Explainability

The ability to understand how an AI model or system arrives at its predictions, decisions, or outputs by examining its internal mechanisms, decision-making process, or contributing factors.

The degree to which an AI system's inner workings, decision logic, training data, and operations are visible and understandable.

The framework of policies, processes, and oversight that ensures AI systems are developed, deployed, and operated responsibly, safely, and in compliance with regulations.

The practice of monitoring, reviewing, and governing an AI system's decisions, actions, and outputs by human operators to ensure safety, accuracy, compliance, accountability, and appropriate intervention when necessary.