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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 526 · 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: voices of children and adults from many regions? (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 training data (d) its colour
  3. 3.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  4. 4.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  5. 5.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  6. 6.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) check who is missing (d) test on one group only
  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: “add varied examples” adds to bias. (a) True (b) False
  9. 9.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  11. 11.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) add varied examples (d) ignore complaints
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a fair model (d) a strong battery
  14. 14.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  15. 15.True or false: “ask different people” helps reduce bias. (a) False (b) True
  16. 16.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  17. 17.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) ask different people (d) add more of the same
  18. 18.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  20. 20.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) fix wrong labels (d) check who is missing
  22. 22.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  23. 23.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  24. 24.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  25. 25.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  26. 26.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  27. 27.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) ask different people (d) test on one group only
  28. 28.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  30. 30.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
  31. 31.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  32. 32.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  33. 33.True or false: “use one group only” adds to bias. (a) False (b) True
  34. 34.True or false: “ask different people” adds to bias. (a) False (b) True
  35. 35.True or false: “balance the data” adds to bias. (a) True (b) False
  36. 36.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  37. 37.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  39. 39.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  40. 40.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) fix wrong labels (d) add more of the same

Answer key

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

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