AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 796 · 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: “test on many groups” adds to bias. (a) True (b) False
2. 2.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
3. 3.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
4. 4.🗣️ 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) children speak too fast (d) the phone was new
5. 5.Which of these adds to bias? (a) balance the data (b) ask different people (c) skip testing (d) check who is missing
6. 6.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
7. 7.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) use one group only (d) check who is missing
9. 9.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) ignoring mistakes (d) fewer tests
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
11. 11.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
12. 12.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) add varied examples (d) fix wrong labels
13. 13.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
14. 14.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
15. 15.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
17. 17.True or false: “skip testing” helps reduce bias. (a) False (b) True
18. 18.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) copy old unfair choices (d) add varied examples
19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.Which of these adds to bias? (a) ignore complaints (b) ask different people (c) add varied examples (d) balance the data
21. 21.True or false: “ask different people” adds to bias. (a) True (b) False
22. 22.Which of these helps reduce bias? (a) test on many groups (b) add more of the same (c) use one group only (d) copy old unfair choices
23. 23.True or false: “use one group only” helps reduce bias. (a) False (b) True
24. 24.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) use one group only (d) ignore complaints
25. 25.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
26. 26.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
27. 27.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) fix wrong labels (d) skip testing
28. 28.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
29. 29.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) add varied examples (d) copy old unfair choices
30. 30.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) fix wrong labels (d) check who is missing
31. 31.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
32. 32.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) add varied examples (d) ask different people
33. 33.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
34. 34.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
35. 35.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
36. 36.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
37. 37.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
38. 38.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
39. 39.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False

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