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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 123 · 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.True or false: “check who is missing” adds to bias. (a) True (b) False
  2. 2.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
  3. 3.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) add more of the same (d) add varied examples
  4. 4.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) add more of the same (d) ask different people
  5. 5.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) add varied examples (d) use one group only
  6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
  7. 7.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) copy old unfair choices (d) use one group only
  8. 8.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  9. 9.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  11. 11.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
  12. 12.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  13. 13.True or false: “balance the data” helps reduce bias. (a) False (b) True
  14. 14.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) skip testing (d) add more of the same
  16. 16.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) copy old unfair choices (d) use one group only
  17. 17.True or false: “use one group only” helps reduce bias. (a) True (b) False
  18. 18.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  19. 19.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  20. 20.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) add varied examples (d) use one group only
  21. 21.True or false: “skip testing” helps reduce bias. (a) True (b) False
  22. 22.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  23. 23.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  26. 26.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  27. 27.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  28. 28.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  29. 29.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  30. 30.True or false: “test on one group only” adds to bias. (a) True (b) False
  31. 31.True or false: “ask different people” adds to bias. (a) False (b) True
  32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  33. 33.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  34. 34.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  35. 35.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  36. 36.True or false: “ask different people” helps reduce bias. (a) False (b) True
  37. 37.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) check who is missing (d) ignore complaints
  38. 38.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  39. 39.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  40. 40.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias

Answer key

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

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