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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 106 · 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 of these adds to bias? (a) ignore complaints (b) ask different people (c) test on many groups (d) balance the data
  2. 2.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) ignore complaints (d) check who is missing
  3. 3.True or false: “balance the data” helps reduce bias. (a) False (b) True
  4. 4.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  5. 5.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  6. 6.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  7. 7.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  9. 9.True or false: “use one group only” helps reduce bias. (a) False (b) True
  10. 10.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
  11. 11.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) check who is missing (d) skip testing
  13. 13.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  14. 14.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  15. 15.True or false: “balance the data” adds to bias. (a) True (b) False
  16. 16.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) add varied examples (d) check who is missing
  17. 17.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  18. 18.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
  19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  20. 20.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) fix wrong labels (d) test on one group only
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  24. 24.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  25. 25.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) copy old unfair choices (d) check who is missing
  27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  28. 28.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  29. 29.Which of these adds to bias? (a) skip testing (b) add varied examples (c) ask different people (d) test on many groups
  30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) test on one group only (d) test on many groups
  31. 31.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  32. 32.True or false: “check who is missing” adds to bias. (a) False (b) True
  33. 33.True or false: “test on many groups” adds to bias. (a) False (b) True
  34. 34.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  35. 35.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  36. 36.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  37. 37.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) add more of the same (d) fix wrong labels
  38. 38.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  39. 39.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  40. 40.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) ask different people (d) use one group only

Answer key

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

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