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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 157 · 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.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) add more of the same (d) check who is missing
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  3. 3.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  4. 4.Which of these adds to bias? (a) balance the data (b) ask different people (c) copy old unfair choices (d) test on many groups
  5. 5.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
  6. 6.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  7. 7.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) ask different people (d) check who is missing
  8. 8.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  9. 9.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
  10. 10.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  11. 11.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  12. 12.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on one group only (d) check who is missing
  14. 14.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  15. 15.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
  16. 16.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  17. 17.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  18. 18.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  21. 21.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  22. 22.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  23. 23.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) test on many groups (d) use one group only
  24. 24.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  25. 25.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  26. 26.True or false: “add varied examples” adds to bias. (a) False (b) True
  27. 27.Which of these adds to bias? (a) balance the data (b) check who is missing (c) ask different people (d) test on one group only
  28. 28.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) check who is missing (d) add varied examples
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  30. 30.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  31. 31.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  32. 32.True or false: “balance the data” helps reduce bias. (a) True (b) False
  33. 33.True or false: “skip testing” helps reduce bias. (a) False (b) True
  34. 34.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) copy old unfair choices (d) ignore complaints
  35. 35.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  36. 36.True or false: “test on one group only” adds to bias. (a) False (b) True
  37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  38. 38.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  39. 39.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) use one group only (d) copy old unfair choices
  40. 40.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias

Answer key

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

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