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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 91 · 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 of these adds to bias? (a) ignore complaints (b) balance the data (c) check who is missing (d) test on many groups
  2. 2.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
  5. 5.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  7. 7.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) ask different people (d) add varied examples
  8. 8.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) fix wrong labels (d) balance the data
  10. 10.🖼️ 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
  11. 11.True or false: “balance the data” adds to bias. (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) use one group only (d) skip testing
  13. 13.True or false: “add varied examples” adds to bias. (a) True (b) False
  14. 14.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) ignoring mistakes (d) fewer tests
  15. 15.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  17. 17.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) fix wrong labels (d) copy old unfair choices
  18. 18.True or false: “ask different people” adds to bias. (a) True (b) False
  19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  20. 20.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  21. 21.True or false: “test on many groups” adds to bias. (a) False (b) True
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  24. 24.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  25. 25.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  26. 26.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  28. 28.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) ignore complaints (d) test on one group only
  29. 29.Which of these adds to bias? (a) check who is missing (b) balance the data (c) add varied examples (d) test on one group only
  30. 30.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) test on many groups (d) copy old unfair choices
  31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) ask different people (d) balance the data
  32. 32.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  33. 33.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) use one group only (d) skip testing
  34. 34.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) ignore complaints (d) add varied examples
  35. 35.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  36. 36.Which of these helps reduce bias? (a) balance the data (b) skip testing (c) copy old unfair choices (d) use one group only
  37. 37.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  38. 38.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  40. 40.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias

Answer key

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

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