AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 109 · 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.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) add more of the same (d) add varied examples
2. 2.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
3. 3.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
4. 4.True or false: “ask different people” adds to bias. (a) False (b) True
5. 5.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
6. 6.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
7. 7.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
8. 8.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
9. 9.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
10. 10.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
11. 11.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
12. 12.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) add varied examples (d) skip testing
13. 13.🔍 Which is the odd one out? (a) test on many groups (b) test on one group only (c) ignore complaints (d) use one group only
14. 14.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
15. 15.True or false: “test on many groups” adds to bias. (a) False (b) True
16. 16.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
17. 17.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
18. 18.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
19. 19.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
20. 20.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) balance the data (d) copy old unfair choices
21. 21.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
22. 22.Which of these adds to bias? (a) use one group only (b) fix wrong labels (c) check who is missing (d) add varied examples
23. 23.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
25. 25.True or false: “balance the data” adds to bias. (a) True (b) False
26. 26.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) ignore complaints (d) test on one group only
27. 27.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
28. 28.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) copy old unfair choices (d) fix wrong labels
29. 29.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
30. 30.True or false: “skip testing” helps reduce bias. (a) True (b) False
31. 31.Which of these adds to bias? (a) test on one group only (b) test on many groups (c) add varied examples (d) ask different people
32. 32.Which of these helps reduce bias? (a) add varied examples (b) skip testing (c) ignore complaints (d) copy old unfair choices
33. 33.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
34. 34.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) test on one group only (d) ask different people
35. 35.Which of these helps reduce bias? (a) copy old unfair choices (b) check who is missing (c) use one group only (d) add more of the same
36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
37. 37.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
38. 38.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
39. 39.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
40. 40.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False

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