Dictionary · Glossary of Governance Terms

A system of laws, policies, frameworks, practices and processes at international, national and organizational levels. AI governance helps various stakeholders implement, manage, oversee and regulate the development, deployment and use of AI technology. It also helps manage associated risks to ensure AI aligns with stakeholders' objectives, is developed and used responsibly and ethically, and complies with applicable legal and regulatory requirements.

An evaluation process designed to identify, understand, document and mitigate the potential ethical, legal, economic and societal implications of an AI system in a specific use case.

Steps performed after a machine learning model has been run to adjust its output. This can include adjusting a model's outputs or using a holdout dataset — data not used in the training of the model — to create a function run on the model's predictions to improve fairness or meet business requirements.

A brief document that discloses information about an AI model, like explanations about intended use, performance metrics and benchmarked evaluation in various conditions, such as across different cultures, demographics or race.