AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 162 · 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: fix wrong labels? (a) adds to bias (b) reduces bias
2. 2.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
3. 3.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) add more of the same (d) skip testing
4. 4.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
5. 5.True or false: “add varied examples” adds to bias. (a) False (b) True
6. 6.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) fix wrong labels (d) use one group only
8. 8.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
9. 9.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
10. 10.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
11. 11.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) skip testing (d) copy old unfair choices
12. 12.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
13. 13.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) check who is missing
14. 14.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
15. 15.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
16. 16.True or false: “ignore complaints” adds to bias. (a) False (b) True
17. 17.Which of these adds to bias? (a) copy old unfair choices (b) test on many groups (c) ask different people (d) fix wrong labels
18. 18.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
19. 19.True or false: “balance the data” adds to bias. (a) True (b) False
20. 20.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
21. 21.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
22. 22.True or false: “check who is missing” adds to bias. (a) False (b) True
23. 23.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) balance the data (d) ignore complaints
25. 25.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) copy old unfair choices (d) test on many groups
26. 26.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
27. 27.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ask different people (d) add more of the same
29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
30. 30.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
31. 31.Which of these adds to bias? (a) add more of the same (b) balance the data (c) check who is missing (d) ask different people
32. 32.True or false: “check who is missing” helps reduce bias. (a) False (b) True
33. 33.True or false: “fix wrong labels” adds to bias. (a) False (b) True
34. 34.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) use one group only (d) add varied examples
36. 36.Which of these adds to bias? (a) add varied examples (b) test on one group only (c) check who is missing (d) ask different people
37. 37.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
39. 39.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
40. 40.True or false: “balance the data” helps reduce bias. (a) False (b) True

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