AI-102 Plan and manage an Azure AI solution Practice Question
You plan to use Azure AI Content Safety to detect hate speech in user-generated content. Which type of content safety is most appropriate for this scenario?
⚠ Common exam trap
Many candidates confuse the broad 'text moderation' capability with the more specialized 'Prompt Shields' feature, mistakenly thinking prompt injection protection is the same as hate speech detection, or assume 'custom categories' are needed when the built-in hate category already suffices.
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
✓
Text moderation
Text moderation is the correct choice because Azure AI Content Safety's text moderation API is specifically designed to detect and filter hate speech, along with other harmful content categories like violence and self-harm, in user-generated text. It uses machine learning classifiers trained on a vast corpus to assign severity scores across predefined categories, making it the direct and most appropriate tool for this scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Custom categories
Why it's wrong here
Custom categories let you train a classifier on your own labelled examples; they do not provide the built-in hate speech taxonomy the scenario requires. It is tempting because custom categories can be tuned for niche abuse patterns, but they are the correct choice only when predefined hate, violence and sexual classifiers miss domain-specific terminology.
- ✗
Image moderation
Why it's wrong here
Image moderation classifies visual content for violence, self-harm or sexual material; it cannot parse the text of user-generated posts, so hate speech in written content goes undetected. It is tempting because it is a Content Safety capability, but it is the correct choice only when the offending content is an uploaded picture.
- ✗
Prompt Shields
Why it's wrong here
Prompt Shields detect jailbreak and indirect prompt-injection attempts aimed at a large language model, not hate speech in user-generated content. It is tempting because it sits within Azure AI Content Safety, but it is the right selection only when defending an LLM application against adversarial prompts rather than moderating published text.
- ✓
Text moderation
Why this is correct
Text moderation analyses written user-generated content and returns severity scores for hate, violence, self-harm and sexual categories. This satisfies the stem's requirement to detect hate speech in text, unlike image moderation, which only classifies visual content.
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JA
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.