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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 846 · 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 handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  2. 2.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  3. 3.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) fix wrong labels (d) test on one group only
  4. 4.True or false: “skip testing” helps reduce bias. (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  6. 6.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) add more of the same (d) add varied examples
  8. 8.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  9. 9.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  10. 10.Which of these adds to bias? (a) add varied examples (b) ask different people (c) test on many groups (d) skip testing
  11. 11.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  12. 12.Which of these adds to bias? (a) use one group only (b) add varied examples (c) ask different people (d) test on many groups
  13. 13.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  16. 16.True or false: “ask different people” adds to bias. (a) False (b) True
  17. 17.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  20. 20.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  21. 21.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  22. 22.True or false: “ask different people” helps reduce bias. (a) False (b) True
  23. 23.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) add more of the same (d) test on one group only
  24. 24.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) add more of the same (d) fix wrong labels
  25. 25.True or false: “add varied examples” adds to bias. (a) False (b) True
  26. 26.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
  27. 27.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  28. 28.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  29. 29.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) balance the data (d) fix wrong labels
  30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) add more of the same (d) balance the data
  31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  32. 32.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  33. 33.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  34. 34.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  35. 35.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
  36. 36.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  37. 37.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  38. 38.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  39. 39.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  40. 40.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) skip testing (d) use one group only

Answer key

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

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