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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 345 · 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: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  3. 3.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  4. 4.True or false: “ask different people” helps reduce bias. (a) False (b) True
  5. 5.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
  6. 6.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  9. 9.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  10. 10.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ignore complaints (d) balance the data
  11. 11.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  12. 12.True or false: “balance the data” helps reduce bias. (a) False (b) True
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  15. 15.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
  16. 16.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  18. 18.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) test on many groups (d) skip testing
  19. 19.True or false: “check who is missing” adds to bias. (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  21. 21.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) balance the data (d) use one group only
  22. 22.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  23. 23.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  24. 24.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  26. 26.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  27. 27.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) check who is missing (d) test on one group only
  28. 28.Which of these adds to bias? (a) fix wrong labels (b) copy old unfair choices (c) add varied examples (d) ask different people
  29. 29.True or false: “skip testing” helps reduce bias. (a) False (b) True
  30. 30.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  31. 31.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  32. 32.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) fix wrong labels (d) ignore complaints
  33. 33.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  34. 34.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
  35. 35.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  36. 36.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  37. 37.True or false: “add varied examples” adds to bias. (a) False (b) True
  38. 38.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  40. 40.True or false: “balance the data” adds to bias. (a) True (b) False

Answer key

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

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