AIP-C01 practice question: AI governance frameworks (model cards, lineage, approval)

AI Safety, Security, and Governance A free question from our original AIP-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.

An HR technology company sells a candidate screening assistant that ranks applicants with a model hosted on Amazon SageMaker AI. Customers in several countries use the same model version.

Auditors from two customers have asked for documentation of what the model is meant to do, which uses it should not support, and where its accuracy is weaker. The company's model registry already tracks each version and its approval status.

The documentation must stay with each model version, and no version should reach production unless that documentation is complete.

Which TWO actions meet these requirements? (Choose two.)

Choose two answers.

A. Store the training notebook and hyperparameters in the team's Git repository, and point auditors to the commit history as the record of what the model is intended to do.
B. Create a SageMaker Model Card for each model version that records intended use, prohibited uses, subgroup evaluation results and known limitations, linked to that version in the registry.
C. Publish one company-wide responsible AI policy document that applies to all models, and ask each product team to read it before launch, without recording anything specific to each model version.
D. Add a pipeline check that sets a version's status to Approved only after its model card lists intended use and limitations, and deploy only Approved versions.
E. Add a tag with the model owner's name to each endpoint, and keep the design review's chat history as the record of decisions about the model and its limits.

Show the answer and explanation

Answers: B, D

A. Wrong: Commit history shows how the model was built, but it does not state the intended use, the prohibited uses or the known weak spots that auditors need. The requirement asks for documentation a reviewer can read, and commit logs do not provide that.
B. Right: A model card keeps the intended use, prohibited uses, evaluation results and limitations together, and attaching it to the registered version ties the record to the exact version in use. This answers the auditors' request for documentation that stays with each version. Learn more: Amazon SageMaker Model Cards (opens in a new tab)
C. Wrong: A general policy describes principles but does not say what a specific model version is for or where it is weak. Without a per-version record, auditors cannot match the documentation to the version that is running in production. Learn more: Responsible AI on AWS (opens in a new tab)
D. Right: Making the approval status depend on a complete card turns the documentation into a gate, so no version reaches production without it. It links the model card to the approval process that the company already uses for each version. Learn more: Update the approval status of a model (opens in a new tab)
E. Wrong: Tags show ownership but not the model's limits, and chat history is hard to audit and easy to lose. Neither gives auditors a maintained description of the model version they are reviewing.

Explanation

Model cards record intended use, prohibited uses, subgroup results and limitations for each version, and keeping the card with the registered version ties the record to what runs in production. Making the approved status depend on a complete card stops any version from reaching production without that documentation. Commit history, a general policy and tags do not give auditors a version-specific record.

AIP-C01 practice question: AI governance frameworks (model cards, lineage, approval)

Explanation

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