AI-102 Implement generative AI solutions Practice Question
Exhibit
Refer to the exhibit.
{
"role": "system",
"content": "You are an AI assistant that helps users find information. When you don't know the answer, say 'I don't know' and do not make up information."
}You have configured a system message for an Azure OpenAI chat completion deployment as shown in the exhibit. Users are reporting that the assistant sometimes refuses to answer questions that are clearly within the scope of the provided data. What is the most likely issue?
⚠ Common exam trap
Microsoft often tests the misconception that refusal issues are caused by missing data instructions or high temperature, when in fact the root cause is the system message's overly cautious phrasing that induces false-negative refusals.
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
✓
The system message encourages the model to err on the side of caution, leading to false-negative refusals.
The system message likely contains overly cautious language (e.g., 'only answer if you are certain' or 'do not speculate'), which causes the model to refuse answering even when the data clearly supports the response. This is a known behavior in Azure OpenAI chat completions where the system message's tone and constraints directly influence refusal rates, leading to false-negative refusals.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The system message encourages the model to err on the side of caution, leading to false-negative refusals.
Why this is correct
The instruction 'say I don't know' and not make up information can cause the model to refuse when uncertain.
- ✗
The system message explicitly prohibits making up information, which is correct behavior.
Why it's wrong here
While correct, it may be too strict and cause unnecessary refusals.
- ✗
The system message does not include instructions to use the provided data.
Why it's wrong here
The message is about honesty, not data usage.
- ✗
The temperature parameter is set too high, causing the model to hallucinate.
Why it's wrong here
Hallucination would produce incorrect answers, not refusals.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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