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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 540 · 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: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  3. 3.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  4. 4.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) ask different people (d) add varied examples
  5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  6. 6.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) use one group only (d) add more of the same
  8. 8.Which of these adds to bias? (a) test on one group only (b) ask different people (c) test on many groups (d) add varied examples
  9. 9.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  10. 10.True or false: “ask different people” adds to bias. (a) True (b) False
  11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  12. 12.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) ignore complaints
  14. 14.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  15. 15.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  17. 17.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) ask different people (d) test on many groups
  18. 18.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  19. 19.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  20. 20.True or false: “balance the data” adds to bias. (a) True (b) False
  21. 21.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  22. 22.True or false: “balance the data” helps reduce bias. (a) False (b) True
  23. 23.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  24. 24.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  25. 25.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) test on one group only (d) use one group only
  26. 26.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) check who is missing (d) ask different people
  27. 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  28. 28.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) add more of the same (d) ignore complaints
  29. 29.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  30. 30.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  31. 31.Which of these helps reduce bias? (a) balance the data (b) skip testing (c) ignore complaints (d) test on one group only
  32. 32.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) add varied examples
  33. 33.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  34. 34.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  35. 35.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  37. 37.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  38. 38.Which of these adds to bias? (a) ask different people (b) skip testing (c) balance the data (d) test on many groups
  39. 39.True or false: “add varied examples” adds to bias. (a) True (b) False
  40. 40.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

Answer key

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

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