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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 938 · 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: “ask different people” adds to bias. (a) True (b) False
  2. 2.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
  5. 5.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) test on many groups (d) skip testing
  6. 6.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  7. 7.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  8. 8.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  9. 9.True or false: “add varied examples” adds to bias. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  11. 11.Which of these adds to bias? (a) add varied examples (b) balance the data (c) test on many groups (d) copy old unfair choices
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  13. 13.Which of these helps reduce bias? (a) use one group only (b) fix wrong labels (c) add more of the same (d) test on one group only
  14. 14.Which of these helps reduce bias? (a) ask different people (b) test on one group only (c) add more of the same (d) skip testing
  15. 15.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on one group only (d) test on many groups
  16. 16.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  17. 17.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  18. 18.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  19. 19.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) check who is missing (d) use one group only
  20. 20.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.🗣️ 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
  24. 24.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  25. 25.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  26. 26.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  27. 27.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  28. 28.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  29. 29.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) test on one group only (d) skip testing
  30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  31. 31.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  33. 33.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) add varied examples (d) skip testing
  34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  35. 35.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) add varied examples (d) ask different people
  37. 37.Which of these adds to bias? (a) use one group only (b) balance the data (c) fix wrong labels (d) test on many groups
  38. 38.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  39. 39.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) test on many groups (d) ignore complaints
  40. 40.True or false: “add more of the same” adds to bias. (a) True (b) False

Answer key

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

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