AIF-C01 Guidelines for Responsible AI Practice Question
A company uses Amazon Rekognition for facial analysis. They want to ensure the model doesn't exhibit bias based on skin tone. What should they do?
⚠ Common exam trap
Candidates often confuse increasing dataset size (via augmentation or larger models) with ensuring dataset diversity, but without explicit inclusion of diverse skin tones, bias remains unaddressed.
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
✓
Ensure the training dataset includes diverse skin tones
Bias in facial analysis models, such as those used by Amazon Rekognition, often stems from imbalanced training data. By ensuring the training dataset includes diverse skin tones, the model learns to recognize features across all demographic groups, reducing performance disparities and promoting fairness. This directly addresses the root cause of bias in machine learning models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Ensure the training dataset includes diverse skin tones
Why this is correct
Balanced representation mitigates bias.
- ✗
Apply data augmentation to increase dataset size
Why it's wrong here
Data augmentation does not guarantee diversity.
- ✗
Use a larger neural network
Why it's wrong here
Network size does not address bias.
- ✗
Use a pre-trained model from AWS Marketplace
Why it's wrong here
Pre-trained models may have inherent bias.
Go deeper
Related to this question
About these practice questions
This AIF-C01 question is part of Courseiva's 619-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.