AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 226 · 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 handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
2. 2.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
3. 3.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
4. 4.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
5. 5.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
7. 7.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
8. 8.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
9. 9.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
10. 10.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
11. 11.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
12. 12.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
13. 13.True or false: “check who is missing” helps reduce bias. (a) False (b) True
14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
15. 15.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
16. 16.Which of these adds to bias? (a) skip testing (b) test on many groups (c) fix wrong labels (d) check who is missing
17. 17.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
18. 18.Which of these adds to bias? (a) use one group only (b) fix wrong labels (c) balance the data (d) ask different people
19. 19.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) ask different people (d) fix wrong labels
20. 20.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
21. 21.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
22. 22.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
23. 23.Which of these adds to bias? (a) check who is missing (b) test on one group only (c) add varied examples (d) balance the data
24. 24.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
25. 25.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
26. 26.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) ignore complaints (d) copy old unfair choices
28. 28.True or false: “add varied examples” helps reduce bias. (a) False (b) True
29. 29.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) skip testing (d) test on one group only
30. 30.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
31. 31.True or false: “test on one group only” helps reduce bias. (a) False (b) True
32. 32.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
33. 33.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) fix wrong labels (d) ignore complaints
34. 34.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) ask different people (d) add more of the same
35. 35.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) add varied examples (b) use one group only (c) check who is missing (d) test on many groups
37. 37.True or false: “use one group only” helps reduce bias. (a) False (b) True
38. 38.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) test on many groups (d) copy old unfair choices
39. 39.True or false: “skip testing” adds to bias. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) use one group only (d) check who is missing

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