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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 293 · 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 helps reduce bias? (a) skip testing (b) add more of the same (c) add varied examples (d) test on one group only
  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.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) test on many groups (d) add more of the same
  4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  5. 5.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  6. 6.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) copy old unfair choices (d) skip testing
  7. 7.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  8. 8.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  10. 10.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  11. 11.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
  12. 12.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  13. 13.True or false: “skip testing” helps reduce bias. (a) True (b) False
  14. 14.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  15. 15.True or false: “balance the data” adds to bias. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  17. 17.True or false: “test on one group only” adds to bias. (a) False (b) True
  18. 18.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) copy old unfair choices (d) use one group only
  19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
  20. 20.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) skip testing (d) balance the data
  21. 21.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) copy old unfair choices (d) balance the data
  22. 22.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  23. 23.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  24. 24.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  25. 25.True or false: “add more of the same” adds to bias. (a) False (b) True
  26. 26.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ask different people (d) test on many groups
  27. 27.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  28. 28.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
  29. 29.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) ignore complaints (d) add more of the same
  30. 30.True or false: “add varied examples” adds to bias. (a) True (b) False
  31. 31.Which of these adds to bias? (a) use one group only (b) check who is missing (c) fix wrong labels (d) balance the data
  32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  33. 33.True or false: “skip testing” adds to bias. (a) False (b) True
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  35. 35.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  36. 36.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) ask different people (d) balance the data
  37. 37.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  38. 38.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
  39. 39.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  40. 40.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) fix wrong labels (d) copy old unfair choices

Answer key

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

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