AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 400 · 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.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
2. 2.True or false: “balance the data” adds to bias. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) check who is missing (d) test on many groups
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.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) fix wrong labels (d) test on many groups
6. 6.True or false: “ask different people” adds to bias. (a) True (b) False
7. 7.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
8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
9. 9.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
10. 10.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
12. 12.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
14. 14.True or false: “use one group only” adds to bias. (a) False (b) True
15. 15.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
16. 16.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) ignore complaints (d) balance the data
18. 18.True or false: “test on many groups” adds to bias. (a) False (b) True
19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
20. 20.True or false: “add varied examples” adds to bias. (a) True (b) False
21. 21.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) balance the data (d) use one group only
22. 22.Which of these helps reduce bias? (a) add more of the same (b) balance the data (c) skip testing (d) use one group only
23. 23.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) check who is missing (d) add varied examples
24. 24.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) copy old unfair choices
25. 25.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) skip testing (d) copy old unfair choices
26. 26.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) fix wrong labels (d) skip testing
27. 27.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
28. 28.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
29. 29.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
30. 30.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) check who is missing
32. 32.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
33. 33.Which of these helps reduce bias? (a) ask different people (b) add more of the same (c) copy old unfair choices (d) ignore complaints
34. 34.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
35. 35.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
36. 36.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
37. 37.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
38. 38.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
39. 39.🗣️ 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
40. 40.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

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