← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 855 · 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: photos of people from only one age group? (a) balanced data (b) one-sided data
  2. 2.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
  4. 4.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  6. 6.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.True or false: “use one group only” helps reduce bias. (a) False (b) True
  8. 8.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  9. 9.True or false: “balance the data” adds to bias. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  11. 11.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  12. 12.True or false: “test on many groups” adds to bias. (a) True (b) False
  13. 13.Which of these adds to bias? (a) add varied examples (b) balance the data (c) add more of the same (d) test on many groups
  14. 14.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  15. 15.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) fix wrong labels (d) test on many groups
  16. 16.Which of these adds to bias? (a) ask different people (b) add varied examples (c) test on many groups (d) copy old unfair choices
  17. 17.True or false: “check who is missing” adds to bias. (a) True (b) False
  18. 18.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) skip testing (d) copy old unfair choices
  19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  20. 20.Which of these helps reduce bias? (a) skip testing (b) add varied examples (c) copy old unfair choices (d) use one group only
  21. 21.True or false: “add more of the same” adds to bias. (a) False (b) True
  22. 22.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  24. 24.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) fix wrong labels
  25. 25.Which of these adds to bias? (a) ask different people (b) check who is missing (c) test on many groups (d) use one group only
  26. 26.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  28. 28.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  29. 29.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  30. 30.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  31. 31.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  34. 34.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) test on one group only (d) add more of the same
  36. 36.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  37. 37.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) skip testing (d) check who is missing
  38. 38.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) ask different people (d) add more of the same
  39. 39.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  40. 40.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

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

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