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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 50 · 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.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  2. 2.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  3. 3.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  4. 4.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  5. 5.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  6. 6.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
  7. 7.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  8. 8.🔍 Which is the odd one out? (a) skip testing (b) fix wrong labels (c) copy old unfair choices (d) test on one group only
  9. 9.True or false: “skip testing” adds to bias. (a) False (b) True
  10. 10.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  11. 11.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) check who is missing (d) use one group only
  12. 12.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) test on one group only (d) balance the data
  13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  14. 14.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  15. 15.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) copy old unfair choices (d) check who is missing
  16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  17. 17.Which of these adds to bias? (a) ask different people (b) balance the data (c) check who is missing (d) skip testing
  18. 18.True or false: “ask different people” adds to bias. (a) True (b) False
  19. 19.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  21. 21.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  22. 22.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  26. 26.Which of these helps reduce bias? (a) balance the data (b) add more of the same (c) copy old unfair choices (d) use one group only
  27. 27.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) test on many groups (d) test on one group only
  28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  29. 29.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
  30. 30.True or false: “use one group only” helps reduce bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  32. 32.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.True or false: “test on one group only” adds to bias. (a) False (b) True
  34. 34.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) copy old unfair choices (d) balance the data
  35. 35.True or false: “test on many groups” adds to bias. (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  37. 37.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  38. 38.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  39. 39.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) copy old unfair choices
  40. 40.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True

Answer key

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

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