AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 386 · 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.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
2. 2.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
3. 3.✨ What does generative AI do? (a) charges batteries (b) only adds numbers (c) only stores files (d) makes new content
4. 4.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
6. 6.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
7. 7.Which of these is a fact about AI? (a) AI has real feelings (b) AI copies data patterns (c) confident means correct (d) AI is never wrong
8. 8.True or false: “a soft lullaby melody” asks for an image. (a) False (b) True
9. 9.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
10. 10.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
11. 11.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) blurry, unclear photos (d) examples of every type
12. 12.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
13. 13.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
14. 14.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
15. 15.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) photos in many lights (d) testing on training data
16. 16.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
17. 17.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
18. 18.🛠️ Which does this job need: suggesting the next word as you type? (a) needs AI (learning) (b) a simple rule is enough
19. 19.True or false: a shop guessing how many umbrellas will sell is AI predicting something. (a) True (b) False
20. 20.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
21. 21.Which of these is not AI? (a) a map predicting traffic (b) an app translating signs (c) a torch (d) face unlock on a phone
22. 22.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) music or sound (b) text (c) an image
23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
24. 24.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add more of the same (d) fix wrong labels
25. 25.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) recognising (b) generating (c) predicting (d) recommending
26. 26.Which of these uses AI? (a) photos grouped by face (b) a microwave timer (c) a light switch (d) a calculator
27. 27.🛠️ Which does this job need: reading messy handwriting? (a) a simple rule is enough (b) needs AI (learning)
28. 28.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
29. 29.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) add more of the same (d) add varied examples
30. 30.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
32. 32.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) a light switch (b) a map predicting traffic (c) face unlock on a phone (d) a spam filter
35. 35.🔍 Which is the odd one out? (a) unlocking with a face (b) suggesting a video (c) inventing a recipe (d) spotting a sick leaf
36. 36.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI answers need checking (c) AI has real feelings (d) AI can make up facts
37. 37.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) examples of every type (d) correct labels
38. 38.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
39. 39.True or false: “find a trusted source” is NOT a real way to check an AI answer. (a) False (b) True
40. 40.🏷️ 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

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