CSCI1491
Fairness in Automated Decision Making
Spring 2025
We know we want to build more equitable technology, but how? In this course we’ll review the latest developments in how to build more equitable algorithms, including definitions of (un)fairness, the challenges of explaining how ML works, making sure we can get accountability, and much more.
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| Meets: | TTh 1pm-2:20pm in CIT Center (Thomas Watson CIT) 368 |
| Exam: | If an exam is scheduled for the final exam period, it will be held: |
| Max Seats: | 50 Full |
| CRN: | 27672 |
