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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 348 · 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: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.Which of these adds to bias? (a) balance the data (b) copy old unfair choices (c) ask different people (d) add varied examples
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
  4. 4.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
  6. 6.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  7. 7.Which of these adds to bias? (a) ask different people (b) check who is missing (c) test on one group only (d) add varied examples
  8. 8.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  9. 9.True or false: “ask different people” helps reduce bias. (a) False (b) True
  10. 10.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) balance the data (d) use one group only
  11. 11.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) check who is missing (d) fix wrong labels
  12. 12.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  13. 13.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  15. 15.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) copy old unfair choices (d) use one group only
  16. 16.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) balance the data (d) check who is missing
  17. 17.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  19. 19.Which of these adds to bias? (a) fix wrong labels (b) use one group only (c) check who is missing (d) balance the data
  20. 20.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) it was a rainy day (d) children speak too fast
  23. 23.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) balance the data (d) skip testing
  24. 24.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  25. 25.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  26. 26.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) test on many groups (d) add more of the same
  27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  28. 28.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
  29. 29.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  30. 30.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  31. 31.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  32. 32.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  34. 34.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ask different people (d) add more of the same
  35. 35.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) test on one group only (d) add varied examples
  37. 37.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on one group only (d) balance the data
  39. 39.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) test on one group only (d) use one group only
  40. 40.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False

Answer key

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

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