AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 593 · 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.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
2. 2.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) check who is missing (d) copy old unfair choices
3. 3.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
4. 4.Which of these adds to bias? (a) test on many groups (b) use one group only (c) fix wrong labels (d) check who is missing
5. 5.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) skip testing (d) add more of the same
6. 6.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
7. 7.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
8. 8.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) copy old unfair choices (d) add varied examples
9. 9.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
10. 10.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
11. 11.True or false: “use one group only” helps reduce bias. (a) False (b) True
12. 12.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
14. 14.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
15. 15.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) add more of the same (d) balance the data
16. 16.True or false: “balance the data” adds to bias. (a) False (b) True
17. 17.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
18. 18.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.True or false: “check who is missing” adds to bias. (a) True (b) False
20. 20.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) test on one group only
21. 21.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
22. 22.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) copy old unfair choices (d) skip testing
24. 24.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) skip testing
25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
26. 26.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
28. 28.True or false: “add varied examples” helps reduce bias. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) use one group only (d) ask different people
30. 30.Which of these helps reduce bias? (a) skip testing (b) balance the data (c) use one group only (d) copy old unfair choices
31. 31.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
32. 32.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
34. 34.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
35. 35.True or false: “check who is missing” helps reduce bias. (a) True (b) False
36. 36.Which of these adds to bias? (a) add varied examples (b) balance the data (c) ask different people (d) copy old unfair choices
37. 37.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on one group only (d) fix wrong labels
38. 38.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) skip testing (d) add varied examples
39. 39.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) test on many groups (d) copy old unfair choices
40. 40.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias

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