Explainability (explainable AI)

Large neural networks are considered “black boxes”: even experts often cannot say exactly why a model decided as it did. Explainability methods show, for example, which features most influenced a result.

Explainability matters when decisions affect people – such as in lending, insurance or recruitment – and a justification is required.