AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 822 · 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.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
2. 2.✍️ How does an AI chatbot write its replies? (a) uses magic (b) copies one website (c) predicts likely words (d) asks a person
3. 3.🏷️ 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) spam (b) not spam
4. 4.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
6. 6.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
7. 7.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
8. 8.Which of these is good for training a model? (a) many varied examples (b) copies of one photo (c) only one kind of example (d) wrong labels
9. 9.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
10. 10.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
11. 11.🔍 Which is the odd one out? (a) ask different people (b) use one group only (c) add varied examples (d) check who is missing
12. 12.True or false: “AI can make up facts” is a fact about AI. (a) True (b) False
13. 13.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
14. 14.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
16. 16.True or false: “check who is missing” helps reduce bias. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) testing on training data (d) correct labels
18. 18.Which of these uses AI? (a) a fan regulator (b) a stopwatch (c) an image generator (d) a calculator
19. 19.🔍 Which is the odd one out? (a) creating a cartoon (b) unlocking with a face (c) spotting spam (d) spotting a sick leaf
20. 20.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) False (b) True
21. 21.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) photos in many lights (d) blurry, unclear photos
22. 22.✅ Is this a real check of an AI answer: ask your teacher? (a) a real check (b) not a real check
23. 23.🛠️ Which does this job need: reading messy handwriting? (a) needs AI (learning) (b) a simple rule is enough
24. 24.🏷️ 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
25. 25.Which of these describes how a normal program works? (a) makes a best guess (b) gives a likely answer (c) uses rules people wrote (d) learns from examples
26. 26.True or false: “skip testing” adds to bias. (a) False (b) True
27. 27.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) no, it finds patterns (c) yes, it gets sad (d) only on weekends
28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
29. 29.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
30. 30.True or false: “one set rule per case” describes how a normal program works. (a) False (b) True
31. 31.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recommending (b) generating (c) predicting (d) recognising
32. 32.True or false: “photos in many lights” is good for training a model. (a) False (b) True
33. 33.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
34. 34.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
35. 35.True or false: a video app suggesting what to watch next is AI recommending something. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) confident means correct (b) AI always checks facts (c) AI knows everything (d) AI can make up facts
37. 37.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
38. 38.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) new data for testing (d) correct labels
39. 39.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) test on many groups (d) ask different people
40. 40.Which of these is a myth about AI? (a) AI can be wrong (b) AI has real feelings (c) AI copies data patterns (d) AI can mix up numbers

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