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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 639 · 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: “ask different people” adds to bias. (a) False (b) True
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
  5. 5.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  7. 7.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) balance the data
  8. 8.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  9. 9.True or false: “skip testing” helps reduce bias. (a) False (b) True
  10. 10.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  11. 11.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  12. 12.🗣️ 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
  13. 13.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  14. 14.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) add more of the same (d) ignore complaints
  15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  16. 16.True or false: “skip testing” adds to bias. (a) True (b) False
  17. 17.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  18. 18.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  19. 19.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ignore complaints (d) test on one group only
  20. 20.Which of these adds to bias? (a) add varied examples (b) use one group only (c) fix wrong labels (d) test on many groups
  21. 21.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) ask different people (d) copy old unfair choices
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  24. 24.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) balance the data (d) use one group only
  26. 26.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) use one group only (d) test on many groups
  27. 27.True or false: “test on many groups” adds to bias. (a) True (b) False
  28. 28.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  29. 29.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
  30. 30.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  31. 31.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.True or false: “balance the data” adds to bias. (a) False (b) True
  33. 33.Which of these helps reduce bias? (a) fix wrong labels (b) copy old unfair choices (c) test on one group only (d) add more of the same
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  35. 35.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  37. 37.True or false: “use one group only” helps reduce bias. (a) False (b) True
  38. 38.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  39. 39.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) add more of the same (d) check who is missing
  40. 40.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) balance the data (d) ignore complaints

Answer key

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

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