AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 334 · 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.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
2. 2.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
3. 3.🔍 Which is the odd one out? (a) add varied examples (b) balance the data (c) skip testing (d) fix wrong labels
4. 4.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
5. 5.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
6. 6.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) ignore complaints (d) fix wrong labels
7. 7.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) use one group only (d) add more of the same
8. 8.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) add more of the same (d) check who is missing
9. 9.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
10. 10.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
11. 11.True or false: “add varied examples” helps reduce bias. (a) False (b) True
12. 12.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) check who is missing (d) test on many groups
14. 14.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
15. 15.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) copy old unfair choices (d) add varied examples
16. 16.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) test on one group only (d) skip testing
18. 18.Which of these adds to bias? (a) ask different people (b) balance the data (c) skip testing (d) test on many groups
19. 19.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) add more of the same (d) check who is missing
20. 20.True or false: “skip testing” adds to bias. (a) False (b) True
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
22. 22.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
23. 23.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
24. 24.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) use one group only (d) test on many groups
25. 25.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) test on many groups (d) ask different people
26. 26.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
27. 27.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
28. 28.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
30. 30.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
31. 31.Which of these adds to bias? (a) ask different people (b) balance the data (c) add varied examples (d) copy old unfair choices
32. 32.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
33. 33.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
34. 34.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) ask different people (d) copy old unfair choices
35. 35.True or false: “test on one group only” helps reduce bias. (a) True (b) False
36. 36.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
37. 37.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
38. 38.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
39. 39.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
40. 40.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) use one group only (d) ask different people

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