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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 141 · 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: test on one group only? (a) reduces bias (b) adds to bias
  2. 2.Which of these adds to bias? (a) skip testing (b) test on many groups (c) check who is missing (d) add varied examples
  3. 3.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) ignore complaints (d) add more of the same
  4. 4.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) add varied examples (d) test on many groups
  5. 5.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) fix wrong labels (d) check who is missing
  6. 6.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  7. 7.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ignore complaints (d) copy old unfair choices
  8. 8.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) use one group only (d) add varied examples
  9. 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  10. 10.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) skip testing (d) add varied examples
  11. 11.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) copy old unfair choices (d) add more of the same
  12. 12.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  14. 14.True or false: “ignore complaints” adds to bias. (a) True (b) False
  15. 15.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  16. 16.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
  17. 17.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  18. 18.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  19. 19.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  20. 20.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
  21. 21.True or false: “test on many groups” adds to bias. (a) True (b) False
  22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  23. 23.True or false: “add varied examples” adds to bias. (a) False (b) True
  24. 24.Which of these adds to bias? (a) balance the data (b) test on many groups (c) copy old unfair choices (d) check who is missing
  25. 25.Which of these helps reduce bias? (a) add more of the same (b) check who is missing (c) test on one group only (d) use one group only
  26. 26.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  28. 28.True or false: “balance the data” adds to bias. (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  30. 30.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  31. 31.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  32. 32.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) use one group only (d) fix wrong labels
  33. 33.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  34. 34.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  35. 35.Which of these adds to bias? (a) test on many groups (b) balance the data (c) add more of the same (d) fix wrong labels
  36. 36.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  37. 37.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  40. 40.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data

Answer key

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

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