AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 865 · 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: balance the data? (a) reduces bias (b) adds to bias
2. 2.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
3. 3.🔍 Which is the odd one out? (a) wrong labels (b) new data for testing (c) copies of one photo (d) very few examples
4. 4.🔍 Which is the odd one out? (a) a torch (b) a calculator (c) a doorbell (d) face unlock on a phone
5. 5.Which of these describes how AI works? (a) gives a likely answer (b) follows fixed rules (c) uses rules people wrote (d) never learns from data
6. 6.Which of these is AI that sorts, spots or predicts (not generative)? (a) creating a cartoon (b) composing a new tune (c) drafting a letter (d) spotting spam
7. 7.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
9. 9.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
10. 10.Which of these describes how a normal program works? (a) one set rule per case (b) makes a best guess (c) spots patterns in data (d) learns from examples
11. 11.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
12. 12.True or false: “does exactly as coded” describes how a normal program works. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) test on one group only (d) check who is missing
14. 14.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) music or sound (b) text (c) an image
15. 15.Which of these is generative AI (it makes something new)? (a) turning speech to text (b) suggesting a video (c) spotting spam (d) drafting a letter
16. 16.🔍 Which is the odd one out? (a) unlocking with a face (b) inventing a recipe (c) spotting spam (d) turning speech to text
17. 17.True or false: “match it to the textbook” is NOT a real way to check an AI answer. (a) True (b) False
18. 18.🔍 Which is the odd one out? (a) clear, sharp examples (b) testing on training data (c) blurry, unclear photos (d) labels added at random
19. 19.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) very few examples (d) checking labels twice
20. 20.🏠 AI or not AI: an AI chatbot? (a) uses AI (b) not AI
21. 21.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) copies of one photo (d) new data for testing
22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) copy old unfair choices (d) balance the data
23. 23.True or false: “recorded spoken words” is a prediction. (a) True (b) False
24. 24.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) False (b) True
25. 25.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
26. 26.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) examples of every type (d) checking labels twice
27. 27.True or false: “past weather records” is a prediction. (a) False (b) True
28. 28.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
29. 29.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
30. 30.⏩ In machine learning, which comes first: flagging a new email or old emails marked spam? (a) flagging a new email (b) old emails marked spam
31. 31.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
32. 32.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) ask different people
34. 34.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
35. 35.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
36. 36.🔍 Which is the odd one out? (a) checking labels twice (b) blurry, unclear photos (c) many varied examples (d) clear, sharp examples
37. 37.True or false: “handles unseen examples” describes how a normal program works. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) a digital watch (b) a map predicting traffic (c) photos grouped by face (d) video suggestions
39. 39.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
40. 40.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) add varied examples (d) use one group only

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