AAIA AI Auditing Tools And Techniques Practice Question
When selecting testing techniques for an AI model, which THREE are considered 'Model-Agnostic'?
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
✓
SHAP (SHapley Additive exPlanations)
LIME, SHAP, and Partial Dependence Plots (PDPs) are model-agnostic methods that work with any ML model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
SHAP (SHapley Additive exPlanations)
Why this is correct
A model-agnostic method for feature contribution.
- ✗
Neural network weight pruning
Why it's wrong here
Specific to neural networks.
- ✓
Partial Dependence Plots (PDPs)
Why this is correct
Shows the effect of a feature on predicted outcomes for any model.
- ✗
Linear regression coefficients
Why it's wrong here
Specific to linear models.
- ✓
LIME (Local Interpretable Model-agnostic Explanations)
Why this is correct
Designed to work with any model.
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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 AAIA 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 AAIA exam.