AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 481 · 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 a fact about AI? (a) AI is never wrong (b) AI can make up facts (c) AI has real feelings (d) AI always checks facts
2. 2.True or false: “check who is missing” adds to bias. (a) False (b) True
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
4. 4.True or false: “test on one group only” helps reduce bias. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) labels added at random (b) checking labels twice (c) blurry, unclear photos (d) wrong labels
6. 6.🏠 AI or not AI: a map predicting traffic? (a) uses AI (b) not AI
7. 7.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
8. 8.True or false: a phone unlocking when it sees your face is AI predicting something. (a) True (b) False
9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
10. 10.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
12. 12.Which of these is a myth about AI? (a) AI can make up facts (b) AI can mix up numbers (c) AI has real feelings (d) AI learns from data
13. 13.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) music or sound (b) text (c) an image
14. 14.🤖 What does AI stand for? (a) artificial intelligence (b) actual information (c) automatic internet (d) app installer
15. 15.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
16. 16.True or false: “old emails marked spam” is training data. (a) True (b) False
17. 17.Which of these is not AI? (a) a voice assistant (b) a microwave timer (c) photos grouped by face (d) a map predicting traffic
18. 18.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
19. 19.Which of these is not AI? (a) a map predicting traffic (b) face unlock on a phone (c) a spam filter (d) a printed timetable
20. 20.🔍 Which is the odd one out? (a) predicting rain (b) spotting spam (c) making up a story (d) unlocking with a face
21. 21.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
22. 22.Which of these is a prediction? (a) 500 labelled leaf photos (b) the trained program (c) flagging a new email (d) recorded spoken words
23. 23.🔍 Which is the odd one out? (a) a calculator (b) voice typing (c) a light switch (d) a torch
24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
25. 25.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
26. 26.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) test on one group only (d) balance the data
27. 27.True or false: “five quiz questions on fractions” asks for text. (a) False (b) True
28. 28.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
29. 29.Which of these is a myth about AI? (a) AI is never wrong (b) AI answers need checking (c) AI can make up facts (d) AI copies data patterns
30. 30.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it uses electricity (c) it learns from examples (d) it has a screen
31. 31.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
32. 32.📚 An AI chatbot names a book that does not exist. This is called… (a) a hallucination (b) a backup (c) a password (d) a summary
33. 33.Which of these is the model? (a) recorded spoken words (b) old emails marked spam (c) what training builds (d) 500 labelled leaf photos
34. 34.📱 What is the AI doing here: an AI chatbot writing a poem about rain? (a) predicting (b) recommending (c) generating (d) recognising
35. 35.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
36. 36.True or false: finding 10% of a price needs AI that learns from examples. (a) True (b) False
37. 37.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) add more of the same (d) add varied examples
38. 38.🤖 Who builds and trains AI systems? (a) nobody at all (b) people (c) the weather (d) the Moon
39. 39.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.True or false: “ignore complaints” adds to bias. (a) False (b) True

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