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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 119 · 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: “test on many groups” helps reduce bias. (a) False (b) True
  2. 2.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  5. 5.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  6. 6.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  8. 8.Which of these helps reduce bias? (a) balance the data (b) add more of the same (c) use one group only (d) ignore complaints
  9. 9.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) test on one group only (d) fix wrong labels
  10. 10.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  12. 12.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
  13. 13.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) skip testing (d) use one group only
  15. 15.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  16. 16.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  17. 17.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) ignore complaints (d) test on one group only
  18. 18.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  19. 19.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) ignore complaints (d) test on many groups
  20. 20.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  21. 21.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  22. 22.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  23. 23.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  25. 25.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) fix wrong labels (d) use one group only
  27. 27.🗣️ 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) it was a rainy day (d) children speak too fast
  28. 28.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  30. 30.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) balance the data (d) ask different people
  31. 31.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  32. 32.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) ignore complaints (d) test on one group only
  33. 33.True or false: “balance the data” adds to bias. (a) False (b) True
  34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  35. 35.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) balance the data (d) add more of the same
  37. 37.True or false: “ask different people” adds to bias. (a) False (b) True
  38. 38.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  39. 39.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  40. 40.True or false: “add more of the same” helps reduce bias. (a) False (b) True

Answer key

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

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