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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 286 · 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 is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) use one group only (d) test on many groups
  2. 2.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) ignore complaints (d) ask different people
  3. 3.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  4. 4.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) fix wrong labels (d) check who is missing
  5. 5.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  6. 6.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) copy old unfair choices (d) test on many groups
  8. 8.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
  9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  10. 10.True or false: “balance the data” adds to bias. (a) True (b) False
  11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  13. 13.True or false: “ignore complaints” adds to bias. (a) True (b) False
  14. 14.True or false: “check who is missing” adds to bias. (a) True (b) False
  15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  16. 16.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  17. 17.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  18. 18.True or false: “skip testing” adds to bias. (a) True (b) False
  19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  20. 20.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  21. 21.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  22. 22.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  23. 23.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  25. 25.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  26. 26.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  28. 28.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) add varied examples (d) copy old unfair choices
  29. 29.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) use one group only (d) add more of the same
  30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) copy old unfair choices (d) skip testing
  31. 31.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  33. 33.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  34. 34.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  35. 35.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: “balance the data” helps reduce bias. (a) False (b) True
  37. 37.Which of these helps reduce bias? (a) add more of the same (b) check who is missing (c) test on one group only (d) ignore complaints
  38. 38.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
  39. 39.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  40. 40.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) fix wrong labels (d) use one group only

Answer key

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

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