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AI Bias Worksheet for Kids

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

Answer key

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

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