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.
Unraveling the Threads of America’s Gun Culture
Megan Kang, a Crime Lab affiliate and Ph.D. candidate in sociology at Princeton University, outlines new historical evidence that charts the growth in firearm ownership.
Chicago nonprofits gather to discuss progress, solutions for gun violence
CBS Chicago’s Darius Johnson speaks with the Crime Lab’s Kim Smith and Dar’tavous Dorsey about the goals of the event, which hosted nearly 50 nonprofits from every corner of Chicago for its first gun violence prevention expo.
Strides for Peace to debut Gun Violence Prevention Expo
Strides for Peace hosted a new expo focusing on gun violence prevention in Chicago, featuring an information session from the Crime Lab’s Chico Tillmon.