AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 368 · 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.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
2. 2.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
3. 3.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
4. 4.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
5. 5.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
6. 6.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
7. 7.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) test on one group only (d) test on many groups
8. 8.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) test on one group only (d) test on many groups
9. 9.Which of these adds to bias? (a) fix wrong labels (b) copy old unfair choices (c) add varied examples (d) balance the data
10. 10.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) ignore complaints (d) ask different people
11. 11.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
12. 12.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
13. 13.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
14. 14.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
16. 16.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
17. 17.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) balance the data (d) add more of the same
19. 19.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) test on one group only
20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
21. 21.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
22. 22.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) its training data (d) the weather
23. 23.True or false: “add varied examples” helps reduce bias. (a) True (b) False
24. 24.Which of these helps reduce bias? (a) copy old unfair choices (b) check who is missing (c) use one group only (d) add more of the same
25. 25.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
26. 26.Which of these adds to bias? (a) balance the data (b) add varied examples (c) ignore complaints (d) fix wrong labels
27. 27.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
28. 28.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
29. 29.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
30. 30.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) add varied examples (d) add more of the same
32. 32.True or false: “check who is missing” adds to bias. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) fix wrong labels (d) use one group only
34. 34.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) add more of the same (d) balance the data
35. 35.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
37. 37.Which of these adds to bias? (a) add more of the same (b) fix wrong labels (c) add varied examples (d) test on many groups
38. 38.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
39. 39.True or false: “add varied examples” adds to bias. (a) False (b) True
40. 40.True or false: “use one group only” helps reduce bias. (a) False (b) True

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