AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 119 · 40 questions

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

1. 1.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) unlocking with a face (c) inventing a recipe (d) reading number plates
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
3. 3.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) use one group only (d) fix wrong labels
4. 4.Which of these is training data? (a) what training builds (b) naming a new leaf (c) naming a new fruit photo (d) past weather records
5. 5.✅ Is this a real check of an AI answer: it answered quickly? (a) not a real check (b) a real check
6. 6.Which of these adds to bias? (a) ask different people (b) test on many groups (c) ignore complaints (d) check who is missing
7. 7.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
8. 8.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
9. 9.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) very few examples (d) many varied examples
10. 10.🔍 Which is the odd one out? (a) unlocking with a face (b) drawing a new picture (c) writing a new poem (d) inventing a recipe
11. 11.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
12. 12.🧐 Fact or myth: “AI can mix up numbers”? (a) a fact (b) a myth
13. 13.True or false: “a cheerful tune for Sports Day” asks for text. (a) True (b) False
14. 14.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) blurry, unclear photos (d) examples of every type
15. 15.Which of these is the model? (a) flagging a new email (b) past weather records (c) the learned patterns (d) labelled fruit photos
16. 16.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
17. 17.✅ Is this a real check of an AI answer: it uses big words? (a) a real check (b) not a real check
18. 18.🔍 Which is the odd one out? (a) blurry, unclear photos (b) checking labels twice (c) labels added at random (d) wrong labels
19. 19.True or false: switching on a street light at 6 pm needs AI that learns from examples. (a) True (b) False
20. 20.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
21. 21.True or false: a map app guessing how long a trip will take is AI generating something new. (a) False (b) True
22. 22.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
23. 23.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
24. 24.True or false: “a poster of a rainforest” asks for an image. (a) True (b) False
25. 25.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
26. 26.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
27. 27.True or false: “see if the book exists” is NOT a real way to check an AI answer. (a) False (b) True
28. 28.Which of these is generative AI (it makes something new)? (a) spotting spam (b) unlocking with a face (c) sorting photos by face (d) composing a new tune
29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
31. 31.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) clear, sharp examples (d) very few examples
33. 33.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
34. 34.True or false: showing the time on a clock needs AI that learns from examples. (a) True (b) False
35. 35.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) ignoring mistakes (d) one group only
36. 36.🛠️ Which does this job need: reading messy handwriting? (a) a simple rule is enough (b) needs AI (learning)
37. 37.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) ask it to hurry (c) check it on paper (d) copy it straight away
38. 38.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
39. 39.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
40. 40.Which of these is the model? (a) what training builds (b) 500 labelled leaf photos (c) old emails marked spam (d) recorded spoken words

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