Explainability
Also called: XAI, explainable AI
Being able to give a human a meaningful account of why a system produced a particular output.
Explainability is about the audience: an explanation must be usable by the person who needs it — an applicant, an auditor, an engineer. It is often achieved with post-hoc methods that approximate the model’s behaviour rather than reveal its actual mechanism. That approximation is a real limitation, not a technicality.
In practice: ‘Declined mainly due to debt-to-income ratio and short credit history.’