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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 438 · 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 many groups” helps reduce bias. (a) False (b) True
  2. 2.Which of these helps reduce bias? (a) add more of the same (b) ask different people (c) copy old unfair choices (d) use one group only
  3. 3.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) balance the data (d) copy old unfair choices
  4. 4.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  6. 6.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) add varied examples (d) ignore complaints
  8. 8.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  9. 9.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  10. 10.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  12. 12.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  13. 13.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  14. 14.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  15. 15.True or false: “test on one group only” adds to bias. (a) False (b) True
  16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  17. 17.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) test on many groups (d) skip testing
  18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  19. 19.Which of these adds to bias? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) add varied examples
  20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  23. 23.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  24. 24.True or false: “use one group only” adds to bias. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) skip testing (d) test on many groups
  26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  27. 27.True or false: “balance the data” adds to bias. (a) False (b) True
  28. 28.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  30. 30.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) copy old unfair choices (d) add varied examples
  31. 31.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) fix wrong labels (d) test on one group only
  34. 34.Which of these helps reduce bias? (a) copy old unfair choices (b) check who is missing (c) test on one group only (d) add more of the same
  35. 35.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) balance the data (d) test on one group only
  36. 36.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  37. 37.True or false: “ask different people” adds to bias. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) use one group only (d) ignore complaints
  39. 39.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) use one group only (d) add varied examples
  40. 40.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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