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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 914 · 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.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  3. 3.Which of these adds to bias? (a) fix wrong labels (b) add more of the same (c) ask different people (d) check who is missing
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
  5. 5.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  8. 8.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  9. 9.Which of these adds to bias? (a) add varied examples (b) copy old unfair choices (c) fix wrong labels (d) ask different people
  10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  11. 11.True or false: “test on one group only” adds to bias. (a) True (b) False
  12. 12.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) skip testing (d) ignore complaints
  13. 13.Which of these adds to bias? (a) balance the data (b) test on many groups (c) use one group only (d) fix wrong labels
  14. 14.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) use one group only (d) add varied examples
  16. 16.Which of these adds to bias? (a) test on many groups (b) ask different people (c) skip testing (d) balance the data
  17. 17.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  18. 18.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  20. 20.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) test on one group only (d) add more of the same
  21. 21.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) add more of the same (d) add varied examples
  22. 22.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
  23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) balance the data (d) add more of the same
  24. 24.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  25. 25.🔍 Which is the odd one out? (a) add varied examples (b) use one group only (c) fix wrong labels (d) balance the data
  26. 26.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  27. 27.Which of these helps reduce bias? (a) ask different people (b) test on one group only (c) ignore complaints (d) skip testing
  28. 28.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
  29. 29.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  30. 30.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) test on many groups (d) ignore complaints
  31. 31.True or false: “skip testing” adds to bias. (a) False (b) True
  32. 32.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  34. 34.Which of these helps reduce bias? (a) fix wrong labels (b) ignore complaints (c) use one group only (d) test on one group only
  35. 35.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) test on one group only (d) ask different people
  36. 36.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  37. 37.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  38. 38.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

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

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