AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 751 · 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.Which of these adds to bias? (a) ask different people (b) add varied examples (c) check who is missing (d) copy old unfair choices
2. 2.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) ask different people (d) skip testing
4. 4.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
5. 5.🗣️ 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
6. 6.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
7. 7.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
8. 8.True or false: “ask different people” helps reduce bias. (a) True (b) False
9. 9.True or false: “balance the data” adds to bias. (a) False (b) True
10. 10.True or false: “test on many groups” helps reduce bias. (a) False (b) True
11. 11.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
12. 12.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) fix wrong labels (d) skip testing
13. 13.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
14. 14.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
15. 15.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) add varied examples (d) ignore complaints
16. 16.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
17. 17.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
18. 18.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) use one group only (d) check who is missing
20. 20.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) skip testing (d) check who is missing
22. 22.Which of these adds to bias? (a) add more of the same (b) test on many groups (c) balance the data (d) add varied examples
23. 23.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) test on many groups (d) copy old unfair choices
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.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
26. 26.True or false: “check who is missing” helps reduce bias. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
28. 28.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
30. 30.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) fix wrong labels (d) use one group only
31. 31.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) balance the data (d) test on one group only
32. 32.True or false: “ask different people” adds to bias. (a) True (b) False
33. 33.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
34. 34.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
35. 35.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
36. 36.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) add varied examples (d) check who is missing
37. 37.True or false: “test on one group only” helps reduce bias. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) balance the data (d) test on one group only
39. 39.True or false: “test on one group only” adds to bias. (a) True (b) False
40. 40.True or false: “ignore complaints” helps reduce bias. (a) True (b) False

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