← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 80 · 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.True or false: “test on one group only” adds to bias. (a) False (b) True
  2. 2.True or false: “ask different people” adds to bias. (a) True (b) False
  3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  4. 4.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  5. 5.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  7. 7.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) use one group only (d) add more of the same
  8. 8.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  9. 9.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  10. 10.True or false: “check who is missing” adds to bias. (a) False (b) True
  11. 11.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) skip testing (d) test on many groups
  12. 12.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ask different people (d) add varied examples
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
  14. 14.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) check who is missing (d) copy old unfair choices
  15. 15.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  17. 17.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  18. 18.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) add more of the same (d) skip testing
  19. 19.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  20. 20.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) skip testing (d) test on one group only
  21. 21.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  22. 22.True or false: “ask different people” helps reduce bias. (a) False (b) True
  23. 23.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  24. 24.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  25. 25.True or false: “test on many groups” adds to bias. (a) False (b) True
  26. 26.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  27. 27.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) balance the data (d) skip testing
  28. 28.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  30. 30.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  32. 32.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) add varied examples (d) add more of the same
  33. 33.Which of these adds to bias? (a) add varied examples (b) ask different people (c) balance the data (d) copy old unfair choices
  34. 34.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  35. 35.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) use one group only (d) copy old unfair choices
  36. 36.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) check who is missing (d) ask different people
  37. 37.Which of these helps reduce bias? (a) use one group only (b) fix wrong labels (c) skip testing (d) test on one group only
  38. 38.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) use one group only (d) add varied examples
  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. True
  2. False
  3. reduces bias
  4. one-sided data
  5. balanced data
  6. balanced data
  7. ask different people
  8. True
  9. True
  10. False
  11. skip testing
  12. test on one group only
  13. few child voices in data
  14. copy old unfair choices
  15. one-sided data
  16. one-sided data
  17. False
  18. add varied examples
  19. adds to bias
  20. test on many groups
  21. balanced data
  22. True
  23. False
  24. its training data
  25. False
  26. more varied data
  27. balance the data
  28. False
  29. reduces bias
  30. adds to bias
  31. balanced data
  32. add more of the same
  33. copy old unfair choices
  34. False
  35. test on many groups
  36. ignore complaints
  37. fix wrong labels
  38. False
  39. use one group only
  40. balanced data

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