AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 592 · 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.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
2. 2.True or false: “add varied examples” adds to bias. (a) False (b) True
3. 3.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) check who is missing (d) test on many groups
5. 5.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) skip testing (d) copy old unfair choices
6. 6.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) skip testing (d) balance the data
7. 7.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
8. 8.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
9. 9.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
10. 10.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
11. 11.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
12. 12.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (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.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
17. 17.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) check who is missing
18. 18.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) add varied examples (d) skip testing
19. 19.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
21. 21.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
22. 22.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) use one group only (d) check who is missing
23. 23.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
24. 24.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) add varied examples (d) check who is missing
26. 26.Which of these adds to bias? (a) fix wrong labels (b) use one group only (c) ask different people (d) balance the data
27. 27.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) ask different people (d) ignore complaints
28. 28.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
29. 29.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
30. 30.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
31. 31.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) add varied examples (d) test on many groups
33. 33.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
34. 34.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
35. 35.True or false: “balance the data” helps reduce bias. (a) True (b) False
36. 36.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
37. 37.🖼️ 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
38. 38.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
39. 39.True or false: “check who is missing” helps reduce bias. (a) False (b) True
40. 40.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data

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