AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 579 · 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 uses AI? (a) an app translating signs (b) a kitchen weighing scale (c) a calculator (d) a printed timetable
2. 2.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
3. 3.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
4. 4.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) many varied examples (d) blurry, unclear photos
5. 5.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) text (c) an image
6. 6.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) labels added at random (d) very few examples
7. 7.Which of these is generative AI (it makes something new)? (a) reading number plates (b) predicting rain (c) drawing a new picture (d) turning speech to text
8. 8.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
10. 10.Which of these adds to bias? (a) copy old unfair choices (b) test on many groups (c) add varied examples (d) fix wrong labels
11. 11.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) clear, sharp examples (d) very few examples
12. 12.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
13. 13.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) music or sound (b) text (c) an image
14. 14.📅 An AI gives a date for a history event. How can you check? (a) look in your textbook (b) ask it to repeat (c) pick a lucky number (d) guess
15. 15.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
16. 16.🏠 AI or not AI: a light switch? (a) uses AI (b) not AI
17. 17.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) yes, it gets sad (c) no, it finds patterns (d) only on weekends
18. 18.🔍 Which is the odd one out? (a) AI has real feelings (b) AI answers need checking (c) AI can make up facts (d) AI can mix up numbers
19. 19.Which of these is a fact about AI? (a) AI is never wrong (b) AI knows everything (c) AI can make up facts (d) AI has real feelings
20. 20.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
21. 21.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
22. 22.Which of these describes how a normal program works? (a) spots patterns in data (b) learns from examples (c) handles unseen examples (d) does exactly as coded
23. 23.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) test on many groups (d) ask different people
24. 24.Which of these is the model? (a) tomorrow’s rain guess (b) labelled fruit photos (c) what training builds (d) flagging a new email
25. 25.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) False (b) True
26. 26.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) correct labels (d) testing on training data
27. 27.True or false: sorting names in A to Z order needs AI that learns from examples. (a) False (b) True
28. 28.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
29. 29.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
30. 30.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI
31. 31.Which of these adds to bias? (a) use one group only (b) fix wrong labels (c) check who is missing (d) balance the data
32. 32.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
33. 33.🏠 AI or not AI: a fan regulator? (a) uses AI (b) not AI
34. 34.True or false: “labels added at random” is good for training a model. (a) False (b) True
35. 35.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) use one group only (d) add varied examples
36. 36.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
37. 37.True or false: “skip testing” adds to bias. (a) False (b) True
38. 38.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
39. 39.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
40. 40.✨ Generative or not: inventing a recipe? (a) makes something new (b) sorts or predicts

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