← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 255 · 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.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  2. 2.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  3. 3.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) copy old unfair choices (d) fix wrong labels
  4. 4.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  5. 5.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  7. 7.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  8. 8.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) add varied examples
  9. 9.True or false: “balance the data” helps reduce bias. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  11. 11.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  12. 12.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ignore complaints (d) add varied examples
  13. 13.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  15. 15.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  16. 16.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) fix wrong labels (d) balance the data
  17. 17.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  18. 18.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  19. 19.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) test on many groups
  20. 20.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) use one group only
  21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  22. 22.True or false: “skip testing” helps reduce bias. (a) False (b) True
  23. 23.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  24. 24.Which of these helps reduce bias? (a) copy old unfair choices (b) test on many groups (c) test on one group only (d) skip testing
  25. 25.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  26. 26.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  27. 27.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  28. 28.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  29. 29.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  30. 30.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  32. 32.True or false: “add more of the same” adds to bias. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  34. 34.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) copy old unfair choices (d) use one group only
  36. 36.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  37. 37.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  38. 38.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) skip testing (d) check who is missing
  39. 39.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  40. 40.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data

Answer key

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

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