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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 762 · 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 of these adds to bias? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) check who is missing
  2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.True or false: “add more of the same” adds to bias. (a) True (b) False
  4. 4.🗣️ 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
  5. 5.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  6. 6.Which of these helps reduce bias? (a) balance the data (b) test on one group only (c) copy old unfair choices (d) use one group only
  7. 7.True or false: “skip testing” adds to bias. (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  9. 9.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  10. 10.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  11. 11.Which of these adds to bias? (a) add varied examples (b) ask different people (c) test on one group only (d) fix wrong labels
  12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  13. 13.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  14. 14.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) add more of the same (d) skip testing
  15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  17. 17.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  18. 18.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather
  19. 19.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on one group only (d) ask different people
  20. 20.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  21. 21.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  22. 22.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  23. 23.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  24. 24.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) skip testing (d) test on many groups
  26. 26.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) balance the data (d) test on one group only
  28. 28.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) fix wrong labels (d) use one group only
  29. 29.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
  30. 30.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  31. 31.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
  32. 32.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  33. 33.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  34. 34.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  35. 35.True or false: “test on many groups” adds to bias. (a) True (b) False
  36. 36.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) copy old unfair choices
  37. 37.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
  38. 38.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  39. 39.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: “check who is missing” adds to bias. (a) True (b) False

Answer key

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

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