AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 978 · 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 is the odd one out? (a) test on many groups (b) ignore complaints (c) check who is missing (d) fix wrong labels
2. 2.Which of these helps reduce bias? (a) test on many groups (b) use one group only (c) skip testing (d) ignore complaints
3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
4. 4.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
5. 5.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
6. 6.True or false: “test on one group only” adds to bias. (a) False (b) True
7. 7.Which of these adds to bias? (a) ask different people (b) test on many groups (c) skip testing (d) check who is missing
8. 8.True or false: “test on one group only” helps reduce bias. (a) False (b) True
9. 9.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ask different people (d) add varied examples
10. 10.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) ignoring mistakes (d) fewer tests
11. 11.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on many groups (d) test on one group only
12. 12.True or false: “add more of the same” helps reduce bias. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) ask different people (d) test on many groups
14. 14.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
15. 15.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
16. 16.🗣️ 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
17. 17.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.True or false: “add more of the same” adds to bias. (a) False (b) True
19. 19.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
20. 20.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
23. 23.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
24. 24.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) skip testing (d) fix wrong labels
25. 25.Which of these adds to bias? (a) balance the data (b) ask different people (c) test on many groups (d) ignore complaints
26. 26.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
28. 28.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
29. 29.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) use one group only (d) add varied examples
30. 30.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) fix wrong labels (d) skip testing
31. 31.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
32. 32.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
33. 33.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
34. 34.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
35. 35.True or false: “add varied examples” helps reduce bias. (a) True (b) False
36. 36.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
37. 37.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) balance the data
39. 39.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) check who is missing (d) add more of the same
40. 40.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) add varied examples (d) ask different people

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