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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 699 · 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: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  2. 2.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  3. 3.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add varied examples (d) copy old unfair choices
  4. 4.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) use one group only (d) ask different people
  5. 5.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) copy old unfair choices (d) use one group only
  6. 6.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  8. 8.True or false: “use one group only” adds to bias. (a) True (b) False
  9. 9.🗣️ 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) it was a rainy day (d) the phone was new
  10. 10.True or false: “use one group only” helps reduce bias. (a) False (b) True
  11. 11.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) fix wrong labels (d) skip testing
  12. 12.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  13. 13.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  14. 14.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) add more of the same (d) test on many groups
  15. 15.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) copy old unfair choices (d) add varied examples
  16. 16.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  17. 17.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  20. 20.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) use one group only (d) balance the data
  21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  22. 22.True or false: “add more of the same” adds to bias. (a) False (b) True
  23. 23.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) check who is missing (d) add more of the same
  24. 24.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  25. 25.True or false: “skip testing” adds to bias. (a) False (b) True
  26. 26.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  27. 27.True or false: “ignore complaints” adds to bias. (a) True (b) False
  28. 28.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) copy old unfair choices (d) skip testing
  30. 30.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  31. 31.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  32. 32.Which of these adds to bias? (a) add varied examples (b) ask different people (c) use one group only (d) check who is missing
  33. 33.True or false: “check who is missing” adds to bias. (a) True (b) False
  34. 34.True or false: “ask different people” helps reduce bias. (a) False (b) True
  35. 35.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  36. 36.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  37. 37.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) check who is missing (d) test on many groups
  38. 38.True or false: “add varied examples” adds to bias. (a) True (b) False
  39. 39.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  40. 40.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False

Answer key

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

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