AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 616 · 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) copy old unfair choices (b) add more of the same (c) fix wrong labels (d) ignore complaints
2. 2.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) skip testing (d) use one group only
3. 3.Which of these adds to bias? (a) check who is missing (b) balance the data (c) test on many groups (d) ignore complaints
4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
5. 5.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) check who is missing (d) fix wrong labels
6. 6.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
7. 7.🖼️ 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
8. 8.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) copy old unfair choices (d) fix wrong labels
9. 9.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add varied examples (d) ignore complaints
10. 10.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
11. 11.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
12. 12.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
13. 13.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
14. 14.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) balance the data (d) copy old unfair choices
15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
17. 17.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) fix wrong labels (d) skip testing
18. 18.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
19. 19.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
20. 20.True or false: “use one group only” adds to bias. (a) False (b) True
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
22. 22.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) use one group only (d) test on many groups
24. 24.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
25. 25.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
26. 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
27. 27.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.Which of these helps reduce bias? (a) check who is missing (b) skip testing (c) test on one group only (d) use one group only
29. 29.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
30. 30.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) balance the data (d) add more of the same
32. 32.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
34. 34.True or false: “add varied examples” helps reduce bias. (a) True (b) False
35. 35.True or false: “skip testing” adds to bias. (a) True (b) False
36. 36.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) use one group only
37. 37.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
38. 38.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) skip testing (d) ignore complaints
39. 39.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

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