Individual Fairness

The principle that similar individuals should be treated similarly by an AI system, often formalised as a Lipschitz condition on the model's output.

The idea that two people who are similar should get similar results from an AI. If two job candidates have nearly identical qualifications, the AI shouldn't treat them very differently.

Governance frameworks should address fairness at both the individual and group level. Individual fairness ensures your AI does not produce arbitrary or inconsistent outcomes for similar cases, which is important for legal defensibility.