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• Outdated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Outdated Information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• Superseded information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

1. **RAG-based**: Answers grounded in your documents

2. **Source citations**: Shows where information came from

3. **Scoped responses**: Only answers from your knowledge base

4. **Uncertainty handling**: Acknowledges when information is missing

Hallucinations are inherent to how LLMs work. The solution is grounding AI in verified content.

[Try Grounded AI →](/signup)