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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 745 · 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.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) test on many groups (d) ask different people
  2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  3. 3.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  4. 4.True or false: “check who is missing” adds to bias. (a) False (b) True
  5. 5.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  6. 6.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
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  8. 8.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) ask different people
  9. 9.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  10. 10.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  11. 11.Which of these helps reduce bias? (a) fix wrong labels (b) copy old unfair choices (c) test on one group only (d) skip testing
  12. 12.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) ignore complaints (d) skip testing
  14. 14.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  16. 16.Which of these helps reduce bias? (a) ask different people (b) ignore complaints (c) add more of the same (d) use one group only
  17. 17.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) fix wrong labels (d) skip testing
  18. 18.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  19. 19.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  20. 20.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) check who is missing (d) ask different people
  21. 21.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) balance the data (d) ask different people
  22. 22.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) use one group only (d) fix wrong labels
  24. 24.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) test on one group only (d) copy old unfair choices
  25. 25.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  26. 26.True or false: “ask different people” adds to bias. (a) True (b) False
  27. 27.True or false: “use one group only” adds to bias. (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  30. 30.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  31. 31.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  32. 32.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  33. 33.True or false: “skip testing” adds to bias. (a) True (b) False
  34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  35. 35.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  36. 36.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  37. 37.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  38. 38.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  39. 39.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  40. 40.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data

Answer key

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

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