AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 825 · 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.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
2. 2.True or false: “test on many groups” adds to bias. (a) False (b) True
3. 3.Which of these describes how AI works? (a) never learns from data (b) follows fixed rules (c) handles unseen examples (d) one set rule per case
4. 4.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
5. 5.True or false: “ignore complaints” adds to bias. (a) False (b) True
6. 6.True or false: “it uses big words” is a real way to check an AI answer. (a) False (b) True
7. 7.Which of these is the model? (a) the learned patterns (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) labelled fruit photos
8. 8.🛠️ Which does this job need: adding up the marks on a report card? (a) a simple rule is enough (b) needs AI (learning)
9. 9.True or false: an online shop showing “you may also like” is AI recommending something. (a) True (b) False
10. 10.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
11. 11.True or false: an online shop showing “you may also like” is AI predicting something. (a) False (b) True
12. 12.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
14. 14.🔍 Which is the odd one out? (a) spotting spam (b) making up a story (c) composing a new tune (d) drafting a letter
15. 15.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) copies of one photo (d) clear, sharp examples
16. 16.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
17. 17.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) drawing (c) predicting (d) singing
18. 18.True or false: “a cartoon of a dancing elephant” asks for an image. (a) False (b) True
19. 19.True or false: “fix wrong labels” adds to bias. (a) True (b) False
20. 20.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) test on one group only (d) skip testing
21. 21.🤖 Who builds and trains AI systems? (a) people (b) the Moon (c) the weather (d) nobody at all
22. 22.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
23. 23.Which of these describes how AI works? (a) spots patterns in data (b) same steps every time (c) does exactly as coded (d) never learns from data
24. 24.True or false: sorting names in A to Z order only needs a simple fixed rule. (a) True (b) False
25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
26. 26.🔍 Which is the odd one out? (a) an AI chatbot (b) a light switch (c) a map predicting traffic (d) an image generator
27. 27.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
28. 28.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
29. 29.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
30. 30.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
31. 31.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) children speak too fast (d) the phone was new
32. 32.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
34. 34.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
35. 35.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) trust the textbook (c) share it online (d) stop studying
36. 36.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recognising (b) generating (c) predicting (d) recommending
37. 37.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
38. 38.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
39. 39.Which of these is a myth about AI? (a) AI copies data patterns (b) AI learns from data (c) confident means correct (d) AI can make up facts
40. 40.True or false: “makes a best guess” describes how AI works. (a) False (b) True

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