Lesson 5 of 6
Why AI Gets Things Wrong
Models hallucinate because they generate plausible text, not verified truth. This lesson explains why — and why grounding and evidence are the defense.
Learning objectives
- ▸Define an AI hallucination.
- ▸Explain the root cause of hallucination.
- ▸Explain how grounding and evidence reduce it.
The lesson
Read the full lesson →Why Do AI Models Hallucinate?AI models hallucinate — state false things confidently — because they generate the most plausible text, not verified truth. When training patterns run thin, they fill the gap with fluent fabrication. Grounding in real sources is the main fix.2 min readKey takeaways
- ▸A hallucination is confident, fluent output that's false or unsupported.
- ▸Root cause: models optimize for plausibility, not truth, and can't tell the difference.
- ▸Grounding in retrieved sources reduces it — and engines favor evidenced, low-risk sources.
Knowledge check
Knowledge check
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1. Why do LLMs hallucinate?
2. What's the most effective way to reduce hallucination?
3. Why is being well-evidenced good for AEO?