AAISM AI Risk Management Practice Question
You are managing an AI project and notice the model is performing poorly on a subset of data representing a protected class. What is the correct next step in the risk assessment process?
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
✓
Investigate the data representation and training balance for that subgroup.
Performing a root cause analysis on the data used to train that specific segment is the correct diagnostic step.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Immediately delete all training data.
Why it's wrong here
This is an extreme and destructive action without investigation.
- ✓
Investigate the data representation and training balance for that subgroup.
Why this is correct
Bias is often rooted in data imbalances, which must be investigated.
- ✗
Dismiss the finding as a minor edge case.
Why it's wrong here
This ignores the ethical and risk implications of bias.
- ✗
Replace the model architecture with a simpler one.
Why it's wrong here
Architecture does not solve dataset bias issues.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official ISACA exam blueprint
This AAISM 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 AAISM exam.