AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 412 · 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) add more of the same (b) use one group only (c) test on many groups (d) copy old unfair choices
2. 2.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) ignore complaints (d) balance the data
3. 3.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
4. 4.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
5. 5.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) add more of the same (d) add varied examples
6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
7. 7.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
8. 8.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
9. 9.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
10. 10.True or false: “test on many groups” helps reduce bias. (a) True (b) False
11. 11.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
12. 12.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
13. 13.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ask different people (d) copy old unfair choices
14. 14.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
15. 15.🗣️ 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) it was a rainy day (d) the phone was new
16. 16.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) check who is missing (d) use one group only
17. 17.True or false: “test on one group only” helps reduce bias. (a) True (b) False
18. 18.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
20. 20.True or false: “check who is missing” helps reduce bias. (a) False (b) True
21. 21.Which of these adds to bias? (a) ask different people (b) check who is missing (c) copy old unfair choices (d) balance the data
22. 22.True or false: “skip testing” helps reduce bias. (a) True (b) False
23. 23.True or false: “add varied examples” helps reduce bias. (a) False (b) True
24. 24.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) skip testing (d) balance the data
25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
26. 26.🔍 Which is the odd one out? (a) ask different people (b) test on one group only (c) skip testing (d) copy old unfair choices
27. 27.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
29. 29.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
30. 30.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) use one group only (d) fix wrong labels
31. 31.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) add more of the same (d) test on many groups
33. 33.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) skip testing (d) add varied examples
34. 34.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
35. 35.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
36. 36.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
37. 37.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
39. 39.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) skip testing (d) add varied examples
40. 40.Which of these adds to bias? (a) add varied examples (b) test on one group only (c) balance the data (d) test on many groups

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