← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 948 · 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.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) add varied examples
  2. 2.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) test on many groups (d) skip testing
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
  4. 4.Which of these adds to bias? (a) fix wrong labels (b) skip testing (c) test on many groups (d) add varied examples
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  6. 6.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  8. 8.Which of these adds to bias? (a) check who is missing (b) ask different people (c) ignore complaints (d) balance the data
  9. 9.Which of these adds to bias? (a) check who is missing (b) balance the data (c) copy old unfair choices (d) fix wrong labels
  10. 10.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) fix wrong labels (d) use one group only
  11. 11.Which of these adds to bias? (a) add varied examples (b) test on one group only (c) test on many groups (d) ask different people
  12. 12.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  13. 13.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
  14. 14.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  15. 15.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  16. 16.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  20. 20.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  21. 21.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) skip testing (d) copy old unfair choices
  22. 22.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
  24. 24.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  25. 25.True or false: “add varied examples” adds to bias. (a) False (b) True
  26. 26.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) test on one group only
  27. 27.True or false: “skip testing” helps reduce bias. (a) False (b) True
  28. 28.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  29. 29.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  30. 30.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  31. 31.True or false: “balance the data” adds to bias. (a) False (b) True
  32. 32.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  33. 33.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) test on many groups
  34. 34.True or false: “ignore complaints” adds to bias. (a) True (b) False
  35. 35.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  36. 36.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  38. 38.True or false: “ask different people” helps reduce bias. (a) True (b) False
  39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  40. 40.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias

Answer key

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

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