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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 935 · 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: test on many groups? (a) reduces bias (b) adds to bias
  2. 2.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  3. 3.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) copy old unfair choices (d) fix wrong labels
  4. 4.Which of these helps reduce bias? (a) fix wrong labels (b) ignore complaints (c) copy old unfair choices (d) test on one group only
  5. 5.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  6. 6.True or false: “add varied examples” adds to bias. (a) True (b) False
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  8. 8.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  9. 9.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  10. 10.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  11. 11.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) use one group only (d) ignore complaints
  12. 12.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) test on one group only (d) copy old unfair choices
  13. 13.True or false: “ignore complaints” adds to bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) ask different people (d) balance the data
  15. 15.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  16. 16.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  18. 18.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  20. 20.Which of these adds to bias? (a) add varied examples (b) skip testing (c) check who is missing (d) ask different people
  21. 21.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) test on many groups (d) check who is missing
  22. 22.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  24. 24.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  25. 25.True or false: “ask different people” helps reduce bias. (a) False (b) True
  26. 26.Which of these adds to bias? (a) use one group only (b) ask different people (c) test on many groups (d) add varied examples
  27. 27.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  28. 28.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  30. 30.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  31. 31.Which of these adds to bias? (a) add varied examples (b) test on one group only (c) balance the data (d) test on many groups
  32. 32.Which of these helps reduce bias? (a) ignore complaints (b) balance the data (c) skip testing (d) use one group only
  33. 33.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  34. 34.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
  35. 35.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  36. 36.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) test on many groups (d) ignore complaints
  37. 37.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) add more of the same (d) ignore complaints
  38. 38.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) skip testing (d) test on many groups
  39. 39.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  40. 40.True or false: “test on many groups” adds to bias. (a) False (b) True

Answer key

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

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