AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 150 · 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: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
2. 2.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
3. 3.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) use one group only (d) copy old unfair choices
4. 4.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
5. 5.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) add more of the same (d) skip testing
6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
7. 7.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) test on one group only (d) test on many groups
8. 8.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) use one group only (d) check who is missing
9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
10. 10.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
11. 11.True or false: “check who is missing” adds to bias. (a) False (b) True
12. 12.True or false: “test on one group only” helps reduce bias. (a) False (b) True
13. 13.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) test on many groups (d) balance the data
14. 14.True or false: “check who is missing” helps reduce bias. (a) False (b) True
15. 15.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
16. 16.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
17. 17.True or false: “add varied examples” helps reduce bias. (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) balance the data (d) ask different people
19. 19.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
22. 22.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
23. 23.Which of these adds to bias? (a) balance the data (b) add varied examples (c) test on many groups (d) skip testing
24. 24.True or false: “skip testing” helps reduce bias. (a) False (b) True
25. 25.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
27. 27.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) ignore complaints (d) add varied examples
28. 28.🖼️ 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
29. 29.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
30. 30.Which of these helps reduce bias? (a) ignore complaints (b) balance the data (c) copy old unfair choices (d) skip testing
31. 31.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) skip testing (d) balance the data
32. 32.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
34. 34.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
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: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
38. 38.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
39. 39.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.True or false: “skip testing” adds to bias. (a) False (b) True

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