Fairness and Discrimination in Mechanism Design and Machine Learning

Abstract:

As fairness and discrimination concerns permeate the design of both machine learning algorithms and mechanism design problems, we discuss differences in approaches between these two fields. We aim to bridge these two communities into a cohesive narrative that en- compasses both the large-scale capabilities of machine learning and group-focused fairness as well as the strategic incentives and utility- based notions of fairness from mechanism de- sign, showing their necessity in designing a fair pipeline.

Back to AI for Social Good event