AI Bias Worksheet for Kids

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

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