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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 743 · 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) skip testing (b) check who is missing (c) copy old unfair choices (d) use one group only
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  3. 3.True or false: “add varied examples” adds to bias. (a) False (b) True
  4. 4.Which of these helps reduce bias? (a) use one group only (b) ask different people (c) ignore complaints (d) skip testing
  5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  6. 6.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  7. 7.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  8. 8.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  9. 9.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) add more of the same (d) ask different people
  10. 10.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  11. 11.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
  12. 12.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
  13. 13.True or false: “ignore complaints” adds to bias. (a) True (b) False
  14. 14.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  16. 16.True or false: “balance the data” helps reduce bias. (a) True (b) False
  17. 17.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  19. 19.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) test on one group only (d) check who is missing
  20. 20.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  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: “check who is missing” adds to bias. (a) True (b) False
  23. 23.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  24. 24.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) skip testing (d) add varied examples
  25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) ignore complaints (d) fix wrong labels
  26. 26.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) use one group only (d) balance the data
  27. 27.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) fix wrong labels (d) add varied examples
  28. 28.True or false: “ask different people” helps reduce bias. (a) True (b) False
  29. 29.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) use one group only
  30. 30.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) add more of the same (d) ignore complaints
  31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  33. 33.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  34. 34.True or false: “balance the data” adds to bias. (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) check who is missing (d) balance the data
  36. 36.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  37. 37.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
  38. 38.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  39. 39.True or false: “use one group only” helps reduce bias. (a) True (b) False
  40. 40.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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