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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 928 · 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.Which of these adds to bias? (a) ignore complaints (b) fix wrong labels (c) test on many groups (d) check who is missing
  2. 2.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
  4. 4.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  6. 6.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) check who is missing (d) add varied examples
  8. 8.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) balance the data (d) ignore complaints
  9. 9.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) skip testing (d) add varied examples
  10. 10.Which of these helps reduce bias? (a) use one group only (b) fix wrong labels (c) skip testing (d) copy old unfair choices
  11. 11.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  12. 12.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) add more of the same (d) add varied examples
  13. 13.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  14. 14.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) balance the data (d) skip testing
  15. 15.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  16. 16.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  17. 17.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) add more of the same (d) test on one group only
  18. 18.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  19. 19.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  20. 20.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: “skip testing” helps reduce bias. (a) False (b) True
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  23. 23.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) ask different people (d) ignore complaints
  24. 24.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  25. 25.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) add varied examples (d) skip testing
  26. 26.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  28. 28.True or false: “balance the data” helps reduce bias. (a) True (b) False
  29. 29.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  30. 30.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  31. 31.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  32. 32.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  33. 33.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  34. 34.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  35. 35.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  36. 36.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) balance the data (d) check who is missing
  37. 37.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  38. 38.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  39. 39.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) test on one group only (d) use one group only
  40. 40.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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