AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 120 · 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.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) ignore complaints (d) test on many groups
2. 2.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ask different people (d) skip testing
3. 3.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
4. 4.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
5. 5.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a broken screen (d) a strong battery
6. 6.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) ask different people (d) add more of the same
7. 7.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
8. 8.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
9. 9.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
10. 10.🗣️ 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
11. 11.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
12. 12.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
13. 13.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
14. 14.True or false: “test on many groups” adds to bias. (a) True (b) False
15. 15.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
16. 16.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
17. 17.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
20. 20.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
21. 21.True or false: “add varied examples” helps reduce bias. (a) False (b) True
22. 22.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
23. 23.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
24. 24.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) test on one group only
25. 25.Which of these helps reduce bias? (a) balance the data (b) copy old unfair choices (c) test on one group only (d) ignore complaints
26. 26.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) use one group only (d) add varied examples
27. 27.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) fix wrong labels (d) skip testing
28. 28.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) check who is missing (d) fix wrong labels
29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
30. 30.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
31. 31.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
32. 32.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
33. 33.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.Which of these adds to bias? (a) balance the data (b) add varied examples (c) fix wrong labels (d) skip testing
35. 35.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) copy old unfair choices (d) add varied examples
37. 37.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
38. 38.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) copy old unfair choices (d) use one group only
40. 40.True or false: “skip testing” helps reduce bias. (a) False (b) True

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