FairTorch is a fairness library for PyTorch. It lets developers add constraints to their models to equalize metrics across subgroups by simply adding a few lines of code. Model builders can choose a metric definition of fairness for their context, and enforce it at time of training. The library offers a suite of metrics that measure an AI system’s performance among subgroups, and can apply to high-stakes examples where decision-making algorithms are deployed, such as hiring, school admissions, and banking.





2nd place: Fluence