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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 979 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
  2. 2.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts
  3. 3.📱 What is the AI doing here: a keyboard guessing your next word? (a) recognising (b) generating (c) recommending (d) predicting
  4. 4.Which of these is AI that sorts, spots or predicts (not generative)? (a) suggesting a video (b) making up a story (c) writing quiz questions (d) inventing a recipe
  5. 5.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  6. 6.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  7. 7.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  8. 8.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
  9. 9.True or false: “naming a new leaf” is the model. (a) False (b) True
  10. 10.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  11. 11.True or false: converting metres into centimetres only needs a simple fixed rule. (a) False (b) True
  12. 12.True or false: “write a poem about the monsoon” asks for an image. (a) False (b) True
  13. 13.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
  14. 14.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
  15. 15.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  16. 16.True or false: “flagging a new email” is the model. (a) False (b) True
  17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  18. 18.Which of these is a fact about AI? (a) AI learns from data (b) AI knows everything (c) confident means correct (d) long answers are true
  19. 19.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
  20. 20.🔍 Which is the odd one out? (a) AI can mix up numbers (b) AI knows everything (c) AI answers need checking (d) AI can make up facts
  21. 21.Which of these is a myth about AI? (a) AI can be wrong (b) AI can make up facts (c) AI has real feelings (d) AI learns from data
  22. 22.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  23. 23.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  24. 24.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
  25. 25.🏠 AI or not AI: a microwave timer? (a) uses AI (b) not AI
  26. 26.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  27. 27.🔍 Which is the odd one out? (a) predicting rain (b) inventing a recipe (c) making up a story (d) drafting a letter
  28. 28.🧮 Which of these is NOT AI? (a) a spam filter (b) face unlock (c) voice typing (d) a basic calculator
  29. 29.Which of these is generative AI (it makes something new)? (a) making up a story (b) predicting rain (c) spotting spam (d) sorting photos by face
  30. 30.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can be wrong (c) AI can mix up numbers (d) AI has real feelings
  31. 31.✨ What does generative AI do? (a) only stores files (b) only adds numbers (c) charges batteries (d) makes new content
  32. 32.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  33. 33.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
  34. 34.Which of these is a fact about AI? (a) AI knows everything (b) long answers are true (c) AI is never wrong (d) AI answers need checking
  35. 35.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
  36. 36.Which of these is the model? (a) tomorrow’s rain guess (b) flagging a new email (c) naming a new leaf (d) the trained program
  37. 37.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
  38. 38.True or false: “add more of the same” adds to bias. (a) False (b) True
  39. 39.✨ Generative or not: predicting rain? (a) sorts or predicts (b) makes something new
  40. 40.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True

Answer key

  1. not spam
  2. sorts or predicts
  3. predicting
  4. suggesting a video
  5. True
  6. training data
  7. training data
  8. False
  9. False
  10. a fact
  11. True
  12. False
  13. AI
  14. a normal program
  15. True
  16. False
  17. old emails marked spam
  18. AI learns from data
  19. makes something new
  20. AI knows everything
  21. AI has real feelings
  22. training data
  23. AI
  24. it may get it wrong
  25. not AI
  26. adds to bias
  27. predicting rain
  28. a basic calculator
  29. making up a story
  30. AI has real feelings
  31. makes new content
  32. good for training
  33. True
  34. AI answers need checking
  35. uses AI
  36. the trained program
  37. a myth
  38. True
  39. sorts or predicts
  40. False

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