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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 82 · 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.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  2. 2.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  3. 3.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  4. 4.True or false: “balance the data” helps reduce bias. (a) True (b) False
  5. 5.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) skip testing
  6. 6.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
  8. 8.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  10. 10.Which of these adds to bias? (a) ignore complaints (b) test on many groups (c) fix wrong labels (d) add varied examples
  11. 11.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  12. 12.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) check who is missing (d) use one group only
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  14. 14.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  15. 15.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) use one group only (d) ask different people
  16. 16.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) test on many groups (d) fix wrong labels
  17. 17.True or false: “use one group only” adds to bias. (a) False (b) True
  18. 18.True or false: “ignore complaints” adds to bias. (a) False (b) True
  19. 19.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  20. 20.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  21. 21.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  23. 23.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  24. 24.Which of these adds to bias? (a) test on many groups (b) balance the data (c) add more of the same (d) ask different people
  25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  27. 27.True or false: “skip testing” helps reduce bias. (a) True (b) False
  28. 28.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) use one group only (d) fix wrong labels
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  30. 30.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  31. 31.Which of these adds to bias? (a) balance the data (b) ask different people (c) copy old unfair choices (d) fix wrong labels
  32. 32.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) add varied examples (d) add more of the same
  34. 34.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  35. 35.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
  36. 36.True or false: “use one group only” helps reduce bias. (a) True (b) False
  37. 37.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) ask different people (d) copy old unfair choices
  38. 38.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  39. 39.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  40. 40.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias

Answer key

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

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