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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 446 · 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.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  2. 2.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  3. 3.True or false: “ask different people” adds to bias. (a) False (b) True
  4. 4.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
  5. 5.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) ask different people (d) add varied examples
  6. 6.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) add more of the same (d) skip testing
  7. 7.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  8. 8.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  9. 9.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  10. 10.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  11. 11.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) ask different people (d) skip testing
  15. 15.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) fix wrong labels (d) test on one group only
  16. 16.True or false: “skip testing” helps reduce bias. (a) True (b) False
  17. 17.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  18. 18.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  19. 19.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  21. 21.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) test on one group only (d) use one group only
  23. 23.True or false: “use one group only” adds to bias. (a) True (b) False
  24. 24.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  25. 25.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  26. 26.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) copy old unfair choices (d) skip testing
  27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
  28. 28.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  29. 29.Which of these adds to bias? (a) use one group only (b) add varied examples (c) check who is missing (d) ask different people
  30. 30.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  31. 31.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) copy old unfair choices (d) ask different people
  32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
  34. 34.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  35. 35.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) add more of the same
  36. 36.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) copy old unfair choices (d) add varied examples
  37. 37.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  38. 38.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  39. 39.True or false: “ask different people” helps reduce bias. (a) False (b) True
  40. 40.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data

Answer key

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

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