Removing Unfair Bias in Machine Learning

AI can embed human and societal bias and be then deployed at scale. Many algorithms are now being reexamined due to illegal bias. So how do you remove bias & discrimination in the machine learning pipeline? In this workshop you will learn the debiasing techniques that can be implemented by using the open source toolkit AI Fairness 360.

AI Fairness 360 (AIF360) is an extensible, open source toolkit for measuring, understanding, and removing AI bias. It contains the most widely used bias metrics, bias mitigation algorithms, and metric explainers from the top AI fairness researchers across industry & academia.

You will learn:
how to measure bias in your data sets & models
how to apply the fairness algorithms to reduce bias
how to apply a practical use case of bias measurement & mitigation