The correct answer is to configure a content filter in Azure OpenAI Service. This is because the service includes built-in content filtering that automatically screens both input prompts and generated completions for categories like hate speech, profanity, and self-harm references, applying predefined severity thresholds to block harmful language before it reaches the output. On the AI-900 exam, this question tests your understanding of responsible AI principles and the specific safety tools available within Azure OpenAI, often appearing as a scenario where you must distinguish between content filtering, moderation APIs, or prompt engineering. A common trap is to assume you need to pre-process the input text manually, but the content filter works at the service level to catch harmful language even in generated summaries. Memory tip: think of the content filter as a “safety guardrail” that runs automatically on both sides of the conversation—input and output—to block hate, profanity, and self-harm.
AI-900 Practice Question: Describe features of generative AI workloads on Azure
This AI-900 practice question tests your understanding of describe features of generative ai workloads on azure. 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.
A social media platform uses Azure OpenAI Service to generate summaries of user comments. The development team discovers that sometimes the generated summaries include offensive or harmful language that was present in the original comments. The team wants to ensure that the generated output is always free of hate speech, profanity, and self-harm references. What should the team configure in the Azure OpenAI Service?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "always"
Why it matters: Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
Why wrong: Temperature controls the randomness of the output; setting it to 0 makes the output more deterministic but does not filter harmful content.
B
Configure a content filter
Content filters in Azure OpenAI Service allow you to specify categories of harmful content to block, directly addressing the requirement.
C
Increase the max_tokens parameter
Why wrong: Max_tokens controls the maximum length of the generated output; it does not filter specific types of content.
D
Use a grounding source
Why wrong: Grounding sources help the model base its responses on provided data, but they do not guarantee the elimination of harmful language from the input.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure a content filter
Option B is correct because Azure OpenAI Service provides built-in content filtering that can be configured to block hate speech, profanity, and self-harm references in both input prompts and generated completions. This ensures that even if offensive language appears in the original user comments, the generated summaries will be free of such harmful content. The content filter operates at the service level, applying predefined severity thresholds to filter out undesirable language.
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.
✗
Set the temperature parameter to 0
Why it's wrong here
Temperature controls the randomness of the output; setting it to 0 makes the output more deterministic but does not filter harmful content.
✓
Configure a content filter
Why this is correct
Content filters in Azure OpenAI Service allow you to specify categories of harmful content to block, directly addressing the requirement.
Clue confirmation
The clue word "always" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the max_tokens parameter
Why it's wrong here
Max_tokens controls the maximum length of the generated output; it does not filter specific types of content.
✗
Use a grounding source
Why it's wrong here
Grounding sources help the model base its responses on provided data, but they do not guarantee the elimination of harmful language from the input.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse model parameters like temperature or max_tokens with safety controls, or assume that grounding sources automatically sanitize output, when in fact content filters are the dedicated mechanism for blocking harmful language.
Trap categories for this question
Command / output trap
Temperature controls the randomness of the output; setting it to 0 makes the output more deterministic but does not filter harmful content.
Detailed technical explanation
How to think about this question
Azure OpenAI content filters use a multi-level classification system with severity levels (safe, low, medium, high) for categories like hate, sexual, violence, and self-harm. Administrators can configure these filters via the Azure Portal or API to block or warn at specific severity thresholds, and the filtering applies to both prompt and completion text. In real-world scenarios, this is critical for compliance with responsible AI policies and to avoid brand damage from unintended harmful outputs.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of generative AI workloads on Azure — This question tests Describe features of generative AI workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure a content filter — Option B is correct because Azure OpenAI Service provides built-in content filtering that can be configured to block hate speech, profanity, and self-harm references in both input prompts and generated completions. This ensures that even if offensive language appears in the original user comments, the generated summaries will be free of such harmful content. The content filter operates at the service level, applying predefined severity thresholds to filter out undesirable language.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "always". Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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