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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 187 · 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: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) balance the data
  3. 3.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add varied examples (d) copy old unfair choices
  4. 4.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  6. 6.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) skip testing (d) test on many groups
  7. 7.True or false: “add more of the same” adds to bias. (a) True (b) False
  8. 8.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  9. 9.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) balance the data (d) add varied examples
  10. 10.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  11. 11.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
  12. 12.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  13. 13.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  15. 15.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  16. 16.True or false: “skip testing” adds to bias. (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  18. 18.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) add more of the same (d) fix wrong labels
  19. 19.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  20. 20.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) check who is missing (d) ask different people
  21. 21.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) use one group only (d) fix wrong labels
  22. 22.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  23. 23.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) the phone was new (d) it was a rainy day
  25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  26. 26.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  27. 27.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  28. 28.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) balance the data (d) copy old unfair choices
  30. 30.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  32. 32.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  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) True (b) False
  34. 34.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  35. 35.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  36. 36.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  37. 37.True or false: “use one group only” adds to bias. (a) True (b) False
  38. 38.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  39. 39.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  40. 40.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) use one group only (d) skip testing

Answer key

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

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