AAIA AI Governance And Risk Practice Question
A firm uses a 'Federated Learning' approach. Which governance benefit does this provide?
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
✓
Enhanced data privacy by keeping raw data locally on devices
Federated learning allows training on decentralized data, keeping raw data on local devices, which enhances privacy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduced usage of electricity
Why it's wrong here
Federated learning is not necessarily more energy-efficient.
- ✗
Faster model training times
Why it's wrong here
Federated learning is usually slower than centralized training.
- ✗
Improved model interpretability
Why it's wrong here
Interpretability is about model logic, not the learning architecture.
- ✓
Enhanced data privacy by keeping raw data locally on devices
Why this is correct
Because raw data is not centralized, the privacy risk is significantly reduced.
About these practice questions
One of 209 original AAIA practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
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.