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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 442 · 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.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) ignore complaints (d) balance the data
  2. 2.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
  3. 3.True or false: “use one group only” helps reduce bias. (a) False (b) True
  4. 4.True or false: “balance the data” adds to bias. (a) True (b) False
  5. 5.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  6. 6.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) children speak too fast (d) the phone was new
  7. 7.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  9. 9.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  11. 11.Which of these helps reduce bias? (a) skip testing (b) check who is missing (c) ignore complaints (d) copy old unfair choices
  12. 12.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  13. 13.True or false: “skip testing” helps reduce bias. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) test on one group only (d) test on many groups
  15. 15.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  16. 16.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  17. 17.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.True or false: “check who is missing” adds to bias. (a) True (b) False
  19. 19.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
  20. 20.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  21. 21.🖼️ 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
  22. 22.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  23. 23.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) ask different people (d) skip testing
  24. 24.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) add more of the same (d) skip testing
  25. 25.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  26. 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  27. 27.True or false: “ignore complaints” adds to bias. (a) True (b) False
  28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  29. 29.True or false: “skip testing” adds to bias. (a) True (b) False
  30. 30.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  31. 31.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  32. 32.Which of these adds to bias? (a) add more of the same (b) balance the data (c) check who is missing (d) ask different people
  33. 33.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  34. 34.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) test on many groups (d) use one group only
  35. 35.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  37. 37.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  38. 38.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  39. 39.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  40. 40.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data

Answer key

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

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