What are some data sets that can be used to study fairness in machine learning? Specifically, I'm looking for a data set to illustrate a classification method that tries to balance accuracy, false-positive rates, and false-negative rates between different sub-population identified by a "protected attribute" (e.g. gender, race, age). I know of the "standard data set" that are very frequently used in fair machine learning literature, like COMPAS, UCI Adult Income, German Credit. What are some more recent, less well-used datasets suitable for this topic?