ESE 3090-Social Choice Systems 

Description

Social choice systems are all around us, from how we decide to split the check to who becomes president. This course introduces many conceptual and computational problems in the study of systems of social choice and offers a variety of tools to understand them. We will consider both micro and macro social choice systems; for the latter drawing on modern statistical techniques to understand (and reframe) questions like "what is a fair map of congressional districts?" In order to address modeling and design challenges in social choice systems we'll explore mathematical and software tools such as game theory, linear optimization, Monte Carlo / MCMC methods, and geographical data representation in Python.

The course has (loosely) three sections:

• Weeks 1-5: Social choice theory  what are social choice systems and how do we analyze or evaluate them?

• Weeks 6-9: Computational voting theory  what are some more modern social choice systems that protect against manipulation?

• Weeks 10-15: Redistricting problems  how do we design fair electoral district maps?

This class uses many features from inquiry-based learning and so class spaces may feel different to other courses you've taken.

Timings

• Class: TuTh 2:30-3:50pm in Lopata 103.

• Office hours: Tu 4-5pm, W 11-12pm in Green 2155.

Resources

The course will draw from several resources including:

• Mathematics & Politics, Alan D. Taylor and Allison M. Pacelli (freely available through Springer with WashU login)

• Handbook of Computational Social Choice, ed. Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang and Ariel D. Procaccia (freely available through CUP)

• Political Geometry, ed. Moon Duchin and Olivia Walch (freely available here).

We will also likely reference the following articles:

• The Myth of the Condorcet Winner, Paul Edelman (freely available here)

• Monotonic Power Indices, Gina Richard (freely available here)

• Enlargement of the EU and Weighted Voting in its Council of Ministers, Dan S. Felsenthal and Moshé Machover (freely available here)

• Luxembourg in the Early Days of the EEC, Alexander Mayer (freely available here)

• Schulze's Beatpath Voting Method, RangeVoting.org (link)

• An Impossibility Theorem for Gerrymandering, Boris Alexeev and Dustin G. Mixon (freely available here)

• The Adjusted Winner Procedure: Characterizations and Equilibria, H. Aziz, S. Brânzei, A. Filos-Ratsikas and S. Frederiksen (freely available here).

Safe + Brave

This is a largely discussion-based course where we will all commit to cultivating a safe and brave environment for all students to participate in. We use the five pillars of Arao and Clemens to frame what such a space consists of:

• “Controversy with civility” where varying opinions are accepted,

• “Owning intentions and impacts” in which participants acknowledge and discuss instances where a dialogue has affected the emotional well-being of another person,

• “Challenge by choice” where participants have an option to step in and out of challenging conversations,

• “Respect” where students show respect for one another’s basic personhood,

• “No attacks” where students agree not to intentionally inflict harm on one another.

You can also feel very free to call me out on words or actions that hinder these aims. Here is an anonymous google form where you can let me know about any concerns.

Key Connections

• (Computational) social choice theory

• Graph theory

• Voting theory

• Linear programming / optimization

• Monte Carlo / MCMC methods

• Python (geo)pandas

Assessment

• Project - due 11:59pm, 12/7; "late" due date 12/10 (25%)

• Participation (25%)

  • • preparing for and actively engaging in discussion (10%)

    • ~biweekly self-reflections (15%)

• Homework (25%)

• Midterm "assessed conversation" on 10/16 or 10/17 (25%)

Completion: We will allow for one missed reflection without impacting your grade. After this point, each missed reflection counts as -3% of your grade up to -15%. We will drop your lowest homework score at the end of the semester.

Virtual testing: We will offer a virtual option for exams and quizzes in circumstances such as quarantine due to sickness or potential exposure to covid-19.

Late submission: The final project is due at 11:59pm. It can still be submitted until 10am the next day but may receive a 10% penalty (applied to the grade they receive, so if you score 90% it will count as 81%).

Makeups: Because of the features above we don't allow for makeups under any circumstances.

Praxis: Each homework contains a 'praxis prompt' where you will practice an additional academic skill.

Integrity

• Attempting to cheat in this course is unacceptable and will be strongly penalised. A first offense will be penalised with a zero grade on the relevant piece of assessment. A second offense will be penalised with an immediate fail grade. Using generative AI without citation is an instance of cheating.

• Collaboration is permitted (actually encouraged!) on homework assignments, however each student must write up solutions in their own words.  Please write the names of any other students you have collaborated with at the top of each assignment. Significant similarities between submissions from different students that fail to mention any collaboration counts as an act of cheating and will be penalised as such.

Other Information

• This is a 3 credit class.

• There is no online option for the class except as described above for assessment.

• Prerequisites: ESE 105 (or equivalent)

• Final letter grades will be distributed according to the scale A- 90%, B- 80%, C-70%, D-50%. There are no minuses in the course and pluses will be distributed at discretion of the instructor to recognize outstanding academic engagement and/or contributions to class community.

• Attendance to class or recitation is not required but, as with any advanced STEM class, will usually impact your learning. Notes from class will be posted each week.

• I encourage you to discuss with me, my department chair, or your academic advisor(s) about any concerns you have around classroom dynamics.

• This class will involve a meaningful amount of coding in either Matlab or Python (your choice).

Relevant Policies

• In all academic work, the ideas and contributions of others (including generative artificial intelligence) must be appropriately acknowledged and work that is presented as original must be, in fact, original. You should familiarize yourself with the appropriate academic integrity policies of your academic program(s).

• Except as otherwise expressly authorized by the instructor or the university, students may not record, stream, reproduce, display, publish or further distribute any classroom activities or course materials. This includes lectures, class discussions, advising meetings, office hours, assessments, problems, answers, presentations, slides, screenshots or other materials presented as part of the course.  If a student with a disability wishes to request the use of assistive technology as a reasonable accommodation, the student must first contact the Office of Disability Resources to seek approval. If recording is permitted, unauthorized use or distribution of recordings is also prohibited.  

• WashU supports the right of all enrolled students to an equitable educational opportunity and strives to create an inclusive learning environment. In the event the physical or online environment results in barriers to your inclusion due to a disability, please contact WashU’s Disability Resources (DR) as soon as possible and engage in a process for determining and communicating reasonable accommodations. As soon as possible after receiving an accommodation from DR, send me your WashU Accommodation Letter. Remember that accommodations cannot be applied retroactively.

• If you are a victim of sexual discrimination, harassment or violence, we encourage you to speak with someone as soon as possible. Understand that if you choose to speak to your instructor, they must report your disclosure to their department chair, dean, or the Gender Equity and Title IX Compliance Officer, which may trigger an investigation into the incident. You may also reach out to the Relationship & Sexual Violence Prevention (RSVP) Center to discuss your rights and your options with individuals who are not mandatory reporters -- further resources are available here.

• To ensure that accommodations may be made for students who miss class, assignments, or exams to observe a religious holiday, you must me over email before the end of the third week of class, or as soon as possible if the holiday occurs during the first three weeks of the semester. For more information, please see the university's Religious Holiday Class Absence Policy.

• Before an emergency affects our class, students can take steps to be prepared by downloading the WashU SAFE App.  In addition, each classroom contains a “Quick Guide for Emergencies” near the door.

• WashU provides many resources to support services that address academic, personal, and professional needs.  You can explore resources that might help you here.