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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 569 · 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 is the odd one out? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) add varied examples
  2. 2.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
  3. 3.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  4. 4.Which of these adds to bias? (a) fix wrong labels (b) ignore complaints (c) check who is missing (d) ask different people
  5. 5.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
  6. 6.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
  8. 8.Which of these adds to bias? (a) test on many groups (b) copy old unfair choices (c) fix wrong labels (d) add varied examples
  9. 9.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  10. 10.True or false: “ask different people” adds to bias. (a) False (b) True
  11. 11.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  12. 12.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
  14. 14.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  15. 15.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  16. 16.True or false: “ask different people” helps reduce bias. (a) True (b) False
  17. 17.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) use one group only (d) add varied examples
  18. 18.True or false: “balance the data” adds to bias. (a) False (b) True
  19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  20. 20.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  21. 21.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  22. 22.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
  23. 23.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  24. 24.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) add varied examples (d) copy old unfair choices
  25. 25.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
  26. 26.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  27. 27.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) ask different people (d) balance the data
  28. 28.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  29. 29.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  30. 30.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  33. 33.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  34. 34.Which of these adds to bias? (a) test on many groups (b) skip testing (c) add varied examples (d) balance the data
  35. 35.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  36. 36.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  37. 37.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  38. 38.True or false: “skip testing” adds to bias. (a) True (b) False
  39. 39.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  40. 40.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

Answer key

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

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