AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 869 · 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.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
2. 2.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
3. 3.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
4. 4.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
6. 6.True or false: “add varied examples” adds to bias. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) ask different people (d) add varied examples
8. 8.Which of these adds to bias? (a) ask different people (b) skip testing (c) check who is missing (d) test on many groups
9. 9.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
10. 10.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
11. 11.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.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
14. 14.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
15. 15.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
16. 16.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) balance the data (d) test on many groups
17. 17.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) add varied examples (d) ask different people
18. 18.Which of these adds to bias? (a) add varied examples (b) ignore complaints (c) fix wrong labels (d) check who is missing
19. 19.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) add more of the same (d) ask different people
20. 20.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
22. 22.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) test on many groups (d) use one group only
23. 23.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
24. 24.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
26. 26.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
27. 27.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) add more of the same (d) ignore complaints
28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
29. 29.Which of these adds to bias? (a) balance the data (b) ask different people (c) copy old unfair choices (d) test on many groups
30. 30.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) check who is missing (d) copy old unfair choices
32. 32.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
33. 33.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
35. 35.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
36. 36.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
37. 37.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
38. 38.True or false: “check who is missing” helps reduce bias. (a) False (b) True
39. 39.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) fix wrong labels
40. 40.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data

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