AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 490 · 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 is the odd one out? (a) balance the data (b) ignore complaints (c) copy old unfair choices (d) skip testing
2. 2.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
3. 3.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
4. 4.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
5. 5.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
6. 6.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
7. 7.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) add varied examples (d) use one group only
8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
10. 10.🖼️ 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
11. 11.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
12. 12.True or false: “test on many groups” helps reduce bias. (a) True (b) False
13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
14. 14.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
15. 15.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
16. 16.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
17. 17.Which of these helps reduce bias? (a) ignore complaints (b) balance the data (c) skip testing (d) copy old unfair choices
18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
19. 19.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
20. 20.True or false: “balance the data” helps reduce bias. (a) False (b) True
21. 21.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) add varied examples (d) use one group only
22. 22.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) add varied examples (d) fix wrong labels
23. 23.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) balance the data (d) test on many groups
24. 24.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
25. 25.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) add varied examples (d) test on many groups
26. 26.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
27. 27.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
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.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) copy old unfair choices (d) ask different people
31. 31.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) skip testing (d) check who is missing
32. 32.True or false: “balance the data” adds to bias. (a) False (b) True
33. 33.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
34. 34.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) skip testing (d) copy old unfair choices
35. 35.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) add varied examples (d) check who is missing
36. 36.True or false: “add more of the same” helps reduce bias. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) ignore complaints (d) use one group only
38. 38.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
39. 39.True or false: “ask different people” helps reduce bias. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) ask different people (b) use one group only (c) copy old unfair choices (d) add more of the same

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