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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 861 · 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) skip testing (b) fix wrong labels (c) check who is missing (d) add varied examples
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  3. 3.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) add varied examples (d) test on one group only
  4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  5. 5.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  6. 6.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) use one group only
  7. 7.True or false: “skip testing” helps reduce bias. (a) True (b) False
  8. 8.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  10. 10.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) ignore complaints
  11. 11.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) skip testing (d) ignore complaints
  13. 13.Which of these adds to bias? (a) ask different people (b) skip testing (c) fix wrong labels (d) check who is missing
  14. 14.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
  15. 15.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  16. 16.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  17. 17.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) fix wrong labels (d) ask different people
  18. 18.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  20. 20.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  21. 21.True or false: “use one group only” helps reduce bias. (a) False (b) True
  22. 22.True or false: “use one group only” adds to bias. (a) False (b) True
  23. 23.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  24. 24.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  25. 25.🖼️ 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
  26. 26.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  27. 27.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  29. 29.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) add varied examples (d) test on one group only
  30. 30.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  31. 31.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) test on many groups (d) copy old unfair choices
  32. 32.🗣️ 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
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) check who is missing (d) add more of the same
  34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  35. 35.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  36. 36.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  37. 37.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  38. 38.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  39. 39.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) copy old unfair choices (d) balance the data
  40. 40.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data

Answer key

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

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