Fall 2020: T-Th 11:00 am -- 12:15 pm, Online (Zoom -- Link on Blackboard)
| Week | Date | Topic | Slides | Notes/Resources |
|---|---|---|---|---|
| 1 | T. 8/25 | Course Introduction | Slides | |
| Th. 8/27 | Harms of Data | Slides |
Book: Fairness in Machine Learning
A Summary for Weapons of Math Destruction (Link to video) Ruha Benjamin: "Reimagining the Default Settings of Technology and Society" |
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| 2 | T. 8/29 | From Data to Action (Part 1) | ||
| T. 9/3 | Cancelled (Conflict with VLDB 2020 Presentation) Link to the Tutorial Slides and Videos |
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| 3 | T. 9/8 | From Data to Action (Part 2) | Slides | |
| T. 9/10 | On Fairness and its Definitions (Part 1) | Slides | (Link to video) Arvind Narayanan: "Tutorial: 21 fairness definitions and their politics" | |
| 4 | T. 9/15 | On Fairness and its Definitions (Part 2) | Slides | (Link to video) Judea Pearl: "The Foundations of Causal Inference" [The Book of WHY] |
| T. 9/17 | On Fairness and its Definitions (Part 3) | Slides | (Link to video) Jon Kleinberg: "Inherent Trade-Offs in Algorithmic Fairness"
(Link to video) Alexandra Chouldechova: "Algorithmic bias: Practical and technical challenges" |
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| 5 | T. 9/22 | Beynod Fairness, related notions (Part 1) | Slides | (Link to video) Jon Kleinberg: "Fairness, Rankings, and Behavioral Biases" |
| T. 9/24 | Beynod Fairness, related notions (Part 2) | Project Proposal Instruction | ||
| 6 | T. 9/29 | Pre-process Interventions to Acheive Fairness (Part 1) | Slides | |
| Th. 10/1 | Pre-process Interventions to Acheive Fairness (Part 2) | Project Proposal Due (11:59pm) | ||
| 7 | T. 10/6 | In-process Interventions to Acheive Fairness (Part 1 -- Classification) | Slides | |
| Th. 10/8 | In-process Interventions to Acheive Fairness (Part 2 -- Ranking) | Slides | ||
| 8 | T. 10/13 | Paper Presentation (Shishir Adhikari) | Slides | Salimi, Babak, et al. "Interventional fairness: Causal database repair for algorithmic fairness." in SIGMOD. 2019. |
| Th. 10/15 | Paper Presentation (Omid Memarrast) | Slides | Basu, Kinjal, et al. "A Framework for Fairness in Two-Sided Marketplaces." arXiv preprint arXiv:2006.12756 (2020). | |
| 9 | T. 10/20 | Paper Presentation (Mohammad Arvan) | Slides | Language (Technology) is Power: A Critical Survey of “Bias” in NLP |
| Th. 10/22 | Paper Presentation (Shubham Singh) | Slides | Tramer, Florian, et al. "FairTest: Discovering unwarranted associations in data-driven applications." 2017 IEEE European Symposium on Security and Privacy (EuroS&P). IEEE, 2017. | |
| 10 | T. 10/27 | Paper Presentation (Mina Valizadeh) | Slides | Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016) by Tolga Bolukbasi et al. |
| Th. 10/29 | Paper Presentation (Nima Shahbazi) | Slides | Feldman, Michael, et al. "Certifying and removing disparate impact." SIGKDD. 2015. Adler, P., Falk, C., Friedler, S.A. et al. Auditing black-box models for indirect influence. Knowl Inf Syst 54, 95–122 (2018). (Tutorial) Auditing Black Box Models (Tutorial Video) Link to the github repository |
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| 11 | Th. 11/5 | Paper Presentation (Ishan Bhatnagar) | Slides | Kuppam, Satya, et al. "Fair decision making using privacy-protected data." arXiv preprint arXiv:1905.12744 (2019).
Other Resources: Differentially Private Fair Learning Achieving Differential Privacy and Fairness in Logistic Regression Differential Privacy Has Disparate Impact on Model Accuracy |
| 12 | T. 11/10 | Paper Presentation (Sriparna Ghosh) | Slides | Palowitch, John, and Bryan Perozzi. "Monet: Debiasing graph embeddings via the metadata-orthogonal training unit." arXiv preprint arXiv:1909.11793 (2019).
Arduini, Mario, et al. "Adversarial Learning for Debiasing Knowledge Graph Embeddings." arXiv preprint arXiv:2006.16309 (2020). |
| Th. 11/12 | Paper Presentation (Ankit Aich) | Slides | How we talk about other people, group unfairness in natural language image description - AAAI - 2017 | |
| 13 | T. 11/17 | Paper Presentation (Teja Gollapudi) | Slides | “Why should I trust you? Explaining the predictions of any classifier”, Ribeiro, Singh, Guestrin (2016) |
| Th. 11/19 | Paper Presentaton | Slides | Abolfazl Asudeh, HV Jagadish, You (Will) Wu, Cong Yu. On Detecting Cherry-picked Trendlines. PVLDB 13(6)939--952, 2020 | |
| 14 | T. 11/24 | Paper Presentation | Slides | Asudeh, Abolfazl, Tanya Berger-Wolf, Bhaskar DasGupta, and Anastasios Sidiropoulos. "Maximizing coverage while ensuring fairness: a tale of conflicting objective." arXiv preprint arXiv:2007.08069 (2020). |
| 15 | T. 12/1 | Project Presentation | ||
| Th. 12/3 | Project Presentation | |||