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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 259 · 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) ask different people (b) add varied examples (c) fix wrong labels (d) copy old unfair choices
  2. 2.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  4. 4.Which of these adds to bias? (a) test on many groups (b) ask different people (c) use one group only (d) balance the data
  5. 5.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) test on many groups
  7. 7.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  8. 8.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.True or false: “check who is missing” adds to bias. (a) False (b) True
  10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  11. 11.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
  13. 13.True or false: “add more of the same” adds to bias. (a) False (b) True
  14. 14.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) test on many groups (d) balance the data
  15. 15.True or false: “skip testing” adds to bias. (a) True (b) False
  16. 16.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) ask different people
  17. 17.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) balance the data (d) test on many groups
  18. 18.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  19. 19.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  20. 20.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  22. 22.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  24. 24.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  25. 25.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  27. 27.🔍 Which is the odd one out? (a) test on many groups (b) skip testing (c) copy old unfair choices (d) add more of the same
  28. 28.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) ignore complaints (d) balance the data
  29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  30. 30.True or false: “ask different people” adds to bias. (a) True (b) False
  31. 31.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  32. 32.True or false: “test on one group only” adds to bias. (a) True (b) False
  33. 33.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) fix wrong labels (d) test on one group only
  34. 34.True or false: “test on many groups” adds to bias. (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) balance the data
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  37. 37.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  38. 38.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) test on many groups (d) test on one group only
  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: use one group only? (a) adds to bias (b) reduces bias

Answer key

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

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