AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 448 · 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 book app suggesting a story like your last one is AI recommending something. (a) False (b) True
2. 2.Which of these is a fact about AI? (a) long answers are true (b) AI always checks facts (c) confident means correct (d) AI can make up facts
3. 3.Which of these describes how AI works? (a) follows fixed rules (b) one set rule per case (c) makes a best guess (d) does exactly as coded
4. 4.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
5. 5.🎨 This prompt asks a generative AI for: rain sound effects for a play. What kind of output is that? (a) an image (b) text (c) music or sound
6. 6.🔍 Which is the odd one out? (a) AI can be wrong (b) AI can mix up numbers (c) AI can make up facts (d) AI always checks facts
7. 7.Which of these describes how AI works? (a) uses rules people wrote (b) one set rule per case (c) learns from examples (d) does exactly as coded
8. 8.Which of these is generative AI (it makes something new)? (a) predicting rain (b) sorting photos by face (c) spotting spam (d) writing quiz questions
9. 9.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) making up a story (c) unlocking with a face (d) drafting a letter
10. 10.🔍 Which is the odd one out? (a) a light switch (b) a stopwatch (c) face unlock on a phone (d) a torch
11. 11.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) add varied examples (d) ignore complaints
12. 12.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
13. 13.True or false: “does exactly as coded” describes how AI works. (a) True (b) False
14. 14.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
15. 15.True or false: “a thank-you note to the bus driver” asks for an image. (a) False (b) True
16. 16.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) drawing (c) predicting (d) sleeping
17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
18. 18.Which of these describes how a normal program works? (a) follows fixed rules (b) spots patterns in data (c) handles unseen examples (d) gives a likely answer
19. 19.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
20. 20.True or false: “five quiz questions on fractions” asks for an image. (a) False (b) True
21. 21.True or false: “a poster of a rainforest” asks for text. (a) True (b) False
22. 22.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) test on one group only (d) test on many groups
23. 23.🔍 Which is the odd one out? (a) confident means correct (b) AI always checks facts (c) AI knows everything (d) AI learns from data
24. 24.📚 An AI chatbot names a book that does not exist. This is called… (a) a backup (b) a password (c) a summary (d) a hallucination
25. 25.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) writing a new poem (c) spotting spam (d) predicting rain
26. 26.True or false: “naming a new fruit photo” is training data. (a) False (b) True
27. 27.Which of these uses AI? (a) a fan regulator (b) a calculator (c) a microwave timer (d) photos grouped by face
28. 28.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) test on one group only (d) copy old unfair choices
29. 29.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
30. 30.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
32. 32.True or false: “check who is missing” helps reduce bias. (a) False (b) True
33. 33.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
34. 34.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
36. 36.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
37. 37.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
38. 38.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
39. 39.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
40. 40.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos

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