AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 736 · 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 adds to bias? (a) check who is missing (b) balance the data (c) use one group only (d) ask different people
2. 2.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
3. 3.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
4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) use one group only (d) skip testing
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
6. 6.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) add more of the same (d) use one group only
7. 7.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
8. 8.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
9. 9.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
10. 10.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) add varied examples (d) balance the data
11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) a fair model (d) bias from data
12. 12.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) ask different people (d) ignore complaints
13. 13.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
14. 14.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) check who is missing (d) ignore complaints
15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
16. 16.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
18. 18.True or false: “check who is missing” adds to bias. (a) False (b) True
19. 19.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
20. 20.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) skip testing (d) add more of the same
21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
22. 22.Which of these adds to bias? (a) test on many groups (b) balance the data (c) add varied examples (d) copy old unfair choices
23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) add more of the same (d) balance the data
24. 24.True or false: “add varied examples” helps reduce bias. (a) False (b) True
25. 25.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
26. 26.Which of these helps reduce bias? (a) fix wrong labels (b) skip testing (c) copy old unfair choices (d) ignore complaints
27. 27.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
28. 28.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
29. 29.Which of these adds to bias? (a) ask different people (b) skip testing (c) fix wrong labels (d) add varied examples
30. 30.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) add more of the same (d) check who is missing
32. 32.True or false: “test on many groups” helps reduce bias. (a) True (b) False
33. 33.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) use one group only (d) test on many groups
34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
35. 35.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
36. 36.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) test on one group only (d) balance the data
38. 38.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
39. 39.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
40. 40.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data

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