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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 538 · 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: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  2. 2.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  4. 4.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  5. 5.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  6. 6.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) balance the data (d) copy old unfair choices
  7. 7.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) add more of the same (d) copy old unfair choices
  8. 8.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  10. 10.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  11. 11.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) check who is missing (d) copy old unfair choices
  12. 12.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) add varied examples (d) ignore complaints
  13. 13.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  14. 14.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  15. 15.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  16. 16.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  17. 17.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  18. 18.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) balance the data (d) ignore complaints
  19. 19.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  20. 20.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) check who is missing (d) use one group only
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  23. 23.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  24. 24.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) test on one group only (d) add more of the same
  25. 25.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  26. 26.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  27. 27.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  28. 28.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) use one group only (d) ignore complaints
  29. 29.True or false: “test on many groups” adds to bias. (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  31. 31.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) use one group only (d) ask different people
  32. 32.Which of these adds to bias? (a) ask different people (b) copy old unfair choices (c) test on many groups (d) balance the data
  33. 33.True or false: “add more of the same” adds to bias. (a) False (b) True
  34. 34.True or false: “use one group only” adds to bias. (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) test on one group only (d) skip testing
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
  37. 37.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  39. 39.Which of these adds to bias? (a) balance the data (b) ignore complaints (c) test on many groups (d) ask different people
  40. 40.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) fix wrong labels (d) add more of the same

Answer key

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

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