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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 210 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  2. 2.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
  3. 3.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  4. 4.True or false: “test on many groups” adds to bias. (a) True (b) False
  5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  7. 7.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  8. 8.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
  9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  10. 10.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  11. 11.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) add more of the same (d) check who is missing
  13. 13.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  14. 14.True or false: “ask different people” adds to bias. (a) True (b) False
  15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  16. 16.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) balance the data (d) ignore complaints
  17. 17.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  18. 18.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  19. 19.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  20. 20.True or false: “check who is missing” adds to bias. (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  22. 22.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  23. 23.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  24. 24.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  25. 25.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  27. 27.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  28. 28.True or false: “ask different people” helps reduce bias. (a) True (b) False
  29. 29.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  30. 30.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  31. 31.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  32. 32.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) copy old unfair choices (d) skip testing
  34. 34.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) copy old unfair choices (d) check who is missing
  35. 35.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) ignore complaints (d) check who is missing
  36. 36.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ask different people (d) check who is missing
  37. 37.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) fix wrong labels (d) ask different people
  38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  39. 39.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  40. 40.True or false: “ignore complaints” adds to bias. (a) False (b) True

Answer key

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

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