AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 823 · 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: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
2. 2.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
3. 3.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) add varied examples (d) skip testing
4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
5. 5.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
6. 6.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
7. 7.Which of these adds to bias? (a) use one group only (b) add varied examples (c) ask different people (d) test on many groups
8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
9. 9.True or false: “check who is missing” helps reduce bias. (a) True (b) False
10. 10.True or false: “fix wrong labels” adds to bias. (a) True (b) False
11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
12. 12.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) fix wrong labels (d) copy old unfair choices
13. 13.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add varied examples (d) test on one group only
14. 14.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
15. 15.True or false: “test on one group only” adds to bias. (a) True (b) False
16. 16.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
17. 17.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
18. 18.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) test on one group only (d) skip testing
19. 19.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
20. 20.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) fix wrong labels (d) add more of the same
21. 21.True or false: “add varied examples” helps reduce bias. (a) False (b) True
22. 22.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
23. 23.True or false: “use one group only” helps reduce bias. (a) True (b) False
24. 24.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
25. 25.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
26. 26.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
27. 27.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) use one group only (d) check who is missing
28. 28.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) test on many groups (d) ignore complaints
29. 29.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) balance the data (d) ignore complaints
30. 30.True or false: “check who is missing” adds to bias. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) copy old unfair choices
32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) test on one group only (d) ask different people
36. 36.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
37. 37.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
38. 38.Which of these helps reduce bias? (a) balance the data (b) test on one group only (c) add more of the same (d) ignore complaints
39. 39.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
40. 40.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias

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