← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 473 · 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) skip testing (b) use one group only (c) ignore complaints (d) add varied examples
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  3. 3.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  4. 4.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  6. 6.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) test on one group only (d) test on many groups
  7. 7.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) skip testing (d) test on one group only
  8. 8.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  9. 9.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  10. 10.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  11. 11.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) test on many groups (d) fix wrong labels
  12. 12.True or false: “ignore complaints” adds to bias. (a) True (b) False
  13. 13.Which of these adds to bias? (a) test on many groups (b) skip testing (c) add varied examples (d) check who is missing
  14. 14.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  16. 16.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) test on many groups (d) fix wrong labels
  17. 17.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  20. 20.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
  21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  22. 22.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  23. 23.True or false: “skip testing” helps reduce bias. (a) True (b) False
  24. 24.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  25. 25.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  26. 26.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  27. 27.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
  28. 28.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) add more of the same (d) balance the data
  29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  30. 30.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ask different people (d) use one group only
  31. 31.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) use one group only (d) fix wrong labels
  32. 32.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) check who is missing (d) use one group only
  33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  34. 34.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
  35. 35.Which of these adds to bias? (a) balance the data (b) use one group only (c) test on many groups (d) check who is missing
  36. 36.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  37. 37.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  38. 38.True or false: “test on many groups” adds to bias. (a) True (b) False
  39. 39.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) check who is missing (d) balance the data
  40. 40.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) skip testing (d) test on many groups

Answer key

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

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