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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 808 · 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.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  2. 2.Which of these adds to bias? (a) skip testing (b) check who is missing (c) balance the data (d) add varied examples
  3. 3.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a fair model (d) a broken screen
  6. 6.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  7. 7.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) balance the data (d) use one group only
  8. 8.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) use one group only (d) add more of the same
  10. 10.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  12. 12.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  14. 14.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) test on many groups
  15. 15.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
  16. 16.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  17. 17.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  18. 18.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  19. 19.True or false: “test on one group only” adds to bias. (a) True (b) False
  20. 20.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) test on one group only (d) test on many groups
  21. 21.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  22. 22.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) skip testing (d) use one group only
  23. 23.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  24. 24.True or false: “test on many groups” adds to bias. (a) True (b) False
  25. 25.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  26. 26.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  27. 27.True or false: “skip testing” adds to bias. (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) ignore complaints (d) skip testing
  29. 29.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  30. 30.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  32. 32.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  33. 33.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.Which of these adds to bias? (a) add varied examples (b) ask different people (c) fix wrong labels (d) add more of the same
  35. 35.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  37. 37.True or false: “add more of the same” adds to bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  39. 39.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) use one group only (d) fix wrong labels
  40. 40.True or false: “check who is missing” adds to bias. (a) True (b) False

Answer key

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

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