AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 56 · 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.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
2. 2.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) fix wrong labels (d) balance the data
3. 3.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
4. 4.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
5. 5.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
6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
7. 7.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
8. 8.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) copy old unfair choices (d) check who is missing
9. 9.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) copy old unfair choices (d) ask different people
10. 10.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
12. 12.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
14. 14.Which of these adds to bias? (a) balance the data (b) test on many groups (c) check who is missing (d) skip testing
15. 15.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) check who is missing (d) add more of the same
16. 16.True or false: “check who is missing” adds to bias. (a) False (b) True
17. 17.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
18. 18.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
19. 19.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
20. 20.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
21. 21.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
22. 22.Which of these helps reduce bias? (a) add varied examples (b) skip testing (c) add more of the same (d) use one group only
23. 23.True or false: “use one group only” adds to bias. (a) False (b) True
24. 24.True or false: “add more of the same” helps reduce bias. (a) True (b) False
25. 25.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
26. 26.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) test on one group only (d) ask different people
27. 27.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
28. 28.True or false: “ignore complaints” adds to bias. (a) False (b) True
29. 29.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
30. 30.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
31. 31.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
32. 32.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) check who is missing (d) test on one group only
33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) use one group only
34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
35. 35.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
37. 37.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
38. 38.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
39. 39.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
40. 40.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) add more of the same (d) use one group only

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