AIF-C01 Fundamentals of Generative AI Practice Question
A developer is using Amazon Bedrock to create a chatbot. They want to ensure the bot does not generate toxic or offensive content. Which feature should they enable?
⚠ Common exam trap
A common misconception is that prompt engineering alone is sufficient for safety, when in fact Bedrock's content filtering is the explicit, managed feature designed to enforce content policies at runtime.
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
✓
Enable content filtering on the Bedrock model.
Amazon Bedrock provides built-in content filtering capabilities that can be enabled at the model invocation level to automatically detect and block toxic or offensive content in both input prompts and generated responses. This feature uses predefined safety filters (e.g., hate, insults, sexual content, violence) and is the most direct and managed way to prevent harmful outputs without requiring custom development.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use careful prompt engineering to avoid toxic responses.
Why it's wrong here
Prompt engineering can reduce risk but is not a guarantee.
- ✗
Fine-tune the model on a dataset of safe responses.
Why it's wrong here
Fine-tuning reduces but does not guarantee elimination of toxic outputs.
- ✓
Enable content filtering on the Bedrock model.
Why this is correct
Content filtering provides automated detection and blocking of inappropriate content.
- ✗
Implement external response validation using a third-party API.
Why it's wrong here
Outside the scope of Bedrock; not as integrated.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.