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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 498 · 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 is the odd one out? (a) ask different people (b) balance the data (c) copy old unfair choices (d) add varied examples
  2. 2.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) use one group only (d) ask different people
  3. 3.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  4. 4.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  5. 5.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) skip testing (d) check who is missing
  7. 7.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  9. 9.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) add more of the same (d) add varied examples
  10. 10.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) skip testing (d) add varied examples
  12. 12.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) ask different people (d) ignore complaints
  13. 13.True or false: “ask different people” adds to bias. (a) False (b) True
  14. 14.True or false: “balance the data” helps reduce bias. (a) False (b) True
  15. 15.True or false: “add more of the same” adds to bias. (a) False (b) True
  16. 16.Which of these helps reduce bias? (a) skip testing (b) fix wrong labels (c) copy old unfair choices (d) add more of the same
  17. 17.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  18. 18.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  19. 19.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  20. 20.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  21. 21.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  22. 22.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) balance the data (d) add varied examples
  23. 23.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
  24. 24.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) copy old unfair choices (d) test on many groups
  26. 26.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  27. 27.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  28. 28.Which of these adds to bias? (a) test on many groups (b) ignore complaints (c) balance the data (d) check who is missing
  29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  30. 30.True or false: “check who is missing” adds to bias. (a) False (b) True
  31. 31.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  33. 33.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  34. 34.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  35. 35.True or false: “add varied examples” adds to bias. (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  37. 37.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) check who is missing (d) skip testing
  38. 38.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  39. 39.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  40. 40.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

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

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