Fairly Accurate Machine Learning


A few posts back, I talked about how fairness could be related to information theory. By removing any information that could be used to identify a group, you make it impossible to give that group preferential treatment. A talented student in our group, Umang Gupta, has taken that line of reasoning further and shown how information theory can give guarantees about trade-offs between fairness and accuracy for some task. Umang made this cool 1 minute explainer video for his paper which will appear in AAAI that sums it up better than I can.

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