AWS Certified AI Practitioner AIF-C01 Practice Question
A startup is building a customer-facing generative AI assistant by invoking foundation models through Amazon Bedrock. The team must ensure that any personally identifiable information (PII) that the model might return is removed or masked before the text reaches end users. Which Guardrails for Amazon Bedrock feature directly addresses this requirement?
Guardrails for Amazon Bedrock offers a built-in PII redaction capability that automatically detects common forms of personally identifiable information in model inputs or outputs and replaces them with placeholders. This safeguard helps organizations meet privacy requirements by preventing exposure of sensitive user data. Denied topics policies block entire subject areas, toxicity filters screen for harmful content, and model version pinning simply locks a model revision; none of these functions perform automatic PII detection and masking.
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What is PII redaction in Amazon Bedrock?
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How does PII redaction differ from a denied topics policy?
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Are PII redaction capabilities customizable in Amazon Bedrock?
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How does PII redaction work in Amazon Bedrock?
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What types of PII can Amazon Bedrock detect and redact?
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How does PII redaction differ from other Amazon Bedrock guardrails like toxicity filters or denied topics policies?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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