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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 812 · 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: “add varied examples” adds to bias. (a) True (b) False
  2. 2.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  3. 3.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  4. 4.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  5. 5.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  6. 6.True or false: “test on one group only” adds to bias. (a) True (b) False
  7. 7.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
  8. 8.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) check who is missing (d) copy old unfair choices
  9. 9.Which of these adds to bias? (a) add varied examples (b) ask different people (c) use one group only (d) fix wrong labels
  10. 10.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  12. 12.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
  13. 13.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  14. 14.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) skip testing (d) copy old unfair choices
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  16. 16.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  17. 17.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) fix wrong labels (d) test on many groups
  18. 18.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) check who is missing (d) use one group only
  19. 19.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  21. 21.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  23. 23.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  24. 24.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) fix wrong labels (d) test on many groups
  26. 26.True or false: “ask different people” adds to bias. (a) True (b) False
  27. 27.True or false: “skip testing” helps reduce bias. (a) True (b) False
  28. 28.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  29. 29.Which of these adds to bias? (a) copy old unfair choices (b) test on many groups (c) ask different people (d) add varied examples
  30. 30.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  31. 31.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  32. 32.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  34. 34.True or false: “use one group only” helps reduce bias. (a) True (b) False
  35. 35.True or false: “ignore complaints” adds to bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  37. 37.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) test on many groups (d) ask different people
  38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) balance the data (d) skip testing
  39. 39.Which of these adds to bias? (a) skip testing (b) balance the data (c) check who is missing (d) fix wrong labels
  40. 40.True or false: “test on many groups” helps reduce bias. (a) False (b) True

Answer key

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

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