AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 816 · 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 balanced data (fairer for everyone). (a) False (b) True
2. 2.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
3. 3.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) check who is missing (d) skip testing
4. 4.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) balance the data (d) test on one group only
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
6. 6.True or false: “check who is missing” helps reduce bias. (a) True (b) False
7. 7.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
8. 8.Which of these adds to bias? (a) add more of the same (b) add varied examples (c) check who is missing (d) fix wrong labels
9. 9.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add more of the same (d) fix wrong labels
10. 10.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
11. 11.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
12. 12.Which of these adds to bias? (a) test on many groups (b) ask different people (c) skip testing (d) check who is missing
13. 13.True or false: “fix wrong labels” adds to bias. (a) False (b) True
14. 14.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.True or false: “use one group only” adds to bias. (a) False (b) True
16. 16.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) test on one group only
17. 17.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
18. 18.True or false: “test on one group only” helps reduce bias. (a) True (b) False
19. 19.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
20. 20.Which of these adds to bias? (a) ask different people (b) balance the data (c) check who is missing (d) ignore complaints
21. 21.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
24. 24.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
25. 25.Which of these helps reduce bias? (a) skip testing (b) check who is missing (c) test on one group only (d) ignore complaints
26. 26.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
27. 27.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
28. 28.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
30. 30.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
31. 31.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) balance the data (d) skip testing
33. 33.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
34. 34.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
35. 35.True or false: “ignore complaints” adds to bias. (a) True (b) False
36. 36.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
37. 37.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
38. 38.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) test on one group only (d) add more of the same
39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
40. 40.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias

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