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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 586 · 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.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  2. 2.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
  4. 4.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) check who is missing
  5. 5.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) add varied examples (d) test on one group only
  6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
  7. 7.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  8. 8.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
  9. 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.True or false: “ask different people” helps reduce bias. (a) False (b) True
  11. 11.Which of these adds to bias? (a) ask different people (b) add varied examples (c) skip testing (d) fix wrong labels
  12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  13. 13.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) add varied examples (d) balance the data
  15. 15.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) fix wrong labels (d) add more of the same
  16. 16.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  17. 17.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) use one group only (d) balance the data
  18. 18.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  19. 19.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  20. 20.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  21. 21.True or false: “skip testing” helps reduce bias. (a) True (b) False
  22. 22.True or false: “ask different people” adds to bias. (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  24. 24.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) copy old unfair choices (d) ignore complaints
  25. 25.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  26. 26.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  27. 27.True or false: “add more of the same” adds to bias. (a) False (b) True
  28. 28.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  30. 30.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  31. 31.True or false: “skip testing” adds to bias. (a) True (b) False
  32. 32.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) use one group only (d) skip testing
  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) add varied examples (b) test on many groups (c) copy old unfair choices (d) balance the data
  35. 35.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  36. 36.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  37. 37.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) add more of the same
  38. 38.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  39. 39.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) skip testing (d) fix wrong labels

Answer key

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

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