← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 568 · 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) copy old unfair choices (d) use one group only
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  3. 3.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  4. 4.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  5. 5.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) test on many groups (d) copy old unfair choices
  6. 6.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  7. 7.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
  8. 8.True or false: “use one group only” helps reduce bias. (a) True (b) False
  9. 9.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  10. 10.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  11. 11.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
  12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) fix wrong labels (d) add more of the same
  14. 14.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
  15. 15.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  16. 16.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) test on one group only (d) ask different people
  17. 17.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) add more of the same (d) ask different people
  18. 18.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  19. 19.True or false: “ask different people” adds to bias. (a) False (b) True
  20. 20.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
  21. 21.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  23. 23.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  24. 24.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  25. 25.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  26. 26.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
  27. 27.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  28. 28.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) ask different people (d) fix wrong labels
  29. 29.True or false: “ask different people” helps reduce bias. (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  32. 32.Which of these adds to bias? (a) check who is missing (b) test on one group only (c) balance the data (d) add varied examples
  33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  34. 34.Which of these adds to bias? (a) ask different people (b) check who is missing (c) ignore complaints (d) fix wrong labels
  35. 35.True or false: “check who is missing” adds to bias. (a) False (b) True
  36. 36.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  37. 37.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  38. 38.True or false: “add varied examples” adds to bias. (a) False (b) True
  39. 39.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  40. 40.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True

Answer key

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

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