Explainable AI (XAI)

What is Explainable AI (XAI)?

Explainable AI (XAI) is the set of methods and design practices that make an AI system’s predictions and decisions understandable to humans—via feature attributions, counterfactuals, rule surrogates, or transparent architectures.

XAI supports debugging, regulatory compliance, and user trust when black-box models affect people.

Related Giskard articles

• OWASP, MITRE ATLAS, and NIST AI RMF

Make AI behavior auditable with Giskard — pair model explainability work with documented scenario evals that show failure modes clearly. See OWASP, MITRE ATLAS, and NIST AI RMF · giskard.ai.

Authority: NIST: Four Principles of Explainable AI