What is an AI Hallucination?

It's one of the most intriguing and dangerous quirks of modern AI. A hallucination is when an AI model generates false, nonsensical, or factually incorrect information but presents it with complete confidence, as if it were a proven fact.

First, The Ideal Scenario: A Factual Response

When you ask a well-behaved AI a question it knows, it generates a response that is grounded in the data it was trained on. Its internal "fact-checker" can trace its statement back to reliable sources in its knowledge base.

The Problem: The Confident Guess

But what if you ask a question where the answer isn't in its data? An LLM's core function is to predict the next word, not to know the truth. It will generate a sequence of words that is statistically plausible, even if it has no factual basis. It's essentially a confident, convincing guess.

Why Does This Happen?

Hallucinations occur because the AI is a pattern-matcher, not a database. It doesn't "look up" answers. It creates them. It's trying to be helpful and provide a fluent response, and in doing so, it can invent "facts," sources, and details that seem real but aren't connected to reality.

Trust, But Verify

AI hallucinations are a powerful reminder that these models are tools, not oracles. They can be incredibly creative and powerful, but their outputs must always be critically evaluated and fact-checked, especially in high-stakes situations like research, medicine, or law.