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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 946 · 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 is the odd one out? (a) add more of the same (b) use one group only (c) skip testing (d) check who is missing
  2. 2.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  4. 4.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) children speak too fast (d) the phone was new
  6. 6.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  8. 8.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  9. 9.True or false: “add varied examples” adds to bias. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  11. 11.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  12. 12.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) copy old unfair choices (d) balance the data
  13. 13.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) ask different people (d) use one group only
  14. 14.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) use one group only (d) skip testing
  17. 17.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) add varied examples (d) use one group only
  18. 18.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  19. 19.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
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  21. 21.Which of these adds to bias? (a) balance the data (b) add varied examples (c) ask different people (d) test on one group only
  22. 22.True or false: “ask different people” adds to bias. (a) True (b) False
  23. 23.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
  24. 24.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) fix wrong labels (d) test on many groups
  25. 25.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  26. 26.True or false: “ask different people” helps reduce bias. (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  29. 29.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  30. 30.True or false: “balance the data” helps reduce bias. (a) False (b) True
  31. 31.True or false: “balance the data” adds to bias. (a) False (b) True
  32. 32.True or false: “skip testing” adds to bias. (a) False (b) True
  33. 33.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  34. 34.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) add varied examples (d) use one group only
  36. 36.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  37. 37.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  39. 39.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  40. 40.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias

Answer key

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

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