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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 158 · 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.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) add more of the same (d) fix wrong labels
  2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  4. 4.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) copy old unfair choices (d) check who is missing
  5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) bias from data (d) a strong battery
  6. 6.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  7. 7.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  8. 8.True or false: “test on one group only” adds to bias. (a) False (b) True
  9. 9.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) add varied examples (d) test on one group only
  10. 10.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) ignore complaints (d) ask different people
  11. 11.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  12. 12.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  14. 14.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  16. 16.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  17. 17.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  18. 18.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) ignore complaints (d) add varied examples
  19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  20. 20.True or false: “ask different people” adds to bias. (a) True (b) False
  21. 21.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  24. 24.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  25. 25.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) add varied examples (d) balance the data
  26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  28. 28.True or false: “skip testing” adds to bias. (a) True (b) False
  29. 29.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  30. 30.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  31. 31.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  32. 32.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  34. 34.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) add varied examples (d) balance the data
  35. 35.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  36. 36.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) fix wrong labels (d) test on one group only
  37. 37.Which of these adds to bias? (a) test on many groups (b) ask different people (c) use one group only (d) check who is missing
  38. 38.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) use one group only (d) ignore complaints
  40. 40.True or false: “check who is missing” adds to bias. (a) False (b) True

Answer key

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

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