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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 810 · 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: photos of people from only one age group? (a) balanced data (b) one-sided data
  2. 2.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
  3. 3.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  4. 4.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  5. 5.Which of these helps reduce bias? (a) ignore complaints (b) add varied examples (c) skip testing (d) add more of the same
  6. 6.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  7. 7.🖼️ 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
  8. 8.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  9. 9.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  11. 11.Which of these adds to bias? (a) fix wrong labels (b) use one group only (c) balance the data (d) ask different people
  12. 12.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
  15. 15.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) ignore complaints (d) balance the data
  16. 16.True or false: “ignore complaints” adds to bias. (a) False (b) True
  17. 17.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) fix wrong labels (d) balance the data
  18. 18.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  19. 19.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  22. 22.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) add varied examples (d) add more of the same
  23. 23.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  24. 24.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  25. 25.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  26. 26.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  27. 27.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  28. 28.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  29. 29.Which of these adds to bias? (a) ignore complaints (b) add varied examples (c) fix wrong labels (d) balance the data
  30. 30.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  31. 31.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  32. 32.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
  33. 33.Which of these adds to bias? (a) skip testing (b) balance the data (c) fix wrong labels (d) ask different people
  34. 34.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  35. 35.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) copy old unfair choices (d) add more of the same
  37. 37.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
  38. 38.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) balance the data (d) test on many groups
  40. 40.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

Answer key

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

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