AI UNIT 1 • STAGE 3 OF 5
Training data, in plain language, and why it shapes what the AI can say about your people
In Stage 2 you saw the AI do well on some questions and poorly on others, especially about your own nation. This stage answers why.
It comes down to one idea: training data. An AI learns by being shown an enormous pile of writing, mostly text collected from the internet, and finding patterns in it. It doesn't look anything up. It repeats and remixes the patterns it saw.
Put the question to the AI directly.
Notice whether it admits the limits of what it was trained on.
Here's the part that matters for your community. The AI is only as good as what people wrote down and put online. So ask yourself:
An AI can't know your nation better than the internet does. When your community's own voices aren't in the training data, the AI fills the gap with guesses and stereotypes.
Look back at your Stage 2 examples. In your Field Notes, explain training data in your own words, and connect it to what you saw: where were the AI's answers thin, and whose voices were missing from the "pile"?
Who gets to write the record about your people? Who owns that data? You're now asking the exact questions the later AI units are built around.
Explain what you're learning in your own words:
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