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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 921 · 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) use one group only (b) ignore complaints (c) add varied examples (d) copy old unfair choices
  2. 2.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  4. 4.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) fix wrong labels (d) ignore complaints
  5. 5.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  7. 7.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  8. 8.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
  9. 9.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) use one group only (d) ignore complaints
  10. 10.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  11. 11.True or false: “ignore complaints” adds to bias. (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) fix wrong labels (d) ask different people
  13. 13.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  15. 15.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  16. 16.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) copy old unfair choices
  17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  18. 18.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  19. 19.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  20. 20.Which of these adds to bias? (a) balance the data (b) ignore complaints (c) ask different people (d) add varied examples
  21. 21.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) check who is missing (d) add more of the same
  22. 22.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  23. 23.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  24. 24.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.True or false: “add more of the same” adds to bias. (a) False (b) True
  26. 26.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  27. 27.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  28. 28.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  30. 30.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  31. 31.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) use one group only (d) copy old unfair choices
  32. 32.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) add more of the same (d) copy old unfair choices
  33. 33.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  35. 35.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: “skip testing” adds to bias. (a) True (b) False
  37. 37.Which of these adds to bias? (a) check who is missing (b) ask different people (c) balance the data (d) use one group only
  38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  39. 39.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  40. 40.True or false: “check who is missing” adds to bias. (a) True (b) False

Answer key

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

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