Law, Algorithms, and Justice (Fall 2023)

Welcome!

This course will examine the relationship between law, technology, and public policy. We will analyze the legal and ethical principles for assessing the equity of algorithms; examine techniques for promoting algorithmic fairness, accountability, and transparency; and consider how law, policy, and algorithms should each change to produce a more just society.

Algorithms and machine learning are rapidly transforming our society, including both civil and criminal legal systems. Algorithms are now adept at specialized tasks including speech recognition, decision support systems, prediction and forecasting, image classification, and more. Within our legal system, algorithms have supplanted human decision makers to determine where police should patrol, who should receive government benefits, how long people should be incarcerated, and who should be investigated for child neglect or abuse, among other examples.

The hope is that modern computational and statistical methods can increase the accuracy and efficiency of legal decision-making while reducing human bias and error. The concern is that these tools can be unaccountable “black boxes” that reproduce bias and erode personal privacy, all while concealing these harms behind a mask of scientific objectivity. In recent years, many groups have called for the regulation of A.I. systems according to principles that include fairness, accountability, and transparency. A growing body of interdisciplinary scholarship explores how these principles might be defined, understood, and applied in practice.

Throughout the course, we will engage with a range of perspectives from law, computer science, philosophy, and sociology. Reading assignments will include interdisciplinary scholarly writing, judicial opinions, technical writing, and popular commentary. The class will be discussion-based and case-study driven, with a focus on current events and real-world applications.

To take this class, there is no requirement for any level of technical expertise.