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 10/19 | Inherent tradeoffs <br> **Reading:** [*Inherent Trade-Offs in the Fair Determination of Risk Scores*](https://arxiv.org/pdf/1609.05807) | Shiyu/Rita | Rishabh/Aaron |
 10/21 | Fairness and causality <br> **Reading:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/causal.html), Chapter 4 | Justin | --- |
 10/23 | Fairness in unsupervised learning <br> **Reading:** [*Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings*](https://arxiv.org/pdf/1607.06520) <br> **See also:** [*Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints*](https://arxiv.org/pdf/1707.09457) | Keaton/Anna | Shiyu/Rita |
-10/26 | Testing fairness, empirically <br> **Reading:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/testing.html), Chapter 5 | Rishabh/Aaron | Mike |
+10/26 | Testing fairness, empirically <br> **Reading:** [*Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination*](https://arxiv.org/pdf/1408.6491.pdf) <br> **Reading:** [*Discrimination through optimization: How Facebook’s ad delivery can lead to skewed outcomes*](https://arxiv.org/pdf/1904.02095.pdf) <br> **See also:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/testing.html), Chapter 5 | Rishabh/Aaron | Mike |
       | <center> <h4> **PL and Verification** </h4> </center> | | |
 10/28 | Overview and basic notions | Justin | --- |
 10/30 | Probabilistic programming languages <br> **Reading:** [*Probabilistic Programming*](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/fose-icse2014.pdf) | Vishal/Nikita | Zijian/Yuchen |