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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 872 · 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: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  2. 2.Which of these adds to bias? (a) use one group only (b) test on many groups (c) balance the data (d) ask different people
  3. 3.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  4. 4.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
  5. 5.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  6. 6.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
  7. 7.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  8. 8.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) fix wrong labels (d) skip testing
  9. 9.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) test on many groups (d) add more of the same
  10. 10.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ignore complaints (d) test on many groups
  11. 11.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  12. 12.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) fix wrong labels (d) copy old unfair choices
  14. 14.True or false: “skip testing” adds to bias. (a) True (b) False
  15. 15.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  16. 16.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  17. 17.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) ask different people (d) add more of the same
  18. 18.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  19. 19.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  20. 20.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) use one group only (d) test on one group only
  21. 21.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.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
  23. 23.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  24. 24.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  26. 26.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  27. 27.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  28. 28.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  29. 29.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  30. 30.True or false: “ask different people” adds to bias. (a) True (b) False
  31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  32. 32.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  33. 33.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  35. 35.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  36. 36.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) skip testing (d) ask different people
  37. 37.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) test on many groups (d) balance the data
  39. 39.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  40. 40.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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