AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 522 · 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.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) check who is missing (d) add more of the same
3. 3.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) fix wrong labels (d) ask different people
4. 4.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
7. 7.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
8. 8.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) fix wrong labels (d) copy old unfair choices
9. 9.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
10. 10.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) ask different people (d) add varied examples
11. 11.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) the weather (d) its training data
12. 12.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) use one group only (d) ignore complaints
14. 14.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
15. 15.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
16. 16.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
17. 17.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
18. 18.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
19. 19.Which of these adds to bias? (a) ask different people (b) test on many groups (c) skip testing (d) check who is missing
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
21. 21.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) ignore complaints (d) use one group only
23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
24. 24.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
25. 25.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) skip testing (d) copy old unfair choices
26. 26.True or false: “ask different people” adds to bias. (a) False (b) True
27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
28. 28.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) check who is missing (d) balance the data
29. 29.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
30. 30.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
31. 31.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
32. 32.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
33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) use one group only (d) balance the data
34. 34.Which of these helps reduce bias? (a) copy old unfair choices (b) test on many groups (c) test on one group only (d) skip testing
35. 35.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
36. 36.True or false: “test on many groups” adds to bias. (a) True (b) False
37. 37.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
38. 38.True or false: “ask different people” helps reduce bias. (a) True (b) False
39. 39.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

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