AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 564 · 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.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
3. 3.True or false: “check who is missing” adds to bias. (a) False (b) True
4. 4.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
6. 6.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) test on many groups (d) add varied examples
7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
8. 8.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) skip testing (d) test on many groups
9. 9.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
10. 10.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
11. 11.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.True or false: “skip testing” helps reduce bias. (a) False (b) True
13. 13.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
14. 14.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) test on one group only (d) check who is missing
15. 15.True or false: “skip testing” adds to bias. (a) True (b) False
16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
17. 17.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on many groups (d) copy old unfair choices
18. 18.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
21. 21.True or false: “test on many groups” helps reduce bias. (a) False (b) True
22. 22.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) balance the data (d) copy old unfair choices
23. 23.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) skip testing (d) test on one group only
24. 24.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) add varied examples (d) ask different people
25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
26. 26.True or false: “ask different people” helps reduce bias. (a) True (b) False
27. 27.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
28. 28.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
29. 29.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
30. 30.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) test on many groups
32. 32.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) add more of the same
33. 33.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
34. 34.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) add more of the same (d) add varied examples
35. 35.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.Which of these helps reduce bias? (a) test on one group only (b) ask different people (c) skip testing (d) copy old unfair choices
37. 37.True or false: “add varied examples” helps reduce bias. (a) False (b) True
38. 38.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
40. 40.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True

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