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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 401 · 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: check who is missing? (a) adds to bias (b) reduces bias
  2. 2.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) use one group only (d) fix wrong labels
  3. 3.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) add more of the same (d) check who is missing
  4. 4.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  6. 6.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  7. 7.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  8. 8.True or false: “balance the data” adds to bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  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.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) copy old unfair choices (d) add varied examples
  12. 12.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  13. 13.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) add varied examples
  14. 14.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  15. 15.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  16. 16.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
  17. 17.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) balance the data (d) use one group only
  18. 18.True or false: “use one group only” adds to bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  20. 20.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
  21. 21.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  22. 22.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) add varied examples (d) add more of the same
  23. 23.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  24. 24.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  25. 25.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  26. 26.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
  28. 28.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  29. 29.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) ignore complaints (d) check who is missing
  30. 30.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  32. 32.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) ignore complaints (d) use one group only
  33. 33.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  34. 34.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) ask different people (d) fix wrong labels
  35. 35.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  36. 36.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  37. 37.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  38. 38.True or false: “ask different people” adds to bias. (a) True (b) False
  39. 39.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  40. 40.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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