AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 604 · 40 questions

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.

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

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