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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 336 · 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: photos of people from only one age group? (a) balanced data (b) one-sided data
  2. 2.🖼️ 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
  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: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  5. 5.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  6. 6.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) add more of the same (d) use one group only
  7. 7.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) use one group only
  8. 8.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  10. 10.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  11. 11.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  12. 12.Which of these adds to bias? (a) test on many groups (b) balance the data (c) check who is missing (d) copy old unfair choices
  13. 13.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  15. 15.True or false: “add varied examples” adds to bias. (a) False (b) True
  16. 16.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  17. 17.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ignore complaints (d) use one group only
  18. 18.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) ignore complaints (d) balance the data
  19. 19.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  20. 20.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) fix wrong labels (d) ignore complaints
  21. 21.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
  22. 22.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  23. 23.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  24. 24.True or false: “test on one group only” adds to bias. (a) False (b) True
  25. 25.True or false: “use one group only” helps reduce bias. (a) False (b) True
  26. 26.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  28. 28.🔍 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
  29. 29.True or false: “ask different people” adds to bias. (a) False (b) True
  30. 30.Which of these adds to bias? (a) ask different people (b) add varied examples (c) check who is missing (d) test on one group only
  31. 31.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) use one group only (d) check who is missing
  32. 32.Which of these adds to bias? (a) balance the data (b) add varied examples (c) check who is missing (d) add more of the same
  33. 33.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  34. 34.Which of these adds to bias? (a) skip testing (b) check who is missing (c) ask different people (d) test on many groups
  35. 35.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) add varied examples (d) fix wrong labels
  36. 36.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  37. 37.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  38. 38.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) add more of the same (d) test on many groups
  39. 39.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  40. 40.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests

Answer key

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

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