AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 338 · 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 adds to bias? (a) test on many groups (b) balance the data (c) ignore complaints (d) add varied examples
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) clear, sharp examples (c) many varied examples (d) correct labels
3. 3.True or false: “AI copies data patterns” is a myth about AI. (a) True (b) False
4. 4.True or false: “see if the book exists” is a real way to check an AI answer. (a) True (b) False
5. 5.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
6. 6.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
7. 7.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) predicting (b) singing (c) sleeping (d) drawing
8. 8.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) an image (b) music or sound (c) text
9. 9.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) many varied examples (d) correct labels
10. 10.True or false: “AI is never wrong” is a fact about AI. (a) False (b) True
11. 11.📺 A video app suggests what to watch next. What is the AI doing? (a) printing (b) cooking (c) charging (d) recommending
12. 12.🏠 AI or not AI: a voice assistant? (a) uses AI (b) not AI
13. 13.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
14. 14.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it is always right (c) it has a screen (d) it learns from examples
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
16. 16.🔍 Which is the odd one out? (a) long answers are true (b) AI knows everything (c) AI can make up facts (d) confident means correct
17. 17.🏷️ 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
18. 18.Which of these is a fact about AI? (a) AI copies data patterns (b) AI is never wrong (c) AI has real feelings (d) AI knows everything
19. 19.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) text (b) an image (c) music or sound
20. 20.Which of these describes how AI works? (a) follows fixed rules (b) one set rule per case (c) handles unseen examples (d) never learns from data
21. 21.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) text (b) music or sound (c) an image
22. 22.✨ What does generative AI do? (a) only adds numbers (b) only stores files (c) makes new content (d) charges batteries
23. 23.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
24. 24.True or false: turning spoken words into typed text only needs a simple fixed rule. (a) False (b) True
25. 25.True or false: a music app suggesting a song you may like is AI generating something new. (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) very few examples (d) clear, sharp examples
27. 27.Which of these describes how a normal program works? (a) gives a likely answer (b) makes a best guess (c) improves with more data (d) follows fixed rules
28. 28.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) many varied examples (d) copies of one photo
29. 29.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
30. 30.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) yes, it gets sad (c) only on weekends (d) no, it finds patterns
31. 31.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
32. 32.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) use one group only (d) test on many groups
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
34. 34.Which of these describes how a normal program works? (a) same steps every time (b) learns from examples (c) improves with more data (d) handles unseen examples
35. 35.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
36. 36.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
37. 37.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
39. 39.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recommending (b) recognising (c) generating (d) predicting
40. 40.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather

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