AI RESEARCH
Mind the Gap: Optimal and Equitable Encouragement Policies
arXiv CS.LG
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ArXi:2309.07176v5 Announce Type: replace In consequential domains, it is often impossible to compel individuals to take treatment, so that optimal policy rules are merely suggestions in the presence of human non-adherence to treatment recommendations. We study personalized decision problems in which the planner controls recommendations into treatment rather than treatment itself. Under a covariate-conditional no-direct-effect model of encouragement, policy value depends on two distinct objects: responsiveness to encouragement and treatment efficacy.