AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 376 · 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.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) ask different people
3. 3.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
4. 4.Which of these adds to bias? (a) add varied examples (b) ask different people (c) check who is missing (d) add more of the same
5. 5.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
6. 6.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) test on one group only (d) use one group only
7. 7.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a fair model (d) a strong battery
8. 8.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
9. 9.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
10. 10.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
11. 11.True or false: “add varied examples” adds to bias. (a) False (b) True
12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
15. 15.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
16. 16.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
17. 17.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) skip testing (d) fix wrong labels
18. 18.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
20. 20.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
22. 22.Which of these adds to bias? (a) test on many groups (b) balance the data (c) use one group only (d) fix wrong labels
23. 23.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) balance the data (d) test on one group only
26. 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
27. 27.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) ask different people (d) copy old unfair choices
29. 29.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
30. 30.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
31. 31.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) skip testing (d) add varied examples
32. 32.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) add varied examples (d) skip testing
33. 33.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) check who is missing (d) test on one group only
35. 35.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) test on many groups (d) test on one group only
36. 36.True or false: mangoes both raw and ripe 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 balanced data (fairer for everyone). (a) False (b) True
38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
39. 39.True or false: “test on many groups” adds to bias. (a) False (b) True
40. 40.True or false: “test on one group only” helps reduce bias. (a) False (b) True

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