AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 155 · 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.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
3. 3.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
6. 6.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
7. 7.Which of these helps reduce bias? (a) ask different people (b) copy old unfair choices (c) ignore complaints (d) test on one group only
8. 8.True or false: “ask different people” adds to bias. (a) False (b) True
9. 9.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
10. 10.Which of these adds to bias? (a) ask different people (b) add varied examples (c) use one group only (d) fix wrong labels
11. 11.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
12. 12.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
13. 13.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) test on many groups (d) ask different people
14. 14.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
16. 16.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
17. 17.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
18. 18.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) balance the data (d) skip testing
20. 20.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
21. 21.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
22. 22.Which of these helps reduce bias? (a) skip testing (b) balance the data (c) test on one group only (d) add more of the same
23. 23.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) add more of the same (d) fix wrong labels
24. 24.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) test on one group only (d) use one group only
25. 25.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
26. 26.True or false: “test on one group only” adds to bias. (a) False (b) True
27. 27.True or false: “test on many groups” adds to bias. (a) True (b) False
28. 28.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
29. 29.🖼️ 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
30. 30.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) test on many groups (d) ignore complaints
31. 31.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) ask different people (d) fix wrong labels
32. 32.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) balance the data (d) skip testing
34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
35. 35.True or false: “add more of the same” helps reduce bias. (a) True (b) False
36. 36.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
37. 37.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
38. 38.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
39. 39.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) test on many groups (d) add more of the same
40. 40.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) ignore complaints (d) test on many groups

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