AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 695 · 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) use one group only (b) ask different people (c) add more of the same (d) copy old unfair choices
2. 2.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) balance the data (d) use one group only
3. 3.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
4. 4.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
6. 6.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
7. 7.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
8. 8.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
9. 9.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
10. 10.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
11. 11.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) balance the data
13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
14. 14.Which of these adds to bias? (a) balance the data (b) add varied examples (c) ignore complaints (d) check who is missing
15. 15.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
16. 16.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) skip testing (d) test on many groups
17. 17.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
18. 18.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
19. 19.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) balance the data (d) check who is missing
20. 20.True or false: “test on one group only” helps reduce bias. (a) True (b) False
21. 21.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
22. 22.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
24. 24.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) check who is missing (d) ignore complaints
26. 26.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
27. 27.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) ignore complaints (d) copy old unfair choices
28. 28.True or false: “check who is missing” adds to bias. (a) True (b) False
29. 29.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
30. 30.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
31. 31.True or false: “use one group only” adds to bias. (a) True (b) False
32. 32.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (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.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
35. 35.Which of these adds to bias? (a) skip testing (b) balance the data (c) test on many groups (d) ask different people
36. 36.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
37. 37.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
38. 38.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) balance the data (d) ask different people
39. 39.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) check who is missing (d) ignore complaints
40. 40.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes

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