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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 388 · 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 is the odd one out? (a) skip testing (b) add varied examples (c) use one group only (d) copy old unfair choices
  2. 2.True or false: “test on many groups” adds to bias. (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  4. 4.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) use one group only (d) ignore complaints
  5. 5.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  6. 6.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  7. 7.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  8. 8.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) test on one group only (d) ask different people
  10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
  11. 11.🗣️ 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) children speak too fast (d) the phone was new
  12. 12.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  13. 13.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) test on one group only (d) add varied examples
  15. 15.Which of these helps reduce bias? (a) use one group only (b) fix wrong labels (c) copy old unfair choices (d) add more of the same
  16. 16.True or false: “add varied examples” adds to bias. (a) False (b) True
  17. 17.Which of these adds to bias? (a) ask different people (b) add more of the same (c) check who is missing (d) fix wrong labels
  18. 18.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  19. 19.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  20. 20.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  22. 22.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  23. 23.True or false: “ask different people” adds to bias. (a) True (b) False
  24. 24.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  25. 25.True or false: “balance the data” adds to bias. (a) False (b) True
  26. 26.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
  27. 27.Which of these helps reduce bias? (a) add varied examples (b) test on one group only (c) ignore complaints (d) copy old unfair choices
  28. 28.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) check who is missing (d) use one group only
  29. 29.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  30. 30.True or false: “test on one group only” adds to bias. (a) True (b) False
  31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) use one group only (d) ignore complaints
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  33. 33.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  34. 34.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add varied examples (d) skip testing
  35. 35.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
  36. 36.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  37. 37.True or false: “add more of the same” adds to bias. (a) False (b) True
  38. 38.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  39. 39.True or false: “ignore complaints” adds to bias. (a) False (b) True
  40. 40.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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