Microsoft Azure AI Engineer Associate AI-102 Practice Question
A company plans to launch a customer-facing chat experience that uses Azure OpenAI Service. You are asked to help draft the organization's responsible AI governance framework. The framework must provide technical and procedural measures that allow the organization to detect and mitigate emerging risks after the system is in production. According to Microsoft's recommended governance practices, which measure should you include?
Turn off user feedback collection to avoid processing personally identifiable information (PII).
Schedule periodic human-in-the-loop reviews of real-world model outputs against predefined harm and fairness metrics.
Replace all access keys with managed identities for authentication purposes.
Restrict the deployment to a single geographic region that matches users' residency.
Microsoft's responsible AI guidance states that governance must extend beyond model development into post-deployment operations. Ongoing risk management should combine automation with human oversight, such as regularly sampling and reviewing live user interactions, auditing harm metrics, and retraining or updating the system when issues are found. Merely choosing a data residency, disabling feedback channels, or swapping authentication methods are valuable security or privacy steps but do not satisfy the requirement for continuous, risk-based oversight that a governance framework must provide.
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What is 'human-in-the-loop' and why is it important for responsible AI governance?
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Microsoft Azure AI Engineer Associate AI-102
Plan and manage an Azure AI solution
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