AWS Certified AI Practitioner AIF-C01 Practice Question
A team plans to deploy a generative AI chatbot on AWS. To meet responsible AI requirements for privacy and security, which action MOST directly protects users' personally identifiable information (PII) that might appear in prompts or responses?
Apply a PII redaction rule in Guardrails for Amazon Bedrock.
Enable word filters that block profanity in user input.
Publish a model card describing the model's intended use and evaluation metrics.
Run a post-training bias analysis using Amazon SageMaker Clarify.
Configuring PII redaction in Guardrails for Amazon Bedrock masks or removes personal data before it is logged or returned, directly addressing the privacy and security pillar of responsible AI. Bias analysis with SageMaker Clarify improves fairness, publishing a model card supports transparency, and word filters that block profanity improve content safety, but none of these measures specifically safeguard PII.
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What is personally identifiable information (PII)?
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How does PII redaction work in Guardrails for Amazon Bedrock?
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Why is bias analysis with Amazon SageMaker Clarify not sufficient to protect PII?
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What is Guardrails for Amazon Bedrock and how does it redact PII?
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Why is PII protection critical in generative AI applications?
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How do Guardrails differ from other tools like SageMaker Clarify or model cards in AI workflows?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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