← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 283 · 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: “check who is missing” adds to bias. (a) True (b) False
  2. 2.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) check who is missing (d) ignore complaints
  3. 3.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  4. 4.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  6. 6.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  7. 7.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) add varied examples (d) skip testing
  8. 8.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  9. 9.Which of these adds to bias? (a) check who is missing (b) test on one group only (c) add varied examples (d) ask different people
  10. 10.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  13. 13.True or false: “balance the data” helps reduce bias. (a) False (b) True
  14. 14.True or false: “skip testing” helps reduce bias. (a) True (b) False
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  16. 16.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  17. 17.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) skip testing (d) add more of the same
  18. 18.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  19. 19.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  20. 20.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  21. 21.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
  22. 22.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  23. 23.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  24. 24.True or false: “add more of the same” adds to bias. (a) False (b) True
  25. 25.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  26. 26.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  27. 27.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) fix wrong labels (d) test on many groups
  28. 28.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  30. 30.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  32. 32.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
  33. 33.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  34. 34.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  36. 36.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) use one group only (d) add more of the same
  39. 39.True or false: “ask different people” adds to bias. (a) False (b) True
  40. 40.Which of these adds to bias? (a) test on many groups (b) ignore complaints (c) check who is missing (d) balance the data

Answer key

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

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students