AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 494 · 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.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
2. 2.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
3. 3.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) check who is missing (d) skip testing
4. 4.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
7. 7.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
8. 8.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) skip testing (d) add more of the same
9. 9.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
10. 10.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
11. 11.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) skip testing (d) balance the data
14. 14.True or false: “use one group only” helps reduce bias. (a) False (b) True
15. 15.Which of these adds to bias? (a) test on many groups (b) use one group only (c) fix wrong labels (d) add varied examples
16. 16.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
17. 17.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
18. 18.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ask different people (d) skip testing
19. 19.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) balance the data
20. 20.True or false: “ask different people” adds to bias. (a) True (b) False
21. 21.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
22. 22.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
23. 23.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) copy old unfair choices (d) test on many groups
24. 24.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
25. 25.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) ask different people (d) fix wrong labels
26. 26.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
28. 28.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) add more of the same (d) balance the data
29. 29.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) ask different people (d) ignore complaints
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
31. 31.🗣️ 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) it was a rainy day (d) children speak too fast
32. 32.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
33. 33.True or false: “test on one group only” helps reduce bias. (a) False (b) True
34. 34.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
35. 35.True or false: “add varied examples” adds to bias. (a) False (b) True
36. 36.True or false: “test on many groups” helps reduce bias. (a) False (b) True
37. 37.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
38. 38.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
39. 39.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
40. 40.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias

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