Computational Policy Lab

The Computational Policy Lab, led by HKS Professor of Public Policy Sharad Goel in collaboration with Professor Alex Cholas-Wood of NYU, uses technology to tackle pressing issues in criminal justice, education, voting rights, and beyond. Leveraging advances in data science, we study the impact of policy choices at unprecedented scales, and build algorithmic tools to guide high-stakes decisions. By bringing a computational perspective to public policy, our interdisciplinary team aims to improve the lives of millions of people — especially those affected by inefficient and unfair systems and practices.

The lab’s major projects include:

• PingPong: PingPong is an innovative tool that harnesses the power of large language models (LLMs) like GPT-4o for teaching and learning. It is specifically designed to facilitate learning, meaning that it won’t simply provide students with answers. This software platform allows instructors and students to create and share custom virtual teaching assistants that are available 24/7.
• Race-Blind Charging: Prosecutors have nearly absolute discretion to charge or dismiss criminal cases. There is concern, however, that these high-stakes judgments may not be made fairly. We designed an algorithm that automatically redacts race-related information from free-text case narratives, allowing prosecutors to make a race-blind decision about whether to charge each arrestee.

Visit PolicyLab.hks.harvard.edu

to learn more about the lab’s ongoing research projects, team members, and publications.