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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 497 · 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
  2. 2.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  4. 4.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) add more of the same (d) use one group only
  5. 5.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  6. 6.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  8. 8.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) fix wrong labels (d) balance the data
  9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  10. 10.True or false: “skip testing” helps reduce bias. (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) test on one group only
  12. 12.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  13. 13.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) use one group only (d) skip testing
  15. 15.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  16. 16.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  18. 18.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add more of the same (d) balance the data
  19. 19.True or false: “ignore complaints” adds to bias. (a) False (b) True
  20. 20.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) check who is missing (d) test on one group only
  21. 21.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  22. 22.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  24. 24.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) test on many groups (d) fix wrong labels
  25. 25.Which of these adds to bias? (a) test on many groups (b) balance the data (c) skip testing (d) add varied examples
  26. 26.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  27. 27.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  28. 28.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  29. 29.Which of these helps reduce bias? (a) copy old unfair choices (b) test on many groups (c) use one group only (d) test on one group only
  30. 30.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) copy old unfair choices
  31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  32. 32.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  34. 34.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  35. 35.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  36. 36.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
  37. 37.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) test on many groups (d) add more of the same
  38. 38.True or false: “use one group only” adds to bias. (a) False (b) True
  39. 39.True or false: “balance the data” adds to bias. (a) True (b) False
  40. 40.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on many groups (d) copy old unfair choices

Answer key

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

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