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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 658 · 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.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  2. 2.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
  3. 3.🔦 Is a torch with an on/off switch AI? (a) no (b) only if it is bright (c) yes
  4. 4.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
  6. 6.True or false: “add varied examples” adds to bias. (a) False (b) True
  7. 7.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
  8. 8.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) printing (c) recommending (d) charging
  9. 9.🎨 An image generator makes a picture from… (a) a phone number (b) your password (c) the weather (d) a text description
  10. 10.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
  12. 12.🔍 Which is the odd one out? (a) AI has real feelings (b) AI can make up facts (c) AI can be wrong (d) AI learns from data
  13. 13.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  14. 14.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  15. 15.True or false: “use one group only” adds to bias. (a) True (b) False
  16. 16.🤖 Who builds and trains AI systems? (a) people (b) nobody at all (c) the weather (d) the Moon
  17. 17.🔍 Which is the odd one out? (a) unlocking with a face (b) drawing a new picture (c) inventing a recipe (d) making up a story
  18. 18.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
  19. 19.True or false: “improves with more data” describes how AI works. (a) True (b) False
  20. 20.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) examples of every type (d) blurry, unclear photos
  21. 21.🛠️ Which does this job need: showing the time on a clock? (a) a simple rule is enough (b) needs AI (learning)
  22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) use one group only (d) test on many groups
  23. 23.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) ignore complaints
  24. 24.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) text (b) music or sound (c) an image
  25. 25.🔍 Which is the odd one out? (a) AI learns from data (b) AI can make up facts (c) AI can be wrong (d) AI knows everything
  26. 26.🔍 Which is the odd one out? (a) composing a new tune (b) drawing a new picture (c) predicting rain (d) writing quiz questions
  27. 27.True or false: “AI always checks facts” is a myth about AI. (a) False (b) True
  28. 28.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  29. 29.True or false: “checking labels twice” is good for training a model. (a) False (b) True
  30. 30.📱 What is the AI doing here: an online shop showing “you may also like”? (a) recognising (b) recommending (c) generating (d) predicting
  31. 31.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) examples of every type (d) wrong labels
  32. 32.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  33. 33.🔍 Which is the odd one out? (a) writing quiz questions (b) writing a new poem (c) creating a cartoon (d) turning speech to text
  34. 34.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
  35. 35.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  36. 36.Which of these is the model? (a) recorded spoken words (b) tomorrow’s rain guess (c) labelled fruit photos (d) what training builds
  37. 37.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) add more of the same (d) fix wrong labels
  38. 38.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  39. 39.Which of these describes how AI works? (a) does exactly as coded (b) uses rules people wrote (c) same steps every time (d) learns from examples
  40. 40.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias

Answer key

  1. AI
  2. uses AI
  3. no
  4. False
  5. not spam
  6. False
  7. needs AI (learning)
  8. recommending
  9. a text description
  10. adds to bias
  11. it may get it wrong
  12. AI has real feelings
  13. balanced data
  14. AI
  15. True
  16. people
  17. unlocking with a face
  18. bad for training
  19. True
  20. examples of every type
  21. a simple rule is enough
  22. use one group only
  23. check who is missing
  24. text
  25. AI knows everything
  26. predicting rain
  27. True
  28. a myth
  29. True
  30. recommending
  31. wrong labels
  32. a prediction
  33. turning speech to text
  34. makes something new
  35. training data
  36. what training builds
  37. fix wrong labels
  38. good for training
  39. learns from examples
  40. reduces bias

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