AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 245 · 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.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
2. 2.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
3. 3.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) add varied examples (d) ask different people
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
6. 6.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) ask different people (d) ignore complaints
7. 7.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) ask different people (d) ignore complaints
8. 8.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) add more of the same (d) fix wrong labels
9. 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
10. 10.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
11. 11.True or false: “add varied examples” helps reduce bias. (a) False (b) True
12. 12.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
13. 13.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) ignore complaints (d) balance the data
14. 14.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
15. 15.True or false: “use one group only” adds to bias. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) ask different people (d) fix wrong labels
17. 17.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) skip testing
18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
19. 19.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
20. 20.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
21. 21.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) add more of the same (d) test on one group only
22. 22.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
23. 23.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
24. 24.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
25. 25.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
26. 26.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
27. 27.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
29. 29.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
30. 30.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
31. 31.Which of these adds to bias? (a) ask different people (b) use one group only (c) fix wrong labels (d) test on many groups
32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
33. 33.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
34. 34.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
35. 35.True or false: “add more of the same” adds to bias. (a) False (b) True
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.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
38. 38.Which of these adds to bias? (a) add more of the same (b) ask different people (c) balance the data (d) add varied examples
39. 39.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) test on many groups (d) use one group only
40. 40.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias

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