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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 781 · 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: neat and messy writing from many people? (a) balanced data (b) one-sided data
  2. 2.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  3. 3.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  4. 4.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  5. 5.Which of these helps reduce bias? (a) add more of the same (b) add varied examples (c) use one group only (d) test on one group only
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) ask different people (c) copy old unfair choices (d) ignore complaints
  7. 7.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  8. 8.True or false: “ask different people” adds to bias. (a) True (b) False
  9. 9.Which of these adds to bias? (a) skip testing (b) test on many groups (c) add varied examples (d) ask different people
  10. 10.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
  11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  12. 12.True or false: “ignore complaints” adds to bias. (a) True (b) False
  13. 13.True or false: “test on many groups” adds to bias. (a) True (b) False
  14. 14.True or false: “skip testing” adds to bias. (a) False (b) True
  15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  18. 18.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  19. 19.True or false: “test on one group only” adds to bias. (a) True (b) False
  20. 20.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  21. 21.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  23. 23.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  25. 25.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
  26. 26.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  27. 27.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) fix wrong labels (d) check who is missing
  28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  29. 29.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  30. 30.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  31. 31.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  32. 32.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  33. 33.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) add more of the same (d) test on one group only
  34. 34.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  35. 35.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) check who is missing (d) add varied examples
  36. 36.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  37. 37.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  38. 38.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  40. 40.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False

Answer key

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

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