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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 596 · 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: “use one group only” adds to bias. (a) True (b) False
  2. 2.True or false: “check who is missing” adds to bias. (a) True (b) False
  3. 3.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  4. 4.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) check who is missing (d) add varied examples
  5. 5.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  6. 6.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) check who is missing (d) add varied examples
  8. 8.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  9. 9.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  10. 10.🔍 Which is the odd one out? (a) test on many groups (b) skip testing (c) add varied examples (d) fix wrong labels
  11. 11.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  13. 13.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  14. 14.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  15. 15.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  16. 16.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  17. 17.🖼️ 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
  18. 18.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  19. 19.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  20. 20.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  24. 24.Which of these adds to bias? (a) test on many groups (b) skip testing (c) balance the data (d) add varied examples
  25. 25.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) add varied examples (d) add more of the same
  26. 26.Which of these adds to bias? (a) balance the data (b) ask different people (c) add more of the same (d) test on many groups
  27. 27.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) add more of the same (d) check who is missing
  28. 28.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  30. 30.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  31. 31.True or false: “ask different people” helps reduce bias. (a) False (b) True
  32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  33. 33.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  34. 34.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  35. 35.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  36. 36.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
  37. 37.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
  38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  40. 40.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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