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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 930 · 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) fix wrong labels (b) ask different people (c) check who is missing (d) copy old unfair choices
  2. 2.True or false: “add more of the same” adds to bias. (a) False (b) True
  3. 3.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  4. 4.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) ignore complaints (d) copy old unfair choices
  5. 5.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) ask different people (d) fix wrong labels
  6. 6.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  9. 9.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  10. 10.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) copy old unfair choices (d) add varied examples
  11. 11.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  13. 13.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  14. 14.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
  15. 15.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  16. 16.Which of these adds to bias? (a) test on one group only (b) ask different people (c) check who is missing (d) balance the data
  17. 17.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  18. 18.True or false: “skip testing” helps reduce bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  20. 20.Which of these adds to bias? (a) ask different people (b) add varied examples (c) balance the data (d) ignore complaints
  21. 21.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  22. 22.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  23. 23.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) skip testing (d) ignore complaints
  24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) it was a rainy day (d) children speak too fast
  25. 25.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  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.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  29. 29.True or false: “balance the data” helps reduce bias. (a) False (b) True
  30. 30.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) test on one group only (d) test on many groups
  31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  32. 32.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) add varied examples (d) balance the data
  33. 33.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  34. 34.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) test on many groups (d) add varied examples
  35. 35.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  37. 37.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  38. 38.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  39. 39.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
  40. 40.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data

Answer key

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

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