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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 832 · 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
  2. 2.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  3. 3.True or false: “ask different people” helps reduce bias. (a) False (b) True
  4. 4.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  5. 5.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  6. 6.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) ignore complaints
  7. 7.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
  9. 9.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  10. 10.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  12. 12.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  14. 14.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
  16. 16.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  17. 17.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) check who is missing (d) test on one group only
  18. 18.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  19. 19.Which of these adds to bias? (a) test on many groups (b) balance the data (c) use one group only (d) fix wrong labels
  20. 20.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  22. 22.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  23. 23.True or false: “check who is missing” adds to bias. (a) False (b) True
  24. 24.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) ask different people (d) test on many groups
  26. 26.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  27. 27.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  29. 29.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) check who is missing (d) add varied examples
  30. 30.True or false: “skip testing” helps reduce bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  32. 32.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
  33. 33.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) balance the data (d) add more of the same
  34. 34.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) add more of the same (d) add varied examples
  36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  37. 37.True or false: “ask different people” adds to bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  39. 39.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  40. 40.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data

Answer key

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

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