AWS Certified AI Practitioner AIF-C01 Practice Question
An application running on AWS makes real-time text classification predictions. The team wants any prediction with a confidence score below 60% automatically routed to a pool of human reviewers so they can approve or correct the result. Which AWS service should they use to add this human review step with minimal custom code?
Amazon Augmented AI (A2I) is designed to insert human review into machine learning workflows. It provides pre-built or custom workflows that automatically send low-confidence predictions to human reviewers and then returns the consolidated result to the application. SageMaker Clarify detects bias and explains model behavior, but it does not manage review tasks. SageMaker Model Monitor tracks data and model drift, not human review. Guardrails for Amazon Bedrock filters and redacts generative AI inputs and outputs but does not orchestrate human approval. Therefore, A2I is the correct choice for the requirement.
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What is Amazon Augmented AI (A2I)?
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How does Amazon A2I handle predictions with low confidence scores?
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What is the difference between Amazon A2I and SageMaker Clarify?
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What is Amazon A2I and how does it work?
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How does A2I compare to SageMaker Model Monitor?
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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