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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 186 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  2. 2.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  3. 3.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  4. 4.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  6. 6.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) skip testing (d) copy old unfair choices
  7. 7.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) add more of the same (d) test on many groups
  8. 8.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
  9. 9.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  10. 10.Which of these adds to bias? (a) fix wrong labels (b) skip testing (c) ask different people (d) balance the data
  11. 11.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) ask different people (d) skip testing
  13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  14. 14.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  15. 15.True or false: “skip testing” helps reduce bias. (a) True (b) False
  16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  17. 17.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) use one group only (d) balance the data
  18. 18.True or false: “use one group only” adds to bias. (a) False (b) True
  19. 19.True or false: “skip testing” adds to bias. (a) True (b) False
  20. 20.True or false: “ask different people” helps reduce bias. (a) True (b) False
  21. 21.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  22. 22.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  24. 24.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
  25. 25.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  26. 26.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) copy old unfair choices (d) balance the data
  27. 27.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  28. 28.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  29. 29.Which of these adds to bias? (a) test on many groups (b) copy old unfair choices (c) fix wrong labels (d) check who is missing
  30. 30.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  32. 32.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) add more of the same (d) ask different people
  33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) use one group only
  34. 34.True or false: “check who is missing” adds to bias. (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) balance the data (d) test on one group only
  36. 36.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  37. 37.True or false: “balance the data” helps reduce bias. (a) True (b) False
  38. 38.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) ask different people (d) add varied examples
  39. 39.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  40. 40.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data

Answer key

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

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