Designing a human-review queue | AWS Certified AI Practitioner (AIF-C01) original practice question

3.4Standard

Low-confidence, high-impact outputs cannot be published automatically.

Route them efficiently.

Choose two designs.

Hint 1: Focus on the requirement

Identify what must change and what must remain unchanged. Then choose the command whose scope matches that requirement.

Hint 2: Check each command's role

Separate commands that display information, change state, remove data, or affect a child process.

信頼度・影響・個人属性・危険カテゴリで優先度を付け、根拠と入力をレビュアーへ渡す: Important cases are reviewed first.
判断・修正・理由・担当者・時刻を記録し、再学習や評価へフィードバックする: The process is traceable.
全出力を同じ順で確認し、影響度を考慮しない: Critical cases may wait.
レビュアーの判断を記録せず、結果だけを本番へ戻す: Audit and learning suffer.

Detailed explanation

CorrectPrioritize by confidence, impact, personal attributes, and risk and provide evidence

Important cases are reviewed first.

CorrectRecord decision, correction, reason, reviewer, and time for audit and improvement

The process is traceable.

IncorrectProcess every case in arrival order regardless of impact

Critical cases may wait.

IncorrectKeep only final outcomes and not reviewer reasons

Audit and learning suffer.

An example you can run in a temporary verification environment.

AWS公式AIF-C01 Domain 3.4・4.3の人的監督、レビュー、監査を確認する。

高影響の出力を優先してレビューし、判断の根拠と結果を追跡できる。

Foundation review

Check whether the command acts on the current shell, a new process, an existing process, or a file.

Use the supplied command and compare the output with the expected result.

Question IDAWS-AIF-445

EnvironmentAWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認

Last technical review2026-08-20