5.1Standard
A model generates unsafe language.
Manage misses and false alarms.
Choose two controls.
× Incorrect
Detect by category, severity, language, and context, then route display, refusal, and human review differently while measuring misses, false positives, and privacy.
Detailed explanation
CorrectMeasure misses, false positives, language gaps, and provide explanation and appeal
Filter side effects are managed.
CorrectUse category, severity, language, and context to route display, refusal, or review
Risk drives handling.
IncorrectOne score has the same meaning in every language and context
Calibration differs.
IncorrectStore every harmful output indefinitely in plaintext
Exposure grows.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 4・5.2の有害出力、ガードレール、ログ保護を確認する。
Official references
What to confirm
危険度に応じて出力を扱い、検出器の言語差と誤検知を改善できる。
Key points
- Harmful output
- Severity
- Appeal
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Harmful-content detector
A classifier or rule set that identifies content associated with a safety policy.
Severity
A level describing the potential impact of a harmful event or output.
Question IDAWS-AIF-496
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
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