It’s when generated text sounds believable but includes claims that are wrong, unsupported, or misleading. Here’s how to recognize it.
AI hallucination is not “bad writing.” It’s a reliability problem: the output may contain facts, quotes, dates, or numbers that don’t match reality—or that can’t be verified.
You’ll usually see it when the text includes specific claims without providing sources, or when it confidently fills gaps that should have been left open.
The goal isn’t to panic. The goal is to spot what to verify first.
Dates, numbers, quotes, and “how-to” steps should have a believable basis.
If references aren’t provided, treat the claim as something to verify.
Use a quick signal to decide what to verify first, then follow up.
Not necessarily. Hallucination usually refers to generated content that sounds convincing while containing claims that can’t be verified.
Verify hard claims first, request sources, and use a consistent review checklist.
Yes. It’s useful when you need accuracy in drafts, reports, and customer-facing answers.
No. It helps you decide what to verify, so your research time is used wisely.