You have already practised judging sources and spotting when media is trying to persuade you. Today the source is an AI chat tool: a large language model that writes answers that sound human.
Quick board prompt before we go further:
By the end of this lesson you will be able to say, in plain words, how these tools work, and you will audit a set of invented AI answers using three calls: trust, verify, or reject.
A large language model (LLM) is the engine inside most AI chat tools. In plain terms, it has read huge amounts of text and learnt patterns in how words tend to follow each other. When you ask a question, it predicts the most likely next stretch of text, one piece at a time, until it has built a full answer.
That is why the answers often sound smooth, polite and confident. The model is good at sounding like helpful writing. It is not checking a facts database the way a librarian would, and it does not know when it is wrong in the way a person does. It can sound just as sure when it is right as when it has invented a detail.
Before you audit any answers, think for a moment: what would make you trust a smooth AI answer straight away, and what would make you double-check it?
Work through the interactive activity together. For each invented AI answer, weigh the tells (the clues in how the answer is written), then commit to one verdict:
After each call, read the reasoning and notice which tell did the most work for you.
Now the whole class plays the rest, on your own devices.
Join with the code on the board. Everyone answers every round, not one person per table, and you can change your answer until the time is up. You also say how sure you are: just checking, fairly sure, or certain. The class's split appears on the board once the round closes, then the reasoning.
Getting it right matters less than being able to say why. A right answer earns what you staked and a wrong one loses it, so being unsure and saying so costs you very little - being certain and wrong is what costs. Every round has a defensible answer, and the reasoning behind it is what you are here for.
For each AI answer you did not simply trust, write one concrete check you would run before using it. Before you finish, check:
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