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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 489 · 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) ignore complaints (b) copy old unfair choices (c) fix wrong labels (d) use one group only
  2. 2.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) skip testing (d) test on many groups
  3. 3.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  4. 4.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  6. 6.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) test on many groups (d) balance the data
  7. 7.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  8. 8.True or false: “add varied examples” adds to bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  10. 10.True or false: “use one group only” adds to bias. (a) True (b) False
  11. 11.Which of these adds to bias? (a) test on many groups (b) ask different people (c) add varied examples (d) use one group only
  12. 12.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  13. 13.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  14. 14.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  15. 15.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) skip testing (d) check who is missing
  16. 16.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  17. 17.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) skip testing (d) add more of the same
  18. 18.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) test on many groups (d) fix wrong labels
  19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  20. 20.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) balance the data (d) use one group only
  21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  23. 23.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) skip testing (d) balance the data
  24. 24.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) balance the data (d) copy old unfair choices
  25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  26. 26.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) use one group only (d) add varied examples
  27. 27.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) skip testing (d) copy old unfair choices
  29. 29.True or false: “ask different people” adds to bias. (a) True (b) False
  30. 30.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  31. 31.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  32. 32.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  34. 34.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  35. 35.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  36. 36.Which of these adds to bias? (a) ask different people (b) balance the data (c) add varied examples (d) ignore complaints
  37. 37.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) ask different people (d) ignore complaints
  38. 38.True or false: “add more of the same” adds to bias. (a) False (b) True
  39. 39.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) check who is missing (d) balance the data
  40. 40.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather

Answer key

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

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