AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 524 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
2. 2.Which of these is training data? (a) naming a new fruit photo (b) recorded spoken words (c) flagging a new email (d) tomorrow’s rain guess
3. 3.True or false: finding 10% of a price only needs a simple fixed rule. (a) False (b) True
4. 4.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
5. 5.Which of these is AI that sorts, spots or predicts (not generative)? (a) reading number plates (b) drafting a letter (c) writing quiz questions (d) writing a new poem
6. 6.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
7. 7.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, if it is long (b) no, check it anyway (c) yes, always
8. 8.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) music or sound (b) text (c) an image
9. 9.📅 An AI gives a date for a history event. How can you check? (a) pick a lucky number (b) ask it to repeat (c) look in your textbook (d) guess
10. 10.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI
11. 11.⏩ In machine learning, which comes first: naming a new leaf or labelled fruit photos? (a) naming a new leaf (b) labelled fruit photos
12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
14. 14.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
16. 16.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) add more of the same
17. 17.True or false: suggesting the next word as you type needs AI that learns from examples. (a) False (b) True
18. 18.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
19. 19.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
20. 20.Which of these describes how AI works? (a) does exactly as coded (b) never learns from data (c) improves with more data (d) follows fixed rules
21. 21.True or false: “photos in many lights” is good for training a model. (a) False (b) True
22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
23. 23.✨ Generative or not: drafting a letter? (a) sorts or predicts (b) makes something new
24. 24.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) testing on training data (d) examples of every type
25. 25.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
26. 26.True or false: “confident means correct” is a myth about AI. (a) True (b) False
27. 27.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
28. 28.🔍 Which is the odd one out? (a) sorting photos by face (b) drawing a new picture (c) inventing a recipe (d) composing a new tune
29. 29.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) stop studying (b) trust the AI (c) trust the textbook (d) share it online
30. 30.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
31. 31.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
32. 32.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
33. 33.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
34. 34.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) only on weekends (c) no, it finds patterns (d) yes, it gets sad
35. 35.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add more of the same (d) balance the data
36. 36.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) no (c) yes
37. 37.Which of these is a myth about AI? (a) AI answers need checking (b) AI learns from data (c) AI copies data patterns (d) AI is never wrong
38. 38.🔍 Which is the odd one out? (a) an image generator (b) video suggestions (c) a digital watch (d) photos grouped by face
39. 39.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program
40. 40.True or false: “match it to the textbook” is a real way to check an AI answer. (a) False (b) True

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