Explainability (ML forensic)

The capacity of a machine-learning model to articulate, in interpretable terms, the features driving its classification or estimation output. Required under Daubert, UK Criminal Procedure Rules Part 19, and the analogous standards in India and Australia, where an expert must explain the basis for their opinion. Neural networks require explainability tools (LIME, SHAP) to partially achieve this.