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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 896 · 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: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  3. 3.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) check who is missing (d) test on many groups
  4. 4.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) test on many groups (d) balance the data
  5. 5.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  6. 6.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  7. 7.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) fix wrong labels (d) balance the data
  9. 9.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
  10. 10.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  11. 11.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) ignore complaints (d) skip testing
  12. 12.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) add varied examples (d) copy old unfair choices
  13. 13.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  16. 16.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  17. 17.True or false: “balance the data” helps reduce bias. (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) check who is missing (d) add more of the same
  19. 19.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) use one group only (d) check who is missing
  20. 20.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  21. 21.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  22. 22.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  23. 23.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  24. 24.Which of these adds to bias? (a) ignore complaints (b) ask different people (c) add varied examples (d) balance the data
  25. 25.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
  26. 26.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) skip testing (d) fix wrong labels
  27. 27.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  28. 28.True or false: “use one group only” adds to bias. (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  30. 30.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  31. 31.True or false: “add varied examples” adds to bias. (a) True (b) False
  32. 32.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  33. 33.Which of these adds to bias? (a) test on many groups (b) skip testing (c) add varied examples (d) fix wrong labels
  34. 34.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  35. 35.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) test on many groups
  36. 36.True or false: “ask different people” adds to bias. (a) False (b) True
  37. 37.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  38. 38.True or false: “test on many groups” adds to bias. (a) True (b) False
  39. 39.True or false: “use one group only” helps reduce bias. (a) True (b) False
  40. 40.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias

Answer key

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

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