Fairness, Incentives, and Mechanism Design
Penn State | IST 597: Special Topics on AI/DS | Fall 2022
Time and location: Tuesday & Thursday, 9:05 am - 10:20 am
Instructor: Hadi Hosseini
Office hours: Wednesday 11:00 am - 12:00 pm on Zoom (or in person: Westgate Building E377)
Fairness, Incentives, and Mechanism Design is a graduate-level course that surveys the principles and algorithmic foundations of robust decision-making with provable societal guarantees that are primary building blocks in the grand scheme of Artificial Intelligence (AI) and economics for social good. The course introduces the foundations for fair and efficient decision making when multiple interested parties such as humans, institutions, or autonomous agents interact with one another. Topics include concepts within mechanism design and social choice such as preference aggregation, fair division, matching theory, and applications such as crowdsourcing and healthcare resource allocation.
Evaluation: course evaluation is based on homework assignments (2 x 10%), paper critiques (20%), participation (15%), and a course project (45%). The projects should include solid and non-trivial implementations and/or novel research questions.
Textbooks
The following books are not required but highly recommended. These books are generally available online for free.
Handbook of Computational Social Choice
Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, and Ariel D. Procaccia, Cambridge University Press, 2016.Economics and Computation: An Introduction to Algorithmic Game Theory, Computational Social Choice, and Fair Division
Editors Jörg Rothe, Springer-Verlag Berlin Heidelberg 2016.Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Kevin Leyton-Brown and Yoav Shoham, Cambridge University Press.