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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 449 · 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: add varied examples? (a) adds to bias (b) reduces bias
  2. 2.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) fix wrong labels (d) test on many groups
  3. 3.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  4. 4.True or false: “check who is missing” adds to bias. (a) False (b) True
  5. 5.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) add varied examples (d) skip testing
  6. 6.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) check who is missing (d) use one group only
  7. 7.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  8. 8.🗣️ 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
  9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  10. 10.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) use one group only (d) add more of the same
  11. 11.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  12. 12.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  13. 13.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ask different people (d) test on one group only
  14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  15. 15.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  16. 16.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
  17. 17.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) check who is missing
  18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  19. 19.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  20. 20.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  21. 21.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add varied examples (d) add more of the same
  22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) ask different people (d) add varied examples
  23. 23.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  24. 24.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  25. 25.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) fix wrong labels (d) add more of the same
  26. 26.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  29. 29.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) balance the data (d) copy old unfair choices
  30. 30.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  31. 31.🖼️ 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
  32. 32.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  33. 33.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) ignore complaints (d) ask different people
  34. 34.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  35. 35.True or false: “test on one group only” adds to bias. (a) False (b) True
  36. 36.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  37. 37.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
  38. 38.True or false: “use one group only” helps reduce bias. (a) True (b) False
  39. 39.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  40. 40.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data

Answer key

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

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