Responsible AI

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

The process of identifying, assessing, mitigating, and monitoring risks associated with the development, deployment, and operation of AI systems.

The ability of an AI system to provide understandable reasons or evidence for how it produced a prediction, recommendation, or decision, enabling humans to interpret and trust its behavior.

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 principle that individuals and organizations are responsible for the decisions, actions, and outcomes of AI systems throughout their lifecycle.