Recourse systems that ignore causal relationships between features and outcomes enable strategic gaming and distribution shift; incorporating causal structure into recourse design creates stable equilibria where recommended changes genuinely improve qualifications rather than just flip predictions.
This paper addresses a critical flaw in algorithmic recourse systems: they often recommend changes that help people game classifiers rather than genuinely improve their qualifications.