AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 587 · 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: “use one group only” helps reduce bias. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) test on many groups (b) ask different people (c) use one group only (d) add varied examples
3. 3.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) add varied examples
4. 4.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) add varied examples (d) fix wrong labels
5. 5.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
6. 6.True or false: “balance the data” adds to bias. (a) False (b) True
7. 7.True or false: “add varied examples” adds to bias. (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) test on many groups (d) skip testing
9. 9.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
11. 11.Which of these helps reduce bias? (a) add more of the same (b) test on many groups (c) ignore complaints (d) skip testing
12. 12.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
13. 13.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
14. 14.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
15. 15.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
16. 16.True or false: “check who is missing” adds to bias. (a) True (b) False
17. 17.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) ignoring mistakes (d) one group only
18. 18.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
19. 19.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
20. 20.Which of these adds to bias? (a) test on one group only (b) check who is missing (c) ask different people (d) add varied examples
21. 21.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
22. 22.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) balance the data (d) ignore complaints
26. 26.True or false: “test on one group only” helps reduce bias. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) ask different people (d) ignore complaints
28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
29. 29.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
30. 30.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
31. 31.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
32. 32.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) add more of the same (b) ask different people (c) test on many groups (d) check who is missing
34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
35. 35.True or false: “ask different people” helps reduce bias. (a) True (b) False
36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
37. 37.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) balance the data (d) use one group only
38. 38.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) add more of the same (d) check who is missing
39. 39.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
40. 40.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) skip testing (d) test on many groups

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