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AI Bias Worksheet for Kids

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

Answer key

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

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