AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 752 · 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) test on many groups (b) balance the data (c) use one group only (d) check who is missing
2. 2.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) use one group only (d) test on many groups
3. 3.Which of these adds to bias? (a) add varied examples (b) balance the data (c) test on many groups (d) add more of the same
4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
5. 5.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) ignore complaints (d) use one group only
6. 6.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
7. 7.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
8. 8.Which of these adds to bias? (a) add varied examples (b) balance the data (c) test on one group only (d) fix wrong labels
9. 9.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) add more of the same (d) balance the data
10. 10.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
11. 11.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) add varied examples (d) ask different people
13. 13.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) test on one group only (d) copy old unfair choices
14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
15. 15.True or false: “test on many groups” adds to bias. (a) False (b) True
16. 16.True or false: “check who is missing” adds to bias. (a) True (b) False
17. 17.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) fix wrong labels (d) ignore complaints
18. 18.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
19. 19.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
20. 20.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) use one group only (d) copy old unfair choices
21. 21.True or false: “balance the data” helps reduce bias. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) balance the data
23. 23.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
24. 24.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
25. 25.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
26. 26.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) add more of the same (d) check who is missing
27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
28. 28.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
29. 29.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
30. 30.Which of these adds to bias? (a) ignore complaints (b) test on many groups (c) ask different people (d) fix wrong labels
31. 31.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
32. 32.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
33. 33.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
34. 34.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
35. 35.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
36. 36.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
37. 37.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) copy old unfair choices (d) use one group only
38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
39. 39.Which of these adds to bias? (a) skip testing (b) check who is missing (c) ask different people (d) balance the data
40. 40.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True

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