AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 608 · 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.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
2. 2.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
3. 3.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
4. 4.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) test on one group only (d) skip testing
5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
6. 6.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
7. 7.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) add varied examples
8. 8.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) check who is missing (d) ignore complaints
9. 9.True or false: “ask different people” adds to bias. (a) True (b) False
10. 10.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
11. 11.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
12. 12.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
13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
14. 14.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
15. 15.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
16. 16.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) add varied examples (d) test on one group only
17. 17.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) use one group only (d) test on many groups
18. 18.True or false: “test on one group only” helps reduce bias. (a) True (b) False
19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
24. 24.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
26. 26.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) ignoring mistakes (d) fewer tests
27. 27.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) ask different people (d) add varied examples
28. 28.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) ignore complaints (d) balance the data
29. 29.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
30. 30.True or false: “add varied examples” helps reduce bias. (a) True (b) False
31. 31.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
33. 33.True or false: “use one group only” adds to bias. (a) True (b) False
34. 34.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
35. 35.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
36. 36.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) ignore complaints
37. 37.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) use one group only (d) test on one group only
39. 39.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
40. 40.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) copy old unfair choices (d) test on many groups

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