← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 156 · 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: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) check who is missing (d) test on many groups
  4. 4.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) balance the data (d) add more of the same
  6. 6.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) skip testing (d) test on many groups
  7. 7.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  8. 8.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) test on one group only (d) add varied examples
  9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
  10. 10.True or false: “check who is missing” adds to bias. (a) True (b) False
  11. 11.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  12. 12.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  13. 13.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) check who is missing (d) add more of the same
  14. 14.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  15. 15.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  16. 16.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  17. 17.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  18. 18.Which of these adds to bias? (a) test on many groups (b) use one group only (c) balance the data (d) ask different people
  19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  20. 20.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
  22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) skip testing (d) balance the data
  23. 23.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  24. 24.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  25. 25.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  26. 26.True or false: “balance the data” adds to bias. (a) True (b) False
  27. 27.True or false: “skip testing” helps reduce bias. (a) True (b) False
  28. 28.True or false: “balance the data” helps reduce bias. (a) False (b) True
  29. 29.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) check who is missing (d) skip testing
  30. 30.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  31. 31.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  32. 32.Which of these adds to bias? (a) add varied examples (b) add more of the same (c) ask different people (d) fix wrong labels
  33. 33.True or false: “test on one group only” adds to bias. (a) False (b) True
  34. 34.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) ignore complaints (d) test on many groups
  35. 35.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  37. 37.True or false: “ask different people” adds to bias. (a) False (b) True
  38. 38.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  39. 39.True or false: “skip testing” adds to bias. (a) False (b) True
  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. False
  2. False
  3. copy old unfair choices
  4. True
  5. add more of the same
  6. test on many groups
  7. False
  8. test on one group only
  9. bias from data
  10. False
  11. balanced data
  12. balanced data
  13. check who is missing
  14. True
  15. False
  16. True
  17. adds to bias
  18. use one group only
  19. reduces bias
  20. False
  21. its training data
  22. skip testing
  23. adds to bias
  24. True
  25. reduces bias
  26. False
  27. False
  28. True
  29. check who is missing
  30. adds to bias
  31. reduces bias
  32. add more of the same
  33. True
  34. ignore complaints
  35. reduces bias
  36. reduces bias
  37. False
  38. adds to bias
  39. True
  40. balanced data

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