AI hallucination
An AI hallucination is when an AI tool states something false or invented while sounding completely confident, presenting a wrong fact, a fake citation, or a made-up source as if it were true. For students using general chatbots to study, it is the main reason answers can quietly mislead.
Large language models predict likely-sounding text, not verified facts. When a model does not actually know something, it often guesses rather than admitting the gap, so the answer can read as polished and certain while being wrong. The confidence is the trap. A hallucinated explanation looks exactly like a correct one.
A common misconception is that hallucinations only happen on obscure topics. They also show up on basic material: a wrong date, a misattributed quote, a citation to a paper that does not exist. If the answer comes with no source you can check, you have no way to tell a real fact from a fluent guess.
A student asks a general chatbot to explain the steps of the Krebs cycle before an exam. The bot lists eight steps confidently, but swaps two intermediates and invents an enzyme name. The student memorizes it, then loses marks on the exam for an error the AI introduced.