AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 974 · 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.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
2. 2.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
3. 3.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
5. 5.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
6. 6.True or false: “use one group only” adds to bias. (a) True (b) False
7. 7.True or false: “fix wrong labels” adds to bias. (a) False (b) True
8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
10. 10.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
11. 11.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
12. 12.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
13. 13.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
16. 16.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
17. 17.True or false: “test on many groups” helps reduce bias. (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) add varied examples (d) fix wrong labels
19. 19.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) add varied examples (d) test on one group only
20. 20.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
21. 21.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) test on one group only (d) add more of the same
22. 22.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
24. 24.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) use one group only (d) test on one group only
25. 25.Which of these adds to bias? (a) copy old unfair choices (b) balance the data (c) add varied examples (d) ask different people
26. 26.True or false: “ignore complaints” adds to bias. (a) False (b) True
27. 27.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) fix wrong labels (d) add varied examples
28. 28.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
29. 29.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) check who is missing (d) skip testing
31. 31.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
32. 32.True or false: “balance the data” helps reduce bias. (a) True (b) False
33. 33.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
34. 34.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
35. 35.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) test on one group only (d) ask different people
36. 36.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) add varied examples (d) check who is missing
38. 38.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
39. 39.Which of these helps reduce bias? (a) add more of the same (b) test on many groups (c) ignore complaints (d) skip testing
40. 40.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data

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