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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 710 · 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: “ignore complaints” helps reduce bias. (a) False (b) True
  2. 2.🖼️ 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
  3. 3.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) balance the data (d) test on one group only
  4. 4.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
  5. 5.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) fix wrong labels
  6. 6.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) add varied examples (d) test on one group only
  7. 7.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  10. 10.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  11. 11.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  12. 12.True or false: “skip testing” helps reduce bias. (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  14. 14.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  15. 15.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  16. 16.True or false: “test on many groups” adds to bias. (a) False (b) True
  17. 17.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) test on many groups (d) add more of the same
  18. 18.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) balance the data (d) check who is missing
  19. 19.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) test on one group only (d) use one group only
  20. 20.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  21. 21.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) ask different people (d) skip testing
  22. 22.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  24. 24.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  25. 25.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) check who is missing (d) ignore complaints
  26. 26.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.True or false: “skip testing” adds to bias. (a) True (b) False
  28. 28.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  29. 29.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  30. 30.True or false: “balance the data” helps reduce bias. (a) False (b) True
  31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  34. 34.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) use one group only (d) test on many groups
  36. 36.Which of these helps reduce bias? (a) add varied examples (b) skip testing (c) use one group only (d) test on one group only
  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.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  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. bias from data
  3. balance the data
  4. more varied data
  5. fix wrong labels
  6. test on one group only
  7. True
  8. reduces bias
  9. balanced data
  10. reduces bias
  11. reduces bias
  12. False
  13. one-sided data
  14. True
  15. reduces bias
  16. False
  17. test on many groups
  18. test on one group only
  19. check who is missing
  20. balanced data
  21. ask different people
  22. False
  23. adds to bias
  24. adds to bias
  25. ignore complaints
  26. False
  27. True
  28. False
  29. one-sided data
  30. True
  31. one-sided data
  32. balanced data
  33. one-sided data
  34. True
  35. test on many groups
  36. add varied examples
  37. True
  38. False
  39. its training data
  40. balanced data

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