AI-102 Implement generative AI solutions Practice Question
You are deploying an Azure OpenAI model for a healthcare application. You need to ensure that the model does not generate medical advice and that all responses include a disclaimer. Which configuration should you use?
⚠ Common exam trap
Test-takers frequently confuse content filtering with behavioral control, assuming Azure AI Content Safety can enforce custom rules like 'do not generate medical advice' when it only filters predefined harmful categories, not domain-specific instructions.
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
✓
Configure a system message with instructions and enable content filtering.
Configuring a system message with explicit instructions (e.g., 'Do not provide medical advice; always include a disclaimer') combined with Azure AI Content Safety's content filtering allows you to enforce behavioral guardrails and block harmful outputs at the application layer. The system message sets the model's behavior, while content filtering provides a secondary safety net to catch policy violations, ensuring compliance in a regulated healthcare environment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ground the model with your own medical documents.
Why it's wrong here
Grounding with your own medical documents supplies domain context but does not itself block medical advice or force a disclaimer into every response. System message instructions and content filters enforce that behaviour. Grounding would be correct when answers must cite your specific internal corpus rather than general knowledge.
- ✗
Set max_tokens to 50 to limit response length.
Why it's wrong here
max_tokens caps response length only; it cannot prevent medical advice or append a disclaimer. Content filtering and system message instructions govern what the model may say. Limiting max_tokens would be correct when responses must stay within a strict length or cost budget, not for safety behaviour.
- ✗
Use Azure AI Content Safety to filter medical terms.
Why it's wrong here
Content Safety filters harmful categories such as violence or hate, not domain-specific medical advice; it cannot enforce disclaimer text or block clinical guidance. It is tempting because it governs model input and output, but it is designed for harm classification, whereas this scenario needs system message instructions plus prompt shields or custom blocklists.
- ✓
Configure a system message with instructions and enable content filtering.
Why this is correct
A system message sets the model's behavioural guardrails, instructing it to refuse medical advice and append a disclaimer to every response. Content filtering adds a safety layer blocking harmful outputs. Together they satisfy both constraints: no medical advice and mandatory disclaimers in a healthcare deployment.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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