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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 613 · 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: add varied examples? (a) adds to bias (b) reduces bias
  2. 2.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) ask different people (d) add varied examples
  3. 3.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) few child voices in data (d) it was a rainy day
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  6. 6.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) balance the data (d) ask different people
  7. 7.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  8. 8.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
  9. 9.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  10. 10.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  12. 12.True or false: “add varied examples” adds to bias. (a) False (b) True
  13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
  15. 15.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  16. 16.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  18. 18.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) add more of the same (d) test on one group only
  19. 19.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
  20. 20.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  21. 21.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  22. 22.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  23. 23.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) check who is missing (d) copy old unfair choices
  24. 24.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  25. 25.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) test on one group only (d) copy old unfair choices
  26. 26.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) skip testing (d) ignore complaints
  28. 28.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  29. 29.True or false: “check who is missing” adds to bias. (a) False (b) True
  30. 30.True or false: “balance the data” adds to bias. (a) True (b) False
  31. 31.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) copy old unfair choices (d) add more of the same
  32. 32.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) use one group only (d) ask different people
  33. 33.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  34. 34.True or false: “use one group only” adds to bias. (a) False (b) True
  35. 35.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  37. 37.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  39. 39.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  40. 40.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data

Answer key

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

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