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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 460 · 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: ignore complaints? (a) adds to bias (b) reduces bias
  2. 2.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  3. 3.Which of these adds to bias? (a) add varied examples (b) balance the data (c) fix wrong labels (d) test on one group only
  4. 4.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  5. 5.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) copy old unfair choices (d) balance the data
  6. 6.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) test on many groups (d) copy old unfair choices
  8. 8.True or false: “balance the data” helps reduce bias. (a) False (b) True
  9. 9.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  11. 11.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  12. 12.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  13. 13.🔍 Which is the odd one out? (a) add varied examples (b) use one group only (c) test on many groups (d) ask different people
  14. 14.Which of these adds to bias? (a) add varied examples (b) use one group only (c) balance the data (d) test on many groups
  15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  16. 16.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) ignore complaints
  17. 17.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) add more of the same (d) skip testing
  18. 18.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  19. 19.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
  20. 20.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  21. 21.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  22. 22.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  23. 23.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  24. 24.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  25. 25.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  26. 26.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) add more of the same (d) check who is missing
  27. 27.Which of these adds to bias? (a) skip testing (b) test on many groups (c) fix wrong labels (d) balance the data
  28. 28.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
  29. 29.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  30. 30.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  31. 31.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  32. 32.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) ignore complaints (d) use one group only
  34. 34.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) add more of the same (d) copy old unfair choices
  36. 36.True or false: “add more of the same” adds to bias. (a) False (b) True
  37. 37.True or false: “use one group only” adds to bias. (a) False (b) True
  38. 38.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) check who is missing (d) add varied examples
  40. 40.Which of these helps reduce bias? (a) add varied examples (b) skip testing (c) ignore complaints (d) use one group only

Answer key

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

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