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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 649 · 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) add varied examples (b) use one group only (c) fix wrong labels (d) check who is missing
  2. 2.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) balance the data (d) check who is missing
  3. 3.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
  4. 4.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  5. 5.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  6. 6.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  7. 7.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  8. 8.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) test on many groups (d) skip testing
  9. 9.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) add more of the same (d) test on many groups
  10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
  11. 11.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  12. 12.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  13. 13.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) test on one group only (d) balance the data
  14. 14.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  15. 15.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  16. 16.True or false: “balance the data” helps reduce bias. (a) False (b) True
  17. 17.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  18. 18.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) test on one group only (d) balance the data
  19. 19.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  20. 20.True or false: “test on one group only” adds to bias. (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  22. 22.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  23. 23.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  24. 24.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) copy old unfair choices (d) ignore complaints
  25. 25.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  26. 26.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  27. 27.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  28. 28.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) check who is missing (d) skip testing
  29. 29.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) ignore complaints
  30. 30.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) add varied examples
  31. 31.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  32. 32.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) check who is missing (d) ignore complaints
  33. 33.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) copy old unfair choices (d) add more of the same
  34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  35. 35.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  36. 36.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  38. 38.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  39. 39.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  40. 40.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) add more of the same (d) balance the data

Answer key

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

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