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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 753 · 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 helps reduce bias? (a) use one group only (b) balance the data (c) add more of the same (d) test on one group only
  2. 2.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  5. 5.Which of these adds to bias? (a) skip testing (b) test on many groups (c) add varied examples (d) balance the data
  6. 6.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  7. 7.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) ignore complaints (d) copy old unfair choices
  8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  9. 9.True or false: “add varied examples” adds to bias. (a) False (b) True
  10. 10.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
  12. 12.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) balance the data (d) copy old unfair choices
  13. 13.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  14. 14.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  15. 15.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  16. 16.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) copy old unfair choices (d) check who is missing
  17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  18. 18.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  20. 20.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  21. 21.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  22. 22.True or false: “test on one group only” adds to bias. (a) True (b) False
  23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  24. 24.True or false: “skip testing” helps reduce bias. (a) False (b) True
  25. 25.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  26. 26.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) test on one group only (d) use one group only
  27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) a broken screen (d) bias from data
  28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  29. 29.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) test on one group only (d) skip testing
  30. 30.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
  31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  32. 32.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) use one group only (d) add more of the same
  33. 33.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ask different people (d) add varied examples
  34. 34.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  35. 35.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  36. 36.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) ignore complaints
  37. 37.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  39. 39.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  40. 40.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False

Answer key

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

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