AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 242 · 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 does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
2. 2.Which of these is a myth about AI? (a) AI answers need checking (b) AI can make up facts (c) confident means correct (d) AI can be wrong
3. 3.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
4. 4.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
5. 5.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) a light switch (b) a digital watch (c) a printed timetable (d) face unlock on a phone
7. 7.Which of these is a prediction? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) recorded spoken words (d) past weather records
8. 8.Which of these describes how AI works? (a) one set rule per case (b) follows fixed rules (c) never learns from data (d) handles unseen examples
9. 9.True or false: “labels added at random” is bad for training a model. (a) True (b) False
10. 10.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts
11. 11.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) photos in many lights (d) copies of one photo
12. 12.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
13. 13.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) very few examples (d) blurry, unclear photos
14. 14.Which of these is a fact about AI? (a) AI always checks facts (b) AI knows everything (c) long answers are true (d) AI can be wrong
15. 15.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
16. 16.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
17. 17.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) an image (b) text (c) music or sound
18. 18.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
19. 19.💬 What do we call the request you type to a generative AI? (a) a password (b) a prompt (c) a label (d) a battery
20. 20.✨ Generative or not: turning speech to text? (a) makes something new (b) sorts or predicts
21. 21.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) balance the data
22. 22.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) only one kind of example (d) many varied examples
23. 23.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
24. 24.🔍 Which is the odd one out? (a) drafting a letter (b) writing a new poem (c) writing quiz questions (d) sorting photos by face
25. 25.Which of these is the model? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) recorded spoken words (d) the learned patterns
26. 26.🤖 What does AI stand for? (a) app installer (b) artificial intelligence (c) actual information (d) automatic internet
27. 27.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.🖼️ 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
29. 29.True or false: “handles unseen examples” describes how AI works. (a) False (b) True
30. 30.True or false: “AI can make up facts” is a fact about AI. (a) False (b) True
31. 31.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) fix wrong labels (d) ignore complaints
32. 32.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
33. 33.🏠 AI or not AI: a voice assistant? (a) not AI (b) uses AI
34. 34.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI answers need checking (c) AI can make up facts (d) AI always checks facts
35. 35.Which of these is a myth about AI? (a) AI learns from data (b) AI answers need checking (c) AI can be wrong (d) AI knows everything
36. 36.Which of these is a myth about AI? (a) AI can be wrong (b) AI has real feelings (c) AI answers need checking (d) AI learns from data
37. 37.Which of these uses AI? (a) an app translating signs (b) a calculator (c) a fan regulator (d) a stopwatch
38. 38.📱 What is the AI doing here: turning your spoken words into typed text? (a) predicting (b) recommending (c) recognising (d) generating
39. 39.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) people (d) the Moon
40. 40.True or false: “see if the book exists” is a real way to check an AI answer. (a) False (b) True

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