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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 231 · 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 where every doctor is a man? (a) one-sided data (b) balanced data
  2. 2.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  4. 4.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) copy old unfair choices (d) balance the data
  5. 5.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  6. 6.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  7. 7.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) ignore complaints (d) fix wrong labels
  8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  9. 9.Which of these adds to bias? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) ask different people
  10. 10.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) ignore complaints (d) add varied examples
  12. 12.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) use one group only (d) add varied examples
  13. 13.Which of these adds to bias? (a) add varied examples (b) ask different people (c) fix wrong labels (d) add more of the same
  14. 14.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  15. 15.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  16. 16.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  17. 17.Which of these adds to bias? (a) skip testing (b) add varied examples (c) check who is missing (d) fix wrong labels
  18. 18.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  20. 20.True or false: “skip testing” helps reduce bias. (a) False (b) True
  21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  22. 22.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  24. 24.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) add more of the same (d) copy old unfair choices
  26. 26.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  28. 28.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) test on many groups (d) skip testing
  29. 29.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  30. 30.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) balance the data (d) check who is missing
  31. 31.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
  32. 32.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add more of the same (d) test on many groups
  33. 33.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  35. 35.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  37. 37.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  38. 38.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  40. 40.True or false: “ask different people” helps reduce bias. (a) False (b) True

Answer key

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

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