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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 118 · 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 of these adds to bias? (a) ignore complaints (b) fix wrong labels (c) add varied examples (d) balance the data
  2. 2.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  3. 3.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  4. 4.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  5. 5.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) use one group only (d) test on many groups
  6. 6.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) use one group only (d) copy old unfair choices
  7. 7.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add more of the same (d) test on many groups
  8. 8.True or false: “ignore complaints” adds to bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  10. 10.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) few child voices in data (d) the phone was new
  12. 12.Which of these helps reduce bias? (a) ignore complaints (b) add varied examples (c) test on one group only (d) add more of the same
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  15. 15.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
  16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  18. 18.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  19. 19.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  20. 20.Which of these adds to bias? (a) balance the data (b) ask different people (c) skip testing (d) check who is missing
  21. 21.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  22. 22.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) add varied examples (d) copy old unfair choices
  23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  24. 24.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  25. 25.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) use one group only (d) balance the data
  26. 26.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  28. 28.True or false: “check who is missing” adds to bias. (a) False (b) True
  29. 29.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) test on many groups
  30. 30.🔍 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
  31. 31.True or false: “test on many groups” adds to bias. (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  33. 33.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  34. 34.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  35. 35.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  36. 36.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  37. 37.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  38. 38.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
  39. 39.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  40. 40.True or false: “balance the data” helps reduce bias. (a) False (b) True

Answer key

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

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