AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 477 · 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: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.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
3. 3.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
4. 4.True or false: “check who is missing” adds to bias. (a) True (b) False
5. 5.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
6. 6.🗣️ 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) it was a rainy day (d) children speak too fast
7. 7.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
8. 8.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
10. 10.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
11. 11.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
12. 12.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) use one group only (d) test on one group only
13. 13.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) check who is missing (d) use one group only
14. 14.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) test on many groups (d) copy old unfair choices
15. 15.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) copy old unfair choices (d) add varied examples
16. 16.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) fix wrong labels (d) check who is missing
17. 17.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) skip testing (d) check who is missing
18. 18.Which of these adds to bias? (a) skip testing (b) fix wrong labels (c) check who is missing (d) add varied examples
19. 19.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
20. 20.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
22. 22.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
23. 23.True or false: “test on many groups” adds to bias. (a) True (b) False
24. 24.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a strong battery (d) a fair model
25. 25.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
26. 26.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
27. 27.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) ignore complaints (d) add varied examples
28. 28.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
29. 29.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) skip testing (d) copy old unfair choices
30. 30.True or false: “use one group only” adds to bias. (a) False (b) True
31. 31.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
32. 32.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
33. 33.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
34. 34.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) ignore complaints (d) use one group only
35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) ignore complaints (d) test on one group only
36. 36.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
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.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
39. 39.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
40. 40.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add varied examples (d) use one group only

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