AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 677 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
2. 2.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) add more of the same (d) ask different people
3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
5. 5.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
6. 6.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
7. 7.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
8. 8.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) ask different people (d) balance the data
9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
10. 10.Which of these adds to bias? (a) balance the data (b) test on many groups (c) check who is missing (d) skip testing
11. 11.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
12. 12.Which of these adds to bias? (a) ask different people (b) balance the data (c) add more of the same (d) check who is missing
13. 13.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
14. 14.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
16. 16.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
18. 18.True or false: “add varied examples” helps reduce bias. (a) False (b) True
19. 19.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
22. 22.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
24. 24.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
25. 25.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) copy old unfair choices (d) skip testing
26. 26.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
27. 27.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) test on many groups (d) test on one group only
28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
29. 29.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
30. 30.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
31. 31.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
32. 32.True or false: “balance the data” adds to bias. (a) False (b) True
33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
34. 34.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
35. 35.True or false: “balance the data” helps reduce bias. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) copy old unfair choices (d) ignore complaints
37. 37.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) check who is missing (d) add more of the same
38. 38.Which of these adds to bias? (a) check who is missing (b) ignore complaints (c) ask different people (d) test on many groups
39. 39.True or false: “test on one group only” adds to bias. (a) False (b) True
40. 40.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True

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