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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 505 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  3. 3.Which of these helps reduce bias? (a) balance the data (b) add more of the same (c) skip testing (d) ignore complaints
  4. 4.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) test on one group only (d) ignore complaints
  5. 5.Which of these adds to bias? (a) balance the data (b) check who is missing (c) test on many groups (d) ignore complaints
  6. 6.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  8. 8.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  9. 9.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) test on many groups (d) test on one group only
  10. 10.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  11. 11.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  12. 12.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) fix wrong labels (d) ask different people
  13. 13.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
  14. 14.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) use one group only (d) fix wrong labels
  17. 17.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.True or false: “add varied examples” adds to bias. (a) True (b) False
  19. 19.🗣️ 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
  20. 20.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  21. 21.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) add varied examples (d) use one group only
  22. 22.True or false: “use one group only” helps reduce bias. (a) True (b) False
  23. 23.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  25. 25.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  26. 26.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  27. 27.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) copy old unfair choices (d) add more of the same
  29. 29.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) copy old unfair choices (d) ignore complaints
  30. 30.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  31. 31.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
  32. 32.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  34. 34.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) check who is missing (d) add varied examples
  35. 35.Which of these adds to bias? (a) balance the data (b) use one group only (c) add varied examples (d) fix wrong labels
  36. 36.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  37. 37.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  38. 38.True or false: “balance the data” adds to bias. (a) False (b) True
  39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  40. 40.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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