AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 301 · 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) check who is missing (b) use one group only (c) add varied examples (d) balance the data
2. 2.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
3. 3.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
4. 4.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
5. 5.Which of these helps reduce bias? (a) test on one group only (b) test on many groups (c) use one group only (d) skip testing
6. 6.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) fix wrong labels (d) test on many groups
8. 8.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
9. 9.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
10. 10.Which of these adds to bias? (a) ask different people (b) test on many groups (c) check who is missing (d) ignore complaints
11. 11.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) add more of the same (d) balance the data
12. 12.True or false: “skip testing” adds to bias. (a) False (b) True
13. 13.True or false: “add more of the same” adds to bias. (a) False (b) True
14. 14.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
15. 15.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
16. 16.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) use one group only (d) test on many groups
17. 17.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
18. 18.True or false: “test on one group only” adds to bias. (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) test on many groups (d) balance the data
20. 20.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) add varied examples
21. 21.True or false: “balance the data” adds to bias. (a) True (b) False
22. 22.True or false: “ask different people” adds to bias. (a) True (b) False
23. 23.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
24. 24.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
25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
26. 26.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
27. 27.Which of these adds to bias? (a) copy old unfair choices (b) fix wrong labels (c) add varied examples (d) balance the data
28. 28.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) test on one group only (d) add more of the same
29. 29.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) add varied examples (d) balance the data
30. 30.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) ask different people (d) skip testing
31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
32. 32.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
33. 33.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
34. 34.True or false: “use one group only” helps reduce bias. (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) skip testing
36. 36.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) use one group only (d) add more of the same
37. 37.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
38. 38.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
39. 39.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
40. 40.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ignore complaints (d) test on one group only

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