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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 252 · 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: balance the data? (a) adds to bias (b) reduces bias
  2. 2.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) ask different people (d) test on many groups
  3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  4. 4.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a strong battery (d) a fair model
  6. 6.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) test on many groups (d) copy old unfair choices
  7. 7.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) test on many groups (d) copy old unfair choices
  8. 8.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) ignore complaints (d) check who is missing
  9. 9.True or false: “test on many groups” adds to bias. (a) False (b) True
  10. 10.True or false: “skip testing” helps reduce bias. (a) False (b) True
  11. 11.True or false: “add varied examples” adds to bias. (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) skip testing (d) test on many groups
  13. 13.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) add varied examples (d) use one group only
  14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  15. 15.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  16. 16.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  20. 20.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  21. 21.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  23. 23.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  24. 24.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) add more of the same (d) balance the data
  26. 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  27. 27.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  29. 29.True or false: “balance the data” adds to bias. (a) False (b) True
  30. 30.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  33. 33.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) ask different people (d) add more of the same
  34. 34.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  35. 35.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  37. 37.True or false: “use one group only” helps reduce bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  39. 39.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  40. 40.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests

Answer key

  1. reduces bias
  2. test on one group only
  3. one-sided data
  4. adds to bias
  5. bias from data
  6. copy old unfair choices
  7. copy old unfair choices
  8. ignore complaints
  9. False
  10. False
  11. False
  12. skip testing
  13. add varied examples
  14. reduces bias
  15. adds to bias
  16. balanced data
  17. adds to bias
  18. one-sided data
  19. reduces bias
  20. test on many groups
  21. reduces bias
  22. balanced data
  23. True
  24. False
  25. balance the data
  26. adds to bias
  27. balanced data
  28. one-sided data
  29. False
  30. True
  31. True
  32. balanced data
  33. add more of the same
  34. adds to bias
  35. True
  36. its training data
  37. False
  38. one-sided data
  39. reduces bias
  40. more varied data

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