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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 769 · 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.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) check who is missing (d) use one group only
  2. 2.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  3. 3.True or false: “ignore complaints” adds to bias. (a) False (b) True
  4. 4.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) ask different people (d) skip testing
  5. 5.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) test on one group only (d) check who is missing
  6. 6.True or false: “use one group only” helps reduce bias. (a) True (b) False
  7. 7.True or false: “add varied examples” adds to bias. (a) True (b) False
  8. 8.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  9. 9.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  10. 10.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  11. 11.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  13. 13.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  15. 15.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  16. 16.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) use one group only (d) fix wrong labels
  17. 17.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) ignore complaints (d) check who is missing
  18. 18.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) balance the data
  19. 19.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  20. 20.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) test on many groups (d) fix wrong labels
  21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  22. 22.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) skip testing (d) ask different people
  23. 23.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  24. 24.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on many groups (d) ignore complaints
  25. 25.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  26. 26.True or false: “balance the data” helps reduce bias. (a) False (b) True
  27. 27.🖼️ 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
  28. 28.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  29. 29.True or false: “ask different people” adds to bias. (a) True (b) False
  30. 30.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  31. 31.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) test on one group only (d) check who is missing
  32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  34. 34.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
  35. 35.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  37. 37.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) ignore complaints (d) skip testing
  38. 38.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  39. 39.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  40. 40.True or false: “skip testing” adds to bias. (a) False (b) True

Answer key

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

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