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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 950 · 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.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) skip testing (d) add varied examples
  3. 3.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) copy old unfair choices (d) balance the data
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  5. 5.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) skip testing (d) add more of the same
  6. 6.Which of these helps reduce bias? (a) balance the data (b) copy old unfair choices (c) add more of the same (d) use one group only
  7. 7.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  8. 8.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  9. 9.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  10. 10.🖼️ 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
  11. 11.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  12. 12.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
  13. 13.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  14. 14.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) ignore complaints
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  16. 16.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  17. 17.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) ignore complaints (d) fix wrong labels
  18. 18.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  20. 20.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  22. 22.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  23. 23.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  24. 24.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  26. 26.True or false: “ask different people” adds to bias. (a) True (b) False
  27. 27.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  29. 29.True or false: “skip testing” helps reduce bias. (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  31. 31.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  32. 32.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) balance the data (d) test on one group only
  33. 33.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  34. 34.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  35. 35.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) copy old unfair choices (d) skip testing
  37. 37.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  38. 38.True or false: “ask different people” helps reduce bias. (a) False (b) True
  39. 39.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  40. 40.Which of these adds to bias? (a) balance the data (b) add varied examples (c) copy old unfair choices (d) fix wrong labels

Answer key

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

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