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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 511 · 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: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  2. 2.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) ask different people (d) skip testing
  3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) balance the data (d) add more of the same
  5. 5.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
  7. 7.True or false: “test on many groups” adds to bias. (a) False (b) True
  8. 8.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  9. 9.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
  10. 10.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) check who is missing (d) add more of the same
  11. 11.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: “check who is missing” adds to bias. (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) ignore complaints (d) ask different people
  14. 14.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  15. 15.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  16. 16.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  18. 18.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) test on many groups (d) copy old unfair choices
  19. 19.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  20. 20.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  22. 22.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) add varied examples
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  24. 24.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  25. 25.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) test on one group only (d) skip testing
  26. 26.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  27. 27.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  28. 28.True or false: “balance the data” adds to bias. (a) True (b) False
  29. 29.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  31. 31.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) ask different people (d) test on one group only
  32. 32.Which of these adds to bias? (a) add varied examples (b) use one group only (c) balance the data (d) fix wrong labels
  33. 33.True or false: “use one group only” helps reduce bias. (a) False (b) True
  34. 34.True or false: “ask different people” helps reduce bias. (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) test on one group only (d) copy old unfair choices
  36. 36.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) skip testing (d) balance the data
  37. 37.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  38. 38.True or false: “ask different people” adds to bias. (a) False (b) True
  39. 39.Which of these adds to bias? (a) test on one group only (b) check who is missing (c) fix wrong labels (d) add varied examples
  40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

Answer key

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

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