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
UChicago Crime Lab’s Mayoral Public Safety Pledge
Chicago has a high-stakes mayoral election coming up in 2027. Given our dire budget situation, what should – or even can – whoever is in charge next do to address the city’s top priority: gun violence?
Senate Passes Promoting Police Leadership Act Inspired by University of Chicago’s PLA
The U.S. Senate passes the bipartisan Promoting Police Leadership Act, landmark legislation that draws heavily from the University of Chicago Crime Lab’s Policing Leadership Academy (PLA).
UChicago Crime Lab’s Policing Leadership Academy Informs First-Ever Bipartisan Federal Legislation to Expand Commander-Level Law Enforcement Training
Bipartisan Promoting Police Leadership Act, introduced by Senators Cornyn and Whitehouse, draws on UChicago model to set national standards