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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 793 · 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: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  3. 3.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) use one group only (d) test on many groups
  4. 4.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) copy old unfair choices (d) add more of the same
  5. 5.Which of these adds to bias? (a) add varied examples (b) balance the data (c) ignore complaints (d) test on many groups
  6. 6.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  8. 8.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  9. 9.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) check who is missing (d) use one group only
  10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  11. 11.True or false: “test on many groups” adds to bias. (a) False (b) True
  12. 12.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  13. 13.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  14. 14.Which of these adds to bias? (a) check who is missing (b) ask different people (c) add varied examples (d) copy old unfair choices
  15. 15.True or false: “add varied examples” adds to bias. (a) False (b) True
  16. 16.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  17. 17.True or false: “balance the data” adds to bias. (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) copy old unfair choices (d) test on many groups
  19. 19.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
  20. 20.Which of these adds to bias? (a) check who is missing (b) add more of the same (c) balance the data (d) test on many groups
  21. 21.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  22. 22.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  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.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) ask different people
  26. 26.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  27. 27.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  28. 28.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  30. 30.True or false: “test on one group only” adds to bias. (a) False (b) True
  31. 31.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  32. 32.True or false: “check who is missing” adds to bias. (a) False (b) True
  33. 33.Which of these adds to bias? (a) test on many groups (b) use one group only (c) balance the data (d) fix wrong labels
  34. 34.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  35. 35.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  37. 37.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) balance the data (d) use one group only
  38. 38.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) fix wrong labels (d) skip testing
  40. 40.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data

Answer key

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

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