AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 578 · 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) test on one group only (b) balance the data (c) copy old unfair choices (d) use one group only
2. 2.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
4. 4.True or false: “check who is missing” adds to bias. (a) True (b) False
5. 5.🗣️ 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
6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
7. 7.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
8. 8.🔍 Which is the odd one out? (a) add varied examples (b) add more of the same (c) test on many groups (d) check who is missing
9. 9.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
10. 10.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
11. 11.True or false: “add varied examples” adds to bias. (a) False (b) True
12. 12.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
13. 13.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
14. 14.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
16. 16.True or false: “test on many groups” helps reduce bias. (a) True (b) False
17. 17.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
18. 18.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) add varied examples (d) fix wrong labels
19. 19.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
20. 20.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
21. 21.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) check who is missing (d) test on one group only
22. 22.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
24. 24.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) add varied examples (d) use one group only
25. 25.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
26. 26.True or false: “balance the data” helps reduce bias. (a) False (b) True
27. 27.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) ignore complaints (d) test on one group only
28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
29. 29.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) ignore complaints (d) test on many groups
30. 30.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
31. 31.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
32. 32.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
34. 34.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
35. 35.True or false: “check who is missing” helps reduce bias. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) skip testing (d) add more of the same
37. 37.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
38. 38.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) use one group only (d) add varied examples
39. 39.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) add more of the same (d) copy old unfair choices
40. 40.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) skip testing (d) fix wrong labels

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