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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 229 · 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.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  2. 2.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  3. 3.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) test on many groups (d) add more of the same
  4. 4.True or false: “ask different people” adds to bias. (a) False (b) True
  5. 5.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  6. 6.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  7. 7.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a broken screen (d) a strong battery
  9. 9.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  10. 10.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  11. 11.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  12. 12.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  13. 13.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  14. 14.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  15. 15.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) add varied examples (d) skip testing
  16. 16.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
  17. 17.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) balance the data (d) skip testing
  18. 18.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) balance the data (d) add varied examples
  19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
  20. 20.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  22. 22.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  24. 24.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  25. 25.True or false: “add more of the same” adds to bias. (a) False (b) True
  26. 26.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  27. 27.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) balance the data (d) use one group only
  28. 28.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  29. 29.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  30. 30.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  31. 31.True or false: “check who is missing” adds to bias. (a) True (b) False
  32. 32.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  33. 33.🗣️ 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
  34. 34.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) ignore complaints (d) add more of the same
  35. 35.Which of these adds to bias? (a) ask different people (b) ignore complaints (c) add varied examples (d) balance the data
  36. 36.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  37. 37.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  38. 38.Which of these adds to bias? (a) copy old unfair choices (b) test on many groups (c) check who is missing (d) ask different people
  39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  40. 40.True or false: “balance the data” helps reduce bias. (a) False (b) True

Answer key

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

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