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AI & Machine Learning · Foundational

Responsible AI

Developing and using AI in ways that are fair, reliable, safe, private, secure, transparent, accountable and inclusive.

Definition

Responsible AI frameworks turn ethical principles into practices such as impact assessments, bias testing, explainability, human oversight, documentation and monitoring. Microsoft's principles are fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability; AWS and Google publish similar dimensions.

Exam tip

Know Microsoft's six responsible AI principles for AI-900/AI-901.

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