Glossary · AI governance
Explainability
The degree to which the reasoning behind an AI system's outputs can be understood and explained to people.
Put the term into practice: KaitoSec AI
Explainability is the ability to describe, in human terms, why an AI system produced a particular output. It supports trust, accountability, and the ability to challenge or correct decisions, especially for individuals affected by them.
Many high-performing models are opaque, so explainability often relies on supporting techniques and documentation. It is closely linked to transparency requirements in AI governance and the EU AI Act.
