AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 996 · 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: leaves from every season of the year? (a) one-sided data (b) balanced data
2. 2.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
4. 4.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) ignore complaints (d) add varied examples
5. 5.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
6. 6.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
7. 7.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) fix wrong labels (d) test on one group only
8. 8.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) balance the data (d) add more of the same
9. 9.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) ask different people (d) use one group only
10. 10.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
12. 12.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) use one group only (d) check who is missing
13. 13.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on one group only (d) test on many groups
14. 14.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
16. 16.🔍 Which is the odd one out? (a) ask different people (b) test on one group only (c) copy old unfair choices (d) add more of the same
17. 17.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) test on many groups (d) ask different people
18. 18.True or false: “test on many groups” adds to bias. (a) False (b) True
19. 19.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
20. 20.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
21. 21.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
22. 22.Which of these adds to bias? (a) balance the data (b) ask different people (c) add more of the same (d) fix wrong labels
23. 23.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) add varied examples (d) use one group only
24. 24.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) use one group only (d) skip testing
26. 26.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
27. 27.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) fix wrong labels (d) copy old unfair choices
28. 28.True or false: “check who is missing” helps reduce bias. (a) False (b) True
29. 29.True or false: “balance the data” helps reduce bias. (a) False (b) True
30. 30.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
32. 32.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
33. 33.True or false: “add varied examples” helps reduce bias. (a) True (b) False
34. 34.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
35. 35.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) balance the data (d) add more of the same
36. 36.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
37. 37.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
38. 38.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) test on one group only (d) check who is missing
39. 39.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
40. 40.True or false: “skip testing” adds to bias. (a) False (b) True

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