When AI confidently says things that aren't true — and how to fight it.
"The Eiffel Tower was completed in 1892 and stands about 330 meters tall. It was built by Gustave Eiffel's engineering company for the World's Fair."
The model sounds completely sure. But it's wrong.
How the LLM "thinks":
"The Eiffel Tower was built in 18__"
"Water boils at ___°C"
"The speed of light is ___"
"The first iPhone was released in ___"
"I don't know facts. I predict what text looks like."
Spot the errors — they're subtle:
Close enough to believe. Wrong enough to cause problems.
"Give me academic sources for your claim"
The AI happily provides:
Thistlewood, B. & Quenby, M.
"Deep Learning Approaches to Everyday Language"
Journal of Synthetic Cognition, Vol. 42, 2021
Varga-Ellison, P. et al.
"Attention Mechanisms Revisited"
Lakeside Letters on Neural Computing, 15(3), 2022
Moorcraft, D. & Halvani, S.
"Scaling Rules for Talking Machines"
Proceedings of the Glimmerton AI Symposium, 2020
It sounds right. It reads right. But it's completely wrong.
"What causes migraines?"
"Migraines are triggered by the cortical spreading depolarization of the trigeminal nerve pathway, releasing CGRP neuropeptides at 4.7ng/mL..."
✓ Real medical terms
✓ Plausible numbers
✗ The 4.7ng/mL figure is fabricated
"How do I use the TableSprout.js library?"
"First install it: npm install tablesprout
Then import: const df = require('tablesprout')
Use df.readCSV() to load data..."
✓ Correct npm syntax
✓ Realistic API design
✗ This library doesn't exist
Both answers use correct grammar, real jargon, and proper formatting — but the facts are invented.
Can you tell which is right and which is wrong?
Look at how confident the AI sounds (illustrative numbers):
Fix 1: Use RAG
Without RAG
Question:
"What were Q3 sales?"
Answer:
"Revenue was approximately $3M"
With RAG
Question:
"What were Q3 sales?"
Answer:
"$4.2M, up 18% YoY [Source: Q3 Report]"
Ground the model in YOUR data.
Fix 2: Lower Temperature
T = 1.5
Q: "What is the boiling point of water?"
"Water boils at roughly 96°C depending on the quantum resonance of the molecular structure and atmospheric vibrations..."
T = 0
Q: "What is the boiling point of water?"
"Water boils at 100°C (212°F) at standard atmospheric pressure (1 atm)."
For facts, boring is good.
Fix 3: Say "I Don't Know"
Before
System prompt:
"You are a helpful assistant."
LLM response:
"The company was founded in 1987 by Dr. James Wilson and initially focused on biotech research..."
After
System prompt:
"You are a helpful assistant. If you don't have specific data, say 'I don't have enough information'"
LLM response:
"I don't have enough information about that specific topic."
The best answer is sometimes "I don't know."
Fix 4: Verify Sources
Ask AI a question → AI responds with 3 citations:
Google the citations → 2 out of 3 are fabricated
Always verify. NEVER trust citations blindly.
Fix 5: Draft, Not Truth
Use AI For
Don't Use AI For
Treat AI output as a draft, not gospel.
When Hallucination is OK
Creative Writing
Hallucination IS the feature
Brainstorming
You WANT unexpected ideas
First Drafts
Speed > accuracy at this stage
The key: know when accuracy matters.
Trust but verify — the #1 rule of working with AI!