Socially-Stratified Validation for ML Fairness

In this talk, I cover some of the frameworks used to think about fairness in machine learning. Then I turn to more practical matters of determining which social factors are important in machine leaning, how to find appropriate validation data, and considerations when selecting metrics. Finally, I walk through a sample socially-stratified validation pipeline.

• Link to slides