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A fluent answer can contain an invented fact, an unsupported conclusion or a citation that does not support the claim. Confidence in the writing is not evidence of factual accuracy.
For practical work, separate two questions: is the answer consistent with the supplied material, and is that material itself reliable and current? An answer can pass one test while failing the other.
A confident answer needs evidence. RAG can supply relevant source material, while a deliberately chosen evaluation set helps reveal cases where the answer is still unsupported.
Use a claim-checking worksheet
Choose a short AI-generated explanation of a topic you can verify. Break it into individual factual claims. For each claim, record the original source, the supporting passage and your verdict: supported, contradicted or unresolved.
Be especially careful with:
- Exact figures and publication dates.
- Product features and pricing.
- References to research papers or official policies.
- Claims about what a tool “always” or “never” does.
Design a better failure response
If a customer assistant lacks evidence about a refund exception, it should identify the missing information and route the question appropriately. It should not produce a more polished guess. A citation is useful only when readers can inspect it and it supports the answer.
For a project report, publish the number of checked claims and explain the checking process. Do not invent a reliability percentage from a handful of convenient examples.
Discussion: What is the most useful way to communicate uncertainty to users without making an assistant unhelpful?
Background: Google Machine Learning glossary.
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