Teaching

Quantitative Analysis and Empirical Methods

API-201 · Fall 2023

This MPP core course introduces students to a range of analytic tools commonly used to inform public policy issues. Key content falls in the areas of descriptive statistics, probability theory, decision analysis, statistical inference, and qualitative approaches, with an emphasis on the ways in which they are applied to practical policy questions. The course also provides students with an introduction to the statistical programming language R, a powerful tool to analyze quantitative data.

Law, Order, and Algorithms

DPI-617 · Spring 2024

Data and algorithms are rapidly transforming law enforcement and the criminal legal system, including how police officers are deployed, how discrimination is detected, and how sentencing, probation, and parole terms are set. 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 examine the often subtle relationship between law, public policy, and technology, drawing on recent court decisions, and applying methods from machine learning and game theory. We survey the legal and ethical principles for assessing the equity of algorithms, describe computational techniques for designing fairer systems, and consider how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. Concepts will be developed in part through guided in-class coding exercises, though prior programming experience is not necessary.

The Science and Implications of Generative AI

DPI-681M · Spring 2 Module 2024

The latest generation of “generative AI” can produce novel content — including essays, computer code, and artwork — that is often hard to distinguish from materials produced by humans. “The Science and Implications of Generative AI” is an interdisciplinary course designed to equip you with a solid understanding of how generative AI works, how to use it, and the larger opportunities and challenges it poses for society. This course blends technical learning with hands-on experiences, encouraging you to explore the inner workings of modern AI models, such as ChatGPT, while engaging in practical applications of these systems. Through case studies, simulations, and project-based assignments, you will learn to assess the advantages and risks of deploying generative AI. The curriculum underscores the significance of informed policymaking in this rapidly evolving field, seeking to ensure that HKS graduates can harness AI technology responsibly for the benefit of society.