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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 386 · 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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  2. 2.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) ask different people (d) copy old unfair choices
  3. 3.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) skip testing (d) ask different people
  4. 4.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) ignore complaints (d) copy old unfair choices
  5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  7. 7.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  8. 8.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ask different people (d) test on many groups
  9. 9.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  11. 11.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  12. 12.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  13. 13.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) balance the data (d) add varied examples
  14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  16. 16.True or false: “skip testing” adds to bias. (a) True (b) False
  17. 17.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.Which of these helps reduce bias? (a) skip testing (b) balance the data (c) add more of the same (d) copy old unfair choices
  19. 19.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
  20. 20.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  22. 22.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) skip testing (d) copy old unfair choices
  23. 23.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  24. 24.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  26. 26.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  28. 28.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
  29. 29.🔍 Which is the odd one out? (a) copy old unfair choices (b) fix wrong labels (c) ask different people (d) balance the data
  30. 30.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) fix wrong labels (d) add more of the same
  31. 31.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) copy old unfair choices (d) ask different people
  32. 32.True or false: “skip testing” helps reduce bias. (a) False (b) True
  33. 33.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) ignore complaints (d) ask different people
  34. 34.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  36. 36.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) test on many groups (d) ask different people
  37. 37.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) add varied examples (d) test on one group only
  38. 38.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) test on many groups
  39. 39.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) skip testing (d) check who is missing
  40. 40.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) fix wrong labels (d) use one group only

Answer key

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

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