AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 791 · 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) skip testing (b) test on many groups (c) add more of the same (d) copy old unfair choices
2. 2.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) fix wrong labels (d) test on one group only
3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
5. 5.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) add more of the same (d) check who is missing
6. 6.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
7. 7.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
8. 8.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) test on one group only
9. 9.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
11. 11.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.True or false: “add more of the same” adds to bias. (a) True (b) False
13. 13.True or false: “skip testing” helps reduce bias. (a) False (b) True
14. 14.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
15. 15.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
17. 17.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
18. 18.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) ask different people (d) test on many groups
19. 19.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
20. 20.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
21. 21.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
22. 22.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.Which of these adds to bias? (a) ask different people (b) ignore complaints (c) check who is missing (d) fix wrong labels
24. 24.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
25. 25.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
26. 26.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
27. 27.True or false: “add varied examples” adds to bias. (a) False (b) True
28. 28.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
29. 29.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) copy old unfair choices (d) skip testing
30. 30.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
32. 32.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) test on many groups (d) fix wrong labels
33. 33.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
34. 34.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
35. 35.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
36. 36.True or false: “test on one group only” helps reduce bias. (a) False (b) True
37. 37.🗣️ 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
38. 38.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
39. 39.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
40. 40.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) add varied examples (d) use one group only

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