AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 318 · 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) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
2. 2.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) use one group only (d) copy old unfair choices
4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
5. 5.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
6. 6.True or false: “balance the data” helps reduce bias. (a) True (b) False
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) check who is missing (d) add varied examples
8. 8.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
9. 9.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) balance the data (d) use one group only
10. 10.🔍 Which is the odd one out? (a) skip testing (b) fix wrong labels (c) ignore complaints (d) use one group only
11. 11.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
12. 12.True or false: “ask different people” adds to bias. (a) False (b) True
13. 13.True or false: “skip testing” helps reduce bias. (a) True (b) False
14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
15. 15.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
16. 16.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
17. 17.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
20. 20.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) use one group only (d) skip testing
21. 21.Which of these adds to bias? (a) add varied examples (b) ask different people (c) check who is missing (d) use one group only
22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
24. 24.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
25. 25.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) ask different people (d) add varied examples
26. 26.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
28. 28.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
29. 29.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) use one group only (d) check who is missing
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
31. 31.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
32. 32.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) balance the data
33. 33.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) add more of the same (d) skip testing
34. 34.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) add more of the same
35. 35.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
36. 36.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) test on many groups (d) fix wrong labels
38. 38.Which of these adds to bias? (a) fix wrong labels (b) ignore complaints (c) add varied examples (d) ask different people
39. 39.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
40. 40.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data

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