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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 675 · 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: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  2. 2.True or false: “skip testing” helps reduce bias. (a) True (b) False
  3. 3.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) fix wrong labels (d) add more of the same
  4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  5. 5.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  7. 7.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  9. 9.Which of these helps reduce bias? (a) skip testing (b) add varied examples (c) ignore complaints (d) add more of the same
  10. 10.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  11. 11.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) use one group only (d) check who is missing
  12. 12.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  13. 13.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) fix wrong labels (d) ask different people
  17. 17.True or false: “ask different people” helps reduce bias. (a) True (b) False
  18. 18.Which of these adds to bias? (a) ignore complaints (b) ask different people (c) add varied examples (d) fix wrong labels
  19. 19.🖼️ 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
  20. 20.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  21. 21.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) use one group only (d) ignore complaints
  22. 22.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) add more of the same (d) check who is missing
  23. 23.True or false: “add varied examples” adds to bias. (a) True (b) False
  24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  25. 25.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  26. 26.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  27. 27.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) copy old unfair choices (d) skip testing
  29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  30. 30.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.True or false: “ask different people” adds to bias. (a) True (b) False
  32. 32.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  34. 34.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  35. 35.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  37. 37.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) balance the data (d) check who is missing
  38. 38.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  39. 39.True or false: “test on one group only” adds to bias. (a) True (b) False
  40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

Answer key

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

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