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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 851 · 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.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  2. 2.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) ignore complaints (d) use one group only
  3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  4. 4.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  5. 5.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) check who is missing (d) test on one group only
  6. 6.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  8. 8.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) balance the data (d) check who is missing
  9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  10. 10.True or false: “skip testing” helps reduce bias. (a) True (b) False
  11. 11.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) use one group only (d) balance the data
  12. 12.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  14. 14.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  15. 15.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  16. 16.True or false: “test on one group only” adds to bias. (a) True (b) False
  17. 17.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add varied examples (d) skip testing
  18. 18.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  19. 19.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
  20. 20.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  21. 21.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) use one group only (d) fix wrong labels
  22. 22.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  24. 24.True or false: “balance the data” helps reduce bias. (a) True (b) False
  25. 25.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  26. 26.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) fix wrong labels (d) check who is missing
  27. 27.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) test on many groups (d) copy old unfair choices
  28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  30. 30.Which of these helps reduce bias? (a) skip testing (b) add varied examples (c) use one group only (d) ignore complaints
  31. 31.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  33. 33.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  34. 34.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  35. 35.Which of these adds to bias? (a) test on one group only (b) fix wrong labels (c) test on many groups (d) balance the data
  36. 36.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) ask different people (d) skip testing
  37. 37.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) check who is missing (d) skip testing
  38. 38.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  39. 39.True or false: “test on many groups” adds to bias. (a) False (b) True
  40. 40.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data

Answer key

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

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