AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 508 · 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: stories where every doctor is a man? (a) one-sided data (b) balanced data
2. 2.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
3. 3.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
4. 4.🗣️ 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
5. 5.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
7. 7.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
8. 8.Which of these helps reduce bias? (a) balance the data (b) copy old unfair choices (c) ignore complaints (d) test on one group only
9. 9.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) add varied examples (d) skip testing
10. 10.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) copy old unfair choices (d) use one group only
11. 11.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
12. 12.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
13. 13.Which of these adds to bias? (a) copy old unfair choices (b) balance the data (c) add varied examples (d) check who is missing
14. 14.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
15. 15.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
16. 16.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) add more of the same (d) test on many groups
17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
18. 18.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) add varied examples (d) fix wrong labels
19. 19.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.True or false: “fix wrong labels” adds to bias. (a) True (b) False
22. 22.True or false: “test on many groups” helps reduce bias. (a) False (b) True
23. 23.True or false: “add more of the same” adds to bias. (a) False (b) True
24. 24.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
25. 25.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
26. 26.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
27. 27.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
28. 28.True or false: “balance the data” helps reduce bias. (a) True (b) False
29. 29.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
30. 30.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
32. 32.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
33. 33.Which of these helps reduce bias? (a) fix wrong labels (b) use one group only (c) ignore complaints (d) add more of the same
34. 34.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
35. 35.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) fix wrong labels (d) test on many groups
36. 36.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) copy old unfair choices (d) balance the data
37. 37.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
38. 38.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
39. 39.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
40. 40.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) test on many groups (d) skip testing

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