Choosing fairness mitigations | AWS Certified AI Practitioner (AIF-C01) original practice question

4.1Standard

One group has a high false-rejection rate.

Find the cause and reduce impact.

Choose two responses.

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.

ラベル、特徴量、サンプリング、閾値、人手確認の各段階で原因を分解する: The intervention point can be identified.
グループ別性能と業務影響を再評価し、関係者承認の下で段階導入する: Side effects are checked.
全体精度を下げてもグループ差は必ず解消すると仮定する: Effectiveness must be measured.
問題のグループを訓練データから削除する: Impact is hidden or worsened.

Detailed explanation

CorrectDecompose causes across labels, features, sampling, thresholds, and human review

The intervention point can be identified.

CorrectReevaluate group quality and business impact and stage mitigations with approval

Side effects are checked.

IncorrectAssume lowering overall accuracy always fixes the gap

Effectiveness must be measured.

IncorrectRemove the affected group from training

Impact is hidden or worsened.

An example you can run in a temporary verification environment.

AWS公式AIF-C01 Domain 4.1の公平性、緩和策、影響評価を確認する。

公平性の差を原因段階へ分解し、検証付きで対策を導入できる。

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-403

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