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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 433 · 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 of these helps reduce bias? (a) skip testing (b) add more of the same (c) add varied examples (d) ignore complaints
  2. 2.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  3. 3.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  4. 4.True or false: “skip testing” helps reduce bias. (a) False (b) True
  5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
  6. 6.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) add more of the same (d) test on many groups
  8. 8.Which of these adds to bias? (a) ask different people (b) check who is missing (c) test on one group only (d) balance the data
  9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  10. 10.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) ignore complaints (d) copy old unfair choices
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  12. 12.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  13. 13.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  14. 14.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  16. 16.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
  17. 17.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  18. 18.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) use one group only (d) copy old unfair choices
  19. 19.True or false: “skip testing” adds to bias. (a) True (b) False
  20. 20.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) balance the data (d) ignore complaints
  21. 21.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  22. 22.True or false: “ignore complaints” adds to bias. (a) False (b) True
  23. 23.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) check who is missing (d) use one group only
  24. 24.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) copy old unfair choices (d) add varied examples
  25. 25.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  26. 26.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  27. 27.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) skip testing (d) fix wrong labels
  28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  29. 29.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
  30. 30.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  31. 31.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) ignore complaints (d) test on one group only
  32. 32.True or false: “add varied examples” adds to bias. (a) False (b) True
  33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  34. 34.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) copy old unfair choices (d) add more of the same
  35. 35.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  36. 36.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  37. 37.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  38. 38.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) test on many groups (d) test on one group only
  39. 39.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  40. 40.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) use one group only (d) balance the data

Answer key

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

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