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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 134 · 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 adds to bias? (a) check who is missing (b) ask different people (c) fix wrong labels (d) use one group only
  2. 2.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
  3. 3.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  4. 4.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) use one group only
  5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  6. 6.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  7. 7.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) ask different people (d) ignore complaints
  8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  9. 9.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) balance the data (d) test on one group only
  10. 10.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  11. 11.True or false: “check who is missing” adds to bias. (a) False (b) True
  12. 12.True or false: “skip testing” helps reduce bias. (a) True (b) False
  13. 13.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  14. 14.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  15. 15.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  16. 16.True or false: “ask different people” helps reduce bias. (a) True (b) False
  17. 17.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
  18. 18.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  20. 20.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add varied examples (d) test on one group only
  21. 21.🖼️ 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
  22. 22.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) add varied examples (d) fix wrong labels
  23. 23.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  24. 24.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
  25. 25.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  26. 26.True or false: “balance the data” helps reduce bias. (a) False (b) True
  27. 27.🗣️ 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
  28. 28.True or false: “add varied examples” adds to bias. (a) False (b) True
  29. 29.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) balance the data (d) check who is missing
  30. 30.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
  31. 31.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) test on many groups (d) skip testing
  32. 32.Which of these helps reduce bias? (a) add more of the same (b) test on many groups (c) test on one group only (d) skip testing
  33. 33.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  34. 34.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  35. 35.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  36. 36.Which of these adds to bias? (a) check who is missing (b) add more of the same (c) test on many groups (d) ask different people
  37. 37.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) ask different people (d) test on many groups
  39. 39.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  40. 40.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather

Answer key

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

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