Assistant Professor Sharad Goel, in the Department of Management Science & Engineering (in the School of Engineering) at Stanford University, will be teaching “Law, Order & Algorithms” (MS&E 330) this spring, on Mondays from 1:30 to 4:20 on the campus.

“Data and algorithms are rapidly transforming law enforcement and criminal justice, including how police officers are deployed, how discrimination is detected and how sentencing, probation, and parole terms are set,” he explains.

“Modern computational and statistical methods offer the promise of greater efficiency, equity, and transparency, but their use also raises complex legal, social, and ethical questions. In this course, we analyze recent court decisions, discuss methods from machine learning and game theory, and examine the often subtle relationship between law, public policy, and statistics.”

“The class is centered around several data-intensive projects in criminal justice that students work on in interdisciplinary teams,” Goel notes. “Students work closely with criminal justice agencies to carry out these projects, with the goal of producing research that impacts policy. Students with a background in statistics, computer science, law, and/or public policy are encouraged to participate. Enrollment is limited, and project teams will be selected during the first week of class.”

In addition to his role at School of Engineering, he also has courtesy appointments in both sociology and computer science. “My primary area of research is computational social science, an emerging discipline at the intersection of computer science, statistics, and the social sciences, he says on his bio. ” I’m particularly interested in applying modern computational and statistical techniques to understand and improve public policy. Some topics I’ve recently worked on are: stop-and-frisk, tests for racial bias, algorithmic fairness, swing voting, voter fraud, filter bubbles, and online privacy.”

Goel studied at the University of Chicago (B.S., mathematics) and at Cornell (M.S. in computer science; Ph.D. in applied mathematics), he notes. “Before joining the Stanford faculty, I worked at Microsoft Research in New York City.” He also worked at Yahoo Labs.

His recent classes have included “Introduction to Applied Statistics,” and “Computational Social Science.”

You can reach him at scgoel@stanford.edu.

Monica Bay is a Fellow at CodeX and a freelance journalist. She is a member of the California bar. Email: mbay@codex.stanford.edu. Twitter: @MonicaBay.

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