← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 968 · 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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  2. 2.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  3. 3.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  4. 4.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) test on one group only (d) add varied examples
  5. 5.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  6. 6.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  7. 7.True or false: “balance the data” helps reduce bias. (a) False (b) True
  8. 8.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) skip testing (d) test on one group only
  9. 9.True or false: “ignore complaints” adds to bias. (a) True (b) False
  10. 10.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) ask different people (d) copy old unfair choices
  11. 11.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  14. 14.True or false: “add varied examples” adds to bias. (a) True (b) False
  15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on many groups (d) use one group only
  17. 17.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  18. 18.True or false: “test on one group only” adds to bias. (a) False (b) True
  19. 19.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
  20. 20.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) ignore complaints (d) test on one group only
  21. 21.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) skip testing (d) ask different people
  22. 22.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  24. 24.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  25. 25.True or false: “skip testing” helps reduce bias. (a) False (b) True
  26. 26.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  28. 28.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  29. 29.True or false: “use one group only” adds to bias. (a) True (b) False
  30. 30.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  33. 33.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) copy old unfair choices (d) fix wrong labels
  34. 34.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  35. 35.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  36. 36.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) add more of the same
  37. 37.True or false: “use one group only” helps reduce bias. (a) True (b) False
  38. 38.True or false: “test on many groups” adds to bias. (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) ask different people (d) use one group only
  40. 40.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) skip testing (d) ask different people

Answer key

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

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