AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 544 · 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: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
2. 2.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) add more of the same (d) add varied examples
3. 3.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) use one group only (d) add more of the same
4. 4.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) balance the data (d) fix wrong labels
5. 5.🗣️ 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
6. 6.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) ignore complaints (d) skip testing
7. 7.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
8. 8.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
10. 10.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) check who is missing
11. 11.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
12. 12.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
13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
14. 14.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) use one group only
15. 15.True or false: “use one group only” helps reduce bias. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) skip testing (d) add more of the same
17. 17.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) test on many groups (d) balance the data
18. 18.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
20. 20.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
22. 22.True or false: “check who is missing” adds to bias. (a) False (b) True
23. 23.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
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) balance the data (b) ask different people (c) ignore complaints (d) add varied examples
27. 27.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) skip testing (d) fix wrong labels
28. 28.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
29. 29.Which of these adds to bias? (a) ask different people (b) test on many groups (c) add varied examples (d) test on one group only
30. 30.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
31. 31.Which of these adds to bias? (a) skip testing (b) ask different people (c) fix wrong labels (d) balance the data
32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
33. 33.True or false: “add varied examples” adds to bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) add more of the same (d) use one group only
35. 35.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
36. 36.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
37. 37.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
38. 38.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
39. 39.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
40. 40.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data

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