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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 444 · 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: “skip testing” helps reduce bias. (a) False (b) True
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
  4. 4.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  6. 6.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) ask different people (d) add varied examples
  7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  8. 8.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add varied examples (d) use one group only
  10. 10.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  11. 11.True or false: “ignore complaints” adds to bias. (a) True (b) False
  12. 12.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  13. 13.True or false: “add varied examples” adds to bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) use one group only
  15. 15.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  16. 16.True or false: “ask different people” helps reduce bias. (a) True (b) False
  17. 17.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  18. 18.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  20. 20.Which of these adds to bias? (a) ask different people (b) test on many groups (c) copy old unfair choices (d) add varied examples
  21. 21.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) check who is missing (d) add more of the same
  22. 22.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  23. 23.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) add more of the same (d) test on one group only
  24. 24.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  25. 25.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  26. 26.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  27. 27.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) use one group only (d) skip testing
  28. 28.🗣️ 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
  29. 29.True or false: “test on one group only” adds to bias. (a) True (b) False
  30. 30.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  32. 32.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  33. 33.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  34. 34.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  36. 36.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  38. 38.True or false: “test on many groups” adds to bias. (a) False (b) True
  39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  40. 40.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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