AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 45 · 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: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
2. 2.Which of these adds to bias? (a) use one group only (b) check who is missing (c) fix wrong labels (d) ask different people
3. 3.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) test on many groups
4. 4.True or false: “ignore complaints” adds to bias. (a) False (b) True
5. 5.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
6. 6.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
8. 8.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
10. 10.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
11. 11.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
12. 12.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
13. 13.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) balance the data
14. 14.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) balance the data (d) ignore complaints
15. 15.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) fix wrong labels (d) add more of the same
16. 16.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
17. 17.True or false: “skip testing” helps reduce bias. (a) True (b) False
18. 18.Which of these helps reduce bias? (a) ask different people (b) copy old unfair choices (c) use one group only (d) add more of the same
19. 19.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
20. 20.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
22. 22.🗣️ 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
23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
24. 24.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
25. 25.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
27. 27.True or false: “test on one group only” helps reduce bias. (a) True (b) False
28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
29. 29.True or false: “use one group only” adds to bias. (a) True (b) False
30. 30.True or false: “ask different people” helps reduce bias. (a) True (b) False
31. 31.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
32. 32.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
33. 33.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
35. 35.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) copy old unfair choices (d) skip testing
36. 36.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
37. 37.Which of these adds to bias? (a) test on many groups (b) balance the data (c) ignore complaints (d) check who is missing
38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
39. 39.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
40. 40.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

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