← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 970 · 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) test on many groups (b) copy old unfair choices (c) add varied examples (d) check who is missing
  2. 2.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) test on one group only (d) fix wrong labels
  3. 3.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  5. 5.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  7. 7.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  9. 9.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  10. 10.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  11. 11.True or false: “use one group only” adds to bias. (a) False (b) True
  12. 12.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) copy old unfair choices (d) test on one group only
  14. 14.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) test on one group only (d) skip testing
  15. 15.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) add more of the same (d) test on one group only
  16. 16.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) skip testing (d) balance the data
  17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  18. 18.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  19. 19.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  20. 20.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  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: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  23. 23.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  24. 24.Which of these adds to bias? (a) add varied examples (b) skip testing (c) check who is missing (d) test on many groups
  25. 25.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  26. 26.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) test on one group only (d) copy old unfair choices
  27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
  28. 28.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) the phone was new (d) children speak too fast
  29. 29.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) check who is missing (d) skip testing
  30. 30.True or false: “test on many groups” adds to bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  32. 32.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  33. 33.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  34. 34.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  35. 35.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  36. 36.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  37. 37.True or false: “balance the data” helps reduce bias. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  39. 39.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) skip testing (d) balance the data
  40. 40.True or false: “ask different people” helps reduce bias. (a) True (b) False

Answer key

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

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