Reducing Pretrial Incarceration with Open-Source Technology
Every day, American jails hold half a million people who have not been convicted of a crime. This reality creates social and economic hardships for individuals who might be held for months awaiting court dates and costs local governments $13.6 billion each year. In California's Santa Clara County, approximately 30% of clients fail to appear for scheduled court dates annually, resulting in bench warrants for their arrest. In other jurisdictions, this rate can reach as high as 50%.
Funded by a 2020 Stage 2 investment, the Computational Policy Lab (CPL) teamed up with the Santa Clara County Office of the Public Defender and The Bail Project to conduct research aimed at reducing pretrial incarceration by using text message reminders and behavioral nudges to help defendants remember and attend mandatory hearings.
The team’s initial study with 2,540 defendants showed that sending text message reminders through their open-source app (at 7 days, 3 days, and 1 day before court dates) reduced both warrants issued and pretrial incarceration by approximately 20%. CPL is now testing whether different reminder templates perform better and whether monetary assistance can help overcome financial barriers to court attendance.
2020 and 2021 PhD Fellow
Quantitative Researcher, Citadel Securities
2023 Scholar in Service; Associate Professor, Computer Science
Faculty Co-Director, Computational Policy Lab
PhD Candidate, Harvard University
Founder , Computational Policy Lab
Engineer, Computational Policy Lab
Lead Engineer, Computational Policy Lab
Assistant Professor, University of Michigan, School of Information