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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 783 · 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 more of the same (b) ignore complaints (c) use one group only (d) ask different people
  2. 2.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) skip testing (d) add varied examples
  3. 3.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) test on one group only (d) test on many groups
  4. 4.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  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.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  7. 7.True or false: “ask different people” helps reduce bias. (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  9. 9.Which of these adds to bias? (a) fix wrong labels (b) ignore complaints (c) add varied examples (d) check who is missing
  10. 10.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
  11. 11.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  12. 12.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) ask different people (d) skip testing
  13. 13.True or false: “ignore complaints” adds to bias. (a) False (b) True
  14. 14.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) ask different people (d) balance the data
  15. 15.True or false: “check who is missing” adds to bias. (a) True (b) False
  16. 16.Which of these helps reduce bias? (a) skip testing (b) fix wrong labels (c) ignore complaints (d) use one group only
  17. 17.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  19. 19.🖼️ 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
  20. 20.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  21. 21.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  22. 22.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  23. 23.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) check who is missing (d) add varied examples
  24. 24.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  25. 25.Which of these adds to bias? (a) balance the data (b) skip testing (c) check who is missing (d) ask different people
  26. 26.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  28. 28.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  29. 29.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  30. 30.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  31. 31.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) add more of the same (d) test on one group only
  32. 32.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  33. 33.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  34. 34.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  35. 35.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  36. 36.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) use one group only (d) test on one group only
  37. 37.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  38. 38.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  40. 40.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias

Answer key

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

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