Intersectional Fairness with Fairness-Oriented Multiobjective Optimization (FOMO)

Interfair is our Bias Detection Tool Entry for the #ExpeditionHacks competition on bias in healthcare. Our entry uses a new fair machine learning framework called Fairness Oriented Multiobjective Optimization, or Fomo. Interfair allows any interested healthcare entity (a hospital system, insurance payor, or individual clinic) to feed in an ML model for a given prediction task, measure its performance across intersectional groups of patients, and optimize it with respect to several flexible fairness constraints.


Further guide to using our entry can be found here.

Supporting Documentation

Supporting Documentation PDF Link