Course Policies
Table of contents
About
Fairness is a recurring theme in game theory, social choice theory, political philosophy, and ethics. Today, as AI systems influence critical decisions—from loan approvals to criminal risk assessments—it is crucial to understand when algorithms are fair. This course is divided into four parts, each focused on different ways that fairness considerations influence individual and group decision-making:
- Fairness norms and social preferences;
- Fair division;
- Fair representation; and
- Algorithmic fairness.
This course equips students to identify fairness trade-offs, analyze competing fairness criteria, and evaluate both human and algorithmic decision-making systems.
Resources
Readings: The readings for the course will be made available on the course website.
PollEverywhere: We will use PollEverywhere for in-class quizzes and surveys. You can sign-up (for free) using the following link.
Piazza: This term we will be using Piazza for questions and discussion. The system is highly catered to getting you help fast and efficiently from me and your classmates. Rather than emailing questions to me, I encourage you to post your questions on Piazza (available on the course website).
Weekly Schedule/Due Dates
The tentative weekly schedule:
- In-person lectures on Mondays and Wednesdays 2:00pm - 3:15pm in TWS 0223.
- Throughout the week, use Piazza to ask questions about the problem sets, reading or lectures, or anything else you might want to discuss related to the course.
- Submit your weekly reflection by Friday at 11:00pm.
Course Requirements
The course requirements are:
Participation: There will be a number of short quizzes given periodically during the semester. Typically, these short quizzes will consist of 1 question that is given during class using PollEverywhere, but some lectures may have more than 1 question. Make-up quizzes will not be offered. I will drop the lowest 5-10% of the quizzes (so you can miss some of the questions without losing any points).
Weekly reflection: Students must submit a weekly reflection on ELMS. Each week, you will be asked to describe one thing that surprised/confused/interested you from the readings and/or the lectures during week, or an example you observed of an interaction that illustrates some issue discussed that week. Your reaction should be approximately 200 words. Each weekly reflection is worth 5 points and is due Friday at 11:00pm. You will be graded, in part, on how it relates to the material discussed that week.
Problem Sets: There will be 4 problem sets (after each part). Problem sets will be submitted through the course website. You can use your notes, the readings, and the online textbook, but you should not discuss your answers with your classmates or use any AI tools, such as ChatGPT, to answer these questions.
Final exam: There will be an in-person final exam given during finals week. Consult https://registrar.umd.edu/registration/register-classes/final-exams/fall for more information about the time and location of the final exam.
Topics
Below is a list of topics that we will discuss during the semester.
- Ultimatum game and social preferences
- Nash bargaining game
- Evolutionary game theoretic models of fairness
- Criticisms of evolutionary game-theoretic models of fairness
- Fair division of indivisible goods
- Pardoxes of fair division
- Fair division of divisible goods
- Using lotteries to ensure fairness
- Fairness in group decision-making
- Fairness in machine learning
- Algorithmic fairness and statistical discrimination
Grades
Grades will be assigned according to the following weights:
| Activity | Percent |
|---|---|
| Participation | 25% |
| Problem Sets | 30% |
| Weekly Reflections | 30% |
| Final Exam | 15% |
Support
It’s expected that some aspects of the course will take time to master, and the best way to master challenging material is to ask questions. For online questions, use Piazza.
UMD has many resources available to help students. Below are links to some resources that you might find helpful.