← Bias: when data is unfair lesson New set →

AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 897 · 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.True or false: “ignore complaints” adds to bias. (a) True (b) False
  2. 2.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) copy old unfair choices (d) balance the data
  3. 3.Which of these helps reduce bias? (a) fix wrong labels (b) copy old unfair choices (c) add more of the same (d) ignore complaints
  4. 4.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) copy old unfair choices (d) use one group only
  5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  6. 6.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  7. 7.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  9. 9.True or false: “balance the data” helps reduce bias. (a) False (b) True
  10. 10.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  12. 12.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) skip testing (d) use one group only
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  15. 15.True or false: “add varied examples” adds to bias. (a) False (b) True
  16. 16.Which of these adds to bias? (a) ask different people (b) add varied examples (c) fix wrong labels (d) use one group only
  17. 17.Which of these helps reduce bias? (a) add more of the same (b) check who is missing (c) copy old unfair choices (d) test on one group only
  18. 18.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  20. 20.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
  21. 21.Which of these adds to bias? (a) add varied examples (b) balance the data (c) skip testing (d) ask different people
  22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  23. 23.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  24. 24.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  25. 25.True or false: “test on many groups” adds to bias. (a) True (b) False
  26. 26.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  27. 27.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  28. 28.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  29. 29.Which of these adds to bias? (a) test on many groups (b) ask different people (c) balance the data (d) ignore complaints
  30. 30.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  31. 31.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  32. 32.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  33. 33.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
  34. 34.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  35. 35.True or false: “skip testing” helps reduce bias. (a) False (b) True
  36. 36.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) test on many groups (d) copy old unfair choices
  38. 38.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) add varied examples (d) use one group only
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  40. 40.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data

Answer key

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

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