Since late 2015, gun violence in Chicago has increased greatly. This is why the majority of the news media now focused their attention towards the city’s strategies to address the issue with the use of the Strategic Subject List (S.S.L.).

An algorithm created the list that attempts to predict individuals who could potentially be involved in a shooting, whether as a victim or perpetrator. Although they did not yet make the algorithm available to the public, the city published an online version of the list without the names via an open data portal. For the first time, they finally made it possible to see how the city gauges threat.

They evaluated the data and discovered that the appointed threat scores and their particular characteristics can be at odds with the public statements of the Chicago Police Department and get rid of the common opinions.

  • Chicago’s violence is not that condensed at the top – between a group of around 1,400 individuals with the highest threats scores – compared to a few public observations that the Chicago police suggested.
  • Gangs are typically attributed to the overwhelming surge in gun violence in the city, but gang membership had a minor predictive impact and is being removed from the algorithm’s most recent version.
  • Being a shooting or assault victim is far more foretelling of gun violence in the future compared to getting arrested on charges of weapons possession or domestic violence.
  • The Chicago has been using this algorithm for several years, and its usefulness is far from distinct. Chicago reported a massive portion in the surge of urban murders a year before.

The threat scores can be helpful in foreseeing violence, but their value as a piece of the crime-fighting resource in Chicago is still questionable. Murder rate in the city is significantly greater compared to what it was before violence began increasing a couple of years ago.

Who knows, crime would probably be even worse without the use of threat scores. It’s difficult to tell exactly at the moment because several aspects can lead to crime fluxes. However, it appears to be clear that taking full advantage of the algorithm’s score may necessitate recognizing new means of avoiding risk from turning into a reality.

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