AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 338 · 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
2. 2.True or false: “use one group only” adds to bias. (a) True (b) False
3. 3.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
5. 5.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
6. 6.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
7. 7.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) check who is missing (d) test on one group only
8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
9. 9.True or false: “add more of the same” helps reduce bias. (a) True (b) False
10. 10.Which of these helps reduce bias? (a) ask different people (b) skip testing (c) ignore complaints (d) use one group only
11. 11.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
12. 12.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
13. 13.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
14. 14.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) use one group only
15. 15.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
16. 16.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
18. 18.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
19. 19.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) add varied examples (d) ignore complaints
20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
22. 22.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) ask different people (d) fix wrong labels
25. 25.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) ignore complaints (d) fix wrong labels
26. 26.Which of these adds to bias? (a) skip testing (b) add varied examples (c) check who is missing (d) test on many groups
27. 27.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
28. 28.Which of these adds to bias? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) test on many groups
29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
30. 30.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
31. 31.Which of these adds to bias? (a) ask different people (b) test on one group only (c) fix wrong labels (d) balance the data
32. 32.True or false: “add more of the same” adds to bias. (a) True (b) False
33. 33.True or false: “ask different people” helps reduce bias. (a) True (b) False
34. 34.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
35. 35.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) test on many groups (d) skip testing
36. 36.Which of these adds to bias? (a) check who is missing (b) balance the data (c) ask different people (d) use one group only
37. 37.True or false: “test on one group only” helps reduce bias. (a) True (b) False
38. 38.Which of these helps reduce bias? (a) test on one group only (b) fix wrong labels (c) skip testing (d) copy old unfair choices
39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data

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