Use an AI-assisted lending decision system.
Users need to understand the purpose, limits, and source of a result.
Which activity improves transparency and explainability?
Document the purpose, input data, limitations, human involvement, and a contact or appeal path for users.
Detailed explanation
Users can understand the system's role and seek human review when necessary.
Users can understand the system's role and seek human review when necessary.
This encourages overreliance and prevents informed risk decisions.
This encourages overreliance and prevents informed risk decisions.
Without records, explanations and audits cannot be performed.
Without records, explanations and audits cannot be performed.
The automation boundary and accountability become unclear.
The automation boundary and accountability become unclear.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 4.2で、透明性・説明可能性・監査の説明を確認する。Expected result
説明可能性を、モデルの内部だけでなく利用者への情報提供と責任分担まで含めて説明できる。Key points
- Transparency
- Stating limitations
- Accountability
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
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.