← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 323 · 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.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
  2. 2.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  3. 3.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  4. 4.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  5. 5.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  8. 8.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  9. 9.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  10. 10.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  11. 11.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  12. 12.True or false: “ask different people” helps reduce bias. (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) add varied examples (d) fix wrong labels
  14. 14.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) test on many groups (d) check who is missing
  15. 15.Which of these adds to bias? (a) ask different people (b) copy old unfair choices (c) balance the data (d) check who is missing
  16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  17. 17.True or false: “add varied examples” adds to bias. (a) True (b) False
  18. 18.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
  19. 19.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  21. 21.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  23. 23.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  24. 24.True or false: “skip testing” adds to bias. (a) True (b) False
  25. 25.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) add more of the same (d) use one group only
  26. 26.Which of these adds to bias? (a) balance the data (b) skip testing (c) test on many groups (d) ask different people
  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.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  29. 29.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  30. 30.True or false: “check who is missing” adds to bias. (a) False (b) True
  31. 31.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) balance the data (d) use one group only
  32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  33. 33.True or false: “test on one group only” adds to bias. (a) False (b) True
  34. 34.True or false: “use one group only” adds to bias. (a) False (b) True
  35. 35.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) ask different people (d) balance the data
  37. 37.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  38. 38.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  40. 40.🗣️ 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) children speak too fast (d) it was a rainy day

Answer key

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

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