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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 304 · 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: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
  3. 3.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) skip testing (d) use one group only
  4. 4.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  5. 5.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add more of the same (d) balance the data
  6. 6.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  7. 7.True or false: “ignore complaints” adds to bias. (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  9. 9.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  10. 10.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) test on one group only
  11. 11.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  12. 12.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) use one group only (d) ignore complaints
  13. 13.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  14. 14.True or false: “check who is missing” adds to bias. (a) True (b) False
  15. 15.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  16. 16.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  17. 17.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) test on one group only (d) use one group only
  18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  20. 20.Which of these adds to bias? (a) add varied examples (b) balance the data (c) skip testing (d) check who is missing
  21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  22. 22.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
  23. 23.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  24. 24.🔍 Which is the odd one out? (a) copy old unfair choices (b) fix wrong labels (c) skip testing (d) ignore complaints
  25. 25.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  26. 26.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  28. 28.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) test on one group only (d) skip testing
  29. 29.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  30. 30.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  31. 31.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  33. 33.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) ask different people (d) test on one group only
  34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  35. 35.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  37. 37.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  38. 38.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  39. 39.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: “ask different people” adds to bias. (a) True (b) False

Answer key

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

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