AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 47 · 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.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
2. 2.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on many groups (d) test on one group only
3. 3.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) use one group only (d) ask different people
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
5. 5.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
6. 6.Which of these adds to bias? (a) ask different people (b) balance the data (c) skip testing (d) add varied examples
7. 7.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
8. 8.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) test on one group only (d) ask different people
9. 9.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
10. 10.Which of these adds to bias? (a) balance the data (b) ignore complaints (c) check who is missing (d) add varied examples
11. 11.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
12. 12.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
13. 13.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) skip testing (d) balance the data
15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
16. 16.🔍 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
17. 17.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) copy old unfair choices (d) check who is missing
18. 18.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
19. 19.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
20. 20.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
21. 21.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
22. 22.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
24. 24.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
25. 25.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
26. 26.Which of these adds to bias? (a) ask different people (b) test on many groups (c) test on one group only (d) add varied examples
27. 27.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) copy old unfair choices (d) skip testing
28. 28.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
29. 29.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
30. 30.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
31. 31.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) use one group only (d) fix wrong labels
32. 32.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
33. 33.True or false: “use one group only” helps reduce bias. (a) True (b) False
34. 34.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
35. 35.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
36. 36.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
37. 37.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
38. 38.True or false: “check who is missing” adds to bias. (a) True (b) False
39. 39.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
40. 40.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) add more of the same (d) test on one group only

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