AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 983 · 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.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
2. 2.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
3. 3.True or false: “use one group only” helps reduce bias. (a) True (b) False
4. 4.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
5. 5.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) copy old unfair choices (d) balance the data
7. 7.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
8. 8.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
9. 9.True or false: “skip testing” helps reduce bias. (a) True (b) False
10. 10.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
11. 11.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
13. 13.🔍 Which is the odd one out? (a) add varied examples (b) use one group only (c) ask different people (d) balance the data
14. 14.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
15. 15.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
16. 16.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.True or false: “use one group only” adds to bias. (a) False (b) True
18. 18.Which of these adds to bias? (a) add more of the same (b) add varied examples (c) test on many groups (d) check who is missing
19. 19.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) ignore complaints (d) use one group only
20. 20.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) skip testing (d) test on many groups
21. 21.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) test on one group only (d) add varied examples
23. 23.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) copy old unfair choices (d) add varied examples
24. 24.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) add more of the same (d) test on many groups
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) balance the data (d) skip testing
26. 26.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
27. 27.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
28. 28.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
29. 29.True or false: “add varied examples” adds to bias. (a) True (b) False
30. 30.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
31. 31.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) test on many groups (d) check who is missing
32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) copy old unfair choices
34. 34.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) use one group only (d) ask different people
35. 35.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
36. 36.Which of these adds to bias? (a) test on one group only (b) balance the data (c) check who is missing (d) add varied examples
37. 37.True or false: “test on many groups” helps reduce bias. (a) True (b) False
38. 38.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
40. 40.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False

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