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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 901 · 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: “skip testing” adds to bias. (a) False (b) True
  2. 2.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  4. 4.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  5. 5.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  6. 6.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) check who is missing (d) skip testing
  7. 7.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  9. 9.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  10. 10.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
  15. 15.Which of these adds to bias? (a) balance the data (b) ask different people (c) test on many groups (d) test on one group only
  16. 16.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  18. 18.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  19. 19.Which of these adds to bias? (a) add varied examples (b) use one group only (c) test on many groups (d) check who is missing
  20. 20.True or false: “add varied examples” adds to bias. (a) True (b) False
  21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
  23. 23.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  24. 24.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) skip testing (d) fix wrong labels
  25. 25.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  27. 27.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  28. 28.Which of these helps reduce bias? (a) add varied examples (b) test on one group only (c) ignore complaints (d) use one group only
  29. 29.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  30. 30.True or false: “add more of the same” adds to bias. (a) False (b) True
  31. 31.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  32. 32.True or false: “use one group only” adds to bias. (a) True (b) False
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) test on one group only (d) add varied examples
  34. 34.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) ask different people (d) copy old unfair choices
  35. 35.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  36. 36.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  37. 37.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) ask different people (d) skip testing
  38. 38.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) test on many groups
  39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  40. 40.True or false: “ignore complaints” adds to bias. (a) True (b) False

Answer key

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

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