AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 419 · 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 of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) test on one group only (d) check who is missing
2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
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 of these adds to bias? (a) ask different people (b) fix wrong labels (c) use one group only (d) check who is missing
6. 6.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
7. 7.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
8. 8.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a fair model (d) a broken screen
10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
11. 11.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) use one group only (d) test on one group only
12. 12.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) ignore complaints (d) add varied examples
13. 13.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) test on one group only
14. 14.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) test on one group only (d) ignore complaints
15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
16. 16.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
19. 19.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
20. 20.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: “use one group only” helps reduce bias. (a) False (b) True
24. 24.Which of these adds to bias? (a) test on one group only (b) check who is missing (c) ask different people (d) fix wrong labels
25. 25.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) skip testing (d) check who is missing
26. 26.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) ignore complaints (d) test on many groups
27. 27.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) test on many groups (d) balance the data
28. 28.True or false: “skip testing” adds to bias. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) fix wrong labels (d) skip testing
30. 30.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) test on many groups (d) use one group only
32. 32.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
33. 33.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
34. 34.True or false: “test on many groups” helps reduce bias. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) add varied examples (d) test on one group only
36. 36.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
37. 37.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
38. 38.True or false: “ignore complaints” adds to bias. (a) False (b) True
39. 39.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
40. 40.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) balance the data (d) ask different people

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