AI Bias Worksheet for Kids

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

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