AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 436 · 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.True or false: “add varied examples” adds to bias. (a) True (b) False
2. 2.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) skip testing (d) add more of the same
3. 3.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ignore complaints (d) skip testing
4. 4.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
5. 5.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
6. 6.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) ask different people (d) copy old unfair choices
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.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
9. 9.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
10. 10.True or false: “ignore complaints” adds to bias. (a) False (b) True
11. 11.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
12. 12.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
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.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
15. 15.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) copy old unfair choices (d) balance the data
16. 16.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) balance the data (d) copy old unfair choices
17. 17.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) copy old unfair choices (d) fix wrong labels
18. 18.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) use one group only (d) ask different people
19. 19.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
20. 20.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
21. 21.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
22. 22.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) add more of the same (d) copy old unfair choices
23. 23.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
24. 24.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
25. 25.🗣️ 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) the phone was new (d) children speak too fast
26. 26.True or false: “add more of the same” adds to bias. (a) False (b) True
27. 27.True or false: “test on many groups” helps reduce bias. (a) False (b) True
28. 28.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
30. 30.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) ask different people (d) skip testing
31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
32. 32.Which of these adds to bias? (a) balance the data (b) test on many groups (c) fix wrong labels (d) skip testing
33. 33.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) copy old unfair choices (d) check who is missing
34. 34.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
35. 35.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) ignore complaints (d) test on many groups
36. 36.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
37. 37.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
38. 38.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
39. 39.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
40. 40.Which of these adds to bias? (a) ignore complaints (b) add varied examples (c) balance the data (d) ask different people

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students