang raid performed last week were on the list as well.

The police is not only using the list to target individuals for arrest, but is also asking social workers and community leaders to meet the people who score high on the list and attempt to intervene, offering them a way out of gang life.

So, this gives us a through proof that big data analytics is not being used in healthcare and research field, but is also helping in fighting crime and nabbing criminals.


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