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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 55 · 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: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  2. 2.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  3. 3.🗣️ 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
  4. 4.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  5. 5.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  6. 6.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  7. 7.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  8. 8.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) fix wrong labels (d) copy old unfair choices
  9. 9.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) test on one group only (d) use one group only
  10. 10.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) skip testing
  12. 12.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  13. 13.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  16. 16.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) add more of the same (d) test on many groups
  17. 17.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  18. 18.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  19. 19.Which of these adds to bias? (a) ask different people (b) copy old unfair choices (c) test on many groups (d) check who is missing
  20. 20.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  21. 21.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
  22. 22.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) ignore complaints (d) use one group only
  23. 23.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) copy old unfair choices (d) check who is missing
  24. 24.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) ask different people (d) add varied examples
  25. 25.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  26. 26.True or false: “skip testing” adds to bias. (a) True (b) False
  27. 27.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) skip testing (d) fix wrong labels
  28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  29. 29.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  30. 30.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) ask different people
  31. 31.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  33. 33.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  35. 35.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) ask different people (d) test on many groups
  37. 37.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  39. 39.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  40. 40.True or false: “skip testing” helps reduce bias. (a) False (b) True

Answer key

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

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