AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 309 · 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: “add varied examples” adds to bias. (a) True (b) False
2. 2.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) music or sound (b) an image (c) text
3. 3.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
4. 4.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) sleeping (c) drawing (d) predicting
5. 5.📚 An AI chatbot names a book that does not exist. This is called… (a) a hallucination (b) a summary (c) a password (d) a backup
6. 6.🏠 AI or not AI: face unlock on a phone? (a) uses AI (b) not AI
7. 7.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag
8. 8.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
9. 9.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) reading number plates (c) composing a new tune (d) creating a cartoon
10. 10.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
11. 11.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) ignore complaints (d) skip testing
12. 12.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
13. 13.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
15. 15.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI copies data patterns (c) AI is never wrong (d) AI can be wrong
16. 16.True or false: a music app suggesting a song you may like is AI predicting something. (a) False (b) True
17. 17.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
18. 18.✨ Generative or not: sorting photos by face? (a) makes something new (b) sorts or predicts
19. 19.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.🏠 AI or not AI: a map predicting traffic? (a) uses AI (b) not AI
21. 21.True or false: “what training builds” is the model. (a) False (b) True
22. 22.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
23. 23.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
24. 24.Which of these is good for training a model? (a) many varied examples (b) labels added at random (c) wrong labels (d) copies of one photo
25. 25.Which of these is bad for training a model? (a) new data for testing (b) wrong labels (c) clear, sharp examples (d) examples of every type
26. 26.Which of these is a myth about AI? (a) AI has real feelings (b) AI can mix up numbers (c) AI learns from data (d) AI can be wrong
27. 27.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) only one kind of example (d) blurry, unclear photos
28. 28.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
29. 29.✅ Is this a real check of an AI answer: it uses big words? (a) not a real check (b) a real check
30. 30.True or false: a weather app guessing tomorrow’s rain is AI recognising something. (a) False (b) True
31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
32. 32.🌍 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
33. 33.True or false: “try the sum on paper” is NOT a real way to check an AI answer. (a) False (b) True
34. 34.True or false: “one set rule per case” describes how AI works. (a) False (b) True
35. 35.Which of these adds to bias? (a) check who is missing (b) copy old unfair choices (c) fix wrong labels (d) ask different people
36. 36.True or false: “confident means correct” is a myth about AI. (a) True (b) False
37. 37.True or false: “redo the maths yourself” is NOT a real way to check an AI answer. (a) True (b) False
38. 38.🛠️ Which does this job need: showing the time on a clock? (a) needs AI (learning) (b) a simple rule is enough
39. 39.🐶 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
40. 40.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) new data for testing (d) labels added at random

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