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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 567 · 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 of these adds to bias? (a) test on one group only (b) fix wrong labels (c) add varied examples (d) test on many groups
  2. 2.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) copy old unfair choices (d) test on many groups
  3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  4. 4.True or false: “ask different people” helps reduce bias. (a) True (b) False
  5. 5.True or false: “add more of the same” adds to bias. (a) False (b) True
  6. 6.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  7. 7.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  8. 8.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) copy old unfair choices (d) fix wrong labels
  9. 9.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) check who is missing (d) add more of the same
  10. 10.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  11. 11.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) skip testing (d) check who is missing
  12. 12.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  13. 13.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
  14. 14.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  15. 15.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  16. 16.True or false: “skip testing” adds to bias. (a) True (b) False
  17. 17.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  18. 18.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  19. 19.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) ask different people (d) test on one group only
  20. 20.True or false: “test on one group only” adds to bias. (a) False (b) True
  21. 21.🔍 Which is the odd one out? (a) ask different people (b) use one group only (c) fix wrong labels (d) add varied examples
  22. 22.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) use one group only (d) test on one group only
  23. 23.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) copy old unfair choices
  24. 24.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) fix wrong labels (d) skip testing
  25. 25.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  26. 26.True or false: “test on many groups” adds to bias. (a) True (b) False
  27. 27.Which of these helps reduce bias? (a) balance the data (b) test on one group only (c) copy old unfair choices (d) use one group only
  28. 28.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  29. 29.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  30. 30.True or false: “balance the data” helps reduce bias. (a) True (b) False
  31. 31.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) test on many groups
  32. 32.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  33. 33.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  35. 35.True or false: “check who is missing” adds to bias. (a) False (b) True
  36. 36.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
  37. 37.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) test on many groups (d) add varied examples
  38. 38.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  40. 40.True or false: “balance the data” adds to bias. (a) True (b) False

Answer key

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

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