AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 704 · 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: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) add more of the same (d) check who is missing
3. 3.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) check who is missing (d) add varied examples
5. 5.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) ignore complaints (d) fix wrong labels
6. 6.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) use one group only (d) copy old unfair choices
7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) add varied examples (d) skip testing
8. 8.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) add more of the same (d) fix wrong labels
9. 9.Which of these adds to bias? (a) balance the data (b) ask different people (c) test on many groups (d) skip testing
10. 10.Which of these adds to bias? (a) test on many groups (b) balance the data (c) test on one group only (d) ask different people
11. 11.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
12. 12.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) fix wrong labels (d) use one group only
13. 13.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) use one group only
14. 14.True or false: “ignore complaints” adds to bias. (a) False (b) True
15. 15.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
16. 16.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
17. 17.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.Which of these adds to bias? (a) add varied examples (b) ask different people (c) fix wrong labels (d) add more of the same
19. 19.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
21. 21.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
23. 23.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
24. 24.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
25. 25.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
26. 26.Which of these adds to bias? (a) balance the data (b) test on many groups (c) ask different people (d) ignore complaints
27. 27.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) ignore complaints (d) ask different people
28. 28.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
29. 29.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
30. 30.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) use one group only (d) copy old unfair choices
31. 31.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
32. 32.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) test on one group only (d) add varied examples
33. 33.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
34. 34.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
35. 35.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
36. 36.True or false: “test on many groups” helps reduce bias. (a) False (b) True
37. 37.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
38. 38.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) one group only (d) ignoring mistakes
39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
40. 40.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data

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