LittleAIMaster Activity Pack

Machine Learning for Teens

ages 13–18 · 2 activities · about 50 minutes each

Print this and work through one activity at a time. Each one ends with something you can check, so you can tell whether the idea actually landed rather than guessing.

1. Train a rock-paper-scissors classifier

Ages 7–14 · about 30 minutes

You need: A laptop with a webcam, Teachable Machine

  1. Create three classes: rock, paper, scissors.
  2. Record about thirty webcam samples of each hand shape.
  3. Train the model and test it live.
  4. Now test it with the child's other hand, or in a darker corner of the room, and note where it breaks.
  5. Add samples covering those failures and retrain.
It worked if: The child can say why the model failed on the untrained hand — the examples did not cover that case.

What went wrong / what surprised us:

2. Deliberately bias a model, then fix it

Ages 10–18 · about 45 minutes

You need: A laptop with a webcam, Teachable Machine

  1. Train a two-class model using samples of only one person.
  2. Test it on a second person and record how much accuracy drops.
  3. Write down a prediction for why before changing anything.
  4. Retrain including the second person and measure the difference.
It worked if: The child can connect an unrepresentative training set to a specific real-world harm, using their own measurement as evidence.

What went wrong / what surprised us:

A note on tools: everything recommended for ages 13–18 is free and runs in a browser. If a product asks you to pay before your child can finish an activity, there is almost always a free equivalent.

littleaimaster.com · Machine Learning for Teens

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