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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 474 · 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.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
  2. 2.True or false: “ignore complaints” adds to bias. (a) True (b) False
  3. 3.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  4. 4.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.Which of these adds to bias? (a) ask different people (b) balance the data (c) check who is missing (d) skip testing
  6. 6.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  7. 7.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  8. 8.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
  9. 9.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  10. 10.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  11. 11.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  12. 12.🗣️ 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
  13. 13.True or false: “use one group only” adds to bias. (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  15. 15.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  16. 16.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  18. 18.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  19. 19.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) copy old unfair choices (d) add varied examples
  20. 20.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) add varied examples (d) balance the data
  21. 21.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) ignore complaints (d) fix wrong labels
  23. 23.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) ask different people
  24. 24.True or false: “balance the data” adds to bias. (a) True (b) False
  25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  26. 26.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  27. 27.Which of these adds to bias? (a) balance the data (b) use one group only (c) fix wrong labels (d) check who is missing
  28. 28.True or false: “use one group only” helps reduce bias. (a) True (b) False
  29. 29.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) copy old unfair choices (d) ask different people
  30. 30.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  31. 31.True or false: “add varied examples” adds to bias. (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  33. 33.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  35. 35.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  37. 37.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
  38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) skip testing (d) test on many groups
  40. 40.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on one group only (d) balance the data

Answer key

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

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