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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 687 · 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 broken screen (b) bias from data (c) a strong battery (d) a fair model
  2. 2.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  4. 4.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) fix wrong labels (d) test on many groups
  5. 5.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) test on one group only (d) balance the data
  6. 6.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
  7. 7.Which of these adds to bias? (a) test on many groups (b) use one group only (c) balance the data (d) ask different people
  8. 8.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) ask different people (d) test on many groups
  9. 9.🗣️ 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
  10. 10.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  11. 11.Which of these adds to bias? (a) ask different people (b) add varied examples (c) check who is missing (d) copy old unfair choices
  12. 12.True or false: “use one group only” helps reduce bias. (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  14. 14.True or false: “use one group only” adds to bias. (a) False (b) True
  15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  16. 16.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  17. 17.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) skip testing (d) add varied examples
  18. 18.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  19. 19.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  20. 20.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  22. 22.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
  23. 23.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  24. 24.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) test on many groups
  25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  26. 26.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  28. 28.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  29. 29.True or false: “ask different people” adds to bias. (a) True (b) False
  30. 30.True or false: “check who is missing” adds to bias. (a) False (b) True
  31. 31.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) check who is missing (d) ignore complaints
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  33. 33.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) fix wrong labels (d) ignore complaints
  34. 34.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  35. 35.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  36. 36.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  37. 37.True or false: “test on one group only” adds to bias. (a) False (b) True
  38. 38.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  39. 39.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  40. 40.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour

Answer key

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

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