Every AI system has an error rate. The useful question is never "is it accurate?" but "accurate at what, measured how, and how would I notice a mistake?" Different tasks fail in different ways, and the measurements are not interchangeable.

Two very different failure modes

Speech recognition fails by mishearing. You get a word that sounds like the right one, and word error rate counts it. Text generation fails by inventing. You get a fluent, well-formed sentence that happens to be false — and no counting metric will flag it for you.

How to check without becoming an expert

  • Spot-check the hard parts. Names, numbers, dates and technical terms are where errors cluster.
  • Ask for sources, then open them. A citation that cannot be opened is not a citation.
  • Re-ask differently. Answers that change materially on rephrasing were never well grounded.
  • Compare against something you already know. Test the tool on a topic where you would catch a mistake.

Rule of thumb: trust an AI system in proportion to how easily you could verify it. Easy to check means low risk. Impossible to check means high risk, regardless of how confident the output sounds.

is never 'is it accurate?' but 'accurate at what, measured how?' Word error rate answers it for speech. For text generation the failure mode is different, and stranger.

These guides define the measurements, explain why confident-sounding output can still be wrong, and set out how to check.