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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 802 · 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: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) add more of the same (d) fix wrong labels
  3. 3.Which of these adds to bias? (a) skip testing (b) test on many groups (c) add varied examples (d) ask different people
  4. 4.True or false: “use one group only” helps reduce bias. (a) True (b) False
  5. 5.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ignore complaints (d) ask different people
  6. 6.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  7. 7.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  8. 8.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  9. 9.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) ignore complaints (d) copy old unfair choices
  10. 10.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) test on one group only
  11. 11.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  12. 12.True or false: “add more of the same” adds to bias. (a) False (b) True
  13. 13.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  15. 15.True or false: “ask different people” helps reduce bias. (a) False (b) True
  16. 16.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  19. 19.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  20. 20.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  22. 22.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  23. 23.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) test on many groups (d) add more of the same
  24. 24.True or false: “add varied examples” adds to bias. (a) True (b) False
  25. 25.True or false: “check who is missing” adds to bias. (a) False (b) True
  26. 26.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
  27. 27.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  28. 28.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) check who is missing (d) add varied examples
  29. 29.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) add varied examples (d) ignore complaints
  30. 30.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  31. 31.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
  32. 32.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on one group only (d) balance the data
  33. 33.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  34. 34.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  35. 35.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) check who is missing (d) skip testing
  36. 36.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) check who is missing (d) test on many groups
  37. 37.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  38. 38.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  39. 39.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: “balance the data” helps reduce bias. (a) False (b) True

Answer key

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

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