See related work on fairness in Duchi 2020.

• Dwork, et al 2011 - Fairness Through Awareness
• Hardt et al 2016 - Equality of Opportunity in Supervised Learning “We show how to optimally adjust any learned predictor so as to remove discrimination according to our definition.”
• Kilbertus et al 2017 - Avoiding Discrimination through Causal Reasoning
• Kearns et al 2017 - Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
• Bird et al 2020 - Fairlearn: A Toolkit for Assessing and Improving Fairness in AI

• Tutorial: Bias and Fairness in Natural Language Processing

• Bias
• Distribution Shift (Methods that are not robust to distribution shift may not be fair across populations)
• Ethics