AAISM AI Risk Management Practice Question
Which TWO measures are most effective in reducing the risk of 'Hallucinations' in LLM systems?
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
✓
Using Retrieval-Augmented Generation (RAG).
RAG and Grounding ensure the model relies on external, verified context rather than its internal probabilistic memory.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Training the model on larger public internet datasets.
Why it's wrong here
More internet data often increases hallucination risks.
- ✓
Using Retrieval-Augmented Generation (RAG).
Why this is correct
RAG anchors the model's output to specific, verifiable source documents.
- ✓
Providing clear system prompts defining constraints.
Why this is correct
System prompts can instruct the model to admit when it lacks information.
- ✗
Removing all punctuation from the input.
Why it's wrong here
This does not impact hallucination frequency.
- ✗
Increasing the model's temperature parameter to 2.0.
Why it's wrong here
High temperature increases randomness and hallucinations.
About these practice questions
Courseiva writes every AAISM question from scratch — 205 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. 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 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.