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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 409 · 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.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  2. 2.True or false: “use one group only” helps reduce bias. (a) True (b) False
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  4. 4.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  5. 5.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  6. 6.Which of these adds to bias? (a) balance the data (b) add varied examples (c) skip testing (d) fix wrong labels
  7. 7.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  9. 9.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) balance the data (d) copy old unfair choices
  10. 10.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) test on many groups (d) add varied examples
  11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  12. 12.True or false: “test on one group only” adds to bias. (a) False (b) True
  13. 13.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  14. 14.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  15. 15.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) add varied examples (d) use one group only
  16. 16.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  19. 19.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  20. 20.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  21. 21.True or false: “ask different people” helps reduce bias. (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  23. 23.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  24. 24.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  26. 26.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
  30. 30.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) copy old unfair choices (d) test on one group only
  31. 31.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  32. 32.Which of these adds to bias? (a) balance the data (b) add varied examples (c) check who is missing (d) ignore complaints
  33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  34. 34.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) ignore complaints
  35. 35.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  37. 37.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) use one group only (d) add varied examples
  38. 38.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  39. 39.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) use one group only (d) test on many groups
  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. adds to bias
  2. False
  3. its training data
  4. balanced data
  5. adds to bias
  6. skip testing
  7. balanced data
  8. reduces bias
  9. balance the data
  10. add more of the same
  11. reduces bias
  12. True
  13. True
  14. one-sided data
  15. add varied examples
  16. False
  17. False
  18. True
  19. False
  20. one-sided data
  21. True
  22. balanced data
  23. True
  24. True
  25. reduces bias
  26. False
  27. adds to bias
  28. adds to bias
  29. few child voices in data
  30. ask different people
  31. adds to bias
  32. ignore complaints
  33. reduces bias
  34. ignore complaints
  35. one-sided data
  36. balanced data
  37. use one group only
  38. reduces bias
  39. test on many groups
  40. one-sided data

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