AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 193 · 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 good for training a model? (a) new data for testing (b) testing on training data (c) wrong labels (d) labels added at random
2. 2.🛠️ Which does this job need: recognising a friend’s face in photos? (a) needs AI (learning) (b) a simple rule is enough
3. 3.True or false: “it has a neat layout” is a real way to check an AI answer. (a) True (b) False
4. 4.True or false: a phone unlocking when it sees your face is AI generating something new. (a) True (b) False
5. 5.💬 What do we call the request you type to a generative AI? (a) a password (b) a prompt (c) a battery (d) a label
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
7. 7.🔍 Which is the odd one out? (a) AI learns from data (b) AI has real feelings (c) AI can be wrong (d) AI answers need checking
8. 8.🧪 Why test a model on NEW examples? (a) to change its name (b) to make it slower (c) to delete its data (d) to see if it works
9. 9.Which of these describes how a normal program works? (a) learns from examples (b) spots patterns in data (c) improves with more data (d) one set rule per case
10. 10.Which of these is good for training a model? (a) labels added at random (b) clear, sharp examples (c) only one kind of example (d) testing on training data
11. 11.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) an image (b) music or sound (c) text
12. 12.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it learns from examples (c) it has a screen (d) it uses electricity
13. 13.Which of these is a myth about AI? (a) AI can be wrong (b) AI answers need checking (c) AI is never wrong (d) AI can mix up numbers
14. 14.⏩ In machine learning, which comes first: naming a new fruit photo or recorded spoken words? (a) naming a new fruit photo (b) recorded spoken words
15. 15.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
16. 16.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
17. 17.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) blurry, unclear photos (d) photos in many lights
18. 18.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
19. 19.True or false: sorting names in A to Z order only needs a simple fixed rule. (a) True (b) False
20. 20.True or false: “new data for testing” is bad for training a model. (a) True (b) False
21. 21.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
22. 22.✨ Generative or not: reading number plates? (a) sorts or predicts (b) makes something new
23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
24. 24.True or false: “improves with more data” describes how AI works. (a) True (b) False
25. 25.🤖 Does an AI system think and feel like a person? (a) yes, it gets sad (b) no, it finds patterns (c) yes, just like us (d) only on weekends
26. 26.🔍 Which is the odd one out? (a) an AI chatbot (b) a calculator (c) video suggestions (d) a spam filter
27. 27.Which of these adds to bias? (a) balance the data (b) ignore complaints (c) fix wrong labels (d) add varied examples
28. 28.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
29. 29.True or false: “past weather records” is the model. (a) False (b) True
30. 30.True or false: counting the words in an essay needs AI that learns from examples. (a) False (b) True
31. 31.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) a list of rules only (d) many labelled photos
32. 32.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
33. 33.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) share it online (c) trust the textbook (d) stop studying
34. 34.🏠 AI or not AI: a microwave timer? (a) uses AI (b) not AI
35. 35.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) music or sound (b) text (c) an image
36. 36.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
37. 37.True or false: “it sounds very sure” is a real way to check an AI answer. (a) False (b) True
38. 38.🧐 Fact or myth: “AI knows everything”? (a) a myth (b) a fact
39. 39.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
40. 40.True or false: “recorded spoken words” is a prediction. (a) False (b) True

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