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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 254 · 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: “copy old unfair choices” adds to bias. (a) False (b) True
  2. 2.Which of these adds to bias? (a) test on many groups (b) ask different people (c) check who is missing (d) skip testing
  3. 3.Which of these adds to bias? (a) ignore complaints (b) ask different people (c) check who is missing (d) balance the data
  4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  5. 5.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  6. 6.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  8. 8.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  9. 9.Which of these adds to bias? (a) balance the data (b) use one group only (c) ask different people (d) fix wrong labels
  10. 10.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) ignore complaints (d) use one group only
  11. 11.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) copy old unfair choices (d) test on one group only
  12. 12.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  13. 13.True or false: “balance the data” adds to bias. (a) False (b) True
  14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  15. 15.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  16. 16.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) fix wrong labels (d) use one group only
  17. 17.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  19. 19.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  20. 20.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  21. 21.🖼️ 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
  22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  24. 24.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  25. 25.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  26. 26.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  29. 29.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) balance the data (d) test on one group only
  30. 30.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  31. 31.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) test on one group only (d) add more of the same
  32. 32.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  33. 33.True or false: “use one group only” helps reduce bias. (a) True (b) False
  34. 34.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) ignore complaints (d) test on many groups
  35. 35.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) copy old unfair choices (d) add more of the same
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
  37. 37.Which of these helps reduce bias? (a) check who is missing (b) add more of the same (c) skip testing (d) use one group only
  38. 38.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  40. 40.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data

Answer key

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

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