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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 919 · 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: test on one group only? (a) reduces bias (b) adds to bias
  2. 2.True or false: “ask different people” helps reduce bias. (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  4. 4.Which of these adds to bias? (a) use one group only (b) balance the data (c) ask different people (d) fix wrong labels
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) bias from data (d) a strong battery
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) add varied examples (d) ignore complaints
  7. 7.True or false: “balance the data” adds to bias. (a) False (b) True
  8. 8.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) balance the data
  9. 9.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  10. 10.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  11. 11.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) fix wrong labels (d) check who is missing
  12. 12.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  13. 13.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  14. 14.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  15. 15.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  16. 16.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) balance the data (d) add varied examples
  17. 17.True or false: “skip testing” helps reduce bias. (a) True (b) False
  18. 18.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) fix wrong labels (d) ignore complaints
  19. 19.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  20. 20.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  21. 21.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) test on many groups (d) skip testing
  22. 22.🔍 Which is the odd one out? (a) ask different people (b) use one group only (c) add more of the same (d) test on one group only
  23. 23.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  24. 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  25. 25.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  26. 26.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  28. 28.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  29. 29.True or false: “add more of the same” adds to bias. (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  31. 31.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  32. 32.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  33. 33.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  36. 36.True or false: “test on many groups” adds to bias. (a) False (b) True
  37. 37.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (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.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  40. 40.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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