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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 624 · 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: “use one group only” helps reduce bias. (a) False (b) True
  2. 2.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  3. 3.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  4. 4.Which of these adds to bias? (a) balance the data (b) test on many groups (c) ask different people (d) copy old unfair choices
  5. 5.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  6. 6.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  8. 8.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  10. 10.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  11. 11.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  12. 12.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
  13. 13.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  14. 14.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) check who is missing (d) ignore complaints
  15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  16. 16.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
  17. 17.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) skip testing (d) ask different people
  19. 19.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  20. 20.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  21. 21.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) add more of the same (d) balance the data
  22. 22.Which of these adds to bias? (a) skip testing (b) check who is missing (c) fix wrong labels (d) balance the data
  23. 23.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  24. 24.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) skip testing (d) ignore complaints
  25. 25.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) use one group only (d) skip testing
  26. 26.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  27. 27.Which of these adds to bias? (a) add varied examples (b) add more of the same (c) fix wrong labels (d) check who is missing
  28. 28.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  29. 29.🗣️ 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
  30. 30.True or false: “skip testing” adds to bias. (a) True (b) False
  31. 31.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) add more of the same (d) test on one group only
  32. 32.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  33. 33.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) ignore complaints (d) check who is missing
  34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  36. 36.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  37. 37.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) fix wrong labels (d) test on one group only
  38. 38.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) ignore complaints (d) balance the data
  39. 39.True or false: “balance the data” helps reduce bias. (a) False (b) True
  40. 40.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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