AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 518 · 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.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
2. 2.True or false: “add varied examples” helps reduce bias. (a) False (b) True
3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
4. 4.True or false: “balance the data” helps reduce bias. (a) False (b) True
5. 5.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on one group only (d) test on many groups
6. 6.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
7. 7.True or false: “ask different people” adds to bias. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) skip testing (d) ask different people
9. 9.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
10. 10.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
11. 11.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) add more of the same (d) skip testing
12. 12.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) test on one group only
13. 13.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
14. 14.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
16. 16.Which of these adds to bias? (a) fix wrong labels (b) add more of the same (c) check who is missing (d) ask different people
17. 17.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
19. 19.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
20. 20.True or false: “test on one group only” helps reduce bias. (a) False (b) True
21. 21.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) test on one group only (d) ignore complaints
22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
23. 23.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
24. 24.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
25. 25.🖼️ 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
26. 26.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) check who is missing (d) test on one group only
27. 27.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) skip testing (d) fix wrong labels
28. 28.True or false: “add varied examples” adds to bias. (a) True (b) False
29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
30. 30.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) use one group only (d) skip testing
31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
32. 32.Which of these helps reduce bias? (a) fix wrong labels (b) test on one group only (c) add more of the same (d) ignore complaints
33. 33.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) balance the data (d) test on many groups
34. 34.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
35. 35.True or false: “check who is missing” helps reduce bias. (a) True (b) False
36. 36.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
37. 37.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
40. 40.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias

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