AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 418 · 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 adds to bias? (a) add varied examples (b) fix wrong labels (c) skip testing (d) ask different people
2. 2.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) copy old unfair choices (d) use one group only
3. 3.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) copy old unfair choices (d) skip testing
4. 4.True or false: “ask different people” adds to bias. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) test on many groups (d) add varied examples
6. 6.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
7. 7.True or false: “ask different people” helps reduce bias. (a) False (b) True
8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
9. 9.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
10. 10.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) fix wrong labels (d) copy old unfair choices
11. 11.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
13. 13.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
14. 14.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
15. 15.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
16. 16.🔍 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
17. 17.Which of these adds to bias? (a) check who is missing (b) balance the data (c) add more of the same (d) test on many groups
18. 18.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.🗣️ 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) it was a rainy day (d) children speak too fast
20. 20.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
22. 22.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) use one group only (d) ask different people
23. 23.True or false: “test on many groups” helps reduce bias. (a) False (b) True
24. 24.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
25. 25.True or false: “check who is missing” adds to bias. (a) False (b) True
26. 26.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) copy old unfair choices (d) ask different people
27. 27.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) test on many groups (d) ignore complaints
28. 28.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) balance the data
29. 29.Which of these helps reduce bias? (a) check who is missing (b) ignore complaints (c) test on one group only (d) copy old unfair choices
30. 30.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
31. 31.Which of these helps reduce bias? (a) use one group only (b) add varied examples (c) add more of the same (d) copy old unfair choices
32. 32.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
33. 33.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
34. 34.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) use one group only (d) add more of the same
35. 35.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
36. 36.True or false: “add varied examples” adds to bias. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) add varied examples (d) check who is missing
38. 38.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) use one group only (d) test on many groups
40. 40.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False

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