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Responsible AI Principles

Reviewed 19 July 2026 Canonical definition Part of: Agent Reliability & Deployment Terms →

Responsible AI principles are the ethical commitments an organisation makes about how it will develop and deploy AI systems, covering values such as fairness, transparency, accountability, privacy, and safety. Principles provide the normative foundation for AI governance: they define what the organisation is trying to achieve, and governance controls are the mechanisms that make those commitments enforceable in practice.

§01 / QUESTIONSterm: Responsible AI Principles
Questions

Common questions.

What are Responsible AI Principles?

Responsible AI principles are the ethical commitments an organisation makes about how it will develop and deploy AI systems, covering values such as fairness, transparency, accountability, privacy, and safety.

How do Responsible AI Principles work?

Principles provide the normative foundation for AI governance: they define what the organisation is trying to achieve, and governance controls are the mechanisms that make those commitments enforceable in practice.

Which terms are related to Responsible AI Principles?

Closely related concepts include Responsible AI Standard (Microsoft), Responsible AI Lead, Enterprise AI Strategy, AI Use-Case Registry. Each is defined in the Prefactor glossary.

§02 / RELATEDnext: where this fits
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Where this fits.

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