AIF-C01 Guidelines for Responsible AI Practice Question
A financial services company uses Amazon Rekognition to verify customer identities. To ensure responsible AI practices, which measure should the company prioritize?
⚠ Common exam trap
A common mix-up: candidates confuse 'responsible AI' with generic model optimization (like increasing accuracy or reducing data), but the exam specifically tests the principle of fairness through bias auditing and transparency.
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
✓
Regularly audit the model for demographic bias
Regularly auditing the model for demographic bias is a core responsible AI practice, especially for identity verification systems where biased outcomes could lead to unfair treatment of certain customer groups. Amazon Rekognition's facial analysis and comparison features must be tested across diverse demographics to ensure equitable performance, as bias can arise from imbalanced training data or algorithmic artifacts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use only black-box models to protect intellectual property
Why it's wrong here
Black-box models reduce transparency.
- ✗
Increase model complexity to improve accuracy
Why it's wrong here
Increasing complexity may reduce explainability.
- ✗
Minimize the amount of training data collected
Why it's wrong here
Data minimization does not guarantee fairness.
- ✓
Regularly audit the model for demographic bias
Why this is correct
Bias audits are essential for fairness.
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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.