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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 425 · 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.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  2. 2.Which of these adds to bias? (a) fix wrong labels (b) ignore complaints (c) balance the data (d) ask different people
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) the phone was new (d) it was a rainy day
  4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a strong battery (d) a fair model
  5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  6. 6.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) use one group only (d) add varied examples
  7. 7.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  8. 8.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) use one group only (d) test on one group only
  9. 9.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) test on one group only
  10. 10.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  11. 11.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  12. 12.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) skip testing (d) ask different people
  14. 14.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  16. 16.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  17. 17.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  18. 18.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  19. 19.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) ignore complaints (d) skip testing
  20. 20.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  22. 22.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  24. 24.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  25. 25.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) use one group only (d) check who is missing
  26. 26.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  27. 27.True or false: “ignore complaints” adds to bias. (a) True (b) False
  28. 28.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  30. 30.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) use one group only (d) fix wrong labels
  31. 31.True or false: “ask different people” helps reduce bias. (a) False (b) True
  32. 32.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  33. 33.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  34. 34.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) fix wrong labels (d) skip testing
  35. 35.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  36. 36.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: “skip testing” helps reduce bias. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  39. 39.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  40. 40.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) copy old unfair choices (d) ignore complaints

Answer key

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

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