FairMultipleDecisionMaking ThroughSoftInterventions

How to ensure fairness in algorithmic decision making models is an important task in machine learning [12,15]. Over the past years, many researchers have been devoted to the design of fair classification algorithms withrespecttoapre-defined protected attribute,suchasraceorsex,anda decision task/model, such as hiring [1,11,24]. In particular,one line of the work istoincorporate fairness constraints into classic learning algorithms tobuild fair classifiers from potentially biased data [4,13,29,31-33]. Most of previous research generally focuses on a single decision model.