The AR Fairness Metamodel proposes a structured framework for representing, analyzing, and comparing fairness measures in AI. It considers key elements like agents, resources, and attributes, enabling systematic definition and comparison of fairness measures. This framework can be used to evaluate and compare fairness in AI systems, promoting fairness and equity in AI decision-making.