AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 346 · 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 fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
3. 3.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) balance the data (d) add varied examples
4. 4.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
5. 5.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
6. 6.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) ignore complaints (d) copy old unfair choices
7. 7.True or false: “test on many groups” helps reduce bias. (a) True (b) False
8. 8.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
11. 11.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
12. 12.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) add more of the same (d) balance the data
13. 13.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
14. 14.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) copy old unfair choices (d) balance the data
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: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
18. 18.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) add varied examples (d) ignore complaints
19. 19.True or false: “test on one group only” helps reduce bias. (a) True (b) False
20. 20.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
22. 22.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) ask different people (d) test on one group only
23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
24. 24.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
25. 25.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
26. 26.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) check who is missing (d) skip testing
27. 27.True or false: “balance the data” adds to bias. (a) False (b) True
28. 28.Which of these adds to bias? (a) balance the data (b) test on many groups (c) add more of the same (d) fix wrong labels
29. 29.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
30. 30.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
31. 31.Which of these adds to bias? (a) add varied examples (b) use one group only (c) ask different people (d) fix wrong labels
32. 32.🔍 Which is the odd one out? (a) ask different people (b) test on one group only (c) check who is missing (d) balance the data
33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
34. 34.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) check who is missing (d) use one group only
35. 35.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
36. 36.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
38. 38.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
39. 39.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) ignore complaints (d) add more of the same
40. 40.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) copy old unfair choices (d) ask different people

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