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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 751 · 40 questions
TalentJR

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.

NameDateTime takenScore ___ / 40
  1. 1.Which of these is not AI? (a) a calculator (b) a spam filter (c) photos grouped by face (d) an AI chatbot
  2. 2.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check
  3. 3.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
  4. 4.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) labels added at random (d) clear, sharp examples
  5. 5.Which of these uses AI? (a) a torch (b) a digital watch (c) a kitchen weighing scale (d) voice typing
  6. 6.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  7. 7.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
  8. 8.True or false: “balance the data” adds to bias. (a) True (b) False
  9. 9.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
  10. 10.🔍 Which is the odd one out? (a) an app translating signs (b) a kitchen weighing scale (c) an image generator (d) an AI chatbot
  11. 11.True or false: “it uses big words” is NOT a real way to check an AI answer. (a) False (b) True
  12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  13. 13.True or false: an AI chatbot writing a story about a lost kite is AI predicting something. (a) False (b) True
  14. 14.🏠 AI or not AI: a fan regulator? (a) uses AI (b) not AI
  15. 15.True or false: “many varied examples” is bad for training a model. (a) True (b) False
  16. 16.True or false: “AI knows everything” is a myth about AI. (a) True (b) False
  17. 17.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) ignore complaints (d) use one group only
  18. 18.True or false: “photos in many lights” is good for training a model. (a) False (b) True
  19. 19.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  20. 20.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) correct labels (d) testing on training data
  21. 21.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  23. 23.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) add varied examples (d) balance the data
  24. 24.True or false: a map app guessing how long a trip will take is AI predicting something. (a) False (b) True
  25. 25.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  26. 26.🔍 Which is the odd one out? (a) a digital watch (b) a calculator (c) a voice assistant (d) a torch
  27. 27.🤖 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
  28. 28.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI can be wrong (c) AI can make up facts (d) long answers are true
  29. 29.True or false: “correct labels” is good for training a model. (a) True (b) False
  30. 30.🏠 AI or not AI: a calculator? (a) not AI (b) uses AI
  31. 31.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) correct labels (d) very few examples
  32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  33. 33.🔍 Which is the odd one out? (a) spotting a sick leaf (b) unlocking with a face (c) inventing a recipe (d) suggesting a video
  34. 34.True or false: “labels added at random” is good for training a model. (a) True (b) False
  35. 35.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  36. 36.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) text (b) an image (c) music or sound
  37. 37.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
  38. 38.True or false: “uses rules people wrote” describes how a normal program works. (a) False (b) True
  39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
  40. 40.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recommending (b) predicting (c) recognising (d) generating

Answer key

  1. a calculator
  2. not a real check
  3. 500 labelled leaf photos
  4. labels added at random
  5. voice typing
  6. reduces bias
  7. True
  8. False
  9. True
  10. a kitchen weighing scale
  11. True
  12. training data
  13. False
  14. not AI
  15. False
  16. True
  17. test on many groups
  18. True
  19. adds to bias
  20. testing on training data
  21. True
  22. adds to bias
  23. ignore complaints
  24. True
  25. False
  26. a voice assistant
  27. no, it finds patterns
  28. long answers are true
  29. True
  30. not AI
  31. very few examples
  32. balanced data
  33. inventing a recipe
  34. False
  35. the model
  36. music or sound
  37. good for training
  38. True
  39. True
  40. recognising

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