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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 922 · 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 helps reduce bias? (a) use one group only (b) add more of the same (c) test on many groups (d) copy old unfair choices
  2. 2.True or false: “add more of the same” adds to bias. (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  4. 4.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  5. 5.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  6. 6.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) use one group only (d) copy old unfair choices
  7. 7.True or false: “test on many groups” adds to bias. (a) False (b) True
  8. 8.True or false: “check who is missing” adds to bias. (a) False (b) True
  9. 9.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  11. 11.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  13. 13.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) use one group only
  15. 15.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  16. 16.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  17. 17.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) ignore complaints (d) add varied examples
  18. 18.Which of these helps reduce bias? (a) ask different people (b) copy old unfair choices (c) test on one group only (d) use one group only
  19. 19.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  20. 20.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  23. 23.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) ask different people (d) add more of the same
  24. 24.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
  26. 26.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  28. 28.True or false: “ignore complaints” adds to bias. (a) True (b) False
  29. 29.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  30. 30.Which of these adds to bias? (a) check who is missing (b) test on one group only (c) ask different people (d) test on many groups
  31. 31.True or false: “skip testing” helps reduce bias. (a) True (b) False
  32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  33. 33.True or false: “ask different people” helps reduce bias. (a) True (b) False
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  36. 36.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) check who is missing (d) test on one group only
  37. 37.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  38. 38.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) use one group only (d) test on one group only
  39. 39.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) test on many groups (d) skip testing
  40. 40.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias

Answer key

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

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