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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 771 · 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) test on one group only (b) add more of the same (c) balance the data (d) ignore complaints
  2. 2.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) skip testing (d) test on many groups
  3. 3.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) skip testing (d) add varied examples
  5. 5.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  6. 6.True or false: “add varied examples” adds to bias. (a) True (b) False
  7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  8. 8.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  10. 10.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  12. 12.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  13. 13.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) add more of the same (d) test on one group only
  14. 14.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  15. 15.Which of these adds to bias? (a) ask different people (b) balance the data (c) skip testing (d) test on many groups
  16. 16.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) fix wrong labels (d) use one group only
  17. 17.🗣️ 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
  18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  19. 19.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  20. 20.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  21. 21.True or false: “ask different people” adds to bias. (a) True (b) False
  22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  23. 23.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  24. 24.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  25. 25.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) add varied examples (d) test on one group only
  26. 26.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  27. 27.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) ask different people (d) add varied examples
  28. 28.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  29. 29.Which of these adds to bias? (a) add varied examples (b) ignore complaints (c) test on many groups (d) fix wrong labels
  30. 30.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add more of the same (d) fix wrong labels
  31. 31.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) fix wrong labels (d) test on one group only
  32. 32.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  33. 33.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  34. 34.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  35. 35.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  36. 36.True or false: “use one group only” helps reduce bias. (a) False (b) True
  37. 37.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) check who is missing (d) ask different people
  38. 38.True or false: “balance the data” adds to bias. (a) True (b) False
  39. 39.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  40. 40.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) ask different people (d) use one group only

Answer key

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

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