Using Machine Learning to Address the Second Chance Gap

Students: Jeff Huang, Nicholas Chaudoir, Vanessa Sanchez, Reeti Joshi, Shelby Anderson, Gabriel Aviles

Faculty Mentor: Caitlin Henry

Criminology & Criminal Justice Studies

College of Humanities, Social Sciences, and the Arts

California public defenders, district attorneys, advocates, and legislators face challenges in implementing second look sentencing, including: (1) lack of data access; and (2) challenges with understanding and analyzing data. In the context of prison-initiated resentencing proceedings, this project will build a machine learning AI tool that can examine trends in what scholars have called a "second chance gap," defined as the difference between eligibility and delivery of second chance relief.