AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 721 · 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: ignore complaints? (a) reduces bias (b) adds to bias
2. 2.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
3. 3.True or false: “add more of the same” adds to bias. (a) False (b) True
4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
6. 6.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) copy old unfair choices (d) test on many groups
7. 7.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
9. 9.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
10. 10.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
12. 12.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
13. 13.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
14. 14.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) ignore complaints (d) check who is missing
15. 15.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) copy old unfair choices (d) add more of the same
16. 16.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
18. 18.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
19. 19.🖼️ 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
20. 20.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) test on one group only (d) use one group only
21. 21.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
22. 22.True or false: “test on many groups” helps reduce bias. (a) False (b) True
23. 23.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
24. 24.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) balance the data (d) use one group only
26. 26.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) test on one group only (d) balance the data
27. 27.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
28. 28.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
29. 29.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) add more of the same (d) fix wrong labels
30. 30.True or false: “check who is missing” helps reduce bias. (a) False (b) True
31. 31.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
32. 32.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
33. 33.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
34. 34.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
35. 35.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
36. 36.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
37. 37.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
38. 38.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
39. 39.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) copy old unfair choices (d) ignore complaints
40. 40.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data

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