AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 637 · 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: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) check who is missing (d) add more of the same
3. 3.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) ask different people (d) use one group only
4. 4.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) copy old unfair choices (d) add varied examples
5. 5.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
6. 6.True or false: “test on many groups” adds to bias. (a) False (b) True
7. 7.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
9. 9.True or false: “fix wrong labels” adds to bias. (a) True (b) False
10. 10.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) skip testing (d) copy old unfair choices
11. 11.🖼️ 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
12. 12.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
14. 14.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
16. 16.True or false: “add varied examples” adds to bias. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) fix wrong labels (d) add varied examples
18. 18.True or false: “check who is missing” adds to bias. (a) False (b) True
19. 19.True or false: “add varied examples” helps reduce bias. (a) False (b) True
20. 20.Which of these adds to bias? (a) copy old unfair choices (b) ask different people (c) balance the data (d) test on many groups
21. 21.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
22. 22.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
23. 23.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) it was a rainy day (d) children speak too fast
24. 24.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
25. 25.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) ignore complaints (d) test on many groups
26. 26.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
27. 27.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
28. 28.True or false: “skip testing” adds to bias. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) use one group only (d) ask different people
30. 30.Which of these adds to bias? (a) ask different people (b) balance the data (c) add varied examples (d) use one group only
31. 31.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) add varied examples (d) test on many groups
32. 32.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
34. 34.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) ask different people (d) fix wrong labels
35. 35.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) skip testing (d) balance the data
36. 36.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) check who is missing (d) add varied examples
37. 37.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) fix wrong labels (d) use one group only
38. 38.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
39. 39.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
40. 40.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data

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