AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 405 · 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.🗣️ 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) few child voices in data (d) the phone was new
2. 2.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
3. 3.Which of these adds to bias? (a) skip testing (b) check who is missing (c) balance the data (d) fix wrong labels
4. 4.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
5. 5.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) ignore complaints (d) use one group only
6. 6.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
7. 7.True or false: stories where every doctor is a man 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: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) a fair model (d) bias from data
11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
12. 12.True or false: “balance the data” adds to bias. (a) True (b) False
13. 13.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) fix wrong labels (d) ignore complaints
14. 14.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) add more of the same (d) balance the data
15. 15.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
16. 16.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
17. 17.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
19. 19.Which of these helps reduce bias? (a) check who is missing (b) test on one group only (c) ignore complaints (d) skip testing
20. 20.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
21. 21.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) ask different people (d) test on many groups
22. 22.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
23. 23.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
24. 24.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) balance the data (d) add more of the same
25. 25.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) test on one group only (d) check who is missing
26. 26.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
27. 27.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
28. 28.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
29. 29.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) use one group only
30. 30.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) check who is missing (d) fix wrong labels
31. 31.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
32. 32.True or false: “test on one group only” adds to bias. (a) False (b) True
33. 33.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
34. 34.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) check who is missing (d) copy old unfair choices
35. 35.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
36. 36.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) fix wrong labels (d) ignore complaints
37. 37.Which of these adds to bias? (a) add more of the same (b) fix wrong labels (c) check who is missing (d) add varied examples
38. 38.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
39. 39.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
40. 40.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False

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