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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 959 · 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 does this job need: telling a cat photo from a dog photo? (a) a simple rule is enough (b) needs AI (learning)
  2. 2.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) clear, sharp examples (d) very few examples
  3. 3.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) new data for testing (d) copies of one photo
  4. 4.🔍 Which is the odd one out? (a) AI can make up facts (b) AI can be wrong (c) AI learns from data (d) confident means correct
  5. 5.Which of these is bad for training a model? (a) many varied examples (b) only one kind of example (c) photos in many lights (d) correct labels
  6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  7. 7.🧮 Is a basic calculator an AI system? (a) only at night (b) no, it follows rules (c) yes, it is smart (d) yes, it can think
  8. 8.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) predicting (b) recommending (c) generating (d) recognising
  9. 9.Which of these is training data? (a) old emails marked spam (b) the trained program (c) naming a new leaf (d) flagging a new email
  10. 10.🏷️ 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
  11. 11.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the textbook (b) stop studying (c) trust the AI (d) share it online
  12. 12.Which of these is generative AI (it makes something new)? (a) spotting spam (b) reading number plates (c) writing a new poem (d) predicting rain
  13. 13.Which of these is training data? (a) typing a new spoken word (b) naming a new leaf (c) naming a new fruit photo (d) labelled fruit photos
  14. 14.📱 What is the AI doing here: turning your spoken words into typed text? (a) recognising (b) generating (c) recommending (d) predicting
  15. 15.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
  16. 16.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
  17. 17.Which of these is not AI? (a) a spam filter (b) a fan regulator (c) face unlock on a phone (d) a voice assistant
  18. 18.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  19. 19.Which of these is training data? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) naming a new leaf (d) the trained program
  20. 20.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) the Moon (d) people
  21. 21.Which of these uses AI? (a) video suggestions (b) a torch (c) a calculator (d) a digital watch
  22. 22.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) copies of one photo (d) examples of every type
  23. 23.🏠 AI or not AI: a light switch? (a) uses AI (b) not AI
  24. 24.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  25. 25.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) spotting spam (c) writing a new poem (d) composing a new tune
  26. 26.Which of these uses AI? (a) a torch (b) a doorbell (c) a calculator (d) an image generator
  27. 27.Which of these describes how AI works? (a) follows fixed rules (b) does exactly as coded (c) one set rule per case (d) improves with more data
  28. 28.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) training data (d) a label error
  29. 29.True or false: recognising a bird from its song needs AI that learns from examples. (a) False (b) True
  30. 30.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
  31. 31.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  32. 32.Which of these is a prediction? (a) recorded spoken words (b) flagging a new email (c) labelled fruit photos (d) the trained program
  33. 33.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
  34. 34.Which of these is a myth about AI? (a) AI learns from data (b) AI copies data patterns (c) AI has real feelings (d) AI answers need checking
  35. 35.Which of these is a fact about AI? (a) AI is never wrong (b) long answers are true (c) AI has real feelings (d) AI can make up facts
  36. 36.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) very few examples (d) many varied examples
  37. 37.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) examples of every type (d) new data for testing
  38. 38.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) predicting rain (b) suggesting a video (c) drawing a new picture (d) unlocking with a face
  40. 40.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI

Answer key

  1. needs AI (learning)
  2. clear, sharp examples
  3. copies of one photo
  4. confident means correct
  5. only one kind of example
  6. balanced data
  7. no, it follows rules
  8. recommending
  9. old emails marked spam
  10. spam
  11. trust the textbook
  12. writing a new poem
  13. labelled fruit photos
  14. recognising
  15. True
  16. False
  17. a fan regulator
  18. False
  19. 500 labelled leaf photos
  20. people
  21. video suggestions
  22. copies of one photo
  23. not AI
  24. needs AI (learning)
  25. spotting spam
  26. an image generator
  27. improves with more data
  28. a prediction
  29. True
  30. uses AI
  31. makes something new
  32. flagging a new email
  33. more varied data
  34. AI has real feelings
  35. AI can make up facts
  36. very few examples
  37. wrong labels
  38. True
  39. drawing a new picture
  40. a normal program

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