Instructor: Amélie Marian
Office hours: Thursdays 2-3pm CoRE 324
TA: Cory Margarucci
Office hours: TBA
Class Announcements
will be posted via Canvas. If you are registered for the course and do not see
the course on Canvas (once the semester has started), please contact the
instructor.
9/2: Recitations will start
on 9/8 (note Monday schedule on Tuesday 9/8)
This class will introduce students to various types of algorithms used for real-world decisions in a wide range of applications: public policy, health, e-commerce, justice. We will discuss the social impacts of algorithmic decisions, their legal implications, and the need for transparency and accountability in algorithmic decision-making. The class will cover topics such as bias in data and processes, fairness, game theory, and trust, as they relate to algorithms.
The class will focus on hands-on projects and discussions that will give students an understanding of a participatory design, and include them as stakeholders of the algorithms they are implementing.
The course will give students a critical understanding of the often competing goals of efficiency and optimization with those of transparency, accountability and fairness, which are necessary for trust and widespread adoption of automated decision systems. It will teach them to consider all stakeholders of a decision process, as well as the broader impacts of their algorithmic designs.
Recitations
Recitations will consist of labs, using Python Jupyter notebooks, that alternate between implementations of the algorithms discussed in class on case studies, and building components to use in the class projects.
Recitations: Mondays 7:45 PM - 8:40 PM Livingston BE-252
Prerequisites
CS210 or CS112 and knowledge of Python, or by permission of instructor.
Grading will be based on 3 projects, (60%), recitation labs and participation activities (20%), and a midterm (20%) .
Readings will be posted on Canvas.
|
Date |
Topics |
Class Activities and Assignments |
|
Thu
September 3 |
|
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Thu
September 10 |
|
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|
Gale-Shapley Algorithm. Top-trading Cycles. Stable
Roommates. |
Activity: Resource Allocation. |
|
Thu
September 24 |
Real-life matchings. Priorities, set-aside, Fairness Lifecycle of the Algorithms, Errors |
Activity:
Participatory Grading (1/2) |
|
|
|
Activity: Fairness. |
|
|
Voting
Algorithms. Ranked Choice Voting. |
Activities:
In-class Voting, Voting for Candy. |
|
|
Redistricting and Gerrymandering |
|
|
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Lottocracy, Sortition |
Activity:
Sortition. |
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Exam (tentative) |
|
|
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Privacy and
Anonymization |
Activity:
De-anonymizing data. |
|
|
Auctions |
|
|
|
Predictions |
Activity: AI Detection |
|
|
Fair
Division |
Activity:
Fair Grading |
|
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||
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|
|
|
Wrapping up. |
|
This course will heavily rely on course discussions and activities. Students are expected to be present and participate in the discussions, but should prioritize their health and safety.
If you cannot attend class, please let the instructor know. Students will not be penalized for notified absences.
Students in need of disability accommodations to register for accommodations and consult the policies and procedures of the Office of Disability Services website: https://ods.rutgers.edu
Some topics covered in the class will relate to ethics and fairness in automated decision systems, as well as the need for diverse viewpoints when designing algorithms. Disagreements on some of these issues are expected, and part of the learning experience. Students are expected to behave in a respectful manner towards everyone in the course, to ensure that all participants in the class feel welcome and supported.
Rutgers University takes academic dishonesty very seriously. By enrolling in this course, you assume responsibility for familiarizing yourself with the Academic Integrity Policy and the possible penalties (including suspension and expulsion) for violating the policy. As per the policy, all suspected violations will be reported to the Office of Student Conduct. Academic dishonesty includes (but is not limited to):
· Cheating
· Plagiarism
· Aiding
others in committing a violation or allowing others to use your work
· Failure
to cite sources correctly
· Fabrication
· Using
another person's ideas or words without attribution, including re-using a
previous assignment Unauthorized collaboration
· Sabotaging
another student's work
If you are ever in doubt, consult your instructor.
Please familiarize yourself with the University Academic Intgrity Policy http://nbacademicintegrity.rutgers.edu/
In the last few years, we have all been going through a lot, individually and together. It is important to acknowledge that events and circumstances outside of the classroom can impact our ability to be present and engaged at any given moment. At Rutgers, we are focused on the whole student. If, at any point, you experience anything impacting your performance or ability to participate in this class, please reach out to me. Please also see the academic, health, and mental wellness resources on the syllabus as well as others searchable at https://success.rutgers.edu/ for further support.
Additional support resources:
· Student
Success Essentials: https://success.rutgers.edu
· Student
Support Services: https://www.rutgers.edu/academics/student-support
· The
Learning Centers: https://rlc.rutgers.edu/
· The
Writing Centers (including Tutoring and Writing Coaching):
https://writingctr.rutgers.edu
· Rutgers
Libraries: https://www.libraries.rutgers.edu/
· Office
of Veteran and Military Programs and Services: https://veterans.rutgers.edu
· Student
Health Services: http://health.rutgers.edu/
· Counseling,
Alcohol and Other Drug Assistance Program & Psychiatric Services (CAPS):
http://health.rutgers.edu/medical-counseling-services/counseling/
· Office
for Violence Prevention and Victim Assistance: www.vpva.rutgers.edu/