FairRover

The potential harms and drawbacks of automated decision making has become a challenge as data science blends into our lives. In particular, fairness issues with deployed machine learning models have drawn significant attention from the research community. Despite the myriad of algorithmic fairness work in various research communities, in practice data scientists still face many roadblocks in ensuring the fairness of their machine learning models. This is primarily because there does not exist an end-to-end system that guides the users in building a fair machine learning model in a responsible way from model auditing, to model explanation, to bias mitigation.