AI Governance Glossary.

An assessment or review of an AI system to evaluate its fairness, bias, effectiveness, and compliance with regulations.

The field that addresses the moral implications of AI, including fairness, transparency, accountability, and privacy.

The frameworks, policies, and laws that guide the development, deployment, and oversight of AI technologies.

Legal rules and frameworks established by governments to control how AI is developed and used.

The responsibility of developers and organizations to ensure their AI systems are explainable and do not cause harm.

Systematic and unfair discrimination in AI outcomes due to biases in data or algorithms.

The simulation of human intelligence in machines that are programmed to think, learn, and solve problems.

The degree to which an AI system can operate without human input; often scrutinized in governance.

A system whose internal workings are not visible or understandable to users, common in complex AI systems.

An AI field that enables computers to interpret and understand visual information from the world.

A type of machine learning that uses neural networks with many layers to analyze data and make decisions.