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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 945 · 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.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  3. 3.True or false: “use one group only” helps reduce bias. (a) False (b) True
  4. 4.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  5. 5.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) skip testing (d) use one group only
  6. 6.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  7. 7.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
  9. 9.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add varied examples (d) ignore complaints
  10. 10.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
  11. 11.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) add more of the same (d) ignore complaints
  12. 12.Which of these helps reduce bias? (a) balance the data (b) use one group only (c) copy old unfair choices (d) skip testing
  13. 13.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  15. 15.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) add more of the same (d) balance the data
  16. 16.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  18. 18.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  19. 19.True or false: “skip testing” helps reduce bias. (a) True (b) False
  20. 20.True or false: “check who is missing” adds to bias. (a) True (b) False
  21. 21.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  23. 23.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  24. 24.Which of these helps reduce bias? (a) add more of the same (b) fix wrong labels (c) use one group only (d) ignore complaints
  25. 25.True or false: “use one group only” adds to bias. (a) True (b) False
  26. 26.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  27. 27.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  28. 28.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) copy old unfair choices (d) ask different people
  29. 29.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  30. 30.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on one group only (d) test on many groups
  31. 31.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) ask different people (d) fix wrong labels
  32. 32.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ask different people (d) ignore complaints
  33. 33.Which of these adds to bias? (a) use one group only (b) ask different people (c) add varied examples (d) test on many groups
  34. 34.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  36. 36.True or false: “test on one group only” adds to bias. (a) True (b) False
  37. 37.Which of these adds to bias? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) test on many groups
  38. 38.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
  39. 39.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  40. 40.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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