AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 937 · 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 adds to bias? (a) check who is missing (b) test on one group only (c) fix wrong labels (d) test on many groups
2. 2.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
3. 3.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.True or false: “test on one group only” adds to bias. (a) True (b) False
5. 5.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
6. 6.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
7. 7.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
8. 8.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
9. 9.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) add more of the same (d) test on one group only
10. 10.🗣️ 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
11. 11.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
12. 12.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) skip testing (d) add varied examples
13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
14. 14.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) ignore complaints (d) fix wrong labels
15. 15.Which of these adds to bias? (a) add more of the same (b) test on many groups (c) add varied examples (d) ask different people
16. 16.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
17. 17.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
19. 19.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) skip testing (d) test on one group only
20. 20.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
21. 21.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
22. 22.Which of these adds to bias? (a) copy old unfair choices (b) check who is missing (c) add varied examples (d) test on many groups
23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) use one group only (d) add varied examples
24. 24.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
26. 26.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
27. 27.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) ask different people (d) test on one group only
28. 28.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) use one group only
29. 29.True or false: “test on one group only” helps reduce bias. (a) False (b) True
30. 30.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) skip testing (d) test on many groups
31. 31.True or false: “skip testing” helps reduce bias. (a) True (b) False
32. 32.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) copy old unfair choices (d) add varied examples
33. 33.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) use one group only (d) add more of the same
34. 34.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
35. 35.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
36. 36.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
37. 37.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
38. 38.True or false: “ask different people” helps reduce bias. (a) False (b) True
39. 39.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
40. 40.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False

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