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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 548 · 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: copy old unfair choices? (a) adds to bias (b) reduces bias
  2. 2.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  4. 4.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  6. 6.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  8. 8.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) add varied examples (d) ignore complaints
  9. 9.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  10. 10.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  11. 11.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  13. 13.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  14. 14.True or false: “use one group only” helps reduce bias. (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) fix wrong labels (d) check who is missing
  16. 16.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) skip testing (d) fix wrong labels
  17. 17.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) ignore complaints (d) ask different people
  18. 18.True or false: “add varied examples” adds to bias. (a) True (b) False
  19. 19.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  20. 20.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) test on one group only
  21. 21.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  23. 23.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  24. 24.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) ask different people (d) skip testing
  25. 25.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  26. 26.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  27. 27.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  28. 28.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  29. 29.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  30. 30.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  31. 31.True or false: “check who is missing” adds to bias. (a) True (b) False
  32. 32.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) test on many groups (d) test on one group only
  33. 33.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  34. 34.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) ignore complaints (d) copy old unfair choices
  35. 35.True or false: “balance the data” helps reduce bias. (a) False (b) True
  36. 36.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  37. 37.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
  38. 38.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) test on one group only (d) skip testing
  39. 39.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) copy old unfair choices (d) test on one group only
  40. 40.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) use one group only (d) test on many groups

Answer key

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

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