AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 933 · 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: “add more of the same” helps reduce bias. (a) True (b) False
2. 2.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
5. 5.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
6. 6.Which of these adds to bias? (a) balance the data (b) skip testing (c) fix wrong labels (d) add varied examples
7. 7.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
8. 8.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) ask different people (d) test on many groups
10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
11. 11.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
12. 12.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) balance the data
13. 13.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
15. 15.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) skip testing (d) test on many groups
16. 16.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) add more of the same (d) ask different people
18. 18.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
19. 19.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) check who is missing (d) skip testing
20. 20.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
21. 21.True or false: “use one group only” adds to bias. (a) True (b) False
22. 22.True or false: “skip testing” adds to bias. (a) True (b) False
23. 23.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
24. 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
25. 25.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) ignore complaints (d) balance the data
26. 26.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
27. 27.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
28. 28.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
29. 29.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
30. 30.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
33. 33.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
34. 34.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
35. 35.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
36. 36.True or false: “check who is missing” helps reduce bias. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) use one group only (d) balance the data
38. 38.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
39. 39.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
40. 40.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) skip testing (d) use one group only

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