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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 488 · 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) balanced data (b) one-sided data
  2. 2.True or false: “ask different people” helps reduce bias. (a) True (b) False
  3. 3.True or false: “test on one group only” adds to bias. (a) False (b) True
  4. 4.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) copy old unfair choices (d) test on many groups
  5. 5.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) ignore complaints (d) skip testing
  6. 6.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) ignore complaints (d) test on many groups
  7. 7.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
  8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  10. 10.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) ask different people (d) add varied examples
  11. 11.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) use one group only (d) fix wrong labels
  12. 12.True or false: “balance the data” adds to bias. (a) False (b) True
  13. 13.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) ignore complaints (d) skip testing
  14. 14.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  15. 15.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  17. 17.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  18. 18.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) ask different people (d) copy old unfair choices
  19. 19.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) ignore complaints (d) check who is missing
  20. 20.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  21. 21.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
  22. 22.True or false: “ignore complaints” adds to bias. (a) True (b) False
  23. 23.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  24. 24.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  25. 25.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  26. 26.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) skip testing (d) ask different people
  27. 27.True or false: “use one group only” helps reduce bias. (a) True (b) False
  28. 28.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
  30. 30.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add varied examples (d) use one group only
  31. 31.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) balance the data (d) add more of the same
  32. 32.Which of these adds to bias? (a) check who is missing (b) balance the data (c) ask different people (d) skip testing
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) add varied examples (d) copy old unfair choices
  34. 34.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  35. 35.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) copy old unfair choices (d) skip testing
  36. 36.True or false: “ask different people” adds to bias. (a) False (b) True
  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: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: “add more of the same” adds to bias. (a) False (b) True
  40. 40.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias

Answer key

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

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