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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 889 · 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.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  2. 2.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  4. 4.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  5. 5.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) ask different people (d) fix wrong labels
  6. 6.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  7. 7.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.True or false: “test on many groups” adds to bias. (a) True (b) False
  9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  10. 10.True or false: “ask different people” helps reduce bias. (a) True (b) False
  11. 11.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
  12. 12.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  13. 13.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  14. 14.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  16. 16.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) use one group only (d) fix wrong labels
  17. 17.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  18. 18.True or false: “balance the data” adds to bias. (a) False (b) True
  19. 19.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  20. 20.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  21. 21.True or false: “balance the data” helps reduce bias. (a) False (b) True
  22. 22.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) test on one group only
  23. 23.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) add more of the same (d) use one group only
  24. 24.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
  25. 25.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) use one group only (d) fix wrong labels
  26. 26.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  27. 27.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  28. 28.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) use one group only (d) test on one group only
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  30. 30.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  32. 32.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  33. 33.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) add varied examples (d) test on one group only
  34. 34.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  35. 35.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  36. 36.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  37. 37.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  38. 38.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) add varied examples (d) use one group only
  39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  40. 40.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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