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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 203 · 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: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  2. 2.True or false: “ask different people” helps reduce bias. (a) False (b) True
  3. 3.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) use one group only (d) add varied examples
  4. 4.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  5. 5.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  6. 6.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  7. 7.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  9. 9.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  10. 10.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  11. 11.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  12. 12.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  13. 13.Which of these helps reduce bias? (a) add varied examples (b) add more of the same (c) ignore complaints (d) use one group only
  14. 14.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  16. 16.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  17. 17.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) add more of the same (d) ignore complaints
  18. 18.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  19. 19.True or false: “ignore complaints” adds to bias. (a) True (b) False
  20. 20.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  21. 21.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
  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) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  24. 24.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  25. 25.Which of these adds to bias? (a) ask different people (b) add more of the same (c) test on many groups (d) check who is missing
  26. 26.True or false: “add more of the same” adds to bias. (a) True (b) False
  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: “fix wrong labels” helps reduce bias. (a) True (b) False
  29. 29.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  30. 30.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  31. 31.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  32. 32.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  33. 33.True or false: “check who is missing” adds to bias. (a) False (b) True
  34. 34.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  35. 35.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  36. 36.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  37. 37.True or false: “skip testing” helps reduce bias. (a) False (b) True
  38. 38.Which of these adds to bias? (a) add varied examples (b) ask different people (c) balance the data (d) copy old unfair choices
  39. 39.True or false: “test on many groups” adds to 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. False
  2. True
  3. add varied examples
  4. reduces bias
  5. True
  6. balanced data
  7. adds to bias
  8. one-sided data
  9. more varied data
  10. one-sided data
  11. reduces bias
  12. one-sided data
  13. add varied examples
  14. True
  15. False
  16. True
  17. check who is missing
  18. False
  19. True
  20. True
  21. its training data
  22. False
  23. few child voices in data
  24. False
  25. add more of the same
  26. True
  27. adds to bias
  28. True
  29. one-sided data
  30. one-sided data
  31. False
  32. adds to bias
  33. False
  34. reduces bias
  35. balanced data
  36. True
  37. False
  38. copy old unfair choices
  39. False
  40. adds to bias

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