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AI explainability is the ability to explain, in human-understandable terms, why an AI system produced a particular output. It is distinct from interpretability (understanding the model's internal workings) and is a legal compliance requirement in multiple jurisdictions.
Key distinction: Explainability techniques explain specific decisions to specific people. Interpretability means understanding what a model computes internally. Both matter for governance, they are not interchangeable.