AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 707 · 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: test on one group only? (a) adds to bias (b) reduces bias
2. 2.🗣️ 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
3. 3.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) fix wrong labels (d) add varied examples
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.Which of these adds to bias? (a) ask different people (b) add more of the same (c) fix wrong labels (d) add varied examples
7. 7.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) add more of the same (d) test on many groups
8. 8.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
9. 9.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
10. 10.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ignore complaints (d) check who is missing
11. 11.True or false: “balance the data” adds to bias. (a) False (b) True
12. 12.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
13. 13.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
14. 14.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) skip testing (d) test on one group only
16. 16.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
17. 17.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
18. 18.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) test on one group only
19. 19.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
20. 20.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
21. 21.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) copy old unfair choices (d) test on one group only
22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add varied examples (d) ignore complaints
24. 24.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
25. 25.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
26. 26.True or false: “ignore complaints” adds to bias. (a) True (b) False
27. 27.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
28. 28.True or false: “check who is missing” adds to bias. (a) False (b) True
29. 29.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
30. 30.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
31. 31.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) use one group only (d) fix wrong labels
32. 32.True or false: “test on many groups” adds to bias. (a) True (b) False
33. 33.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) copy old unfair choices (d) add more of the same
35. 35.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
36. 36.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
37. 37.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
38. 38.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) test on one group only (d) ignore complaints
39. 39.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) test on one group only (d) ignore complaints
40. 40.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data

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