AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 933 · 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.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
2. 2.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
3. 3.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) stop studying (b) share it online (c) trust the AI (d) trust the textbook
4. 4.True or false: telling a cat photo from a dog photo needs AI that learns from examples. (a) True (b) False
5. 5.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) new data for testing (d) clear, sharp examples
6. 6.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) naming a new leaf (d) old emails marked spam
7. 7.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
8. 8.🧮 Which of these is NOT AI? (a) face unlock (b) voice typing (c) a spam filter (d) a basic calculator
9. 9.🔍 Which is the odd one out? (a) drafting a letter (b) writing quiz questions (c) reading number plates (d) creating a cartoon
10. 10.True or false: turning spoken words into typed text needs AI that learns from examples. (a) True (b) False
11. 11.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) music or sound (b) an image (c) text
12. 12.True or false: suggesting the next word as you type needs AI that learns from examples. (a) True (b) False
13. 13.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) new data for testing (d) very few examples
14. 14.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on many groups (d) add more of the same
15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
16. 16.True or false: a car camera reading a speed sign is AI recognising something. (a) True (b) False
17. 17.Which of these describes how a normal program works? (a) learns from examples (b) handles unseen examples (c) makes a best guess (d) uses rules people wrote
18. 18.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
19. 19.Which of these is not AI? (a) an image generator (b) an AI chatbot (c) a voice assistant (d) a doorbell
20. 20.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
21. 21.True or false: “same steps every time” describes how a normal program works. (a) False (b) True
22. 22.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI
23. 23.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
24. 24.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) check it on paper (b) ask it to hurry (c) copy it straight away (d) never do maths
25. 25.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
26. 26.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it learns from examples (c) it uses electricity (d) it has a screen
27. 27.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False
28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
29. 29.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
30. 30.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) yes, if it is long (c) no, check it anyway
31. 31.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) very few examples (d) photos in many lights
32. 32.Which of these is a fact about AI? (a) long answers are true (b) confident means correct (c) AI answers need checking (d) AI is never wrong
33. 33.🧐 Fact or myth: “AI has real feelings”? (a) a myth (b) a fact
34. 34.Which of these is a prediction? (a) the trained program (b) the learned patterns (c) flagging a new email (d) what training builds
35. 35.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
36. 36.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
37. 37.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
38. 38.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
39. 39.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
40. 40.✨ Is everything a generative AI makes true? (a) yes, always (b) no, it can be wrong (c) only on Mondays

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