AIF-C01 Guidelines for Responsible AI Practice Question

Exhibit

Refer to the exhibit.
```
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "sagemaker:CreateNotebookInstance",
      "Resource": "*"
    },
    {
      "Effect": "Allow",
      "Action": "s3:GetObject",
      "Resource": "arn:aws:s3:::company-training-data/*"
    },
    {
      "Effect": "Allow",
      "Action": "sagemaker:CreateModel",
      "Resource": "*"
    }
  ]
}
```

Refer to the exhibit. A team is creating an IAM policy for a SageMaker notebook user. The user needs to access training data in an S3 bucket and create models. Which responsible AI concern is most relevant to this policy?

⚠ Common exam trap

AWS often tests the principle of least privilege by presenting a policy with wildcard permissions (e.g., s3:* or sagemaker:*), and candidates mistakenly focus on missing features like encryption or explainability instead of recognizing the core violation of excessive access.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

The policy grants overly broad permissions, violating the principle of least privilege.

The IAM policy grants the SageMaker notebook user overly broad permissions (e.g., s3:* or sagemaker:*), which violates the principle of least privilege. This is a core responsible AI concern as it increases the risk of unauthorized access or accidental modification of training data and models. The policy should restrict actions to only those necessary for the user's specific role, such as s3:GetObject for specific buckets and sagemaker:CreateModel with resource constraints.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
The policy does not enforce encryption for the notebook.
Why it's wrong here
Encryption is not shown in this policy snippet.
✗
The policy does not restrict which S3 buckets the user can read.
Why it's wrong here
The policy restricts to one bucket (company-training-data).
✗
The policy does not include a condition for model explainability.
Why it's wrong here
Explainability is not enforced via IAM policies.
✓
The policy grants overly broad permissions, violating the principle of least privilege.
Why this is correct
Allowing CreateModel and CreateNotebookInstance on all resources can lead to misuse.

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

Go deeper

AIF-C01 Guidelines for Responsible AI Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

Related to this question