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All glossary terms

AI governance

AI Accountability

AI accountability means assigning responsibility for decisions and impacts involving an artificial intelligence system. It identifies who owns a system, who can explain its use, who reviews harms or errors, and who has authority to change or stop the system when evidence warrants action.

Why it matters in practice

Accountability turns broad principles into named duties across developers, operators, business owners, and oversight teams. Clear records help an organization answer questions about a model’s purpose, data, approvals, and observed behavior. The term describes an organizational practice, not a guarantee that a system will produce fair or correct results.

Example

A product team names an owner for a recommendation model and documents who reviews a complaint about an unexpected recommendation.

Educational note

This definition is general information, not legal advice. It may omit facts that matter to a specific situation and does not establish or guarantee compliance.