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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 626 · 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.True or false: “ask different people” adds to bias. (a) False (b) True
  2. 2.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  3. 3.True or false: “ignore complaints” adds to bias. (a) False (b) True
  4. 4.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  5. 5.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) copy old unfair choices (d) ignore complaints
  6. 6.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  7. 7.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) fix wrong labels (d) ignore complaints
  8. 8.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  9. 9.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  11. 11.Which of these adds to bias? (a) add varied examples (b) copy old unfair choices (c) fix wrong labels (d) balance the data
  12. 12.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  13. 13.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  14. 14.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) ignore complaints (d) balance the data
  16. 16.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) ask different people (d) test on many groups
  17. 17.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  18. 18.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  19. 19.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  20. 20.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  21. 21.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  22. 22.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
  23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  24. 24.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  25. 25.Which of these helps reduce bias? (a) check who is missing (b) add more of the same (c) skip testing (d) copy old unfair choices
  26. 26.Which of these adds to bias? (a) test on many groups (b) balance the data (c) ask different people (d) test on one group only
  27. 27.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  28. 28.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  29. 29.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  30. 30.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) ignore complaints (d) copy old unfair choices
  31. 31.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  32. 32.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  33. 33.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.True or false: “test on many groups” adds to bias. (a) True (b) False
  35. 35.True or false: “balance the data” adds to bias. (a) True (b) False
  36. 36.True or false: “use one group only” adds to bias. (a) True (b) False
  37. 37.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) test on one group only (d) check who is missing
  38. 38.Which of these adds to bias? (a) ask different people (b) ignore complaints (c) test on many groups (d) balance the data
  39. 39.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) use one group only (d) skip testing
  40. 40.True or false: “add varied examples” adds to bias. (a) True (b) False

Answer key

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

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