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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 396 · 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: “test on one group only” adds to bias. (a) False (b) True
  2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  3. 3.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) use one group only (d) add more of the same
  4. 4.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  6. 6.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  7. 7.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) fix wrong labels (d) test on one group only
  8. 8.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  10. 10.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) copy old unfair choices (d) add more of the same
  11. 11.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  13. 13.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  14. 14.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) fix wrong labels (d) test on one group only
  15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  17. 17.Which of these helps reduce bias? (a) skip testing (b) fix wrong labels (c) use one group only (d) ignore complaints
  18. 18.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) add varied examples (d) use one group only
  19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  20. 20.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) skip testing (d) check who is missing
  21. 21.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
  22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  24. 24.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) test on many groups (d) add more of the same
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) use one group only (d) add more of the same
  26. 26.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
  27. 27.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  28. 28.True or false: “check who is missing” adds to bias. (a) True (b) False
  29. 29.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  30. 30.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  31. 31.True or false: “balance the data” helps reduce bias. (a) False (b) True
  32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.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
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  35. 35.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  36. 36.True or false: “ask different people” helps reduce bias. (a) False (b) True
  37. 37.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  38. 38.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) copy old unfair choices (d) use one group only
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  40. 40.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

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

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