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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 426 · 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: “test on one group only” helps reduce bias. (a) False (b) True
  2. 2.Which of these adds to bias? (a) ignore complaints (b) balance the data (c) check who is missing (d) test on many groups
  3. 3.Which of these adds to bias? (a) balance the data (b) add varied examples (c) ask different people (d) use one group only
  4. 4.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  5. 5.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) test on many groups (d) test on one group only
  6. 6.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  7. 7.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) balance the data (d) test on one group only
  8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  9. 9.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  10. 10.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
  12. 12.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) add more of the same (d) add varied examples
  13. 13.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  15. 15.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) use one group only (d) balance the data
  16. 16.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  17. 17.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) copy old unfair choices (d) add varied examples
  18. 18.True or false: “use one group only” adds to bias. (a) True (b) False
  19. 19.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  20. 20.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  21. 21.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) ask different people (d) copy old unfair choices
  23. 23.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) add more of the same (d) balance the data
  24. 24.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  26. 26.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  27. 27.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  29. 29.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  30. 30.True or false: “add varied examples” adds to bias. (a) True (b) False
  31. 31.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  32. 32.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) skip testing (d) ask different people
  33. 33.True or false: “test on many groups” adds to bias. (a) False (b) True
  34. 34.Which of these adds to bias? (a) skip testing (b) check who is missing (c) fix wrong labels (d) balance the data
  35. 35.True or false: “skip testing” helps reduce bias. (a) False (b) True
  36. 36.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  37. 37.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) skip testing (d) ask different people
  38. 38.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  39. 39.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) ask different people (d) ignore complaints
  40. 40.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias

Answer key

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

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