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AIF-C01 Practice Question: A bank wants to use Amazon Augmented AI (A2I) to…

A bank wants to use Amazon Augmented AI (A2I) to review high-value loan applications that require human judgment. Which workflow best implements human-in-the-loop review for these predictions?

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

Set up an A2I workflow with a confidence threshold, so low-confidence predictions are sent to human reviewers

Amazon A2I enables human review of low-confidence predictions or specific conditions. The best practice is to set a confidence threshold; predictions below that threshold are sent to human reviewers.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Set up an A2I workflow with a confidence threshold, so low-confidence predictions are sent to human reviewers

    Why this is correct

    A2I allows setting conditions like a confidence threshold to trigger human review, balancing automation and human oversight.

  • Route all loan applications to human reviewers for approval

    Why it's wrong here

    Routing all applications defeats the purpose of automation and is not efficient; A2I is designed for selective review.

  • Use Amazon Mechanical Turk to review all predictions in real time

    Why it's wrong here

    Mechanical Turk is not designed for real-time production review and does not integrate seamlessly with A2I workflows.

  • Configure a private workforce in Amazon SageMaker Ground Truth

    Why it's wrong here

    Ground Truth is for data labeling, not human review of model predictions in production.

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