AI-102 Plan and manage an Azure AI solution Practice Question
You are planning to use Azure AI Content Safety to moderate user-generated content in a social media application. The solution must detect hate speech and self-harm content. Which Content Safety features should you enable?
⚠ Common exam trap
The trap here is that candidates might think custom categories are needed for specific harm types like self-harm, but Azure AI Content Safety already includes these as built-in categories, so enabling the pre-built filters is the correct approach.
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
✓
Hate and self-harm content filters
Azure AI Content Safety provides pre-built filters for specific harm categories, including hate speech and self-harm. Enabling the 'Hate and self-harm content filters' directly activates the detection models for these categories, meeting the requirement without needing custom categories or additional features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Severity levels for all categories
Why it's wrong here
Severity levels refine scoring within categories already returned; they do not add detection of hate speech or self-harm, which the standard categories already cover. Enabling severity is tempting because it lets you tune thresholds and route content by risk, which suits graduated review workflows rather than simply detecting those categories.
- ✓
Hate and self-harm content filters
Why this is correct
Enabling the hate and self-harm content filters directly satisfies the stem's requirement to detect both categories. Azure AI Content Safety classifies text against these severity-based harm categories, so the moderation pipeline can flag or block the specified content types without additional custom models.
- ✗
Custom categories for hate speech and self-harm
Why it's wrong here
Custom categories require you to supply your own labelled training data and are intended for organisation-specific content the built-in taxonomy misses. Hate speech and self-harm are already covered by standard categories, so custom training adds effort without adding detection — tempting only when your domain vocabulary falls outside the default model.
- ✗
Image moderation
Why it's wrong here
Image moderation analyses pictures and does not evaluate the text of user posts, so it cannot detect hate speech or self-harm expressed in written content. It is tempting because social platforms do host harmful imagery, making it correct when the requirement explicitly includes moderating uploaded images alongside text.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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