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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 79 · 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.Which of these adds to bias? (a) test on one group only (b) fix wrong labels (c) add varied examples (d) balance the data
  2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  4. 4.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) use one group only (d) test on many groups
  5. 5.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  7. 7.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  8. 8.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
  9. 9.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) skip testing (d) test on many groups
  10. 10.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  11. 11.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  13. 13.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) skip testing (d) test on many groups
  15. 15.True or false: “ask different people” helps reduce bias. (a) False (b) True
  16. 16.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (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) True (b) False
  19. 19.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) ask different people (d) copy old unfair choices
  20. 20.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  21. 21.Which of these adds to bias? (a) use one group only (b) check who is missing (c) balance the data (d) fix wrong labels
  22. 22.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  23. 23.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) fix wrong labels (d) ask different people
  24. 24.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  26. 26.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) balance the data (d) add more of the same
  27. 27.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  28. 28.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.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
  30. 30.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  31. 31.True or false: “skip testing” helps reduce bias. (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  33. 33.True or false: “test on one group only” adds to bias. (a) False (b) True
  34. 34.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) ask different people (d) check who is missing
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  36. 36.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  38. 38.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  39. 39.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) check who is missing (d) skip testing
  40. 40.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) add more of the same (d) balance the data

Answer key

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

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