← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 74 · 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) test on one group only (b) test on many groups (c) fix wrong labels (d) add varied examples
  2. 2.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  3. 3.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  4. 4.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) fix wrong labels (d) add varied examples
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  6. 6.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) ignore complaints (d) add varied examples
  7. 7.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) ask different people
  8. 8.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  9. 9.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  10. 10.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) fix wrong labels
  11. 11.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  13. 13.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  14. 14.Which of these adds to bias? (a) ask different people (b) balance the data (c) test on one group only (d) fix wrong labels
  15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  16. 16.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  19. 19.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  20. 20.True or false: “add varied examples” adds to bias. (a) False (b) True
  21. 21.True or false: “add more of the same” adds to bias. (a) True (b) False
  22. 22.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  24. 24.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  25. 25.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  26. 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  27. 27.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  28. 28.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) test on many groups (d) ignore complaints
  29. 29.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  30. 30.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  31. 31.True or false: “ignore complaints” adds to bias. (a) False (b) True
  32. 32.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) fix wrong labels (d) skip testing
  33. 33.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) test on one group only (d) skip testing
  34. 34.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  35. 35.True or false: “balance the data” helps reduce bias. (a) False (b) True
  36. 36.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  37. 37.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  38. 38.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  39. 39.True or false: “use one group only” adds to bias. (a) True (b) False
  40. 40.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data

Answer key

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

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