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AI-102 Plan and manage an Azure AI solution Practice Question

Which THREE are required when planning to use Azure OpenAI Service for a generative AI application that must comply with responsible AI principles?

⚠ Common exam trap

A common mix-up: candidates confuse operational controls (like token limits or rate limiting) with responsible AI requirements, which are specifically about fairness, safety, transparency, and accountability, not performance or security.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Implement content filters to block harmful outputs.

Azure OpenAI Service provides built-in content filtering that can block harmful outputs such as hate speech, violence, or self-harm. This is a core requirement for responsible AI compliance, as outlined in Microsoft's Responsible AI Standard, and must be configured to prevent the model from generating unsafe content.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Restrict the model to a maximum of 1000 tokens.
Why it's wrong here
Not a requirement of responsible AI.
✓
Implement content filters to block harmful outputs.
Why this is correct
Required for safety.
✓
Design with human-in-the-loop for critical decisions.
Why this is correct
Human oversight is a key responsible AI principle.
✗
Enable rate limiting to prevent abuse.
Why it's wrong here
Rate limiting is operational, not specifically responsible AI.
✓
Establish data governance policies for training data.
Why this is correct
Ensures data privacy and compliance.

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AI-102 Plan and manage an Azure AI solution Practice Question

Why each option matters

Option-by-option breakdown

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