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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

This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.