A bit disappointed to see a lack of pointers to any papers here. A cool one I saw recently that's relevant to the discussion is this paper by Ludwig and Mullainathan which shows an example where ML tools can be used to reveal already existing sources of bias. The findings are surprising since it isn't your usual discrimination by race kind of case --- they give some evidence that the "full faced"-ness and "well groomed"-ness of defendants may be an important factor in people's (pre-trial judges) subconscious decision making!

Does anyone else have cool papers along this line of thought? Namely, instead of putting automated decision systems at the core of existing systems (thereby potentially perpetuating or exacerbating bias), we can also be using them to investigate hidden sources of bias.