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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 476 · 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.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) fix wrong labels (d) use one group only
  3. 3.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
  4. 4.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  6. 6.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) add varied examples
  7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  8. 8.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) test on many groups (d) skip testing
  10. 10.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  11. 11.True or false: “use one group only” adds to bias. (a) True (b) False
  12. 12.True or false: “use one group only” helps reduce bias. (a) True (b) False
  13. 13.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  14. 14.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  15. 15.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  17. 17.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
  18. 18.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  19. 19.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) check who is missing (d) balance the data
  20. 20.True or false: “balance the data” helps reduce bias. (a) True (b) False
  21. 21.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.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
  23. 23.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  25. 25.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  26. 26.Which of these adds to bias? (a) balance the data (b) ask different people (c) test on many groups (d) add more of the same
  27. 27.Which of these adds to bias? (a) balance the data (b) check who is missing (c) add varied examples (d) ignore complaints
  28. 28.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  29. 29.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  30. 30.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
  31. 31.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  32. 32.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) test on many groups (d) ignore complaints
  33. 33.True or false: “test on many groups” adds to bias. (a) False (b) True
  34. 34.True or false: “ask different people” helps reduce bias. (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) skip testing (d) ignore complaints
  36. 36.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  37. 37.True or false: “check who is missing” adds to bias. (a) True (b) False
  38. 38.🗣️ 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) the phone was new (d) few child voices in data
  39. 39.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) skip testing (d) copy old unfair choices
  40. 40.True or false: “fix wrong labels” adds to bias. (a) False (b) True

Answer key

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

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