Abstract
Growing concerns about the fairness of algorithmic decision-making systems have prompted a proliferation of mathematical formulations aimed at remedying algorithmic bias. Yet, integrating mathematical fairness alone into algorithms is insufficient to ensure their acceptance, trust, and support by humans. It is also essential to understand what humans perceive as fair.
... read more