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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 306 · 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: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) check who is missing (d) use one group only
  3. 3.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) ask different people
  4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  6. 6.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  7. 7.True or false: “ignore complaints” adds to bias. (a) False (b) True
  8. 8.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  9. 9.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  10. 10.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  11. 11.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  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.True or false: “balance the data” helps reduce bias. (a) True (b) False
  14. 14.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) use one group only (d) add more of the same
  15. 15.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  16. 16.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  17. 17.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) test on one group only (d) add varied examples
  19. 19.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) copy old unfair choices (d) check who is missing
  20. 20.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) add varied examples (d) ignore complaints
  21. 21.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  23. 23.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  25. 25.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  26. 26.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.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
  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 where every doctor is a man? (a) balanced data (b) one-sided data
  30. 30.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  31. 31.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
  32. 32.Which of these adds to bias? (a) check who is missing (b) skip testing (c) fix wrong labels (d) ask different people
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  35. 35.True or false: “ask different people” helps reduce bias. (a) False (b) True
  36. 36.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  38. 38.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) copy old unfair choices (d) test on many groups
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  40. 40.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False

Answer key

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

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