AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 994 · 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 is the odd one out? (a) add varied examples (b) ignore complaints (c) test on many groups (d) balance the data
2. 2.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
4. 4.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) copy old unfair choices (d) ask different people
5. 5.True or false: “use one group only” helps reduce bias. (a) True (b) False
6. 6.🗣️ 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
7. 7.Which of these helps reduce bias? (a) balance the data (b) add more of the same (c) copy old unfair choices (d) ignore complaints
8. 8.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) test on one group only (d) check who is missing
9. 9.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) balance the data (d) copy old unfair choices
10. 10.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) add more of the same (d) fix wrong labels
11. 11.Which of these helps reduce bias? (a) add varied examples (b) add more of the same (c) copy old unfair choices (d) test on one group only
12. 12.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) ignore complaints (d) add more of the same
13. 13.True or false: “use one group only” adds to bias. (a) False (b) True
14. 14.True or false: “test on one group only” helps reduce bias. (a) True (b) False
15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
16. 16.Which of these adds to bias? (a) test on many groups (b) ask different people (c) use one group only (d) fix wrong labels
17. 17.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
18. 18.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
19. 19.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
20. 20.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
22. 22.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
24. 24.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
25. 25.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) add varied examples (d) test on many groups
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: “ignore complaints” adds to bias. (a) True (b) False
28. 28.True or false: “test on many groups” helps reduce bias. (a) True (b) False
29. 29.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
30. 30.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) test on one group only (d) add varied examples
32. 32.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) test on one group only (d) add varied examples
33. 33.Which of these adds to bias? (a) ignore complaints (b) test on many groups (c) ask different people (d) fix wrong labels
34. 34.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
35. 35.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
36. 36.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
37. 37.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
38. 38.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
39. 39.True or false: “add more of the same” adds to bias. (a) False (b) True
40. 40.True or false: “ask different people” helps reduce bias. (a) False (b) True

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