AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 378 · 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.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
2. 2.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
3. 3.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
4. 4.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
5. 5.True or false: “test on one group only” helps reduce bias. (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) use one group only (d) ignore complaints
7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) add more of the same (d) ignore complaints
8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
10. 10.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
11. 11.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) test on many groups (d) copy old unfair choices
13. 13.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) balance the data (d) ask different people
14. 14.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
15. 15.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
16. 16.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) test on many groups (d) copy old unfair choices
17. 17.🗣️ 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) children speak too fast (d) few child voices in data
18. 18.True or false: “test on many groups” helps reduce bias. (a) True (b) False
19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
20. 20.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
21. 21.True or false: “check who is missing” adds to bias. (a) False (b) True
22. 22.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
24. 24.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
25. 25.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) copy old unfair choices (d) add more of the same
26. 26.True or false: “ask different people” helps reduce bias. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add more of the same (d) fix wrong labels
28. 28.Which of these adds to bias? (a) fix wrong labels (b) use one group only (c) add varied examples (d) ask different people
29. 29.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
30. 30.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
32. 32.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) test on many groups (d) copy old unfair choices
33. 33.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
34. 34.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
35. 35.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
36. 36.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
37. 37.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) fix wrong labels (d) skip testing
38. 38.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) check who is missing (d) test on many groups
39. 39.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
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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