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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 122 · 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) check who is missing (b) ask different people (c) copy old unfair choices (d) test on many groups
  2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) check who is missing (d) ignore complaints
  3. 3.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  5. 5.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  6. 6.🖼️ 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
  7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  8. 8.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  9. 9.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  11. 11.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) fix wrong labels (d) ignore complaints
  13. 13.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  14. 14.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) use one group only (d) test on many groups
  15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  16. 16.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  17. 17.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  18. 18.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  20. 20.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  21. 21.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) skip testing (d) test on many groups
  22. 22.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  23. 23.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) use one group only (d) add varied examples
  24. 24.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  25. 25.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) add more of the same (d) balance the data
  26. 26.Which of these adds to bias? (a) add varied examples (b) balance the data (c) use one group only (d) check who is missing
  27. 27.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) balance the data (d) use one group only
  28. 28.True or false: “use one group only” helps reduce bias. (a) True (b) False
  29. 29.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) test on many groups (d) fix wrong labels
  30. 30.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) it was a rainy day (d) children speak too fast
  31. 31.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  32. 32.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) check who is missing
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  34. 34.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  35. 35.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  37. 37.True or false: “test on many groups” adds to bias. (a) True (b) False
  38. 38.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: “ignore complaints” adds to bias. (a) False (b) True
  40. 40.True or false: “add varied examples” adds to bias. (a) False (b) True

Answer key

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

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