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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 565 · 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: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  4. 4.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
  5. 5.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) use one group only (d) balance the data
  6. 6.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  7. 7.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  8. 8.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  11. 11.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) ask different people (d) copy old unfair choices
  12. 12.True or false: “skip testing” adds to bias. (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) add varied examples (d) test on many groups
  14. 14.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  15. 15.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  17. 17.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  18. 18.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  20. 20.True or false: “add varied examples” adds to bias. (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) ignore complaints (d) add varied examples
  22. 22.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) use one group only (d) copy old unfair choices
  23. 23.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
  24. 24.Which of these helps reduce bias? (a) fix wrong labels (b) copy old unfair choices (c) ignore complaints (d) add more of the same
  25. 25.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
  26. 26.True or false: “balance the data” helps reduce bias. (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  28. 28.True or false: “test on many groups” adds to bias. (a) False (b) True
  29. 29.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  30. 30.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  32. 32.True or false: “skip testing” helps reduce bias. (a) False (b) True
  33. 33.True or false: “ignore complaints” adds to bias. (a) True (b) False
  34. 34.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  35. 35.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  37. 37.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) balance the data (d) use one group only
  38. 38.True or false: “balance the data” adds to bias. (a) False (b) True
  39. 39.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

Answer key

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

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