AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 836 · 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.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
2. 2.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
3. 3.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
4. 4.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) skip testing (d) test on many groups
5. 5.Which of these helps reduce bias? (a) test on one group only (b) fix wrong labels (c) skip testing (d) copy old unfair choices
6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
7. 7.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
8. 8.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
10. 10.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) test on many groups (d) check who is missing
11. 11.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
13. 13.Which of these helps reduce bias? (a) add more of the same (b) balance the data (c) copy old unfair choices (d) use one group only
14. 14.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
15. 15.🖼️ 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
16. 16.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
17. 17.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
18. 18.🗣️ 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) it was a rainy day (d) children speak too fast
19. 19.True or false: “ask different people” adds to bias. (a) False (b) True
20. 20.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
21. 21.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
22. 22.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
23. 23.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
24. 24.True or false: “use one group only” helps reduce bias. (a) True (b) False
25. 25.True or false: “add varied examples” adds to bias. (a) False (b) True
26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
27. 27.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) balance the data (d) ignore complaints
29. 29.True or false: “test on many groups” helps reduce bias. (a) False (b) True
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
31. 31.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) check who is missing (d) copy old unfair choices
34. 34.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) skip testing (d) test on one group only
35. 35.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) add more of the same (d) add varied examples
36. 36.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
37. 37.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
38. 38.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
39. 39.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
40. 40.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data

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