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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 495 · 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: add more of the same? (a) adds to bias (b) reduces bias
  2. 2.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) skip testing (d) test on one group only
  3. 3.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  4. 4.Which of these helps reduce bias? (a) check who is missing (b) use one group only (c) ignore complaints (d) add more of the same
  5. 5.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  6. 6.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) use one group only (d) test on one group only
  8. 8.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  9. 9.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  10. 10.True or false: “skip testing” adds to bias. (a) False (b) True
  11. 11.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  12. 12.🗣️ 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
  13. 13.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  14. 14.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  15. 15.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
  16. 16.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
  17. 17.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) check who is missing (d) skip testing
  19. 19.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) test on one group only (d) add varied examples
  20. 20.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
  21. 21.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  22. 22.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  23. 23.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  24. 24.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  25. 25.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  26. 26.True or false: “test on one group only” adds to bias. (a) True (b) False
  27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  28. 28.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) use one group only (d) ignore complaints
  29. 29.True or false: “ask different people” adds to bias. (a) True (b) False
  30. 30.True or false: “balance the data” adds to bias. (a) True (b) False
  31. 31.Which of these adds to bias? (a) ask different people (b) use one group only (c) add varied examples (d) check who is missing
  32. 32.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) balance the data (d) test on many groups
  33. 33.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) ignore complaints (d) add more of the same
  34. 34.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  36. 36.True or false: “check who is missing” adds to bias. (a) True (b) False
  37. 37.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  38. 38.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  39. 39.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  40. 40.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data

Answer key

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

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