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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 555 · 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: leaves from every season of the year? (a) one-sided data (b) balanced data
  2. 2.Which of these adds to bias? (a) add varied examples (b) ask different people (c) use one group only (d) test on many groups
  3. 3.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  4. 4.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather
  5. 5.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) ask different people
  6. 6.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  7. 7.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  8. 8.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) add more of the same (d) ask different people
  9. 9.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  10. 10.🗣️ 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
  11. 11.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  12. 12.True or false: “skip testing” helps reduce bias. (a) True (b) False
  13. 13.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  14. 14.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ignore complaints (d) ask different people
  15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  16. 16.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
  17. 17.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  18. 18.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
  19. 19.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) ignore complaints (d) add more of the same
  20. 20.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  21. 21.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) use one group only (d) balance the data
  22. 22.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  24. 24.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  26. 26.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) add more of the same (d) copy old unfair choices
  27. 27.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  29. 29.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  30. 30.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) check who is missing (d) add varied examples
  31. 31.True or false: “skip testing” adds to bias. (a) False (b) True
  32. 32.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  33. 33.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) a fair model (d) bias from data
  34. 34.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  35. 35.Which of these adds to bias? (a) ignore complaints (b) balance the data (c) add varied examples (d) test on many groups
  36. 36.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: “add varied examples” adds to bias. (a) False (b) True
  38. 38.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  39. 39.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  40. 40.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

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

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