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
#CelebratePolicyImpact: Crime Lab’s Research Expands Drug Treatment Access
The Association for Public Policy Analysis and Management (APPAM) highlights the Crime Lab’s study of Chicago’s Narcotics Arrest Diversion Program (NADP), a local agency collaboration that seeks to address the root causes of substance use by offering treatment in lieu of prosecution.
Jens Ludwig — Unforgiving Places: The Unexpected Origins of American Gun Violence
Join Crime Lab Pritzker Director Jens Ludwig for a book talk and signing at Politics and Prose Bookstore at Union Market in Washington, DC for his upcoming book, “Unforgiving Places: The Unexpected Origins of American Gun Violence.”
Jens Ludwig and Chief Bill Scott: The Unexpected Origins of Gun Violence
Join Crime Lab Pritzker Director Jens Ludwig for a book talk and signing at The Commonwealth Club in San Francisco, CA for his upcoming book, “Unforgiving Places: The Unexpected Origins of American Gun Violence.”
