AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 895 · 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.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
2. 2.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
3. 3.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
4. 4.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) check who is missing (d) add varied examples
5. 5.🖼️ 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
6. 6.True or false: “add more of the same” helps reduce bias. (a) True (b) False
7. 7.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) use one group only
8. 8.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
9. 9.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
10. 10.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
11. 11.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
13. 13.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather
14. 14.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
16. 16.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) test on many groups (d) ask different people
17. 17.Which of these helps reduce bias? (a) fix wrong labels (b) ignore complaints (c) test on one group only (d) use one group only
18. 18.Which of these helps reduce bias? (a) balance the data (b) skip testing (c) test on one group only (d) use one group only
19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
20. 20.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
21. 21.Which of these helps reduce bias? (a) test on many groups (b) ignore complaints (c) copy old unfair choices (d) skip testing
22. 22.Which of these adds to bias? (a) add more of the same (b) balance the data (c) test on many groups (d) ask different people
23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
24. 24.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
26. 26.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) fix wrong labels (d) test on many groups
27. 27.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) ask different people (d) skip testing
28. 28.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
29. 29.True or false: “skip testing” helps reduce bias. (a) False (b) True
30. 30.🗣️ 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
31. 31.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
32. 32.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
33. 33.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
34. 34.True or false: “add more of the same” adds to bias. (a) False (b) True
35. 35.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
36. 36.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
37. 37.True or false: “test on many groups” helps reduce bias. (a) True (b) False
38. 38.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) skip testing (d) add more of the same
40. 40.True or false: “add varied examples” helps reduce bias. (a) True (b) False

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