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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 688 · 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) add varied examples (b) balance the data (c) add more of the same (d) ask different people
  2. 2.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) copy old unfair choices (d) use one group only
  3. 3.Which of these adds to bias? (a) fix wrong labels (b) copy old unfair choices (c) add varied examples (d) ask different people
  4. 4.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  5. 5.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  6. 6.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  7. 7.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  9. 9.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  10. 10.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  11. 11.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  12. 12.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  13. 13.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  14. 14.True or false: “add varied examples” adds to bias. (a) False (b) True
  15. 15.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  16. 16.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  17. 17.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) copy old unfair choices (d) ignore complaints
  18. 18.True or false: “ignore complaints” adds to bias. (a) False (b) True
  19. 19.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) balance the data (d) ignore complaints
  20. 20.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  22. 22.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) add varied examples (d) skip testing
  23. 23.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
  24. 24.🔍 Which is the odd one out? (a) skip testing (b) fix wrong labels (c) add varied examples (d) ask different people
  25. 25.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  26. 26.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  27. 27.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  29. 29.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
  30. 30.True or false: “balance the data” adds to bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  32. 32.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  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.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) add varied examples (d) copy old unfair choices
  36. 36.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
  37. 37.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  39. 39.True or false: “ask different people” adds to bias. (a) False (b) True
  40. 40.True or false: “check who is missing” helps reduce bias. (a) True (b) False

Answer key

  1. add more of the same
  2. test on many groups
  3. copy old unfair choices
  4. adds to bias
  5. adds to bias
  6. True
  7. reduces bias
  8. reduces bias
  9. reduces bias
  10. False
  11. True
  12. False
  13. True
  14. False
  15. one-sided data
  16. balanced data
  17. fix wrong labels
  18. True
  19. balance the data
  20. True
  21. reduces bias
  22. add varied examples
  23. its training data
  24. skip testing
  25. False
  26. True
  27. test on many groups
  28. balanced data
  29. bias from data
  30. False
  31. reduces bias
  32. one-sided data
  33. True
  34. True
  35. copy old unfair choices
  36. more varied data
  37. one-sided data
  38. one-sided data
  39. False
  40. True

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