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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 502 · 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.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  2. 2.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  3. 3.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) add more of the same (d) check who is missing
  4. 4.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  6. 6.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  7. 7.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
  8. 8.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  9. 9.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  10. 10.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  11. 11.Which of these adds to bias? (a) ask different people (b) test on one group only (c) test on many groups (d) check who is missing
  12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  13. 13.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  14. 14.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.True or false: “skip testing” helps reduce bias. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  17. 17.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  18. 18.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) test on many groups (d) fix wrong labels
  19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  20. 20.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  21. 21.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) test on many groups (d) ignore complaints
  22. 22.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  23. 23.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  24. 24.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) add varied examples (d) test on many groups
  26. 26.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  27. 27.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
  28. 28.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) ask different people (d) copy old unfair choices
  29. 29.True or false: “balance the data” adds to bias. (a) False (b) True
  30. 30.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  31. 31.True or false: “test on one group only” adds to bias. (a) False (b) True
  32. 32.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) use one group only (d) ignore complaints
  33. 33.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  35. 35.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) skip testing (d) ignore complaints
  36. 36.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  37. 37.Which of these helps reduce bias? (a) add more of the same (b) balance the data (c) test on one group only (d) use one group only
  38. 38.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  39. 39.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  40. 40.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data

Answer key

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

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