AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 213 · 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: photos of people from only one age group? (a) one-sided data (b) balanced data
2. 2.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
3. 3.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
4. 4.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) balance the data (d) skip testing
5. 5.True or false: “fix wrong labels” adds to bias. (a) True (b) False
6. 6.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
7. 7.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
8. 8.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
9. 9.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
10. 10.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
11. 11.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
13. 13.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
14. 14.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
16. 16.Which of these adds to bias? (a) test on many groups (b) balance the data (c) test on one group only (d) ask different people
17. 17.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
18. 18.True or false: “test on one group only” adds to bias. (a) False (b) True
19. 19.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
20. 20.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
21. 21.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
22. 22.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
23. 23.True or false: “skip testing” adds to bias. (a) False (b) True
24. 24.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) ask different people (d) ignore complaints
25. 25.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
26. 26.Which of these adds to bias? (a) add more of the same (b) test on many groups (c) ask different people (d) balance the data
27. 27.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) add more of the same (d) test on one group only
28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
29. 29.Which of these adds to bias? (a) copy old unfair choices (b) balance the data (c) fix wrong labels (d) add varied examples
30. 30.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
31. 31.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
32. 32.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) use one group only (d) skip testing
33. 33.True or false: “test on one group only” helps reduce bias. (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) test on many groups (d) test on one group only
35. 35.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) fix wrong labels (d) test on one group only
36. 36.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) check who is missing
37. 37.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
39. 39.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
40. 40.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True

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