- A
Apply a blur filter to all faces in the dataset using Amazon Rekognition before labeling.
Why wrong: Blurring faces does not give consent; using the image may still be a violation.
- B
Use Amazon Rekognition to detect faces in all images and re-label those without consent as invalid.
Why wrong: Rekognition detects faces but cannot determine consent status; re-labeling is manual and expensive.
- C
Create an Amazon Simple Workflow Service (SWF) workflow that cross-references image metadata with the consent list, and update the Ground Truth manifest to include only approved images.
This creates an automated pipeline to filter approved images based on the consent list, using SWF for workflow orchestration.
- D
Use Amazon SageMaker Clarify to detect bias in the training data and exclude images of people.
Why wrong: Clarify is for bias metrics, not consent management; excluding all people images may remove necessary data.
Quick Answer
The correct answer is to create an Amazon Simple Workflow Service (SWF) workflow that cross-references image metadata with the consent list, and update the Ground Truth manifest to include only approved images. This approach is correct because SWF provides a reliable orchestration layer for coordinating multi-step, human-in-the-loop processes, such as the Ground Truth consent compliance cross-reference with SWF, where a privacy team’s consent list must be programmatically matched against image metadata before the manifest is filtered. On the AWS Certified AI Practitioner AIF-C01 exam, this scenario tests your understanding of how to enforce data privacy within SageMaker workflows without modifying the original dataset—a common trap is to suggest relabeling or deleting images, which violates audit requirements. Remember the memory tip: “SWF syncs the consent list, then the manifest is kissed.” This highlights that SWF handles the cross-referencing step, and the manifest update is the final action to ensure only consented images proceed to training.
AIF-C01 Practice Question: Security, Compliance and Governance for AI Solutions
This AIF-C01 practice question tests your understanding of security, compliance and governance for ai solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is using Amazon SageMaker Ground Truth to create labeled datasets for a computer vision model. The dataset contains images of people in public places. The company must comply with data privacy regulations that require explicit consent for using images of individuals. The company has a privacy team that reviews the images and provides consent lists. The ML team suspects that some images in the dataset might include individuals who have not consented. The company wants to ensure that only those images with consent are used for training. What should the company do?
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
Create an Amazon Simple Workflow Service (SWF) workflow that cross-references image metadata with the consent list, and update the Ground Truth manifest to include only approved images.
Option C is correct because it uses Amazon Simple Workflow Service (SWF) to orchestrate a cross-referencing workflow between image metadata and the consent list, then updates the SageMaker Ground Truth manifest to include only approved images. This ensures that only images with explicit consent are used for training, directly addressing the data privacy compliance requirement without altering or mislabeling the data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Apply a blur filter to all faces in the dataset using Amazon Rekognition before labeling.
Why it's wrong here
Blurring faces does not give consent; using the image may still be a violation.
- ✗
Use Amazon Rekognition to detect faces in all images and re-label those without consent as invalid.
Why it's wrong here
Rekognition detects faces but cannot determine consent status; re-labeling is manual and expensive.
- ✓
Create an Amazon Simple Workflow Service (SWF) workflow that cross-references image metadata with the consent list, and update the Ground Truth manifest to include only approved images.
Why this is correct
This creates an automated pipeline to filter approved images based on the consent list, using SWF for workflow orchestration.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Amazon SageMaker Clarify to detect bias in the training data and exclude images of people.
Why it's wrong here
Clarify is for bias metrics, not consent management; excluding all people images may remove necessary data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse privacy compliance with data anonymization (blurring faces) or bias detection, rather than recognizing that explicit consent requires a cross-referencing workflow against an external consent list, which is best orchestrated by a workflow service like SWF.
Detailed technical explanation
How to think about this question
Amazon SWF coordinates distributed tasks across multiple services, making it suitable for workflows that require human approval steps, such as cross-referencing image metadata with an external consent list. The SageMaker Ground Truth manifest is a JSON Lines file where each line contains the image URI and labels; updating this manifest to include only approved images effectively filters the dataset before training. This approach maintains data integrity by not modifying the original images, which is critical for audit trails in regulated environments.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
Security, Compliance and Governance for AI Solutions — This question tests Security, Compliance and Governance for AI Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an Amazon Simple Workflow Service (SWF) workflow that cross-references image metadata with the consent list, and update the Ground Truth manifest to include only approved images. — Option C is correct because it uses Amazon Simple Workflow Service (SWF) to orchestrate a cross-referencing workflow between image metadata and the consent list, then updates the SageMaker Ground Truth manifest to include only approved images. This ensures that only images with explicit consent are used for training, directly addressing the data privacy compliance requirement without altering or mislabeling the data.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 2026
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.
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