AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 925 · 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 is the odd one out? (a) add varied examples (b) check who is missing (c) skip testing (d) test on many groups
2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
3. 3.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
4. 4.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
5. 5.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
6. 6.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
7. 7.Which of these helps reduce bias? (a) add varied examples (b) use one group only (c) test on one group only (d) ignore complaints
8. 8.True or false: “check who is missing” helps reduce bias. (a) True (b) False
9. 9.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
10. 10.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
11. 11.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
12. 12.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
13. 13.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
14. 14.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) check who is missing (d) use one group only
15. 15.Which of these helps reduce bias? (a) ask different people (b) skip testing (c) ignore complaints (d) test on one group only
16. 16.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
17. 17.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) use one group only (d) skip testing
18. 18.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) add more of the same (d) test on one group only
20. 20.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
21. 21.True or false: “add varied examples” helps reduce bias. (a) False (b) True
22. 22.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
23. 23.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) balance the data (d) skip testing
24. 24.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
26. 26.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
27. 27.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
28. 28.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) ignore complaints (d) skip testing
29. 29.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) fix wrong labels
31. 31.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
33. 33.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
34. 34.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
35. 35.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
36. 36.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
37. 37.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ask different people (d) ignore complaints
38. 38.True or false: “skip testing” adds to bias. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) add varied examples (d) use one group only
40. 40.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias

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