The answer is to add the new phrases to the existing custom term list using the List Management API. This is the fastest approach because Azure Content Moderator’s custom term lists are checked in real-time during content review; adding terms via the API immediately updates the screening without requiring any model retraining or redeployment. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your understanding of how to dynamically update moderation rules for emerging patterns, often contrasting with options like retraining a custom model or recreating the list from scratch—both of which are slower and unnecessary. A common trap is assuming you need to rebuild or retrain, but the List Management API is designed for rapid, live updates. Memory tip: think “API add, no retrain—catch the hate speech in the fast lane.”
AI-102 Implement content moderation solutions Practice Question
This AI-102 practice question tests your understanding of implement content moderation solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
You are a content moderator for a social media platform that uses Azure Content Moderator. The platform has a custom blocklist of URLs (e.g., 'example.com/spam') and a custom term list for hate speech. Recently, users have been posting comments that contain a new form of hate speech not yet in the term list. The comments are being allowed through moderation. You need to update the solution to catch these new phrases as quickly as possible. What should you do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add the new phrases to the existing custom term list using the List Management API
Option C is correct because Azure Content Moderator's custom term lists allow you to dynamically add new offensive terms or phrases via the List Management API, which immediately updates the moderation screening without retraining or redeploying any model. This provides the fastest way to catch new hate speech patterns as they emerge, as the term list is checked in real-time during content review.
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.
✗
Create a new custom model using Custom Vision to detect the new phrases in text
Why it's wrong here
Custom Vision is for images, not text; also building a new model is slower than updating a term list.
✗
Retrain the image classification model using the new phrases as training data
Why it's wrong here
Image classification does not apply to text comments.
✓
Add the new phrases to the existing custom term list using the List Management API
Why this is correct
This quickly adds new terms to be matched against incoming comments.
Related concept
Read the scenario before looking for a memorised answer.
✗
Delete the existing term list and recreate it with the new phrases included
Why it's wrong here
Deleting the existing list would temporarily remove protection against previously known hate speech.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume retraining or creating a new model is required for new patterns, but Azure Content Moderator's term lists are designed for rapid, rule-based updates without the overhead of model training, and the List Management API enables immediate addition of terms to an existing list.
Detailed technical explanation
How to think about this question
Azure Content Moderator's term lists are stored as key-value pairs in a review team's workspace, and updates via the List Management API (e.g., POST /contentmoderator/lists/v1.0/termlists/{listId}/terms/{term}) take effect immediately for subsequent moderation calls. The API supports bulk addition of terms, and the service evaluates text against both the built-in machine learning classifiers and custom term lists in a single pass, ensuring low-latency screening. In a real-world scenario, a moderator could script a PowerShell or REST call to add dozens of new hate speech phrases within seconds of detection, preventing further exposure.
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 content moderation solutions — This question tests Implement content moderation solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add the new phrases to the existing custom term list using the List Management API — Option C is correct because Azure Content Moderator's custom term lists allow you to dynamically add new offensive terms or phrases via the List Management API, which immediately updates the moderation screening without retraining or redeploying any model. This provides the fastest way to catch new hate speech patterns as they emerge, as the term list is checked in real-time during content review.
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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