AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 515 · 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.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
4. 4.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
5. 5.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
6. 6.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
7. 7.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
8. 8.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
9. 9.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) use one group only (d) add more of the same
10. 10.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) copy old unfair choices (d) add varied examples
11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
12. 12.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) add more of the same (d) test on one group only
13. 13.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
14. 14.True or false: “check who is missing” helps reduce bias. (a) False (b) True
15. 15.True or false: “balance the data” helps reduce bias. (a) False (b) True
16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
17. 17.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
18. 18.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
19. 19.Which of these adds to bias? (a) test on many groups (b) copy old unfair choices (c) check who is missing (d) add varied examples
20. 20.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
21. 21.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
22. 22.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
25. 25.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) add varied examples (d) fix wrong labels
27. 27.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
28. 28.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
29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) test on many groups (d) skip testing
31. 31.True or false: “add varied examples” helps reduce bias. (a) True (b) False
32. 32.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) use one group only (d) fix wrong labels
33. 33.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
34. 34.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
35. 35.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
37. 37.Which of these helps reduce bias? (a) check who is missing (b) ignore complaints (c) skip testing (d) test on one group only
38. 38.Which of these adds to bias? (a) fix wrong labels (b) add more of the same (c) add varied examples (d) test on many groups
39. 39.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
40. 40.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data

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