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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 588 · 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: fix wrong labels? (a) reduces bias (b) adds to bias
  2. 2.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  3. 3.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  4. 4.True or false: “add varied examples” helps reduce bias. (a) True (b) False
  5. 5.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  6. 6.🖼️ 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
  7. 7.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  8. 8.Which of these adds to bias? (a) check who is missing (b) skip testing (c) balance the data (d) fix wrong labels
  9. 9.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  10. 10.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  11. 11.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
  12. 12.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) add more of the same (d) fix wrong labels
  14. 14.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) fix wrong labels (d) ignore complaints
  15. 15.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  16. 16.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) ignore complaints (d) skip testing
  17. 17.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
  18. 18.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add more of the same (d) test on many groups
  19. 19.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) ignore complaints (d) use one group only
  20. 20.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  21. 21.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  22. 22.True or false: “add varied examples” adds to bias. (a) False (b) True
  23. 23.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
  24. 24.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
  25. 25.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  26. 26.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  27. 27.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) add varied examples (d) copy old unfair choices
  29. 29.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  30. 30.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) test on one group only (d) add varied examples
  31. 31.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  32. 32.Which of these adds to bias? (a) check who is missing (b) balance the data (c) test on many groups (d) add more of the same
  33. 33.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  35. 35.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  36. 36.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  38. 38.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) balance the data (d) skip testing
  39. 39.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) add varied examples (d) ask different people

Answer key

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

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