Explainability

What it is

Explainability is the ability to describe how an AI system reached a decision in understandable terms. Explainable AI (XAI) techniques aim to provide insights into model reasoning—which features mattered, what patterns were matched, why this output was chosen.

Why it matters

Explainability builds trust and enables oversight. When you understand why AI suggested something, you can better evaluate whether to follow that suggestion. In high-stakes contexts, explainability may be legally required. It's an active research area as AI becomes more complex.