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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 859 · 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: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) it was a rainy day (d) children speak too fast
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
  4. 4.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
  5. 5.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) ignore complaints (d) balance the data
  6. 6.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  7. 7.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) add varied examples
  8. 8.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  9. 9.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) test on one group only (d) balance the data
  10. 10.True or false: “balance the data” helps reduce bias. (a) False (b) True
  11. 11.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) add more of the same (d) check who is missing
  12. 12.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  13. 13.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) ask different people (d) check who is missing
  14. 14.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  16. 16.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  17. 17.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  18. 18.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  20. 20.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  21. 21.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  23. 23.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  24. 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  25. 25.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  26. 26.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  27. 27.True or false: “check who is missing” adds to bias. (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ignore complaints (d) skip testing
  29. 29.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) ignore complaints (d) test on one group only
  30. 30.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) add more of the same (d) use one group only
  31. 31.True or false: “balance the data” adds to bias. (a) False (b) True
  32. 32.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) fix wrong labels (d) test on many groups
  33. 33.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) ask different people (d) copy old unfair choices
  34. 34.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) ask different people (d) check who is missing
  35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) add more of the same (d) add varied examples
  36. 36.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) use one group only (d) copy old unfair choices
  37. 37.True or false: “skip testing” helps reduce bias. (a) True (b) False
  38. 38.True or false: “use one group only” helps reduce bias. (a) True (b) False
  39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  40. 40.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) skip testing (d) balance the data

Answer key

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

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