AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 211 · 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.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
2. 2.True or false: “add varied examples” helps reduce bias. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) skip testing (d) test on one group only
4. 4.True or false: “ignore complaints” adds to bias. (a) True (b) False
5. 5.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) test on one group only (d) use one group only
6. 6.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) add varied examples (d) check who is missing
7. 7.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
9. 9.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) ask different people (d) balance the data
10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
11. 11.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
12. 12.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
13. 13.True or false: “check who is missing” helps reduce bias. (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
15. 15.Which of these adds to bias? (a) test on many groups (b) copy old unfair choices (c) add varied examples (d) fix wrong labels
16. 16.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
17. 17.True or false: “test on one group only” adds to bias. (a) False (b) True
18. 18.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
19. 19.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) use one group only (d) fix wrong labels
20. 20.True or false: “test on many groups” helps reduce bias. (a) False (b) True
21. 21.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) balance the data (d) add varied examples
22. 22.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) balance the data (d) ignore complaints
23. 23.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.True or false: “check who is missing” adds to bias. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) test on many groups (d) test on one group only
26. 26.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) ask different people (d) use one group only
27. 27.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
28. 28.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
29. 29.Which of these helps reduce bias? (a) check who is missing (b) use one group only (c) copy old unfair choices (d) skip testing
30. 30.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ignore complaints (d) check who is missing
31. 31.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
32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
33. 33.True or false: “ask different people” helps reduce bias. (a) True (b) False
34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
35. 35.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
36. 36.True or false: “skip testing” adds to bias. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) ignore complaints (d) add varied examples
38. 38.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
39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False

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