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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 777 · 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: balance the data? (a) adds to bias (b) reduces bias
  2. 2.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
  3. 3.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) test on one group only (d) skip testing
  4. 4.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  5. 5.True or false: “add varied examples” adds to bias. (a) False (b) True
  6. 6.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) fix wrong labels (d) ignore complaints
  7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) ask different people (d) test on one group only
  8. 8.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
  9. 9.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  10. 10.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  11. 11.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) ignore complaints (d) add varied examples
  12. 12.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided 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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  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.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  18. 18.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
  19. 19.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  20. 20.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) add varied examples (d) add more of the same
  21. 21.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
  22. 22.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) balance the data (d) add varied examples
  23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  24. 24.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) fix wrong labels (d) check who is missing
  26. 26.True or false: “add more of the same” helps reduce bias. (a) False (b) True
  27. 27.🖼️ 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
  28. 28.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.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
  30. 30.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on one group only (d) ask different people
  31. 31.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  32. 32.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
  35. 35.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
  36. 36.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  37. 37.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  38. 38.True or false: “ask different people” helps reduce bias. (a) True (b) False
  39. 39.True or false: “balance the data” helps reduce bias. (a) True (b) False
  40. 40.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data

Answer key

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

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