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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 692 · 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.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  2. 2.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) ask different people (d) test on many groups
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) a broken screen (d) bias from data
  4. 4.Which of these adds to bias? (a) test on many groups (b) ask different people (c) skip testing (d) fix wrong labels
  5. 5.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) test on many groups (d) ignore complaints
  6. 6.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  7. 7.True or false: “ask different people” helps reduce bias. (a) True (b) False
  8. 8.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  9. 9.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  10. 10.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
  11. 11.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  12. 12.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) use one group only (d) balance the data
  13. 13.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
  14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  15. 15.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) ask different people (d) copy old unfair choices
  16. 16.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  17. 17.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  18. 18.True or false: “use one group only” adds to bias. (a) False (b) True
  19. 19.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  20. 20.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  21. 21.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) check who is missing (d) add more of the same
  22. 22.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  23. 23.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  24. 24.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  25. 25.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) copy old unfair choices (d) test on one group only
  26. 26.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  27. 27.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  28. 28.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  30. 30.True or false: “test on many groups” adds to bias. (a) False (b) True
  31. 31.True or false: “ask different people” adds to bias. (a) False (b) True
  32. 32.Which of these adds to bias? (a) use one group only (b) add varied examples (c) check who is missing (d) test on many groups
  33. 33.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  34. 34.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) use one group only (d) fix wrong labels
  35. 35.True or false: “test on one group only” adds to bias. (a) False (b) True
  36. 36.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  38. 38.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) ask different people (d) copy old unfair choices
  39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  40. 40.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias

Answer key

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

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