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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 84 · 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: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  3. 3.True or false: “skip testing” adds to bias. (a) False (b) True
  4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
  5. 5.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  6. 6.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  7. 7.True or false: “balance the data” helps reduce bias. (a) False (b) True
  8. 8.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
  9. 9.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  10. 10.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) skip testing (d) add more of the same
  11. 11.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  12. 12.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  13. 13.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  14. 14.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  17. 17.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
  18. 18.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) use one group only (d) balance the data
  19. 19.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) ignore complaints (d) use one group only
  20. 20.True or false: “add varied examples” adds to bias. (a) True (b) False
  21. 21.True or false: “test on one group only” adds to bias. (a) False (b) True
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather
  24. 24.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) test on one group only (d) ignore complaints
  25. 25.🔍 Which is the odd one out? (a) ask different people (b) test on one group only (c) add varied examples (d) test on many groups
  26. 26.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) use one group only (d) add varied examples
  27. 27.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add varied examples (d) ignore complaints
  29. 29.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) add more of the same (d) check who is missing
  30. 30.True or false: “test on many groups” adds to bias. (a) False (b) True
  31. 31.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  32. 32.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  34. 34.True or false: “add more of the same” helps reduce bias. (a) True (b) False
  35. 35.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  36. 36.True or false: “ignore complaints” adds to bias. (a) True (b) False
  37. 37.True or false: “check who is missing” adds to bias. (a) False (b) True
  38. 38.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) ignore complaints (d) add more of the same
  39. 39.🔍 Which is the odd one out? (a) skip testing (b) fix wrong labels (c) add more of the same (d) use one group only
  40. 40.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data

Answer key

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

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