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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 958 · 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) balanced data (b) one-sided data
  2. 2.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  4. 4.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) ignore complaints (d) fix wrong labels
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  8. 8.True or false: “skip testing” helps reduce bias. (a) False (b) True
  9. 9.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  10. 10.Which of these adds to bias? (a) use one group only (b) ask different people (c) add varied examples (d) check who is missing
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  12. 12.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  13. 13.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  14. 14.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) test on one group only (d) add varied examples
  16. 16.True or false: “ignore complaints” adds to bias. (a) True (b) False
  17. 17.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) ignore complaints (d) ask different people
  18. 18.True or false: “skip testing” adds to bias. (a) True (b) False
  19. 19.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  20. 20.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) use one group only (d) check who is missing
  21. 21.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  22. 22.True or false: “check who is missing” adds to bias. (a) False (b) True
  23. 23.Which of these adds to bias? (a) check who is missing (b) skip testing (c) test on many groups (d) add varied examples
  24. 24.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  26. 26.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) add varied examples (d) copy old unfair choices
  28. 28.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  30. 30.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) skip testing (d) check who is missing
  31. 31.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  32. 32.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  33. 33.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) skip testing (d) ignore complaints
  34. 34.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
  35. 35.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  36. 36.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  37. 37.True or false: “balance the data” helps reduce bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  39. 39.True or false: “ask different people” adds to bias. (a) False (b) True
  40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data

Answer key

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

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