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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 214 · 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: “ask different people” adds to bias. (a) False (b) True
  2. 2.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  3. 3.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  4. 4.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) ignore complaints (d) fix wrong labels
  5. 5.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) add more of the same (d) fix wrong labels
  6. 6.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  8. 8.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  10. 10.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  11. 11.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  12. 12.Which of these adds to bias? (a) check who is missing (b) balance the data (c) copy old unfair choices (d) fix wrong labels
  13. 13.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  14. 14.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) ignore complaints (d) add more of the same
  15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  16. 16.Which of these adds to bias? (a) ask different people (b) balance the data (c) test on many groups (d) test on one group only
  17. 17.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  19. 19.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  20. 20.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  22. 22.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) copy old unfair choices (d) skip testing
  23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) add varied examples
  24. 24.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) copy old unfair choices (d) test on many groups
  25. 25.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  27. 27.True or false: “ignore complaints” adds to bias. (a) True (b) False
  28. 28.Which of these adds to bias? (a) ask different people (b) add more of the same (c) fix wrong labels (d) add varied examples
  29. 29.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  30. 30.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  32. 32.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
  33. 33.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  34. 34.True or false: “test on many groups” adds to bias. (a) False (b) True
  35. 35.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  36. 36.Which of these adds to bias? (a) use one group only (b) test on many groups (c) check who is missing (d) add varied examples
  37. 37.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  38. 38.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
  39. 39.Which of these adds to bias? (a) ask different people (b) skip testing (c) test on many groups (d) add varied examples
  40. 40.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data

Answer key

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

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