Table of Contents
AI Hallucinations: What They Are and How to Prevent Them
AI confidently stating false information is a real problem. Here's how to understand and address it.
What Are AI Hallucinations?
Hallucinations occur when AI generates information that sounds plausible but is:
- Factually incorrect
- Made up entirely
- Misattributed
- Outdated
Why AI Hallucinate
LLMs predict the most likely next words based on patterns. They don't:
- Verify facts
- Check sources
- Know what they don't know
- Distinguish truth from fiction
They're pattern-matching, not fact-checking.
Types of Hallucinations
Factual Errors
- Wrong dates, numbers, names
- Incorrect attributions
- Non-existent citations
Confident Fabrication
- Made-up statistics
- Invented quotes
- Fictional events
Outdated Information
- Old data presented as current
- Superseded information
- Historical inaccuracies
Prevention Strategies
1. Use RAG (Retrieval Augmented Generation)
Ground AI in your actual content. This is what Assisters does.
2. Limit Scope
Tell the AI what it can and can't answer.
3. Request Sources
Ask for citations and verify them.
4. Acknowledge Uncertainty
Train AI to say "I don't know" when appropriate.
5. Human Review
Critical applications need human verification.
How Assisters Reduces Hallucinations
- RAG-based: Answers grounded in your documents
- Source citations: Shows where information came from
- Scoped responses: Only answers from your knowledge base
- Uncertainty handling: Acknowledges when information is missing
Hallucinations are inherent to how LLMs work. The solution is grounding AI in verified content.