← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 390 · 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) balanced data (b) one-sided data
  2. 2.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) ignore complaints (d) add varied examples
  3. 3.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  4. 4.True or false: “balance the data” adds to bias. (a) False (b) True
  5. 5.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  6. 6.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  7. 7.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  9. 9.Which of these adds to bias? (a) ask different people (b) add varied examples (c) copy old unfair choices (d) balance the data
  10. 10.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) balance the data
  11. 11.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  12. 12.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) use one group only (d) copy old unfair choices
  13. 13.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) ask different people (d) use one group only
  14. 14.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
  15. 15.True or false: “balance the data” helps reduce bias. (a) True (b) False
  16. 16.🗣️ 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
  17. 17.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) ignore complaints (d) test on many groups
  18. 18.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
  19. 19.True or false: “ask different people” adds to bias. (a) False (b) True
  20. 20.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) a broken screen (d) bias from data
  21. 21.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  22. 22.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  23. 23.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
  24. 24.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
  25. 25.True or false: “use one group only” adds to bias. (a) True (b) False
  26. 26.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  29. 29.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  30. 30.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  31. 31.True or false: “skip testing” helps reduce bias. (a) False (b) True
  32. 32.True or false: “check who is missing” adds to bias. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  34. 34.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  35. 35.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) test on one group only (d) ask different people
  37. 37.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  39. 39.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  40. 40.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) ask different people (d) copy old unfair choices

Answer key

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

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