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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 617 · 40 questions
TalentJR

AI tip (Fair data, fairer AI): Bias usually comes from the training data: if a group is missing or shown in only one way, the model copies that. One-sided data: one age group, only ripe mangoes, only adult voices, only neat handwriting. Balanced data: many ages, colours, voices, regions and styles. Reduce bias: add varied examples, check who is missing, test on many groups, fix wrong labels and listen to complaints.

NameDateTime takenScore ___ / 40
  1. 1.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  2. 2.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
  4. 4.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) copy old unfair choices (d) check who is missing
  5. 5.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  6. 6.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  8. 8.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) ignore complaints
  9. 9.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  10. 10.True or false: “check who is missing” adds to bias. (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  12. 12.True or false: “ask different people” helps reduce bias. (a) True (b) False
  13. 13.True or false: “add varied examples” adds to bias. (a) True (b) False
  14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  15. 15.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  16. 16.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) fix wrong labels (d) use one group only
  17. 17.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  19. 19.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  20. 20.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  21. 21.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) use one group only
  22. 22.True or false: “use one group only” helps reduce bias. (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  24. 24.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) balance the data (d) test on one group only
  25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  26. 26.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) add more of the same (d) ask different people
  27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  28. 28.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  29. 29.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  30. 30.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  31. 31.Which of these adds to bias? (a) add varied examples (b) ask different people (c) skip testing (d) test on many groups
  32. 32.True or false: “skip testing” adds to bias. (a) True (b) False
  33. 33.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  35. 35.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  36. 36.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  37. 37.True or false: “use one group only” adds to bias. (a) True (b) False
  38. 38.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) test on one group only (d) ask different people
  39. 39.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  40. 40.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias

Answer key

  1. its training data
  2. bias from data
  3. few child voices in data
  4. copy old unfair choices
  5. reduces bias
  6. False
  7. one-sided data
  8. ignore complaints
  9. adds to bias
  10. False
  11. adds to bias
  12. True
  13. False
  14. False
  15. one-sided data
  16. fix wrong labels
  17. True
  18. balanced data
  19. False
  20. False
  21. add varied examples
  22. False
  23. one-sided data
  24. balance the data
  25. one-sided data
  26. add more of the same
  27. one-sided data
  28. False
  29. adds to bias
  30. True
  31. skip testing
  32. True
  33. True
  34. adds to bias
  35. reduces bias
  36. adds to bias
  37. True
  38. ask different people
  39. True
  40. reduces bias

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