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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 827 · 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.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
  3. 3.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) skip testing (d) test on one group only
  5. 5.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a strong battery (d) a fair model
  7. 7.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  9. 9.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  10. 10.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) ask different people (d) copy old unfair choices
  11. 11.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) add more of the same (d) test on many groups
  12. 12.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) test on many groups (d) add more of the same
  13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  14. 14.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  16. 16.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) test on one group only
  17. 17.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
  18. 18.True or false: “add varied examples” adds to bias. (a) True (b) False
  19. 19.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) test on many groups (d) add more of the same
  20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  22. 22.True or false: “use one group only” helps reduce bias. (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  25. 25.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) balance the data (d) skip testing
  26. 26.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  27. 27.True or false: “test on one group only” adds to bias. (a) True (b) False
  28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  29. 29.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  30. 30.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) ask different people (d) test on one group only
  31. 31.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) ask different people (d) fix wrong labels
  32. 32.Which of these helps reduce bias? (a) add more of the same (b) fix wrong labels (c) copy old unfair choices (d) skip testing
  33. 33.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  35. 35.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) use one group only (d) balance the data
  36. 36.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  37. 37.True or false: “ignore complaints” adds to bias. (a) True (b) False
  38. 38.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  39. 39.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  40. 40.True or false: “test on many groups” helps reduce bias. (a) False (b) True

Answer key

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

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