THE SHORT ANSWER

Ask the system to separate claims from assumptions, identify uncertainty, offer alternatives and suggest sources to verify. Treat those responses as generated leads, not access to hidden reasoning or evidence. Check important claims against authoritative independent sources.

Turn a fluent answer into checkable parts

  • What assumptions does this answer depend on?
  • Which claims need external evidence?
  • Which parts are uncertain or context-dependent?
  • What alternative explanation fits the same information?
  • What missing information would change the answer?
  • Can you separate reported facts, calculations and inference?

Evidence & context: NIST

Leave the chat when the claim matters

Ask for a precise source, then open and evaluate it. Check whether it exists, supports the claim, is current enough and is independent of the answer. Lateral reading—investigating a source beyond its own presentation—can help assess credibility.

Use How to Verify AI-Generated Information for the full process and Why Does AI Hallucinate? for the mechanism.

Evidence & context: Digital Inquiry Group

Match scrutiny to consequence

A brainstorming suggestion and a consequential recommendation do not deserve the same review. NIST guidance treats human and AI roles, reliance and oversight as context-dependent. For high-consequence choices, use qualified sources and accountable human review.

Do not use a longer prompt as a substitute for evidence. Repeating the question may produce a different answer without resolving which one is supported.

Evidence & context: NIST AI Resource Center

Run a three-pass challenge

  1. Frame: state the decision, audience, constraints and unknowns.
  2. Challenge: ask for assumptions, uncertainty, alternatives and falsifying information.
  3. Verify: select one consequential claim and check it outside the model.

Then record what you accepted, rejected and left unresolved. Using AI as a Thinking Partner shows how to explore without outsourcing judgment.

Sources & further reading

  1. Generative Artificial Intelligence Profile (NIST AI 600-1)

    NIST. Risk-management guidance, including confabulation. It does not establish a universal error rate.

  2. AI Risk Management and Human-AI Interaction

    NIST AI Resource Center. Official guidance on different human and AI decision roles and oversight. Appropriate reliance depends on context, consequence and system evidence.

  3. Civic Online Reasoning

    Digital Inquiry Group. Source-evaluation teaching resources, including lateral reading: investigating a source beyond its own website.

Examples and exercises are illustrative unless attributed to a source. No independent expert review is claimed.

A correction, a counterexample or an experience worth sharing?

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