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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 230 · 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) bias from data (c) a broken screen (d) a fair model
  2. 2.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  3. 3.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) copy old unfair choices (d) ask different people
  4. 4.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  5. 5.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) add varied examples (d) ignore complaints
  6. 6.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) check who is missing
  7. 7.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  8. 8.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
  9. 9.True or false: “skip testing” helps reduce bias. (a) True (b) False
  10. 10.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) balance the data (d) fix wrong labels
  11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  12. 12.🗣️ 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) children speak too fast (d) few child voices in data
  13. 13.True or false: “ask different people” helps reduce bias. (a) True (b) False
  14. 14.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) balance the data (d) test on one group only
  15. 15.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  16. 16.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  17. 17.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  18. 18.True or false: “test on many groups” adds to bias. (a) True (b) False
  19. 19.🔍 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
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  21. 21.True or false: “check who is missing” adds to bias. (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) check who is missing (d) copy old unfair choices
  23. 23.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  24. 24.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) add varied examples (d) test on many groups
  25. 25.True or false: “add varied examples” adds to bias. (a) True (b) False
  26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  27. 27.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  29. 29.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  30. 30.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  31. 31.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  32. 32.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  33. 33.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  34. 34.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  35. 35.Which of these helps reduce bias? (a) fix wrong labels (b) test on one group only (c) use one group only (d) add more of the same
  36. 36.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  37. 37.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  38. 38.True or false: “add more of the same” adds to bias. (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add varied examples (d) ignore complaints
  40. 40.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias

Answer key

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

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