AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 284 · 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: a phone unlocking when it sees your face is AI recommending something. (a) False (b) True
2. 2.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) yes, if it is long (c) no, check it anyway
3. 3.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
4. 4.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
5. 5.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) only one kind of example (d) many varied examples
6. 6.Which of these is not AI? (a) a spam filter (b) an image generator (c) a calculator (d) photos grouped by face
7. 7.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
8. 8.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) composing a new tune (c) making up a story (d) reading number plates
9. 9.🏷️ 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
10. 10.Which of these is a fact about AI? (a) AI has real feelings (b) AI can mix up numbers (c) long answers are true (d) AI is never wrong
11. 11.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) music or sound (b) text (c) an image
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) only one kind of example (d) many varied examples
13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
14. 14.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
15. 15.✨ Generative or not: drafting a letter? (a) makes something new (b) sorts or predicts
16. 16.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
17. 17.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
18. 18.True or false: “examples of every type” is bad for training a model. (a) False (b) True
19. 19.True or false: “wrong labels” is bad for training a model. (a) False (b) True
20. 20.True or false: adding up the marks on a report card needs AI that learns from examples. (a) True (b) False
21. 21.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
22. 22.⏩ In machine learning, which comes first: naming a new leaf or 500 labelled leaf photos? (a) naming a new leaf (b) 500 labelled leaf photos
23. 23.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) yes, it is smart (c) only at night (d) no, it follows rules
24. 24.True or false: “it is long and detailed” is NOT a real way to check an AI answer. (a) False (b) True
25. 25.Which of these is the model? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) typing a new spoken word (d) the trained program
26. 26.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
27. 27.True or false: “AI can make up facts” is a myth about AI. (a) False (b) True
28. 28.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) wrong labels (d) many varied examples
29. 29.Which of these describes how AI works? (a) does exactly as coded (b) learns from examples (c) never learns from data (d) uses rules people wrote
30. 30.Which of these is generative AI (it makes something new)? (a) reading number plates (b) creating a cartoon (c) predicting rain (d) suggesting a video
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
32. 32.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
33. 33.🛠️ Which does this job need: converting metres into centimetres? (a) a simple rule is enough (b) needs AI (learning)
34. 34.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
35. 35.🏷️ 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
36. 36.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
37. 37.🔍 Which is the odd one out? (a) voice typing (b) a fan regulator (c) an AI chatbot (d) an image generator
38. 38.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
40. 40.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias

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