Fair Active Learning

Fair active learning is a discipline of machine learning in which one has a data set which is not fully labeled. Labels can be expensive or difficult to obtain, so we associate a cost with labeling a point. The fair active learning algorithm can try to find the best points to label which makes the machine learning model better and more fair.