AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 506 · 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.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
2. 2.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) predicting (b) generating (c) recognising (d) recommending
3. 3.🎨 An image generator makes a picture from… (a) the weather (b) a phone number (c) your password (d) a text description
4. 4.Which of these is AI that sorts, spots or predicts (not generative)? (a) unlocking with a face (b) writing a new poem (c) composing a new tune (d) making up a story
5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
6. 6.True or false: “a story about a brave ant” asks for text. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) check who is missing (d) fix wrong labels
8. 8.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
9. 9.✨ Generative or not: suggesting a video? (a) sorts or predicts (b) makes something new
10. 10.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
11. 11.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
12. 12.Which of these is a fact about AI? (a) confident means correct (b) AI knows everything (c) AI learns from data (d) AI always checks facts
13. 13.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
14. 14.True or false: finding 10% of a price needs AI that learns from examples. (a) False (b) True
15. 15.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
16. 16.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) testing on training data (d) clear, sharp examples
17. 17.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) check it on paper (b) never do maths (c) ask it to hurry (d) copy it straight away
18. 18.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
19. 19.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
20. 20.True or false: “AI can make up facts” is a myth about AI. (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) a kitchen weighing scale (b) a doorbell (c) a calculator (d) an AI chatbot
22. 22.True or false: switching on a street light at 6 pm needs AI that learns from examples. (a) False (b) True
23. 23.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
24. 24.True or false: “try the sum on paper” is a real way to check an AI answer. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) a spam filter (b) a digital watch (c) video suggestions (d) an app translating signs
26. 26.Which of these describes how AI works? (a) makes a best guess (b) does exactly as coded (c) follows fixed rules (d) one set rule per case
27. 27.True or false: “a cheerful tune for Sports Day” asks for text. (a) True (b) False
28. 28.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
29. 29.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it has a screen (c) it uses electricity (d) it learns from examples
30. 30.Which of these is a myth about AI? (a) AI copies data patterns (b) AI can mix up numbers (c) AI can make up facts (d) confident means correct
31. 31.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
32. 32.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) fix wrong labels (d) check who is missing
33. 33.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
34. 34.🧐 Fact or myth: “long answers are true”? (a) a fact (b) a myth
35. 35.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
36. 36.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) only on weekends (c) yes, it gets sad (d) no, it finds patterns
37. 37.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
38. 38.Which of these describes how a normal program works? (a) never learns from data (b) gives a likely answer (c) learns from examples (d) spots patterns in data
39. 39.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
40. 40.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True

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