← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 622 · 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.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  3. 3.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  4. 4.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  5. 5.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  6. 6.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) balance the data (d) copy old unfair choices
  8. 8.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
  9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
  10. 10.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  11. 11.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  14. 14.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) ask different people (d) skip testing
  15. 15.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) add more of the same (d) copy old unfair choices
  17. 17.True or false: “test on many groups” adds to bias. (a) True (b) False
  18. 18.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  19. 19.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) test on many groups (d) test on one group only
  20. 20.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  23. 23.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  24. 24.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  25. 25.True or false: “skip testing” helps reduce bias. (a) False (b) True
  26. 26.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) check who is missing (d) skip testing
  27. 27.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  28. 28.True or false: “skip testing” adds to bias. (a) True (b) False
  29. 29.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
  30. 30.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  31. 31.Which of these adds to bias? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) test on many groups
  32. 32.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  33. 33.True or false: “ignore complaints” adds to bias. (a) True (b) False
  34. 34.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  35. 35.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  36. 36.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) ignore complaints (d) ask different people
  37. 37.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  38. 38.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
  39. 39.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) ignore complaints (d) use one group only
  40. 40.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) use one group only (d) test on one group only

Answer key

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

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