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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 772 · 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: “skip testing” helps reduce bias. (a) True (b) False
  2. 2.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  3. 3.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) skip testing
  5. 5.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) ask different people (d) ignore complaints
  6. 6.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) add more of the same (d) ask different people
  7. 7.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) ignore complaints (d) copy old unfair choices
  8. 8.Which of these adds to bias? (a) add varied examples (b) copy old unfair choices (c) ask different people (d) check who is missing
  9. 9.True or false: “balance the data” helps reduce bias. (a) True (b) False
  10. 10.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
  11. 11.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  12. 12.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  13. 13.True or false: “use one group only” helps reduce bias. (a) True (b) False
  14. 14.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) use one group only (d) balance the data
  15. 15.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  16. 16.True or false: “balance the data” adds to bias. (a) True (b) False
  17. 17.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  18. 18.True or false: “add more of the same” adds to bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  21. 21.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) ignore complaints (d) test on many groups
  22. 22.🗣️ 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
  23. 23.Which of these helps reduce bias? (a) test on many groups (b) use one group only (c) skip testing (d) ignore complaints
  24. 24.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  25. 25.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  26. 26.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  28. 28.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  29. 29.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
  30. 30.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  31. 31.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) fix wrong labels (d) use one group only
  32. 32.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  33. 33.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  34. 34.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  36. 36.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) fix wrong labels (d) skip testing
  37. 37.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  38. 38.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  39. 39.True or false: “skip testing” adds to bias. (a) False (b) True
  40. 40.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias

Answer key

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

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