AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 668 · 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 screen size (c) the weather (d) its training data
2. 2.Which of these adds to bias? (a) add varied examples (b) copy old unfair choices (c) ask different people (d) check who is missing
3. 3.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.True or false: “balance the data” adds to bias. (a) False (b) True
5. 5.True or false: “ask different people” helps reduce bias. (a) True (b) False
6. 6.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
9. 9.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
11. 11.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
13. 13.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
14. 14.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
16. 16.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) skip testing (d) balance the data
17. 17.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) test on one group only (d) add varied examples
19. 19.Which of these adds to bias? (a) fix wrong labels (b) add more of the same (c) test on many groups (d) add varied examples
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) ignore complaints (d) use one group only
22. 22.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) use one group only (d) add more of the same
23. 23.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.Which of these adds to bias? (a) test on many groups (b) balance the data (c) ask different people (d) skip testing
25. 25.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) copy old unfair choices (d) test on many groups
27. 27.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
29. 29.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
30. 30.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) ask different people (d) check who is missing
32. 32.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
33. 33.True or false: “test on many groups” adds to bias. (a) True (b) False
34. 34.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
35. 35.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
36. 36.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add varied examples (d) copy old unfair choices
37. 37.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on one group only (d) ask different people
39. 39.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
40. 40.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) ignore complaints (d) check who is missing

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