Fairness vs Performance: Characterizing the Pareto Frontier of Algorithmic Decision Systems

ArXi:2605.10604v1 Announce Type: cross Designing fair algorithmic decision systems requires balancing model performance with fairness toward affected individuals: fairness might require sacrificing some performance and vice versa, yet the space of possible trade-offs is still poorly understood. We investigate fairness in binary prediction-based decision problems by conceptualizing decision making as a multi-objective optimization problem that simultaneously considers decision-maker utility and group fairness.