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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 665 · 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.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  2. 2.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
  3. 3.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  4. 4.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  6. 6.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  7. 7.Which of these adds to bias? (a) ask different people (b) add varied examples (c) fix wrong labels (d) use one group only
  8. 8.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  9. 9.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on many groups (d) use one group only
  10. 10.True or false: “use one group only” helps reduce bias. (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  12. 12.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) fix wrong labels (d) ignore complaints
  13. 13.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) use one group only (d) skip testing
  14. 14.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  15. 15.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  18. 18.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) ignore complaints (d) use one group only
  19. 19.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  20. 20.Which of these helps reduce bias? (a) ignore complaints (b) balance the data (c) use one group only (d) copy old unfair choices
  21. 21.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  24. 24.True or false: “add more of the same” adds to bias. (a) True (b) False
  25. 25.🗣️ 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) the phone was new (d) it was a rainy day
  26. 26.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  28. 28.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  30. 30.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  31. 31.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  32. 32.Which of these adds to bias? (a) ignore complaints (b) check who is missing (c) add varied examples (d) balance the data
  33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  34. 34.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  35. 35.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) add more of the same (d) check who is missing
  36. 36.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) ask different people (d) copy old unfair choices
  37. 37.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
  38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) check who is missing (d) test on many groups
  40. 40.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False

Answer key

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

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