AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 918 · 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.Which of these helps reduce bias? (a) add more of the same (b) ask different people (c) skip testing (d) ignore complaints
2. 2.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
3. 3.🖼️ 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
4. 4.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
5. 5.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) copy old unfair choices (d) add more of the same
8. 8.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) check who is missing (d) test on many groups
9. 9.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
10. 10.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
11. 11.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) balance the data (d) test on many groups
12. 12.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
13. 13.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) add more of the same (d) fix wrong labels
14. 14.True or false: “check who is missing” adds to bias. (a) False (b) True
15. 15.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
16. 16.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) ignore complaints (d) add varied examples
18. 18.True or false: “add more of the same” adds to bias. (a) True (b) False
19. 19.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
20. 20.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
21. 21.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
23. 23.Which of these adds to bias? (a) use one group only (b) add varied examples (c) ask different people (d) test on many groups
24. 24.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
26. 26.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
27. 27.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ignore complaints (d) check who is missing
28. 28.True or false: “add more of the same” helps reduce bias. (a) True (b) False
29. 29.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) use one group only (d) test on one group only
31. 31.True or false: “balance the data” helps reduce bias. (a) False (b) True
32. 32.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
34. 34.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) test on one group only (d) add varied examples
36. 36.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
37. 37.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
38. 38.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) use one group only (d) check who is missing
39. 39.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) check who is missing (d) use one group only
40. 40.True or false: “check who is missing” helps reduce bias. (a) True (b) False

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