AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 445 · 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 is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) making up a story (c) reading number plates (d) writing a new poem
2. 2.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
3. 3.True or false: counting the words in an essay only needs a simple fixed rule. (a) False (b) True
4. 4.True or false: “a drawing of a cat on the Moon” asks for music or sound. (a) True (b) False
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
6. 6.Which of these is good for training a model? (a) only one kind of example (b) many varied examples (c) blurry, unclear photos (d) wrong labels
7. 7.🛠️ Which does this job need: finding 10% of a price? (a) a simple rule is enough (b) needs AI (learning)
8. 8.Which of these is training data? (a) recorded spoken words (b) what training builds (c) naming a new leaf (d) tomorrow’s rain guess
9. 9.🔍 Which is the odd one out? (a) drafting a letter (b) drawing a new picture (c) unlocking with a face (d) inventing a recipe
10. 10.🏠 AI or not AI: a fan regulator? (a) uses AI (b) not AI
11. 11.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
12. 12.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) testing on training data (d) wrong labels
13. 13.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
14. 14.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
15. 15.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
16. 16.True or false: an online shop showing “you may also like” is AI recommending something. (a) False (b) True
17. 17.Which of these describes how AI works? (a) learns from examples (b) follows fixed rules (c) one set rule per case (d) never learns from data
18. 18.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
19. 19.🔍 Which is the odd one out? (a) labels added at random (b) new data for testing (c) blurry, unclear photos (d) wrong labels
20. 20.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
21. 21.Which of these is a myth about AI? (a) AI is never wrong (b) AI answers need checking (c) AI can make up facts (d) AI can be wrong
22. 22.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) typing a new spoken word (d) old emails marked spam
23. 23.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) spotting a sick leaf (c) inventing a recipe (d) sorting photos by face
24. 24.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) only at night (c) yes, it is smart (d) no, it follows rules
25. 25.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) labels added at random (d) wrong labels
26. 26.🔍 Which is the odd one out? (a) writing quiz questions (b) making up a story (c) composing a new tune (d) suggesting a video
27. 27.Which of these is a fact about AI? (a) AI has real feelings (b) AI always checks facts (c) AI is never wrong (d) AI can make up facts
28. 28.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
29. 29.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
30. 30.True or false: a map app guessing how long a trip will take is AI recommending something. (a) True (b) False
31. 31.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
32. 32.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
33. 33.Which of these is not AI? (a) photos grouped by face (b) an image generator (c) a calculator (d) an app translating signs
34. 34.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
35. 35.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) no, check it anyway (c) yes, if it is long
36. 36.🔍 Which is the odd one out? (a) examples of every type (b) blurry, unclear photos (c) only one kind of example (d) labels added at random
37. 37.True or false: “the trained program” is training data. (a) True (b) False
38. 38.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI
39. 39.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
40. 40.Which of these is not AI? (a) a stopwatch (b) video suggestions (c) an app translating signs (d) voice typing

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