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AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 247 · 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.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  2. 2.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  3. 3.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) add varied examples (d) skip testing
  4. 4.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  5. 5.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
  6. 6.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  7. 7.True or false: “test on many groups” adds to bias. (a) True (b) False
  8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  9. 9.Which of these adds to bias? (a) balance the data (b) test on many groups (c) check who is missing (d) copy old unfair choices
  10. 10.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  11. 11.True or false: “use one group only” adds to bias. (a) True (b) False
  12. 12.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  15. 15.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) add more of the same
  16. 16.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  17. 17.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) test on many groups (d) use one group only
  18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  20. 20.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  21. 21.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
  24. 24.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
  25. 25.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
  26. 26.True or false: “test on one group only” adds to bias. (a) False (b) True
  27. 27.True or false: “balance the data” adds to bias. (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) ignore complaints
  29. 29.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
  30. 30.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) fix wrong labels (d) test on one group only
  31. 31.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
  32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  33. 33.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) skip testing (d) fix wrong labels
  34. 34.True or false: “balance the data” helps reduce bias. (a) True (b) False
  35. 35.True or false: “check who is missing” adds to bias. (a) True (b) False
  36. 36.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  37. 37.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  38. 38.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  39. 39.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  40. 40.Which of these helps reduce bias? (a) test on one group only (b) ask different people (c) add more of the same (d) skip testing

Answer key

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

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