AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 375 · 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: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
2. 2.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) test on one group only (d) use one group only
4. 4.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
5. 5.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
6. 6.True or false: “add more of the same” helps reduce bias. (a) True (b) False
7. 7.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
8. 8.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
9. 9.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) test on one group only (d) copy old unfair choices
10. 10.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) copy old unfair choices (d) add more of the same
11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
12. 12.Which of these adds to bias? (a) add varied examples (b) ask different people (c) ignore complaints (d) check who is missing
13. 13.True or false: “fix wrong labels” adds to bias. (a) False (b) True
14. 14.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
17. 17.True or false: “balance the data” adds to bias. (a) True (b) False
18. 18.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) balance the data (d) fix wrong labels
19. 19.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
20. 20.True or false: “test on one group only” helps reduce bias. (a) False (b) True
21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
22. 22.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) use one group only (d) skip testing
23. 23.True or false: “check who is missing” helps reduce bias. (a) False (b) True
24. 24.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
25. 25.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
26. 26.Which of these adds to bias? (a) check who is missing (b) use one group only (c) fix wrong labels (d) balance the data
27. 27.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
28. 28.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) test on one group only (d) test on many groups
29. 29.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
30. 30.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) add varied examples (d) balance the data
31. 31.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.Which of these helps reduce bias? (a) add varied examples (b) use one group only (c) add more of the same (d) ignore complaints
33. 33.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
34. 34.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
35. 35.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) copy old unfair choices (d) add more of the same
36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
37. 37.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
38. 38.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
39. 39.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) skip testing (d) ask different people
40. 40.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data

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