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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 815 · 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: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  2. 2.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
  4. 4.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  6. 6.True or false: “use one group only” adds to bias. (a) True (b) False
  7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  8. 8.Which of these adds to bias? (a) skip testing (b) balance the data (c) add varied examples (d) check who is missing
  9. 9.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  11. 11.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  13. 13.True or false: “balance the data” helps reduce bias. (a) False (b) True
  14. 14.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  15. 15.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  16. 16.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  17. 17.True or false: “test on many groups” adds to bias. (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) use one group only (d) test on many groups
  19. 19.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) add varied examples (d) ask different people
  20. 20.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  21. 21.True or false: “add more of the same” adds to bias. (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) use one group only (d) balance the data
  23. 23.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  24. 24.Which of these helps reduce bias? (a) balance the data (b) use one group only (c) copy old unfair choices (d) skip testing
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ignore complaints (d) use one group only
  26. 26.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  27. 27.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  29. 29.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  30. 30.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  32. 32.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  33. 33.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) use one group only (d) fix wrong labels
  34. 34.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.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
  36. 36.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  37. 37.Which of these adds to bias? (a) check who is missing (b) ignore complaints (c) balance the data (d) ask different people
  38. 38.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  40. 40.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias

Answer key

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

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