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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 763 · 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: use one group only? (a) adds to bias (b) reduces bias
  2. 2.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  4. 4.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) copy old unfair choices (d) ignore complaints
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  6. 6.🗣️ 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) children speak too fast (d) the phone was new
  7. 7.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  8. 8.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
  9. 9.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) use one group only
  10. 10.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) ask different people (d) check who is missing
  12. 12.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  13. 13.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  14. 14.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  15. 15.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
  16. 16.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  18. 18.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  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.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  22. 22.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  24. 24.True or false: “balance the data” adds to bias. (a) True (b) False
  25. 25.True or false: “skip testing” adds to bias. (a) False (b) True
  26. 26.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  27. 27.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) fix wrong labels (d) use one group only
  28. 28.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  29. 29.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) balance the data (d) add varied examples
  30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  31. 31.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  32. 32.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a fair model (d) a broken screen
  33. 33.Which of these adds to bias? (a) add varied examples (b) balance the data (c) copy old unfair choices (d) ask different people
  34. 34.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
  35. 35.True or false: “add more of the same” adds to bias. (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) use one group only (d) balance the data
  37. 37.Which of these adds to bias? (a) check who is missing (b) ask different people (c) ignore complaints (d) balance the data
  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: “skip testing” helps reduce bias. (a) False (b) True
  40. 40.Which of these adds to bias? (a) check who is missing (b) use one group only (c) balance the data (d) fix wrong labels

Answer key

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

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