SAP-C03 practice question: Responsible AI controls (Bedrock Guardrails, AgentCore Identity, human approval) (1 of 2)
Security, Compliance, and Governance A free question from our original SAP-C03 practice exam. Try it, then open the answer to see why each option is right or wrong.
A news publisher is launching an assistant that answers readers' questions from its article archive through an Amazon Bedrock knowledge base. Editors require that the assistant decline medical and financial advice, never reveal personal data such as email addresses or account numbers, and make claims only where they are supported by the retrieved articles.
The assistant is used on the website and in the mobile app, and the same rules must apply to every question without depending on each app's code. Editors also want to change the list of blocked topics without redeploying the apps.
Which solution meets these requirements?
Choose one answer.
AA. Add instructions to the system prompt that tell the model to decline medical and financial questions, never repeat personal data, and answer only from the supplied articles, and store the prompt centrally.
BB. Run every answer through an AWS Lambda function that removes email addresses and account numbers with regular expressions before the answer is shown.
CC. Fine-tune a foundation model in Amazon SageMaker AI with examples of refusals and redacted answers, and have both apps call the fine-tuned model.
DD. Create a Bedrock guardrail with denied topics for medical and financial advice, sensitive information filters and contextual grounding checks, and apply it to the model invocations.
Show the answer and explanation
Answer: D
A. Wrong: Prompt instructions are not enforced, and a user can craft a question that gets around them. Even a centrally stored prompt gives no grounding check and no reliable filtering of personal data.
B. Wrong: The function redacts only the patterns it knows, and it does not decline topics or check that the claims are grounded in the articles. Each app would also need to call the function.
C. Wrong: Fine-tuning adds a training project, and the refusals are learned behavior rather than a policy that can be checked and changed on request. Editors would also need a new model each time the blocked topics change.
D. Right: Correct. The guardrail is applied to the model calls on the back end, so both apps get the same rules without changing their code. Editors can change the denied topics and filters in the guardrail, and grounding checks test the answers against the retrieved articles.
Explanation
A Bedrock Guardrail applied to the model invocations enforces denied topics, sensitive information filters and grounding checks for every app, and editors can change its settings without redeploying. Prompt text, fine-tuning and a redaction function each leave one rule unenforced or tied to app code.
Want more on Responsible AI controls (Bedrock Guardrails, AgentCore Identity, human approval)? The 5 full-length practice sets have 7 more Responsible AI controls (Bedrock Guardrails, AgentCore Identity, human approval) questions, 375 in all, none of them in the free exam. One payment of $14.99, no subscription. See the practice sets →