The Center for Data Science and Public Policy (DSaPP) at the University of Chicago is a joint center between  The Harris School of Public Policy and the Computation Institute to further the use of data science in policy research and practice.

DSaPP is a leader in data science for public policy and social problems. We work on projects with government and non-profit partners to solve high-impact social problems using data science, create scalable, data-driven systems for improving public health, education, public safety, and economic development, and develop trainings, methods, and tools to ensure ethical and fair use of data driven methods in public policy.

We bring together data scientists, researchers, and practitioners from Computer Science, Statistics, Math, Physical Sciences, Social Sciences, and Public Policy. Our work uses design and systems thinking to develop reusable, open-source software tools and data products. We combine methods and tools from predictive analytics and machine learning with rigorous social science methods to build systems that help solve large-scale social challenges. Our research focus is on developing methods that help make data science, machine learning, and artificial intelligence tools being used to make policy decisions fair, ethical, understandable, and transparent.

We’re always interested in partnering with researchers, practitioners, and organizations on trainings, projects, and research. Please contact us if you have a problem or idea that you want to collaborate with us on.