AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 547 · 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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) few child voices in data (d) the phone was new
3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
4. 4.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on one group only (d) add varied examples
5. 5.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
6. 6.Which of these adds to bias? (a) fix wrong labels (b) use one group only (c) check who is missing (d) ask different people
7. 7.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
8. 8.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) copy old unfair choices (d) use one group only
9. 9.True or false: “balance the data” adds to bias. (a) False (b) True
10. 10.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
14. 14.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
15. 15.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
16. 16.Which of these adds to bias? (a) add more of the same (b) add varied examples (c) balance the data (d) fix wrong labels
17. 17.True or false: “test on one group only” adds to bias. (a) False (b) True
18. 18.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
19. 19.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
22. 22.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
23. 23.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
24. 24.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
25. 25.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
26. 26.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
28. 28.True or false: “check who is missing” helps reduce bias. (a) False (b) True
29. 29.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
30. 30.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
31. 31.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) copy old unfair choices (d) check who is missing
32. 32.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) copy old unfair choices (d) add more of the same
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.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) balance the data (d) copy old unfair choices
36. 36.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
37. 37.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) balance the data (d) copy old unfair choices
38. 38.True or false: “add varied examples” helps reduce bias. (a) False (b) True
39. 39.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) use one group only (d) ignore complaints
40. 40.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True

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