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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 843 · 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.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  4. 4.True or false: “ask different people” helps reduce bias. (a) True (b) False
  5. 5.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  6. 6.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  7. 7.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) fix wrong labels (d) skip testing
  8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  9. 9.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  10. 10.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  11. 11.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  12. 12.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  13. 13.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  14. 14.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  16. 16.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) use one group only (d) test on many groups
  17. 17.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) ignore complaints (d) test on one group only
  18. 18.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  19. 19.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  20. 20.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.True or false: “balance the data” adds to bias. (a) True (b) False
  22. 22.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) copy old unfair choices (d) balance the data
  23. 23.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  24. 24.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) ask different people
  25. 25.True or false: “use one group only” adds to bias. (a) True (b) False
  26. 26.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  27. 27.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  28. 28.Which of these adds to bias? (a) ask different people (b) skip testing (c) test on many groups (d) add varied examples
  29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  30. 30.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  31. 31.True or false: “check who is missing” adds to bias. (a) True (b) False
  32. 32.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  34. 34.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) ignore complaints (d) balance the data
  35. 35.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) balance the data (d) test on one group only
  36. 36.True or false: “test on many groups” adds to bias. (a) True (b) False
  37. 37.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) use one group only (d) skip testing
  38. 38.True or false: “skip testing” adds to bias. (a) True (b) False
  39. 39.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  40. 40.🔍 Which is the odd one out? (a) add varied examples (b) add more of the same (c) ignore complaints (d) copy old unfair choices

Answer key

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

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