AIF-C01 Fundamentals of Generative AI Practice Question
A machine learning engineer notices that a generative AI model occasionally produces biased outputs. Which AWS feature can automatically filter harmful content before it reaches users?
⚠ Common exam trap
Many candidates confuse Amazon SageMaker Clarify (which detects bias in training data or model predictions) with a real-time content filtering solution, but Clarify is a static analysis tool, not a runtime guardrail for generative AI outputs.
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
✓
Amazon Bedrock Guardrails
Amazon Bedrock Guardrails is specifically designed to implement safeguards for generative AI applications, including the ability to filter harmful, biased, or inappropriate content before it reaches users. It allows you to define denied topics, content filters, and sensitive information filters that are applied at inference time, directly addressing the need to automatically filter biased outputs from a generative AI model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon CloudWatch alarms
Why it's wrong here
CloudWatch alarms trigger notifications or automated actions from metric thresholds; they cannot inspect generated text and filter harmful content. They would be correct for alerting on latency, error rates or token usage, not for content moderation.
- ✗
Amazon SageMaker Clarify
Why it's wrong here
SageMaker Clarify detects bias in datasets and model predictions, and explains feature attribution; it does not intercept or filter live model output. It would be the right pick for auditing training data or measuring bias metrics, not for blocking harmful content at inference time.
- ✗
AWS Identity and Access Management (IAM) policies
Why it's wrong here
IAM policies control which principals may call AWS APIs and resources; they cannot evaluate model output and block harmful text. They would be the right choice for restricting who can invoke a model or access training data, not for filtering generated responses.
- ✓
Amazon Bedrock Guardrails
Why this is correct
Amazon Bedrock Guardrails applies configurable content filters and denied-topic policies to model inputs and outputs, blocking harmful content before it reaches users. This automated intervention satisfies the requirement to filter biased or harmful generative output without custom moderation code.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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