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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 831 · 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: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
  5. 5.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
  6. 6.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) test on many groups (d) copy old unfair choices
  7. 7.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  8. 8.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  9. 9.Which of these adds to bias? (a) balance the data (b) add varied examples (c) ignore complaints (d) test on many groups
  10. 10.True or false: “check who is missing” adds to bias. (a) True (b) False
  11. 11.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  12. 12.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
  13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  14. 14.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  15. 15.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) add varied examples (d) fix wrong labels
  16. 16.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a fair model (d) a broken screen
  17. 17.True or false: “add varied examples” adds to bias. (a) False (b) True
  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 of these helps reduce bias? (a) skip testing (b) test on one group only (c) add varied examples (d) use one group only
  20. 20.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  21. 21.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  22. 22.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  23. 23.True or false: “use one group only” helps reduce bias. (a) True (b) False
  24. 24.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) ignore complaints (d) skip testing
  25. 25.True or false: “test on many groups” adds to bias. (a) False (b) True
  26. 26.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  29. 29.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  30. 30.True or false: “ignore complaints” adds to bias. (a) False (b) True
  31. 31.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  32. 32.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) check who is missing (d) balance the data
  33. 33.True or false: “add more of the same” adds to bias. (a) False (b) True
  34. 34.Which of these helps reduce bias? (a) balance the data (b) use one group only (c) ignore complaints (d) copy old unfair choices
  35. 35.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) use one group only (d) test on many groups
  36. 36.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
  37. 37.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
  38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  39. 39.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  40. 40.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) skip testing (d) check who is missing

Answer key

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

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