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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 765 · 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.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  2. 2.True or false: “add varied examples” adds to bias. (a) True (b) False
  3. 3.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) test on one group only (d) fix wrong labels
  4. 4.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  5. 5.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  6. 6.Which of these adds to bias? (a) test on many groups (b) copy old unfair choices (c) check who is missing (d) balance the data
  7. 7.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) balance the data (d) add more of the same
  8. 8.True or false: “check who is missing” adds to bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  10. 10.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  11. 11.🗣️ 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) it was a rainy day (d) the phone was new
  12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  13. 13.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) fix wrong labels (d) test on one group only
  17. 17.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) ask different people (d) skip testing
  18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  19. 19.True or false: “ask different people” adds to bias. (a) True (b) False
  20. 20.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) skip testing (d) check who is missing
  21. 21.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  22. 22.True or false: “skip testing” helps reduce bias. (a) True (b) False
  23. 23.True or false: “use one group only” helps reduce bias. (a) False (b) True
  24. 24.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  25. 25.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
  26. 26.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  27. 27.Which of these adds to bias? (a) balance the data (b) ignore complaints (c) ask different people (d) test on many groups
  28. 28.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) skip testing (d) ignore complaints
  29. 29.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  30. 30.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) check who is missing (d) copy old unfair choices
  31. 31.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  32. 32.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  34. 34.True or false: “add more of the same” adds to bias. (a) False (b) True
  35. 35.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  36. 36.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  38. 38.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  39. 39.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  40. 40.True or false: “balance the data” adds to bias. (a) True (b) False

Answer key

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

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