AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 510 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
2. 2.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) yes, it gets sad (c) only on weekends (d) no, it finds patterns
3. 3.Which of these is a fact about AI? (a) AI answers need checking (b) AI is never wrong (c) confident means correct (d) long answers are true
4. 4.Which of these is a fact about AI? (a) AI always checks facts (b) AI can mix up numbers (c) AI knows everything (d) AI is never wrong
5. 5.📱 What is the AI doing here: turning your spoken words into typed text? (a) generating (b) predicting (c) recommending (d) recognising
6. 6.True or false: “a soft lullaby melody” asks for text. (a) True (b) False
7. 7.True or false: an AI chatbot writing a poem about rain is AI generating something new. (a) False (b) True
8. 8.True or false: “add varied examples” helps reduce bias. (a) False (b) True
9. 9.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
10. 10.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) copies of one photo (d) new data for testing
11. 11.True or false: “a poster of a rainforest” asks for text. (a) True (b) False
12. 12.True or false: “typing a new spoken word” is the model. (a) True (b) False
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
14. 14.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
15. 15.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
16. 16.✍️ How does an AI chatbot write its replies? (a) copies one website (b) uses magic (c) predicts likely words (d) asks a person
17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
18. 18.Which of these is generative AI (it makes something new)? (a) writing a new poem (b) spotting a sick leaf (c) reading number plates (d) suggesting a video
19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
20. 20.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
21. 21.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) clear, sharp examples (d) very few examples
22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) a prediction (d) training data
23. 23.🔍 Which is the odd one out? (a) a calculator (b) face unlock on a phone (c) video suggestions (d) voice typing
24. 24.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
25. 25.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) labels added at random (d) wrong labels
26. 26.🤖 AI or a normal program: which one “same steps every time”? (a) a normal program (b) AI
27. 27.True or false: “a soft lullaby melody” asks for music or sound. (a) True (b) False
28. 28.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
29. 29.Which of these is a fact about AI? (a) long answers are true (b) AI can make up facts (c) AI is never wrong (d) AI has real feelings
30. 30.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ignore complaints (d) ask different people
31. 31.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
32. 32.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
33. 33.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) drafting a letter (c) unlocking with a face (d) predicting rain
34. 34.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) clear, sharp examples (d) new data for testing
35. 35.💬 What do we call the request you type to a generative AI? (a) a prompt (b) a label (c) a password (d) a battery
36. 36.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
37. 37.🏠 AI or not AI: a torch? (a) not AI (b) uses AI
38. 38.True or false: “a poster of a rainforest” asks for an image. (a) True (b) False
39. 39.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
40. 40.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI

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