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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 207 · 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.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) skip testing (d) add varied examples
  2. 2.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
  3. 3.True or false: “balance the data” adds to bias. (a) True (b) False
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  6. 6.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  8. 8.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) skip testing (d) test on many groups
  9. 9.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) fix wrong labels (d) ignore complaints
  10. 10.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) fix wrong labels (d) add more of the same
  11. 11.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  12. 12.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  13. 13.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  14. 14.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  15. 15.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  16. 16.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) copy old unfair choices (d) ignore complaints
  17. 17.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  18. 18.Which of these adds to bias? (a) test on many groups (b) use one group only (c) fix wrong labels (d) balance the data
  19. 19.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
  20. 20.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: “skip testing” adds to bias. (a) False (b) True
  22. 22.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  23. 23.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  24. 24.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) fix wrong labels (d) skip testing
  25. 25.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) balance the data (d) add varied examples
  26. 26.True or false: “test on many groups” adds to bias. (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  28. 28.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
  29. 29.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  30. 30.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  31. 31.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  32. 32.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  33. 33.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) check who is missing (d) skip testing
  34. 34.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) ignore complaints (d) add more of the same
  36. 36.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) add more of the same (d) add varied examples
  37. 37.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  38. 38.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  39. 39.True or false: “use one group only” helps reduce bias. (a) True (b) False
  40. 40.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data

Answer key

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

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