AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 934 · 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) wrong labels (b) only one kind of example (c) checking labels twice (d) labels added at random
2. 2.True or false: “test on one group only” helps reduce bias. (a) True (b) False
3. 3.True or false: “ask your teacher” is NOT a real way to check an AI answer. (a) False (b) True
4. 4.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
5. 5.Which of these is the model? (a) what training builds (b) past weather records (c) typing a new spoken word (d) 500 labelled leaf photos
6. 6.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it uses electricity (c) it learns from examples (d) it is always right
7. 7.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
10. 10.📱 What is the AI doing here: a car camera reading a speed sign? (a) recommending (b) predicting (c) generating (d) recognising
11. 11.True or false: suggesting the next word as you type needs AI that learns from examples. (a) False (b) True
12. 12.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
13. 13.True or false: counting the words in an essay only needs a simple fixed rule. (a) False (b) True
14. 14.True or false: turning your spoken words into typed text is AI recognising something. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) AI knows everything (b) AI is never wrong (c) AI answers need checking (d) AI always checks facts
16. 16.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
17. 17.Which of these is good for training a model? (a) only one kind of example (b) examples of every type (c) copies of one photo (d) testing on training data
18. 18.🔍 Which is the odd one out? (a) wrong labels (b) new data for testing (c) clear, sharp examples (d) many varied examples
19. 19.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can be wrong (c) AI learns from data (d) AI always checks facts
20. 20.🤖 Who builds and trains AI systems? (a) people (b) the Moon (c) nobody at all (d) the weather
21. 21.Which of these is a myth about AI? (a) AI can be wrong (b) AI can mix up numbers (c) AI always checks facts (d) AI copies data patterns
22. 22.Which of these describes how AI works? (a) does exactly as coded (b) makes a best guess (c) one set rule per case (d) same steps every time
23. 23.True or false: “one set rule per case” describes how AI works. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) new data for testing (d) labels added at random
25. 25.✨ Generative or not: reading number plates? (a) sorts or predicts (b) makes something new
26. 26.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
27. 27.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
28. 28.🔦 Is a torch with an on/off switch AI? (a) yes (b) no (c) only if it is bright
29. 29.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
30. 30.Which of these describes how AI works? (a) follows fixed rules (b) same steps every time (c) never learns from data (d) gives a likely answer
31. 31.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
32. 32.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
33. 33.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
34. 34.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) copies of one photo (d) labels added at random
35. 35.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) False (b) True
36. 36.Which of these is training data? (a) what training builds (b) the trained program (c) typing a new spoken word (d) 500 labelled leaf photos
37. 37.True or false: an AI chatbot writing a story about a lost kite is AI generating something new. (a) True (b) False
38. 38.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) 500 labelled leaf photos (d) tomorrow’s rain guess
39. 39.Which of these describes how AI works? (a) does exactly as coded (b) never learns from data (c) learns from examples (d) one set rule per case
40. 40.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program

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