CRISC Information Technology and Security Practice Question
A bank is considering adopting artificial intelligence for credit scoring. The risk manager identifies that the AI model might produce biased outcomes against certain demographic groups. Which AI/ML risk is most directly associated with this concern?
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
✓
Model bias
Model bias occurs when training data or algorithms produce unfair or discriminatory outcomes, directly impacting fairness and regulatory compliance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Model bias
Why this is correct
Correct. Model bias leads to unfair outcomes based on demographics.
- ✗
Adversarial attacks
Why it's wrong here
Adversarial attacks involve manipulating input data to deceive the model, not bias.
- ✗
Explainability requirements
Why it's wrong here
Explainability is about understanding model decisions, not bias itself.
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Data privacy in AI training
Why it's wrong here
Data privacy concerns confidentiality, not bias.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CRISC practice question is part of Courseiva's free ISACA 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 CRISC exam.