AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 754 · 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.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
2. 2.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
3. 3.✨ Is everything a generative AI makes true? (a) yes, always (b) no, it can be wrong (c) only on Mondays
4. 4.🤖 AI or a normal program: which one “gives a likely answer”? (a) a normal program (b) AI
5. 5.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) very few examples (d) testing on training data
6. 6.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
7. 7.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts
8. 8.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) copy old unfair choices (d) add varied examples
9. 9.🔁 What is the right order? (a) data, model, prediction (b) model, prediction, data (c) data, prediction, model (d) prediction, data, model
10. 10.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) needs AI (learning) (b) a simple rule is enough
11. 11.✍️ How does an AI chatbot write its replies? (a) uses magic (b) predicts likely words (c) asks a person (d) copies one website
12. 12.🔍 Which is the odd one out? (a) making up a story (b) composing a new tune (c) suggesting a video (d) writing a new poem
13. 13.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
14. 14.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) unlocking with a face (c) turning speech to text (d) drafting a letter
15. 15.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
16. 16.True or false: “gives a likely answer” describes how a normal program works. (a) False (b) True
17. 17.🧐 Fact or myth: “AI copies data patterns”? (a) a fact (b) a myth
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
19. 19.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
20. 20.True or false: “ask different people” adds to bias. (a) False (b) True
21. 21.True or false: “past weather records” is a prediction. (a) True (b) False
22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
23. 23.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
24. 24.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) drawing (c) singing (d) predicting
25. 25.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
28. 28.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
29. 29.Which of these is a prediction? (a) old emails marked spam (b) tomorrow’s rain guess (c) recorded spoken words (d) what training builds
30. 30.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
31. 31.🤖 Who builds and trains AI systems? (a) nobody at all (b) the Moon (c) people (d) the weather
32. 32.Which of these is a myth about AI? (a) AI can make up facts (b) AI answers need checking (c) AI copies data patterns (d) AI has real feelings
33. 33.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
34. 34.True or false: “handles unseen examples” describes how a normal program works. (a) True (b) False
35. 35.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
36. 36.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
37. 37.🏠 AI or not AI: video suggestions? (a) not AI (b) uses AI
38. 38.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) only on weekends (c) yes, it gets sad (d) no, it finds patterns
39. 39.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) True (b) False
40. 40.Which of these describes how AI works? (a) learns from examples (b) follows fixed rules (c) same steps every time (d) does exactly as coded

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