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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 551 · 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: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  4. 4.True or false: “check who is missing” adds to bias. (a) False (b) True
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  6. 6.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  8. 8.Which of these adds to bias? (a) ask different people (b) copy old unfair choices (c) balance the data (d) add varied examples
  9. 9.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  10. 10.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
  11. 11.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) balance the data (d) test on many groups
  12. 12.🖼️ 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
  13. 13.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) use one group only (d) test on many groups
  14. 14.Which of these helps reduce bias? (a) ask different people (b) test on one group only (c) skip testing (d) use one group only
  15. 15.True or false: “ask different people” helps reduce bias. (a) True (b) False
  16. 16.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  17. 17.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) skip testing (d) add varied examples
  18. 18.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  19. 19.True or false: “ask different people” adds to bias. (a) True (b) False
  20. 20.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  21. 21.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  22. 22.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) fix wrong labels (d) ignore complaints
  24. 24.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  25. 25.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  26. 26.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) balance the data (d) fix wrong labels
  27. 27.True or false: “add more of the same” adds to bias. (a) True (b) False
  28. 28.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  33. 33.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  35. 35.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  37. 37.True or false: “balance the data” helps reduce bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  39. 39.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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