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
The best way to cut gun violence, and it’s almost free
In an op-ed for Crain’s Chicago Business, Crime Lab Pritzker Director Jens Ludwig highlights the importance of using data-informed practices to improve public safety and shares key insights from behavioral economics that provide a playbook for addressing gun violence that is both effective and low-cost.
Research on cognitive behavioral therapy for at-risk youth
Dr. Nour Abdul-Razzak joins host Jennifer Doleac on the Probable Causation podcast to discuss the Choose to Change program—an intervention that integrates trauma-informed therapy with comprehensive support to reduce youth violence and improve educational outcomes.
Deaths of decision-making are killing American teens. Schools can fix it.
Crime Lab executive director Katie Hill pens an op-ed for Brookings about how cognitive behavioral programs can teach teens decision-making skills that can dramatically reduce violence and save lives – often at little or no additional cost.
