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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 964 · 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: “copy old unfair choices” adds to bias. (a) False (b) True
  2. 2.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  3. 3.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
  4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  5. 5.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) use one group only (d) ignore complaints
  6. 6.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
  7. 7.True or false: “use one group only” helps reduce bias. (a) True (b) False
  8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  9. 9.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
  12. 12.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) add varied examples (d) copy old unfair choices
  13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
  14. 14.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  15. 15.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  16. 16.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  17. 17.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
  18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  19. 19.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  22. 22.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  24. 24.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) add varied examples (d) check who is missing
  25. 25.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  26. 26.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ignore complaints (d) check who is missing
  27. 27.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  29. 29.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  30. 30.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) ask different people (d) fix wrong labels
  31. 31.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  32. 32.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  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: “add varied examples” adds to bias. (a) False (b) True
  36. 36.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) add more of the same (d) ignore complaints
  37. 37.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  38. 38.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  39. 39.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) ask different people (d) check who is missing
  40. 40.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias

Answer key

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

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