AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 940 · 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) ignore complaints (d) test on one group only
2. 2.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
3. 3.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) test on one group only (d) fix wrong labels
4. 4.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) use one group only (d) ask different people
7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
8. 8.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) test on one group only (d) add more of the same
9. 9.🗣️ 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) children speak too fast (d) the phone was new
10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
11. 11.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) fix wrong labels (d) skip testing
12. 12.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) ignore complaints (d) ask different people
13. 13.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
14. 14.True or false: “fix wrong labels” adds to bias. (a) True (b) False
15. 15.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
16. 16.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
17. 17.True or false: “add more of the same” adds to bias. (a) False (b) True
18. 18.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
19. 19.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) copy old unfair choices (d) balance the data
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) test on one group only (d) skip testing
22. 22.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
23. 23.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) ask different people (d) add varied examples
24. 24.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
25. 25.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) test on one group only (d) fix wrong labels
26. 26.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
27. 27.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) add varied examples (d) copy old unfair choices
28. 28.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
30. 30.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) ignore complaints (d) balance the data
31. 31.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) add varied examples (d) ignore complaints
32. 32.True or false: “test on one group only” adds to bias. (a) True (b) False
33. 33.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
34. 34.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) ask different people (d) skip testing
35. 35.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
36. 36.True or false: “check who is missing” helps reduce bias. (a) False (b) True
37. 37.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
38. 38.True or false: “test on many groups” helps reduce bias. (a) False (b) True
39. 39.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
40. 40.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias

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