AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 693 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
3. 3.True or false: “use one group only” helps reduce bias. (a) False (b) True
4. 4.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
5. 5.🗣️ 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) the phone was new (d) children speak too fast
6. 6.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) test on one group only (d) add varied examples
8. 8.Which of these adds to bias? (a) ask different people (b) add varied examples (c) skip testing (d) test on many groups
9. 9.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
10. 10.Which of these adds to bias? (a) check who is missing (b) ask different people (c) fix wrong labels (d) ignore complaints
11. 11.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) test on one group only (d) use one group only
12. 12.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) skip testing (d) ask different people
13. 13.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
14. 14.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ask different people (d) skip testing
15. 15.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) balance the data (d) ignore complaints
16. 16.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
17. 17.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) skip testing (d) fix wrong labels
18. 18.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
22. 22.True or false: “skip testing” adds to bias. (a) False (b) True
23. 23.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
24. 24.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
25. 25.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
26. 26.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
27. 27.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
29. 29.Which of these adds to bias? (a) check who is missing (b) balance the data (c) test on many groups (d) use one group only
30. 30.True or false: “use one group only” adds to bias. (a) False (b) True
31. 31.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
32. 32.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
33. 33.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
34. 34.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
35. 35.Which of these helps reduce bias? (a) ignore complaints (b) balance the data (c) add more of the same (d) use one group only
36. 36.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) ask different people (d) test on many groups
37. 37.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) use one group only (d) copy old unfair choices
38. 38.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) balance the data
39. 39.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) use one group only (d) balance the data

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