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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 322 · 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.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  2. 2.Which of these adds to bias? (a) ask different people (b) add more of the same (c) balance the data (d) fix wrong labels
  3. 3.True or false: “ask different people” helps reduce bias. (a) True (b) False
  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: “check who is missing” helps reduce bias. (a) True (b) False
  6. 6.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) balance the data (d) check who is missing
  7. 7.True or false: “skip testing” helps reduce bias. (a) False (b) True
  8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  9. 9.Which of these helps reduce bias? (a) ask different people (b) skip testing (c) test on one group only (d) add more of the same
  10. 10.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) test on one group only (d) check who is missing
  11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
  12. 12.True or false: “balance the data” helps reduce bias. (a) False (b) True
  13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  14. 14.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  15. 15.Which of these adds to bias? (a) add varied examples (b) copy old unfair choices (c) test on many groups (d) check who is missing
  16. 16.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  17. 17.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  18. 18.Which of these helps reduce bias? (a) skip testing (b) fix wrong labels (c) test on one group only (d) add more of the same
  19. 19.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  20. 20.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  21. 21.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  22. 22.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  23. 23.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  24. 24.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) add varied examples (d) balance the data
  25. 25.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  26. 26.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  27. 27.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) ignore complaints (d) copy old unfair choices
  29. 29.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) balance the data (d) skip testing
  30. 30.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) add varied examples (d) skip testing
  31. 31.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  32. 32.True or false: “use one group only” adds to bias. (a) False (b) True
  33. 33.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) skip testing (d) copy old unfair choices
  34. 34.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  35. 35.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
  36. 36.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  37. 37.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  38. 38.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
  39. 39.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  40. 40.Which of these adds to bias? (a) add varied examples (b) balance the data (c) ask different people (d) use one group only

Answer key

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

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