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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 319 · 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) a broken screen (d) bias from data
  2. 2.True or false: “add varied examples” adds to bias. (a) False (b) True
  3. 3.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) add varied examples (d) copy old unfair choices
  4. 4.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
  5. 5.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  6. 6.True or false: “skip testing” helps reduce bias. (a) True (b) False
  7. 7.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) balance the data (d) add more of the same
  8. 8.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) add varied examples (d) balance the data
  9. 9.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) skip testing (d) add varied examples
  10. 10.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  11. 11.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) test on many groups (d) test on one group only
  12. 12.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  13. 13.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  14. 14.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  15. 15.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) skip testing (d) copy old unfair choices
  16. 16.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  17. 17.True or false: “ask different people” helps reduce bias. (a) True (b) False
  18. 18.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  19. 19.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  20. 20.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  22. 22.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
  23. 23.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  24. 24.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  25. 25.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  26. 26.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) ask different people (d) balance the data
  27. 27.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  29. 29.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  30. 30.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  31. 31.Which of these adds to bias? (a) test on many groups (b) balance the data (c) copy old unfair choices (d) add varied examples
  32. 32.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  33. 33.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  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: “copy old unfair choices” adds to bias. (a) False (b) True
  36. 36.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  37. 37.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  38. 38.Which of these adds to bias? (a) add varied examples (b) use one group only (c) balance the data (d) check who is missing
  39. 39.True or false: “test on many groups” adds to bias. (a) True (b) False
  40. 40.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data

Answer key

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

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