AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 234 · 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: ignore complaints? (a) adds to bias (b) reduces bias
2. 2.Which of these helps reduce bias? (a) balance the data (b) ignore complaints (c) use one group only (d) test on one group only
3. 3.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) balance the data (d) fix wrong labels
4. 4.🗣️ 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) few child voices in data (d) the phone was new
5. 5.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) add more of the same (d) copy old unfair choices
6. 6.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
7. 7.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
9. 9.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
10. 10.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) add varied examples (d) skip testing
11. 11.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
12. 12.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) test on many groups (d) test on one group only
13. 13.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) ask different people (d) add more of the same
14. 14.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
15. 15.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
16. 16.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
17. 17.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
18. 18.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
20. 20.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
21. 21.True or false: “use one group only” helps reduce bias. (a) True (b) False
22. 22.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
23. 23.True or false: “use one group only” adds to bias. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) add varied examples (d) check who is missing
25. 25.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
26. 26.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
27. 27.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
28. 28.True or false: “check who is missing” helps reduce bias. (a) False (b) True
29. 29.True or false: “skip testing” helps reduce bias. (a) True (b) False
30. 30.Which of these adds to bias? (a) check who is missing (b) copy old unfair choices (c) ask different people (d) test on many groups
31. 31.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
32. 32.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
33. 33.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
34. 34.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) use one group only (d) check who is missing
35. 35.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) skip testing (d) ask different people
37. 37.True or false: “fix wrong labels” adds to bias. (a) True (b) False
38. 38.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
40. 40.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather

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