The answer is to add a system message that informs users the summary is generated by AI. This configuration directly fulfills the transparency principle under Microsoft’s Responsible AI framework, which mandates that users must be clearly informed when they are interacting with or receiving content from an AI system. In the context of an Azure OpenAI document summarization solution, embedding a system message like “This summary was generated by AI” provides the necessary disclosure, making the system’s nature transparent to end users. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of how to operationalize Responsible AI principles within Azure OpenAI deployments, often appearing as a scenario where you must distinguish transparency from other safeguards like content filtering or diagnostic logging. A common trap is confusing diagnostic logging (which aids accountability but not user-facing disclosure) with transparency. Remember the memory tip: “Transparency = Tell the user,” so always look for the option that directly communicates AI involvement to the person receiving the output.
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your team is developing an AI-powered document summarization solution using Azure OpenAI. You need to ensure that the solution complies with Microsoft's Responsible AI principles, specifically transparency. Which configuration should you implement?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add a system message that informs users the summary is generated by AI.
Transparency under Microsoft's Responsible AI principles requires that users are aware when they are interacting with an AI system. Adding a system message that explicitly states the summary is AI-generated fulfills this disclosure requirement. Diagnostic logging (A) aids in accountability and debugging but does not directly inform the user. Fine-tuning (B) improves accuracy but does not address transparency. Content filtering (C) mitigates harmful outputs but does not disclose AI involvement.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Configure diagnostic logging to capture all model inputs and outputs.
Why it's wrong here
Logging supports accountability, but transparency requires direct user-facing disclosure.
✗
Fine-tune the model on a custom dataset to improve accuracy.
Why it's wrong here
Fine-tuning improves performance, not transparency.
✗
Enable content filtering with severity levels high and medium.
Why it's wrong here
Content filtering addresses harmful content, not transparency.
✓
Add a system message that informs users the summary is generated by AI.
Why this is correct
Transparency requires clear disclosure of AI involvement.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'transparency' with 'accountability' or 'safety' and select diagnostic logging or content filtering, not realizing that transparency specifically requires user-facing disclosure of AI involvement.
Detailed technical explanation
How to think about this question
In Azure OpenAI, the system message is part of the chat completion API's 'messages' array and is used to set the assistant's behavior and persona. For transparency, you can include a directive like 'You are an AI assistant that always discloses your AI nature at the start of each response.' This message is processed by the model before generating any user-facing output, ensuring the disclosure is embedded in the response itself. In a real-world scenario, failing to include such a disclosure could violate regulatory requirements like the EU AI Act's transparency obligations for generative AI systems.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Implement generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add a system message that informs users the summary is generated by AI. — Transparency under Microsoft's Responsible AI principles requires that users are aware when they are interacting with an AI system. Adding a system message that explicitly states the summary is AI-generated fulfills this disclosure requirement. Diagnostic logging (A) aids in accountability and debugging but does not directly inform the user. Fine-tuning (B) improves accuracy but does not address transparency. Content filtering (C) mitigates harmful outputs but does not disclose AI involvement.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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