CSCI3358 · Computer Science

Foundations of algorithmic (un)fairness

Morrissey College of Arts & Sciences

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4.7 / 5Course rating

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Across 1 instructor

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Who teaches this? 1

Both ratings are out of 5, for each instructor’s sections of CSCI3358.

Jessica Finocchiaro

Assistant Professor, Computer Science

1 evaluation for this course

Instructor: 4.9
Course: 4.7

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Jessica Finocchiaro

Assistant Professor, Computer Science

1 evaluation for this course

Instructor: 4.9
Course: 4.7

About this course

Computation is increasingly used to support decision-making in our society: banks are given to algorithmic predictions to help them determine loan qualification; in the COVID-19 pandemic, algorithms were used to allocate scarce vaccines; facial recognition algorithms allow us to use our faces as "keys" to unlock our phones and even houses. In these high-stakes settings, concerns of fairness and justice are salient. This course will equip students with the mathematical tools to understand and address some of these concerns. Topics will include: how to computationally define and diagnose (un)fairness, the role of uncertainty in fairness, disparate treatment vs disparate impact, and contextualization within US anti-discrimination law.

All evaluation ratings

Averages use numerical 1–5 ratings, including the ratings submitted with new anonymous reviews.

OrganizationHow well the course was organized: 4.70 / 5
ChallengeHow intellectually challenging students found it: 4.48 / 5
AttendanceHow necessary attendance was: 4.56 / 5
AssignmentsHow helpful assignments were: 4.70 / 5

Weekly effort: ~5 hours

Estimated from the original workload response buckets. Individual sections may differ.

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Evaluation history 1 terms

All available terms for CSCI3358. Numerical averages use the five-point scale.
Term	Evaluations	Course rating	Instructor rating
Fall 2024	1	4.7	4.9