Lecture 15: Justice, Fairness, Bias (Part 2) PDF
Required: D’Ignazio, C., & Klein, L. (2020). 2. Collect, Analyze, Imagine, Teach. In Data Feminism. Retrieved from https://data-feminism.mitpress.mit.edu/pub/ei7cogfn
Required Video: 21 Definitions of Fairness - Arvind Narayanan
Optional: Lundgard, Alan, Measuring Justice in Machine Learning (2020) 2020 ACM Conference on Fairness, Accountability, and Transparency (FAT*)
Lecture 16: Watch Together + Discussion
Required Video (first 30 minutes): https://www.youtube.com/watch?v=N5c2X8vhfBE
Optional: Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). Association for Computing Machinery, New York, NY, USA, 610–623. https://doi.org/10.1145/3442188.3445922