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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 288 · 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 helps reduce bias? (a) check who is missing (b) skip testing (c) ignore complaints (d) copy old unfair choices
  2. 2.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  3. 3.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) ignore complaints
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
  5. 5.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  6. 6.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) fix wrong labels (d) test on one group only
  7. 7.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  9. 9.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) balance the data (d) test on many groups
  10. 10.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  11. 11.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  12. 12.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  13. 13.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) skip testing (d) add more of the same
  14. 14.True or false: “check who is missing” 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.True or false: “skip testing” adds to bias. (a) True (b) False
  17. 17.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  20. 20.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  21. 21.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  22. 22.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) balance the data (d) add more of the same
  23. 23.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  24. 24.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) skip testing (d) check who is missing
  25. 25.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  26. 26.Which of these helps reduce bias? (a) add more of the same (b) fix wrong labels (c) copy old unfair choices (d) use one group only
  27. 27.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) balance the data (d) use one group only
  28. 28.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
  30. 30.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  31. 31.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  32. 32.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  33. 33.True or false: “add more of the same” adds to bias. (a) False (b) True
  34. 34.True or false: “balance the data” adds to bias. (a) True (b) False
  35. 35.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  37. 37.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  38. 38.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  39. 39.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  40. 40.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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