Machine Learning
Machine learning tools continually leverage data to “learn” and improve performance — whether that’s cleaning datasets or analyzing the data within them to make recommendations.
Good data is essential to developing successful interventions to reduce violence and reform our criminal justice system. But too often, public safety datasets are disjointed or otherwise incomplete, which makes it difficult to analyze the effects of an intervention. Machine learning tools can strengthen data analysis by gathering information across multiple datasets or by making predictions based on trends in the data — allowing researchers to analyze data more efficiently.
The Crime Lab team is utilizing and developing machine learning tools to expand and improve our data analysis capacity within many of our projects.
Latest Updates
What new tactic Knoxville police and city officials say helped reduce shootings in 2024
The Knoxville News Sentinel’s Myron Thompson cites a Crime Lab study showing that streets with more lighting see a decline in crime.
Chicago violence: City sees fewer than 600 murders in 2024 for 1st time since 2019; shootings, carjackings also down
ABC 7’s Craig Wall covers the Crime Lab’s year-end analysis of crime trends in Chicago showing that despite encouraging signs of progress, Black Chicagoans are still 20 times more likely than their white counterparts to be killed by a gun or to be a victim of a homicide.
Maintaining violent crime decline is Chicago’s evergreen resolution
The Chicago Sun-Times Editorial Board provides commentary on the promising declines in violence from the Crime Lab’s end-of-year analysis and the need for continued support for successful violence prevention programs.
