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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 454 · 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: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) balance the data (d) use one group only
  3. 3.Which of these helps reduce bias? (a) ignore complaints (b) add varied examples (c) test on one group only (d) skip testing
  4. 4.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  5. 5.Which of these adds to bias? (a) check who is missing (b) use one group only (c) ask different people (d) add varied examples
  6. 6.Which of these helps reduce bias? (a) ask different people (b) skip testing (c) use one group only (d) ignore complaints
  7. 7.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) fix wrong labels (d) add more of the same
  8. 8.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.True or false: “balance the data” helps reduce bias. (a) True (b) False
  10. 10.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a broken screen (d) a strong battery
  12. 12.Which of these adds to bias? (a) balance the data (b) skip testing (c) add varied examples (d) ask different people
  13. 13.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) ask different people (d) test on many groups
  15. 15.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  16. 16.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) it was a rainy day (d) children speak too fast
  17. 17.True or false: “test on one group only” adds to bias. (a) False (b) True
  18. 18.True or false: “check who is missing” adds to bias. (a) True (b) False
  19. 19.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  21. 21.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) test on many groups (d) use one group only
  22. 22.True or false: “skip testing” adds to bias. (a) False (b) True
  23. 23.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  24. 24.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  25. 25.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) use one group only
  26. 26.True or false: “balance the data” adds to bias. (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  28. 28.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  29. 29.True or false: “test on many groups” adds to bias. (a) False (b) True
  30. 30.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  31. 31.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) add varied examples
  32. 32.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  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: add more of the same? (a) reduces bias (b) adds to bias
  36. 36.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  37. 37.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) check who is missing
  38. 38.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  39. 39.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  40. 40.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data

Answer key

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

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