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
Unforgiving Places: The Unexpected Origins of American Gun Violence
Crime Lab Pritzker Director Jens Ludwig authored a book that argues the lack of progress in reducing gun violence ultimately stems from our having misunderstood the nature of the problem, and that behavioral science gives us a new way to understand – and solve – gun violence in America.
A History of Violence
Chicago Magazine’s Paula Kamen profiles Crime Lab Pritzker Director Jens Ludwig to discuss his new book, “Unforgiving Places: The Unexpected Origins of American Gun Violence,” which offers social policy strategies for creating safer communities.
Editorial: A recognition that good policing starts from the top
The Crain’s Editorial Board highlights a $15 million gift from the Sue Ling Gin Foundation to support the Crime Lab in adapting its Policing Leadership Academy to provide management training to the Chicago Police Department’s leadership ranks.
