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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 878 · 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.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  3. 3.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) add more of the same (d) ignore complaints
  4. 4.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  5. 5.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  6. 6.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) test on one group only
  7. 7.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  10. 10.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  11. 11.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  12. 12.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) add varied examples (d) ignore complaints
  13. 13.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  14. 14.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  15. 15.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) test on one group only (d) ignore complaints
  16. 16.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  17. 17.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  18. 18.True or false: “check who is missing” adds to bias. (a) False (b) True
  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.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  21. 21.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
  22. 22.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  23. 23.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  24. 24.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  25. 25.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.True or false: “use one group only” adds to bias. (a) False (b) True
  27. 27.Which of these adds to bias? (a) add varied examples (b) ask different people (c) add more of the same (d) balance the data
  28. 28.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) copy old unfair choices (d) balance the data
  29. 29.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) fix wrong labels (d) test on one group only
  30. 30.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add varied examples (d) test on one group only
  34. 34.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  35. 35.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) use one group only (d) test on one group only
  37. 37.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  38. 38.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  39. 39.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  40. 40.True or false: “use one group only” helps reduce bias. (a) True (b) False

Answer key

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

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