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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 112 · 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) test on many groups (b) ask different people (c) check who is missing (d) copy old unfair choices
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  3. 3.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ignore complaints (d) fix wrong labels
  4. 4.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  5. 5.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) add varied examples (d) add more of the same
  6. 6.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  9. 9.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
  10. 10.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  11. 11.True or false: “use one group only” helps reduce bias. (a) True (b) False
  12. 12.True or false: “skip testing” helps reduce bias. (a) False (b) True
  13. 13.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  15. 15.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) use one group only (d) test on many groups
  16. 16.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  17. 17.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  19. 19.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  20. 20.True or false: “add varied examples” adds to bias. (a) True (b) False
  21. 21.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
  23. 23.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  24. 24.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  26. 26.True or false: “use one group only” adds to bias. (a) True (b) False
  27. 27.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  28. 28.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a broken screen (d) a strong battery
  29. 29.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) skip testing (d) test on many groups
  30. 30.True or false: “skip testing” adds to bias. (a) True (b) False
  31. 31.True or false: “add more of the same” adds to bias. (a) False (b) True
  32. 32.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  33. 33.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  34. 34.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
  35. 35.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  36. 36.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) test on one group only (d) ask different people
  37. 37.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  39. 39.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) ask different people (d) fix wrong labels
  40. 40.Which of these adds to bias? (a) check who is missing (b) ask different people (c) ignore complaints (d) test on many groups

Answer key

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

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