AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 413 · 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: copy old unfair choices? (a) reduces bias (b) adds to bias
2. 2.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
3. 3.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
4. 4.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
5. 5.True or false: “test on many groups” adds to bias. (a) True (b) False
6. 6.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
7. 7.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
9. 9.Which of these adds to bias? (a) balance the data (b) add varied examples (c) use one group only (d) check who is missing
10. 10.🗣️ 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) it was a rainy day (d) the phone was new
11. 11.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
13. 13.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
14. 14.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
15. 15.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) check who is missing (d) add more of the same
16. 16.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) add varied examples (d) ignore complaints
17. 17.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add more of the same (d) fix wrong labels
18. 18.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
20. 20.True or false: “add more of the same” helps reduce bias. (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
22. 22.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) add more of the same (d) use one group only
23. 23.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
24. 24.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) balance the data (d) test on one group only
26. 26.Which of these helps reduce bias? (a) balance the data (b) copy old unfair choices (c) use one group only (d) add more of the same
27. 27.Which of these helps reduce bias? (a) test on one group only (b) ask different people (c) use one group only (d) copy old unfair choices
28. 28.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) add more of the same (d) add varied examples
29. 29.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) test on many groups (d) add varied examples
30. 30.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ignore complaints (d) add varied examples
31. 31.True or false: “fix wrong labels” adds to bias. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) test on many groups (d) check who is missing
33. 33.True or false: “check who is missing” adds to bias. (a) False (b) True
34. 34.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
35. 35.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
36. 36.True or false: “test on one group only” adds to bias. (a) False (b) True
37. 37.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
38. 38.True or false: “balance the data” adds to bias. (a) True (b) False
39. 39.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
40. 40.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

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