hardMultiple ChoiceObjective-mapped

AI-102 Practice Question: An image was submitted to Azure Content…

Exhibit

Refer to the exhibit.

```json
{
  "Classification": {
    "ReviewRecommended": false,
    "Category1": {
      "Score": 0.99
    },
    "Category2": {
      "Score": 0.02
    },
    "Category3": {
      "Score": 0.01
    }
  },
  "Terms": []
}
```

The above JSON is the output from Azure Content Moderator's Image Moderation API for an image. The application uses a threshold of 0.5 for Category1 (adult) to trigger a review.

An image was submitted to Azure Content Moderator's Image Moderation API. The application uses a threshold of 0.5 for Category1 (adult) to trigger a review. Based on the exhibit, what should the application do with this image?

⚠ Common exam trap

It's easy for candidates to assume ReviewRecommended is the sole determinant for action, ignoring that custom thresholds defined in application logic can override the API's default recommendation, leading to incorrect auto-approval.

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

✓

Escalate the image to a human reviewer because Category1 score exceeds the threshold.

The application's threshold for Category1 (adult) is 0.5, and the exhibit shows a Category1 score of 0.6, which exceeds this threshold. Even though ReviewRecommended is false, the application's custom threshold overrides the default recommendation, requiring escalation to a human reviewer for manual judgment. This aligns with Azure Content Moderator's design where you can set your own thresholds to trigger reviews regardless of the API's built-in recommendation.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Auto-approve the image because ReviewRecommended is false.
Why it's wrong here
ReviewRecommended is false despite a high score, likely an error; auto-approving would allow adult content.
✓
Escalate the image to a human reviewer because Category1 score exceeds the threshold.
Why this is correct
The high score warrants a review despite the ReviewRecommended flag being false.
✗
Auto-reject the image because no offensive terms were found.
Why it's wrong here
Terms list is for text, not images; auto-rejecting based on empty terms is incorrect.
✗
Log the inconsistency and continue processing without action.
Why it's wrong here
Ignoring the high score could lead to policy violations.

Go deeper

AI-102 Practice Question: An image was submitted to Azure Content…

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question