Require one doubt, one check, one source
A standing rule for every AI answer: one place it could be wrong, one way to check it, one non-AI source to consult.
Sep 30, 2026 · 1 min read
The danger is not that students believe everything a chatbot says; it is that they stop asking whether they should. A fixed three-part routine turns scepticism into procedure: after any AI explanation, students write one place it could be wrong, one test that would check it, and one non-AI source they would consult. Long and Magerko (2020) put exactly this evaluative stance at the centre of AI literacy: treating output as a claim to assess, not truth to absorb. (Manning's ai-claim-checker skill builds a full protocol around this routine.)
In practice
After any AI answer, before you use it, write:
1. One place it could be wrong (name the exact
claim, step or statement).
2. One check that would test it (a calculation,
a comparison, an experiment).
3. One source you would consult that is not
another AI: textbook, database, journal,
person who knows.- Print the three questions on a card or slide: where could this be wrong, what would you check, and name one source that is not another AI.
- Ban vague answers: 'it might be biased' scores nothing, while 'the 1987 date needs checking against the textbook' counts.
- Sample a few responses aloud each week and probe the weak ones, so the routine stays thinking rather than box-ticking.
- When a genuine error surfaces, celebrate it and ask the finder to explain to the class why the model got it wrong.
Quick takeaway: no AI answer is finished until it carries a doubt, a check and a source.